Publications

2022
Hyun, S. ; Mishra, A. ; Follett, C.L. ; Jönsson, B. ; Kulk, G. ; Forget, G. ; Racault, M.F. ; Jackson, T. ; Dutkiewicz, S. ; Müller, C. ; Bien, J.
Proc. R. Soc. London A 478:20210875 (2022)
Remote sensing observations from satellites and global biogeochemical models have combined to revolutionize the study of ocean biogeochemical cycling, but comparing the two data streams to each other and across time remains challenging due to the strong spatial-temporal structuring of the ocean. Here, we show that the Wasserstein distance provides a powerful metric for harnessing these structured datasets for better marine ecosystem and climate predictions. The Wasserstein distance complements commonly used point-wise difference methods such as the root-mean-squared error, by quantifying differences in terms of spatial displacement in addition to magnitude. As a test case, we consider chlorophyll (a key indicator of phytoplankton biomass) in the northeast Pacific Ocean, obtained from model simulations, in situ measurements, and satellite observations. We focus on two main applications: (i) comparing model predictions with satellite observations, and (ii) temporal evolution of chlorophyll both seasonally and over longer time frames. The Wasserstein distance successfully isolates temporal and depth variability and quantifies shifts in biogeochemical province boundaries. It also exposes relevant temporal trends in satellite chlorophyll consistent with climate change predictions. Our study shows that optimal transport vectors underlying the Wasserstein distance provide a novel visualization tool for testing models and better understanding temporal dynamics in the ocean.
Wissenschaftlicher Artikel
Scientific Article
Herrera-Luis, E. ; Ortega, V.E. ; Ampleford, E.J. ; Sio, Y.Y. ; Granell, R. ; de Roos, E. ; Terzikhan, N. ; Vergara, E.E. ; Hernandez-Pacheco, N. ; Perez-Garcia, J. ; Martin-Gonzalez, E. ; Lorenzo-Diaz, F. ; Hashimoto, S. ; Brinkman, P. ; Jorgensen, A.L. ; Yan, Q. ; Forno, E. ; Vijverberg, S.J. ; Lethem, R. ; Espuela-Ortiz, A. ; Gorenjak, M. ; Eng, C. ; González-Pérez, R. ; Hernández-Pérez, J.M. ; Poza-Guedes, P. ; Sardón, O. ; Corcuera, P. ; Hawkins, G.A. ; Marsico, A. ; Bahmer, T. ; Rabe, K.F. ; Hansen, G. ; Kopp, M.V. ; Rios, R. ; Cruz, M.J. ; González-Barcala, F.J. ; Olaguibel, J.M. ; Plaza, V. ; Quirce, S. ; Canino, G. ; Cloutier, M.M. ; Del Pozo, V. ; Rodriguez-Santana, J.R. ; Korta-Murua, J. ; Villar, J. ; Potocnik, U. ; Figueiredo, C. ; Kabesch, M. ; Mukhopadhyay, S. ; Pirmohamed, M. ; Hawcutt, D.B. ; Melén, E. ; Palmer, C.N. ; Turner, S. ; Maitland-van der Zee, A.H. ; von Mutius, E. ; Celedón, J.C. ; Brusselle, G. ; Chew, F.T. ; Bleecker, E.R. ; Meyers, D. ; Burchard, E.G. ; Pino-Yanes, M.
Pediatr. Allergy Immunol. 33:e13802 (2022)
BACKGROUND: Asthma exacerbations are a serious public health concern due to high healthcare resource utilization, work/school productivity loss, impact on quality of life, and risk of mortality. The genetic basis of asthma exacerbations has been studied in several populations, but no prior study has performed a multi-ancestry meta-analysis of genome-wide association studies (meta-GWAS) for this trait. We aimed to identify common genetic loci associated with asthma exacerbations across diverse populations and to assess their functional role in regulating DNA methylation and gene expression. METHODS: A meta-GWAS of asthma exacerbations in 4989 Europeans, 2181 Hispanics/Latinos, 1250 Singaporean Chinese, and 972 African Americans analyzed 9.6 million genetic variants. Suggestively associated variants (p ≤ 5 × 10-5 ) were assessed for replication in 36,477 European and 1078 non-European asthma patients. Functional effects on DNA methylation were assessed in 595 Hispanic/Latino and African American asthma patients and in publicly available databases. The effect on gene expression was evaluated in silico. RESULTS: One hundred and twenty-six independent variants were suggestively associated with asthma exacerbations in the discovery phase. Two variants independently replicated: rs12091010 located at vascular cell adhesion molecule-1/exostosin like glycosyltransferase-2 (VCAM1/EXTL2) (discovery: odds ratio (ORT allele ) = 0.82, p = 9.05 × 10-6 and replication: ORT allele  = 0.89, p = 5.35 × 10-3 ) and rs943126 from pantothenate kinase 1 (PANK1) (discovery: ORC allele  = 0.85, p = 3.10 × 10-5 and replication: ORC allele  = 0.89, p = 1.30 × 10-2 ). Both variants regulate gene expression of genes where they locate and DNA methylation levels of nearby genes in whole blood. CONCLUSIONS: This multi-ancestry study revealed novel suggestive regulatory loci for asthma exacerbations located in genomic regions participating in inflammation and host defense.
Wissenschaftlicher Artikel
Scientific Article
Thareja, G. ; Evans, A.M. ; Wood, S.D. ; Stephan, N. ; Zaghlool, S. ; Halama, A. ; Kastenmüller, G. ; Belkadi, A. ; Albagha, O.M.E. ; Suhre, K.
Metabolites 12:496 (2022)
Genome-wide association studies (GWAS) with non-targeted metabolomics have identified many genetic loci of biomedical interest. However, metabolites with a high degree of missingness, such as drug metabolites and xenobiotics, are often excluded from such studies due to a lack of statistical power and higher uncertainty in their quantification. Here we propose ratios between related drug metabolites as GWAS phenotypes that can drastically increase power to detect genetic associations between pairs of biochemically related molecules. As a proof-of-concept we conducted a GWAS with 520 individuals from the Qatar Biobank for who at least five of the nine available acetaminophen metabolites have been detected. We identified compelling evidence for genetic variance in acetaminophen glucuronidation and methylation by UGT2A15 and COMT, respectively. Based on the metabolite ratio association profiles of these two loci we hypothesized the chemical structure of one of their products or substrates as being 3-methoxyacetaminophen, which we then confirmed experimentally. Taken together, our study suggests a novel approach to analyze metabolites with a high degree of missingness in a GWAS setting with ratios, and it also demonstrates how pharmacological pathways can be mapped out using non-targeted metabolomics measurements in large population-based studies.
Wissenschaftlicher Artikel
Scientific Article
Frishberg, A. ; Kooistra, E. ; Nuesch-Germano, M. ; Pecht, T. ; Milman, N. ; Reusch, N. ; Warnat-Herresthal, S. ; Bruse, N. ; Händler, K. ; Theis, H. ; Kraut, M. ; van Rijssen, E. ; van Cranenbroek, B. ; Koenen, H.J. ; Heesakkers, H. ; van den Boogaard, M.J. ; Zegers, M. ; Pickkers, P. ; Becker, M. ; Aschenbrenner, A.C. ; Ulas, T. ; Theis, F.J. ; Shen-Orr, S.S. ; Schultze, J.L. ; Kox, M.
Cell Rep. Med. 3:100652 (2022)
Disease recovery dynamics are often difficult to assess, as patients display heterogeneous recovery courses. To model recovery dynamics, exemplified by severe COVID-19, we apply a computational scheme on longitudinally sampled blood transcriptomes, generating recovery states, which we then link to cellular and molecular mechanisms, presenting a framework for studying the kinetics of recovery compared with non-recovery over time and long-term effects of the disease. Specifically, a decrease in mature neutrophils is the strongest cellular effect during recovery, with direct implications on disease outcome. Furthermore, we present strong indications for global regulatory changes in gene programs, decoupled from cell compositional changes, including an early rise in T cell activation and differentiation, resulting in immune rebalancing between interferon and NF-κB activity and restoration of cell homeostasis. Overall, we present a clinically relevant computational framework for modeling disease recovery, paving the way for future studies of the recovery dynamics in other diseases and tissues.
Wissenschaftlicher Artikel
Scientific Article
Kindt, A. ; Förster, K. ; Cochius-den Otter, S.C.M. ; Flemmer, A.W. ; Hauck, S.M. ; Flatley, A. ; Kamphuis, J. ; Karrasch, S. ; Behr, J. ; Franz, A. ; Härtel, C. ; Krumsiek, J. ; Tibboel, D. ; Hilgendorff, A.
Pediatr. Res., DOI: 10.1038/s41390-022-02093-w (2022)
OBJECTIVE: To demonstrate and validate the improvement of current risk stratification for bronchopulmonary dysplasia (BPD) early after birth by plasma protein markers (sialic acid-binding Ig-like lectin 14 (SIGLEC-14), basal cell adhesion molecule (BCAM), angiopoietin-like 3 protein (ANGPTL-3)) in extremely premature infants. METHODS AND RESULTS: Proteome screening in first-week-of-life plasma samples of n = 52 preterm infants <32 weeks gestational age (GA) on two proteomic platforms (SomaLogic®, Olink-Proteomics®) confirmed three biomarkers with significant predictive power: BCAM, SIGLEC-14, and ANGPTL-3. We demonstrate high sensitivity (0.92) and specificity (0.86) under consideration of GA, show the proteins' critical contribution to the predictive power of known clinical risk factors, e.g., birth weight and GA, and predicted the duration of mechanical ventilation, oxygen supplementation, as well as neonatal intensive care stay. We confirmed significant predictive power for BPD cases when switching to a clinically applicable method (enzyme-linked immunosorbent assay) in an independent sample set (n = 25, p < 0.001) and demonstrated disease specificity in different cohorts of neonatal and adult lung disease. CONCLUSION: While successfully addressing typical challenges of clinical biomarker studies, we demonstrated the potential of BCAM, SIGLEC-14, and ANGPTL-3 to inform future clinical decision making in the preterm infant at risk for BPD. TRIAL REGISTRATION: Deutsches Register Klinische Studien (DRKS) No. 00004600; https://www.drks.de . IMPACT: The urgent need for biomarkers that enable early decision making and personalized monitoring strategies in preterm infants with BPD is challenged by targeted marker analyses, cohort size, and disease heterogeneity. We demonstrate the potential of the plasma proteins BCAM, SIGLEC-14, and ANGPTL-3 to identify infants with BPD early after birth while improving the predictive power of clinical variables, confirming the robustness toward proteome assays and proving disease specificity. Our comprehensive analysis enables a phase-III clinical trial that allows full implementation of the biomarkers into clinical routine to enable early risk stratification in preterms with BPD.
Wissenschaftlicher Artikel
Scientific Article
Efendiyev, M.A. ; Ôtani, M. ; Eberl, H.J.
J. Differ. Equations 339, 602-636 (2022)
We study the existence and the longterm behavior of solutions of a parabolic equation governed by the p-Laplacian with nonlinear growth terms that are coupled with the solutions of a system of ordinary differential equations. The existence and the uniqueness are shown by using a fixed point argument and the longterm behavior of solutions is discussed by using energy estimates together with the nonlinear peculiarity of the p-Laplacian. Numerical simulations are carried out by using a Finite Volume Method for spatial treatment. For time integration of the p-Laplacian, an implicit Euler method is used, and direct integration for the ODE system.
Wissenschaftlicher Artikel
Scientific Article
Müller, J. ; Tellier, A.
Math. Biosci. 349:108826 (2022)
Due to the relevance for conservation biology, there is an increasing interest to extend evolutionary genomics models to plant, animal or microbial species. However, this requires to understand the effect of life-history traits absent in humans on genomic evolution. In this context, it is fundamentally of interest to generalize the replicator equation, which is at the heart of most population genomics models. However, as the inclusion of life-history traits generates models with a large state space, the analysis becomes involving. We focus, here, on quiescence and seed banks, two features common to many plant, invertebrate and microbial species. We develop a method to obtain a low-dimensional replicator equation in the context of evolutionary game theory, based on two assumptions: (1) the life-history traits are per se neutral, and (2) frequency-dependent selection is weak. We use the results to investigate the evolution and maintenance of cooperation based on the Prisoner's dilemma and the snowdrift game. We first consider the generalized replicator equation, and then refine the investigation using adaptive dynamics. It turns out that, depending on the structure and timing of the quiescence/dormancy life-history trait, cooperation in a homogeneous population can be stabilized. We finally discuss and highlight the relevance of these results for plant, invertebrate and microbial communities.
Wissenschaftlicher Artikel
Scientific Article
van der Does, A.M. ; Mahbub, R.M. ; Ninaber, D.K. ; Rathnayake, S.N.H. ; Timens, W. ; van den Berge, M. ; Aliee, H. ; Theis, F.J. ; Nawijn, M.C. ; Hiemstra, P.S. ; Faiz, A.
Respir. Res. 23:227 (2022)
BACKGROUND: Despite the well-known detrimental effects of cigarette smoke (CS), little is known about the complex gene expression dynamics in the early stages after exposure. This study aims to investigate early transcriptomic responses following CS exposure of airway epithelial cells in culture and compare these to those found in human CS exposure studies. METHODS: Primary bronchial epithelial cells (PBEC) were differentiated at the air-liquid interface (ALI) and exposed to whole CS. Bulk RNA-sequencing was performed at 1 h, 4 h, and 24 h hereafter, followed by differential gene expression analysis. Results were additionally compared to data retrieved from human CS studies. RESULTS: ALI-PBEC gene expression in response to CS was most significantly changed at 4 h after exposure. Early transcriptomic changes (1 h, 4 h post CS exposure) were related to oxidative stress, xenobiotic metabolism, higher expression of immediate early genes and pro-inflammatory pathways (i.e., Nrf2, AP-1, AhR). At 24 h, ferroptosis-associated genes were significantly increased, whereas PRKN, involved in removing dysfunctional mitochondria, was downregulated. Importantly, the transcriptome dynamics of the current study mirrored in-vivo human studies of acute CS exposure, chronic smokers, and inversely mirrored smoking cessation. CONCLUSION: These findings show that early after CS exposure xenobiotic metabolism and pro-inflammatory pathways were activated, followed by activation of the ferroptosis-related cell death pathway. Moreover, significant overlap between these transcriptomic responses in the in-vitro model and human in-vivo studies was found, with an early response of ciliated cells. These results provide validation for the use of ALI-PBEC cultures to study the human lung epithelial response to inhaled toxicants.
Wissenschaftlicher Artikel
Scientific Article
Schmidt, S. ; Luecken, M. ; Trümbach, D. ; Hembach, S. ; Niedermeier, K.M. ; Wenck, N. ; Pflügler, K. ; Stautner, C. ; Böttcher, A. ; Lickert, H. ; Ramirez Suastegui, C. ; Ahmad, R. ; Ziller, M.J. ; Fitzgerald, J.C. ; Ruf, V. ; van de Berg, W.D.J. ; Jonker, A.J. ; Gasser, T. ; Winner, B. ; Winkler, J. ; Weisenhorn, D.M. ; Giesert, F. ; Theis, F.J. ; Wurst, W.
Nat. Commun. 13:4819 (2022)
Parkinson's disease (PD) as a progressive neurodegenerative disorder arises from multiple genetic and environmental factors. However, underlying pathological mechanisms remain poorly understood. Using multiplexed single-cell transcriptomics, we analyze human neural precursor cells (hNPCs) from sporadic PD (sPD) patients. Alterations in gene expression appear in pathways related to primary cilia (PC). Accordingly, in these hiPSC-derived hNPCs and neurons, we observe a shortening of PC. Additionally, we detect a shortening of PC in PINK1-deficient human cellular and mouse models of familial PD. Furthermore, in sPD models, the shortening of PC is accompanied by increased Sonic Hedgehog (SHH) signal transduction. Inhibition of this pathway rescues the alterations in PC morphology and mitochondrial dysfunction. Thus, increased SHH activity due to ciliary dysfunction may be required for the development of pathoetiological phenotypes observed in sPD like mitochondrial dysfunction. Inhibiting overactive SHH signaling may be a potential neuroprotective therapy for sPD.
Wissenschaftlicher Artikel
Scientific Article
Spitzer, H. ; Ripart, M. ; Whitaker, K. ; D'Arco, F. ; Mankad, K. ; Chen, A.A. ; Napolitano, A. ; De Palma, L. ; De Benedictis, A. ; Foldes, S. ; Humphreys, Z. ; Zhang, K. ; Hu, W. ; Mo, J. ; Likeman, M. ; Davies, S. ; Guttler, C. ; Lenge, M. ; Cohen, N.T. ; Tang, Y. ; Wang, S. ; Chari, A. ; Tisdall, M. ; Bargallo, N. ; Conde-Blanco, E. ; Pariente, J.C. ; Pascual-Diaz, S. ; Delgado-Martinez, I. ; Perez-Enriquez, C. ; Lagorio, I. ; Abela, E. ; Mullatti, N. ; O'Muircheartaigh, J. ; Vecchiato, K. ; Liu, Y. ; Caligiuri, M.E. ; Sinclair, B. ; Vivash, L. ; Willard, A. ; Kandasamy, J. ; McLellan, A. ; Sokol, D. ; Semmelroch, M. ; Kloster, A.G. ; Opheim, G. ; Ribeiro, L. ; Yasuda, C. ; Rossi-Espagnet, C. ; Hamandi, K. ; Tietze, A. ; Barba, C. ; Guerrini, R. ; Gaillard, W.D. ; You, X. ; Wang, I. ; Gonzalez-Ortiz, S. ; Severino, M. ; Striano, P. ; Tortora, D. ; Kälviäinen, R. ; Gambardella, A. ; Labate, A. ; Desmond, P. ; Lui, E. ; O'Brien, T. ; Shetty, J. ; Jackson, G. ; Duncan, J.S. ; Winston, G.P. ; Pinborg, L.H. ; Cendes, F. ; Theis, F.J. ; Shinohara, R.T. ; Cross, J.H. ; Baldeweg, T. ; Adler, S. ; Wagstyl, K.
Brain, DOI: 10.1093/brain/awac224 (2022)
One outstanding challenge for machine learning in diagnostic biomedical imaging is algorithm interpretability. A key application is the identification of subtle epileptogenic focal cortical dysplasias (FCDs) from structural MRI. FCDs are difficult to visualize on structural MRI but are often amenable to surgical resection. We aimed to develop an open-source, interpretable, surface-based machine-learning algorithm to automatically identify FCDs on heterogeneous structural MRI data from epilepsy surgery centres worldwide. The Multi-centre Epilepsy Lesion Detection (MELD) Project collated and harmonized a retrospective MRI cohort of 1015 participants, 618 patients with focal FCD-related epilepsy and 397 controls, from 22 epilepsy centres worldwide. We created a neural network for FCD detection based on 33 surface-based features. The network was trained and cross-validated on 50% of the total cohort and tested on the remaining 50% as well as on 2 independent test sites. Multidimensional feature analysis and integrated gradient saliencies were used to interrogate network performance. Our pipeline outputs individual patient reports, which identify the location of predicted lesions, alongside their imaging features and relative saliency to the classifier. On a restricted 'gold-standard' subcohort of seizure-free patients with FCD type IIB who had T1 and fluid-attenuated inversion recovery MRI data, the MELD FCD surface-based algorithm had a sensitivity of 85%. Across the entire withheld test cohort the sensitivity was 59% and specificity was 54%. After including a border zone around lesions, to account for uncertainty around the borders of manually delineated lesion masks, the sensitivity was 67%. This multicentre, multinational study with open access protocols and code has developed a robust and interpretable machine-learning algorithm for automated detection of focal cortical dysplasias, giving physicians greater confidence in the identification of subtle MRI lesions in individuals with epilepsy.
Wissenschaftlicher Artikel
Scientific Article
Musundi, B. ; Müller, J. ; Feng, Z.
Mathematics 10:3114 (2022)
Cholera, caused by the pathogenic Vibrio cholerae bacteria, remains a severe public health threat. Although a lot of emphasis has been placed on the population-level spread of the disease, the infection itself starts within the body. As such, we formulated a multi-scale model that explicitly connects the within-host and between-host dynamics of the disease. To model the within-host dynamics, we assigned each susceptible individual with a pathogen load that increases through the uptake of contaminated food and water (booster event). We introduced minimal and maximal times when the booster events happen and defined a time since the last booster event. We then scaled the within-host dynamics to the population where we structured the susceptible population using the two variables (pathogen load and time since the last booster event). We analyzed the pathogen load’s invariant distribution and utilized the results and time scale assumptions to reduce the dimension of the multi-scale model. The resulting model is an SIR model whose incidence function has terms derived from the multi-scale model. We finally conducted numerical simulations to investigate the long-term behavior of the SIR model. The simulations revealed parameter regions where either no cholera cases happen, where cholera is present at a low prevalence, and where a full-blown cholera epidemic takes off.
Wissenschaftlicher Artikel
Scientific Article
Bohnacker, S. ; Hartung, F. ; Henkel, F. ; Quaranta, A. ; Kolmert, J. ; Priller, A. ; Ud-Dean, M. ; Giglberger, J. ; Kugler, L.M. ; Pechtold, L. ; Yazici, S. ; Lechner, A. ; Erber, J. ; Protzer, U. ; Lingor, P. ; Knolle, P. ; Chaker, A. ; Schmidt-Weber, C.B. ; Wheelock, C.E. ; Esser-von Bieren, J.
Mucosal Immunol. 15:798 (2022)
The original version of this article contained an error in the ESM. The supplemental file titled “Supplementary information 1” is a marked version of the correct file, “Supplementary information 2”. “Supplementary information 1” was therefore removed. The authors apologize for the error. The original article has been corrected.
Matos, G.M. ; Lewis, M.D. ; Talavera Lopez, C.N. ; Yeo, M. ; Grisard, E.C. ; Messenger, L.A. ; Miles, M.A. ; Andersson, B.
eLife 11:e75237 (2022)
Protozoa and fungi are known to have extraordinarily diverse mechanisms of genetic exchange. However, the presence and epidemiological relevance of genetic exchange in Trypanosoma cruzi, the agent of Chagas disease, has been controversial and debated for many years. Field studies have identified both predominantly clonal and sexually recombining natural populations. Two of six natural T. cruzi lineages (TcV and TcVI) show hybrid mosaicism, using analysis of single-gene locus markers. The formation of hybrid strains in vitro has been achieved and this provides a framework to study the mechanisms and adaptive significance of genetic exchange. Using whole genome sequencing of a set of experimental hybrids strains, we have confirmed that hybrid formation initially results in tetraploid parasites. The hybrid progeny showed novel mutations that were not attributable to either (diploid) parent showing an increase in amino acid changes. In long-term culture, up to 800 generations, there was a variable but gradual erosion of progeny genomes towards triploidy, yet retention of elevated copy number was observed at several core housekeeping loci. Our findings indicate hybrid formation by fusion of diploid T. cruzi, followed by sporadic genome erosion, but with substantial potential for adaptive evolution, as has been described as a genetic feature of other organisms, such as some fungi.
Wissenschaftlicher Artikel
Scientific Article
Schulte, E.C. ; Kondofersky, I. ; Budde, M. ; Papiol, S. ; Senner, F. ; Schaupp, S.K. ; Reich-Erkelenz, D. ; Klöhn-Saghatolislam, F. ; Kalman, J.L. ; Gade, K. ; Hake, M. ; Comes, A.L. ; Anderson-Schmidt, H. ; Adorjan, K. ; Juckel, G. ; Schmauß, M. ; Zimmermann, J. ; Reimer, J. ; Wiltfang, J. ; Reininghaus, E.Z. ; Anghelescu, I.G. ; Konrad, C. ; Figge, C. ; von Hagen, M. ; Jäger, M. ; Dietrich, D.E. ; Spitzer, C. ; Witt, S.H. ; Forstner, A.J. ; Rietschel, M. ; Nöthen, M.M. ; Falkai, P. ; Heilbronner, U. ; Müller, N.S. ; Schulze, T.G.
Schizophr. Res. 244, 29-38 (2022)
Biological research and clinical management in psychiatry face two major impediments: the high degree of overlap in psychopathology between diagnoses and the inherent heterogeneity with regard to severity. Here, we aim to stratify cases into homogeneous transdiagnostic subgroups using psychometric information with the ultimate aim of identifying individuals with higher risk for severe illness. 397 participants of the PsyCourse study with schizophrenia- or bipolar-spectrum diagnoses were prospectively phenotyped over 18 months. Factor analysis of mixed data of different rating scales and subsequent longitudinal clustering were used to cluster disease trajectories. Five clusters of longitudinal trajectories were identified in the psychopathologic dimensions. Clusters differed significantly with regard to Global Assessment of Functioning, disease course, and-in some cases-diagnosis while there were no significant differences regarding sex, age at baseline or onset, duration of illness, or polygenic burden for schizophrenia. Longitudinal clustering may aid in identifying transdiagnostic homogeneous subgroups of individuals with severe psychiatric disease.
Wissenschaftlicher Artikel
Scientific Article
Efendiyev, M.A. ; Vougalter, V.
J. Dyn. Differ. Equ., DOI: 10.1007/s10884-022-10199-2 (2022)
We prove the existence in the sense of sequences of solutions for some system of integro-differential type equations in two dimensions containing the normal diffusion in one direction and the anomalous diffusion in the other direction in H2(R2, RN) using the fixed point technique. The system of elliptic equations contains second order differential operators without the Fredholm property. It is established that, under the reasonable technical assumptions, the convergence in L1(R2) of the integral kernels yields the existence and convergence in H2(R2, RN) of the solutions. We emphasize that the study of the systems is more difficult than of the scalar case and requires to overcome more cumbersome technicalities.
Wissenschaftlicher Artikel
Scientific Article
Vonk, J. ; Kukacka, J. ; Steinkamp, P.J. ; de Wit, J.G. ; Voskuil, F.J. ; Hooghiemstra, W.T.R. ; Bader, M. ; Jüstel, D. ; Ntziachristos, V. ; van Dam, G.M. ; Witjes, M.J.H.
Photoacoustics 26:100362 (2022)
Oral cancer patients undergo diagnostic surgeries to detect occult lymph node metastases missed by preoperative structural imaging techniques. Reducing these invasive procedures that are associated with considerable morbidity, requires better preoperative detection. Multispectral optoacoustic tomography (MSOT) is a rapidly evolving imaging technique that may improve preoperative detection of (early-stage) lymph node metastases, enabling the identification of molecular changes that often precede structural changes in tumorigenesis. Here, we characterize the optoacoustic properties of cetuximab-800CW, a tumor-specific fluorescent tracer showing several photophysical properties that benefit optoacoustic signal generation. In this first clinical proof-of-concept study, we explore its use as optoacoustic to differentiate between malignant and benign lymph nodes. We characterize the appearance of malignant lymph nodes and show differences in the distribution of intrinsic chromophores compared to benign lymph nodes. In addition, we suggest several approaches to improve the efficiency of follow-up studies.
Wissenschaftlicher Artikel
Scientific Article
Mishra, A.K. ; Müller, C.
Stat. Med. 41, 2786-2803 (2022)
The human microbiome provides essential physiological functions and helps maintain host homeostasis via the formation of intricate ecological host-microbiome relationships. While it is well established that the lifestyle of the host, dietary preferences, demographic background, and health status can influence microbial community composition and dynamics, robust generalizable associations between specific host-associated factors and specific microbial taxa have remained largely elusive. Here, we propose factor regression models that allow the estimation of structured parsimonious associations between host-related features and amplicon-derived microbial taxa. To account for the overdispersed nature of the amplicon sequencing count data, we propose negative binomial reduced rank regression (NB-RRR) and negative binomial co-sparse factor regression (NB-FAR). While NB-RRR encodes the underlying dependency among the microbial abundances as outcomes and the host-associated features as predictors through a rank-constrained coefficient matrix, NB-FAR uses a sparse singular value decomposition of the coefficient matrix. The latter approach avoids the notoriously difficult joint parameter estimation by extracting sparse unit-rank components of the coefficient matrix sequentially, effectively delivering interpretable bi-clusters of taxa and host-associated factors. To solve the nonconvex optimization problems associated with these factor regression models, we present a novel iterative block-wise majorization procedure. Extensive simulation studies and an application to the microbial abundance data from the American Gut Project (AGP) demonstrate the efficacy of the proposed procedure. In the AGP data, we identify several factors that strongly link dietary habits and host life style to specific microbial families.
Wissenschaftlicher Artikel
Scientific Article
Efendiyev, M.A. ; Vougalter, V.
Anal. Math. Phys. 12:110 (2022)
We establish the existence in the sense of sequences of solutions for certain systems of integro-differential equations which involve the drift terms and the square root of the one dimensional negative Laplace operator, on the whole real line or on a finite interval with periodic boundary conditions in the corresponding H2 spaces. The argument is based on the fixed point technique when the elliptic systems contain first order differential operators with and without Fredholm property. It is proven that, under the reasonable technical conditions, the convergence in L1 of the integral kernels yields the existence and convergence in H2 of the solutions. We emphasize that the study of the systems is more complicated than of the scalar case and requires to overcome more cumbersome technicalities.
Wissenschaftlicher Artikel
Scientific Article
Bassler, K. ; Fujii, W. ; Kapellos, T.S. ; Dudkin, E. ; Reusch, N. ; Horne, A. ; Reiz, B. ; Luecken, M. ; Osei-Sarpong, C. ; Warnat-Herresthal, S. ; Bonaguro, L. ; Schulte-Schrepping, J. ; Wagner, A. ; Guenther, P. ; Pizarro, C. ; Schreiber, T. ; Knöll, R. ; Holsten, L. ; Kroeger, C. ; De Domenico, E. ; Becker, M. ; Haendler, K. ; Wohnhaas, C.T. ; Baumgartner, F. ; Koehler, M. ; Theis, H. ; Kraut, M. ; Wadsworth, M.H. ; Hughes, T.K. ; Ferreira, H.J. ; Hinkley, E. ; Kaltheuner, I.H. ; Geyer, M. ; Thiele, C. ; Shalek, A.K. ; Feisst, A. ; Thomas, D. ; Dickten, H. ; Beyer, M. ; Baum, P. ; Yosef, N. ; Aschenbrenner, A.C. ; Ulas, T. ; Hasenauer, J. ; Theis, F.J. ; Skowasch, D. ; Schultze, J.L.
Front. Immunol. 13:917232 (2022)
Despite its high prevalence, the cellular and molecular mechanisms of chronic obstructive pulmonary disease (COPD) are far from being understood. Here, we determine disease-related changes in cellular and molecular compositions within the alveolar space and peripheral blood of a cohort of COPD patients and controls. Myeloid cells were the largest cellular compartment in the alveolar space with invading monocytes and proliferating macrophages elevated in COPD. Modeling cell-to-cell communication, signaling pathway usage, and transcription factor binding predicts TGF-β1 to be a major upstream regulator of transcriptional changes in alveolar macrophages of COPD patients. Functionally, macrophages in COPD showed reduced antigen presentation capacity, accumulation of cholesteryl ester, reduced cellular chemotaxis, and mitochondrial dysfunction, reminiscent of impaired immune activation.
Wissenschaftlicher Artikel
Scientific Article
Lederer, J. ; Müller, C.
Mathematics 10:1244 (2022)
We introduce Graphical TREX (GTREX), a novel method for graph estimation in highdimensional Gaussian graphical models. By conducting neighborhood selection with TREX, GTREX avoids tuning parameters and is adaptive to the graph topology. We compared GTREX with standard methods on a new simulation setup that was designed to assess accurately the strengths and shortcomings of different methods. These simulations showed that a neighborhood selection scheme based on Lasso and an optimal (in practice unknown) tuning parameter outperformed other standard methods over a large spectrum of scenarios. Moreover, we show that GTREX can rival this scheme and, therefore, can provide competitive graph estimation without the need for tuning parameter calibration.
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Scientific Article
Bakhti, M. ; Bastidas-Ponce, A. ; Tritschler, S. ; Czarnecki, O. ; Tarquis Medina, M. ; Nedvedova, E. ; Jaki, J. ; Willmann, S. ; Scheibner, K. ; Cota, P. ; Salinno, C. ; Boldt, K. ; Horn, N. ; Ueffing, M. ; Burtscher, I. ; Theis, F.J. ; Coskun, Ü. ; Lickert, H.
Nat. Commun. 13:4540 (2022)
During pancreas development endocrine cells leave the ductal epithelium to form the islets of Langerhans, but the morphogenetic mechanisms are incompletely understood. Here, we identify the Ca2+-independent atypical Synaptotagmin-13 (Syt13) as a key regulator of endocrine cell egression and islet formation. We detect specific upregulation of the Syt13 gene and encoded protein in endocrine precursors and the respective lineage during islet formation. The Syt13 protein is localized to the apical membrane of endocrine precursors and to the front domain of egressing endocrine cells, marking a previously unidentified apical-basal to front-rear repolarization during endocrine precursor cell egression. Knockout of Syt13 impairs endocrine cell egression and skews the α-to-β-cell ratio. Mechanistically, Syt13 is a vesicle trafficking protein, transported via the microtubule cytoskeleton, and interacts with phosphatidylinositol phospholipids for polarized localization. By internalizing a subset of plasma membrane proteins at the front domain, including α6β4 integrins, Syt13 modulates cell-matrix adhesion and allows efficient endocrine cell egression. Altogether, these findings uncover an unexpected role for Syt13 as a morphogenetic driver of endocrinogenesis and islet formation.
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Scientific Article
Suls, J. ; Salive, M.E. ; Koroukian, S.M. ; Alemi, F. ; Silber, J.H. ; Kastenmüller, G. ; Klabunde, C.N.
J. Am. Geriatr. Soc., DOI: 10.1111/jgs.17914 (2022)
Older adults experience a higher prevalence of multiple chronic conditions (MCCs). Establishing the presence and pattern of MCCs in individuals or populations is important for healthcare delivery, research, and policy. This report describes four emerging approaches and discusses their potential applications for enhancing assessment, treatment, and policy for the aging population. The National Institutes of Health convened a 2-day panel workshop of experts in 2018. Four emerging models were identified by the panel, including classification and regression tree (CART), qualifying comorbidity sets (QCS), the multimorbidity index (MMI), and the application of omics to network medicine. Future research into models of multiple chronic condition assessment may improve understanding of the epidemiology, diagnosis, and treatment of older persons.
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Scientific Article
Milaneschi, Y. ; Arnold, M. ; Kastenmüller, G. ; Dehkordi, S.M. ; Krishnan, R.R. ; Dunlop, B.W. ; Rush, A.J. ; Penninx, B.W.J.H. ; Kaddurah-Daouk, R.
J. Affect. Disord. 307, 254-263 (2022)
Background: Altered metabolism of acylcarnitines – transporting fatty acids to mitochondria – may link cellular energy dysfunction to depression. We examined the potential causal role of acylcarnitine metabolism in depression by leveraging genomics and Mendelian randomization. Methods: Summary statistics were obtained from large GWAS: the Fenland Study (N = 9363), and the Psychiatric Genomics Consortium (246,363 depression cases and 561,190 controls). Two-sample Mendelian randomization analyses tested the potential causal link of 15 endogenous acylcarnitines with depression. Results: In univariable analyses, genetically-predicted lower levels of short-chain acylcarnitines C2 (odds ratio [OR] 0.97, 95% confidence intervals [CIs] 0.95–1.00) and C3 (OR 0.97, 95%CIs 0.96–0.99) and higher levels of medium-chain acylcarnitines C8 (OR 1.04, 95%CIs 1.01–1.06) and C10 (OR 1.04, 95%CIs 1.02–1.06) were associated with increased depression risk. No reverse potential causal role of depression genetic liability on acylcarnitines levels was found. Multivariable analyses showed that the association with depression was driven by the medium-chain acylcarnitines C8 (OR 1.04, 95%CIs 1.02–1.06) and C10 (OR 1.04, 95%CIs 1.02–1.06), suggesting a potential causal role in the risk of depression. Causal estimates for C8 (OR = 1.05, 95%CIs = 1.02–1.07) and C10 (OR = 1.05, 95%CIs = 1.02–1.08) were confirmed in follow-up analyses using genetic instruments derived from a GWAS meta-analysis including up to 16,841 samples. Discussion: Accumulation of medium-chain acylcarnitines is a signature of inborn errors of fatty acid metabolism and age-related metabolic conditions. Our findings point to a link between altered mitochondrial energy production and depression pathogenesis. Acylcarnitine metabolism represents a promising access point for the development of novel therapeutic approaches for depression.
Wissenschaftlicher Artikel
Scientific Article
Fiorentino, J. ; Scialdone, A.
PLoS Comput. Biol. 18:e1009552 (2022)
Cells can measure shallow gradients of external signals to initiate and accomplish a migration or a morphogenetic process. Recently, starting from mathematical models like the local-excitation global-inhibition (LEGI) model and with the support of empirical evidence, it has been proposed that cellular communication improves the measurement of an external gradient. However, the mathematical models that have been used have over-simplified geometries (e.g., they are uni-dimensional) or assumptions about cellular communication, which limit the possibility to analyze the gradient sensing ability of more complex cellular systems. Here, we generalize the existing models to study the effects on gradient sensing of cell number, geometry and of long- versus short-range cellular communication in 2D systems representing epithelial tissues. We find that increasing the cell number can be detrimental for gradient sensing when the communication is weak and limited to nearest neighbour cells, while it is beneficial when there is long-range communication. We also find that, with long-range communication, the gradient sensing ability improves for tissues with more disordered geometries; on the other hand, an ordered structure with mostly hexagonal cells is advantageous with nearest neighbour communication. Our results considerably extend the current models of gradient sensing by epithelial tissues, making a step further toward predicting the mechanism of communication and its putative mediator in many biological processes.
Wissenschaftlicher Artikel
Scientific Article
Ogris, C. ; Castresana-Aguirre, M. ; Sonnhammer, E.L.L.
Bioinformatics 38, 2659-2660 (2022)
MOTIVATION: Pathway annotation tools are indispensable for the interpretation of a wide range of experiments in life sciences. Network-based algorithms have recently been developed which are more sensitive than traditional overlap-based algorithms, but there is still a lack of good online tools for network-based pathway analysis. RESULTS: We present PathwAX II-a pathway analysis web tool based on network crosstalk analysis using the BinoX algorithm. It offers several new features compared to the first version, including interactive graphical network visualization of the crosstalk between a query gene set and an enriched pathway, and the addition of Reactome pathways. AVAILABILITY: PathwAX II is available at http://pathwax.sbc.su.se. SUPPLEMENTARY INFORMATION: Supplementary materials are available at Bioinformatics online.
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Scientific Article
Gomari, D.P. ; Schweickart, A. ; Cerchietti, L. ; Paietta, E. ; Fernandez, H.H. ; Al-Amin, H. ; Suhre, K. ; Krumsiek, J.
Comm. Biol. 5:645 (2022)
Dimensionality reduction approaches are commonly used for the deconvolution of high-dimensional metabolomics datasets into underlying core metabolic processes. However, current state-of-the-art methods are widely incapable of detecting nonlinearities in metabolomics data. Variational Autoencoders (VAEs) are a deep learning method designed to learn nonlinear latent representations which generalize to unseen data. Here, we trained a VAE on a large-scale metabolomics population cohort of human blood samples consisting of over 4500 individuals. We analyzed the pathway composition of the latent space using a global feature importance score, which demonstrated that latent dimensions represent distinct cellular processes. To demonstrate model generalizability, we generated latent representations of unseen metabolomics datasets on type 2 diabetes, acute myeloid leukemia, and schizophrenia and found significant correlations with clinical patient groups. Notably, the VAE representations showed stronger effects than latent dimensions derived by linear and non-linear principal component analysis. Taken together, we demonstrate that the VAE is a powerful method that learns biologically meaningful, nonlinear, and transferrable latent representations of metabolomics data.
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Scientific Article
Ebert, K. ; Haffner, I. ; Zwingenberger, G. ; Keller, S. ; Raimúndez, E. ; Geffers, R. ; Wirtz, R. ; Barbaria, E. ; Hollerieth, V. ; Arnold, R. ; Walch, A.K. ; Hasenauer, J. ; Maier, D. ; Lordick, F. ; Luber, B.
BMC Cancer 22:254 (2022)
BACKGROUND: The standard treatment for patients with advanced HER2-positive gastric cancer is a combination of the antibody trastuzumab and platin-fluoropyrimidine chemotherapy. As some patients do not respond to trastuzumab therapy or develop resistance during treatment, the search for alternative treatment options and biomarkers to predict therapy response is the focus of research. We compared the efficacy of trastuzumab and other HER-targeting drugs such as cetuximab and afatinib. We also hypothesized that treatment-dependent regulation of a gene indicates its importance in response and that it can therefore be used as a biomarker for patient stratification. METHODS: A selection of gastric cancer cell lines (Hs746T, MKN1, MKN7 and NCI-N87) was treated with EGF, cetuximab, trastuzumab or afatinib for a period of 4 or 24 h. The effects of treatment on gene expression were measured by RNA sequencing and the resulting biomarker candidates were tested in an available cohort of gastric cancer patients from the VARIANZ trial or functionally analyzed in vitro. RESULTS: After treatment of the cell lines with afatinib, the highest number of regulated genes was observed, followed by cetuximab and trastuzumab. Although trastuzumab showed only relatively small effects on gene expression, BMF, HAS2 and SHB could be identified as candidate biomarkers for response to trastuzumab. Subsequent studies confirmed HAS2 and SHB as potential predictive markers for response to trastuzumab therapy in clinical samples from the VARIANZ trial. AREG, EREG and HBEGF were identified as candidate biomarkers for treatment with afatinib and cetuximab. Functional analysis confirmed that HBEGF is a resistance factor for cetuximab. CONCLUSION: By confirming HAS2, SHB and HBEGF as biomarkers for anti-HER therapies, we provide evidence that the regulation of gene expression after treatment can be used for biomarker discovery. TRIAL REGISTRATION: Clinical specimens of the VARIANZ study (NCT02305043) were used to test biomarker candidates.
Wissenschaftlicher Artikel
Scientific Article
Efendiyev, M.A. ; Vougalter, V.
J. Dyn. Differ. Equ., DOI: 10.1007/s10884-022-10147-0 (2022)
We establish the existence in the sense of sequences of solutions for some integro-differential type equations containing the drift term and the square root of the one dimensional negative Laplacian, on the whole real line or on a finite interval with periodic boundary conditions in the corresponding H2 spaces. The argument relies on the fixed point technique when the elliptic equations involve first order differential operators with and without Fredholm property. It is proven that, under the reasonable technical assumptions, the convergence in L1 of the integral kernels implies the existence and convergence in H2 of solutions.
Wissenschaftlicher Artikel
Scientific Article
Bohnacker, S. ; Hartung, F. ; Henkel, F. ; Quaranta, A. ; Kolmert, J. ; Priller, A. ; Ud-Dean, M. ; Giglberger, J. ; Kugler, L.M. ; Pechtold, L. ; Yazici, S. ; Lechner, A. ; Erber, J. ; Protzer, U. ; Lingor, P. ; Knolle, P. ; Chaker, A. ; Schmidt-Weber, C.B. ; Wheelock, C.E. ; Esser-von Bieren, J.
Mucosal Immunol. 15, 515–524 (2022)
Monocyte-derived macrophages (MDM) drive the inflammatory response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and they are a major source of eicosanoids in airway inflammation. Here we report that MDM from SARS-CoV-2-infected individuals with mild disease show an inflammatory transcriptional and metabolic imprint that lasts for at least 5 months after SARS-CoV-2 infection. MDM from convalescent SARS-CoV-2-infected individuals showed a downregulation of pro-resolving factors and an increased production of pro-inflammatory eicosanoids, particularly 5-lipoxygenase-derived leukotrienes. Leukotriene synthesis was further enhanced by glucocorticoids and remained elevated at 3–5 months, but had returned to baseline at 12 months post SARS-CoV-2 infection. Stimulation with SARS-CoV-2 spike protein or LPS triggered exaggerated prostanoid-, type I IFN-, and chemokine responses in post COVID-19 MDM. Thus, SARS-CoV-2 infection leaves an inflammatory imprint in the monocyte/ macrophage compartment that drives aberrant macrophage effector functions and eicosanoid metabolism, resulting in long-term immune aberrations in patients recovering from mild COVID-19.
Wissenschaftlicher Artikel
Scientific Article
Fritz, C. ; Dorigatti, E. ; Rügamer, D.
Sci. Rep. 12:3930 (2022)
During 2020, the infection rate of COVID-19 has been investigated by many scholars from different research fields. In this context, reliable and interpretable forecasts of disease incidents are a vital tool for policymakers to manage healthcare resources. In this context, several experts have called for the necessity to account for human mobility to explain the spread of COVID-19. Existing approaches often apply standard models of the respective research field, frequently restricting modeling possibilities. For instance, most statistical or epidemiological models cannot directly incorporate unstructured data sources, including relational data that may encode human mobility. In contrast, machine learning approaches may yield better predictions by exploiting these data structures yet lack intuitive interpretability as they are often categorized as black-box models. We propose a combination of both research directions and present a multimodal learning framework that amalgamates statistical regression and machine learning models for predicting local COVID-19 cases in Germany. Results and implications: the novel approach introduced enables the use of a richer collection of data types, including mobility flows and colocation probabilities, and yields the lowest mean squared error scores throughout the observational period in the reported benchmark study. The results corroborate that during most of the observational period more dispersed meeting patterns and a lower percentage of people staying put are associated with higher infection rates. Moreover, the analysis underpins the necessity of including mobility data and showcases the flexibility and interpretability of the proposed approach.
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Scientific Article
Kukacka, J. ; Metz, S. ; Dehner, C. ; Muckenhuber, A. ; Paul-Yuan, K. ; Karlas, A. ; Fallenberg, E.M. ; Rummeny, E. ; Jüstel, D. ; Ntziachristos, V.
Photoacoustics 26, 100343 (2022)
Background: Since the initial breast transillumination almost a century ago, breast cancer imaging using light has been considered in different implementations aiming to improve diagnostics, minimize the number of available biopsies, or monitor treatment. However, due to strong photon scattering, conventional optical imaging yields low resolution images, challenging quantification and interpretation. Optoacoustic imaging addresses the scattering limitation and yields high-resolution visualization of optical contrast, offering great potential value for breast cancer imaging. Nevertheless, the image quality of experimental systems remains limited due to a number of factors, including signal attenuation with depth and partial view angle and motion effects, particularly in multi-wavelength measurements. Methods: We developed data analytics methods to improve the accuracy of handheld optoacoustic breast cancer imaging, yielding second-generation optoacoustic imaging performance operating in tandem with ultrasonography. Results: We produced the most advanced images yet with handheld optoacoustic examinations of the human breast and breast cancer, in terms of resolution and contrast. Using these advances, we examined optoacoustic markers of malignancy, including vasculature abnormalities, hypoxia, and inflammation, on images obtained from breast cancer patients. Conclusions: We achieved a new level of quality for optoacoustic images from a handheld examination of the human breast, advancing the diagnostic and theranostic potential of the hybrid optoacoustic-ultrasound (OPUS) examination over routine ultrasonography.
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Scientific Article
Pardo, M. ; Offer, S. ; Hartner, E. ; Di Bucchianico, S. ; Bisig, B. ; Bauer, S. ; Pantzke, J. ; Zimmermann, E. ; Cao, X. ; Binder, S. ; Kuhn, E. ; Huber, A. ; Jeong, S. ; Käfer, U. ; Schneider, E. ; Mesceriakovas, A. ; Bendl, J. ; Brejcha, R. ; Buchholz, A. ; Gat, D. ; Hohaus, T. ; Rastak, N. ; Karg, E.W. ; Jakobi, G. ; Kalberer, M. ; Kanashova, T. ; Hu, Y. ; Ogris, C. ; Marsico, A. ; Theis, F.J. ; Shalit, T. ; Gröger, T.M. ; Rüger, C.P. ; Oeder, S. ; Orasche, J. ; Paul, A. ; Ziehm, T. ; Zhang, Z.H. ; Adam, T. ; Sippula, O. ; Sklorz, M. ; Schnelle-Kreis, J. ; Czech, H. ; Kiendler-Scharr, A. ; Zimmermann, R. ; Rudich, Y.
Environ. Int. 166:107366 (2022)
The health effects of exposure to secondary organic aerosols (SOAs) are still limited. Here, we investigated and compared the toxicities of soot particles (SP) coated with β-pinene SOA (SOAβPin-SP) and SP coated with naphthalene SOA (SOANap-SP) in a human bronchial epithelial cell line (BEAS-2B) residing at the air-liquid interface. SOAβPin-SP mostly contained oxygenated aliphatic compounds from β-pinene photooxidation, whereas SOANap-SP contained a significant fraction of oxygenated aromatic products under similar conditions. Following exposure, genome-wide transcriptome responses showed an Nrf2 oxidative stress response, particularly for SOANap-SP. Other signaling pathways, such as redox signaling, inflammatory signaling, and the involvement of matrix metalloproteinase, were identified to have a stronger impact following exposure to SOANap-SP. SOANap-SP also induced a stronger genotoxicity response than that of SOAβPin-SP. This study elucidated the mechanisms that govern SOA toxicity and showed that, compared to SOAs derived from a typical biogenic precursor, SOAs from a typical anthropogenic precursor have higher toxicological potency, which was accompanied with the activation of varied cellular mechanisms, such as aryl hydrocarbon receptor. This can be attributed to the difference in chemical composition; specifically, the aromatic compounds in the naphthalene-derived SOA had higher cytotoxic potential than that of the β-pinene-derived SOA.
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Scientific Article
Cadby, G. ; Giles, C. ; Melton, P.E. ; Huynh, K. ; Mellett, N.A. ; Duong, T. ; Nguyen, A. ; Cinel, M. ; Smith, A. ; Olshansky, G. ; Wang, T. ; Brozynska, M. ; Inouye, M. ; McCarthy, N.S. ; Ariff, A. ; Hung, J. ; Hui, J. ; Beilby, J. ; Dubé, M.P. ; Watts, G.F. ; Shah, S. ; Wray, N.R. ; Lim, W.L.F. ; Chatterjee, P. ; Martins, I. ; Laws, S.M. ; Porter, T. ; Vacher, M. ; Bush, A.I. ; Rowe, C.C. ; Villemagne, V.L. ; Ames, D. ; Masters, C.L. ; Taddei, K. ; Arnold, M. ; Kastenmüller, G. ; Nho, K. ; Saykin, A.J. ; Han, X. ; Kaddurah-Daouk, R. ; Martins, R.N. ; Blangero, J. ; Meikle, P.J. ; Moses, E.K.
Nat. Commun. 13:3124 (2022)
We integrated lipidomics and genomics to unravel the genetic architecture of lipid metabolism and identify genetic variants associated with lipid species putatively in the mechanistic pathway for coronary artery disease (CAD). We quantified 596 lipid species in serum from 4,492 individuals from the Busselton Health Study. The discovery GWAS identified 3,361 independent lipid-loci associations, involving 667 genomic regions (479 previously unreported), with validation in two independent cohorts. A meta-analysis revealed an additional 70 independent genomic regions associated with lipid species. We identified 134 lipid endophenotypes for CAD associated with 186 genomic loci. Associations between independent lipid-loci with coronary atherosclerosis were assessed in ∼456,000 individuals from the UK Biobank. Of the 53 lipid-loci that showed evidence of association (P < 1 × 10-3), 43 loci were associated with at least one lipid endophenotype. These findings illustrate the value of integrative biology to investigate the aetiology of atherosclerosis and CAD, with implications for other complex diseases.
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Scientific Article
Lopez, J.P. ; Luecken, M. ; Brivio, E. ; Karamihalev, S. ; Kos, A. ; De Donno, C. ; Benjamin, A. ; Yang, H. ; Dick, A.L.W. ; Stoffel, R. ; Flachskamm, C. ; Ressle, A. ; Roeh, S. ; Huettl, R.E. ; Parl, A. ; Eggert, C. ; Novak, B. ; Yan, Y. ; Yeoh, K. ; Holzapfel, M. ; Hauger, B. ; Harbich, D. ; Schmid, B. ; Di Giaimo, R. ; Turck, C.W. ; Schmidt, M.V. ; Deussing, J.M. ; Eder, M. ; Dine, J. ; Theis, F.J. ; Chen, A.
Neuron 110, 2283-2298.e9 (2022)
A single sub-anesthetic dose of ketamine produces a rapid and sustained antidepressant response, yet the molecular mechanisms responsible for this remain unclear. Here, we identified cell-type-specific transcriptional signatures associated with a sustained ketamine response in mice. Most interestingly, we identified the Kcnq2 gene as an important downstream regulator of ketamine action in glutamatergic neurons of the ventral hippocampus. We validated these findings through a series of complementary molecular, electrophysiological, cellular, pharmacological, behavioral, and functional experiments. We demonstrated that adjunctive treatment with retigabine, a KCNQ activator, augments ketamine's antidepressant-like effects in mice. Intriguingly, these effects are ketamine specific, as they do not modulate a response to classical antidepressants, such as escitalopram. These findings significantly advance our understanding of the mechanisms underlying the sustained antidepressant effects of ketamine, with important clinical implications.
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Scientific Article
Schultze, J.L. ; Büttner, M. ; Becker, M.
Nat. Rev. Immunol. 22, 401–403 (2022)
Sonstiges: Meinungsartikel
Other: Opinion
Mertes, C. ; Scheller, I.F. ; Yépez, V.A. ; Çelik, M.H. ; Liang, Y. ; Kremer, L.S. ; Gusic, M. ; Prokisch, H. ; Gagneur, J.
Nat. Commun. 13:3474 (2022)
Filbir, F. ; Schroeder, K. ; Veselovska, A.
Numer. Funct. Anal. Optim. 43, 755-795 (2022)
We study the problem of recovering an atomic measure on the unit 2-sphere (Formula presented.) given finitely many moments with respect to spherical harmonics. The analysis relies on the formulation of this problem as an optimization problem on the space of bounded Borel measures on (Formula presented.) as it was considered by Y. de Castro & F. Gamboa (J. Math. Anal. Appl. 395(1):336–354, 2012) and E. Candés & C. Fernandez-Granda (J. Fourier Anal. Appl. 19(6):1229–1254, 2013). We construct a dual certificate using a kernel given in an explicit form and make a concrete analysis of the interpolation problem. Numerical examples are provided and analyzed.
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Erber, J. ; Kappler, V. ; Haller, B. ; Mijočević, H. ; Galhoz, A. ; da Costa, C.P. ; Gebhardt, F. ; Graf, N. ; Hoffmann, D. ; Thaler, M. ; Lorenz, E. ; Roggendorf, H. ; Kohlmayer, F. ; Henkel, A. ; Menden, M. ; Ruland, J. ; Spinner, C.D. ; Protzer, U. ; Knolle, P. ; Lingor, P.
Emerg. Infect. Dis 28, 572-581 (2022)
Hospital staff are at high risk for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection during the coronavirus disease (COVID-19) pandemic. This cross-sectional study aimed to determine the prevalence of SARS-CoV-2 infection in hospital staff at the University Hospital rechts der Isar in Munich, Germany, and identify modulating factors. Overall seroprevalence of SARS-CoV-2-IgG in 4,554 participants was 2.4%. Staff engaged in direct patient care, including those working in COVID-19 units, had a similar probability of being seropositive as non–patient-facing staff. Increased probability of infection was observed in staff reporting interactions with SARS-CoV-2-infected coworkers or private contacts or exposure to COVID-19 patients without appropriate personal protective equipment. Analysis of spatiotemporal trajectories identified that distinct hotspots for SARS-CoV-2-positive staff and patients only partially overlap. Patient-facing work in a healthcare facility during the SARS-CoV-2 pandemic might be safe as long as adequate personal protective equipment is used and infection prevention practices are followed inside and outside the hospital.
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Scientific Article
Efendiyev, M.A. ; Vougalter, V.
Electron. Res. Arch. 30, 515-534 (2022)
In this survey we discuss the recent results on the existence in the sense of sequences of solutions for certain elliptic problems containing the non-Fredholm operators. First of all, we deal with the solvability in the sense of sequences for some fourth order non-Fredholm operators, such that the methods of the spectral and scattering theory for Schrödinger type operators are used for the analysis. Moreover, we present the easily verifiable necessary condition of the preservation of the nonnegativity of the solutions of a system of parabolic equations in the case of the anomalous diffusion with the negative Laplacian in a fractional power in one dimension, which imposes the necessary form of such system of equations that must be studied mathematically. This class of systems of PDEs has a wide range of applications. We conclude the survey with several new results nowhere published concerning the solvability in the sense of sequences for the generalized Poisson type equation with a scalar potential.
Wissenschaftlicher Artikel
Scientific Article
Lutz, K. ; Musumeci, A. ; Sie, C. ; Dursun, E. ; Winheim, E. ; Bagnoli, J. ; Ziegenhain, C. ; Rausch, L. ; Bergen, V. ; Luecken, M. ; Oostendorp, R.A.J. ; Schraml, B.U. ; Theis, F.J. ; Enard, W. ; Korn, T. ; Krug, A.B.
Nat. Commun. 13:3456 (2022)
Plasmacytoid and conventional dendritic cells (pDC and cDC) are generated from progenitor cells in the bone marrow and commitment to pDCs or cDC subtypes may occur in earlier and later progenitor stages. Cells within the CD11c+MHCII-/loSiglec-H+CCR9lo DC precursor fraction of the mouse bone marrow generate both pDCs and cDCs. Here we investigate the heterogeneity and commitment of subsets in this compartment by single-cell transcriptomics and high-dimensional flow cytometry combined with cell fate analysis: Within the CD11c+MHCII-/loSiglec-H+CCR9lo DC precursor pool cells expressing high levels of Ly6D and lacking expression of transcription factor Zbtb46 contain CCR9loB220hi immediate pDC precursors and CCR9loB220lo (lo-lo) cells which still generate pDCs and cDCs in vitro and in vivo under steady state conditions. cDC-primed cells within the Ly6DhiZbtb46- lo-lo precursors rapidly upregulate Zbtb46 and pass through a Zbtb46+Ly6D+ intermediate stage before acquiring cDC phenotype after cell division. Type I IFN stimulation limits cDC and promotes pDC output from this precursor fraction by arresting cDC-primed cells in the Zbtb46+Ly6D+ stage preventing their expansion and differentiation into cDCs. Modulation of pDC versus cDC output from precursors by external factors may allow for adaptation of DC subset composition at later differentiation stages.
Wissenschaftlicher Artikel
Scientific Article
Grimalt, J.O. ; Garí, M. ; Santa-Marina, L. ; Ibarluzea, J. ; Sunyer, J.
Environ. Res. 209:112783 (2022)
BACKGROUND: Transplacental transfer and breastfeeding are the main transport routes of organic pollutants into children at the beginning of life. Although pollutant transmission through these mechanisms primarily depends on the maternal pollution burden, its impact may be modulated by physiological effects. OBJECTIVES: We have examined whether gestational weight gain (GWG) exerts an influence on the content of lipophilic low volatile pollutants in breast milk. RESULTS: Colostrum from mothers from the INMA cohorts of Sabadell and Gipuzkoa (n = 256 and 119, respectively) with low GWG as defined by the Institute of Medicine (IOM) from the US National Academies of Sciences, Engineering and Medicine had significantly higher concentrations of polychlorobiphenyls (PCBs) and 4,4'-DDE than colostrum in mothers who gained weight within IOM recommendations or in those who exceeded this threshold. Statistically significant differences were also found in the colostrum:maternal serum ratios of these compounds. Women with low GWG retained higher pollutant amounts in colostrum. These observations are consistent with previously described higher concentrations of these pollutants in infant cord blood from mothers with low GWG by IOM standards. They indicate that mobilization of lipophilic organic pollutants by metabolic pregnant changes not only leads to higher fetal transfer but to higher accumulation into the mammary system upon low GWG. CONCLUSIONS: The present results show that insufficient GWG, besides increasing in utero exposure, also enhances pollutant transfer to infants during breastfeeding which considerably extends the significance of this physiological change for the pollutant children intake in early life.
Wissenschaftlicher Artikel
Scientific Article
Gehlert, S. ; Weinisch, P. ; Römisch-Margl, W. ; Jaspers, R.T. ; Artati, A. ; Adamski, J. ; Dyar, K.A. ; Aussieker, T. ; Jacko, D. ; Bloch, W. ; Wackerhage, H. ; Kastenmüller, G.
Metabolites 12:445 (2022)
Resistance training promotes metabolic health and stimulates muscle hypertrophy, but the precise routes by which resistance exercise (RE) conveys these health benefits are largely unknown. Aim: To investigate how acute RE affects human skeletal muscle metabolism. Methods: We collected vastus lateralis biopsies from six healthy male untrained volunteers at rest, before the first of 13 RE training sessions, and 45 min after the first and last bouts of RE. Biopsies were analysed using untargeted mass spectrometry-based metabolomics. Results: We measured 617 metabolites covering a broad range of metabolic pathways. In the untrained state RE altered 33 metabolites, including increased 3-methylhistidine and N-lactoylvaline, suggesting increased protein breakdown, as well as metabolites linked to ATP (xanthosine) and NAD (N1-methyl-2-pyridone-5-carboxamide) metabolism; the bile acid chenodeoxycholate also increased in response to RE in muscle opposing previous findings in blood. Resistance training led to muscle hypertrophy, with slow type I and fast/intermediate type II muscle fibre diameter increasing by 10.7% and 10.4%, respectively. Comparison of post-exercise metabolite levels between trained and untrained state revealed alterations of 46 metabolites, including decreased N-acetylated ketogenic amino acids and increased beta-citrylglutamate which might support growth. Only five of the metabolites that changed after acute exercise in the untrained state were altered after chronic training, indicating that training induces multiple metabolic changes not directly related to the acute exercise response. Conclusion: The human skeletal muscle metabolome is sensitive towards acute RE in the trained and untrained states and reflects a broad range of adaptive processes in response to repeated stimulation.
Wissenschaftlicher Artikel
Scientific Article
Zimmermann, P. ; Antonelli, M.C. ; Sharma, R. ; Müller, A. ; Zelgert, C. ; Fabre, B. ; Wenzel, N. ; Wu, H.T. ; Frasch, M.G. ; Lobmaier, S.M.
Sci. Rep. 12:9341 (2022)
The adverse effects of maternal prenatal stress (PS) on child's neurodevelopment warrant the establishment of biomarkers that enable early interventional therapeutic strategies. We performed a prospective matched double cohort study screening 2000 pregnant women in third trimester with Cohen Perceived Stress Scale-10 (PSS-10) questionnaire; 164 participants were recruited and classified as stressed and control group (SG, CG). Fetal cord blood iron parameters of 107 patients were measured at birth. Transabdominal electrocardiograms-based Fetal Stress Index (FSI) was derived. We investigated sex contribution to group differences and conducted causal inference analyses to assess the total effect of PS exposure on iron homeostasis using a directed acyclic graph (DAG) approach. Differences are reported for p < 0.05 unless noted otherwise. Transferrin saturation was lower in male stressed neonates. The minimum adjustment set of the DAG to estimate the total effect of PS exposure on fetal ferritin iron biomarkers consisted of maternal age and socioeconomic status: SG revealed a 15% decrease in fetal ferritin compared with CG. Mean FSI was higher among SG than among CG. FSI-based timely detection of fetuses affected by PS can support early individualized iron supplementation and neurodevelopmental follow-up to prevent long-term sequelae due to PS-exacerbated impairment of the iron homeostasis.
Wissenschaftlicher Artikel
Scientific Article
Pieschner, S. ; Hasenauer, J. ; Fuchs, C.
J. Math. Biol. 84:56 (2022)
Mechanistic models are a powerful tool to gain insights into biological processes. The parameters of such models, e.g. kinetic rate constants, usually cannot be measured directly but need to be inferred from experimental data. In this article, we study dynamical models of the translation kinetics after mRNA transfection and analyze their parameter identifiability. That is, whether parameters can be uniquely determined from perfect or realistic data in theory and practice. Previous studies have considered ordinary differential equation (ODE) models of the process, and here we formulate a stochastic differential equation (SDE) model. For both model types, we consider structural identifiability based on the model equations and practical identifiability based on simulated as well as experimental data and find that the SDE model provides better parameter identifiability than the ODE model. Moreover, our analysis shows that even for those parameters of the ODE model that are considered to be identifiable, the obtained estimates are sometimes unreliable. Overall, our study clearly demonstrates the relevance of considering different modeling approaches and that stochastic models can provide more reliable and informative results.
Wissenschaftlicher Artikel
Scientific Article
Shaikh, B. ; Smith, L.P. ; Vasilescu, D. ; Marupilla, G. ; Wilson, M. ; Agmon, E. ; Agnew, H. ; Andrews, S.S. ; Anwar, A. ; Beber, M.E. ; Bergmann, F.T. ; Brooks, D. ; Brusch, L. ; Calzone, L. ; Choi, K. ; Cooper, J. ; Detloff, J. ; Drawert, B. ; Dumontier, M. ; Ermentrout, G.B. ; Faeder, J.R. ; Freiburger, A.P. ; Fröhlich, F. ; Funahashi, A. ; Garny, A. ; Gennari, J.H. ; Gleeson, P. ; Goelzer, A. ; Haiman, Z. ; Hasenauer, J. ; Hellerstein, J.L. ; Hermjakob, H. ; Hoops, S. ; Ison, J.C. ; Jahn, D. ; Jakubowski, H.V. ; Jordan, R. ; Kalaš, M. ; König, M. ; Liebermeister, W. ; Sheriff, R.S.M. ; Mandal, S. ; McDougal, R. ; Medley, J.K. ; Mendes, P. ; Müller, R. ; Myers, C.J. ; Naldi, A. ; Nguyen, T.V.N. ; Nickerson, D.P. ; Olivier, B.G. ; Patoliya, D. ; Paulevé, L. ; Petzold, L.R. ; Priya, A. ; Rampadarath, A.K. ; Rohwer, J.M. ; Saglam, A.S. ; Singh, D. ; Sinha, A. ; Snoep, J.D. ; Sorby, H. ; Spangler, R. ; Starruß, J. ; Thomas, P.J. ; van Niekerk, D. ; Weindl, D. ; Zhang, F. ; Zhukova, A. ; Goldberg, A.P. ; Schaff, J.C. ; Blinov, M.L. ; Sauro, H.M. ; Moraru, I.I. ; Karr, J.R.
Nucleic Acids Res. 50, W108-W114 (2022)
Computational models have great potential to accelerate bioscience, bioengineering, and medicine. However, it remains challenging to reproduce and reuse simulations, in part, because the numerous formats and methods for simulating various subsystems and scales remain siloed by different software tools. For example, each tool must be executed through a distinct interface. To help investigators find and use simulation tools, we developed BioSimulators (https://biosimulators.org), a central registry of the capabilities of simulation tools and consistent Python, command-line and containerized interfaces to each version of each tool. The foundation of BioSimulators is standards, such as CellML, SBML, SED-ML and the COMBINE archive format, and validation tools for simulation projects and simulation tools that ensure these standards are used consistently. To help modelers find tools for particular projects, we have also used the registry to develop recommendation services. We anticipate that BioSimulators will help modelers exchange, reproduce, and combine simulations.
Wissenschaftlicher Artikel
Scientific Article
Mutsch, B. ; Heiber, M. ; Grätz, F. ; Hain, R. ; Schönfelder, M. ; Kaps, S. ; Schranner, D. ; Kähler, C.J. ; Wackerhage, H.
Proc. Natl. Acad. Sci. U.S.A. 119:e2202521119 (2022)
SignificanceAirborne transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) or other pathogens is probably increased during indoor exercise, but data on the emission of aerosol particles by an exercising individual are lacking. Here, we report that aerosol particle emission increases on average 132-fold from 580 ± 489 particles/min at rest to 76,200 ± 48,000 particles/min during maximal exercise. Aerosol particle emission increases moderately up to an exercise intensity of ≈2 W/kg and exponentially at higher exercise intensities. These data not only explain SARS-CoV-2 transmissions during indoor group exercise but also can be used to design better targeted mitigation measures for physical activity indoors such as physical education in school, dance events during weddings, or high-intensity gym classes such as spinning.
Wissenschaftlicher Artikel
Scientific Article
Muhammad, M.H. ; Prakash, J. ; Liapis, E. ; Ntziachristos, V. ; Jüstel, D.
J. Biophotonics 15:e202100334 (2022)
Acoustic heterogeneities in biological samples are known to cause artefacts in tomographic optoacoustic (photoacoustic) image reconstruction. A statistical weighted model-based reconstruction approach was previously introduced to mitigate such artefacts. However, this approach does not reliably provide high-quality reconstructions for partial-view imaging systems, which are common in preclinical and clinical optoacoustics. In this paper, the capability of the weighted model-based algorithm is extended to generate optoacoustic reconstructions with less distortions for partial-view geometry data. This is achieved by manipulating the weighting scheme based on the detector geometry. Using partial-view optoacoustic tomography data from a tissue-mimicking phantom containing a strong acoustic reflector, tumors grafted onto mice, and a mouse brain with intact skull, the proposed partial-view-corrected weighted model-based algorithm is shown to mitigate reflection artefacts in reconstructed images without distorting structures or boundaries, compared to both conventional model-based and the weighted model-based algorithms. It is also demonstrated that the partial-view-corrected weighted model-based algorithm has the additional advantage of suppressing streaking artefacts due to the partial-view geometry itself in the presence of a very strong optoacoustic chromophore. Due to its enhanced performance, the partial-view-corrected weighted model-based algorithm may prove useful for improving the quality of partial-view multispectral optoacoustic tomography, leading to enhanced visualization of functional parameters such as tissue oxygenation. This article is protected by copyright. All rights reserved.
Wissenschaftlicher Artikel
Scientific Article
Brydges, C.R. ; Bhattacharyya, S. ; Dehkordi, S.M. ; Milaneschi, Y. ; Penninx, B. ; Jansen, R. ; Kristal, B.S. ; Han, X. ; Arnold, M. ; Kastenmüller, G. ; Bekhbat, M. ; Mayberg, H.S. ; Craighead, W.E. ; Rush, A.J. ; Fiehn, O. ; Dunlop, B.W. ; Kaddurah-Daouk, R.
Brain Behav. Immun. 102, 42-52 (2022)
BACKGROUND: Major depressive disorder (MDD) is a highly heterogenous disease, both in terms of clinical profiles and pathobiological alterations. Recently, immunometabolic dysregulations were shown to be correlated with atypical, energy-related symptoms but less so with the Melancholic or Anxious distress symptom dimensions of depression in The Netherlands Study of Depression and Anxiety (NESDA) study. In this study, we aimed to replicate these immunometabolic associations and to characterize the metabolomic correlates of each of the three MDD dimensions. METHODS: Using three clinical rating scales, Melancholic, and Anxious distress, and Immunometabolic (IMD) dimensions were characterized in 158 patients who participated in the Predictors of Remission to Individual and Combined Treatments (PReDICT) study and from whom plasma and serum samples were available. The NESDA-defined inflammatory index, a composite measure of interleukin-6 and C-reactive protein, was measured from pre-treatment plasma samples and a metabolomic profile was defined using serum samples analyzed on three metabolomics platforms targeting fatty acids and complex lipids, amino acids, acylcarnitines, and gut microbiome-derived metabolites among other metabolites of central metabolism. RESULTS: The IMD clinical dimension and the inflammatory index were positively correlated (r=0.19, p=.019) after controlling for age, sex, and body mass index, whereas the Melancholic and Anxious distress dimensions were not, replicating the previous NESDA findings. The three symptom dimensions had distinct metabolomic signatures using both univariate and set enrichment statistics. IMD severity correlated mainly with gut-derived metabolites and a few acylcarnitines and long chain saturated free fatty acids. Melancholia severity was significantly correlated with several phosphatidylcholines, primarily the ether-linked variety, lysophosphatidylcholines, as well as several amino acids. Anxious distress severity correlated with several medium and long chain free fatty acids, both saturated and polyunsaturated ones, sphingomyelins, as well as several amino acids and bile acids. CONCLUSION: The IMD dimension of depression appears reliably associated with markers of inflammation. Metabolomics provides powerful tools to inform about depression heterogeneity and molecular mechanisms related to clinical dimensions in MDD, which include a link to gut microbiome and lipids implicated in membrane structure and function.
Wissenschaftlicher Artikel
Scientific Article
Sommer, A. ; Peters, A. ; Rommel, M. ; Cyrys, J. ; Grallert, H. ; Haller, D. ; Müller, C. ; Bind, M.C.
PLoS Comput. Biol. 18:e1010044 (2022)
Statistical analysis of microbial genomic data within epidemiological cohort studies holds the promise to assess the influence of environmental exposures on both the host and the host-associated microbiome. However, the observational character of prospective cohort data and the intricate characteristics of microbiome data make it challenging to discover causal associations between environment and microbiome. Here, we introduce a causal inference framework based on the Rubin Causal Model that can help scientists to investigate such environment-host microbiome relationships, to capitalize on existing, possibly powerful, test statistics, and test plausible sharp null hypotheses. Using data from the German KORA cohort study, we illustrate our framework by designing two hypothetical randomized experiments with interventions of (i) air pollution reduction and (ii) smoking prevention. We study the effects of these interventions on the human gut microbiome by testing shifts in microbial diversity, changes in individual microbial abundances, and microbial network wiring between groups of matched subjects via randomization-based inference. In the smoking prevention scenario, we identify a small interconnected group of taxa worth further scrutiny, including Christensenellaceae and Ruminococcaceae genera, that have been previously associated with blood metabolite changes. These findings demonstrate that our framework may uncover potentially causal links between environmental exposure and the gut microbiome from observational data. We anticipate the present statistical framework to be a good starting point for further discoveries on the role of the gut microbiome in environmental health.
Wissenschaftlicher Artikel
Scientific Article
Ayhan, M.S. ; Kuemmerle, L. ; Kühlewein, L. ; Inhoffen, W. ; Aliyeva, G. ; Ziemssen, F. ; Berens, P.
Med. Image Anal. 77:102364 (2022)
Deep neural networks (DNNs) have achieved physician-level accuracy on many imaging-based medical diagnostic tasks, for example classification of retinal images in ophthalmology. However, their decision mechanisms are often considered impenetrable leading to a lack of trust by clinicians and patients. To alleviate this issue, a range of explanation methods have been proposed to expose the inner workings of DNNs leading to their decisions. For imaging-based tasks, this is often achieved via saliency maps. The quality of these maps are typically evaluated via perturbation analysis without experts involved. To facilitate the adoption and success of such automated systems, however, it is crucial to validate saliency maps against clinicians. In this study, we used three different network architectures and developed ensembles of DNNs to detect diabetic retinopathy and neovascular age-related macular degeneration from retinal fundus images and optical coherence tomography scans, respectively. We used a variety of explanation methods and obtained a comprehensive set of saliency maps for explaining the ensemble-based diagnostic decisions. Then, we systematically validated saliency maps against clinicians through two main analyses — a direct comparison of saliency maps with the expert annotations of disease-specific pathologies and perturbation analyses using also expert annotations as saliency maps. We found the choice of DNN architecture and explanation method to significantly influence the quality of saliency maps. Guided Backprop showed consistently good performance across disease scenarios and DNN architectures, suggesting that it provides a suitable starting point for explaining the decisions of DNNs on retinal images.
Wissenschaftlicher Artikel
Scientific Article
Matek, C.
Patterns 3:100426 (2022)
Label-efficient algorithms are of central importance for machine learning applications in many medical fields, where obtaining expert annotations is often expensive and time-consuming. Soni et al. show how contrastive learning can help build classifiers for one of the oldest and most revered methods of clinical medicine: auscultation of heart and lung sounds.
Editorial
Editorial
Cuschieri, S. ; Borg, D. ; Agius, S. ; Scherb, H. ; Grech, V.
J. Egypt. Public Health Assoc. 97:7 (2022)
BACKGROUND: COVID-19 has severely impacted global healthcare services. Malta has only one acute state hospital, Mater Dei Hospital (MDH), and at the time of writing is the most vaccinated country in Europe. Malta thus provides an ideal setting to assess the impact of COVID-19 on healthcare services at population level, including the impact of vaccination on hospital admissions. METHODS: Hospital data was obtained as anonymised totals from MDH's Clinical Performance Unit and the European Centre for Disease Prevention and Control. COVID-19-related data was obtained from the Ministry of Health dashboard. Comparative assessments were performed to explore associations between the COVID-19 situation, vaccination, and hospital activity. Poisson regression was used to model the counts of monthly accident and emergency (A&E), outpatient clinics attendances and hospital admissions. RESULTS: A&E, hospital admissions, and outpatient clinics attendances declined (31.88%; 23.89%; 29.57%; p < 0.01 respectively) with onset of COVID-19 till April 2021 when compared to pre-COVID years (2017-2019). Admissions due to COVID-19 initially increased in parallel to the population's COVID positivity. Vaccination rollout led to a decline in COVID-19 admissions. CONCLUSIONS: The drastic drop in admissions and outpatient attendees was expected but not for A&E attendees as acutely ill patients should still have attended. This is of public health concern since delayed or deferred medical management increases population morbidity, mortality and increases the eventual burden on the healthcare system. Mass vaccination saw the return to normality with an increase in A&E burden.
Wissenschaftlicher Artikel
Scientific Article
Maddu, S. ; Sturm, D. ; Müller, C. ; Sbalzarini, I.F.
Mach. Learn.: Sci. Technol. 3:015026 (2022)
We characterize and remedy a failure mode that may arise from multi-scale dynamics with scale imbalances during training of deep neural networks, such as physics informed neural networks (PINNs). PINNs are popular machine-learning templates that allow for seamless integration of physical equation models with data. Their training amounts to solving an optimization problem over a weighted sum of data-fidelity and equation-fidelity objectives. Conflicts between objectives can arise from scale imbalances, heteroscedasticity in the data, stiffness of the physical equation, or from catastrophic interference during sequential training. We explain the training pathology arising from this and propose a simple yet effective inverse Dirichlet weighting strategy to alleviate the issue. We compare with Sobolev training of neural networks, providing the baseline of analytically epsilon-optimal training. We demonstrate the effectiveness of inverse Dirichlet weighting in various applications, including a multi-scale model of active turbulence, where we show orders of magnitude improvement in accuracy and convergence over conventional PINN training. For inverse modeling using sequential training, we find that inverse Dirichlet weighting protects a PINN against catastrophic forgetting.
Wissenschaftlicher Artikel
Scientific Article
Falkai, P. ; Koutsouleris, N. ; Bertsch, K. ; Bialas, M. ; Binder, E. ; Bühner, M. ; Buyx, A. ; Cai, N. ; Cappello, S. ; Ehring, T. ; Gensichen, J. ; Hamann, J. ; Hasan, A. ; Henningsen, P. ; Leucht, S. ; Möhrmann, K.H. ; Nagelstutz, E. ; Padberg, F. ; Peters, A. ; Pfäffel, L. ; Reich-Erkelenz, D. ; Riedl, V. ; Rueckert, D. ; Schmitt, A. ; Schulte-Körne, G. ; Scheuring, E. ; Schulze, T.G. ; Starzengruber, R. ; Stier, S. ; Theis, F.J. ; Winkelmann, J. ; Wurst, W. ; Priller, J.
Front. Psychiatr. 13:815718 (2022)
The Federal Ministry of Education and Research (BMBF) issued a call for a new nationwide research network on mental disorders, the German Center of Mental Health (DZPG). The Munich/Augsburg consortium was selected to participate as one of six partner sites with its concept "Precision in Mental Health (PriMe): Understanding, predicting, and preventing chronicity." PriMe bundles interdisciplinary research from the Ludwig-Maximilians-University (LMU), Technical University of Munich (TUM), University of Augsburg (UniA), Helmholtz Center Munich (HMGU), and Max Planck Institute of Psychiatry (MPIP) and has a focus on schizophrenia (SZ), bipolar disorder (BPD), and major depressive disorder (MDD). PriMe takes a longitudinal perspective on these three disorders from the at-risk stage to the first-episode, relapsing, and chronic stages. These disorders pose a major health burden because in up to 50% of patients they cause untreatable residual symptoms, which lead to early social and vocational disability, comorbidities, and excess mortality. PriMe aims at reducing mortality on different levels, e.g., reducing death by psychiatric and somatic comorbidities, and will approach this goal by addressing interdisciplinary and cross-sector approaches across the lifespan. PriMe aims to add a precision medicine framework to the DZPG that will propel deeper understanding, more accurate prediction, and personalized prevention to prevent disease chronicity and mortality across mental illnesses. This framework is structured along the translational chain and will be used by PriMe to innovate the preventive and therapeutic management of SZ, BPD, and MDD from rural to urban areas and from patients in early disease stages to patients with long-term disease courses. Research will build on platforms that include one on model systems, one on the identification and validation of predictive markers, one on the development of novel multimodal treatments, one on the regulation and strengthening of the uptake and dissemination of personalized treatments, and finally one on testing of the clinical effectiveness, utility, and scalability of such personalized treatments. In accordance with the translational chain, PriMe's expertise includes the ability to integrate understanding of bio-behavioral processes based on innovative models, to translate this knowledge into clinical practice and to promote user participation in mental health research and care.
Review
Review
Loh, M. ; Zhang, W. ; Ng, H.K. ; Schmid, K. ; Lamri, A. ; Tong, L. ; Ahmad, M. ; Lee, J.J. ; Ng, M.C.Y. ; Petty, L.E. ; Spracklen, C.N. ; Takeuchi, F. ; Islam, M.T. ; Jasmine, F. ; Kasturiratne, A. ; Kibriya, M.G. ; Mohlke, K.L. ; Paré, G. ; Prasad, G. ; Shahriar, M. ; Chee, M.L. ; de Silva, H.J. ; Engert, J.C. ; Gerstein, H.C. ; Mani, K.R. ; Sabanayagam, C. ; Vujkovic, M.R. ; Wickremasinghe, A.R. ; Wong, T.Y. ; Yajnik, C.S. ; Yusuf, S. ; Ahsan, H. ; Bharadwaj, D. ; Anand, S.S. ; Below, J.E. ; Boehnke, M. ; Bowden, D.W. ; Chandak, G.R. ; Cheng, C.Y. ; Kato, N. ; Mahajan, A. ; Sim, X. ; McCarthy, M.I. ; Morris, A.P. ; Kooner, J.S. ; Saleheen, D.
Comm. Biol. 5:329 (2022)
South Asians are at high risk of developing type 2 diabetes (T2D). We carried out a genome-wide association meta-analysis with South Asian T2D cases (n = 16,677) and controls (n = 33,856), followed by combined analyses with Europeans (neff = 231,420). We identify 21 novel genetic loci for significant association with T2D (P = 4.7 × 10-8 to 5.2 × 10-12), to the best of our knowledge at the point of analysis. The loci are enriched for regulatory features, including DNA methylation and gene expression in relevant tissues, and highlight CHMP4B, PDHB, LRIG1 and other genes linked to adiposity and glucose metabolism. A polygenic risk score based on South Asian-derived summary statistics shows ~4-fold higher risk for T2D between the top and bottom quartile. Our results provide further insights into the genetic mechanisms underlying T2D, and highlight the opportunities for discovery from joint analysis of data from across ancestral populations.
Wissenschaftlicher Artikel
Scientific Article
Stirm, L. ; Huypens, P. ; Sass, S. ; Batra, R. ; Fritsche, L. ; Brucker, S. ; Abele, H. ; Hennige, A.M. ; Theis, F.J. ; Beckers, J. ; Hrabě de Angelis, M. ; Fritsche, A. ; Häring, H.-U. ; Staiger, H.
Sci. Rep. 12:6793 (2022)
This Article contains an error in Table 1 where the mean value and standard deviation of pregnancy week for the "screening group:NGT women" was incorrectly given as 23.0 +/- 9.5. The correct numbers are 26.5 +/- 2.1. Incorrect: (Table presented.) Correct: (Table presented.).
Loh, M. ; Zhang, W. ; Ng, H.K. ; Schmid, K. ; Lamri, A. ; Tong, L. ; Ahmad, M. ; Lee, J.J. ; Ng, M.C.Y. ; Petty, L.E. ; Spracklen, C.N. ; Takeuchi, F. ; Islam, M.T. ; Jasmine, F. ; Kasturiratne, A. ; Kibriya, M.G. ; Mohlke, K.L. ; Paré, G. ; Prasad, G. ; Shahriar, M. ; Chee, M.L. ; de Silva, H.J. ; Engert, J.C. ; Gerstein, H.C. ; Mani, K.R. ; Sabanayagam, C. ; Vujkovic, M.R. ; Wickremasinghe, A.R. ; Wong, T.Y. ; Yajnik, C.S. ; Yusuf, S. ; Ahsan, H. ; Bharadwaj, D. ; Anand, S.S. ; Below, J.E. ; Boehnke, M. ; Bowden, D.W. ; Chandak, G.R. ; Cheng, C.Y. ; Kato, N. ; Mahajan, A. ; Sim, X. ; McCarthy, M.I. ; Morris, A.P. ; Kooner, J.S. ; Saleheen, D.
Comm. Biol. 5:441 (2022)
Ruiz Tejada Segura, M.L. ; Abou Moussa, E. ; Garabello, E. ; Nakahara, T.S. ; Makhlouf, M. ; Mathew, L.S. ; Wang, L. ; Valle, F. ; Huang, S.S.Y. ; Mainland, J.D. ; Caselle, M. ; Osella, M. ; Lorenz, S. ; Reisert, J. ; Logan, D.W. ; Malnic, B. ; Scialdone, A. ; Saraiva, L.R.
Cell Rep. 38:110547 (2022)
The sense of smell helps us navigate the environment, but its molecular architecture and underlying logic remain understudied. The spatial location of odorant receptor genes (Olfrs) in the nose is thought to be independent of the structural diversity of the odorants they detect. Using spatial transcriptomics, we create a genome-wide 3D atlas of the mouse olfactory mucosa (OM). Topographic maps of genes differentially expressed in space reveal that both Olfrs and non-Olfrs are distributed in a continuous and overlapping fashion over at least five broad zones in the OM. The spatial locations of Olfrs correlate with the mucus solubility of the odorants they recognize, providing direct evidence for the chromatographic theory of olfaction. This resource resolves the molecular architecture of the mouse OM and will inform future studies on mechanisms underlying Olfr gene choice, axonal pathfinding, patterning of the nervous system, and basic logic for the peripheral representation of smell.
Wissenschaftlicher Artikel
Scientific Article
Günsel, G.G. ; Conlon, T.M. ; Jeridi, A. ; Kim, R. ; Ertüz, Z. ; Lang, N.J. ; Ansari, M. ; Novikova, M. ; Jiang, D. ; Strunz, M. ; Gaianova, M. ; Hollauer, C. ; Gabriel, C. ; Angelidis, I. ; Doll, S. ; Pestoni, J. ; Edelmann, S.L. ; Kohlhepp, M.S. ; Guillot, A. ; Bassler, K. ; Van Eeckhoutte, H.P. ; Kayalar, Ö. ; Konyalilar, N. ; Kanashova, T. ; Rodius, S. ; Ballester-Lopez, C. ; Genes Robles, C.M. ; Smirnova, N.F. ; Rehberg, M. ; Agarwal, C. ; Krikki, I. ; Piavaux, B. ; Verleden, S.E. ; Vanaudenaerde, B. ; Königshoff, M. ; Dittmar, G. ; Bracke, K.R. ; Schultze, J.L. ; Watz, H. ; Eickelberg, O. ; Stöger, T. ; Burgstaller, G. ; Tacke, F. ; Heissmeyer, V. ; Rinkevich, Y. ; Bayram, H. ; Schiller, H. B. ; Conrad, M. ; Schneider, R. ; Yildirim, A.Ö.
Nat. Commun. 13:1303 (2022)
Extravasation of monocytes into tissue and to the site of injury is a fundamental immunological process, which requires rapid responses via post translational modifications (PTM) of proteins. Protein arginine methyltransferase 7 (PRMT7) is an epigenetic factor that has the capacity to mono-methylate histones on arginine residues. Here we show that in chronic obstructive pulmonary disease (COPD) patients, PRMT7 expression is elevated in the lung tissue and localized to the macrophages. In mouse models of COPD, lung fibrosis and skin injury, reduced expression of PRMT7 associates with decreased recruitment of monocytes to the site of injury and hence less severe symptoms. Mechanistically, activation of NF-κB/RelA in monocytes induces PRMT7 transcription and consequential mono-methylation of histones at the regulatory elements of RAP1A, which leads to increased transcription of this gene that is responsible for adhesion and migration of monocytes. Persistent monocyte-derived macrophage accumulation leads to ALOX5 over-expression and accumulation of its metabolite LTB4, which triggers expression of ACSL4 a ferroptosis promoting gene in lung epithelial cells. Conclusively, inhibition of arginine mono-methylation might offer targeted intervention in monocyte-driven inflammatory conditions that lead to extensive tissue damage if left untreated.
Wissenschaftlicher Artikel
Scientific Article
Brunner, A.D. ; Thielert, M. ; Vasilopoulou, C.G. ; Ammar, C. ; Coscia, F. ; Mund, A. ; Hoerning, O.B. ; Bache, N. ; Apalategui, A. ; Lubeck, M. ; Richter, S. ; Fischer, D.S. ; Raether, O. ; Park, M.A. ; Meier, F. ; Theis, F.J. ; Mann, M.
Mol. Syst. Biol. 18:e10798 (2022)
Single-cell technologies are revolutionizing biology but are today mainly limited to imaging and deep sequencing. However, proteins are the main drivers of cellular function and in-depth characterization of individual cells by mass spectrometry (MS)-based proteomics would thus be highly valuable and complementary. Here, we develop a robust workflow combining miniaturized sample preparation, very low flow-rate chromatography, and a novel trapped ion mobility mass spectrometer, resulting in a more than 10-fold improved sensitivity. We precisely and robustly quantify proteomes and their changes in single, FACS-isolated cells. Arresting cells at defined stages of the cell cycle by drug treatment retrieves expected key regulators. Furthermore, it highlights potential novel ones and allows cell phase prediction. Comparing the variability in more than 430 single-cell proteomes to transcriptome data revealed a stable-core proteome despite perturbation, while the transcriptome appears stochastic. Our technology can readily be applied to ultra-high sensitivity analyses of tissue material, posttranslational modifications, and small molecule studies from small cell counts to gain unprecedented insights into cellular heterogeneity in health and disease.
Wissenschaftlicher Artikel
Scientific Article
Giehrl-Schwab, J. ; Giesert, F. ; Rauser, B. ; Lao, C.L. ; Hembach, S. ; Lefort, S. ; Ibarra Del Rio, I.A. ; Koupourtidou; C. ; Luecken, M. ; Truong, D.-J.J. ; Fischer-Sternjak, J. ; Masserdotti, G. ; Prakash, N. ; Ninkovic, J. ; Hölter, S.M. ; Vogt Weisenhorn, D.M. ; Theis, F.J. ; Götz, M. ; Wurst, W.
EMBO Mol. Med.:e14797 (2022)
Direct reprogramming based on genetic factors resembles a promising strategy to replace lost cells in degenerative diseases such as Parkinson's disease. For this, we developed a knock-in mouse line carrying a dual dCas9 transactivator system (dCAM) allowing the conditional in vivo activation of endogenous genes. To enable a translational application, we additionally established an AAV-based strategy carrying intein-split-dCas9 in combination with activators (AAV-dCAS). Both approaches were successful in reprogramming striatal astrocytes into induced GABAergic neurons confirmed by single-cell transcriptome analysis of reprogrammed neurons in vivo. These GABAergic neurons functionally integrate into striatal circuits, alleviating voluntary motor behavior aspects in a 6-OHDA Parkinson's disease model. Our results suggest a novel intervention strategy beyond the restoration of dopamine levels. Thus, the AAV-dCAS approach might enable an alternative route for clinical therapies of Parkinson's disease.
Wissenschaftlicher Artikel
Scientific Article
Yépez, V.A. ; Gusic, M. ; Kopajtich, R. ; Mertes, C. ; Smith, N.H. ; Alston, C.L. ; Ban, R. ; Beblo, S. ; Berutti, R. ; Blessing, H. ; Ciara, E. ; Distelmaier, F. ; Freisinger, P. ; Häberle, J. ; Hayflick, S.J. ; Hempel, M. ; Itkis, Y.S. ; Kishita, Y. ; Klopstock, T. ; Krylova, T.D. ; Lamperti, C. ; Lenz, D. ; Makowski, C. ; Mosegaard, S. ; Müller, M.F. ; Muñoz-Pujol, G. ; Nadel, A. ; Ohtake, A. ; Okazaki, Y. ; Procopio, E. ; Schwarzmayr, T. ; Smet, J. ; Staufner, C. ; Stenton, S. ; Strom, T.-M. ; Terrile, C. ; Tort, F. ; van Coster, R. ; Vanlander, A. ; Wagner, M. ; Xu, M. ; Fang, F. ; Ghezzi, D. ; Mayr, J.A. ; Piekutowska-Abramczuk, D. ; Ribes, A. ; Rötig, A. ; Taylor, R.W. ; Wortmann, S.B. ; Murayama, K. ; Meitinger, T. ; Gagneur, J. ; Prokisch, H.
Genome Med. 14:38 (2022)
BACKGROUND: Lack of functional evidence hampers variant interpretation, leaving a large proportion of individuals with a suspected Mendelian disorder without genetic diagnosis after whole genome or whole exome sequencing (WES). Research studies advocate to further sequence transcriptomes to directly and systematically probe gene expression defects. However, collection of additional biopsies and establishment of lab workflows, analytical pipelines, and defined concepts in clinical interpretation of aberrant gene expression are still needed for adopting RNA sequencing (RNA-seq) in routine diagnostics. METHODS: We implemented an automated RNA-seq protocol and a computational workflow with which we analyzed skin fibroblasts of 303 individuals with a suspected mitochondrial disease that previously underwent WES. We also assessed through simulations how aberrant expression and mono-allelic expression tests depend on RNA-seq coverage. RESULTS: We detected on average 12,500 genes per sample including around 60% of all disease genes-a coverage substantially higher than with whole blood, supporting the use of skin biopsies. We prioritized genes demonstrating aberrant expression, aberrant splicing, or mono-allelic expression. The pipeline required less than 1 week from sample preparation to result reporting and provided a median of eight disease-associated genes per patient for inspection. A genetic diagnosis was established for 16% of the 205 WES-inconclusive cases. Detection of aberrant expression was a major contributor to diagnosis including instances of 50% reduction, which, together with mono-allelic expression, allowed for the diagnosis of dominant disorders caused by haploinsufficiency. Moreover, calling aberrant splicing and variants from RNA-seq data enabled detecting and validating splice-disrupting variants, of which the majority fell outside WES-covered regions. CONCLUSION: Together, these results show that streamlined experimental and computational processes can accelerate the implementation of RNA-seq in routine diagnostics.
Wissenschaftlicher Artikel
Scientific Article
Iturbide Martinez De Albeniz, A. ; Ruiz Tejada Segura, M.L. ; Noll, C. ; Schorpp, K.K. ; Rothenaigner, I. ; Lubatti, G. ; Agami, A. ; Hadian, K. ; Scialdone, A. ; Torres-Padilla, M.E.
Nat. Struct. Mol. Biol. 29:282 (2022)
In the version of this article initially published, the surname of author Mayra L. Ruiz Tejada Segura was misspelled as Ruiz Tejeda Segura. The error has been corrected in the online version of the article.
Nakatani, T. ; Lin, J. ; Ji, F. ; Ettinger, A. ; Pontabry, J. ; Tokoro, M. ; Altamirano-Pacheco, L. ; Fiorentino, J. ; Mahammadov, E. ; Hatano, Y. ; Van Rechem, C. ; Chakraborty, D. ; Ruiz-Morales, E.R. ; Scialdone, A. ; Yamagata, K. ; Whetstine, J.R. ; Sadreyev, R.I. ; Torres-Padilla, M.E.
Nat. Genet. 54, 318–327 (2022)
Totipotency emerges in early embryogenesis, but its molecular underpinnings remain poorly characterized. In the present study, we employed DNA fiber analysis to investigate how pluripotent stem cells are reprogrammed into totipotent-like 2-cell-like cells (2CLCs). We show that totipotent cells of the early mouse embryo have slow DNA replication fork speed and that 2CLCs recapitulate this feature, suggesting that fork speed underlies the transition to a totipotent-like state. 2CLCs emerge concomitant with DNA replication and display changes in replication timing (RT), particularly during the early S-phase. RT changes occur prior to 2CLC emergence, suggesting that RT may predispose to gene expression changes and consequent reprogramming of cell fate. Slowing down replication fork speed experimentally induces 2CLCs. In vivo, slowing fork speed improves the reprogramming efficiency of somatic cell nuclear transfer. Our data suggest that fork speed regulates cellular plasticity and that remodeling of replication features leads to changes in cell fate and reprogramming.
Wissenschaftlicher Artikel
Scientific Article
Gayoso, A. ; Lopez, R. ; Xing, G. ; Boyeau, P. ; Valiollah Pour Amiri, V. ; Hong, J. ; Wu, K. ; Jayasuriya, M. ; Mehlman, E. ; Langevin, M. ; Liu, Y. ; Samaran, J. ; Misrachi, G. ; Nazaret, A. ; Clivio, O. ; Xu, C. ; Ashuach, T. ; Gabitto, M. ; Lotfollahi, M. ; Svensson, V. ; da Veiga Beltrame, E. ; Kleshchevnikov, V. ; Talavera-López, C. ; Pachter, L. ; Theis, F.J. ; Streets, A. ; Jordan, M.I. ; Regier, J. ; Yosef, N.
Nat. Biotechnol. 40, 163-166 (2022)
Letter to the Editor
Letter to the Editor
Palla, G. ; Spitzer, H. ; Klein, M. ; Fischer, D.S. ; Schaar, A. ; Kuemmerle, L. ; Rybakov, S. ; Ibarra Del Rio, I.A. ; Holmberg, O. ; Virshup, I. ; Lotfollahi, M. ; Richter, S. ; Theis, F.J.
Nat. Methods 19, 171–178 (2022)
Spatial omics data are advancing the study of tissue organization and cellular communication at an unprecedented scale. Flexible tools are required to store, integrate and visualize the large diversity of spatial omics data. Here, we present Squidpy, a Python framework that brings together tools from omics and image analysis to enable scalable description of spatial molecular data, such as transcriptome or multivariate proteins. Squidpy provides efficient infrastructure and numerous analysis methods that allow to efficiently store, manipulate and interactively visualize spatial omics data. Squidpy is extensible and can be interfaced with a variety of already existing libraries for the scalable analysis of spatial omics data.
Wissenschaftlicher Artikel
Scientific Article
Romer, P. ; Filbir, F. ; Krahmer, F.
In: (55th Asilomar Conference on Signals, Systems and Computers, ACSSC 2021, 31 October - 3 November 2021, Virtual, Pacific Grov). 2022. 847-851 ( ; 2021-October)
We investigate a variant of the randomized Kaczmarz algorithm as a method for solving the phase retrieval problem. The main contribution of this paper is a recovery guarantee for phase retrieval from measurements perturbed with additive noise via the randomized Kaczmarz algorithm. We consider the scenario that the measurement vectors are drawn independently and uniformly at random from the unit sphere and that the number of measurements is a sufficiently large multiple of the dimension. We show that, with high probability, the randomized Kaczmarz algorithm converges to a neighborhood around the ground-truth solution whose radius depends on the noise level.
Offer, S. ; Hartner, E. ; Di Bucchianico, S. ; Bisig, B. ; Bauer, S. ; Pantzke, J. ; Zimmermann, E. ; Cao, X. ; Binder, S. ; Kuhn, E. ; Huber, A. ; Jeong, S. ; Käfer, U. ; Martens, P. ; Mesceriakovas, A. ; Bendl, J. ; Brejcha, R. ; Buchholz, A. ; Gat, D. ; Hohaus, T. ; Rastak, N. ; Jakobi, G. ; Kalberer, M. ; Kanashova, T. ; Hu, Y. ; Ogris, C. ; Marsico, A. ; Theis, F.J. ; Pardo, M. ; Gröger, T.M. ; Oeder, S. ; Orasche, J. ; Paul, A. ; Ziehm, T. ; Zhang, Z.H. ; Adam, T. ; Sippula, O. ; Sklorz, M. ; Schnelle-Kreis, J. ; Czech, H. ; Kiendler-Scharr, A. ; Rudich, Y. ; Zimmermann, R.
Environ. Health Perspect. 130:27003 (2022)
BACKGROUND: Secondary organic aerosols (SOAs) formed from anthropogenic or biogenic gaseous precursors in the atmosphere substantially contribute to the ambient fine particulate matter [PM ≤2.5μm in aerodynamic diameter (PM2.5)] burden, which has been associated with adverse human health effects. However, there is only limited evidence on their differential toxicological impact. OBJECTIVES: We aimed to discriminate toxicological effects of aerosols generated by atmospheric aging on combustion soot particles (SPs) of gaseous biogenic (β-pinene) or anthropogenic (naphthalene) precursors in two different lung cell models exposed at the air-liquid interface (ALI). METHODS: Mono- or cocultures of lung epithelial cells (A549) and endothelial cells (EA.hy926) were exposed at the ALI for 4 h to different aerosol concentrations of a photochemically aged mixture of primary combustion SP and β-pinene (SOAβPIN-SP) or naphthalene (SOANAP-SP). The internally mixed soot/SOA particles were comprehensively characterized in terms of their physical and chemical properties. We conducted toxicity tests to determine cytotoxicity, intracellular oxidative stress, primary and secondary genotoxicity, as well as inflammatory and angiogenic effects. RESULTS: We observed considerable toxicity-related outcomes in cells treated with either SOA type. Greater adverse effects were measured for SOANAP-SP compared with SOAβPIN-SP in both cell models, whereas the nano-sized soot cores alone showed only minor effects. At the functional level, we found that SOANAP-SP augmented the secretion of malondialdehyde and interleukin-8 and may have induced the activation of endothelial cells in the coculture system. This activation was confirmed by comet assay, suggesting secondary genotoxicity and greater angiogenic potential. Chemical characterization of PM revealed distinct qualitative differences in the composition of the two secondary aerosol types. DISCUSSION: In this study using A549 and EA.hy926 cells exposed at ALI, SOA compounds had greater toxicity than primary SPs. Photochemical aging of naphthalene was associated with the formation of more oxidized, more aromatic SOAs with a higher oxidative potential and toxicity compared with β-pinene. Thus, we conclude that the influence of atmospheric chemistry on the chemical PM composition plays a crucial role for the adverse health outcome of emissions. https://doi.org/10.1289/EHP9413.
Wissenschaftlicher Artikel
Scientific Article
Grech, V. ; Scherb, H.
Med. Princ. Pract. 31, 83-87 (2022)
OBJECTIVE: In humans, males are born slightly in excess of females. Many factors have been shown to affect this ratio, including stressful events such as terrorist attacks. Two shootings occurred in early August 2019 in the Oregon District in Dayton, Montgomery County, Ohio, and in El Paso County, Texas, in the USA. This study was carried out in order to identify whether there were any effects on sex ratio at birth at the state or county level 3-5 months later. SUBJECT AND METHODS: Births by sex, month of birth (2015-2019), and county were obtained for Ohio and Texas from the website of the Centers for Disease Control and Prevention. Ordinary linear logistic regression was used to assess the time trend in the probability of boys and to investigate changes in the trend functions. Poisson regression (SAS GENMOD) and linear logistic regression using SAS procedure LOGISTIC was applied. RESULTS: This study analyzed 2,623,714 live births, 1,939,938 in Texas (sex odds [SO] 1.044) and 683,776 in Ohio (SO 1.045). The only significant effect noted was seasonality (month) at the state level. CONCLUSION: It has been postulated that male fetal loss in pregnant women during stressful periods may occur in accordance with the Trivers-Willard hypothesis. Several studies have found significant effects after terrorist attacks in the USA (as well as in other countries), but this study did not reveal such effects. This may be due to several reasons including underpowered datasets and the possibility that populations may be becoming relatively immured to these events.
Wissenschaftlicher Artikel
Scientific Article
Wörheide, M. ; Krumsiek, J. ; Kastenmüller, G. ; Kaddurah-Daouk, R.F. ; Arnold, M.
Alzheimers Dement. 17, 3:e056673 (2022)
BACKGROUND: Alzheimer's disease (AD) is a devastating neurodegenerative disorder for which there currently are no disease-modifying treatments available. To accelerate the path to effective intervention strategies, drug repositioning - the application of available compounds in a novel disease context - has gained increasing attention as a promising alternative to de novo drug development. Rich multi-omics data, generated by large international and interdisciplinary AD consortia, is now enabling the implementation of novel methods that have the potential to drive the computational identification and prioritization of promising repositioning candidates. METHOD: We recently developed the AD atlas, a web-based multi-omics resource that integrates multiple layers of heterogenous data from different studies and cohorts, including omics QTLs, transcriptomic, proteomic and metabolomic correlation networks, as well as genetic and multi-omics associations with AD and associated biomarkers/endophenotypes. Using this atlas, we generated and analyzed molecular context networks surrounding AD-associated genes as well as those targeted by drug repositioning candidates proposed in the literature. Subsequent enrichment analysis on AD subnetworks was used to identify drugs with overlapping molecular signatures on the gene expression level, while target networks of repositioning candidates were investigated for their potential involvement in AD pathogenesis. RESULT: We found ample evidence for the potential of integrative multi-omics approaches for drug repositioning in AD. For instance, enrichment analysis of the context network surrounding the AD-associated genes APOE and CLU identified multiple repositioning candidates, where the top hits were drugs that were either previously proposed as promising or already subjected to clinical trials, such as fluoxetine, rosiglitazone, and valproate. Investigating candidate drugs, the exploration of the context network targeted by statins revealed functional links to TYROBP/TREM2 signaling, suggesting a potential protective effect of this drug class through modulation of neuroinflammatory pathways. CONCLUSION: Our results highlight multiple opportunities to advance drug repositioning efforts in AD by integrative analysis of comprehensive multi-omics data. Automation of our analyses using network-based machine learning approaches and extension of the AD atlas with multi-omics data from drug screens to resolve directionalities will allow us to globally identify molecular pathways disturbed in AD that are targetable by drug repositioning candidates.
Meeting abstract
Meeting abstract
Palla, G. ; Fischer, D.S. ; Regev, A. ; Theis, F.J.
Nat. Biotechnol. 40, 308–318 (2022)
Methods for profiling RNA and protein expression in a spatially resolved manner are rapidly evolving, making it possible to comprehensively characterize cells and tissues in health and disease. To maximize the biological insights obtained using these techniques, it is critical to both clearly articulate the key biological questions in spatial analysis of tissues and develop the requisite computational tools to address them. Developers of analytical tools need to decide on the intrinsic molecular features of each cell that need to be considered, and how cell shape and morphological features are incorporated into the analysis. Also, optimal ways to compare different tissue samples at various length scales are still being sought. Grouping these biological problems and related computational algorithms into classes across length scales, thus characterizing common issues that need to be addressed, will facilitate further progress in spatial transcriptomics and proteomics.
Review
Review
Caldi Gomes, L. ; Galhoz, A. ; Jain, G. ; Roser, A.E. ; Maass, F. ; Carboni, E. ; Barski, E. ; Lenz, C. ; Lohmann, K. ; Klein, C. ; Bähr, M. ; Fischer, A. ; Menden, M. ; Lingor, P.
Clin. Transl. Med. 12:e692 (2022)
BACKGROUND: Parkinson's disease (PD) is the second most common neurodegenerative disorder whose prevalence is rapidly increasing worldwide. The molecular mechanisms underpinning the pathophysiology of sporadic PD remain incompletely understood. Therefore, causative therapies are still elusive. To obtain a more integrative view of disease-mediated alterations, we investigated the molecular landscape of PD in human post-mortem midbrains, a region that is highly affected during the disease process. METHODS: Tissue from 19 PD patients and 12 controls were obtained from the Parkinson's UK Brain Bank and subjected to multi-omic analyses: small and total RNA sequencing was performed on an Illumina's HiSeq4000, while proteomics experiments were performed in a hybrid triple quadrupole-time of flight mass spectrometer (TripleTOF5600+) following quantitative sequential window acquisition of all theoretical mass spectra. Differential expression analyses were performed with customized frameworks based on DESeq2 (for RNA sequencing) and with Perseus v.1.5.6.0 (for proteomics). Custom pipelines in R were used for integrative studies. RESULTS: Our analyses revealed multiple deregulated molecular targets linked to known disease mechanisms in PD as well as to novel processes. We have identified and experimentally validated (quantitative real-time polymerase chain reaction/western blotting) several PD-deregulated molecular candidates, including miR-539-3p, miR-376a-5p, miR-218-5p and miR-369-3p, the valid miRNA-mRNA interacting pairs miR-218-5p/RAB6C and miR-369-3p/GTF2H3, as well as multiple proteins, such as CHI3L1, HSPA1B, FNIP2 and TH. Vertical integration of multi-omic analyses allowed validating disease-mediated alterations across different molecular layers. Next to the identification of individual molecular targets in all explored omics layers, functional annotation of differentially expressed molecules showed an enrichment of pathways related to neuroinflammation, mitochondrial dysfunction and defects in synaptic function. CONCLUSIONS: This comprehensive assessment of PD-affected and control human midbrains revealed multiple molecular targets and networks that are relevant to the disease mechanism of advanced PD. The integrative analyses of multiple omics layers underscore the importance of neuroinflammation, immune response activation, mitochondrial and synaptic dysfunction as putative therapeutic targets for advanced PD.
Wissenschaftlicher Artikel
Scientific Article
Luecken, M. ; Zaragosi, L.E. ; Madissoon, E. ; Sikkema, L. ; Firsova, A.B. ; De Domenico, E. ; Kuemmerle, L. ; Saglam, A. ; Berg, M. ; Gay, A.C.A. ; Schniering, J. ; Mayr, C. ; Abalo, X.M. ; Larsson, L. ; Sountoulidis, A. ; Teichmann, S. ; van Eunen, K. ; Koppelman, G.H. ; Saeb-Parsy, K. ; Leroy, S. ; Powell, P. ; Sarkans, U. ; Timens, W. ; Lundeberg, J. ; van den Berge, M. ; Nilsson, M. ; Horváth, P. ; Denning, J. ; Papatheodorou, I. ; Schultze, J.L. ; Schiller, H. B. ; Barbry, P. ; Petoukhov, I. ; Misharin, A.V. ; Adcock, I. ; von Papen, M. ; Theis, F.J. ; Samakovlis, C. ; Meyer, K.B. ; Nawijn, M.C.
Eur. Respir. J. 59:2102057 (2022)
The Human Cell Atlas (HCA) consortium aims to establish an atlas of all organs in the healthy human body at single-cell resolution to increase our understanding of basic biological processes that govern development, physiology and anatomy, and to accelerate diagnosis and treatment of disease. The lung biological network of the HCA aims to generate the Human Lung Cell Atlas as a reference for the cellular repertoire, molecular cell states and phenotypes, and the cell-cell interactions that characterise normal lung homeostasis in healthy lung tissue. Such a reference atlas of the healthy human lung will facilitate mapping the changes in the cellular landscape in disease. The discovAIR project is one of six pilot actions for the HCA funded by the European Commission in the context of the H2020 framework program. DiscovAIR aims to establish the first draft of an integrated Human Lung Cell Atlas, combining single-cell transcriptional and epigenetic profiling with spatially resolving techniques on matched tissue samples, as well as including a number of chronic and infectious diseases of the lung. The integrated Lung Cell Atlas will be available as a resource for the wider respiratory community, including basic and translational scientists, clinical medicine, and the private sector, as well as for patients with lung disease and the interested lay public. We anticipate that the Lung Cell Atlas will be the founding stone for a more detailed understanding of the pathogenesis of lung diseases, guiding the design of novel diagnostics and preventive or curative interventions.
Review
Review
Hawe, J. ; Wilson, R. ; Schmid, K. ; Zhou, L. ; Lakshmanan, L.N. ; Lehne, B.C. ; Kühnel, B. ; Scott, W.R. ; Wielscher, M. ; Yew, Y.W. ; Baumbach, C. ; Lee, D.P. ; Marouli, E. ; Bernard, M. ; Pfeiffer, L. ; Matias-Garcia, P.R. ; Autio, M.I. ; Bourgeois, S. ; Herder, C. ; Karhunen, V. ; Meitinger, T. ; Prokisch, H. ; Rathmann, W. ; Roden, M. ; Sebert, S. ; Shin, J. ; Strauch, K. ; Zhang, W. ; Tan, W.L.W. ; Hauck, S.M. ; Merl-Pham, J. ; Grallert, H. ; Barbosa, E.G.V. ; Illig, T. ; Peters, A. ; Paus, T. ; Pausova, Z. ; Deloukas, P. ; Foo, R.S.Y. ; Jarvelin, M.R. ; Kooner, J.S. ; Loh, M. ; Heinig, M. ; Gieger, C. ; Waldenberger, M. ; Chambers, J.C.
Nat. Genet. 54, 18–29 (2022)
We determined the relationships between DNA sequence variation and DNA methylation using blood samples from 3,799 Europeans and 3,195 South Asians. We identify 11,165,559 SNP-CpG associations (methylation quantitative trait loci (meQTL), P < 10-14), including 467,915 meQTL that operate in trans. The meQTL are enriched for functionally relevant characteristics, including shared chromatin state, High-throuhgput chromosome conformation interaction, and association with gene expression, metabolic variation and clinical traits. We use molecular interaction and colocalization analyses to identify multiple nuclear regulatory pathways linking meQTL loci to phenotypic variation, including UBASH3B (body mass index), NFKBIE (rheumatoid arthritis), MGA (blood pressure) and COMMD7 (white cell counts). For rs6511961 , chromatin immunoprecipitation followed by sequencing (ChIP-seq) validates zinc finger protein (ZNF)333 as the likely trans acting effector protein. Finally, we used interaction analyses to identify population- and lineage-specific meQTL, including rs174548 in FADS1, with the strongest effect in CD8+ T cells, thus linking fatty acid metabolism with immune dysregulation and asthma. Our study advances understanding of the potential pathways linking genetic variation to human phenotype.
Wissenschaftlicher Artikel
Scientific Article
Lange, M. ; Bergen, V. ; Klein, M. ; Setty, M. ; Reuter, B. ; Bakhti, M. ; Lickert, H. ; Ansari, M. ; Schniering, J. ; Schiller, H. B. ; Pe'er, D. ; Theis, F.J.
Nat. Methods 19, 159–170 (2022)
Computational trajectory inference enables the reconstruction of cell state dynamics from single-cell RNA sequencing experiments. However, trajectory inference requires that the direction of a biological process is known, largely limiting its application to differentiating systems in normal development. Here, we present CellRank ( https://cellrank.org ) for single-cell fate mapping in diverse scenarios, including regeneration, reprogramming and disease, for which direction is unknown. Our approach combines the robustness of trajectory inference with directional information from RNA velocity, taking into account the gradual and stochastic nature of cellular fate decisions, as well as uncertainty in velocity vectors. On pancreas development data, CellRank automatically detects initial, intermediate and terminal populations, predicts fate potentials and visualizes continuous gene expression trends along individual lineages. Applied to lineage-traced cellular reprogramming data, predicted fate probabilities correctly recover reprogramming outcomes. CellRank also predicts a new dedifferentiation trajectory during postinjury lung regeneration, including previously unknown intermediate cell states, which we confirm experimentally.
Wissenschaftlicher Artikel
Scientific Article
Magaletta, M.E. ; Lobo, M. ; Kernfeld, E.M. ; Aliee, H. ; Huey, J.D. ; Parsons, T.J. ; Theis, F.J. ; Maehr, R.
Nat. Commun. 13:457 (2022)
Maldevelopment of the pharyngeal endoderm, an embryonic tissue critical for patterning of the pharyngeal region and ensuing organogenesis, ultimately contributes to several classes of human developmental syndromes and disorders. Such syndromes are characterized by a spectrum of phenotypes that currently cannot be fully explained by known mutations or genetic variants due to gaps in characterization of critical drivers of normal and dysfunctional development. Despite the disease-relevance of pharyngeal endoderm, we still lack a comprehensive and integrative view of the molecular basis and gene regulatory networks driving pharyngeal endoderm development. To close this gap, we apply transcriptomic and chromatin accessibility single-cell sequencing technologies to generate a multi-omic developmental resource spanning pharyngeal endoderm patterning to the emergence of organ-specific epithelia in the developing mouse embryo. We identify cell-type specific gene regulation, distill GRN models that define developing organ domains, and characterize the role of an immunodeficiency-associated forkhead box transcription factor.
Wissenschaftlicher Artikel
Scientific Article
Assum, I. ; Krause, J. ; Scheinhardt, M.O. ; Müller, C. ; Hammer, E. ; Börschel, C.S. ; Völker, U. ; Conradi, L. ; Geelhoed, B. ; Zeller, T. ; Schnabel, R.B. ; Heinig, M.
Nat. Commun. 13:441 (2022)
Genome-wide association studies (GWAS) for atrial fibrillation (AF) have uncovered numerous disease-associated variants. Their underlying molecular mechanisms, especially consequences for mRNA and protein expression remain largely elusive. Thus, refined multi-omics approaches are needed for deciphering the underlying molecular networks. Here, we integrate genomics, transcriptomics, and proteomics of human atrial tissue in a cross-sectional study to identify widespread effects of genetic variants on both transcript (cis-eQTL) and protein (cis-pQTL) abundance. We further establish a novel targeted trans-QTL approach based on polygenic risk scores to determine candidates for AF core genes. Using this approach, we identify two trans-eQTLs and five trans-pQTLs for AF GWAS hits, and elucidate the role of the transcription factor NKX2-5 as a link between the GWAS SNP rs9481842 and AF. Altogether, we present an integrative multi-omics method to uncover trans-acting networks in small datasets and provide a rich resource of atrial tissue-specific regulatory variants for transcript and protein levels for cardiovascular disease gene prioritization.
Wissenschaftlicher Artikel
Scientific Article
Wang, T. ; Huynh, K. ; Giles, C. ; Mellett, N.A. ; Duong, T. ; Nguyen, A. ; Lim, W.L.F. ; Smith, A.A.T. ; Olshansky, G. ; Cadby, G. ; Hung, J. ; Hui, J. ; Beilby, J. ; Watts, G.F. ; Chatterjee, P. ; Martins, I. ; Laws, S.M. ; Bush, A.I. ; Rowe, C.C. ; Villemagne, V.L. ; Ames, D. ; Masters, C.L. ; Taddei, K. ; Doré, V. ; Fripp, J. ; Arnold, M. ; Kastenmüller, G. ; Nho, K. ; Saykin, A.J. ; Baillie, R. ; Han, X. ; Martins, R.N. ; Moses, E.K. ; Kaddurah-Daouk, R. ; Meikle, P.J.
Alzheimers Dement., DOI: 10.1002/alz.12538 (2022)
Introduction: The apolipoprotein E (APOE) genotype is the strongest genetic risk factor for late-onset Alzheimer's disease. However, its effect on lipid metabolic pathways, and their mediating effect on disease risk, is poorly understood. Methods: We performed lipidomic analysis on three independent cohorts (the Australian Imaging, Biomarkers and Lifestyle [AIBL] flagship study, n = 1087; the Alzheimer's Disease Neuroimaging Initiative [ADNI] 1 study, n = 819; and the Busselton Health Study [BHS], n = 4384), and we defined associations between APOE ε2 and ε4 and 569 plasma/serum lipid species. Mediation analysis defined the proportion of the treatment effect of the APOE genotype mediated by plasma/serum lipid species. Results: A total of 237 and 104 lipid species were associated with APOE ε2 and ε4, respectively. Of these 68 (ε2) and 24 (ε4) were associated with prevalent Alzheimer's disease. Individual lipid species or lipidomic models of APOE genotypes mediated up to 30% and 10% of APOE ε2 and ε4 treatment effect, respectively. Discussion: Plasma lipid species mediate the treatment effect of APOE genotypes on Alzheimer's disease and as such represent a potential therapeutic target.
Wissenschaftlicher Artikel
Scientific Article
Ringeling, F.R. ; Chakraborty, S. ; Vissers, C. ; Reiman, D. ; Patel, A.M. ; Lee, K.H. ; Hong, A. ; Park, C.W. ; Reska, T. ; Gagneur, J. ; Chang, H. ; Spletter, M.L. ; Yoon, K.J. ; Ming, G.l. ; Song, H. ; Canzar, S.
Nat. Biotechnol. 40, 741–750 (2022)
The accuracy of methods for assembling transcripts from short-read RNA sequencing data is limited by the lack of long-range information. Here we introduce Ladder-seq, an approach that separates transcripts according to their lengths before sequencing and uses the additional information to improve the quantification and assembly of transcripts. Using simulated data, we show that a kallisto algorithm extended to process Ladder-seq data quantifies transcripts of complex genes with substantially higher accuracy than conventional kallisto. For reference-based assembly, a tailored scheme based on the StringTie2 algorithm reconstructs a single transcript with 30.8% higher precision than its conventional counterpart and is more than 30% more sensitive for complex genes. For de novo assembly, a similar scheme based on the Trinity algorithm correctly assembles 78% more transcripts than conventional Trinity while improving precision by 78%. In experimental data, Ladder-seq reveals 40% more genes harboring isoform switches compared to conventional RNA sequencing and unveils widespread changes in isoform usage upon m6A depletion by Mettl14 knockout.
Wissenschaftlicher Artikel
Scientific Article
Stapor, P. ; Schmiester, L. ; Wierling, C. ; Merkt, S. ; Pathirana, D. ; Lange, B.M.H. ; Weindl, D. ; Hasenauer, J.
Nat. Commun. 13:34 (2022)
Quantitative dynamic models are widely used to study cellular signal processing. A critical step in modelling is the estimation of unknown model parameters from experimental data. As model sizes and datasets are steadily growing, established parameter optimization approaches for mechanistic models become computationally extremely challenging. Mini-batch optimization methods, as employed in deep learning, have better scaling properties. In this work, we adapt, apply, and benchmark mini-batch optimization for ordinary differential equation (ODE) models, thereby establishing a direct link between dynamic modelling and machine learning. On our main application example, a large-scale model of cancer signaling, we benchmark mini-batch optimization against established methods, achieving better optimization results and reducing computation by more than an order of magnitude. We expect that our work will serve as a first step towards mini-batch optimization tailored to ODE models and enable modelling of even larger and more complex systems than what is currently possible.
Wissenschaftlicher Artikel
Scientific Article
Sherman, E. ; Alejo, D. ; Wood-Doughty, Z. ; Sussman, M. ; Schena, S. ; Ong, C.S. ; Etchill, E. ; Dinatale, J. ; Ahmidi, N. ; Shpitser, I. ; Whitman, G.
Ann. Thorac. Surg., DOI: 10.1016/j.athoracsur.2021.11.011 (2022)
Background: Hospital readmission within 30 days of discharge is a well-studied outcome. Predicting readmission after cardiac surgery, however, is notoriously challenging; the best-performing models in the literature have areas under the curve around .65. A reliable predictive model would enable clinicians to identify patients at risk for readmission and to develop prevention strategies. Methods: We analyzed The Society of Thoracic Surgeons (STS) Adult Cardiac Surgery Database at our institution, augmented with electronic medical record data. Predictors included demographics, preoperative comorbidities, proxies for intraoperative risk, indicators of postoperative complications, and time series-derived variables. We trained several machine learning models, evaluating each on a held-out test set. Results: Our analysis cohort consisted of 4924 cases from 2011 to 2016. Of those, 723 (14.7%) were readmitted within 30 days of discharge. Our models included 141 STS-derived and 24 electronic medical records-derived variables. A random forest model performed best, with test area under the curve 0.76 (95% confidence interval, 0.73 to 0.79). Using exclusively preoperative variables, as in STS calculated risk scores, degraded the area under the curve, to 0.64 (95% confidence interval, 0.60 to 0.68). Key predictors included length of stay (12.5 times more important than the average variable) and whether the patient was discharged to a rehabilitation facility (11.2 times). Conclusions: Our approach, augmenting STS variables with electronic medical records data and using flexible machine learning modeling, yielded state-of-the-art performance for predicting 30-day readmission. Separately, the importance of variables not directly related to inpatient care, such as discharge location, amplifies questions about the efficacy of assessing care quality by readmissions.
Wissenschaftlicher Artikel
Scientific Article
Luecken, M. ; Büttner, M. ; Chaichoompu, K. ; Danese, A. ; Interlandi, M. ; Müller, M.F. ; Strobl, D.C. ; Zappia, L. ; Dugas, M. ; Colomé-Tatché, M. ; Theis, F.J.
Nat. Methods 19, 41-50 (2022)
Single-cell atlases often include samples that span locations, laboratories and conditions, leading to complex, nested batch effects in data. Thus, joint analysis of atlas datasets requires reliable data integration. To guide integration method choice, we benchmarked 68 method and preprocessing combinations on 85 batches of gene expression, chromatin accessibility and simulation data from 23 publications, altogether representing >1.2 million cells distributed in 13 atlas-level integration tasks. We evaluated methods according to scalability, usability and their ability to remove batch effects while retaining biological variation using 14 evaluation metrics. We show that highly variable gene selection improves the performance of data integration methods, whereas scaling pushes methods to prioritize batch removal over conservation of biological variation. Overall, scANVI, Scanorama, scVI and scGen perform well, particularly on complex integration tasks, while single-cell ATAC-sequencing integration performance is strongly affected by choice of feature space. Our freely available Python module and benchmarking pipeline can identify optimal data integration methods for new data, benchmark new methods and improve method development.
Wissenschaftlicher Artikel
Scientific Article
Hrovatin, K. ; Fischer, D.S. ; Theis, F.J.
Mol. Metab. 57:101396 (2022)
Background: Single-cell metabolic studies bring new insights into cellular function, which can often not be captured on other omics layers. Metabolic information has wide applicability, such as for the study of cellular heterogeneity or for the understanding of drug mechanisms and biomarker development. However, metabolic measurements on single-cell level are limited by insufficient scalability and sensitivity, as well as resource intensiveness, and are currently not possible in parallel with measuring transcript state, commonly used to identify cell types. Nevertheless, because omics layers are strongly intertwined, it is possible to make metabolic predictions based on measured data of more easily measurable omics layers together with prior metabolic network knowledge. Scope of review: We summarize the current state of single-cell metabolic measurement and modeling approaches, motivating the use of computational techniques. We review three main classes of computational methods used for prediction of single-cell metabolism: pathway-level analysis, constraint-based modeling, and kinetic modeling. We describe the unique challenges arising when transitioning from bulk to single-cell modeling. Finally, we propose potential model extensions and computational methods that could be leveraged to achieve these goals. Major conclusions: Single-cell metabolic modeling is a rising field that provides a new perspective for understanding cellular functions. The presented modeling approaches vary in terms of input requirements and assumptions, scalability, modeled metabolic layers, and newly gained insights. We believe that the use of prior metabolic knowledge will lead to more robust predictions and will pave the way for mechanistic and interpretable machine-learning models.
Review
Review
Chetnik, K. ; Benedetti, E. ; Gomari, D.P. ; Schweickart, A. ; Batra, R. ; Buyukozkan, M. ; Wang, Z. ; Arnold, M. ; Zierer, J. ; Suhre, K. ; Krumsiek, J.
Bioinformatics 38, 1168-1170 (2022)
This paper presents maplet, an open-source R package for the creation of highly customizable, fully reproducible statistical pipelines for metabolomics data analysis. It builds on the SummarizedExperiment data structure to create a centralized pipeline framework for storing data, analysis steps, results, and visualizations. maplet's key design feature is its modularity, which offers several advantages, such as ensuring code quality through the maintenance of individual functions and promoting collaborative development by removing technical barriers to code contribution. With over 90 functions, the package includes a wide range of functionalities, covering many widely used statistical approaches and data visualization techniques. AVAILABILITY: The maplet package is implemented in R and freely available at https://github.com/krumsieklab/maplet.
Wissenschaftlicher Artikel
Scientific Article
Villaverde, A.F. ; Pathirana, D. ; Fröhlich, F. ; Hasenauer, J. ; Banga, J.R.
Brief. Bioinform. 23:bbab387 (2022)
Ordinary differential equation models are nowadays widely used for the mechanistic description of biological processes and their temporal evolution. These models typically have many unknown and nonmeasurable parameters, which have to be determined by fitting the model to experimental data. In order to perform this task, known as parameter estimation or model calibration, the modeller faces challenges such as poor parameter identifiability, lack of sufficiently informative experimental data and the existence of local minima in the objective function landscape. These issues tend to worsen with larger model sizes, increasing the computational complexity and the number of unknown parameters. An incorrectly calibrated model is problematic because it may result in inaccurate predictions and misleading conclusions. For nonexpert users, there are a large number of potential pitfalls. Here, we provide a protocol that guides the user through all the steps involved in the calibration of dynamic models. We illustrate the methodology with two models and provide all the code required to reproduce the results and perform the same analysis on new models. Our protocol provides practitioners and researchers in biological modelling with a one-stop guide that is at the same time compact and sufficiently comprehensive to cover all aspects of the problem.
Wissenschaftlicher Artikel
Scientific Article
Zacharias, H.U. ; Altenbuchinger, M. ; Schultheiss, U.T. ; Raffler, J. ; Kotsis, F. ; Ghasemi, S. ; Ali, I. ; Kollerits, B. ; Metzger, M. ; Steinbrenner, I. ; Sekula, P. ; Massy, Z.A. ; Combe, C. ; Kalra, P.A. ; Kronenberg, F. ; Stengel, B. ; Eckardt, K.U. ; Köttgen, A. ; Schmid, M. ; Gronwald, W. ; Oefner, P.J.
Am. J. Kidney Dis. 79, 217-230.e1 (2022)
RATIONALE & OBJECTIVE: Stratification of chronic kidney disease (CKD) patients at risk for progressing to end-stage kidney disease (ESKD) requiring kidney replacement therapy (KRT) is important for clinical decision-making and trial enrollment. STUDY DESIGN: Four independent prospective observational cohort studies. SETTING & PARTICIPANTS: The development cohort was comprised of 4,915 CKD patients and three independent validation cohorts were comprised of a total of 3,063. Patients were followed-up for approximately five years. NEW PREDICTORS & ESTABLISHED PREDICTORS: 22 demographic, anthropometric and laboratory variables commonly assessed in CKD patients. OUTCOMES: Progression to ESKD requiring KRT. ANALYTICAL APPROACH: A Least Absolute Shrinkage and Selection Operator (LASSO) Cox proportional hazards model was fit to select laboratory variables that best identified patients at high risk for ESKD. Model discrimination and calibration were assessed and compared against the 4-variable Tangri (T4) risk equation. Both used a resampling approach within the development cohort and in the validation cohorts using cause-specific concordance (C) statistics, net reclassification improvement, and calibration graphs. RESULTS: The newly derived 6-variable (Z6) risk score included serum creatinine, albumin, cystatin C and urea, as well as hemoglobin and the urine albumin-to-creatinine ratio. Based on the resampling approach, Z6 achieved a median C value of 0.909 (95% CI, 0.868-0.937) at two years after the baseline visit, whereas the T4 achieved a median C value of 0.855 (95% CI, 0.799-0.915). In the three independent validation cohorts, Z6 C values were 0.894, 0.921, and 0.891, whereas the T4 C values were 0.882, 0.913, and 0.862. LIMITATIONS: The Z6 was both derived and tested only in White European cohorts. CONCLUSIONS: A new risk equation, based on six routinely available laboratory tests facilitates identification of patients with CKD who are at high risk of progressing to ESKD.
Wissenschaftlicher Artikel
Scientific Article
2021
Hetzel, L. ; Fischer, D.S. ; Günnemann, S. ; Theis, F.J.
Curr. Opin. Syst. Biol. 28:100347 (2021)
Single cell RNA sequencing measures gene expression at an unprecedented resolution and scale and allows the analysis of cellular phenotypes which was not possible before. In this context, graphs occur as a natural representation of the system - both as gene-centric and cell-centric. However, many advances in machine learning on graphs are not yet harnessed in models on single-cell data. Taking the inference of cell types or gene interactions as examples, graph representation learning has a wide applicability to both cell and gene graphs. Recent advances in spatial molecular profiling additionally put graph-learning in the focus of attention due the innate resemblance of spatial information to spatial graphs. We argue that graph embedding techniques have great potential for various applications across single cell biology. Here, we discuss how graph representation learning maps to current models and concepts used in single cell biology and formalise overlaps to developments in graph-based deep learning.
Review
Review
Ostaszewski, M. ; Niarakis, A. ; Mazein, A. ; Kuperstein, I. ; Phair, R. ; Orta-Resendiz, A. ; Singh, V. ; Aghamiri, S.S. ; Acencio, M.L. ; Glaab, E. ; Ruepp, A. ; Fobo, G. ; Montrone, C. ; Brauner, B. ; Frishman, G. ; Monraz Gómez, L.C. ; Somers, J. ; Hoch, M. ; Kumar Gupta, S. ; Scheel, J. ; Borlinghaus, H. ; Czauderna, T. ; Schreiber, F. ; Montagud, A. ; Ponce de Leon, M. ; Funahashi, A. ; Hiki, Y. ; Hiroi, N. ; Yamada, T.G. ; Dräger, A. ; Renz, A. ; Naveez, M. ; Bocskei, Z. ; Messina, F. ; Börnigen, D. ; Fergusson, L. ; Conti, M. ; Rameil, M. ; Nakonecnij, V. ; Vanhoefer, J. ; Schmiester, L. ; Wang, M. ; Ackerman, E.E. ; Shoemaker, J.E. ; Zucker, J. ; Oxford, K. ; Teuton, J. ; Kocakaya, E. ; Summak, G.Y. ; Hanspers, K. ; Kutmon, M. ; Coort, S. ; Eijssen, L. ; Ehrhart, F. ; Rex, D.A.B. ; Slenter, D. ; Martens, M. ; Pham, N. ; Haw, R. ; Jassal, B. ; Matthews, L. ; Orlic-Milacic, M. ; Senff-Ribeiro, A. ; Rothfels, K. ; Shamovsky, V. ; Stephan, R. ; Sevilla, C. ; Varusai, T. ; Ravel, J. ; Fraser, R. ; Ortseifen, V. ; Marchesi, S. ; Gawron, P. ; Smula, E. ; Heirendt, L. ; Satagopam, V. ; Wu, G. ; Riutta, A. ; Golebiewski, M. ; Owen, S. ; Goble, C. ; Hu, X. ; Overall, R.W. ; Maier, D. ; Bauch, A. ; Gyori, B.M. ; Bachman, J.A. ; Vega, C. ; Grouès, V. ; Vázquez, M.J. ; Porras, P. ; Licata, L. ; Iannuccelli, M. ; Sacco, F. ; Nesterova, A. ; Yuryev, A. ; de Waard, A. ; Türei, D. ; Luna, A. ; Babur, O. ; Soliman, S. ; Valdeolivas, A. ; Esteban-Medina, M. ; Peña-Chilet, M. ; Rian, K. ; Helikar, T. ; Puniya, B.L. ; Módos, D. ; Treveil, A. ; Ölbei, M. ; De Meulder, B. ; Ballereau, S. ; Dugourd, A. ; Naldi, A. ; Noël, V. ; Calzone, L. ; Sander, C. ; Demir, E. ; Korcsmáros, T. ; Freeman, T.C. ; Augé, F. ; Beckmann, J.S. ; Hasenauer, J. ; Wolkenhauer, O. ; Willighagen, E.L. ; Pico, A.R. ; Evelo, C.T. ; Gillespie, M.E. ; Stein, L.D. ; Hermjakob, H. ; D'Eustachio, P. ; Saez-Rodriguez, J. ; Dopazo, J. ; Valencia, A. ; Kitano, H. ; Barillot, E. ; Auffray, C. ; Balling, R. ; Schneider, R.
Mol. Syst. Biol. 17:e10851 (2021)
Efendiyev, M.A. ; Muradova, A. ; Muradov, N. ; Zischka, H.
Adv. Math. Sci. Appl. 30, 377-385 (2021)
In this paper, we consider deterministic, continuous, nonlocal models for the mitochondrial permeability transition, i.e. mitochondrial swelling. Based on seminal papers [1], [2], [3], [5] and the book [4], in which ODE-PDE and PDE-PDE local models for the swelling of mitochondria have been considered, we suggest here new nonlocal models for this process. This new nonlocal deterministic continuous model for mitochondrial swelling scenario contains nonlocal diffusion, nonlocal chemotaxis, as well as nonlocal source term. We would like to especially emphasize that some of the new nonlocal models that we consider in this paper do not have local counterparts in the literature.
Wissenschaftlicher Artikel
Scientific Article
Hawe, J.
München, Technische Universität, Fakultät für Informatik, Diss., 2021, 210 S.
We investigated molecular networks to further our understanding of how complex traits arise from genetic and epigenetic factors in humans. To this end, we leveraged genome-wide statistical associations between genetic variants and quantitative molecular traits derived from large-scale human population cohorts. By devising a novel strategy for genomic data integration and applying state-of-the-art network analysis and inference methods we gained novel insights into regulatory patterns underlying genome regulation and complex traits. 
Karollus, A. ; Avsec, Ž. ; Gagneur, J.
PLoS Comput. Biol. 17, e1008982 (2021)
The 5' untranslated region plays a key role in regulating mRNA translation and consequently protein abundance. Therefore, accurate modeling of 5'UTR regulatory sequences shall provide insights into translational control mechanisms and help interpret genetic variants. Recently, a model was trained on a massively parallel reporter assay to predict mean ribosome load (MRL)-a proxy for translation rate-directly from 5'UTR sequence with a high degree of accuracy. However, this model is restricted to sequence lengths investigated in the reporter assay and therefore cannot be applied to the majority of human sequences without a substantial loss of information. Here, we introduced frame pooling, a novel neural network operation that enabled the development of an MRL prediction model for 5'UTRs of any length. Our model shows state-of-the-art performance on fixed length randomized sequences, while offering better generalization performance on longer sequences and on a variety of translation-related genome-wide datasets. Variant interpretation is demonstrated on a 5'UTR variant of the gene HBB associated with beta-thalassemia. Frame pooling could find applications in other bioinformatics predictive tasks. Moreover, our model, released open source, could help pinpoint pathogenic genetic variants.
Wissenschaftlicher Artikel
Scientific Article
Baloni, P. ; Nho, K. ; Arnold, M. ; Louie, G. ; Kueider-Paisley, A. ; Saykin, A.J. ; Ekroos, K. ; Funk, C. ; Hood, L. ; Price, N.D. ; Baillie, R. ; Kastenmüller, G. ; Han, X. ; Kaddurah-Daouk, R.F.
Alzheimers Dement. 17:e056647 (2021)
BACKGROUND: L-carnitine is present in the mammalian cells as free carnitine (FC) and acylcarnitine and the adult human brain contains almost 10% of long chain acylcarnitine. Acylcarnitines are functionally involved in β-oxidation of fatty acids and are also known for their role in neuroprotection. Levels of plasma acylcarnitines are known to decreased on aging. It is important to understand the association of acylcarnitines with cognitive impairment in Alzheimer's disease (AD). METHOD: We integrated the transcriptome data from 1000 post-mortem brain samples from ROS/MAP, Mayo clinic and Mount Sinai Brain bank cohort with the brain region-specific metabolic networks. We calculated the metabolic fluxes for the reactions in the model and identified those that showed differential fluxes in AD samples. We filtered the reactions that are involved in acylcarnitine synthesis and transport namely carnitine transport, fatty acid oxidation, citric acid cycle, and glutathione metabolism. RESULT: We found differences in metabolic fluxes for reactions involved in the acetylcarnitine transport to mitochondria (ACRNtm), carnitine palmitoyl transferase 1 and 2 (CPT1 and CPT2) as well as acyl-CoA dehydrogenase short and medium chain (ACADS, ACADM) located in mitochondria in AD samples. Using gene-based association analysis in participants of the AD Neuroimaging Initiative (ADNI) phases 1, GO and 2, we identified genetic variants linked to CPT1, CPT2, ACADM and ACADS genes suggested from the metabolic flux analysis. CONCLUSION: Our findings suggest that acylcarnitine synthesis and transport is altered in AD. Altered metabolism of short and medium chain acylcarnitines can be used as metabolic features of AD.
Meeting abstract
Meeting abstract
Moore, S.R. ; Halldorsdottir, T. ; Martins, J. ; Lucae, S. ; Müller-Myhsok, B. ; Müller, N.S. ; Piechaczek, C. ; Feldmann, L. ; Freisleder, F.J. ; Greimel, E. ; Schulte-Körne, G. ; Binder, E.B. ; Knauer-Arloth, J.
Transl. Psychiatry 11:632 (2021)
Substantial sex differences have been reported in the physiological response to stress at multiple levels, including the release of the stress hormone, cortisol. Here, we explore the genomic variants in 93 females and 196 males regulating the initial transcriptional response to cortisol via glucocorticoid receptor (GR) activation. Gene expression levels in peripheral blood were obtained before and after GR-stimulation with the selective GR agonist dexamethasone to identify differential expression following GR-activation. Sex stratified analyses revealed that while the transcripts responsive to GR-stimulation were mostly overlapping between males and females, the quantitative trait loci (eQTLs) regulation differential transcription to GR-stimulation was distinct. Sex-stratified eQTL SNPs (eSNPs) were located in different functional genomic elements and sex-stratified transcripts were enriched within postmortem brain transcriptional profiles associated with Major Depressive Disorder (MDD) specifically in males and females in the cingulate cortex. Female eSNPs were enriched among SNPs linked to MDD in genome-wide association studies. Finally, transcriptional sensitive genetic profile scores derived from sex-stratified eSNPS regulating differential transcription to GR-stimulation were predictive of depression status and depressive symptoms in a sex-concordant manner in a child and adolescent cohort (n = 584). These results suggest the potential of eQTLs regulating differential transcription to GR-stimulation as biomarkers of sex-specific biological risk for stress-related psychiatric disorders.
Wissenschaftlicher Artikel
Scientific Article
Mcharo, R. ; Lennemann, T. ; France, J. ; Torres, L. ; Garí, M. ; Mbuya, W. ; Mwalongo, W. ; Mahenge, A. ; Bauer, A.J. ; Mnkai, J. ; Glasmeyer, L. ; Judick, M. ; Paul, M. ; Schroeder, N. ; Msomba, B. ; Sembo, M. ; Chiwerengo, N. ; Hoelscher, M. ; Geisenberger, O. ; Lelle, R.J. ; Saathoff, E. ; Maboko, L. ; Chachage, M. ; Kroidl, A. ; Geldmacher, C.
Front. Oncol. 11:763717 (2021)
Background: Women living with HIV in sub-Saharan Africa are at increased risk to develop cervical cancer (CC), which is caused by persistent infection with 13 oncogenic human papilloma viruses (HR-HPVs). It is important to accurately identify and target HIV-positive women at highest risk to develop CC for early therapeutic intervention. Methods: A total of 2,134 HIV+ and HIV− women from South-West Tanzania were prospectively screened for cervical cancer and precancerous lesions. Women with cervical cancer (n=236), high- and low-grade squamous intraepithelial lesions (HSIL: n=68, LSIL: n=74), and without lesion (n=426) underwent high-resolution HPV genotyping. Results: Eighty percent of women who were diagnosed with HSIL or LSIL were living with HIV. Any lesion, young age, HIV status, and depleted CD4 T cell counts were independent risk factors for HPV infections, which were predominantly caused by HR-HPV types. While multiple HR-HPV type infections were predominant in HIV+ women with HSIL, single-type infections predominated in HIV+ CC cases (p=0.0006). HPV16, 18, and 45 accounted for 85% (68/80) and 75% (82/110) of HIV+ and HIV− CC cases, respectively. Of note, HPV35, the most frequent HPV type in HSIL-positive women living with HIV, was rarely detected as a single-type infection in HSIL and cancer cases. Conclusion: HPV16, 18, and 45 should receive special attention for molecular diagnostic algorithms during CC prevention programs for HIV+ women from sub-Saharan Africa. HPV35 may have a high potential to induce HSIL in women living with HIV, but less potential to cause cervical cancer in single-type infections.
Wissenschaftlicher Artikel
Scientific Article
Wendisch, D. ; Dietrich, O. ; Mari, T. ; von Stillfried, S. ; Ibarra Del Rio, I.A. ; Mittermaier, M. ; Mache, C. ; Chua, R.L. ; Knöll, R. ; Timm, S. ; Brumhard, S. ; Krammer, T. ; Zauber, H. ; Hiller, A.L. ; Pascual-Reguant, A. ; Mothes, R. ; Bülow, R.D. ; Schulze, J. ; Leipold, A.M. ; Djudjaj, S. ; Erhard, F. ; Geffers, R. ; Pott, F. ; Kazmierski, J. ; Radke, J. ; Pergantis, P. ; Baßler, K. ; Conrad, C. ; Aschenbrenner, A.C. ; Sawitzki, B. ; Landthaler, M. ; Wyler, E. ; Horst, D. ; Hippenstiel, S. ; Hocke, A.C. ; Heppner, F.L. ; Uhrig, A. ; Garcia, C. ; Machleidt, F. ; Herold, S. ; Elezkurtaj, S. ; Thibeault, C. ; Witzenrath, M. ; Cochain, C. ; Suttorp, N. ; Drosten, C. ; Goffinet, C. ; Kurth, F. ; Schultze, J.L. ; Radbruch, H. ; Ochs, M. ; Eils, R. ; Müller-Redetzky, H. ; Hauser, A.E. ; Luecken, M. ; Theis, F.J. ; Wolff, T. ; Boor, P. ; Selbach, M. ; Saliba, A.E. ; Sander, L.E.
Cell 184, 6243-6261.e27 (2021)
COVID-19-induced “acute respiratory distress syndrome” (ARDS) is associated with prolonged respiratory failure and high mortality, but the mechanistic basis of lung injury remains incompletely understood. Here, we analyze pulmonary immune responses and lung pathology in two cohorts of patients with COVID-19 ARDS using functional single-cell genomics, immunohistology, and electron microscopy. We describe an accumulation of CD163-expressing monocyte-derived macrophages that acquired a profibrotic transcriptional phenotype during COVID-19 ARDS. Gene set enrichment and computational data integration revealed a significant similarity between COVID-19-associated macrophages and profibrotic macrophage populations identified in idiopathic pulmonary fibrosis. COVID-19 ARDS was associated with clinical, radiographic, histopathological, and ultrastructural hallmarks of pulmonary fibrosis. Exposure of human monocytes to SARS-CoV-2, but not influenza A virus or viral RNA analogs, was sufficient to induce a similar profibrotic phenotype in vitro. In conclusion, we demonstrate that SARS-CoV-2 triggers profibrotic macrophage responses and pronounced fibroproliferative ARDS.
Wissenschaftlicher Artikel
Scientific Article
Azodi, C.B ; Zappia, L. ; Oshlack, A. ; McCarthy, D.J.
Genome Biol. 22:341 (2021)
Population-scale single-cell RNA sequencing (scRNA-seq) is now viable, enabling finer resolution functional genomics studies and leading to a rush to adapt bulk methods and develop new single-cell-specific methods to perform these studies. Simulations are useful for developing, testing, and benchmarking methods but current scRNA-seq simulation frameworks do not simulate population-scale data with genetic effects. Here, we present splatPop, a model for flexible, reproducible, and well-documented simulation of population-scale scRNA-seq data with known expression quantitative trait loci. splatPop can also simulate complex batch, cell group, and conditional effects between individuals from different cohorts as well as genetically-driven co-expression.
Wissenschaftlicher Artikel
Scientific Article
Gjaltema, R.A.F. ; Schwämmle, T. ; Kautz, P. ; Robson, M. ; Schöpflin, R. ; Ravid Lustig, L. ; Brandenburg, L.O. ; Dunkel, I. ; Vechiatto, C. ; Ntini, E. ; Mutzel, V. ; Schmiedel, V. ; Marsico, A. ; Mundlos, S. ; Schulz, E.G.
Mol. Cell 82, 190-208.e17 (2021)
Developmental genes such as Xist, which initiates X chromosome inactivation, are controlled by complex cis-regulatory landscapes, which decode multiple signals to establish specific spatiotemporal expression patterns. Xist integrates information on X chromosome dosage and developmental stage to trigger X inactivation in the epiblast specifically in female embryos. Through a pooled CRISPR screen in differentiating mouse embryonic stem cells, we identify functional enhancer elements of Xist at the onset of random X inactivation. Chromatin profiling reveals that X-dosage controls the promoter-proximal region, while differentiation cues activate several distal enhancers. The strongest distal element lies in an enhancer cluster associated with a previously unannotated Xist-enhancing regulatory transcript, which we named Xert. Developmental cues and X-dosage are thus decoded by distinct regulatory regions, which cooperate to ensure female-specific Xist upregulation at the correct developmental time. With this study, we start to disentangle how multiple, functionally distinct regulatory elements interact to generate complex expression patterns in mammals.
Wissenschaftlicher Artikel
Scientific Article
Jin, K.X. ; Zuo, R. ; Anastassiadis, K. ; Klungland, A. ; Marr, C. ; Filipczyk, A.A.
Proc. Natl. Acad. Sci. U.S.A. 118:e2105192118 (2021)
N6-methyladenosine (m6A) deposition on messenger RNA (mRNA) controls embryonic stem cell (ESC) fate by regulating the mRNA stabilities of pluripotency and lineage transcription factors (TFs) [P. J. Batista et al., Cell Stem Cell 15, 707-719 (2014); Y. Wang et al., Nat. Cell Biol. 16, 191-198 (2014); and S. Geula et al., Science 347, 1002-1006 (2015)]. If the mRNAs of these two TF groups become stabilized, it remains unclear how the pluripotency or lineage commitment decision is implemented. We performed noninvasive quantification of Nanog and Oct4 TF protein levels in reporter ESCs to define cell-state dynamics at single-cell resolution. Long-term single-cell tracking shows that immediate m6A depletion by Mettl3 knock-down in serum/leukemia inhibitory factor supports both pluripotency maintenance and its departure. This is mediated by differential and opposing signaling pathways. Increased FGF5 mRNA stability activates pErk, leading to Nanog down-regulation. FGF5-mediated coactivation of pAkt reenforces Nanog expression. In formative stem cells poised toward differentiation, m6A depletion activates both pErk and pAkt, increasing the propensity for mesendodermal lineage induction. Stable m6A depletion by Mettl3 knock-out also promotes pErk activation. Higher pErk counteracts the pluripotency exit delay exhibited by stably m6A-depleted cells upon differentiation. At single-cell resolution, we illustrate that decreasing m6A abundances activates pErk and pAkt-signaling, regulating pluripotency departure.
Wissenschaftlicher Artikel
Scientific Article
Holmberg, O. ; Lenz, T. ; Koch, V. ; Alyagoob, A. ; Utsch, L. ; Rank, A. ; Sabic, E. ; Seguchi, M. ; Xhepa, E. ; Kufner, S. ; Cassese, S. ; Kastrati, A. ; Marr, C. ; Joner, M. ; Nicol, P.
Front. Cardiovasc. Med. 8:779807 (2021)
Background: Optical coherence tomography is a powerful modality to assess atherosclerotic lesions, but detecting lesions in high-resolution OCT is challenging and requires expert knowledge. Deep-learning algorithms can be used to automatically identify atherosclerotic lesions, facilitating identification of patients at risk. We trained a deep-learning algorithm (DeepAD) with co-registered, annotated histopathology to predict atherosclerotic lesions in optical coherence tomography (OCT). Methods: Two datasets were used for training DeepAD: (i) a histopathology data set from 7 autopsy cases with 62 OCT frames and co-registered histopathology for high quality manual annotation and (ii) a clinical data set from 51 patients with 222 OCT frames in which manual annotations were based on clinical expertise only. A U-net based deep convolutional neural network (CNN) ensemble was employed as an atherosclerotic lesion prediction algorithm. Results were analyzed using intersection over union (IOU) for segmentation. Results: DeepAD showed good performance regarding the prediction of atherosclerotic lesions, with a median IOU of 0.68 ± 0.18 for segmentation of atherosclerotic lesions. Detection of calcified lesions yielded an IOU = 0.34. When training the algorithm without histopathology-based annotations, a performance drop of >0.25 IOU was observed. The practical application of DeepAD was evaluated retrospectively in a clinical cohort (n = 11 cases), showing high sensitivity as well as specificity and similar performance when compared to manual expert analysis. Conclusion: Automated detection of atherosclerotic lesions in OCT is improved using a histopathology-based deep-learning algorithm, allowing accurate detection in the clinical setting. An automated decision-support tool based on DeepAD could help in risk prediction and guide interventional treatment decisions.
Wissenschaftlicher Artikel
Scientific Article
Yang, C. ; Starnecker, F. ; Pang, S. ; Chen, Z. ; Güldener, U. ; Li, L. ; Heinig, M. ; Schunkert, H.
BMC Cardiovasc. Disord. 21:586 (2021)
BACKGROUND: Epidemiological studies have repeatedly observed a markedly higher risk for coronary artery disease (CAD) in Scotland as compared to England. Up to now, it is unclear whether environmental or genetic factors might explain this phenomenon. METHODS: Using UK Biobank (UKB) data, we assessed CAD risk, based on the Framingham risk score (FRS) and common genetic variants, to explore the respective contribution to CAD prevalence in Scotland (n = 31,963) and England (n = 317,889). We calculated FRS based on sex, age, body mass index (BMI), total cholesterol (TC), high density lipoprotein cholesterol (HDL-C), systolic blood pressure (SBP), antihypertensive medication, smoking status, and diabetes. We determined the allele frequency of published genome-wide significant risk CAD alleles and a weighted genetic risk score (wGRS) for quantifying genetic CAD risk. RESULTS: Prevalence of CAD was 16% higher in Scotland as compared to England (8.98% vs. 7.68%, P < 0.001). However, the FRS only predicted a marginally higher CAD risk (less than 1%) in Scotland (12.5 ± 10.5 vs.12.6 ± 10.6, P = 0.03). Likewise, the overall number of genome-wide significant variants affecting CAD risk (157.6 ± 7.7 and 157.5 ± 7.7; P = 0.12) and a wGRS for CAD (2.49 ± 0.25 in both populations, P = 0.14) were remarkably similar in the English and Scottish population. Interestingly, we observed substantial differences in the allele frequencies of individual risk variants. Of the previously described 163 genome-wide significant variants studied here, 35 variants had higher frequencies in Scotland, whereas 37 had higher frequencies in England (P < 0.001 each). CONCLUSIONS: Neither the traditional risk factors included in the FRS nor a genetic risk score (GRS) based on established common risk alleles explained the higher CAD prevalence in Scotland. However, we observed marked differences in the distribution of individual risk alleles, which emphasizes that even geographically and ethnically closely related populations may display relevant differences in the genetic architecture of a common disease.
Wissenschaftlicher Artikel
Scientific Article
Dreher, S.I. ; Höckele, S. ; Huypens, P. ; Irmler, M. ; Hoffmann, C. ; Jeske, T. ; Hastreiter, M. ; Moller, A. ; Birkenfeld, A.L. ; Häring, H.-U. ; Peter, A. ; Beckers, J. ; Hrabě de Angelis, M. ; Weigert, C.
Cells 10:3443 (2021)
Physical training improves insulin sensitivity and can prevent type 2 diabetes (T2D). However, approximately 20% of individuals lack a beneficial outcome in glycemic control. TGF-β, identified as a possible upstream regulator involved in this low response, is also a potent regulator of microRNAs (miRNAs). The aim of this study was to elucidate the potential impact of TGF-β-driven miRNAs on individual exercise response. Non-targeted long and sncRNA sequencing analyses of TGF-β1-treated human skeletal muscle cells corroborated the effects of TGF-β1 on muscle cell differentiation, the induction of extracellular matrix components, and identified several TGF-β1-regulated miRNAs. qPCR validated a potent upregulation of miR-143-3p/145-5p and miR-181a2-5p by TGF-β1 in both human myoblasts and differentiated myotubes. Healthy subjects who were overweight or obese participated in a supervised 8-week endurance training intervention (n = 40) and were categorized as responder or low responder in glycemic control based on fold change ISIMats (≥+1.1 or <+1.1, respectively). In skeletal muscle biopsies of low responders, TGF-β signaling and miR-143/145 cluster levels were induced by training at much higher rates than among responders. Target-mining revealed HDACs, MYHs, and insulin signaling components INSR and IRS1 as potential miR-143/145 cluster targets. All these targets were down-regulated in TGF-β1-treated myotubes. Transfection of miR-143-3p/145-5p mimics in differentiated myotubes validated MYH1, MYH4, and IRS1 as miR-143/145 cluster targets. Elevated TGF-β signaling and miR-143/145 cluster induction in skeletal muscle of low responders might obstruct improvements in insulin sensitivity by training in two ways: by a negative impact of miR-143-3p on muscle cell fusion and myofiber functionality and by directly impairing insulin signaling via a reduction in INSR by TGF-β and finetuned IRS1 suppression by miR-143-3p.
Wissenschaftlicher Artikel
Scientific Article
Neiburga, K.D. ; Vilne, B. ; Bauer, S. ; Bongiovanni, D. ; Ziegler, T. ; Lachmann, M. ; Wengert, S. ; Hawe, J.S. ; Güldener, U. ; Westerlund, A. ; Li, L. ; Pang, S. ; Yang, C. ; Saar, K. ; Huebner, N. ; Maegdefessel, L. ; Lange, R. ; Krane, M. ; Schunkert, H. ; von Scheidt, M.
Biomolecules 11, New Approaches for the Treatment of Civilization Diseases:1683 (2021)
Cardiovascular disease (CVD) is the leading cause of morbidity and mortality worldwide. Non-coding RNAs have already been linked to CVD development and progression. While microR-NAs (miRs) have been well studied in blood samples, there is little data on tissue-specific miRs in cardiovascular relevant tissues and their relation to cardiovascular risk factors. Tissue-specific miRs derived from Arteria mammaria interna (IMA) from 192 coronary artery disease (CAD) patients undergoing coronary artery bypass grafting (CABG) were analyzed. The aims of the study were 1) to establish a reference atlas which can be utilized for identification of novel diagnostic biomarkers and potential therapeutic targets, and 2) to relate these miRs to cardiovascular risk factors. Overall, 393 individual miRs showed sufficient expression levels and passed quality control for further analysis. We identified 17 miRs–miR-10b-3p, miR-10-5p, miR-17-3p, miR-21-5p, miR-151a-5p, miR-181a-5p, miR-185-5p, miR-194-5p, miR-199a-3p, miR-199b-3p, miR-212-3p, miR-363-3p, miR-548d-5p, miR-744-5p, miR-3117-3p, miR-5683 and miR-5701–significantly correlated with cardiovascular risk factors (correlation coefficient >0.2 in both directions, p-value (p < 0.006, false discovery rate (FDR)
Wissenschaftlicher Artikel
Scientific Article
Syga, S. ; David-Rus, D. ; Schälte, Y. ; Hatzikirou, H. ; Deutsch, A.
Sci. Rep. 11:21913 (2021)
Countries around the world implement nonpharmaceutical interventions (NPIs) to mitigate the spread of COVID-19. Design of efficient NPIs requires identification of the structure of the disease transmission network. We here identify the key parameters of the COVID-19 transmission network for time periods before, during, and after the application of strict NPIs for the first wave of COVID-19 infections in Germany combining Bayesian parameter inference with an agent-based epidemiological model. We assume a Watts–Strogatz small-world network which allows to distinguish contacts within clustered cliques and unclustered, random contacts in the population, which have been shown to be crucial in sustaining the epidemic. In contrast to other works, which use coarse-grained network structures from anonymized data, like cell phone data, we consider the contacts of individual agents explicitly. We show that NPIs drastically reduced random contacts in the transmission network, increased network clustering, and resulted in a previously unappreciated transition from an exponential to a constant regime of new cases. In this regime, the disease spreads like a wave with a finite wave speed that depends on the number of contacts in a nonlinear fashion, which we can predict by mean field theory.
Wissenschaftlicher Artikel
Scientific Article
Mertins, J. ; Finke, J. ; Sies, R. ; Rink, K.M. ; Hasenauer, J. ; Lang, T.
eLife 10, 2624-2624 (2021)
SNARE proteins have been described as the effectors of fusion events in the secretory pathway more than two decades ago. The strong interactions between SNARE domains are clearly important in membrane fusion, but it is unclear whether they are involved in any other cellular processes. Here, we analyzed two classical SNARE proteins, syntaxin 1A and SNAP25. Although they are supposed to be engaged in tight complexes, we surprisingly find them largely segregated in the plasma membrane. Syntaxin 1A only occupies a small fraction of the plasma membrane area. Yet, we find it is able to redistribute the far more abundant SNAP25 on the mesoscale by gathering crowds of SNAP25 molecules onto syntaxin clusters in a SNARE-domain-dependent manner. Our data suggest that SNARE domain interactions are not only involved in driving membrane fusion on the nanoscale, but also play an important role in controlling the general organization of proteins on the mesoscale. Further, we propose these mechanisms preserve active syntaxin 1A-SNAP25 complexes at the plasma membrane.
Wissenschaftlicher Artikel
Scientific Article
Aboulmaouahib, B. ; Kastenmüller, G. ; Suhre, K. ; Zöllner, S. ; Weissensteiner, H. ; Gieger, C. ; Wang-Sattler, R. ; Lichtner, P. ; Strauch, K. ; Flaquer, A.
Hum. Mol. Genet., DOI: 10.1093/hmg/ddab312 (2021)
INTRODUCTION: In the era of personalized medicine with more and more patient specific targeted therapies being used, we need reliable, dynamic, faster, and sensitive biomarkers both to track the causes of disease and to develop and evolve therapies during the course of treatment. Metabolomics recently has shown substantial evidence to support its emerging role in disease diagnosis and prognosis. Aside from biomarkers and development of therapies, it is also an important goal to understand the involvement of mitochondrial DNA mtDNA in metabolic regulation, aging, and disease development. Somatic mutations of the mitochondrial genome are also heavily implicated in age-related disease and aging. The general hypothesis is that an alteration in the concentration of metabolite profiles (possibly conveyed by lifestyle and environmental factors) influences the increase of mutation rate in the mtDNA, and thereby contributes to a range of pathophysiological alterations observed in complex diseases. METHODS: We performed an inverted mitochondrial genome wide association analysis between mitochondrial nucleotide variants (mtSNVs) and concentration of metabolites. We used 151 metabolites and the whole sequenced mitochondrial genome from 2718 individuals to identify genetic variants associated with metabolite profiles. Because of the high coverage, next generation sequencing-based analysis of the mitochondrial genome allows for an accurate detection of mitochondrial heteroplasmy and for identification of variants associated with the metabolome. RESULTS: The strongest association was found for mt715G > A located in the MT-12SrRNA with the metabolite ratio C2/C10:1 (p-value = 6.82*10-09, β = 0.909). The second most significant mtSNV was found for mt3714A > G located in the MT-ND1 with the metabolite ratio PC ae C42:5/PC ae C44:5 (p-value = 1.02*10-08, β = 3.631). A large number of significant metabolite ratios were observed involving PC aa C36:6 and the variant mt10689G > A, located in the MT-ND4L gene. CONCLUSION: These results show an important interconnection between mitochondria and metabolite concentrations. Considering that some of the significant metabolites found in this study have been previously related to complex diseases such as neurological disorders and metabolic conditions, these associations found here might play a crucial role for further investigations of such complex diseases. Understanding the mechanisms that control human health and disease, in particular the role of genetic predispositions and their interaction with environmental factors is a prerequisite for the development of safe and efficient therapies for complex disorders.
Wissenschaftlicher Artikel
Scientific Article
Brydges, C.R. ; Fiehn, O. ; Mayberg, H.S. ; Schreiber, H. ; Dehkordi, S.M. ; Bhattacharyya, S. ; Cha, J. ; Choi, K.S. ; Craighead, W.E. ; Krishnan, R.R. ; Rush, A.J. ; Dunlop, B.W. ; Kaddurah-Daouk, R. ; Mood Disorders Precision Medicine Consortium (Kastenmüller, G.) ; Mood Disorders Precision Medicine Consortium (Arnold, M.)
Sci. Rep. 11:21011 (2021)
It is unknown whether indoles, metabolites of tryptophan that are derived entirely from bacterial metabolism in the gut, are associated with symptoms of depression and anxiety. Serum samples (baseline, 12 weeks) were drawn from participants (n = 196) randomized to treatment with cognitive behavioral therapy (CBT), escitalopram, or duloxetine for major depressive disorder. Baseline indoxyl sulfate abundance was positively correlated with severity of psychic anxiety and total anxiety and with resting state functional connectivity to a network that processes aversive stimuli (which includes the subcallosal cingulate cortex (SCC-FC), bilateral anterior insula, right anterior midcingulate cortex, and the right premotor areas). The relation between indoxyl sulfate and psychic anxiety was mediated only through the metabolite’s effect on the SCC-FC with the premotor area. Baseline indole abundances were unrelated to post-treatment outcome measures, and changes in symptoms were not correlated with changes in indole concentrations. These results suggest that CBT and antidepressant medications relieve anxiety via mechanisms unrelated to modulation of indoles derived from gut microbiota; it remains possible that treatment-related improvement stems from their impact on other aspects of the gut microbiome. A peripheral gut microbiome-derived metabolite was associated with altered neural processing and with psychiatric symptom (anxiety) in humans, which provides further evidence that gut microbiome disruption can contribute to neuropsychiatric disorders that may require different therapeutic approaches. Given the exploratory nature of this study, findings should be replicated in confirmatory studies. Clinical trial NCT00360399 “Predictors of Antidepressant Treatment Response: The Emory CIDAR” https://clinicaltrials.gov/ct2/show/NCT00360399.
Wissenschaftlicher Artikel
Scientific Article
Ostner, J. ; Carcy, S. ; Müller, C.
Front. Genet. 12:766405 (2021)
Accurate generative statistical modeling of count data is of critical relevance for the analysis of biological datasets from high-throughput sequencing technologies. Important instances include the modeling of microbiome compositions from amplicon sequencing surveys and the analysis of cell type compositions derived from single-cell RNA sequencing. Microbial and cell type abundance data share remarkably similar statistical features, including their inherent compositionality and a natural hierarchical ordering of the individual components from taxonomic or cell lineage tree information, respectively. To this end, we introduce a Bayesian model for tree-aggregated amplicon and single-cell compositional data analysis (tascCODA) that seamlessly integrates hierarchical information and experimental covariate data into the generative modeling of compositional count data. By combining latent parameters based on the tree structure with spike-and-slab Lasso penalization, tascCODA can determine covariate effects across different levels of the population hierarchy in a data-driven parsimonious way. In the context of differential abundance testing, we validate tascCODA’s excellent performance on a comprehensive set of synthetic benchmark scenarios. Our analyses on human single-cell RNA-seq data from ulcerative colitis patients and amplicon data from patients with irritable bowel syndrome, respectively, identified aggregated cell type and taxon compositional changes that were more predictive and parsimonious than those proposed by other schemes. We posit that tascCODA1 constitutes a valuable addition to the growing statistical toolbox for generative modeling and analysis of compositional changes in microbial or cell population data.
Wissenschaftlicher Artikel
Scientific Article
Büttner, M. ; Ostner, J. ; Müller, C. ; Theis, F.J. ; Schubert, B.
Nat. Commun. 12:6876 (2021)
Compositional changes of cell types are main drivers of biological processes. Their detection through single-cell experiments is difficult due to the compositionality of the data and low sample sizes. We introduce scCODA ( https://github.com/theislab/scCODA ), a Bayesian model addressing these issues enabling the study of complex cell type effects in disease, and other stimuli. scCODA demonstrated excellent detection performance, while reliably controlling for false discoveries, and identified experimentally verified cell type changes that were missed in original analyses.
Wissenschaftlicher Artikel
Scientific Article
Peng, Y. ; Felce, S.L. ; Dong, D. ; Penkava, F. ; Mentzer, A.J. ; Yao, X. ; Liu, G. ; Yin, Z. ; Chen, J.L. ; Lu, Y. ; Wellington, D. ; Wing, P.A.C. ; Dominey-Foy, D.C.C. ; Jin, C. ; Wang, W. ; Hamid, M.A. ; Fernandes, R.A. ; Wang, B. ; Fries, A. ; Zhuang, X. ; Ashley, N. ; Rostron, T. ; Waugh, C. ; Sopp, P. ; Hublitz, P. ; Beveridge, R. ; Tan, T.K. ; Dold, C. ; Kwok, A.J. ; Rich-Griffin, C. ; Dejnirattisa, W. ; Liu, C. ; Kurupati, P. ; Nassiri, I. ; Watson, R.A. ; Tong, O. ; Taylor, C.A. ; Kumar Sharma, P. ; Sun, B. ; Curion, F. ; Revale, S. ; Garner, L.C. ; Jansen, K. ; Ferreira, R.C. ; Attar, M. ; Fry, J.W. ; Russell, R.A. ; COMBAT Consortium ; Stauss, H.J. ; James, W. ; Townsend, A.J. ; Ho, J.-P. ; Klenerman, P. ; Mongkolsapaya, J. ; Screaton, G.R. ; Dendrou, C. ; Sansom, S.N. ; Bashford-Rogers, R. ; Chain, B. ; Smith, G.L. ; McKeating, J.A. ; Fairfax, B.P. ; Bowness, P. ; McMichael, A.J. ; Ogg, G. ; Knight, J.C. ; Dong, T.
Nat. Immunol., DOI: 10.1038/s41590-021-01084-z (2021)
NP105-113-B*07:02-specific CD8+ T cell responses are considered among the most dominant in SARS-CoV-2-infected individuals. We found strong association of this response with mild disease. Analysis of NP105-113-B*07:02-specific T cell clones and single-cell sequencing were performed concurrently, with functional avidity and antiviral efficacy assessed using an in vitro SARS-CoV-2 infection system, and were correlated with T cell receptor usage, transcriptome signature and disease severity (acute n = 77, convalescent n = 52). We demonstrated a beneficial association of NP105-113-B*07:02-specific T cells in COVID-19 disease progression, linked with expansion of T cell precursors, high functional avidity and antiviral effector function. Broad immune memory pools were narrowed postinfection but NP105-113-B*07:02-specific T cells were maintained 6 months after infection with preserved antiviral efficacy to the SARS-CoV-2 Victoria strain, as well as Alpha, Beta, Gamma and Delta variants. Our data show that NP105-113-B*07:02-specific T cell responses associate with mild disease and high antiviral efficacy, pointing to inclusion for future vaccine design.
Wissenschaftlicher Artikel
Scientific Article
Gudina, E.K. ; Ali, S. ; Girma, E. ; Gize, A. ; Tegene, B. ; Hundie, G.B. ; Sime, W.T. ; Ambachew, R. ; Gebreyohanns, A. ; Bekele, M. ; Bakuli, A. ; Elsbernd, K. ; Merkt, S. ; Contento, L. ; Hoelscher, M. ; Hasenauer, J. ; Wieser, A. ; Kroidl, A.
Lancet Glob. Health 9, e1517-e1527 (2021)
Background: Over 1 year since the first reported case, the true COVID-19 burden in Ethiopia remains unknown due to insufficient surveillance. We aimed to investigate the seroepidemiology of SARS-CoV-2 among front-line hospital workers and communities in Ethiopia. Methods: We did a population-based, longitudinal cohort study at two tertiary teaching hospitals involving hospital workers, rural residents, and urban communities in Jimma and Addis Ababa. Hospital workers were recruited at both hospitals, and community participants were recruited by convenience sampling including urban metropolitan settings, urban and semi-urban settings, and rural communities. Participants were eligible if they were aged 18 years or older, had provided written informed consent, and were willing to provide blood samples by venepuncture. Only one participant per household was recruited. Serology was done with Elecsys anti-SARS-CoV-2 anti-nucleocapsid assay in three consecutive rounds, with a mean interval of 6 weeks between tests, to obtain seroprevalence and incidence estimates within the cohorts. Findings: Between Aug 5, 2020, and April 10, 2021, we did three survey rounds with a total of 1104 hospital workers and 1229 community residents participating. SARS-CoV-2 seroprevalence among hospital workers increased strongly during the study period: in Addis Ababa, it increased from 10·9% (95% credible interval [CrI] 8·3–13·8) in August, 2020, to 53·7% (44·8–62·5) in February, 2021, with an incidence rate of 2223 per 100 000 person-weeks (95% CI 1785–2696); in Jimma Town, it increased from 30·8% (95% CrI 26·9–34·8) in November, 2020, to 56·1% (51·1–61·1) in February, 2021, with an incidence rate of 3810 per 100 000 person-weeks (95% CI 3149–4540). Among urban communities, an almost 40% increase in seroprevalence was observed in early 2021, with incidence rates of 1622 per 100 000 person-weeks (1004–2429) in Jimma Town and 4646 per 100 000 person-weeks (2797–7255) in Addis Ababa. Seroprevalence in rural communities increased from 18·0% (95% CrI 13·5–23·2) in November, 2020, to 31·0% (22·3–40·3) in March, 2021. Interpretation: SARS-CoV-2 spread in Ethiopia has been highly dynamic among hospital worker and urban communities. We can speculate that the greatest wave of SARS-CoV-2 infections is currently evolving in rural Ethiopia, and thus requires focused attention regarding health-care burden and disease prevention. Funding: Bavarian State Ministry of Sciences, Research, and the Arts; Germany Ministry of Education and Research; EU Horizon 2020 programme; Deutsche Forschungsgemeinschaft; and Volkswagenstiftung.
Wissenschaftlicher Artikel
Scientific Article
Farnoud, A. ; Tofighian, H. ; Baumann, I. ; Martin, A.R. ; Rashidi, M.M. ; Menden, M. ; Schmid, O.
Front. Pharmacol. 12:76420 (2021)
The nasal olfactory region is a potential route for non-invasive delivery of drugs directly from the nasal epithelium to the brain, bypassing the often impermeable blood-brain barrier. However, efficient aerosol delivery to the olfactory region is challenging due to its location in the nose. Here we explore aerosol delivery with bi-directional pulsatile flow conditions for targeted drug delivery to the olfactory region using a computational fluid dynamics (CFD) model on the patient-specific nasal geometry. Aerosols with aerodynamic diameter of 1 µm, which is large enough for delivery of large enough drug doses and yet potentially small enough for non-inertial aerosol deposition due to, e.g., particle diffusion and flow oscillations, is inhaled for 1.98 s through one nostril and exhaled through the other one. The bi-directional aerosol delivery with steady flow rate of 4 L/min results in deposition efficiencies (DEs) of 50.9 and 0.48% in the nasal cavity and olfactory region, respectively. Pulsatile flow with average flow rate of 4 L/min (frequency: 45 Hz) reduces these values to 34.4 and 0.12%, respectively, and it mitigates the non-uniformity of right-left deposition in both the cavity (from 1.77- to 1.33-fold) and the olfactory region (from 624- to 53.2-fold). The average drug dose deposited in the nasal cavity and the olfactory epithelium region is very similar in the right nasal cavity independent of pulsation conditions (inhalation side). In contrast, the local aerosol dose in the olfactory region of the left side is at least 100-fold lower than that in the nasal cavity independent of pulsation condition. Hence, while pulsatile flow reduces the right-left (inhalation-exhalation) imbalance, it is not able to overcome it. However, the inhalation side (even with pulsation) allows for relatively high olfactory epithelium drug doses per area reaching the same level as in the total nasal cavity. Due to the relatively low drug deposition in olfactory region on the exhalation side, this allows either very efficient targeting of the inhalation side, or uniform drug delivery by performing bidirectional flow first from the one and then from the other side of the nose.
Wissenschaftlicher Artikel
Scientific Article
Winheim, E. ; Rinke, L. ; Lutz, K. ; Reischer, A. ; Leutbecher, A. ; Wolfram, L. ; Rausch, L. ; Kranich, J. ; Wratil, P.R. ; Huber, J.E. ; Baumjohann, D. ; Rothenfußer, S. ; Schubert, B. ; Hilgendorff, A. ; Hellmuth, J.C. ; Scherer, C. ; Muenchhoff, M. ; von Bergwelt-Baildon, M. ; Stark, K. ; Straub, T. ; Brocker, T. ; Keppler, O.T. ; Subklewe, M. ; Krug, A.B.
PLoS Pathog. 17:e1009742 (2021)
Disease manifestations in COVID-19 range from mild to severe illness associated with a dysregulated innate immune response. Alterations in function and regeneration of dendritic cells (DCs) and monocytes may contribute to immunopathology and influence adaptive immune responses in COVID-19 patients. We analyzed circulating DC and monocyte subsets in 65 hospitalized COVID-19 patients with mild/moderate or severe disease from acute illness to recovery and in healthy controls. Persisting reduction of all DC subpopulations was accompanied by an expansion of proliferating Lineage-HLADR+ cells lacking DC markers. Increased frequency of CD163+ CD14+ cells within the recently discovered DC3 subpopulation in patients with more severe disease was associated with systemic inflammation, activated T follicular helper cells, and antibody-secreting cells. Persistent downregulation of CD86 and upregulation of programmed death-ligand 1 (PD-L1) in conventional DCs (cDC2 and DC3) and classical monocytes associated with a reduced capacity to stimulate naïve CD4+ T cells correlated with disease severity. Long-lasting depletion and functional impairment of DCs and monocytes may have consequences for susceptibility to secondary infections and therapy of COVID-19 patients.
Wissenschaftlicher Artikel
Scientific Article
Cruceanu, C. ; Dony, L. ; Krontira, A.C. ; Fischer, D.S. ; Roeh, S. ; Di Giaimo, R. ; Kyrousi, C. ; Kaspar, L. ; Knauer-Arloth, J. ; Czamara, D. ; Martinelli, S. ; Wehner, S. ; Breen, M.S. ; Koedel, M. ; Sauer, S. ; Sportelli, V. ; Rex-Haffner, M. ; Cappello, S. ; Theis, F.J. ; Binder, E.B.
Am. J. Psychiatry 179, 375-387 (2021)
OBJECTIVE: A fine-tuned balance of glucocorticoid receptor (GR) activation is essential for organ formation, with disturbances influencing many health outcomes. In utero, glucocorticoids have been linked to brain-related negative outcomes, with unclear underlying mechanisms, especially regarding cell-type-specific effects. An in vitro model of fetal human brain development, induced human pluripotent stem cell (hiPSC)-derived cerebral organoids, was used to test whether cerebral organoids are suitable for studying the impact of prenatal glucocorticoid exposure on the developing brain. METHODS: The GR was activated with the synthetic glucocorticoid dexamethasone, and the effects were mapped using single-cell transcriptomics across development. RESULTS: The GR was expressed in all cell types, with increasing expression levels through development. Not only did its activation elicit translocation to the nucleus and the expected effects on known GR-regulated pathways, but also neurons and progenitor cells showed targeted regulation of differentiation- and maturation-related transcripts. Uniquely in neurons, differentially expressed transcripts were significantly enriched for genes associated with behavior-related phenotypes and disorders. This human neuronal glucocorticoid response profile was validated across organoids from three independent hiPSC lines reprogrammed from different source tissues from both male and female donors. CONCLUSIONS: These findings suggest that excessive glucocorticoid exposure could interfere with neuronal maturation in utero, leading to increased disease susceptibility through neurodevelopmental processes at the interface of genetic susceptibility and environmental exposure. Cerebral organoids are a valuable translational resource for exploring the effects of glucocorticoids on early human brain development.
Wissenschaftlicher Artikel
Scientific Article
Aliee, H. ; Massip, F. ; Qi, C. ; Stella de Biase, M. ; van Nijnatten, J. ; Kersten, E.T.G. ; Kermani, N.Z. ; Khuder, B. ; Vonk, J.M. ; Vermeulen, R.C.H. ; U-BIOPRED study group ; Cambridge Lung Cancer Early Detection Programme ; INER-Ciencias Mexican Lung Program ; Neighbors, M. ; Tew, G.W. ; Grimbaldeston, M.A. ; Ten Hacken, N.H.T. ; Hu, S. ; Guo, Y. ; Zhang, X. ; Sun, K. ; Hiemstra, P.S. ; Ponder, B.A. ; Makela, M.J. ; Malmström, K. ; Rintoul, R.C. ; Reyfman, P.A. ; Theis, F.J. ; Brandsma, C.A. ; Adcock, I.M. ; Timens, W. ; Xu, C.J. ; van den Berge, M. ; Schwarz, R.F. ; Koppelman, G.H. ; Nawijn, M.C. ; Faiz, A.
Allergy, DOI: 10.1111/all.15152 (2021)
Wissenschaftlicher Artikel
Scientific Article
Horgusluoglu, E. ; Neff, R. ; Song, W.M. ; Wang, M. ; Wang, Q. ; Arnold, M. ; Krumsiek, J. ; Galindo-Prieto, B. ; Ming, C. ; Nho, K. ; Kastenmüller, G. ; Han, X. ; Baillie, R. ; Zeng, Q. ; Andrews, S. ; Cheng, H. ; Hao, K. ; Goate, A. ; Bennett, D.A. ; Saykin, A.J. ; Kaddurah-Daouk, R. ; Zhang, B.
Alzheimers Dement., DOI: 10.1002/alz.12468 (2021)
Metabolites, the biochemical products of the cellular process, can be used to measure alterations in biochemical pathways related to the pathogenesis of Alzheimer's disease (AD). However, the relationships between systemic abnormalities in metabolism and the pathogenesis of AD are poorly understood. In this study, we aim to identify AD-specific metabolomic changes and their potential upstream genetic and transcriptional regulators through an integrative systems biology framework for analyzing genetic, transcriptomic, metabolomic, and proteomic data in AD. Metabolite co-expression network analysis of the blood metabolomic data in the Alzheimer's Disease Neuroimaging Initiative (ADNI) shows short-chain acylcarnitines/amino acids and medium/long-chain acylcarnitines are most associated with AD clinical outcomes, including episodic memory scores and disease severity. Integration of the gene expression data in both the blood from the ADNI and the brain from the Accelerating Medicines Partnership Alzheimer's Disease (AMP-AD) program reveals ABCA1 and CPT1A are involved in the regulation of acylcarnitines and amino acids in AD. Gene co-expression network analysis of the AMP-AD brain RNA-seq data suggests the CPT1A- and ABCA1-centered subnetworks are associated with neuronal system and immune response, respectively. Increased ABCA1 gene expression and adiponectin protein, a regulator of ABCA1, correspond to decreased short-chain acylcarnitines and amines in AD in the ADNI. In summary, our integrated analysis of large-scale multiomics data in AD systematically identifies novel metabolites and their potential regulators in AD and the findings pave a way for not only developing sensitive and specific diagnostic biomarkers for AD but also identifying novel molecular mechanisms of AD pathogenesis.
Wissenschaftlicher Artikel
Scientific Article
Schmid, K. ; Höllbacher, B. ; Cruceanu, C. ; Böttcher, A. ; Lickert, H. ; Binder, E.B. ; Theis, F.J. ; Heinig, M.
Nat. Commun. 12:6625 (2021)
Single cell RNA-seq has revolutionized transcriptomics by providing cell type resolution for differential gene expression and expression quantitative trait loci (eQTL) analyses. However, efficient power analysis methods for single cell data and inter-individual comparisons are lacking. Here, we present scPower; a statistical framework for the design and power analysis of multi-sample single cell transcriptomic experiments. We modelled the relationship between sample size, the number of cells per individual, sequencing depth, and the power of detecting differentially expressed genes within cell types. We systematically evaluated these optimal parameter combinations for several single cell profiling platforms, and generated broad recommendations. In general, shallow sequencing of high numbers of cells leads to higher overall power than deep sequencing of fewer cells. The model, including priors, is implemented as an R package and is accessible as a web tool. scPower is a highly customizable tool that experimentalists can use to quickly compare a multitude of experimental designs and optimize for a limited budget.
Wissenschaftlicher Artikel
Scientific Article
Reddy, K.D. ; Lan, A. ; Boudewijn, I.M. ; Rathnayake, S.N.H. ; Koppelman, G.H. ; Aliee, H. ; Theis, F.J. ; Oliver, B.G. ; van den Berge, M. ; Faiz, A.
Am. J. Respir. Cell Mol. Biol. 65, 366-377 (2021)
Current smoking contributes to worsened asthma prognosis and more severe symptoms and limits the beneficial effects of corticosteroids. As the nasal epithelium can reflect smoking-induced changes in the lower airways, it is a relevant source to investigate changes in gene expression and DNA methylation. This study explores gene expression and DNA methylation changes in current and ex-smokers with asthma. Matched gene expression and epigenome-wide DNA methylation samples collected from nasal brushings of 55 patients enrolled in a clinical trial investigation of current and ex-smoker patients with asthma were analyzed. Differential gene expression and DNA methylation analyses were conducted comparing current smokers with ex-smokers. Expression quantitative trait methylation (eQTM) analysis was completed to explore smoking-relevant genes by CpG sites that differ between current and ex-smokers. To investigate the relevance of the smoking-associated DNA methylation changes for the lower airways, significant CpG sites were explored in bronchial biopsies from patients who had stopped smoking. A total of 809 genes and 18,814 CpG sites were differentially associated with current smoking in the nose. The cis-eQTM analysis uncovered 171 CpG sites with a methylation status associated with smoking-related gene expression, including AHRR, ALDH3A1, CYP1A1, and CYP1B1. The methylation status of CpG sites altered by current smoking reversed with 1 year of smoking cessation. We confirm that current smoking alters epigenetic patterns and affects gene expression in the nasal epithelium of patients with asthma, which is partially reversible in bronchial biopsies after smoking cessation. We demonstrate the ability to discern molecular changes in the nasal epithelium, presenting this as a tool in future investigations into disease-relevant effects of tobacco smoke.
Wissenschaftlicher Artikel
Scientific Article
Ostaszewski, M. ; Niarakis, A. ; Mazein, A. ; Kuperstein, I. ; Phair, R. ; Orta-Resendiz, A. ; Singh, V. ; Aghamiri, S.S. ; Acencio, M.L. ; Glaab, E. ; Ruepp, A. ; Fobo, G. ; Montrone, C. ; Brauner, B. ; Frishman, G. ; Monraz Gómez, L.C. ; Somers, J. ; Hoch, M. ; Kumar Gupta, S. ; Scheel, J. ; Borlinghaus, H. ; Czauderna, T. ; Schreiber, F. ; Montagud, A. ; Ponce de Leon, M. ; Funahashi, A. ; Hiki, Y. ; Hiroi, N. ; Yamada, T.G. ; Dräger, A. ; Renz, A. ; Naveez, M. ; Bocskei, Z. ; Messina, F. ; Börnigen, D. ; Fergusson, L. ; Conti, M. ; Rameil, M. ; Nakonecnij, V. ; Vanhoefer, J. ; Schmiester, L. ; Wang, M. ; Ackerman, E.E. ; Shoemaker, J.E. ; Zucker, J. ; Oxford, K. ; Teuton, J. ; Kocakaya, E. ; Summak, G.Y. ; Hanspers, K. ; Kutmon, M. ; Coort, S. ; Eijssen, L. ; Ehrhart, F. ; Rex, D.A.B. ; Slenter, D. ; Martens, M. ; Pham, N. ; Haw, R. ; Jassal, B. ; Matthews, L. ; Orlic-Milacic, M. ; Senff Ribeiro, A. ; Rothfels, K. ; Shamovsky, V. ; Stephan, R. ; Sevilla, C. ; Varusai, T. ; Ravel, J.M. ; Fraser, R. ; Ortseifen, V. ; Marchesi, S. ; Gawron, P. ; Smula, E. ; Heirendt, L. ; Satagopam, V.P. ; Wu, G. ; Riutta, A. ; Golebiewski, M. ; Owen, S. ; Goble, C. ; Hu, X. ; Overall, R.W. ; Maier, D. ; Bauch, A. ; Gyori, B.M. ; Bachman, J.A. ; Vega, C. ; Grouès, V. ; Vázquez, M.J. ; Porras, P. ; Licata, L. ; Iannuccelli, M. ; Sacco, F. ; Nesterova, A. ; Yuryev, A. ; de Waard, A. ; Turei, D. ; Luna, A. ; Babur, O. ; Soliman, S. ; Valdeolivas, A. ; Esteban-Medina, M. ; Peña-Chilet, M. ; Rian, K. ; Helikar, T. ; Lal Puniya, B. ; Módos, D. ; Treveil, A. ; Olbei, M. ; De Meulder, B. ; Ballereau, S. ; Dugourd, A. ; Naldi, A. ; Noël, V. ; Calzone, L. ; Sander, C. ; Demir, E. ; Korcsmáros, T. ; Freeman, T.C. ; Augé, F. ; Beckmann, J.S. ; Hasenauer, J. ; Wolkenhauer, O. ; Wilighagen, E.L. ; Pico, A.R. ; Evelo, C.T. ; Gillespie, M.E. ; Stein, L.D. ; Hermjakob, H. ; D'Eustachio, P. ; Saez-Rodriguez, J. ; Dopazo, J. ; Valencia, A. ; Kitano, H. ; Barillot, E. ; Auffray, C. ; Balling, R. ; Schneider, R.
Mol. Syst. Biol. 17:e10387 (2021)
We need to effectively combine the knowledge from surging literature with complex datasets to propose mechanistic models of SARS-CoV-2 infection, improving data interpretation and predicting key targets of intervention. Here, we describe a large-scale community effort to build an open access, interoperable and computable repository of COVID-19 molecular mechanisms. The COVID-19 Disease Map (C19DMap) is a graphical, interactive representation of disease-relevant molecular mechanisms linking many knowledge sources. Notably, it is a computational resource for graph-based analyses and disease modelling. To this end, we established a framework of tools, platforms and guidelines necessary for a multifaceted community of biocurators, domain experts, bioinformaticians and computational biologists. The diagrams of the C19DMap, curated from the literature, are integrated with relevant interaction and text mining databases. We demonstrate the application of network analysis and modelling approaches by concrete examples to highlight new testable hypotheses. This framework helps to find signatures of SARS-CoV-2 predisposition, treatment response or prioritisation of drug candidates. Such an approach may help deal with new waves of COVID-19 or similar pandemics in the long-term perspective.
Wissenschaftlicher Artikel
Scientific Article
Way, G.P. ; Greene, C.S. ; Carninci, P. ; Carvalho, B.S. ; de Hoon, M. ; Finley, S. ; Gosline, S.J.C. ; Le Cao, K.A. ; Lee, J.S.H. ; Marchionni, L. ; Robine, N. ; Sindi, S.S. ; Theis, F.J. ; Yang, J.Y.H. ; Carpenter, A.E. ; Fertig, E.J.
PLoS Biol. 19:e3001419 (2021)
Evo:lvPinlegaisnecsoynnfcirwmitthhatthalelhceoamdipnugtleavtieolnsarreevreopluretisoenntoevdecor rtrheectplya:st 30 years, computational biology has emerged as a mature scientific field. While the field has made major contributions toward improving scientific knowledge and human health, individual computational biology practitioners at various institutions often languish in career development. As optimistic biologists passionate about the future of our field, we propose solutions for both eager and reluctant individual scientists, institutions, publishers, funding agencies, and educators to fully embrace computational biology. We believe that in order to pave the way for the next generation of discoveries, we need to improve recognition for computational biologists and better align pathways of career success with pathways of scientific progress. With 10 outlined steps, we call on all adjacent fields to move away from the traditional individual, single-discipline investigator research model and embrace multidisciplinary, data-driven, team science.
Review
Review
Stegelmann, F. ; Wille, K. ; Busen, H. ; Fuchs, C. ; Schauer, S. ; Sadjadian, P. ; Becker, T. ; Kolatzki, V. ; Döhner, H. ; Stadler, R. ; Döhner, K. ; Griesshammer, M.
Leukemia, DOI: 10.1038/s41375-021-01366-3 (2021)
The article Significant association of cutaneous adverse events with hydroxyurea: results from a prospective non-interventional study in BCR-ABL1-negative myeloproliferative neoplasms (MPN) - on behalf of the German Study Group-MPN, written by Frank Stegelmann, Kai Wille, Hannah Busen, Christiane Fuchs, Stefanie Schauer, Parvis Sadjadian, Tatjana Becker, Vera Kolatzki, Hartmut Döhner, Rudolf Stadler, German Study Group-MPN, Konstanze Döhner & Martin Griesshammer, was originally published Online First without Open Access. After publication in volume 35, page 628–631 the author decided to opt for Open Choice and to make the article an Open Access publication. Therefore, the copyright of the article has been changed to © The Author(s) 2020 and the article is forthwith distributed under the terms of the Creative Commons Attribution. FUNDING Open Access funding enabled and organized by Projekt DEAL.
Sadafi, A. ; Makhro, A. ; Livshits, L. ; Navab, N. ; Bogdanova, A. ; Albarqouni, S. ; Marr, C.
In: (3rd MICCAI Workshop on Domain Adaptation and Representation Transfer, DART 2021, 27 September-01 October 2021, Virtual, Online). 2021. 216-225 (Lect. Notes Comput. Sc. ; 12968 LNCS)
Sickle cell disease (SCD) is a severe genetic hemoglobin disorder that results in premature destruction of red blood cells. Assessment of the severity of the disease is a challenging task in clinical routine, since the causes of broad variance in SCD manifestation despite the common genetic cause remain unclear. Identification of biomarkers that would predict the severity grade is of importance for prognosis and assessment of responsiveness of patients to therapy. Detection of the changes in red blood cell (RBC) density by means of separation of Percoll density gradients could be such a marker as it allows to resolve intercellular differences and follow the most damaged dense cells prone to destruction and vasoocclusion. Quantification and interpretation of the images obtained from the distribution of RBCs in Percoll gradients is an important prerequisite for establishment of this approach. Here, we propose a novel approach combining a graph convolutional network, a convolutional neural network, fast Fourier transform, and recursive feature elimination to predict the severity of SCD directly from a Percoll image. Two important but expensive laboratory blood test parameters are used for training the graph convolutional network. To make the model independent from such tests during prediction, these two parameters are estimated by a neural network from the Percoll image directly. On a cohort of 216 subjects, we achieve a prediction performance that is only slightly below an approach where the groundtruth laboratory measurements are used. Our proposed method is the first computational approach for the difficult task of SCD severity prediction. The two-step approach relies solely on inexpensive and simple blood analysis tools and can have a significant impact on the patients’ survival in low resource regions where access to medical instruments and doctors is limited.
Wagner, S.J. ; Khalili, N. ; Sharma, R. ; Boxberg, M. ; Marr, C. ; de Back, W. ; Peng, T.
In: (24th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2021, 27 September-01 October 2021, Virtual, Online). 2021. 257-266 (Lect. Notes Comput. Sc. ; 12908 LNCS)
In digital pathology, different staining procedures and scanners cause substantial color variations in whole-slide images (WSIs), especially across different laboratories. These color shifts result in a poor generalization of deep learning-based methods from the training domain to external pathology data. To increase test performance, stain normalization techniques are used to reduce the variance between training and test domain. Alternatively, color augmentation can be applied during training leading to a more robust model without the extra step of color normalization at test time. We propose a novel color augmentation technique, HistAuGAN, that can simulate a wide variety of realistic histology stain colors, thus making neural networks stain-invariant when applied during training. Based on a generative adversarial network (GAN) for image-to-image translation, our model disentangles the content of the image, i.e., the morphological tissue structure, from the stain color attributes. It can be trained on multiple domains and, therefore, learns to cover different stain colors as well as other domain-specific variations introduced in the slide preparation and imaging process. We demonstrate that HistAuGAN outperforms conventional color augmentation techniques on a classification task on the publicly available dataset Camelyon17 and show that it is able to mitigate present batch effects (Code and model weights are available at https://github.com/sophiajw/HistAuGAN.).
Nguyen, B.H.P. ; Ohnmacht, A. ; Galhoz, A. ; Büttner, M. ; Theis, F.J. ; Menden, M.
Diabetologie, DOI: 10.1007/s11428-021-00817-w (2021)
HintergrundDiabetes mellitus entwickelt sich zu einem globalen Gesundheitsproblem, das eine Transformation der Forschung und der medizinischen Praxis für ein besseres Patientenmanagement erfordert. Diesbezüglich bieten die Fülle an Daten und die Fortschritte in der Technologie und der künstlichen Intelligenz Möglichkeiten für ein solches Unterfangen.ZieleDiese Übersichtsarbeit soll einen Überblick über künstliche Intelligenz und die aktuelle Forschung in ihrer Anwendung im Bereich Diabetes geben, insbesondere zur Risikovorhersage, Diagnose, Prognose und Vorhersage von Komplikationen.FazitKünstliche Intelligenz transformiert die Diabetesforschung in vielen technischen und organisatorischen Aspekten. Obwohl ihr Einsatz noch begrenzt und mit vielen Herausforderungen konfrontiert ist, wird sie wahrscheinlich künftig die medizinische Behandlung beeinflussen, indem sie eine automatisierte und personalisierte Gesundheitsversorgung für Erkrankte bietet.
Review
Review
Welz, L. ; Kakavand, N. ; Hang, X. ; Laue, G. ; Ito, G. ; Silva, M.G. ; Plattner, C. ; Mishra, N. ; Tengen, F. ; Ogris, C. ; Jesinghaus, M. ; Wottawa, F. ; Arnold, P. ; Kaikkonen, L. ; Stengel, S. ; Tran, F. ; Das, S. ; Kaser, A. ; Trajanoski, Z. ; Blumberg, R. ; Roecken, C. ; Saur, D. ; Tschurtschenthaler, M. ; Schreiber, S. ; Rosenstiel, P. ; Aden, K.
Gastroenterology 162, 223-237.e11 (2021)
BACKGROUND AIMS: Throughout life, the intestinal epithelium undergoes constant self-renewal from intestinal stem cells. Together with genotoxic stressors and failing DNA repair, this self-renewal causes susceptibility towards malignant transformation. X-box binding protein 1 (XBP1) is a stress sensor involved in the unfolded protein response (UPR). We hypothesized that XBP1 acts as a signaling hub to regulate epithelial DNA damage responses. METHODS: Data from the TCGA were analyzed for association of XBP1 with CRC survival and molecular interactions between XBP1 andp53 pathway activity. The role of XBP1 in orchestrating p53-driven DNA damage response was tested in-vitro, in mouse models of chronic intestinal epithelial DNA damage (Xbp1/H2bfl/fl, Xbp1ΔIEC, H2bΔIEC, H2b/Xbp1ΔIEC) and via orthotopic tumor organoid transplantation. Transcriptome analysis of intestinal organoids was performed to identify molecular targets of Xbp1-mediated DNA damage response. RESULTS: In the TCGA dataset of CRC, low XBP1 expression was significantly associated with poor overall survival (OS) and reduced p53 pathway activity. In-vivo, H2b/Xbp1ΔIEC mice developed spontaneous intestinal carcinomas. Orthotopic tumor organoid transplantation revealed a metastatic potential of H2b/Xbp1ΔIEC-derived tumors. RNA sequencing of intestinal organoids (H2b/Xbp1fl/fl, H2bΔIEC, H2b/Xbp1ΔIEC, H2b/p53ΔIEC) identified a transcriptional program downstream of p53, in which XBP1 directs DNA damage-induced Ddit4l expression. DDIT4L inhibits mTOR-mediated phosphorylation of 4E-BP1. Pharmacological mTOR inhibition suppressed epithelial hyperproliferation via 4E-BP1. CONCLUSIONS: Our data suggest a crucial role for XBP1 in coordinating epithelial DNA damage responses and stem cell function via a p53-DDIT4L-dependent feedback mechanism.
Wissenschaftlicher Artikel
Scientific Article
Wille, K. ; Huenerbein, K. ; Jagenberg, E. ; Sadjadian, P. ; Becker, T. ; Kolatzki, V. ; Meixner, R. ; Marchi, H. ; Fuchs, C. ; Griesshammer, M.
Eur. J. Haematol., DOI: 10.1111/ejh.13721 (2021)
In patients with bcr-abl-negative myeloproliferative neoplasms (MPN), concerns are often raised about the use of anticoagulants because of an increased bleeding risk. However, there are few MPN studies focusing on bleeding. To investigate bleeding complications in MPN, we report our retrospective, single-center study of 829 patients with a median follow-up of 5.5 years (range: 0.1-35.6). A first bleeding event occurred in 143 of 829 patients (17.2%), corresponding to an incidence rate of 2.29% per patient/year. During the follow-up period, one out of 829 patients (0.1%) died due to bleeding. Regarding anticoagulation, most bleeding occurred in patients on antiplatelet therapies (60.1%), followed by patients on anticoagulation therapies (20.3%) and patients not on anticoagulation (19.6%). In multivariate analysis, administration of antiplatelet (HR 2.31 [1.43, 3.71]) and anticoagulation therapies (HR 4.06 [2.32, 7.09]), but not age, gender or mutation status, was associated with an increased bleeding risk. Comparing the "probability of bleeding-free survival" between the MPN subtypes, no significant difference was observed (p=0.91, log-rank test). Our retrospective study shows that antiplatelet and anticoagulation therapies significantly increase the risk of bleeding in MPN patients without affecting mortality. However, there is no reason to refrain from guideline-conform primary or secondary anticoagulation in MPN patients.
Wissenschaftlicher Artikel
Scientific Article
Zappia, L. ; Theis, F.J.
Genome Biol. 22:301 (2021)
Recent years have seen a revolution in single-cell RNA-sequencing (scRNA-seq) technologies, datasets, and analysis methods. Since 2016, the scRNA-tools database has cataloged software tools for analyzing scRNA-seq data. With the number of tools in the database passing 1000, we provide an update on the state of the project and the field. This data shows the evolution of the field and a change of focus from ordering cells on continuous trajectories to integrating multiple samples and making use of reference datasets. We also find that open science practices reward developers with increased recognition and help accelerate the field.
Review
Review
Westerlund, A. ; Hawe, J.S. ; Heinig, M. ; Schunkert, H.
Int. J. Mol. Sci. 22:10291 (2021)
Cardiovascular diseases (CVD) annually take almost 18 million lives worldwide. Most lethal events occur months or years after the initial presentation. Indeed, many patients experience repeated complications or require multiple interventions (recurrent events). Apart from affecting the individual, this leads to high medical costs for society. Personalized treatment strategies aiming at prediction and prevention of recurrent events rely on early diagnosis and precise prognosis. Complementing the traditional environmental and clinical risk factors, multi-omics data provide a holistic view of the patient and disease progression, enabling studies to probe novel angles in risk stratification. Specifically, predictive molecular markers allow insights into regulatory networks, pathways, and mechanisms underlying disease. Moreover, artificial intelligence (AI) represents a powerful, yet adaptive, framework able to recognize complex patterns in large-scale clinical and molecular data with the potential to improve risk prediction. Here, we review the most recent advances in risk prediction of recurrent cardiovascular events, and discuss the value of molecular data and biomarkers for understanding patient risk in a systems biology context. Finally, we introduce explainable AI which may improve clinical decision systems by making predictions transparent to the medical practitioner.
Review
Review
Oala, L. ; Murchison, A.G. ; Balachandran, P. ; Choudhary, S. ; Fehr, J. ; Leite, A.W. ; Goldschmidt, P.G. ; Johner, C. ; Schörverth, E.D.M. ; Nakasi, R. ; Meyer, M. ; Cabitza, F. ; Baird, P. ; Prabhu, C. ; Weicken, E. ; Liu, X. ; Wenzel, M. ; Vogler, S. ; Akogo, D. ; Alsalamah, S. ; Kazim, E. ; Koshiyama, A. ; Piechottka, S. ; Macpherson, S. ; Shadforth, I. ; Geierhofer, R. ; Matek, C. ; Krois, J. ; Sanguinetti, B. ; Arentz, M. ; Bielik, P. ; Calderon-Ramirez, S. ; Abbood, A. ; Langer, N. ; Haufe, S. ; Kherif, F. ; Pujari, S. ; Samek, W. ; Wiegand, T.
J. Med. Syst. 45:105 (2021)
Developers proposing new machine learning for health (ML4H) tools often pledge to match or even surpass the performance of existing tools, yet the reality is usually more complicated. Reliable deployment of ML4H to the real world is challenging as examples from diabetic retinopathy or Covid-19 screening show. We envision an integrated framework of algorithm auditing and quality control that provides a path towards the effective and reliable application of ML systems in healthcare. In this editorial, we give a summary of ongoing work towards that vision and announce a call for participation to the special issue  Machine Learning for Health: Algorithm Auditing & Quality Control in this journal to advance the practice of ML4H auditing.
Review
Review
Borkowski, K. ; Taha, A.Y. ; Pedersen, T.L. ; de Jager, P.L. ; Bennett, D.A. ; Arnold, M. ; Kaddurah-Daouk, R. ; Newman, J.W.
Sci. Rep. 11:18964 (2021)
Cognitive decline is associated with both normal aging and early pathologies leading to dementia. Here we used quantitative profiling of metabolites involved in the regulation of inflammation, vascular function, neuronal function and energy metabolism, including oxylipins, endocannabinoids, bile acids, and steroid hormones to identify metabolic biomarkers of mild cognitive impairment (MCI). Serum samples (n = 212) were obtained from subjects with or without MCI opportunistically collected with incomplete fasting state information. To maximize power and stratify the analysis of metabolite associations with MCI by the fasting state, we developed an algorithm to predict subject fasting state when unknown (n = 73). In non-fasted subjects, linoleic acid and palmitoleoyl ethanolamide levels were positively associated with perceptual speed. In fasted subjects, soluble epoxide hydrolase activity and tauro-alpha-muricholic acid levels were negatively associated with perceptual speed. Other cognitive domains showed associations with bile acid metabolism, but only in the non-fasted state. Importantly, this study shows unique associations between serum metabolites and cognitive function in the fasted and non-fasted states and provides a fasting state prediction algorithm based on measurable metabolites.
Wissenschaftlicher Artikel
Scientific Article
Bortoluzzi, S. ; Dashtsoodol, N. ; Engleitner, T. ; Drees, C. ; Helmrath, S. ; Mir, J. ; Toska, A. ; Flossdorf, M. ; Öllinger, R. ; Solovey, M. ; Colomé-Tatché, M. ; Kalfaoglu, B. ; Ono, M. ; Buch, T. ; Ammon, T. ; Rad, R. ; Schmidt-Supprian, M.
Immunity 54, 2497-2513.e9 (2021)
Innate-like T cell populations expressing conserved TCRs play critical roles in immunity through diverse developmentally acquired effector functions. Focusing on the prototypical lineage of invariant natural killer T (iNKT) cells, we sought to dissect the mechanisms and timing of fate decisions and functional effector differentiation. Utilizing induced expression of the semi-invariant NKT cell TCR on double positive thymocytes, an initially highly synchronous wave of iNKT cell development was triggered by brief homogeneous TCR signaling. After reaching a uniform progenitor state characterized by IL-4 production potential and proliferation, effector subsets emerged simultaneously, but then diverged toward different fates. While NKT17 specification was quickly completed, NKT1 cells slowly differentiated and expanded. NKT2 cells resembled maturing progenitors, which gradually diminished in numbers. Thus, iNKT subset diversification occurs in dividing progenitor cells without acute TCR input but utilizes multiple active cytokine signaling pathways. These data imply a two-step model of iNKT effector differentiation.
Wissenschaftlicher Artikel
Scientific Article
Pietzner, M. ; Wheeler, E. ; Carrasco-Zanini, J. ; Cortes, A. ; Koprulu, M. ; Wörheide, M. ; Oerton, E. ; Cook, J. ; Stewart, I.D. ; Kerrison, N.D. ; Luan, J. ; Raffler, J. ; Arnold, M. ; Arlt, W. ; O'Rahilly, S. ; Kastenmüller, G. ; Gamazon, E.R. ; Hingorani, A.D. ; Scott, R.A. ; Wareham, N.J. ; Langenberg, C.
Science 374:eabj1541 (2021)
Characterization of the genetic regulation of proteins is essential for understanding disease etiology and developing therapies. We identified 10,674 genetic associations for 3,892 plasma proteins to create a cis-anchored gene-protein-disease map of 1,859 connections that highlights strong cross-disease biological convergence. This proteo-genomic map provides a framework to 1) connect etiologically related diseases, 2) provide biological context for new or emerging disorders, and 3) integrate different biological domains to establish mechanisms for known gene-disease links. Our results identify proteo-genomic connections within and between diseases and establish the value of cis-protein variants for annotation of likely causal disease genes at GWAS loci, addressing a major barrier for experimental validation and clinical translation of genetic discoveries.
Wissenschaftlicher Artikel
Scientific Article
Olbrich, L. ; Castelletti, N. ; Schälte, Y. ; Garí, M. ; Pütz, P. ; Bakuli, A. ; Pritsch, M. ; Kroidl, I. ; Saathoff, E. ; Guggenbüehl Noller, J.M. ; Fingerle, V. ; Le Gleut, R. ; Gilberg, L. ; Brand, I. ; Falk, P. ; Markgraf, A. ; Deák, F. ; Riess, F. ; Diefenbach, M. ; Eser, T. ; Weinauer, F. ; Martin, S. ; Quenzel, E.M. ; Becker, M. ; Durner, J. ; Girl, P. ; Müller, K. ; Radon, K. ; Fuchs, C. ; Wölfel, R. ; Hasenauer, J. ; Hoelscher, M. ; Wieser, A.
J. Gen. Virol. 102:001653 (2021)
A number of seroassays are available for SARS-CoV-2 testing; yet, head-to-head evaluations of different testing principles are limited, especially using raw values rather than categorical data. In addition, identifying correlates of protection is of utmost importance, and comparisons of available testing systems with functional assays, such as direct viral neutralisation, are needed.We analysed 6658 samples consisting of true-positives (n=193), true-negatives (n=1091), and specimens of unknown status (n=5374). For primary testing, we used Euroimmun-Anti-SARS-CoV-2-ELISA-IgA/IgG and Roche-Elecsys-Anti-SARS-CoV-2. Subsequently virus-neutralisation, GeneScriptcPass, VIRAMED-SARS-CoV-2-ViraChip, and Mikrogen-recomLine-SARS-CoV-2-IgG were applied for confirmatory testing. Statistical modelling generated optimised assay cut-off thresholds. Sensitivity of Euroimmun-anti-S1-IgA was 64.8%, specificity 93.3% (manufacturer's cut-off); for Euroimmun-anti-S1-IgG, sensitivity was 77.2/79.8% (manufacturer's/optimised cut-offs), specificity 98.0/97.8%; Roche-anti-N sensitivity was 85.5/88.6%, specificity 99.8/99.7%. In true-positives, mean and median Euroimmun-anti-S1-IgA and -IgG titres decreased 30/90 days after RT-PCR-positivity, Roche-anti-N titres decreased significantly later. Virus-neutralisation was 80.6% sensitive, 100.0% specific (≥1:5 dilution). Neutralisation surrogate tests (GeneScriptcPass, Mikrogen-recomLine-RBD) were >94.9% sensitive and >98.1% specific. Optimised cut-offs improved test performances of several tests. Confirmatory testing with virus-neutralisation might be complemented with GeneScriptcPassTM or recomLine-RBD for certain applications. Head-to-head comparisons given here aim to contribute to the refinement of testing strategies for individual and public health use.
Wissenschaftlicher Artikel
Scientific Article
Rubio-Acero, R. ; Beyerl, J. ; Muenchhoff, M. ; Roth, M.S. ; Castelletti, N. ; Paunovic, I. ; Radon, K. ; Springer, B. ; Nagel, C.H. ; Boehm, B. ; Böhmer, M.M. ; Graf, A. ; Blum, H. ; Krebs, S. ; Keppler, O.T. ; Osterman, A. ; Khan, Z.N. ; Hoelscher, M. ; Wieser, A. ; KoCo19-Study Group (Fuchs, C.) ; KoCo19-Study Group (Le Gleut, R.)
Sci. Total Environ. 797:149031 (2021)
Wastewater-based epidemiology (WBE) is a tool now increasingly proposed to monitor the SARS-CoV-2 burden in populations without the need for individual mass testing. It is especially interesting in metropolitan areas where spread can be very fast, and proper sewage systems are available for sampling with short flow times and thus little decay of the virus. We started in March 2020 to set up a once-a-week qualified spot sampling protocol in six different locations in Munich carefully chosen to contain primarily wastewater of permanent residential areas, rather than industry or hospitals. We used RT-PCR and sequencing to track the spread of SARS-CoV-2 in the Munich population with temporo-spatial resolution. The study became fully operational in mid-April 2020 and has been tracking SARS-CoV-2 RNA load weekly for one year. Sequencing of the isolated viral RNA was performed to obtain information about the presence and abundance of variants of concern in the Munich area over time. We demonstrate that the evolution of SARS-CoV-2 RNA loads (between <7.5 and 3874/ml) in these different areas within Munich correlates well with official seven day incidence notification data (between 0.0 and 327 per 100,000) obtained from the authorities within the respective region. Wastewater viral loads predicted the dynamic of SARS-CoV-2 local incidence about 3 weeks in advance of data based on respiratory swab analyses. Aligning with multiple different point-mutations characteristic for certain variants of concern, we could demonstrate the gradual increase of variant of concern B.1.1.7 in the Munich population beginning in January 2021, weeks before it became apparent in sequencing results of swabs samples taken from patients living in Munich. Overall, the study highlights the potential of WBE to monitor the SARS-CoV-2 pandemic, including the introduction of variants of concern in a local population.
Wissenschaftlicher Artikel
Scientific Article
Beyerl, J. ; Rubio-Acero, R. ; Castelletti, N. ; Paunovic, I. ; Kroidl, I. ; Khan, Z.N. ; Bakuli, A. ; Tautz, A. ; Oft, J. ; Hoelscher, M. ; Wieser, A. ; KoCo19 Study group (Fuchs, C.) ; KoCo19 Study group (Le Gleut, R.)
EBioMedicine 70:103502 (2021)
BACKGROUND: Since 2020 SARS-CoV-2 spreads pandemically, infecting more than 119 million people, causing >2·6 million fatalities. Symptoms of SARS-CoV-2 infection vary greatly, ranging from asymptomatic to fatal. Different populations react differently to the disease, making it very hard to track the spread of the infection in a population. Measuring specific anti-SARS-CoV-2 antibodies is an important tool to assess the spread of the infection or successful vaccinations. To achieve sufficient sample numbers, alternatives to venous blood sampling are needed not requiring medical personnel or cold-chains. Dried-blood-spots (DBS) on filter-cards have been used for different studies, but not routinely for serology. METHODS: We developed a semi-automated protocol using self-sampled DBS for SARS-CoV-2 serology. It was validated in a cohort of matched DBS and venous-blood samples (n = 1710). Feasibility is demonstrated with two large serosurveys with 10247 company employees and a population cohort of 4465 participants. FINDINGS: Sensitivity and specificity reached 99·20% and 98·65%, respectively. Providing written instructions and video tutorials, 99·87% (4465/4471) of the unsupervised home sampling DBS cards could be analysed. INTERPRETATION: DBS-sampling is a valid and highly reliable tool for large scale serosurveys. We demonstrate feasibility and accuracy with a large validation cohort including unsupervised home sampling. This protocol might be of big importance for surveillance in resource-limited settings, providing low-cost highly accurate serology data. FUNDING: Provided by Bavarian State Ministry of Science and the Arts, LMU University-Hospital; Helmholtz-Centre-Munich, German Ministry for Education and Research (project01KI20271); University of Bonn; University of Bielefeld; the Medical Biodefense Research Program of Bundeswehr-Medical-Service; Euroimmun, RocheDiagnostics provided discounted kits and machines.
Wissenschaftlicher Artikel
Scientific Article
Garí, M. ; Grzesiak, M. ; Krekora, M. ; Kaczmarek, P. ; Jankowska, A. ; Krol, A. ; Kaleta, D. ; Jerzyńska, J. ; Janasik, B. ; Kuraś, R. ; Tartaglione, A.M. ; Calamandrei, G. ; Hanke, W. ; Polanska, K.
Environ. Res. 204:112049 (2021)
Exposure to environmental factors, such as neurotoxic metals and micronutrients, during critical periods of development can contribute to long-term consequences in offspring's health, including neurodevelopmental outcomes. The aim of this study was to evaluate the association between simultaneous prenatal exposure to metals [lead (Pb), cadmium (Cd), mercury (Hg)] and micronutrients [selenium (Se), zinc (Zn), copper (Cu)] and neurodevelopmental outcomes in school-age children from the Polish Mother and Child Cohort (REPRO_PL). Metals and micronutrients concentrations were measured in cord blood (Pb, Cd, Se, Zn, Cu) and in maternal hair (Hg) collected during the 3rd trimester of pregnancy. Behavioral and emotional problems, as well as children's cognitive and psychomotor development, were assessed in 436 school-age children using the Strengths and Difficulties Questionnaire (SDQ, filled in by the mothers) and the Polish adaptation of the Intelligence and Development Scales (IDS, administered by trained psychologists). Multivariate regression models were applied after imputation of missing values, using two approaches: (i) a joint analysis taking into account all metals and micronutrients simultaneously, and (ii) an ExWAS study (single-exposure model). In the SDQ, Hyperactivity/Inattention problems and Total difficulties were associated with higher Hg concentrations in maternal hair (0.18, 95% CI: 0.05; 0.3; and 0.14, 95% CI: 0.01; 0.3, respectively), whereas Emotional symptoms were inversely associated with Se and Zn levels in cord blood (-0.13, 95% CI: 0.3; 0.004; and -0.10, 95% CI: 0.2; 0.02, respectively). In the IDS, cord blood Pb levels were found to be negatively associated with Fluid and Crystallized IQ (-0.12, 95% CI: 0.3; 0.02; and -0.14, 95% CI: 0.3; 0.007, respectively) as well as Mathematical skills (-0.15, 95% CI: 0.3; 0.01). The current research has been able to simultaneously assess the exposure to various interacting chemicals during the prenatal period. We demonstrate that prenatal co-exposures to Pb, Hg, Zn and Se have long-term influences on the neuropsychological outcome of school-age children.
Wissenschaftlicher Artikel
Scientific Article
Oppenländer, L. ; Palit, S. ; Stemmer, K. ; Greisle, T. ; Sterr, M. ; Salinno, C. ; Bastidas-Ponce, A. ; Feuchtinger, A. ; Böttcher, A. ; Ansarullah ; Theis, F.J. ; Lickert, H.
Mol. Metab. 54:101330 (2021)
While the effectiveness of bariatric surgery in restoring β-cell function has been described in type-2 diabetes (T2D) patients and animal models for years, the mechanistic underpinnings are largely unknown. The possibility of vertical sleeve gastrectomy (VSG) to rescue a clinically-relevant, late-stage T2D condition and to promote β-cell recovery has not been investigated on a single-cell level. Nevertheless, characterization of the heterogeneity and functional states of β-cells after VSG is a fundamental step to understand mechanisms of glycaemic recovery and to ultimately develop alternative, less-invasive therapies. Here, we report that VSG was superior to calorie restriction in late-stage T2D and rapidly restored normoglycaemia in morbidly obese and overt diabetic db/db mice. Single-cell profiling of islets of Langerhans showed that VSG induced distinct, intrinsic changes in the β-cell transcriptome, but not in that of α-, δ-, and PP-cells. VSG triggered fast β-cell redifferentiation and functional improvement within only two weeks of intervention, which is not seen upon calorie restriction. Furthermore, VSG expanded β-cell area by means of redifferentiation and by creating a proliferation competent β-cell state. Collectively, our study reveals the superiority of VSG in the remission of far-progressed T2D and presents paths of β-cell regeneration and molecular pathways underlying the glycaemic benefits of VSG.
Wissenschaftlicher Artikel
Scientific Article
Verdun, C.M. ; Fuchs, T. ; Harar, P. ; Elbrächter, D. ; Fischer, D.S. ; Berner, J. ; Grohs, P. ; Theis, F.J. ; Krahmer, F.
Front. Publ. Health 9:583377 (2021)
Background: Due to the ongoing COVID-19 pandemic, demand for diagnostic testing has increased drastically, resulting in shortages of necessary materials to conduct the tests and overwhelming the capacity of testing laboratories. The supply scarcity and capacity limits affect test administration: priority must be given to hospitalized patients and symptomatic individuals, which can prevent the identification of asymptomatic and presymptomatic individuals and hence effective tracking and tracing policies. We describe optimized group testing strategies applicable to SARS-CoV-2 tests in scenarios tailored to the current COVID-19 pandemic and assess significant gains compared to individual testing. Methods: We account for biochemically realistic scenarios in the context of dilution effects on SARS-CoV-2 samples and consider evidence on specificity and sensitivity of PCR-based tests for the novel coronavirus. Because of the current uncertainty and the temporal and spatial changes in the prevalence regime, we provide analysis for several realistic scenarios and propose fast and reliable strategies for massive testing procedures. Key Findings: We find significant efficiency gaps between different group testing strategies in realistic scenarios for SARS-CoV-2 testing, highlighting the need for an informed decision of the pooling protocol depending on estimated prevalence, target specificity, and high- vs. low-risk population. For example, using one of the presented methods, all 1.47 million inhabitants of Munich, Germany, could be tested using only around 141 thousand tests if the infection rate is below 0.4% is assumed. Using 1 million tests, the 6.69 million inhabitants from the city of Rio de Janeiro, Brazil, could be tested as long as the infection rate does not exceed 1%. Moreover, we provide an interactive web application, available at www.grouptexting.com, for visualizing the different strategies and designing pooling schemes according to specific prevalence scenarios and test configurations. Interpretation: Altogether, this work may help provide a basis for an efficient upscaling of current testing procedures, which takes the population heterogeneity into account and is fine-grained towards the desired study populations, e.g., mild/asymptomatic individuals vs. symptomatic ones but also mixtures thereof. Funding: German Science Foundation (DFG), German Federal Ministry of Education and Research (BMBF), Chan Zuckerberg Initiative DAF, and Austrian Science Fund (FWF).
Wissenschaftlicher Artikel
Scientific Article
Danese, A. ; Richter, M. ; Chaichoompu, K. ; Fischer, D.S. ; Theis, F.J. ; Colomé-Tatché, M.
Nat. Commun. 12:5228 (2021)
EpiScanpy is a toolkit for the analysis of single-cell epigenomic data, namely single-cell DNA methylation and single-cell ATAC-seq data. To address the modality specific challenges from epigenomics data, epiScanpy quantifies the epigenome using multiple feature space constructions and builds a nearest neighbour graph using epigenomic distance between cells. EpiScanpy makes the many existing scRNA-seq workflows from scanpy available to large-scale single-cell data from other -omics modalities, including methods for common clustering, dimension reduction, cell type identification and trajectory learning techniques, as well as an atlas integration tool for scATAC-seq datasets. The toolkit also features numerous useful downstream functions, such as differential methylation and differential openness calling, mapping epigenomic features of interest to their nearest gene, or constructing gene activity matrices using chromatin openness. We successfully benchmark epiScanpy against other scATAC-seq analysis tools and show its outperformance at discriminating cell types.
Wissenschaftlicher Artikel
Scientific Article
Efendiyev, M.A. ; Vougalter, V.
In: The Many Facets of Complexity Science. 2021. 185-192
The chapter deals with the easily verifiable necessary condition of the preservation of the nonnegativity of the solutions of a system of parabolic equations in the case of the mixed diffusion when the standard Laplacian in the first m variables is added to the Laplace operator in the rest of the variables in a fractional power in the space of an arbitrary dimension. This necessary condition is crucial for the applied analysis community since it imposes the necessary form of the system of equations that must be treated mathematically.
Bergen, V. ; Soldatov, R.A. ; Kharchenko, P.V. ; Theis, F.J.
Mol. Syst. Biol. 17:e10282 (2021)
RNA velocity has enabled the recovery of directed dynamic information from single-cell transcriptomics by connecting measurements to the underlying kinetics of gene expression. This approach has opened up new ways of studying cellular dynamics. Here, we review the current state of RNA velocity modeling approaches, discuss various examples illustrating limitations and potential pitfalls, and provide guidance on how the ensuing challenges may be addressed. We then outline future directions on how to generalize the concept of RNA velocity to a wider variety of biological systems and modalities.
Review
Review
Kaiser, R. ; Leunig, A. ; Pekayvaz, K. ; Popp, O. ; Joppich, M. ; Polewka, V. ; Escaig, R. ; Anjum, A. ; Hoffknecht, M.L. ; Gold, C. ; Brambs, S. ; Engel, A. ; Stockhausen, S. ; Knottenberg, V. ; Titova, A. ; Haji, M. ; Scherer, C. ; Muenchhoff, M. ; Hellmuth, J.C. ; Saar, K. ; Schubert, B. ; Hilgendorff, A. ; Schulz, C. ; Kääb, S. ; Zimmer, R. ; Hübner, N. ; Massberg, S. ; Mertins, P. ; Nicolai, L. ; Stark, K.
JCI insight 6:e150862 (2021)
Neutrophils provide a critical line of defense in immune responses to various pathogens, but also inflict self-damage upon transition to a hyperactivated, procoagulant state. Recent work has highlighted proinflammatory neutrophil phenotypes contributing to lung injury and acute respiratory distress syndrome (ARDS) in patients suffering from COVID-19. Here, we utilize state-of-the art mass spectrometry-based proteomics, transcriptomic and correlative analyses as well as functional in vitro and in vivo studies to dissect how neutrophils contribute to the progression to severe COVID-19. We identify a reinforcing loop of both systemic and neutrophil intrinsic interleukin-8 (CXCL8/IL-8) dysregulation, which initiates and perpetuates neutrophil-driven immunopathology. This positive feedback loop of systemic and neutrophil autocrine IL-8 production leads to an activated, prothrombotic neutrophil phenotype characterized by degranulation and neutrophil extracellular trap (NET) formation. In severe COVID-19, neutrophils directly initiate the coagulation and complement cascade, highlighting a link to the immunothrombotic state observed in these patients. Targeting the IL-8-CXCR-1/-2 axis interferes with this vicious cycle and attenuates neutrophil activation, degranulation, NETosis, and IL-8 release. Finally, we show that blocking IL-8-like signaling reduces SARS-CoV-2 spike protein-induced, hACE2-dependent pulmonary microthrombosis in mice. In summary, our data provide comprehensive insights into the activation mechanisms of neutrophils in COVID-19 and uncover a self-sustaining neutrophil-IL-8-axis as promising therapeutic target in severe SARS-CoV-2 infection.
Wissenschaftlicher Artikel
Scientific Article
Matschinske, J. ; Alcaraz, N. ; Benis, A. ; Golebiewski, M. ; Grimm, D.G. ; Heumos, L. ; Kacprowski, T. ; Lazareva, O. ; List, M. ; Louadi, Z. ; Pauling, J.K. ; Pfeifer, N. ; Röttger, R. ; Schwämmle, V. ; Sturm, G. ; Traverso, A. ; van Steen, K. ; de Freitas, M.V. ; Villalba Silva, G.C. ; Wee, L. ; Wenke, N.K. ; Zanin, M. ; Zolotareva, O. ; Baumbach, J. ; Blumenthal, D.B.
Nat. Methods, DOI: 10.1038/s41592-021-01241-0 (2021)
We present the AIMe registry, a community-driven reporting platform for AI in biomedicine. It aims to enhance the accessibility, reproducibility and usability of biomedical AI models, and allows future revisions by the community.
Review
Review
Fischer, D.S. ; Dony, L. ; König, M. ; Moeed, A. ; Zappia, L. ; Heumos, L. ; Tritschler, S. ; Holmberg, O. ; Aliee, H. ; Theis, F.J.
Genome Biol. 22:248 (2021)
Single-cell RNA-seq datasets are often first analyzed independently without harnessing model fits from previous studies, and are then contextualized with public data sets, requiring time-consuming data wrangling. We address these issues with sfaira, a single-cell data zoo for public data sets paired with a model zoo for executable pre-trained models. The data zoo is designed to facilitate contribution of data sets using ontologies for metadata. We propose an adaption of cross-entropy loss for cell type classification tailored to datasets annotated at different levels of coarseness. We demonstrate the utility of sfaira by training models across anatomic data partitions on 8 million cells.
Wissenschaftlicher Artikel
Scientific Article
Garí, M. ; Moos, R. ; Bury, D. ; Kasper-Sonnenberg, M. ; Jankowska, A. ; Andysz, A. ; Hanke, W. ; Nowak, D. ; Bose-O'Reilly, S. ; Koch, H.M. ; Polanska, K.
Environ. Health 20:95 (2021)
BACKGROUND: Bisphenol A (BPA) is an industrial chemical mostly used in the manufacture of plastics, resins and thermal paper. Several studies have reported adverse health effects with BPA exposures, namely metabolic disorders and altered neurodevelopment in children, among others. The aim of this study was to explore BPA exposure, its socio-demographic and life-style related determinants, and its association with neurodevelopmental outcomes in early school age children from Poland. METHODS: A total of 250 urine samples of 7 year-old children from the Polish Mother and Child Cohort Study (REPRO_PL) were analyzed for BPA concentrations using high performance liquid chromatography with online sample clean-up coupled to tandem mass spectrometry (online-SPE-LC-MS/MS). Socio-demographic and lifestyle-related data was collected by questionnaires or additional biomarker measurements. Emotional and behavioral symptoms in children were assessed using mother-reported Strengths and Difficulties Questionnaire (SDQ). Cognitive and psychomotor development was evaluated by Polish adaptation of the Intelligence and Development Scales (IDS) performed by trained psychologists. RESULTS: Urinary BPA concentrations and back-calculated daily intakes (medians of 1.8 μg/l and 46.3 ng/kg bw/day, respectively) were similar to other European studies. Urinary cotinine levels and body mass index, together with maternal educational level and socio-economic status, were the main determinants of BPA levels in Polish children. After adjusting for confounding factors, BPA has been found to be positively associated with emotional symptoms (β: 0.14, 95% CI: 0.022; 0.27). Cognitive and psychomotor development were not found to be related to BPA levels. CONCLUSIONS: This study represents the first report of BPA levels and their determinants in school age children in Poland. The exposure level was found to be related to child emotional condition, which can have long-term consequences including social functioning and scholastic achievements. Further monitoring of this population in terms of overall chemical exposure is required.
Wissenschaftlicher Artikel
Scientific Article
Nguyen, B.H.P. ; Ohnmacht, A. ; Sharifli, S. ; Garnett, M.J. ; Menden, M.
Int. J. Mol. Sci. 22:10135 (2021)
Disparities between risk, treatment outcomes and survival rates in cancer patients across the world may be attributed to socioeconomic factors. In addition, the role of ancestry is frequently discussed. In preclinical studies, high‐throughput drug screens in cancer cell lines have empowered the identification of clinically relevant molecular biomarkers of drug sensitivity; however, the genetic ancestry from tissue donors has been largely neglected in this setting. In order to address this, here, we show that the inferred ancestry of cancer cell lines is conserved and may impact drug response in patients as a predictive covariate in high‐throughput drug screens. We found that there are differential drug responses between European and East Asian ancestries, especially when treated with PI3K/mTOR inhibitors. Our finding emphasizes a new angle in precision medicine, as cancer intervention strategies should consider the germline landscape, thereby reducing the failure rate of clinical trials.
Wissenschaftlicher Artikel
Scientific Article
Aliluev, A. ; Tritschler, S. ; Sterr, M. ; Oppenländer, L. ; Hinterdobler, J. ; Greisle, T. ; Irmler, M. ; Beckers, J. ; Sun, N. ; Walch, A.K. ; Stemmer, K. ; Kindt, A. ; Krumsiek, J. ; Tschöp, M.H. ; Luecken, M. ; Theis, F.J. ; Lickert, H. ; Böttcher, A.
Nat. Metab. 3, 1202-1216 (2021)
Excess nutrient uptake and altered hormone secretion in the gut contribute to a systemic energy imbalance, which causes obesity and an increased risk of type 2 diabetes and colorectal cancer. This functional maladaptation is thought to emerge at the level of the intestinal stem cells (ISCs). However, it is not clear how an obesogenic diet affects ISC identity and fate. Here we show that an obesogenic diet induces ISC and progenitor hyperproliferation, enhances ISC differentiation and cell turnover and changes the regional identities of ISCs and enterocytes in mice. Single-cell resolution of the enteroendocrine lineage reveals an increase in progenitors and peptidergic enteroendocrine cell types and a decrease in serotonergic enteroendocrine cell types. Mechanistically, we link increased fatty acid synthesis, Ppar signaling and the Insr-Igf1r-Akt pathway to mucosal changes. This study describes molecular mechanisms of diet-induced intestinal maladaptation that promote obesity and therefore underlie the pathogenesis of the metabolic syndrome and associated complications.
Wissenschaftlicher Artikel
Scientific Article
Lotfollahi, M. ; Naghipourfar, M. ; Luecken, M. ; Khajavi, M. ; Büttner, M. ; Wagenstetter, M. ; Avsec, Z. ; Gayoso, A. ; Yosef, N. ; Interlandi, M. ; Rybakov, S. ; Misharin, A.V. ; Theis, F.J.
Nat. Biotechnol., DOI: 10.1038/s41587-021-01001-7 (2021)
Large single-cell atlases are now routinely generated to serve as references for analysis of smaller-scale studies. Yet learning from reference data is complicated by batch effects between datasets, limited availability of computational resources and sharing restrictions on raw data. Here we introduce a deep learning strategy for mapping query datasets on top of a reference called single-cell architectural surgery (scArches). scArches uses transfer learning and parameter optimization to enable efficient, decentralized, iterative reference building and contextualization of new datasets with existing references without sharing raw data. Using examples from mouse brain, pancreas, immune and whole-organism atlases, we show that scArches preserves biological state information while removing batch effects, despite using four orders of magnitude fewer parameters than de novo integration. scArches generalizes to multimodal reference mapping, allowing imputation of missing modalities. Finally, scArches retains coronavirus disease 2019 (COVID-19) disease variation when mapping to a healthy reference, enabling the discovery of disease-specific cell states. scArches will facilitate collaborative projects by enabling iterative construction, updating, sharing and efficient use of reference atlases.
Wissenschaftlicher Artikel
Scientific Article
Sekhri, R. ; Sadjadian, P. ; Becker, T. ; Kolatzki, V. ; Huenerbein, K. ; Meixner, R. ; Marchi, H. ; Wallmann, R. ; Fuchs, C. ; Griesshammer, M. ; Wille, K.
Ann. Hematol., DOI: 10.1007/s00277-021-04647-0 (2021)
Recently, there has been increased concern about a risk of secondary malignancies (SM) occurring in myelofibrosis (MF) patients receiving ruxolitinib (RUX). In polycythemia vera (PV), on the other hand, only limited data on the risk of SM under RUX treatment are available. To investigate the association between RUX therapy in PV and SM, we conducted a retrospective, single-center study that included 289 PV patients. RUX was administered to 32.9% (95/289) of patients for a median treatment duration of 48.0 months (range 1.0-101.6). Within a median follow-up of 97 months (1.0-395.0) after PV diagnosis, 24 SM occurred. Comparing the number of PV patients with RUX-associated SM (n = 10, 41.7%) with the 14 (58.3%) patients who developed SM without RUX, no significant difference (p = 0.34, chi square test) was found. No increased incidences of melanoma, lymphoma, or solid "non-skin" malignancies were observed with RUX (p = 0.31, p = 0.60, and p = 0.63, respectively, chi square test). However, significantly more NMSC occurred in association with RUX treatment (p = 0.03, chi-squared test). The "SM-free survival" was not significantly different by log rank test for all 289 patients (p = 0.65), for the patients (n = 208; 72%) receiving cytoreductive therapy (p = 0.48) or for different therapy sequences (p = 0.074). In multivariate analysis, advanced age at PV diagnosis (HR 1.062 [95% CI 1.028, 1.098]) but not administration of RUX (HR 1.068 [95% CI 0.468, 2.463]) was associated with an increased risk for SM (p = 0.005). According to this retrospective analysis, no increased risk of SM due to RUX treatment could be substantiated for PV.
Wissenschaftlicher Artikel
Scientific Article
Radon, K. ; Bakuli, A. ; Pütz, P. ; Le Gleut, R. ; Guggenbüehl Noller, J.M. ; Olbrich, L. ; Saathoff, E. ; Garí, M. ; Schälte, Y. ; Frahnow, T. ; Wölfel, R. ; Pritsch, M. ; Rothe, C. ; Pletschette, M. ; Rubio-Acero, R. ; Beyerl, J. ; Metaxa, D. ; Förster, F. ; Thiel, V. ; Castelletti, N. ; Rieß, F. ; Diefenbach, M.N. ; Fröschl, G. ; Bruger, J. ; Winter, S. ; Frese, J. ; Puchinger, K. ; Brand, I. ; Kroidl, I. ; Wieser, A. ; Hoelscher, M. ; Hasenauer, J. ; Fuchs, C.
BMC Infect. Dis. 21:925 (2021)
BACKGROUND: In the 2nd year of the COVID-19 pandemic, knowledge about the dynamics of the infection in the general population is still limited. Such information is essential for health planners, as many of those infected show no or only mild symptoms and thus, escape the surveillance system. We therefore aimed to describe the course of the pandemic in the Munich general population living in private households from April 2020 to January 2021. METHODS: The KoCo19 baseline study took place from April to June 2020 including 5313 participants (age 14 years and above). From November 2020 to January 2021, we could again measure SARS-CoV-2 antibody status in 4433 of the baseline participants (response 83%). Participants were offered a self-sampling kit to take a capillary blood sample (dry blood spot; DBS). Blood was analysed using the Elecsys® Anti-SARS-CoV-2 assay (Roche). Questionnaire information on socio-demographics and potential risk factors assessed at baseline was available for all participants. In addition, follow-up information on health-risk taking behaviour and number of personal contacts outside the household (N = 2768) as well as leisure time activities (N = 1263) were collected in summer 2020. RESULTS: Weighted and adjusted (for specificity and sensitivity) SARS-CoV-2 sero-prevalence at follow-up was 3.6% (95% CI 2.9-4.3%) as compared to 1.8% (95% CI 1.3-3.4%) at baseline. 91% of those tested positive at baseline were also antibody-positive at follow-up. While sero-prevalence increased from early November 2020 to January 2021, no indication of geospatial clustering across the city of Munich was found, although cases clustered within households. Taking baseline result and time to follow-up into account, men and participants in the age group 20-34 years were at the highest risk of sero-positivity. In the sensitivity analyses, differences in health-risk taking behaviour, number of personal contacts and leisure time activities partly explained these differences. CONCLUSION: The number of citizens in Munich with SARS-CoV-2 antibodies was still below 5% during the 2nd wave of the pandemic. Antibodies remained present in the majority of SARS-CoV-2 sero-positive baseline participants. Besides age and sex, potentially confounded by differences in behaviour, no major risk factors could be identified. Non-pharmaceutical public health measures are thus still important.
Wissenschaftlicher Artikel
Scientific Article
Adlung, L. ; Stapor, P. ; Tönsing, C. ; Schmiester, L. ; Schwarzmüller, L.E. ; Postawa, L. ; Wang, D. ; Timmer, J. ; Klingmüller, U. ; Hasenauer, J. ; Schilling, M.
Cell Rep. 36:109507 (2021)
Survival or apoptosis is a binary decision in individual cells. However, at the cell-population level, a graded increase in survival of colony-forming unit-erythroid (CFU-E) cells is observed upon stimulation with erythropoietin (Epo). To identify components of Janus kinase 2/signal transducer and activator of transcription 5 (JAK2/STAT5) signal transduction that contribute to the graded population response, we extended a cell-population-level model calibrated with experimental data to study the behavior in single cells. The single-cell model shows that the high cell-to-cell variability in nuclear phosphorylated STAT5 is caused by variability in the amount of Epo receptor (EpoR):JAK2 complexes and of SHP1, as well as the extent of nuclear import because of the large variance in the cytoplasmic volume of CFU-E cells. 24–118 pSTAT5 molecules in the nucleus for 120 min are sufficient to ensure cell survival. Thus, variability in membrane-associated processes is sufficient to convert a switch-like behavior at the single-cell level to a graded population-level response.
Wissenschaftlicher Artikel
Scientific Article
Lakrisenko, P. ; Weindl, D.
Curr. Opin. Syst. Biol. 28:100358 (2021)
As metabolomics datasets are becoming larger and more complex, there is an increasing need for model-based data integration and analysis to optimally leverage these data. Dynamic models of metabolism allow for the integration of heterogeneous data and the analysis of dynamic phenotypes. Here, we review recent efforts in using dynamic metabolic models for data integration, focusing on approaches based on ordinary differential equations that are applicable to both time-resolved and steady-state measurements and that do not require flux distributions as inputs. Furthermore, we discuss recent advances and current challenges. We conclude that much progress has been made in various areas, such as the development of scalable simulation tools, and although challenges remain, dynamic modeling is a powerful tool for metabolomics data analysis that is not yet living up to its full potential.
Review
Review
Serr, I. ; Drost, F. ; Schubert, B. ; Daniel, C.
Front. Immunol. 12:712870 (2021)
Regulatory T cells (Tregs) are key mediators of peripheral self-tolerance and alterations in their frequencies, stability, and function have been linked to autoimmunity. The antigen-specific induction of Tregs is a long-envisioned goal for the treatment of autoimmune diseases given reduced side effects compared to general immunosuppressive therapies. However, the translation of antigen-specific Treg inducing therapies for the treatment or prevention of autoimmune diseases into the clinic remains challenging. In this mini review, we will discuss promising results for antigen-specific Treg therapies in allergy and specific challenges for such therapies in autoimmune diseases, with a focus on type 1 diabetes (T1D). We will furthermore discuss opportunities for antigen-specific Treg therapies in T1D, including combinatorial strategies and tissue-specific Treg targeting. Specifically, we will highlight recent advances in miRNA-targeting as a means to foster Tregs in autoimmunity. Additionally, we will discuss advances and perspectives of computational strategies for the detailed analysis of tissue-specific Tregs on the single-cell level.
Review
Review
Efendiyev, M.A. ; Murley, J. ; Sivaloganathan, S.
Bull. Math. Biol. 83:95 (2021)
High intensity focussed ultrasound (HIFU) has emerged as a novel therapeutic modality, for the treatment of various cancers, that is gaining significant traction in clinical oncology. It is a cancer therapy that avoids many of the associated negative side effects of other more well-established therapies (such as surgery, chemotherapy and radiotherapy) and does not lead to the longer recuperation times necessary in these cases. The increasing interest in HIFU from biomedical researchers and clinicians has led to the development of a number of mathematical models to capture the effects of HIFU energy deposition in biological tissue. In this paper, we study the simplest such model that has been utilized by researchers to study temperature evolution under HIFU therapy. Although the model poses significant theoretical challenges, in earlier work, we were able to establish existence and uniqueness of solutions to this system of PDEs (see Efendiev et al. Adv Appl Math Sci 29(1):231-246, 2020). In the current work, we take the next natural step of studying the long-time dynamics of solutions to this model, in the case where the external forcing is quasi-periodic. In this case, we are able to prove the existence of uniform attractors to the corresponding evolutionary processes generated by our model and to estimate the Hausdorff dimension of the attractors, in terms of the physical parameters of the system.
Review
Review
Pachl, E. ; Zamanian, A. ; Stieler, M. ; Bahr, C. ; Ahmidi, N.
Appl. Sci. 11:6986 (2021)
The main intervention for coronary artery disease is stent implantation. We aim to predict post-intervention target lesion failure (TLF) months before its onset, an extremely challenging task in clinics. This post-intervention decision support tool helps physicians to identify at-risk patients much earlier and to inform their follow-up care. We developed a novel machine-learning model with three components: a TLF predictor at discharge via a combination of nine conventional models and a super-learner, a risk score predictor for time-to-TLF, and an update function to manage the size of the at-risk cohort. We collected data in a prospective study from 120 medical centers in over 25 countries. All 1975 patients were enrolled during Phase I (2016–2020) and were followed up for five years post-intervention. During Phase I, 151 patients (7.6%) developed TLF, which we used for training. Additionally, 12 patients developed TLF after Phase I (right-censored). Our algorithm successfully classifies 1635 patients as not at risk (TNR = 90.23%) and predicts TLF for 86 patients (TPR = 52.76%), outperforming its training by identifying 33% of the right-censored patients. We also compare our model against five state of the art models, outperforming them all. Our prediction tool is able to optimize for both achieving higher sensitivity and maintaining a reasonable size for the at-risk cohort over time.
Wissenschaftlicher Artikel
Scientific Article
Fischer, D.S. ; Ansari, M. ; Wagner, K.I. ; Jarosch, S. ; Huang, Y. ; Mayr, C. ; Strunz, M. ; Lang, N.J. ; D'Ippolito, E. ; Hammel, M. ; Mateyka, L. ; Weber, S. ; Wolff, L.S. ; Witter, K. ; Fernandez, I.E. ; Leuschner, G. ; Milger, K. ; Frankenberger, M. ; Nowak, L. ; Heinig-Menhard, K. ; Koch, I. ; Stoleriu, M.-G. ; Hilgendorff, A. ; Behr, J. ; Pichlmair, A. ; Schubert, B. ; Theis, F.J. ; Busch, D.H. ; Schiller, H. B. ; Schober, K.
Nat. Commun. 12:4515 (2021)
The in vivo phenotypic profile of T cells reactive to severe acute respiratory syndrome (SARS)-CoV-2 antigens remains poorly understood. Conventional methods to detect antigen-reactive T cells require in vitro antigenic re-stimulation or highly individualized peptide-human leukocyte antigen (pHLA) multimers. Here, we use single-cell RNA sequencing to identify and profile SARS-CoV-2-reactive T cells from Coronavirus Disease 2019 (COVID-19) patients. To do so, we induce transcriptional shifts by antigenic stimulation in vitro and take advantage of natural T cell receptor (TCR) sequences of clonally expanded T cells as barcodes for 'reverse phenotyping'. This allows identification of SARS-CoV-2-reactive TCRs and reveals phenotypic effects introduced by antigen-specific stimulation. We characterize transcriptional signatures of currently and previously activated SARS-CoV-2-reactive T cells, and show correspondence with phenotypes of T cells from the respiratory tract of patients with severe disease in the presence or absence of virus in independent cohorts. Reverse phenotyping is a powerful tool to provide an integrated insight into cellular states of SARS-CoV-2-reactive T cells across tissues and activation states.
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Scientific Article
Nho, K. ; Kueider-Paisley, A. ; Arnold, M. ; MahmoudianDehkordi, S. ; Risacher, S.L. ; Louie, G. ; Blach, C. ; Baillie, R. ; Han, X. ; Kastenmüller, G. ; Doraiswamy, P.M. ; Kaddurah-Daouk, R. ; Saykin, A.J.
Brain Commun. 3:fcab139 (2021)
Metabolomics in the Alzheimer's Disease Neuroimaging Initiative cohort provides a powerful tool for mapping biochemical changes in Alzheimer's disease, and a unique opportunity to learn about the association between circulating blood metabolites and brain amyloid-β deposition in Alzheimer's disease. We examined 140 serum metabolites and their associations with brain amyloid-β deposition, cognition and conversion from mild cognitive impairment to Alzheimer's disease in the Alzheimer's Disease Neuroimaging Initiative. Processed [18F] Florbetapir PET images were used to perform a voxel-wise statistical analysis of the effect of metabolite levels on amyloid-β accumulation across the whole brain. We performed a multivariable regression analysis using age, sex, body mass index, apolipoprotein E ε4 status and study phase as covariates. We identified nine metabolites as significantly associated with amyloid-β deposition after multiple comparison correction. Higher levels of one acylcarnitine (C3; propionylcarnitine) and one biogenic amine (kynurenine) were associated with decreased amyloid-β accumulation and higher memory scores. However, higher levels of seven phosphatidylcholines (lysoPC a C18:2, PC aa C42:0, PC ae C42:3, PC ae C44:3, PC ae C44:4, PC ae C44:5 and PC ae C44:6) were associated with increased brain amyloid-β deposition. In addition, higher levels of PC ae C44:4 were significantly associated with lower memory and executive function scores and conversion from mild cognitive impairment to Alzheimer's disease dementia. Our findings suggest that dysregulation of peripheral phosphatidylcholine metabolism is associated with earlier pathological changes noted in Alzheimer's disease as measured by brain amyloid-β deposition as well as later clinical features including changes in memory and executive functioning. Perturbations in phosphatidylcholine metabolism may point to issues with membrane restructuring leading to the accumulation of amyloid-β in the brain. Additional studies are needed to explore whether these metabolites play a causal role in the pathogenesis of Alzheimer's disease or if they are biomarkers for systemic changes during preclinical phases of the disease.
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Scientific Article
Bien, J. ; Yan, X. ; Simpson, L. ; Müller, C.
Sci. Rep. 11:14505 (2021)
Modern high-throughput sequencing technologies provide low-cost microbiome survey data across all habitats of life at unprecedented scale. At the most granular level, the primary data consist of sparse counts of amplicon sequence variants or operational taxonomic units that are associated with taxonomic and phylogenetic group information. In this contribution, we leverage the hierarchical structure of amplicon data and propose a data-driven and scalable tree-guided aggregation framework to associate microbial subcompositions with response variables of interest. The excess number of zero or low count measurements at the read level forces traditional microbiome data analysis workflows to remove rare sequencing variants or group them by a fixed taxonomic rank, such as genus or phylum, or by phylogenetic similarity. By contrast, our framework, which we call trac (tree-aggregation of compositional data), learns data-adaptive taxon aggregation levels for predictive modeling, greatly reducing the need for user-defined aggregation in preprocessing while simultaneously integrating seamlessly into the compositional data analysis framework. We illustrate the versatility of our framework in the context of large-scale regression problems in human gut, soil, and marine microbial ecosystems. We posit that the inferred aggregation levels provide highly interpretable taxon groupings that can help microbiome researchers gain insights into the structure and functioning of the underlying ecosystem of interest.
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Scientific Article
Schmiester, L. ; Weindl, D. ; Hasenauer, J.
Bioinformatics 37, 4493-4500 (2021)
MOTIVATION: Unknown parameters of dynamical models are commonly estimated from experimental data. However, while various efficient optimization and uncertainty analysis methods have been proposed for quantitative data, methods for qualitative data are rare and suffer from bad scaling and convergence. RESULTS: Here, we propose an efficient and reliable framework for estimating the parameters of ordinary differential equation models from qualitative data. In this framework, we derive a semi-analytical algorithm for gradient calculation of the optimal scaling method developed for qualitative data. This enables the use of efficient gradient-based optimization algorithms. We demonstrate that the use of gradient information improves performance of optimization and uncertainty quantification on several application examples. On average, we achieve a speedup of more than one order of magnitude compared to gradient-free optimization. Additionally, in some examples, the gradient-based approach yields substantially improved objective function values and quality of the fits. Accordingly, the proposed framework substantially improves the parameterization of models from qualitative data. AVAILABILITY: The proposed approach is implemented in the open-source Python Parameter EStimation TOolbox (pyPESTO). pyPESTO is available at https://github.com/ICB-DCM/pyPESTO. All application examples and code to reproduce this study are available at https://doi.org/10.5281/zenodo.4507613. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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Pollmann, T.R. ; Schönert, S. ; Müller, J. ; Pollmann, J. ; Resconi, E. ; Wiesinger, C. ; Haack, C. ; Shtembari, L. ; Turcati, A. ; Neumair, B. ; Meighen-Berger, S. ; Zattera, G. ; Neumair, M. ; Apel, U. ; Okolie, A.
EPJ Data Sci. 10:37 (2021)
Contact tracing is one of several strategies employed in many countries to curb the spread of SARS-CoV-2. Digital contact tracing (DCT) uses tools such as cell-phone applications to improve tracing speed and reach. We model the impact of DCT on the spread of the virus for a large epidemiological parameter space consistent with current literature on SARS-CoV-2. We also model DCT in combination with random testing (RT) and social distancing (SD). Modelling is done with two independently developed individual-based (stochastic) models that use the Monte Carlo technique, benchmarked against each other and against two types of deterministic models. For current best estimates of the number of asymptomatic SARS-CoV-2 carriers (approximately 40%), their contagiousness (similar to that of symptomatic carriers), the reproductive number before interventions ( R 0 at least 3) we find that DCT must be combined with other interventions such as SD and/or RT to push the reproductive number below one. At least 60% of the population would have to use the DCT system for its effect to become significant. On its own, DCT cannot bring the reproductive number below 1 unless nearly the entire population uses the DCT system and follows quarantining and testing protocols strictly. For lower uptake of the DCT system, DCT still reduces the number of people that become infected. When DCT is deployed in a population with an ongoing outbreak where O (0.1%) of the population have already been infected, the gains of the DCT intervention come at the cost of requiring up to 15% of the population to be quarantined (in response to being traced) on average each day for the duration of the epidemic, even when there is sufficient testing capability to test every traced person.
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Scientific Article
Matek, C. ; Krappe, S. ; Münzenmayer, C. ; Haferlach, T. ; Marr, C.
Blood 138, 1917-1927 (2021)
Biomedical applications of deep learning algorithms rely on large, expert annotated data sets. The classification of bone marrow cell cytomorphology, an important cornerstone of hematological diagnosis, is still done manually thousands of times every day, due to a lack of datasets and trained models.We apply convolutional neural networks (CNNs) to a large dataset of 171,374 microscopic cytological images taken from bone marrow smears of 945 patients diagnosed with a variety of hematological diseases. The dataset is the largest expert-annotated pool of bone marrow cytology images available in the literature so far. It allows us to train high-quality classifiers of leukocyte cytomorphology that identify a wide range of diagnostically relevant cell species at high precision and recall.Our CNNs outcompete previous feature-based approaches and provide a proof-of-concept to the classification problem of single bone marrow cells.This work is a step towards automated evaluation of bone marrow cell morphology using state-of-the-art image classification algorithms. The underlying dataset represents both an educational resource as well as a reference for future AI-based approaches to bone marrow cytomorphology.
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Scientific Article
Aliee, H. ; Theis, F.J.
Cell Syst. 12, 706-715.e4 (2021)
Knowing cell-type proportions in a tissue is very important to identify which cells or cell types are targeted by a disease or perturbation. Hence, several deconvolution methods have been proposed to infer cell-type proportions from bulk RNA samples. Their performance with noisy reference profiles and closely correlated cell types highly depends on the set of genes undergoing deconvolution. In this work, we introduce AutoGeneS, a platform that automatically extracts discriminative genes and reveals the cellular heterogeneity of bulk RNA samples. AutoGeneS requires no prior knowledge about marker genes and selects genes by simultaneously optimizing multiple criteria: minimizing the correlation and maximizing the distance between cell types. AutoGeneS can be applied to reference profiles from various sources like single-cell experiments or sorted cell populations. Ground truth cell proportions analyzed by flow cytometry confirmed the accuracy of AutoGeneS in identifying cell-type proportions. AutoGeneS is available for use via a standalone Python package (https://github.com/theislab/AutoGeneS).
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Scientific Article
Scheibner, K. ; Schirge, S. ; Burtscher, I. ; Büttner, M. ; Sterr, M. ; Yang, D. ; Böttcher, A. ; Ansarullah ; Irmler, M. ; Beckers, J. ; Cernilogar, F.M. ; Schotta, G. ; Theis, F.J. ; Lickert, H.
Nat. Cell Biol., DOI: 10.1038/s41556-021-00735-5 (2021)
In the version of this Article originally published, text referencing ATAC-seq data was incorrectly retained. References to ATAC-seq data, which are not included in this study, should be removed from the text in the Results sections ‘In vitro-generated definitive endoderm forms by partial EMT’ and ‘Foxa2 suppresses a complete EMT during endoderm formation’, as well as from the author contributions section. The Methods subsection ‘ChIP-seq and ATAC-seq data visualization’ should also be completely removed. The errors have been corrected.
Durso-Cain, K. ; Kumberger, P. ; Schälte, Y. ; Fink, T. ; Dahari, H. ; Hasenauer, J. ; Uprichard, S.L. ; Graw, F.
Viruses 13:1308 (2021)
The hepatitis C virus (HCV) is capable of spreading within a host by two different transmission modes: cell-free and cell-to-cell. However, the contribution of each of these transmission mechanisms to HCV spread is unknown. To dissect the contribution of these different transmission modes to HCV spread, we measured HCV lifecycle kinetics and used an in vitro spread assay to monitor HCV spread kinetics after a low multiplicity of infection in the absence and presence of a neutralizing antibody that blocks cell-free spread. By analyzing these data with a spatially explicit mathematical model that describes viral spread on a single-cell level, we quantified the contribution of cell-free, and cell-to-cell spread to the overall infection dynamics and show that both transmission modes act synergistically to enhance the spread of infection. Thus, the simultaneous occurrence of both transmission modes represents an advantage for HCV that may contribute to viral persistence. Notably, the relative contribution of each viral transmission mode appeared to vary dependent on different experimental conditions and suggests that viral spread is optimized according to the environment. Together, our analyses provide insight into the spread dynamics of HCV and reveal how different transmission modes impact each other.
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Scientific Article
Ditz, B. ; Boekhoudt, J.G. ; Aliee, H. ; Theis, F.J. ; Nawijn, M.C. ; Brandsma, C.A. ; Hiemstra, P.S. ; Timens, W. ; Tew, G.W. ; Grimbaldeston, M.A. ; Neighbors, M. ; Guryev, V. ; van den Berge, M. ; Faiz, A.
ERJ Open Res. 7:00104-2021 (2021)
More DEGs are detected by RNA-Seq than microarrays in COPD lung biopsies and are associated with immunological pathways. Performing bulk tissue cell-type deconvolution in microarray lung samples, using the SVR method, reflects RNA-Seq results. https://bit.ly/2N8sY3s.
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Scientific Article
Schiffer, C. ; Spitzer, H. ; Kiwitz, K. ; Unger, N. ; Wagstyl, K. ; Evans, A.C. ; Harmeling, S. ; Amunts, K. ; Dickscheid, T.
Neuroimage 240:118327 (2021)
Human brain atlases provide spatial reference systems for data characterizing brain organization at different levels, coming from different brains. Cytoarchitecture is a basic principle of the microstructural organization of the brain, as regional differences in the arrangement and composition of neuronal cells are indicators of changes in connectivity and function. Automated scanning procedures and observer-independent methods are prerequisites to reliably identify cytoarchitectonic areas, and to achieve reproducible models of brain segregation. Time becomes a key factor when moving from the analysis of single regions of interest towards high-throughput scanning of large series of whole-brain sections. Here we present a new workflow for mapping cytoarchitectonic areas in large series of cell-body stained histological sections of human postmortem brains. It is based on a Deep Convolutional Neural Network (CNN), which is trained on a pair of section images with annotations, with a large number of un-annotated sections in between. The model learns to create all missing annotations in between with high accuracy, and faster than our previous workflow based on observer-independent mapping. The new workflow does not require preceding 3D-reconstruction of sections, and is robust against histological artefacts. It processes large data sets with sizes in the order of multiple Terabytes efficiently. The workflow was integrated into a web interface, to allow access without expertise in deep learning and batch computing. Applying deep neural networks for cytoarchitectonic mapping opens new perspectives to enable high-resolution models of brain areas, introducing CNNs to identify borders of brain areas.
Wissenschaftlicher Artikel
Scientific Article
Witte, F. ; Ruiz-Orera, J. ; Mattioli, C.C. ; Blachut, S. ; Adami, E. ; Schulz, J.F. ; Schneider-Lunitz, V. ; Hummel, O. ; Patone, G. ; Mücke, M.B. ; Silhavý, J. ; Heinig, M. ; Bottolo, L. ; Sanchis, D. ; Vingron, M. ; Chekulaeva, M. ; Pravenec, M. ; Hubner, N. ; Van Heesch, S.
Genome Biol. 22:191 (2021)
BACKGROUND: Little is known about the impact of trans-acting genetic variation on the rates with which proteins are synthesized by ribosomes. Here, we investigate the influence of such distant genetic loci on the efficiency of mRNA translation and define their contribution to the development of complex disease phenotypes within a panel of rat recombinant inbred lines. RESULTS: We identify several tissue-specific master regulatory hotspots that each control the translation rates of multiple proteins. One of these loci is restricted to hypertrophic hearts, where it drives a translatome-wide and protein length-dependent change in translational efficiency, altering the stoichiometric translation rates of sarcomere proteins. Mechanistic dissection of this locus across multiple congenic lines points to a translation machinery defect, characterized by marked differences in polysome profiles and misregulation of the small nucleolar RNA SNORA48. Strikingly, from yeast to humans, we observe reproducible protein length-dependent shifts in translational efficiency as a conserved hallmark of translation machinery mutants, including those that cause ribosomopathies. Depending on the factor mutated, a pre-existing negative correlation between protein length and translation rates could either be enhanced or reduced, which we propose to result from mRNA-specific imbalances in canonical translation initiation and reinitiation rates. CONCLUSIONS: We show that distant genetic control of mRNA translation is abundant in mammalian tissues, exemplified by a single genomic locus that triggers a translation-driven molecular mechanism. Our work illustrates the complexity through which genetic variation can drive phenotypic variability between individuals and thereby contribute to complex disease.
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Scientific Article
Richter, M. ; Deligiannis, I.K. ; Yin, K. ; Danese, A. ; Lleshi, E. ; Coupland, P. ; Vallejos, C.A. ; Matchett, K.P. ; Henderson, N.C. ; Colomé-Tatché, M. ; Martinez Jimenez, C.P.
Nat. Commun. 12:4264 (2021)
Single-cell RNA-seq reveals the role of pathogenic cell populations in development and progression of chronic diseases. In order to expand our knowledge on cellular heterogeneity, we have developed a single-nucleus RNA-seq2 method tailored for the comprehensive analysis of the nuclear transcriptome from frozen tissues, allowing the dissection of all cell types present in the liver, regardless of cell size or cellular fragility. We use this approach to characterize the transcriptional profile of individual hepatocytes with different levels of ploidy, and have discovered that ploidy states are associated with different metabolic potential, and gene expression in tetraploid mononucleated hepatocytes is conditioned by their position within the hepatic lobule. Our work reveals a remarkable crosstalk between gene dosage and spatial distribution of hepatocytes.
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Scientific Article
Klaus, V. ; Schriever, S.C. ; Monroy Kuhn, J.M. ; Peter, A. ; Irmler, M. ; Tokarz, J. ; Prehn, C. ; Kastenmüller, G. ; Beckers, J. ; Adamski, J. ; Königsrainer, A. ; Müller, T.D. ; Heni, M. ; Tschöp, M.H. ; Pfluger, P.T. ; Lutter, D.
Mol. Metab. 53, 101295 (2021)
Technological advances have brought a steady increase in the availability of various types of omics data, from genomics to metabolomics. Integrating these multi-omics data is a chance and challenge for systems biology, yet tools to fully tap their potential remain scarce. We here present a fully unsupervised and versatile correlation-based method, termed Correlation guided Network Integration (CoNI), to integrate multi-omics data into a hypergraph structure that allows for the identification of effective modulators of metabolism. Our approach yields single transcripts of potential relevance that map to specific, densely connected metabolic sub-graphs or pathways. By applying our method on transcriptomics and metabolomics data from murine livers under standard Chow or high-fat diet, we identified eleven genes with potential regulatory effects on hepatic metabolism. Five candidates, including the hepatokine INHBE, were validated in human liver biopsies to correlate with diabetes-related traits such as overweight, hepatic fat content, and insulin resistance (HOMA-IR). Our method's successful application to an independent omics dataset confirmed that the novel CoNI framework is a transferable, entirely data-driven, flexible, and versatile tool for multiple omics data integration and interpretation.
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Scientific Article
Ahookhosh, K. ; Saidi, M. ; Mohammadpourfard, M. ; Aminfar, H. ; Hamishehkar, H. ; Farnoud, A. ; Schmid, O.
Eur. J. Pharm. Sci. 164:105911 (2021)
Inhalation therapy plays an important role in management or treatment of respiratory diseases such asthma and chronic obstructive pulmonary diseases (COPDs). For decades, pressurized metered dose inhalers (pMDIs) have been the most popular and prescribed drug delivery devices for inhalation therapy. The main objectives of the present computational work are to study flow structure inside a pMDI, as well as transport and deposition of micron-sized particles in a model of human tracheobronchial airways and their dependence on inhalation air flow rate and characteristic pMDI parameters. The upper airway geometry, which includes the extrathoracic region, trachea, and bronchial airways up to the fourth generation in some branches, was constructed based on computed tomography (CT) images of an adult healthy female. Computational fluid dynamics (CFD) simulation was employed using the k-ω model with low-Reynolds number (LRN) corrections to accomplish the objectives. The deposition results of the present study were verified with the in vitro deposition data of our previous investigation on pulmonary drug delivery using a hollow replica of the same airway geometry as used for CFD modeling. It was found that the flow structure inside the pMDI and extrathoracic region strongly depends on inhalation flow rate and geometry of the inhaler. In addition, regional aerosol deposition patterns were investigated at four inhalation flow rates between 30 and 120 L/min and for 60 L/min yielding highest deposition fractions of 24.4% and 3.1% for the extrathoracic region (EX) and the trachea, respectively. It was also revealed that particle deposition was larger in the right branches of the bronchial airways (right lung) than the left branches (left lung) for all of the considered cases. Also, optimization of spray characteristics showed that the optimum values for initial spray velocity, spray cone angle and spray duration were 100 m/s, 10∘ and 0.1 sec, respectively. Moreover, spray cone angle, more than any other of the investigated pMDI parameters can change the deposition pattern of inhaled particles in the airway model. In conclusion, the present investigation provides a validated CFD model for particle deposition and new insights into the relevance of flow structure for deposition of pMDI-emitted pharmaceutical aerosols in the upper respiratory tract.
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Scientific Article
Portero, V. ; Nicol, T. ; Podliesna, S. ; Marchal, G.A. ; Baartscheer, A. ; Casini, S. ; Tadros, R. ; Treur, J.L. ; Tanck, M.W.T. ; Cox, I.J. ; Probert, F. ; Hough, T.A. ; Falcone, S. ; Beekman, L. ; Müller-Nurasyid, M. ; Kastenmüller, G. ; Gieger, C. ; Peters, A. ; Kääb, S. ; Sinner, M.F. ; Blease, A. ; Verkerk, A.O. ; Bezzina, C.R. ; Potter, P.K. ; Remme, C.A.
Cardiovasc. Res. 118:1742–1757 (2021)
AIM: Cardiac arrhythmias comprise a major health and economic burden and are associated with significant morbidity and mortality, including cardiac failure, stroke and sudden cardiac death (SCD). Development of efficient preventive and therapeutic strategies is hampered by incomplete knowledge of disease mechanisms and pathways. Our aim is to identify novel mechanisms underlying cardiac arrhythmia and SCD using an unbiased approach. METHODS AND RESULTS: We employed a phenotype-driven N-ethyl-N-nitrosourea (ENU) mutagenesis screen and identified a mouse line with a high incidence of sudden death at young age (6-9 weeks) in the absence of prior symptoms. Affected mice were found to be homozygous for the nonsense mutation Bcat2p.Q300*/p.Q300* in the Bcat2 gene encoding branched chain amino acid transaminase 2. At the age of 4-5 weeks, Bcat2p.Q300*/p.Q300* mice displayed drastic increase of plasma levels of branch chain amino acids (BCAAs - leucine, isoleucine, valine) due to the incomplete catabolism of BCAAs, in addition to inducible arrhythmias ex vivo as well as cardiac conduction and repolarization disturbances. In line with these findings, plasma BCAA levels were positively correlated to ECG indices of conduction and repolarization in the German community-based KORA F4 Study. Isolated cardiomyocytes from Bcat2p.Q300*/p.Q300* mice revealed action potential (AP) prolongation, pro-arrhythmic events (early and late afterdepolarizations, triggered APs) and dysregulated calcium homeostasis. Incubation of human pluripotent stem cell-derived cardiomyocytes with elevated concentration of BCAAs induced similar calcium dysregulation and pro-arrhythmic events which were prevented by rapamycin, demonstrating the crucial involvement of mTOR pathway activation. CONCLUSIONS: Our findings identify for the first time a causative link between elevated BCAAs and arrhythmia, which has implications for arrhythmogenesis in conditions associated with BCAA metabolism dysregulation such as diabetes, metabolic syndrome and heart failure. TRANSLATIONAL PERSPECTIVES: Development of efficient anti-arrhythmic strategies is hampered by incomplete knowledge of disease mechanisms. Using an unbiased approach, we here identified for the first time a pro-arrhythmic effect of increased levels of branched chain amino acids (BCAAs). This is of particular relevance for conditions associated with BCAA dysregulation and increased arrhythmia risk, including heart failure, obesity and diabetes, as well as for athletes supplementing their diet with BCAAs. Such metabolic dysregulation is potentially modifiable through dietary interventions, paving the way for novel preventive strategies. Our findings furthermore identify mTOR inhibition as a potential anti-arrhythmic strategy in patients with metabolic syndrome.
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Scientific Article
Schranner, D. ; Schönfelder, M. ; Römisch-Margl, W. ; Scherr, J. ; Schlegel, J. ; Zelger, O. ; Riermeier, A. ; Kaps, S. ; Prehn, C. ; Adamski, J. ; Söhnlein, Q. ; Stocker, F. ; Kreuzpointner, F. ; Halle, M. ; Kastenmüller, G. ; Wackerhage, H.
Physiol. Rep. 9:e14885 (2021)
Human metabolism is highly variable. At one end of the spectrum, defects of enzymes, transporters, and metabolic regulation result in metabolic diseases such as diabetes mellitus or inborn errors of metabolism. At the other end of the spectrum, favorable genetics and years of training combine to result in physiologically extreme forms of metabolism in athletes. Here, we investigated how the highly glycolytic metabolism of sprinters, highly oxidative metabolism of endurance athletes, and highly anabolic metabolism of natural bodybuilders affect their serum metabolome at rest and after a bout of exercise to exhaustion. We used targeted mass spectrometry-based metabolomics to measure the serum concentrations of 151 metabolites and 43 metabolite ratios or sums in 15 competitive male athletes (6 endurance athletes, 5 sprinters, and 4 natural bodybuilders) and 4 untrained control subjects at fasted rest and 5 minutes after a maximum graded bicycle test to exhaustion. The analysis of all 194 metabolite concentrations, ratios and sums revealed that natural bodybuilders and endurance athletes had overall different metabolite profiles, whereas sprinters and untrained controls were more similar. Specifically, natural bodybuilders had 1.5 to 1.8-fold higher concentrations of specific phosphatidylcholines and lower levels of branched chain amino acids than all other subjects. Endurance athletes had 1.4-fold higher levels of a metabolite ratio showing the activity of carnitine-palmitoyl-transferase I and 1.4-fold lower levels of various alkyl-acyl-phosphatidylcholines. When we compared the effect of exercise between groups, endurance athletes showed 1.3-fold higher increases of hexose and of tetradecenoylcarnitine (C14:1). In summary, physiologically extreme metabolic capacities of endurance athletes and natural bodybuilders are associated with unique blood metabolite concentrations, ratios, and sums at rest and after exercise. Our results suggest that long-term specific training, along with genetics and other athlete-specific factors systematically change metabolite concentrations at rest and after exercise.
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Scientific Article
Ji, Y. ; Lotfollahi, M. ; Wolf, F.A. ; Theis, F.J.
Cell Syst. 12, 522-537 (2021)
Cell biology is fundamentally limited in its ability to collect complete data on cellular phenotypes and the wide range of responses to perturbation. Areas such as computer vision and speech recognition have addressed this problem of characterizing unseen or unlabeled conditions with the combined advances of big data, deep learning, and computing resources in the past 5 years. Similarly, recent advances in machine learning approaches enabled by single-cell data start to address prediction tasks in perturbation response modeling. We first define objectives in learning perturbation response in single-cell omics; survey existing approaches, resources, and datasets (https://github.com/theislab/sc-pert); and discuss how a perturbation atlas can enable deep learning models to construct an informative perturbation latent space. We then examine future avenues toward more powerful and explainable modeling using deep neural networks, which enable the integration of disparate information sources and an understanding of heterogeneous, complex, and unseen systems.
Review
Review
Lesch, S. ; Blumenberg, V. ; Stoiber, S. ; Gottschlich, A. ; Ogonek, J. ; Cadilha, B.L. ; Dantes, Z. ; Rataj, F. ; Dorman, K. ; Lutz, J. ; Karches, C.H. ; Heise, C. ; Kurzay, M. ; Larimer, B.M. ; Grassmann, S. ; Rapp, M. ; Nottebrock, A. ; Krüger, S. ; Tokarew, N. ; Metzger, P. ; Hoerth, C. ; Benmebarek, M.R. ; Dhoqina, D. ; Grünmeier, R. ; Seifert, M. ; Oener, A. ; Umut, Ö. ; Joaquina, S. ; Vimeux, L. ; Tran, T. ; Hank, T. ; Baba, T. ; Huynh, D. ; Megens, R.T.A. ; Janssen, K.P. ; Jastroch, M. ; Lamp, D. ; Ruehland, S. ; Di Pilato, M. ; Pruessmann, J.N. ; Thomas, M. ; Marr, C. ; Ormanns, S. ; Reischer, A. ; Hristov, M. ; Tartour, E. ; Donnadieu, E. ; Rothenfußer, S. ; Duewell, P. ; König, L.M. ; Schnurr, M. ; Subklewe, M. ; Liss, A.S. ; Halama, N. ; Reichert, M. ; Mempel, T.R. ; Endres, S. ; Kobold, S.
Nat. Bio. Eng. 5, 1246-1260 (2021)
The efficacy of adoptive cell therapy for solid tumours is hampered by the poor accumulation of the transferred T cells in tumour tissue. Here, we show that forced expression of C-X-C chemokine receptor type 6 (whose ligand is highly expressed by human and murine pancreatic cancer cells and tumour-infiltrating immune cells) in antigen-specific T cells enhanced the recognition and lysis of pancreatic cancer cells and the efficacy of adoptive cell therapy for pancreatic cancer. In mice with subcutaneous pancreatic tumours treated with T cells with either a transgenic T-cell receptor or a murine chimeric antigen receptor targeting the tumour-associated antigen epithelial cell adhesion molecule, and in mice with orthotopic pancreatic tumours or patient-derived xenografts treated with T cells expressing a chimeric antigen receptor targeting mesothelin, the T cells exhibited enhanced intratumoral accumulation, exerted sustained anti-tumoral activity and prolonged animal survival only when co-expressing C-X-C chemokine receptor type 6. Arming tumour-specific T cells with tumour-specific chemokine receptors may represent a promising strategy for the realization of adoptive cell therapy for solid tumours.
Wissenschaftlicher Artikel
Scientific Article
Glauche, I. ; Marr, C.
Curr. Opin. Syst. Biol. 28, 100355 (2021)
Billions of functionally distinct blood cells emerge from a pool of hematopoietic stem cells in our bodies every day. This progressive differentiation process is hierarchically structured and remarkably robust. We provide an introductory review to mathematical approaches addressing the functional aspects of how lineage choice is potentially implemented on a molecular level. Emerging from studies on the mutual repression of key transcription factors we illustrate how those simple concepts have been challenged in recent years and subsequently extended. Especially the analysis of omics data on the single cell level with computational tools provide descriptive insights on a yet unknown level, while their embedding into a consistent mechanistic and mathematical framework is still incomplete.
Review
Review
Bauer, A. ; Zierer, A. ; Gieger, C. ; Büyüközkan, M. ; Müller-Nurasyid, M. ; Grallert, H. ; Meisinger, C. ; Strauch, K. ; Prokisch, H. ; Roden, M. ; Peters, A. ; Krumsiek, J. ; Herder, C. ; Koenig, W. ; Thorand, B. ; Huth, C.
Genet. Epidemiol. 45, 633-650 (2021)
It is still unclear how genetic information, provided as single-nucleotide polymorphisms (SNPs), can be most effectively integrated into risk prediction models for coronary heart disease (CHD) to add significant predictive value beyond clinical risk models. For the present study, a population-based case-cohort was used as a trainingset (451 incident cases, 1488 noncases) and an independent cohort as testset (160 incident cases, 2749 noncases). The following strategies to quantify genetic information were compared: A weighted genetic risk score including Metabochip SNPs associated with CHD in the literature (GRSMetabo ); selection of the most predictive SNPs among these literature-confirmed variants using priority-Lasso (PLMetabo ); validation of two comprehensive polygenic risk scores: GRSGola based on Metabochip data, and GRSKhera (available in the testset only) based on cross-validated genome-wide genotyping data. We used Cox regression to assess associations with incident CHD. C-index, category-free net reclassification index (cfNRI) and relative integrated discrimination improvement (IDIrel ) were used to quantify the predictive performance of genetic information beyond Framingham risk score variables. In contrast to GRSMetabo and PLMetabo , GRSGola significantly improved the prediction (delta C-index [95% confidence interval]: 0.0087 [0.0044, 0.0130]; IDIrel : 0.0509 [0.0131, 0.0894]; cfNRI improved only in cases: 0.1761 [0.0253, 0.3219]). GRSKhera yielded slightly worse prediction results than GRSGola .
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Scientific Article
Boniolo, F ; Dorigatti, E. ; Ohnmacht, A. ; Saur, D. ; Schubert, B. ; Menden, M.
Expert Opin. Drug Discov. 16, 991-1007 (2021)
Introduction: Precision medicine is the concept of treating diseases based on environmental factors, lifestyles, and molecular profiles of patients. This approach has been found to increase success rates of clinical trials and accelerate drug approvals. However, current precision medicine applications in early drug discovery use only a handful of molecular biomarkers to make decisions, whilst clinics gear up to capture the full molecular landscape of patients in the near future. This deep multi-omics characterization demands new analysis strategies to identify appropriate treatment regimens, which we envision will be pioneered by artificial intelligence.Areas covered: In this review, the authors discuss the current state of drug discovery in precision medicine and present our vision of how artificial intelligence will impact biomarker discovery and drug design.Expert opinion: Precision medicine is expected to revolutionize modern medicine; however, its traditional form is focusing on a few biomarkers, thus not equipped to leverage the full power of molecular landscapes. For learning how the development of drugs can be tailored to the heterogeneity of patients across their molecular profiles, artificial intelligence algorithms are the next frontier in precision medicine and will enable a fully personalized approach in drug design, and thus ultimately impacting clinical practice.
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Scientific Article
Cadilha, B.L. ; Benmebarek, M.R. ; Dorman, K. ; Oner, A. ; Lorenzini, T. ; Obeck, H. ; Vänttinen, M. ; Pilato, M.D. ; Pruessmann, J.N. ; Stoiber, S. ; Huynh, D. ; Märkl, F. ; Seifert, M. ; Manske, K. ; Suarez-Gosalvez, J. ; Zeng, Y. ; Lesch, S. ; Karches, C.H. ; Heise, C. ; Gottschlich, A. ; Thomas, M. ; Marr, C. ; Zhang, J. ; Pandey, D. ; Feuchtinger, T. ; Subklewe, M. ; Mempel, T.R. ; Endres, S. ; Kobold, S.
Sci. Adv. 7:eabi5781 (2021)
CAR T cell therapy remains ineffective in solid tumors, due largely to poor infiltration and T cell suppression at the tumor site. T regulatory (Treg) cells suppress the immune response via inhibitory factors such as transforming growth factor–β (TGF-β). Treg cells expressing the C-C chemokine receptor 8 (CCR8) have been associated with poor prognosis in solid tumors. We postulated that CCR8 could be exploited to redirect effector T cells to the tumor site while a dominant-negative TGF-β receptor 2 (DNR) can simultaneously shield them from TGF-β. We identified that CCL1 from activated T cells potentiates a feedback loop for CCR8+ T cell recruitment to the tumor site. This sustained and improved infiltration of engineered T cells synergized with TGF-β shielding for improved therapeutic efficacy. Our results demonstrate that addition of CCR8 and DNR into CAR T cells can render them effective in solid tumors.
Wissenschaftlicher Artikel
Scientific Article
Hecker, J.S. ; Hartmann, L. ; Riviere, J. ; Buck, M.C. ; van der Garde, M. ; Rothenberg-Thurley, M. ; Fischer, L. ; Winter, S. ; Ksienzyk, B. ; Ziemann, F. ; Solovey, M. ; Rauner, M. ; Tsourdi, E. ; Sockel, K. ; Schneider, M. ; Kubasch, A.S. ; Nolde, M. ; Hausmann, D. ; Paulus, A.C. ; Lützner, J. ; Roth, A. ; Bassermann, F. ; Spiekermann, K. ; Marr, C. ; Hofbauer, L.C. ; Platzbecker, U. ; Metzeler, K.H. ; Götze, K.S.
Blood 138, 1727-1732 (2021)
Clonal hematopoiesis (CH) is an age-related condition predisposing to blood cancer and cardiovascular disease (CVD). Murine models demonstrate CH-mediated altered immune function and proinflammation. Low-grade inflammation has been implicated in the pathogenesis of osteoarthritis (OA), the main indication for total hip arthroplasty (THA). THA-derived hip bones serve as a major source of 'healthy' hematopoietic cells in experimental hematology. We prospectively investigated frequency and clinical associations of CH in 200 patients without known hematologic disease undergoing THA. Prevalence of CH was 50%, including 77 patients with CH of indeterminate potential (CHIP, defined as somatic variants with allele frequencies [VAF] ≥2%), and 23 patients harboring CH with lower mutation burden (VAF 1-2%). Most commonly mutated genes were DNMT3A (29.5%), TET2 (15.0%) and ASXL1 (3.5%). CHIP significantly associated with lower hemoglobin, higher mean corpuscular volume, prior/present malignant disease, and CVD. Strikingly, we observed a previously unreported association of CHIP with autoimmune diseases (AID; multivariate adjusted odds ratio, 6.6; 95% confidence interval [1.7, 30]; p=0.0081). These findings underscore the association between CH and inflammatory diseases. Our results have considerable relevance for management of patients with OA and AID or mild anemia, and question use of hip bone-derived cells as 'healthy' experimental controls.
Wissenschaftlicher Artikel
Scientific Article
Pacini, G. ; Dunkel, I. ; Mages, N. ; Mutzel, V. ; Timmermann, B. ; Marsico, A. ; Schulz, E.G.
Nat. Commun. 12:3638 (2021)
To ensure dosage compensation between the sexes, one randomly chosen X chromosome is silenced in each female cell in the process of X-chromosome inactivation (XCI). XCI is initiated during early development through upregulation of the long non-coding RNA Xist, which mediates chromosome-wide gene silencing. Cell differentiation, Xist upregulation and gene silencing are thought to be coupled at multiple levels to ensure inactivation of exactly one out of two X chromosomes. Here we perform an integrated analysis of all three processes through allele-specific single-cell RNA-sequencing. Specifically, we assess the onset of random XCI in differentiating mouse embryonic stem cells, and develop dedicated analysis approaches. By exploiting the inter-cellular heterogeneity of XCI onset, we identify putative Xist regulators. Moreover, we show that transient Xist upregulation from both X chromosomes results in biallelic gene silencing right before transitioning to the monoallelic state, confirming a prediction of the stochastic model of XCI. Finally, we show that genetic variation modulates the XCI process at multiple levels, providing a potential explanation for the long-known X-controlling element (Xce) effect, which leads to preferential inactivation of a specific X chromosome in inter-strain crosses. We thus draw a detailed picture of the different levels of regulation that govern the initiation of XCI. The experimental and computational strategies we have developed here will allow us to profile random XCI in more physiological contexts, including primary human cells in vivo.
Wissenschaftlicher Artikel
Scientific Article
Scheibner, K. ; Schirge, S. ; Burtscher, I. ; Büttner, M. ; Sterr, M. ; Yang, D. ; Böttcher, A. ; Ansarullah ; Irmler, M. ; Beckers, J. ; Cernilogar, F.M. ; Schotta, G. ; Theis, F.J. ; Lickert, H.
Nat. Cell Biol. 23, 692-703 (2021)
It is generally accepted that epiblast cells ingress into the primitive streak by epithelial-to-mesenchymal transition (EMT) to give rise to the mesoderm; however, it is less clear how the endoderm acquires an epithelial fate. Here, we used embryonic stem cell and mouse embryo knock‐in reporter systems to combine time-resolved lineage labelling with high-resolution single-cell transcriptomics. This allowed us to resolve the morphogenetic programs that segregate the mesoderm from the endoderm germ layer. Strikingly, while the mesoderm is formed by classical EMT, the endoderm is formed independent of the key EMT transcription factor Snail1 by mechanisms of epithelial cell plasticity. Importantly, forkhead box transcription factor A2 (Foxa2) acts as an epithelial gatekeeper and EMT suppressor to shield the endoderm from undergoing a mesenchymal transition. Altogether, these results not only establish the morphogenetic details of germ layer formation, but also have broader implications for stem cell differentiation and cancer metastasis.
Wissenschaftlicher Artikel
Scientific Article
Iturbide Martinez De Albeniz, A. ; Ruiz Tejada Segura, M.L. ; Noll, C. ; Schorpp, K.K. ; Rothenaigner, I. ; Ruiz-Morales, E.R. ; Lubatti, G. ; Agami, A. ; Hadian, K. ; Scialdone, A. ; Torres-Padilla, M.E.
Nat. Struct. Mol. Biol. 28, 521-532 (2021)
Totipotent cells hold enormous potential for regenerative medicine. Thus, the development of cellular models recapitulating totipotent-like features is of paramount importance. Cells resembling the totipotent cells of early embryos arise spontaneously in mouse embryonic stem (ES) cell cultures. Such ‘2-cell-like-cells’ (2CLCs) recapitulate 2-cell-stage features and display expanded cell potential. Here, we used 2CLCs to perform a small-molecule screen to identify new pathways regulating the 2-cell-stage program. We identified retinoids as robust inducers of 2CLCs and the retinoic acid (RA)-signaling pathway as a key component of the regulatory circuitry of totipotent cells in embryos. Using single-cell RNA-seq, we reveal the transcriptional dynamics of 2CLC reprogramming and show that ES cells undergo distinct cellular trajectories in response to RA. Importantly, endogenous RA activity in early embryos is essential for zygotic genome activation and developmental progression. Overall, our data shed light on the gene regulatory networks controlling cellular plasticity and the totipotency program.
Wissenschaftlicher Artikel
Scientific Article
Warnat-Herresthal, S. ; Schultze, H. ; Shastry, K.L. ; Manamohan, S. ; Mukherjee, S. ; Garg, V. ; Sarveswara, R. ; Händler, K. ; Pickkers, P. ; Aziz, N.A. ; Ktena, S. ; Tran, F. ; Bitzer, M. ; Ossowski, S. ; Casadei, N. ; Herr, C. ; Petersheim, D. ; Behrends, U. ; Kern, F. ; Fehlmann, T. ; Schommers, P. ; Lehmann, C. ; Augustin, M. ; Rybniker, J. ; Altmüller, J. ; Mishra, N. ; Bernardes, J.P. ; Krämer, B.F. ; Bonaguro, L. ; Schulte-Schrepping, J. ; De Domenico, E. ; Siever, C. ; Kraut, M. ; Desai, M. ; Monnet, B. ; Saridaki, M. ; Siegel, C.M. ; Drews, A. ; Nuesch-Germano, M. ; Theis, H. ; Heyckendorf, J. ; Schreiber, S. ; Kim-Hellmuth, S. ; Nattermann, J. ; Skowasch, D. ; Kurth, I. ; Keller, A. ; Bals, R. ; Nürnberg, P. ; Rieß, O. ; Rosenstiel, P. ; Netea, M.G. ; Theis, F.J. ; Backes, M. ; Aschenbrenner, A.C. ; Ulas, T. ; Deutsche COVID-19 Omics Initiative (DeCOI) (De La Rosa Velázquez, I.A.) ; Breteler, M.M.B. ; Giamarellos-Bourboulis, E.J. ; Kox, M. ; Beck, M. ; Cheran, S. ; Woodacre, M.S. ; Lim Goh, E. ; Schultze, J.L.
Nature (2021)
Fast and reliable detection of patients with severe and heterogeneous illnesses is a major goal of precision medicine . Patients with leukaemia can be identified using machine learning on the basis of their blood transcriptomes . However, there is an increasing divide between what is technically possible and what is allowed, because of privacy legislation . Here, to facilitate the integration of any medical data from any data owner worldwide without violating privacy laws, we introduce Swarm Learning—a decentralized machine-learning approach that unites edge computing, blockchain-based peer-to-peer networking and coordination while maintaining confidentiality without the need for a central coordinator, thereby going beyond federated learning. To illustrate the feasibility of using Swarm Learning to develop disease classifiers using distributed data, we chose four use cases of heterogeneous diseases (COVID-19, tuberculosis, leukaemia and lung pathologies). With more than 16,400 blood transcriptomes derived from 127 clinical studies with non-uniform distributions of cases and controls and substantial study biases, as well as more than 95,000 chest X-ray images, we show that Swarm Learning classifiers outperform those developed at individual sites. In addition, Swarm Learning completely fulfils local confidentiality regulations by design. We believe that this approach will notably accelerate the introduction of precision medicine. 1,2 3 4,5
Wissenschaftlicher Artikel
Scientific Article
Brand, I. ; Gilberg, L. ; Bruger, J. ; Garí, M. ; Wieser, A. ; Eser, T.M. ; Frese, J. ; Ahmed, M.I.M. ; Rubio-Acero, R. ; Guggenbüehl Noller, J.M. ; Castelletti, N. ; Diekmannshemke, J. ; Thiesbrummel, S. ; Huynh, D. ; Winter, S. ; Kroidl, I. ; Fuchs, C. ; Hoelscher, M. ; Roider, J. ; Kobold, S. ; Pritsch, M. ; Geldmacher, C.
Front. Immunol. 12:688436 (2021)
Background: Adaptive immune responses to structural proteins of the virion play a crucial role in protection against coronavirus disease 2019 (COVID-19). We therefore studied T cell responses against multiple SARS-CoV-2 structural proteins in a large cohort using a simple, fast, and high-throughput approach. Methods: An automated interferon gamma release assay (IGRA) for the Nucleocapsid (NC)-, Membrane (M)-, Spike-C-terminus (SCT)-, and N-terminus-protein (SNT)-specific T cell responses was performed using fresh whole blood from study subjects with convalescent, confirmed COVID-19 (n = 177, more than 200 days post infection), exposed household members (n = 145), and unexposed controls (n = 85). SARS-CoV-2-specific antibodies were assessed using Elecsys® Anti-SARS-CoV-2 (Ro-N-Ig) and Anti-SARS-CoV-2-ELISA (IgG) (EI-S1-IgG). Results: 156 of 177 (88%) previously PCR confirmed cases were still positive by Ro-N-Ig more than 200 days after infection. In T cells, most frequently the M-protein was targeted by 88% seropositive, PCR confirmed cases, followed by SCT (85%), NC (82%), and SNT (73%), whereas each of these antigens was recognized by less than 14% of non-exposed control subjects. Broad targeting of these structural virion proteins was characteristic of convalescent SARS-CoV-2 infection; 68% of all seropositive individuals targeted all four tested antigens. Indeed, anti-NC antibody titer correlated loosely, but significantly with the magnitude and breadth of the SARS-CoV-2-specific T cell response. Age, sex, and body mass index were comparable between the different groups. Conclusion: SARS-CoV-2 seropositivity correlates with broad T cell reactivity of the structural virus proteins at 200 days after infection and beyond. The SARS-CoV-2-IGRA can facilitate large scale determination of SARS-CoV-2-specific T cell responses with high accuracy against multiple targets.
Wissenschaftlicher Artikel
Scientific Article
Zacharias, H.U. ; Hertel, J. ; Johar, H. ; Pietzner, M. ; Lukaschek, K. ; Atasoy, S. ; Kunze, S. ; Völzke, H. ; Nauck, M. ; Friedrich, N. ; Kastenmüller, G. ; Grabe, H.J. ; Gieger, C. ; Krumsiek, J. ; Ladwig, K.-H.
Mol. Psychiatry 26, 7372–7383 (2021)
Depression constitutes a leading cause of disability worldwide. Despite extensive research on its interaction with psychobiological factors, associated pathways are far from being elucidated. Metabolomics, assessing the final products of complex biochemical reactions, has emerged as a valuable tool for exploring molecular pathways. We conducted a metabolome-wide association analysis to investigate the link between the serum metabolome and depressed mood (DM) in 1411 participants of the KORA (Cooperative Health Research in the Augsburg Region) F4 study (discovery cohort). Serum metabolomics data comprised 353 unique metabolites measured by Metabolon. We identified 72 (5.1%) KORA participants with DM. Linear regression tests were conducted modeling each metabolite value by DM status, adjusted for age, sex, body-mass index, antihypertensive, cardiovascular, antidiabetic, and thyroid gland hormone drugs, corticoids and antidepressants. Sensitivity analyses were performed in subcohorts stratified for sex, suicidal ideation, and use of antidepressants. We replicated our results in an independent sample of 968 participants of the SHIP-Trend (Study of Health in Pomerania) study including 52 (5.4%) individuals with DM (replication cohort). We found significantly lower laurylcarnitine levels in KORA F4 participants with DM after multiple testing correction according to Benjamini/Hochberg. This finding was replicated in the independent SHIP-Trend study. Laurylcarnitine remained significantly associated (p value < 0.05) with depression in samples stratified for sex, suicidal ideation, and antidepressant medication. Decreased blood laurylcarnitine levels in depressed individuals may point to impaired fatty acid oxidation and/or mitochondrial function in depressive disorders, possibly representing a novel therapeutic target.
Wissenschaftlicher Artikel
Scientific Article
Stadler, M. ; Doebler, P. ; Mertins, B. ; Delucchi Danhier, R.
Behav. Res. Methods 53, 2650-2667 (2021)
This paper presents a model that allows group comparisons of gaze behavior while watching dynamic video stimuli. The model is based on the approach of Coutrot and Guyader (2017) and allows linear combinations of feature maps to form a master saliency map. The feature maps in the model are, for example, the dynamically salient contents of a video stimulus or predetermined areas of interest. The model takes into account temporal aspects of the stimuli, which is a crucial difference to other common models. The multi-group extension of the model introduced here allows to obtain relative importance plots, which visualize the effect of a specific feature of a stimulus on the attention and visual behavior for two or more experimental groups. These plots are interpretable summaries of data with high spatial and temporal resolution. This approach differs from many common methods for comparing gaze behavior between natural groups, which usually only include single-dimensional features such as the duration of fixation on a particular part of the stimulus. The method is illustrated by contrasting a sample of a group of persons with particularly high cognitive abilities (high achievement on IQ tests) with a control group on a psycholinguistic task on the conceptualization of motion events. In the example, we find no substantive differences in relative importance, but more exploratory gaze behavior in the highly gifted group. The code, videos, and eye-tracking data we used for this study are available online.
Wissenschaftlicher Artikel
Scientific Article
von Streitberg, A. ; Jäkel, S. ; Eugenin von Bernhardi, J. ; Straube, C. ; Buggenthin, F. ; Marr, C. ; Dimou, L.
Front. Cell Dev. Biol. 9:662056 (2021)
In the adult brain, NG2-glia represent a cell population that responds to injury. To further investigate if, how and why NG2-glia are recruited to the injury site, we analyzed in detail the long-term reaction of NG2-glia after a lesion by time-lapse two-photon in vivo microscopy. Live imaging over several weeks of GFP-labeled NG2-glia in the stab wounded cerebral cortex revealed their fast and heterogeneous reaction, including proliferation, migration, polarization, hypertrophy, or a mixed response, while a small subset of cells remained unresponsive. At the peak of the reaction, 2-4 days after the injury, NG2-glia accumulated around and within the lesion core, overcoming the homeostatic control of their density, which normalized back to physiological conditions only 4 weeks after the insult. Genetic ablation of proliferating NG2-glia demonstrated that this accumulation contributed beneficially to wound closure. Thus, NG2-glia show a fast response to traumatic brain injury (TBI) and participate in tissue repair.
Wissenschaftlicher Artikel
Scientific Article
Esteve-Codina, A. ; Hofer, T.P. ; Burggraf, D. ; Heiss-Neumann, M.S. ; Gesierich, W. ; Boland, A. ; Olaso, R. ; Bihoreau, M.T. ; Deleuze, J.F. ; Möller, W. ; Schmid, O. ; Soler Artigas, M. ; Renner, K. ; Hohlfeld, J.M. ; Welte, T. ; Fuehner, T. ; Jerrentrup, L. ; Koczulla, A.R. ; Greulich, T. ; Prasse, A. ; Müller-Quernheim, J. ; Gupta, S. ; Brightling, C. ; Subramanian, D.R. ; Parr, D.G. ; Kolsum, U. ; Gupta, V. ; Barta, I. ; Döme, B. ; Strausz, J. ; Stendardo, M. ; Piattella, M. ; Boschetto, P. ; Korzybski, D. ; Gorecka, D. ; Nowinski, A. ; Dabad, M. ; Fernández-Callejo, M. ; Endesfelder, D. ; zu Castell, W. ; Hiemstra, P.S. ; Venge, P. ; Nößner, E. ; Griebel, T. ; Heath, S. ; Singh, D. ; Gut, I. ; Ziegler-Heitbrock, L.
Sci. Rep. 11:12848 (2021)
Chronic obstructive pulmonary disease (COPD) is a destructive inflammatory disease and the genes expressed within the lung are crucial to its pathophysiology. We have determined the RNAseq transcriptome of bronchial brush cells from 312 stringently defined ex-smoker patients. Compared to healthy controls there were for males 40 differentially expressed genes (DEGs) and 73 DEGs for females with only 26 genes shared. The gene ontology (GO) term "response to bacterium" was shared, with several different DEGs contributing in males and females. Strongly upregulated genes TCN1 and CYP1B1 were unique to males and females, respectively. For male emphysema (E)-dominant and airway disease (A)-dominant COPD (defined by computed tomography) the term "response to stress" was found for both sub-phenotypes, but this included distinct up-regulated genes for the E-sub-phenotype (neutrophil-related CSF3R, CXCL1, MNDA) and for the A-sub-phenotype (macrophage-related KLF4, F3, CD36). In E-dominant disease, a cluster of mitochondria-encoded (MT) genes forms a signature, able to identify patients with emphysema features in a confirmation cohort. The MT-CO2 gene is upregulated transcriptionally in bronchial epithelial cells with the copy number essentially unchanged. Both MT-CO2 and the neutrophil chemoattractant CXCL1 are induced by reactive oxygen in bronchial epithelial cells. Of the female DEGs unique for E- and A-dominant COPD, 88% were detected in females only. In E-dominant disease we found a pronounced expression of mast cell-associated DEGs TPSB2, TPSAB1 and CPA3. The differential genes discovered in this study point towards involvement of different types of leukocytes in the E- and A-dominant COPD sub-phenotypes in males and females.
Wissenschaftlicher Artikel
Scientific Article
Schubert, B. ; Dorigatti, E. ; Felix, D.
Vortrag: ISMB/ECCB, 25-30 July 2021, virtual. (2021)
Wang, S.-H. ; Zissler, U.M. ; Büttner, M. ; Heine, S. ; Heldner, A. ; Kotz, S. ; Pechtold, L. ; Kau, J. ; Plaschke, M. ; Ullmann, J.T. ; Guerth, F. ; Oelsner, M. ; Alessandrini, F. ; Blank, S. ; Chaker, A. ; Schmidt-Weber, C.B. ; Jakwerth, C.A.
Allergy 76, 2827-2839 (2021)
BACKGROUND: Studies show that proallergic TH 2-cells decrease after successful allergen-specific immunotherapy (AIT). It is likely that iatrogenic administration of allergens drives these cells to exhaustion due to chronic T cell receptor stimulation. This study aimed to investigate the exhaustion of T cells in connection with allergenexposure during AIT in mice and two independent patient cohorts. METHODS: OVA-sensitized C57BL/6J mice were challenged and treated with OVA, and the development of exhaustion inlocal and systemic TH 2-cells was analyzed.In patients, the expression of exhaustion-associated surface markers on TH 2-cells was evaluated using flow cytometry in a cross-sectional grass pollen allergy cohort with and without AIT.The treatment effect was further studied in PBMC collected from a prospective long-termAIT cohort. RESULTS: The exhaustion-associated surface markers CTLA-4 and PD-1 were significantly upregulated on TH 2-cells upon OVA aerosol exposure in OVA-allergic compared to non-allergic mice. CTLA-4 and PD-1decreased after AIT, in particular on the surface oflocal lung TH 2-cells. Similarly, CTLA-4 and PD-1 expression were enhanced on TH 2-cells from patients with allergic rhinitis with an even stronger effect in those with concomitant asthma. Using an unbiased Louvain clustering analysis, we discoveredalate-differentiated TH 2 population expressing both markers that decreased during up-dosing but persisted long-term during the maintenance phase. CONCLUSIONS: This study shows that allergen exposure promotes CTLA-4 and PD-1 expression onTH 2-cells, andthat the dynamic change in frequencies of exhausted TH 2-cells exhibits a differential pattern during the up-dosing versus the maintenance phases of AIT.
Wissenschaftlicher Artikel
Scientific Article
Giacopelli, B. ; Wang, M. ; Cleary, A. ; Wu, Y.Z. ; Schultz, A.R. ; Schmutz, M. ; Blachly, J.S. ; Eisfeld, A.K. ; Mundy-Bosse, B. ; Vosberg, S. ; Greif, P.A. ; Claus, R. ; Bullinger, L. ; Garzon, R. ; Coombes, K.R. ; Bloomfield, C.D. ; Druker, B.J. ; Tyner, J.W. ; Byrd, J.C. ; Oakes, C.C.
Genome Res. 31, 747-761 (2021)
Acute myeloid leukemia (AML) is a molecularly complex disease characterized by heterogeneous tumor genetic profiles and involving numerous pathogenic mechanisms and pathways. Integration of molecular data types across multiple patient cohorts may advance current genetic approaches for improved subclassification and understanding of the biology of the disease. Here, we analyzed genome-wide DNA methylation in 649 AML patients using Illumina arrays and identified a configuration of 13 subtypes (termed "epitypes") using unbiased clustering. Integration of genetic data revealed that most epitypes were associated with a certain recurrent mutation (or combination) in a majority of patients, yet other epitypes were largely independent. Epitypes showed developmental blockage at discrete stages of myeloid differentiation, revealing epitypes that retain arrested hematopoietic stem-cell-like phenotypes. Detailed analyses of DNA methylation patterns identified unique patterns of aberrant hyper- and hypomethylation among epitypes, with variable involvement of transcription factors influencing promoter, enhancer, and repressed regions. Patients in epitypes with stem-cell-like methylation features showed inferior overall survival along with up-regulated stem cell gene expression signatures. We further identified a DNA methylation signature involving STAT motifs associated with FLT3-ITD mutations. Finally, DNA methylation signatures were stable at relapse for the large majority of patients, and rare epitype switching accompanied loss of the dominant epitype mutations and reversion to stem-cell-like methylation patterns. These results show that DNA methylation-based classification integrates important molecular features of AML to reveal the diverse pathogenic and biological aspects of the disease.
Wissenschaftlicher Artikel
Scientific Article
Denkena, J. ; Johannes, F. ; Colomé-Tatché, M.
Heredity 127, 190–202 (2021)
Failure to maintain DNA methylation patterns during plant development can occasionally give rise to so-called “spontaneous epimutations”. These stochastic methylation changes are sometimes heritable across generations and thus accumulate in plant genomes over time. Recent evidence indicates that spontaneous epimutations have a major role in shaping patterns of methylation diversity in plant populations. Using single CG dinucleotides as units of analysis, previous work has shown that the epimutation rate is several orders of magnitude higher than the genetic mutation rate. While these large rate differences have obvious implications for understanding genome-methylome co-evolution, the functional relevance of single CG methylation changes remains questionable. In contrast to single CG, solid experimental evidence has linked methylation gains and losses in larger genomic regions with transcriptional variation and heritable phenotypic effects. Here we show that such region-level changes arise stochastically at about the same rate as those at individual CG sites, are only marginal dependent on region size and cytosine density, but strongly dependent on chromosomal location. We also find consistent evidence that region-level epimutations are not restricted to CG contexts but also frequently occur in non-CG regions at the genome-wide scale. Taken together, our results support the view that many differentially methylated regions (DMRs) in natural populations originate from epimutation events and may not be effectively tagged by proximal SNPs. This possibility reinforces the need for epigenome-wide association studies (EWAS) in plants as a way to identify the epigenetic basis of complex traits.
Wissenschaftlicher Artikel
Scientific Article
Akagi, G. ; Melchionna, S. ; Stefanelli, U.
J. evol. equ. 21, 5203-5207 (2021)
In our paper [2], strong solutions of the Cauchy problem for the doubly nonlinear gradient flow posed on the dual space V* of a uniformly convex Banach space V.
Dieckmann, M.A. ; Beyvers, S. ; Nkouamedjo-Fankep, R.C. ; Hanel, P. ; Jelonek, L. ; Blom, J. ; Goesmann, A.
Nucleic Acids Res. 49, W185-W192 (2021)
The EDGAR platform, a web server providing databases of precomputed orthology data for thousands of microbial genomes, is one of the most established tools in the field of comparative genomics and phylogenomics. Based on precomputed gene alignments, EDGAR allows quick identification of the differential gene content, i.e. the pan genome, the core genome, or singleton genes. Furthermore, EDGAR features a wide range of analyses and visualizations like Venn diagrams, synteny plots, phylogenetic trees, as well as Amino Acid Identity (AAI) and Average Nucleotide Identity (ANI) matrices. During the last few years, the average number of genomes analyzed in an EDGAR project increased by two orders of magnitude. To handle this massive increase, a completely new technical backend infrastructure for the EDGAR platform was designed and launched as EDGAR3.0. For the calculation of new EDGAR3.0 projects, we are now using a scalable Kubernetes cluster running in a cloud environment. A new storage infrastructure was developed using a file-based high-performance storage backend which ensures timely data handling and efficient access. The new data backend guarantees a memory efficient calculation of orthologs, and parallelization has led to drastically reduced processing times. Based on the advanced technical infrastructure new analysis features could be implemented including POCP and FastANI genomes similarity indices, UpSet intersecting set visualization, and circular genome plots. Also the public database section of EDGAR was largely updated and now offers access to 24,317 genomes in 749 free-to-use projects. In summary, EDGAR 3.0 provides a new, scalable infrastructure for comprehensive microbial comparative gene content analysis. The web server is accessible at http://edgar3.computational.bio.
Wissenschaftlicher Artikel
Scientific Article
Klinger, E. ; Motta, A. ; Marr, C. ; Theis, F.J. ; Helmstaedter, M.
Nat. Commun. 12:2785 (2021)
With the availability of cellular-resolution connectivity maps, connectomes, from the mammalian nervous system, it is in question how informative such massive connectomic data can be for the distinction of local circuit models in the mammalian cerebral cortex. Here, we investigated whether cellular-resolution connectomic data can in principle allow model discrimination for local circuit modules in layer 4 of mouse primary somatosensory cortex. We used approximate Bayesian model selection based on a set of simple connectome statistics to compute the posterior probability over proposed models given a to-be-measured connectome. We find that the distinction of the investigated local cortical models is faithfully possible based on purely structural connectomic data with an accuracy of more than 90%, and that such distinction is stable against substantial errors in the connectome measurement. Furthermore, mapping a fraction of only 10% of the local connectome is sufficient for connectome-based model distinction under realistic experimental constraints. Together, these results show for a concrete local circuit example that connectomic data allows model selection in the cerebral cortex and define the experimental strategy for obtaining such connectomic data.
Wissenschaftlicher Artikel
Scientific Article
Loureiro, H. ; Becker, T. ; Bauer-Mehren, A. ; Ahmidi, N. ; Weberpals, J.
Front. Artif. Intell. 4:625573 (2021)
Introduction: Prognostic scores are important tools in oncology to facilitate clinical decision-making based on patient characteristics. To date, classic survival analysis using Cox proportional hazards regression has been employed in the development of these prognostic scores. With the advance of analytical models, this study aimed to determine if more complex machine-learning algorithms could outperform classical survival analysis methods. Methods: In this benchmarking study, two datasets were used to develop and compare different prognostic models for overall survival in pan-cancer populations: a nationwide EHR-derived de-identified database for training and in-sample testing and the OAK (phase III clinical trial) dataset for out-of-sample testing. A real-world database comprised 136K first-line treated cancer patients across multiple cancer types and was split into a 90% training and 10% testing dataset, respectively. The OAK dataset comprised 1,187 patients diagnosed with non-small cell lung cancer. To assess the effect of the covariate number on prognostic performance, we formed three feature sets with 27, 44 and 88 covariates. In terms of methods, we benchmarked ROPRO, a prognostic score based on the Cox model, against eight complex machine-learning models: regularized Cox, Random Survival Forests (RSF), Gradient Boosting (GB), DeepSurv (DS), Autoencoder (AE) and Super Learner (SL). The C-index was used as the performance metric to compare different models. Results: For in-sample testing on the real-world database the resulting C-index [95% CI] values for RSF 0.720 [0.716, 0.725], GB 0.722 [0.718, 0.727], DS 0.721 [0.717, 0.726] and lastly, SL 0.723 [0.718, 0.728] showed significantly better performance as compared to ROPRO 0.701 [0.696, 0.706]. Similar results were derived across all feature sets. However, for the out-of-sample validation on OAK, the stronger performance of the more complex models was not apparent anymore. Consistently, the increase in the number of prognostic covariates did not lead to an increase in model performance. Discussion: The stronger performance of the more complex models did not generalize when applied to an out-of-sample dataset. We hypothesize that future research may benefit by adding multimodal data to exploit advantages of more complex models.
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Storath, M. ; Weinmann, A.
Info. Infern. 10, 195-230 (2021)
In this paper, we consider the variational regularization of manifold-valued data in the inverse problems setting. In particular, we consider total variation and total generalized variation regularization for manifold-valued data with indirect measurement operators. We provide results on the well-posedness and present algorithms for a numerical realization of these models in the manifold setup. Further, we provide experimental results for synthetic and real data to show the potential of the proposed schemes for applications.
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Hummel, S. ; Weiss, A. ; Bonifacio, E. ; Agardh, D. ; Akolkar, B. ; Aronsson, C.A. ; Hagopian, W.A. ; Koletzko, S. ; Krischer, J.P. ; Lernmark, Å. ; Lynch, K. ; Norris, J.M. ; Rewers, M.J. ; She, J.X. ; Toppari, J. ; Uusitalo, U. ; Vehik, K. ; Virtanen, S.M. ; Beyerlein, A. ; Ziegler, A.-G.
Am. J. Clin. Nutr. 114, 134-142 (2021)
BACKGROUND: Breastfeeding has beneficial effects on numerous health outcomes. OBJECTIVES: We investigated whether breastfeeding duration is associated with the development of early childhood autoimmunity, allergies, or obesity in a multinational prospective birth cohort. METHODS: Infants with genetic susceptibility for type 1 diabetes (n = 8676) were followed for the development of autoantibodies to islet autoantigens or transglutaminase, allergies, and for anthropometric measurements to a median age of 8.3 y (IQR: 2.8-10.2 y). Information on breastfeeding was collected at 3 mo of age and prospectively thereafter. A propensity score for longer breastfeeding was calculated from the variables that were likely to influence any or exclusive breastfeeding. The risks of developing autoimmunity or allergy were assessed using Cox proportional hazards models, and the risk of obesity at 5.5 y of age was assessed using logistic regression with adjustment by the propensity score. RESULTS: Breastfeeding duration was not associated with a lower risk of either islet or transglutaminase autoimmunity (any breastfeeding >6 mo, adjusted HR: 1.07; 95% CI: 0.96, 1.19; exclusive breastfeeding >3 mo, adjusted HR: 1.03; 95% CI: 0.92, 1.15). Exclusive breastfeeding >3 mo was associated with a decreased risk of seasonal allergic rhinitis (adjusted HR: 0.70; 95% CI: 0.53, 0.92; P < 0.01). Any breastfeeding >6 mo and exclusive breastfeeding >3 mo were associated with decreased risk of obesity (adjusted OR: 0.62; 95% CI: 0.47, 0.81; P < 0.001; and adjusted OR: 0.68; 95% CI: 0.47, 0.95; P < 0.05, respectively). CONCLUSIONS: Longer breastfeeding was not associated with a lower risk of childhood (islet or transglutaminase) autoimmunity in genetically at-risk children but was associated with decreased risk of seasonal allergic rhinitis and obesity at 5.5 y of age.
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Böttcher, A. ; Büttner, M. ; Tritschler, S. ; Sterr, M. ; Aliluev, A. ; Oppenländer, L. ; Burtscher, I. ; Sass, S. ; Irmler, M. ; Beckers, J. ; Ziegenhain, C. ; Enard, W. ; Schamberger, A.C. ; Verhamme, F.M. ; Eickelberg, O. ; Theis, F.J. ; Lickert, H.
Nat. Cell Biol. 23, 566-576 (2021)
A Correction to this paper has been published: https://doi.org/10.1038/s41556-021-00667-0.
Schulte-Sasse, R. ; Budach, S. ; Hnisz, D. ; Marsico, A.
Nat. Mach. Intell. 3, 513–526 (2021)
The increase in available high-throughput molecular data creates computational challenges for the identification of cancer genes. Genetic as well as non-genetic causes contribute to tumorigenesis, and this necessitates the development of predictive models to effectively integrate different data modalities while being interpretable. We introduce EMOGI, an explainable machine learning method based on graph convolutional networks to predict cancer genes by combining multiomics pan-cancer data—such as mutations, copy number changes, DNA methylation and gene expression—together with protein–protein interaction (PPI) networks. EMOGI was on average more accurate than other methods across different PPI networks and datasets. We used layer-wise relevance propagation to stratify genes according to whether their classification was driven by the interactome or any of the omics levels, and to identify important modules in the PPI network. We propose 165 novel cancer genes that do not necessarily harbour recurrent alterations but interact with known cancer genes, and we show that they correspond to essential genes from loss-of-function screens. We believe that our method can open new avenues in precision oncology and be applied to predict biomarkers for other complex diseases.
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Schouten, J.P.E. ; Matek, C. ; Jacobs, L.F.P. ; Buck, M.C. ; Bošnački, D. ; Marr, C.
Sci. Rep. 11:7995 (2021)
Convolutional neural networks (CNNs) excel as powerful tools for biomedical image classification. It is commonly assumed that training CNNs requires large amounts of annotated data. This is a bottleneck in many medical applications where annotation relies on expert knowledge. Here, we analyze the binary classification performance of a CNN on two independent cytomorphology datasets as a function of training set size. Specifically, we train a sequential model to discriminate non-malignant leukocytes from blast cells, whose appearance in the peripheral blood is a hallmark of leukemia. We systematically vary training set size, finding that tens of training images suffice for a binary classification with an ROC-AUC over 90%. Saliency maps and layer-wise relevance propagation visualizations suggest that the network learns to increasingly focus on nuclear structures of leukocytes as the number of training images is increased. A low dimensional tSNE representation reveals that while the two classes are separated already for a few training images, the distinction between the classes becomes clearer when more training images are used. To evaluate the performance in a multi-class problem, we annotated single-cell images from a acute lymphoblastic leukemia dataset into six different hematopoietic classes. Multi-class prediction suggests that also here few single-cell images suffice if differences between morphological classes are large enough. The incorporation of deep learning algorithms into clinical practice has the potential to reduce variability and cost, democratize usage of expertise, and allow for early detection of disease onset and relapse. Our approach evaluates the performance of a deep learning based cytology classifier with respect to size and complexity of the training data and the classification task.
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Ecker, J. ; Benedetti, E. ; Kindt, A. ; Höring, M. ; Perl, M. ; Machmüller, A.C. ; Sichler, A. ; Plagge, J. ; Wang, Y. ; Zeissig, S. ; Shevchenko, A. ; Burkhardt, R. ; Krumsiek, J. ; Liebisch, G. ; Janssen, K.P.
Gastroenterology 161, 910-923.e19 (2021)
OBJECTIVE: Lipidomic changes were causally linked to metabolic diseases, but the scenario for colorectal cancer (CRC) is less clear. We investigated the CRC lipidome for putative tumour-specific alterations through analysis of three independent retrospective patient cohorts from two clinical centers, to derive a clinically useful signature. DESIGN: Quantitative comprehensive lipidomic analysis was performed by direct infusion electrospray ionization coupled to tandem mass spectrometry (ESI-MS/MS) and high-resolution mass spectrometry (HR-MS) on matched non-diseased mucosa and tumor tissue in a discovery cohort (n=106). Results were validated in two independent cohorts (n=28, and n=20), associated with genomic and clinical data, and lipidomic data from a genetic mouse tumor model (Apc1638N). RESULTS: Significant differences were found between tumor and normal tissue for glycero-, glycerophospho- and sphingolipids in the discovery cohort. Comparison to the validation collectives unveiled that glycerophospholipids showed high interpatient variation and were strongly affected by preanalytical conditions, whereas glycero- and sphingolipids appeared more robust. Signatures of sphingomyelin (SM) and triacylglycerol (TG) species significantly differentiated cancerous from non-diseased tissue in both validation studies. Moreover, lipogenic enzymes were significantly upregulated in CRC, and FASN gene expression was prognostically detrimental. The TG profile was significantly associated with post-operative disease-free survival and lymphovascular invasion, and was essentially conserved in murine digestive cancer, but not associated with microsatellite status, KRAS or BRAF mutations, or T-cell infiltration. CONCLUSION: Analysis of the CRC lipidome revealed a robust TG-species signature with prognostic potential. A better understanding of the cancer-associated glycerolipid and sphingolipid metabolism may lead to novel therapeutic strategies.
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Kappelmann, N. ; Czamara, D. ; Rost, N. ; Moser, S. ; Schmoll, V. ; Trastulla, L. ; Stochl, J. ; Lucae, S. ; Binder, E.B. ; Khandaker, G.M. ; Knauer-Arloth, J.
Brain Behav. Immun. 95, 256-268 (2021)
BACKGROUND: About every fourth patient with major depressive disorder (MDD) shows evidence of systemic inflammation. Previous studies have shown inflammation-depression associations of multiple serum inflammatory markers and multiple specific depressive symptoms. It remains unclear, however, if these associations extend to genetic/lifetime predisposition to higher inflammatory marker levels and what role metabolic factors such as Body Mass Index (BMI) play. It is also unclear whether inflammation-symptom associations reflect direct or indirect associations, which can be disentangled using network analysis. METHODS: This study examined associations of polygenic risk scores (PRSs) for immuno-metabolic markers (C-reactive protein [CRP], interleukin [IL]-6, IL-10, tumour necrosis factor [TNF]-α, BMI) with seven depressive symptoms in one general population sample, the UK Biobank study (n=110,010), and two patient samples, the Munich Antidepressant Response Signature (MARS, n=1,058) and Sequenced Treatment Alternatives to Relieve Depression (STAR*D, n=1,143) studies. Network analysis was applied jointly for these samples using fused graphical least absolute shrinkage and selection operator (FGL) estimation as primary analysis and, individually, using unregularized model search estimation. Stability of results was assessed using bootstrapping and three consistency criteria were defined to appraise robustness and replicability of results across estimation methods, network bootstrapping, and samples. RESULTS: Network analysis results displayed to-be-expected PRS-PRS and symptom-symptom associations (termed edges), respectively, that were mostly positive. Using FGL estimation, results further suggested 28, 29, and six PRS-symptom edges in MARS, STAR*D, and UK Biobank samples, respectively. Unregularized model search estimation suggested three PRS-symptom edges in the UK Biobank sample. Applying our consistency criteria to these associations indicated that only the association of higher CRP PRS with greater changes in appetite fulfilled all three criteria. Four additional associations fulfilled at least two consistency criteria; specifically, higher CRP PRS was associated with greater fatigue and reduced anhedonia, higher TNF-α PRS was associated with greater fatigue, and higher BMI PRS with greater changes in appetite and anhedonia. Associations of the BMI PRS with anhedonia, however, showed an inconsistent valence across estimation methods. CONCLUSIONS: Genetic predisposition to higher systemic inflammatory markers are primarily associated with somatic/neurovegetative symptoms of depression such as changes in appetite and fatigue, consistent with previous studies based on circulating levels of inflammatory markers. We extend these findings by providing evidence that associations are direct (using network analysis) and extend to genetic predisposition to immuno-metabolic markers (using PRSs). Our findings can inform selection of patients with inflammation-related symptoms into clinical trials of immune-modulating drugs for MDD.
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Fröhlich, F. ; Weindl, D. ; Schälte, Y. ; Pathirana, D. ; Paszkowski, L. ; Lines, G.T. ; Stapor, P. ; Hasenauer, J.
Bioinformatics 37, 3676-3677 (2021)
SUMMARY: Ordinary differential equation models facilitate the understanding of cellular signal transduction and other biological processes. However, for large and comprehensive models, the computational cost of simulating or calibrating can be limiting. AMICI is a modular toolbox implemented in C ++/Python/MATLAB that provides efficient simulation and sensitivity analysis routines tailored for scalable, gradient-based parameter estimation and uncertainty quantification. AVAILABILITY: AMICI is published under the permissive BSD-3-Clause license with source code publicly available on https://github.com/AMICI-dev/AMICI. Citeable releases are archived on Zenodo. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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Türei, D. ; Valdeolivas, A. ; Gul, L. ; Palacio-Escat, N. ; Klein, M. ; Ivanova, O. ; Ölbei, M. ; Gábor, A. ; Theis, F.J. ; Módos, D. ; Korcsmáros, T. ; Saez-Rodriguez, J.
Mol. Syst. Biol. 17:e9923 (2021)
Molecular knowledge of biological processes is a cornerstone in omics data analysis. Applied to single-cell data, such analyses provide mechanistic insights into individual cells and their interactions. However, knowledge of intercellular communication is scarce, scattered across resources, and not linked to intracellular processes. To address this gap, we combined over 100 resources covering interactions and roles of proteins in inter- and intracellular signaling, as well as transcriptional and post-transcriptional regulation. We added protein complex information and annotations on function, localization, and role in diseases for each protein. The resource is available for human, and via homology translation for mouse and rat. The data are accessible via OmniPath's web service (https://omnipathdb.org/), a Cytoscape plug-in, and packages in R/Bioconductor and Python, providing access options for computational and experimental scientists. We created workflows with tutorials to facilitate the analysis of cell-cell interactions and affected downstream intracellular signaling processes. OmniPath provides a single access point to knowledge spanning intra- and intercellular processes for data analysis, as we demonstrate in applications studying SARS-CoV-2 infection and ulcerative colitis.
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Haffner, I. ; Schierle, K. ; Raimúndez, E. ; Geier, B. ; Maier, D. ; Hasenauer, J. ; Luber, B. ; Walch, A.K. ; Kolbe, K. ; Riera Knorrenschild, J. ; Kretzschmar, A. ; Rau, B. ; Fischer von Weikersthal, L. ; Ahlborn, M. ; Siegler, G. ; Fuxius, S. ; Decker, T. ; Wittekind, C. ; Lordick, F.
J. Clin. Oncol. 39, 1468-1478 (2021)
PURPOSE: Trastuzumab is the only approved targeted drug for first-line treatment of human epidermal growth factor receptor 2-positive (HER2+) metastatic gastric cancer (mGC). However, not all patients respond and most eventually progress. The multicenter VARIANZ study aimed to investigate the background of response and resistance to trastuzumab in mGC. METHODS: Patients receiving medical treatment for mGC were prospectively recruited in 35 German sites and followed for up to 48 months. HER2 status was assessed centrally by immunohistochemistry and chromogenic in situ hybridization. In addition, HER2 gene expression was assessed using qPCR. RESULTS: Five hundred forty-eight patients were enrolled, and 77 had HER2+ mGC by central assessment (14.1%). A high deviation rate of 22.7% between central and local test results was seen. Patients who received trastuzumab for centrally confirmed HER2+ mGC (central HER2+/local HER2+) lived significantly longer as compared with patients who received trastuzumab for local HER2+ but central HER2- mGC (20.5 months, n = 60 v 10.9 months, n = 65; hazard ratio, 0.42; 95% CI, 8.2 to 14.4; P < .001). In the centrally confirmed cohort, significantly more tumor cells stained HER2+ than in the unconfirmed cohort, and the HER2 amplification ratio was significantly higher. A minimum of 40% HER2+ tumor cells and a HER2 amplification ratio of ≥ 3.0 were calculated as optimized thresholds for predicting benefit from trastuzumab. CONCLUSION: Significant discrepancies in HER2 assessment of mGC were found in tumor specimens with intermediate HER2 expression. Borderline HER2 positivity and heterogeneity of HER2 expression should be considered as resistance factors for HER2-targeting treatment of mGC. HER2 thresholds should be reconsidered. Detailed reports with quantification of HER2 expression and amplification levels may improve selection of patients for HER2-directed treatment.
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Ogris, C. ; Hu, Y. ; Knauer-Arloth, J. ; Müller, N.S.
Sci. Rep. 11:6806 (2021)
Constantly decreasing costs of high-throughput profiling on many molecular levels generate vast amounts of multi-omics data. Studying one biomedical question on two or more omic levels provides deeper insights into underlying molecular processes or disease pathophysiology. For the majority of multi-omics data projects, the data analysis is performed level-wise, followed by a combined interpretation of results. Hence the full potential of integrated data analysis is not leveraged yet, presumably due to the complexity of the data and the lacking toolsets. We propose a versatile approach, to perform a multi-level fully integrated analysis: The Knowledge guIded Multi-Omics Network inference approach, KiMONo ( https://github.com/cellmapslab/kimono ). KiMONo performs network inference by using statistical models for combining omics measurements coupled to a powerful knowledge-guided strategy exploiting prior information from existing biological sources. Within the resulting multimodal network, nodes represent features of all input types e.g. variants and genes while edges refer to knowledge-supported and statistically derived associations. In a comprehensive evaluation, we show that our method is robust to noise and exemplify the general applicability to the full spectrum of multi-omics data, demonstrating that KiMONo is a powerful approach towards leveraging the full potential of data sets for detecting biomarker candidates.
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van Cromvoirt, A.M. ; Fenk, S. ; Sadafi, A. ; Melnikova, E.V. ; Lagutkin, D.A. ; Dey, K. ; Petrushanko, I.Y. ; Hegemann, I. ; Goede, J.S. ; Bogdanova, A.
Front. Physiol. 12:639722 (2021)
The ability of red blood cells (RBCs) to transport gases, their lifespan as well as their rheological properties invariably depend on the deformability, hydration, and membrane stability of these cells, which can be measured by Laser optical rotational red cell analyser (Lorrca® Maxsis, RR Mechatronics). The osmoscan mode of Lorrca is currently used in diagnosis of rare anemias in clinical laboratories. However, a broad range of normal values for healthy subjects reduces the sensitivity of this method for diagnosis of mild disease phenotype. In this pilot study, we explored the impact of age and gender of 45 healthy donors, as well as RBC age on the Lorrca indices. Whereas gender did not affect the Lorrca indices in our study, the age donors had a profound effect on the O_hyper parameter. To study the impact of RBC age on the osmoscan parameters, we have isolated low (L)-, medium (M)-, or high (H)- density fractions enriched with young, mature, and senescent RBCs, respectively, and evaluated the influence of RBC age-related properties, such as density, morphology, and redox state, on the osmoscan indices. As before, O_hyper was the most sensitive parameter, dropping markedly with an increase in RBC density and age. Senescence was associated with a decrease in deformability (EI_max) and tolerability to low and high osmolatites (Area). L-fraction was enriched with reticulocytes and cells with high projected area and EMA staining, but also contained a small number of cells small in projected area and most likely, terminally senescent. L-fraction was on average slightly less deformable than mature cells. The cells from the L-fraction produced more oxidants and NO than all other fractions. However, RBCs from the L-fraction contained maximal levels of reduced thiols compared to other fractions. Our study suggests that reference values for O_hyper should be age-stratified, and, most probably, corrected for the average RBC age. Further multi-center study is required to validate these suggestions before implementing them into clinical practice.
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Kretzschmar, M. ; Müller, J.
eLife 10:e67417 (2021)
Analysing the characteristics of the SARS-CoV-2 virus makes it possible to estimate the length of quarantine that reduces the impact on society and the economy, while minimising infections.
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Amrhein, L. ; Fuchs, C.
BMC Bioinformatics 22:123 (2021)
Background: Tissues are often heterogeneous in their single-cell molecular expression, and this can govern the regulation of cell fate. For the understanding of development and disease, it is important to quantify heterogeneity in a given tissue. Results: We present the R package stochprofML which uses the maximum likelihood principle to parameterize heterogeneity from the cumulative expression of small random pools of cells. We evaluate the algorithm’s performance in simulation studies and present further application opportunities. Conclusion: Stochastic profiling outweighs the necessary demixing of mixed samples with a saving in experimental cost and effort and less measurement error. It offers possibilities for parameterizing heterogeneity, estimating underlying pool compositions and detecting differences between cell populations between samples.
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Pietzner, M. ; Stewart, I.D. ; Raffler, J. ; Khaw, K.T. ; Michelotti, G.A. ; Kastenmüller, G. ; Wareham, N.J. ; Langenberg, C.
Nat. Med. 27, 471-479 (2021)
Multimorbidity, the simultaneous presence of multiple chronic conditions, is an increasing global health problem and research into its determinants is of high priority. We used baseline untargeted plasma metabolomics profiling covering >1,000 metabolites as a comprehensive readout of human physiology to characterize pathways associated with and across 27 incident noncommunicable diseases (NCDs) assessed using electronic health record hospitalization and cancer registry data from over 11,000 participants (219,415 person years). We identified 420 metabolites shared between at least 2 NCDs, representing 65.5% of all 640 significant metabolite-disease associations. We integrated baseline data on over 50 diverse clinical risk factors and characteristics to identify actionable shared pathways represented by those metabolites. Our study highlights liver and kidney function, lipid and glucose metabolism, low-grade inflammation, surrogates of gut microbial diversity and specific health-related behaviors as antecedents of common NCD multimorbidity with potential for early prevention. We integrated results into an open-access webserver ( https://omicscience.org/apps/mwasdisease/ ) to facilitate future research and meta-analyses.
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Suwandhi, L. ; Altun, I. ; Karlina, R. ; Miok, V. ; Wiedemann, T. ; Fischer, D.S. ; Walzthoeni, T. ; Lindner, C. ; Böttcher, A. ; Heinzmann, S.S. ; Israel, A. ; Khalil, A. ; Braun, A. ; Pramme-Steinwachs, I. ; Burtscher, I. ; Schmitt-Kopplin, P. ; Heinig, M. ; Elsner, M. ; Lickert, H. ; Theis, F.J. ; Ussar, S.
Nat. Commun. 12:1588 (2021)
Adipose tissue expansion, as seen in obesity, is often metabolically detrimental causing insulin resistance and the metabolic syndrome. However, white adipose tissue expansion at early ages is essential to establish a functional metabolism. To understand the differences between adolescent and adult adipose tissue expansion, we studied the cellular composition of the stromal vascular fraction of subcutaneous adipose tissue of two and eight weeks old mice using single cell RNA sequencing. We identified a subset of adolescent preadipocytes expressing the mature white adipocyte marker Asc-1 that showed a low ability to differentiate into beige adipocytes compared to Asc-1 negative cells in vitro. Loss of Asc-1 in subcutaneous preadipocytes resulted in spontaneous differentiation of beige adipocytes in vitro and in vivo. Mechanistically, this was mediated by a function of the amino acid transporter ASC-1 specifically in proliferating preadipocytes involving the intracellular accumulation of the ASC-1 cargo D-serine.
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Müller, J. ; Kretzschmar, M.
Nat. Phys. 17, 555–556 (2021)
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Efendiyev, M.A. ; Vougalter, V.
J. Differ. Equations 284, 83-101 (2021)
We establish the existence in the sense of sequences of solutions for certain integro-differential type equations in two dimensions involving the normal diffusion in one direction and the anomalous diffusion in the other direction in H2(R2) via the fixed point technique. The elliptic equation contains a second order differential operator without the Fredholm property. It is proved that, under the reasonable technical conditions, the convergence in L1(R2) of the integral kernels implies the existence and convergence in H2(R2) of the solutions.
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Weberpals, J. ; Becker, T. ; Davies, J. ; Schmich, F. ; Rüttinger, D. ; Theis, F.J. ; Bauer-Mehren, A.
Epidemiology 32, 378-388 (2021)
BACKGROUND: Due to the non-randomized nature of real-world data, prognostic factors need to be balanced, which is often done by propensity scores (PS). This study aimed to investigate whether autoencoders, which are unsupervised deep learning architectures, might be leveraged to compute PS. METHODS: We selected patient-level data of 128,368 first-line treated cancer patients from the Flatiron Health EHR-derived de-identified database. We trained an autoencoder architecture to learn a lower-dimensional patient representation, which we used to compute PS. To compare the performance of an autoencoder-based PS with established methods, we performed a simulation study. We assessed the balancing and adjustment performance using standardized mean differences (SMD), root-mean-square-errors (RMSE), percent bias and confidence interval (CI) coverage. To illustrate the application of the autoencoder-based PS, we emulated the PRONOUNCE trial by applying the trial's protocol elements within an observational database setting, comparing two chemotherapy regimens. RESULTS: All methods but the manual variable selection approach led to well-balanced cohorts with average SMDs <0.1. LASSO yielded on average the lowest deviation of resulting estimates (RMSE 0.0205) followed by the autoencoder approach (RMSE 0.0248). Altering the hyperparameter setup in sensitivity analysis, the autoencoder approach led to similar results as LASSO (RMSE 0.0203 and 0.0205, respectively). In the case study, all methods provided a similar conclusion with point estimates clustered around the null (e.g. HRautoencoder 1.01 [95% CI 0.80-1.27] vs. HRPRONOUNCE 1.07 [0.83-1.36]). INTERPRETATION: Autoencoder-based PS computation was a feasible approach to control for confounding but did not perform better than some established approaches like LASSO.
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Salinno, C. ; Büttner, M. ; Cota, P. ; Tritschler, S. ; Tarquis-Medina, M. ; Bastidas-Ponce, A. ; Scheibner, K. ; Burtscher, I. ; Böttcher, A. ; Theis, F.J. ; Bakhti, M. ; Lickert, H.
Mol. Metab. 49:101188 (2021)
OBJECTIVE: Islets of Langerhans contain heterogeneous populations of insulin-producing β-cells. Surface markers and respective antibodies for isolation, tracking, and analysis are urgently needed to study β-cell heterogeneity and explore the mechanisms to harness the regenerative potential of immature β-cells. METHODS: We performed single-cell mRNA profiling of early postnatal mouse islets and re-analyzed several single-cell mRNA sequencing datasets from mouse and human pancreas and islets. We used mouse primary islets, iPSC-derived endocrine cells, Min6 insulinoma, and human EndoC-βH1 β-cell lines and performed FAC sorting, Western blotting, and imaging to support and complement the findings from the data analyses. RESULTS: We found that all endocrine cell types expressed the cluster of differentiation 81 (CD81) during pancreas development, but the expression levels of this protein were gradually reduced in β-cells during postnatal maturation. Single-cell gene expression profiling and high-resolution imaging revealed an immature signature of β-cells expressing high levels of CD81 (CD81high) compared to a more mature population expressing no or low levels of this protein (CD81low/-). Analysis of β-cells from different diabetic mouse models and in vitro β-cell stress assays indicated an upregulation of CD81 expression levels in stressed and dedifferentiated β-cells. Similarly, CD81 was upregulated and marked stressed human β-cells in vitro. CONCLUSIONS: We identified CD81 as a novel surface marker that labels immature, stressed, and dedifferentiated β-cells in the adult mouse and human islets. This novel surface marker will allow us to better study β-cell heterogeneity in healthy subjects and diabetes progression.
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Scientific Article
Pritsch, M. ; Radon, K. ; Bakuli, A. ; Le Gleut, R. ; Olbrich, L. ; Guggenbüehl Noller, J.M. ; Saathoff, E. ; Castelletti, N. ; Garí, M. ; Pütz, P. ; Schälte, Y. ; Frahnow, T. ; Wölfel, R. ; Rothe, C. ; Pletschette, M. ; Metaxa, D. ; Förster, F. ; Thiel, V. ; Rieß, F. ; Diefenbach, M.N. ; Fröschl, G. ; Bruger, J. ; Winter, S. ; Frese, J. ; Puchinger, K. ; Brand, I. ; Kroidl, I. ; Hasenauer, J. ; Fuchs, C. ; Wieser, A. ; Hoelscher, M.
Int. J. Environ. Res. Public Health 18:3572 (2021)
Given the large number of mild or asymptomatic SARS-CoV-2 cases, only population-based studies can provide reliable estimates of the magnitude of the pandemic. We therefore aimed to assess the sero-prevalence of SARS-CoV-2 in the Munich general population after the first wave of the pandemic. For this purpose, we drew a representative sample of 2994 private households and invited household members 14 years and older to complete questionnaires and to provide blood samples. SARS-CoV-2 seropositivity was defined as Roche N pan-Ig ≥ 0.4218. We adjusted the prevalence for the sampling design, sensitivity, and specificity. We investigated risk factors for SARS-CoV-2 seropositivity and geospatial transmission patterns by generalized linear mixed models and permutation tests. Seropositivity for SARS-CoV-2-specific antibodies was 1.82% (95% confidence interval (CI) 1.28–2.37%) as compared to 0.46% PCR-positive cases officially registered in Munich. Loss of the sense of smell or taste was associated with seropositivity (odds ratio (OR) 47.4; 95% CI 7.2–307.0) and infections clustered within households. By this first population-based study on SARS-CoV-2 prevalence in a large German municipality not affected by a superspreading event, we could show that at least one in four cases in private households was reported and known to the health authorities. These results will help authorities to estimate the true burden of disease in the population and to take evidence-based decisions on public health measures.
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Scientific Article
Veerman, F. ; Popović, N. ; Marr, C.
Int. J. Nonlinear Sci., DOI: 10.1515/ijnsns-2019-0258 (2021)
Stochastic gene expression in regulatory networks is conventionally modelled via the chemical master equation (CME). As explicit solutions to the CME, in the form of so-called propagators, are oftentimes not readily available, various approximations have been proposed. A recently developed analytical method is based on a separation of time scales that assumes significant differences in the lifetimes of mRNA and protein in the network, allowing for the efficient approximation of propagators from asymptotic expansions for the corresponding generating functions. Here, we showcase the applicability of that method to simulated data from a ‘telegraph’ model for gene expression that is extended with an autoregulatory mechanism. We demonstrate that the resulting approximate propagators can be applied successfully for parameter inference in the non-regulated model; moreover, we show that, in the extended autoregulated model, autoactivation or autorepression may be refuted under certain assumptions on the model parameters. These results indicate that our approach may allow for successful parameter inference and model identification from longitudinal single cell data.
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Scientific Article
Maddu, S. ; Cheeseman, B.L. ; Müller, C. ; Sbalzarini, I.F.
Phys. Rev. E 103:042310 (2021)
We propose a statistical learning framework based on group-sparse regression that can be used to (i) enforce conservation laws, (ii) ensure model equivalence, and (iii) guarantee symmetries when learning or inferring differential-equation models from data. Directly learning interpretable mathematical models from data has emerged as a valuable modeling approach. However, in areas such as biology, high noise levels, sensor-induced correlations, and strong intersystem variability can render data-driven models nonsensical or physically inconsistent without additional constraints on the model structure. Hence, it is important to leverage prior knowledge from physical principles to learn biologically plausible and physically consistent models rather than models that simply fit the data best. We present the group iterative hard thresholding algorithm and use stability selection to infer physically consistent models with minimal parameter tuning. We show several applications from systems biology that demonstrate the benefits of enforcing priors in data-driven modeling.
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Scientific Article
MahmoudianDehkordi, S. ; Ahmed, A.T. ; Bhattacharyya, S. ; Han, X. ; Baillie, R.A. ; Arnold, M. ; Skime, M.K. ; John-Williams, L.S. ; Moseley, M.A. ; Thompson, J.W. ; Louie, G. ; Riva-Posse, P. ; Craighead, W.E. ; McDonald, W. ; Krishnan, R. ; Rush, A.J. ; Frye, M.A. ; Dunlop, B.W. ; Weinshilboum, R.M. ; Kaddurah-Daouk, R.
Transl. Psychiatry 11:153 (2021)
Selective serotonin reuptake inhibitors (SSRIs) are the first-line treatment for major depressive disorder (MDD), yet their mechanisms of action are not fully understood and their therapeutic benefit varies among individuals. We used a targeted metabolomics approach utilizing a panel of 180 metabolites to gain insights into mechanisms of action and response to citalopram/escitalopram. Plasma samples from 136 participants with MDD enrolled into the Mayo Pharmacogenomics Research Network Antidepressant Medication Pharmacogenomic Study (PGRN-AMPS) were profiled at baseline and after 8 weeks of treatment. After treatment, we saw increased levels of short-chain acylcarnitines and decreased levels of medium-chain and long-chain acylcarnitines, suggesting an SSRI effect on β-oxidation and mitochondrial function. Amines-including arginine, proline, and methionine sulfoxide-were upregulated while serotonin and sarcosine were downregulated, suggesting an SSRI effect on urea cycle, one-carbon metabolism, and serotonin uptake. Eighteen lipids within the phosphatidylcholine (PC aa and ae) classes were upregulated. Changes in several lipid and amine levels correlated with changes in 17-item Hamilton Rating Scale for Depression scores (HRSD17). Differences in metabolic profiles at baseline and post-treatment were noted between participants who remitted (HRSD17 ≤ 7) and those who gained no meaningful benefits (<30% reduction in HRSD17). Remitters exhibited (a) higher baseline levels of C3, C5, alpha-aminoadipic acid, sarcosine, and serotonin; and (b) higher week-8 levels of PC aa C34:1, PC aa C34:2, PC aa C36:2, and PC aa C36:4. These findings suggest that mitochondrial energetics-including acylcarnitine metabolism, transport, and its link to β-oxidation-and lipid membrane remodeling may play roles in SSRI treatment response.
Wissenschaftlicher Artikel
Scientific Article
Waibel, D.J.E. ; Shetab Boushehri, S. ; Marr, C.
BMC Bioinformatics 22:103 (2021)
BACKGROUND: Deep learning contributes to uncovering molecular and cellular processes with highly performant algorithms. Convolutional neural networks have become the state-of-the-art tool to provide accurate and fast image data processing. However, published algorithms mostly solve only one specific problem and they typically require a considerable coding effort and machine learning background for their application. RESULTS: We have thus developed InstantDL, a deep learning pipeline for four common image processing tasks: semantic segmentation, instance segmentation, pixel-wise regression and classification. InstantDL enables researchers with a basic computational background to apply debugged and benchmarked state-of-the-art deep learning algorithms to their own data with minimal effort. To make the pipeline robust, we have automated and standardized workflows and extensively tested it in different scenarios. Moreover, it allows assessing the uncertainty of predictions. We have benchmarked InstantDL on seven publicly available datasets achieving competitive performance without any parameter tuning. For customization of the pipeline to specific tasks, all code is easily accessible and well documented. CONCLUSIONS: With InstantDL, we hope to empower biomedical researchers to conduct reproducible image processing with a convenient and easy-to-use pipeline.
Wissenschaftlicher Artikel
Scientific Article
Mayr, C. ; Simon, L. ; Leuschner, G. ; Ansari, M. ; Schniering, J. ; Geyer, P.E. ; Angelidis, I. ; Strunz, M. ; Singh, P. ; Kneidinger, N. ; Reichenberger, F. ; Silbernagel, E. ; Böhm, S. ; Adler, H. ; Lindner, M. ; Maurer, B. ; Hilgendorff, A. ; Prasse, A. ; Behr, J. ; Mann, M. ; Eickelberg, O. ; Theis, F.J. ; Schiller, H. B.
EMBO Mol. Med. 13:e12871 (2021)
The correspondence of cell state changes in diseased organs to peripheral protein signatures is currently unknown. Here, we generated and integrated single-cell transcriptomic and proteomic data from multiple large pulmonary fibrosis patient cohorts. Integration of 233,638 single-cell transcriptomes (n = 61) across three independent cohorts enabled us to derive shifts in cell type proportions and a robust core set of genes altered in lung fibrosis for 45 cell types. Mass spectrometry analysis of lung lavage fluid (n = 124) and plasma (n = 141) proteomes identified distinct protein signatures correlated with diagnosis, lung function, and injury status. A novel SSTR2+ pericyte state correlated with disease severity and was reflected in lavage fluid by increased levels of the complement regulatory factor CFHR1. We further discovered CRTAC1 as a biomarker of alveolar type-2 epithelial cell health status in lavage fluid and plasma. Using cross-modal analysis and machine learning, we identified the cellular source of biomarkers and demonstrated that information transfer between modalities correctly predicts disease status, suggesting feasibility of clinical cell state monitoring through longitudinal sampling of body fluid proteomes.
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Scientific Article
Conlon, T.M. ; John-Schuster, G. ; Heide, D. ; Pfister, D. ; Lehmann, M. ; Hu, Y. ; Ertüz, Z. ; López, M.A. ; Ansari, M. ; Strunz, M. ; Mayr, C. ; Angelidis, I. ; Ciminieri, C. ; Costa, R. ; Kohlhepp, M.S. ; Guillot, A. ; Güneş, G. ; Jeridi, A. ; Funk, M.C. ; Beroshvili, G. ; Prokosch, S. ; Hetzer, J. ; Verleden, S.E. ; Alsafadi, H.N. ; Lindner, M. ; Burgstaller, G. ; Becker, L. ; Irmler, M. ; Dudek, M. ; Janzen, J. ; Goffin, E. ; Gosens, R. ; Knolle, P. ; Pirotte, B. ; Stöger, T. ; Beckers, J. ; Wagner, D.E. ; Singh, I. ; Theis, F.J. ; Hrabě de Angelis, M. ; O’Connor, T. ; Tacke, F. ; Boutros, M. ; Dejardin, E. ; Eickelberg, O. ; Schiller, H. B. ; Königshoff, M. ; Heikenwalder, M. ; Yildirim, A.Ö.
Nature 589, E6 (2021)
In the HTML version of this Article, owing to a typesetting error, the affiliations for author Indrabahadur Singh were incorrect. The correct affiliation is ‘Emmy Noether Research Group Epigenetic Machineries and Cancer, Division of Chronic Inflammation and Cancer, German Cancer Research Center (DKFZ), Heidelberg, Germany’. The PDF and print versions of the Article are correct. In addition, Ilias Angelidis should have been listed as an author, with the affiliation: ‘Comprehensive Pneumology Center (CPC), Institute of Lung Biology and Disease, Helmholtz Zentrum München, Member of the German Center for Lung Research (DZL), Neuherberg, Germany’. They designed, undertook, and analysed scRNA-seq experiments, and analysed and interpreted data (see ‘Author contributions’). Finally, in the original Article, authors Mathias Heikenwalder and Ali Önder Yildirim were listed as ‘jointly supervising’ authors instead of ‘equally contributing’ authors, alongside authors Thomas M. Conlon and Gerrit John-Schuster. The original Article has been corrected online.
Martínez, Y.A. ; Guo, X. ; Portales-Pérez, D.P. ; Rivera, G. ; Castañeda-Delgado, J.E. ; Garcia Perez, C. ; Enciso-Moreno, J.A. ; Lara-Ramírez, E.E.
PLoS ONE 16:e0246901 (2021)
The MERS-CoV, SARS-CoV, and SARS-CoV-2 are highly pathogenic viruses that can cause severe pneumonic diseases in humans. Unfortunately, there is a non-available effective treatment to combat these viruses. Domain-motif interactions (DMIs) are an essential means by which viruses mimic and hijack the biological processes of host cells. To disentangle how viruses achieve this process can help to develop new rational therapies. Data mining was performed to obtain DMIs stored as regular expressions (regexp) in 3DID and ELM databases. The mined regexp information was mapped on the coronaviruses’ proteomes. Most motifs on viral protein that could interact with human proteins are shared across the coronavirus species, indicating that molecular mimicry is a common strategy for coronavirus infection. Enrichment ontology analysis for protein domains showed a shared biological process and molecular function terms related to carbon source utilization and potassium channel regulation. Some of the mapped motifs were nested on B, and T cell epitopes, suggesting that it could be as an alternative way for reverse vaccinology. The information obtained in this study could be used for further theoretic and experimental explorations on coronavirus infection mechanism and development of medicines for treatment.
Wissenschaftlicher Artikel
Scientific Article
Rajewsky, N. ; Almouzni, G. ; Gorski, S.A. ; Aerts, S. ; Amit, I. ; Bertero, M.G. ; Bock, C. ; Bredenoord, A.L. ; Cavalli, G. ; Chiocca, S. ; Clevers, H. ; de Strooper, B. ; Eggert, A. ; Ellenberg, J. ; Fernández, X.M. ; Figlerowicz, M. ; Gasser, S.M. ; Hubner, N. ; Kjems, J. ; Knoblich, J.A. ; Krabbe, G. ; Lichter, P. ; Linnarsson, S. ; Marine, J.C. ; Marioni, J.C. ; Marti-Renom, M.A. ; Netea, M.G. ; Nickel, D. ; Nollmann, M. ; Novak, H.R. ; Parkinson, H. ; Piccolo, S. ; Pinheiro, I. ; Pombo, A. ; Popp, C. ; Reik, W. ; Roman-Roman, S. ; Rosenstiel, P. ; Schultze, J.L. ; Stegle, O. ; Tanay, A. ; Testa, G. ; Thanos, D. ; Theis, F.J. ; Torres-Padilla, M.E. ; Valencia, A. ; Vallot, C. ; van Oudenaarden, A. ; Vidal, M. ; Voet, T. ; LifeTime Community (Schiller, H. B. ; Ziegler, A.-G.)
Nature 592:E8 (2021)
In this Perspective, owing to an error in the HTML, the surname of author Alejandro López-Tobón of the LifeTime Community Working Groups consortium was indexed as ‘Tobon’ rather than ‘López-Tobón’ and the accents were missing. The HTML version of the original Perspective has been corrected; the PDF and print versions were always correct. *A list of authors and their affiliations appears online.
Peñuelas, J. ; Germain, J. ; Álvarez, E. ; Aparicio, E. ; Arús, P. ; Basnou, C. ; Blanché, C. ; Bonada, N. ; Canals, P. ; Capodiferro, M. ; Carceller, X. ; Casademunt, A. ; Casals, J. ; Casals, P. ; Casañas, F. ; Catalán, J. ; Checa, J. ; Cordero, P.J. ; Corominas, J. ; De Sostoa, A. ; Morral, J.M.E. ; Estrada, M. ; Folch, R. ; Franquesa, T. ; Garcia-Lozano, C. ; Garí, M. ; Geli, A.M. ; González-Guerrero, Ó. ; Gordillo, J. ; Gosálbez, J. ; Grimalt, J.O. ; Guàrdia, A. ; Isern, R. ; Jordana, J. ; Junqué, E. ; Lascurain, J. ; Lleonart, J. ; Llorente, G.A. ; Lloret, F. ; Lloret, J. ; Mallarach, J.M. ; Martín-Vide, J. ; Medir, R.M. ; Melero, Y. ; Montasell, J. ; Montori, A. ; Munné, A. ; Lo, O.N. ; Palazón, S. ; Palmero, M. ; Parés, M. ; Pino, J. ; Pintó, J. ; Planagumà, L. ; Pons, X. ; Prat, N. ; Puig, C. ; Puig, I. ; Puigdoménech, P. ; Pujol-Buxó, E. ; Roca, N. ; Rodrigo, J. ; Rodríguez-Teijeiro, J.D. ; Roig-Munar, F.X. ; Romanyà, J. ; Rovira, P. ; Sàez, L. ; Sauras-Yera, M.T. ; Serrat, D. ; Simó, J. ; Soler, J. ; Terradas, J. ; Vallejo, R. ; Vicente, P. ; Vilaplana, J.M. ; Vinyoles, D.
Land 10:144 (2021)
This paper provides an overview of the last 40 years of use, and in many cases abuse, of the natural resources in Catalonia, a country that is representative of European countries in general, and especially those in the Mediterranean region. It analyses the use of natural resources made by mining, agriculture, livestock, logging, fishing, nature tourism, and energy production and consumption. This use results in an ecological footprint, i.e., the productive land and sea surface required to generate the consumed resources and absorb the resulting waste, which is about seven times the amount available, a very high number but very similar to other European countries. This overexploitation of natural resources has a huge impact on land and its different forms of cover, air, and water. For the last 25 years, forests and urban areas have each gained almost 3% more of the territory at the expense of agricultural land; those municipalities bordering the sea have increased their number of inhabitants and activity, and although they only occupy 6.7% of the total surface area, they account for 43.3% of the population; air quality has stabilized since the turn of the century, and there has been some improvement in the state of aquatic ecosystems, but still only 36% are in good condition, while the remainder have suffered morphological changes and different forms of nonpoint source pollution; meanwhile the biodiversity of flora and fauna remains still under threat. Environmental policies do not go far enough so there is a need for revision of the legislation related to environmental impact and the protection of natural areas, flora, and fauna. The promotion of environmental research must be accompanied by environmental education to foster a society which ismore knowledgeable, has more control and influence over the decisions that deeply affect it. Indeed, nature conservation goes hand in hand with other social and economic challenges that require a more sustainable vision. Today’s problems with nature derive from the current economic model, which is environmentally unsustainable in that it does not take into account environmental impacts. Lastly, we propose a series of reasonable and feasible priority measures and actions related to each use made of the country’s natural resources, to the impacts they have had, and to their management, in the hope that these can contribute to improving the conservation and management of the environment and biodiversity and move towards sustainability.
Wissenschaftlicher Artikel
Scientific Article
Bast, L. ; Buck, M.C. ; Hecker, J.S. ; Oostendorp, R.A.J. ; Götze, K.S. ; Marr, C.
iScience 24:102120 (2021)
Classically, hematopoietic stem cell (HSC) differentiation is assumed to occur via progenitor compartments of decreasing plasticity and increasing maturity in a specific, hierarchical manner. The classical hierarchy has been challenged in the past by alternative differentiation pathways. We abstracted experimental evidence into 10 differentiation hierarchies, each comprising 7 cell type compartments. By fitting ordinary differential equation models with realistic waiting time distributions to time-resolved data of differentiating HSCs from 10 healthy human donors, we identified plausible lineage hierarchies and rejected others. We found that, for most donors, the classical model of hematopoiesis is preferred. Surprisingly, multipotent lymphoid progenitor differentiation into granulocyte-monocyte progenitors is plausible in 90% of samples. An in silico analysis confirmed that, even for strong noise, the classical model can be identified robustly. Our computational approach infers differentiation hierarchies in a personalized fashion and can be used to gain insights into kinetic alterations of diseased hematopoiesis.
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Scientific Article
Perrin-Cocon, L. ; Vidalain, P.O. ; Jacquemin, C. ; Aublin-Gex, A. ; Olmstead, K. ; Panthu, B. ; Rautureau, G.J.P. ; André, P. ; Nyczka, P. ; Hütt, M.T. ; Amoedo, N. ; Rossignol, R. ; Filipp, F.V. ; Lotteau, V. ; Diaz, O.
Comm. Biol. 4:217 (2021)
During the cancerous transformation of normal hepatocytes into hepatocellular carcinoma (HCC), the enzyme catalyzing the first rate-limiting step of glycolysis, namely the glucokinase (GCK), is replaced by the higher affinity isoenzyme, hexokinase 2 (HK2). Here, we show that in HCC tumors the highest expression level of HK2 is inversely correlated to GCK expression, and is associated to poor prognosis for patient survival. To further explore functional consequences of the GCK-to-HK2 isoenzyme switch occurring during carcinogenesis, HK2 was knocked-out in the HCC cell line Huh7 and replaced by GCK, to generate the Huh7-GCK+/HK2− cell line. HK2 knockdown and GCK expression rewired central carbon metabolism, stimulated mitochondrial respiration and restored essential metabolic functions of normal hepatocytes such as lipogenesis, VLDL secretion, glycogen storage. It also reactivated innate immune responses and sensitivity to natural killer cells, showing that consequences of the HK switch extend beyond metabolic reprogramming.
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Scientific Article
Cheng, J. ; Çelik, M.H. ; Kundaje, A. ; Gagneur, J.
Genome Biol. 22:94 (2021)
We develop the free and open-source model Multi-tissue Splicing (MTSplice) to predict the effects of genetic variants on splicing of cassette exons in 56 human tissues. MTSplice combines MMSplice, which models constitutive regulatory sequences, with a new neural network that models tissue-specific regulatory sequences. MTSplice outperforms MMSplice on predicting tissue-specific variations associated with genetic variants in most tissues of the GTEx dataset, with largest improvements on brain tissues. Furthermore, MTSplice predicts that autism-associated de novo mutations are enriched for variants affecting splicing specifically in the brain. We foresee that MTSplice will aid interpreting variants associated with tissue-specific disorders.
Wissenschaftlicher Artikel
Scientific Article
Cheng, J. ; Çelik, M.H. ; Kundaje, A. ; Gagneur, J.
Genome Biol. 22:107 (2021)
Following publication of the original paper [1], it was noticed that a typesetting error occurred. Julien Gagneur was mistakenly not indicated as a corresponding author. This has been corrected and the original article [1] has been updated.
Yoon, G. ; Müller, C. ; Gaynanova, I.
J. Comput. Graph. Stat. 30, 1249-1256 (2021)
Latent Gaussian copula models provide a powerful means to perform multi-view data integration since these models can seamlessly express dependencies between mixed variable types (binary, continuous, zero-inflated) via latent Gaussian correlations. The estimation of these latent correlations, however, comes at considerable computational cost, having prevented the routine use of these models on high-dimensional data. Here, we propose a new computational approach for estimating latent correlations via a hybrid multilinear interpolation and optimization scheme. Our approach speeds up the current state of the art computation by several orders of magnitude, thus allowing fast computation of latent Gaussian copula models even when the number of variables p is large. We provide theoretical guarantees for the approximation error of our numerical scheme and support its excellent performance on simulated and real-world data. We illustrate the practical advantages of our method on high-dimensional sparse quantitative and relative abundance microbiome data as well as multi-view data from The Cancer Genome Atlas Project. Our method is implemented in the R package mixedCCA, available at https://github.com/irinagain/mixedCCA.
Wissenschaftlicher Artikel
Scientific Article
Filbir, F. ; Krahmer, F. ; Melnyk, O.
J. Fourier Anal. Appl. 27:31 (2021)
The angular synchronization problem of estimating a set of unknown angles from their known noisy pairwise differences arises in various applications. It can be reformulated as an optimization problem on graphs involving the graph Laplacian matrix. We consider a general, weighted version of this problem, where the impact of the noise differs between different pairs of entries and some of the differences are erased completely; this version arises for example in ptychography. We study two common approaches for solving this problem, namely eigenvector relaxation and semidefinite convex relaxation. Although some recovery guarantees are available for both methods, their performance is either unsatisfying or restricted to the unweighted graphs. We close this gap, deriving recovery guarantees for the weighted problem that are completely analogous to the unweighted version.
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Scientific Article
Raimúndez, E. ; Dudkin, E. ; Vanhoefer, J. ; Alamoudi, E. ; Merkt, S. ; Fuhrmann, L. ; Bai, F. ; Hasenauer, J.
Epidemics 34:100439 (2021)
Epidemiological models are widely used to analyze the spread of diseases such as the global COVID-19 pandemic caused by SARS-CoV-2. However, all models are based on simplifying assumptions and often on sparse data. This limits the reliability of parameter estimates and predictions. In this manuscript, we demonstrate the relevance of these limitations and the pitfalls associated with the use of overly simplistic models. We considered the data for the early phase of the COVID-19 outbreak in Wuhan, China, as an example, and perform parameter estimation, uncertainty analysis and model selection for a range of established epidemiological models. Amongst others, we employ Markov chain Monte Carlo sampling, parameter and prediction profile calculation algorithms. Our results show that parameter estimates and predictions obtained for several established models on the basis of reported case numbers can be subject to substantial uncertainty. More importantly, estimates were often unrealistic and the confidence/credibility intervals did not cover plausible values of critical parameters obtained using different approaches. These findings suggest, amongst others, that standard compartmental models can be overly simplistic and that the reported case numbers provide often insufficient information for obtaining reliable and realistic parameter values, and for forecasting the evolution of epidemics.
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Scientific Article
Pietzner, M. ; Wheeler, E. ; Carrasco-Zanini, J. ; Raffler, J. ; Kerrison, N.D. ; Oerton, E. ; Auyeung, V.P.W. ; Luan, J. ; Finan, C. ; Casas, J.P. ; Ostroff, R. ; Williams, S.A. ; Kastenmüller, G. ; Ralser, M. ; Gamazon, E.R. ; Wareham, N.J. ; Hingorani, A.D. ; Langenberg, C.
Nat. Commun. 12:845 (2021)
The original version of this Article cited “Mehra, M. R., Desai, S. S., Kuy, S., Henry, T. D. & Patel, A. N. Cardiovascular disease, drug therapy, and mortality in Covid-19. N. Engl. J. Med. 382, e102 (2020)” as Ref. 20. The cited paper was retracted; accordingly, Ref. 20 has been replaced with "Grasselli G et al. Risk factors associated with mortality among patients with COVID-19 in intensive care units in Lombardy, Italy. JAMA Intern. Med. 180, 1345–1355 (2020)”. This has been corrected in the PDF and HTML versions of the article.
Scherb, H.
Eur. J. Clin. Invest. 51:e13500 (2021)
Sars-CoV-2 positive rates showed delays of about 20 days to proportional counts of positive deaths, worldwide. Using German data for the period 2/24/20 to 1/19/2021, the association of positive deaths with lagged positive rates was updated with focus on temporal homogeneity. A temporal clustering of the association between positive deaths and lagged positive rate was observed. This finding indicates unknown biological or epidemiological determinants of the pandemic and/or highlights deficits in Sars-CoV-2 metrics and statistics.
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Scientific Article
Schmiester, L. ; Schälte, Y. ; Bergmann, F.T. ; Camba, T. ; Dudkin, E. ; Egert, J. ; Fröhlich, F. ; Fuhrmann, L. ; Hauber, A.L. ; Kemmer, S. ; Lakrisenko, P. ; Loos, C. ; Merkt, S. ; Müller, W. ; Pathirana, D. ; Raimundez-Alvarez, E. ; Refisch, L. ; Rosenblatt, M. ; Stapor, P. ; Städter, P. ; Wang, D. ; Wieland, F.G. ; Banga, J.R. ; Timmer, J. ; Villaverde, A.F. ; Sahle, S. ; Kreutz, C. ; Hasenauer, J. ; Weindl, D.
PLoS Comput. Biol. 17:e1008646 (2021)
Reproducibility and reusability of the results of data-based modeling studies are essential. Yet, there has been-so far-no broadly supported format for the specification of parameter estimation problems in systems biology. Here, we introduce PEtab, a format which facilitates the specification of parameter estimation problems using Systems Biology Markup Language (SBML) models and a set of tab-separated value files describing the observation model and experimental data as well as parameters to be estimated. We already implemented PEtab support into eight well-established model simulation and parameter estimation toolboxes with hundreds of users in total. We provide a Python library for validation and modification of a PEtab problem and currently 20 example parameter estimation problems based on recent studies.
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Scientific Article
Städter, P. ; Schälte, Y. ; Schmiester, L. ; Hasenauer, J. ; Stapor, P.
Sci. Rep. 11:2696 (2021)
Ordinary differential equation (ODE) models are a key tool to understand complex mechanisms in systems biology. These models are studied using various approaches, including stability and bifurcation analysis, but most frequently by numerical simulations. The number of required simulations is often large, e.g., when unknown parameters need to be inferred. This renders efficient and reliable numerical integration methods essential. However, these methods depend on various hyperparameters, which strongly impact the ODE solution. Despite this, and although hundreds of published ODE models are freely available in public databases, a thorough study that quantifies the impact of hyperparameters on the ODE solver in terms of accuracy and computation time is still missing. In this manuscript, we investigate which choices of algorithms and hyperparameters are generally favorable when dealing with ODE models arising from biological processes. To ensure a representative evaluation, we considered 142 published models. Our study provides evidence that most ODEs in computational biology are stiff, and we give guidelines for the choice of algorithms and hyperparameters. We anticipate that our results will help researchers in systems biology to choose appropriate numerical methods when dealing with ODE models.
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Lopez, J.P. ; Brivio, E. ; Santambrogio, A. ; De Donno, C. ; Kos, A. ; Peters, M. ; Rost, N. ; Czamara, D. ; Brückl, T.M. ; Roeh, S. ; Pöhlmann, M.L. ; Engelhardt, C. ; Ressle, A. ; Stoffel, R. ; Tontsch, A. ; Villamizar, J.M. ; Reincke, M. ; Riester, A. ; Sbiera, S. ; Fassnacht, M. ; Mayberg, H.S. ; Craighead, W.E. ; Dunlop, B.W. ; Nemeroff, C.B. ; Schmidt, M.V. ; Binder, E.B. ; Theis, F.J. ; Beuschlein, F. ; Andoniadou, C.L. ; Chen, A.
Sci. Adv. 7:eabe4497 (2021)
Chronic activation and dysregulation of the neuroendocrine stress response have severe physiological and psychological consequences, including the development of metabolic and stress-related psychiatric disorders. We provide the first unbiased, cell type-specific, molecular characterization of all three components of the hypothalamic-pituitary- adrenal axis, under baseline and chronic stress conditions. Among others, we identified a previously unreported subpopulation of Abcb1b+ cells involved in stress adaptation in the adrenal gland. We validated our findings in a mouse stress model, adrenal tissues from patients with Cushing's syndrome, adrenocortical cell lines, and peripheral cortisol and genotyping data from depressed patients. This extensive dataset provides a valuable resource for researchers and clinicians interested in the organism's nervous and endocrine responses to stress and the interplay between these tissues. Our findings raise the possibility that modulating ABCB1 function may be important in the development of treatment strategies for patients suffering from metabolic and stress-related psychiatric disorders.
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Sorg, A.L. ; von Kries, R. ; Klemme, M. ; Gerstl, L. ; Beyerlein, A. ; Lack, N. ; Felderhoff-Müser, U. ; Dzietko, M.
Dev. Med. Child. Neurol. 63, 697-704 (2021)
Developmental Medicine & Child Neurology published by John Wiley & Sons Ltd on behalf of Mac Keith Press. Aim: To describe the incidence of term and preterm neonatal cerebral sinovenous thrombosis (CSVT) and identify perinatal risk factors. Method: This was a national capture-recapture calculation-corrected surveillance and nested case–control study. Infants born preterm and at term with magnetic resonance imaging-confirmed neonatal CSVT were identified by surveillance in all paediatric hospitals in Germany (2015–2017). Incidence was corrected for underreporting using a capture-recapture method in one federal state and then extrapolated nationwide. We reviewed PubMed for comparisons with previously reported incidence estimators. We used a population-based perinatal database for quality assurance to select four controls per case and applied univariate and multivariable regression for risk factor analysis. Results: Fifty-one newborn infants (34 males, 17 females; 14 born preterm) with neonatal CSVT were reported in the 3-year period. The incidence of term and preterm neonatal CSVT was 6.6 (95% confidence interval [CI] 4.4–8.7) per 100 000 live births. Median age at time of confirmation of the diagnosis was 9.95 days (range 0–39d). In the univariate analysis, male sex, preterm birth, hypoxia and related indicators (umbilical artery pH <7.1; 5-minute Apgar score <7; intubation/mask ventilation; perinatal asphyxia), operative vaginal delivery, emergency Caesarean section, and pathological fetal Doppler sonography were associated (p<0.05) with neonatal CSVT. Multivariable regression yielded hypoxia (odds ratio=20.3; 95% CI 8.1–50.8) as the independent risk factor. Interpretation: Incidence of neonatal CSVT was within the range of other population-based studies. The results suggest that hypoxia is an important perinatal risk factor for the aetiology of neonatal CSVT.
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Scherb, H. ; Grech, V.
Reprod. Toxicol. 100, 137-142 (2021)
In Europe, the male to female ratio at birth (secondary sex ratio: SSR; sex odds: SO) is 1.04-1.06, is influenced by many factors and is declining in industrialized countries. This study was carried out to identify possible impacts of fallout by atomic bomb tests or by the Chernobyl event on SSR in Italy. Italy is a country without commercial nuclear power generation for the last four decades and thus nearly free of radiological confounders. Counts of annual male and female live births in Italy are provided by the World Health Organization (WHO) and by the Italian Istituto Nazionale di Statistica (ISTAT). This study included 57.7 million live births (1940-2019) with overall SSR 1.05829. The Italian SSR trend was modelled with linear and non-linear logistic regression. Trend changes, i.e., periods with level shifts were estimated with Markov Chain Monte Carlo (MCMC). Two distinct idealized level shifts were identified superimposed on a uniform secular downward trend. The first one is seen towards the end of the 1960s with a jump sex odds ratio (SOR) 1.00681, p < 0.0001. The second one occurred in 1987 with SOR 1.00474, p < 0.0001. In each of the 3 periods separated by the two jumps, SSR uniformly decreased with trend SOR per 100 years of 0.98549, p < 0.0001. In conclusion, the secular trend in the Italian SSR showed two marked level shifts, at the end of the 1960s and from 1987 onward. These follow the release of radioactivity by atmospheric atomic bomb tests during the 1960s and by Chernobyl in 1986 and corroborate the hypothesis that ionizing radiation increases SSR.
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Spiegel, E ; Kneib, T. ; von Gablenz, P. ; Otto‐Sobotka, F.
Biom. J. 63, 1028-1051 (2021)
Expectile regression, in contrast to classical linear regression, allows for heteroscedasticity and omits a parametric specification of the underlying distribution. This model class can be seen as a quantile‐like generalization of least squares regression. Similarly as in quantile regression, the whole distribution can be modeled with expectiles, while still offering the same flexibility in the use of semiparametric predictors as modern mean regression. However, even with no parametric assumption for the distribution of the response in expectile regression, the model is still constructed with a linear relationship between the fitted value and the predictor. If the true underlying relationship is nonlinear then severe biases can be observed in the parameter estimates as well as in quantities derived from them such as model predictions. We observed this problem during the analysis of the distribution of a self‐reported hearing score with limited range. Classical expectile regression should in theory adhere to these constraints, however, we observed predictions that exceeded the maximum score. We propose to include a response function between the fitted value and the predictor similarly as in generalized linear models. However, including a fixed response function would imply an assumption on the shape of the underlying distribution function. Such assumptions would be counterintuitive in expectile regression. Therefore, we propose to estimate the response function jointly with the covariate effects. We design the response function as a monotonically increasing P‐spline, which may also contain constraints on the target set. This results in valid estimates for a self‐reported listening effort score through nonlinear estimates of the response function. We observed strong associations with the speech reception threshold.
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Acevedo, N. ; Scala, G. ; Merid, S.K. ; Frumento, P. ; Bruhn, S. ; Andersson, A. ; Ogris, C. ; Bottai, M. ; Pershagen, G. ; Koppelman, G.H. ; Melén, E. ; Sonnhammer, E. ; Alm, J. ; Söderhäll, C. ; Kere, J. ; Greco, D. ; Scheynius, A.
Int. J. Mol. Sci. 22:801 (2021)
DNA methylation changes may predispose becoming IgE-sensitized to allergens. We analyzed whether DNA methylation in peripheral blood mononuclear cells (PBMC) is associated with IgE sensitization at 5 years of age (5Y). DNA methylation was measured in 288 PBMC samples from 74 mother/child pairs from the birth cohort ALADDIN (Assessment of Lifestyle and Allergic Disease During INfancy) using the HumanMethylation450BeadChip (Illumina). PBMCs were obtained from the mothers during pregnancy and from their children in cord blood, at 2 years and 5Y. DNA methylation levels at each time point were compared between children with and without IgE sensitization to allergens at 5Y. For replication, CpG sites associated with IgE sensitization in ALADDIN were evaluated in whole blood DNA of 256 children, 4 years old, from the BAMSE (Swedish abbreviation for Children, Allergy, Milieu, Stockholm, Epidemiology) cohort. We found 34 differentially methylated regions (DMRs) associated with IgE sensitization to airborne allergens and 38 DMRs associated with sensitization to food allergens in children at 5Y (Sidak p ≤ 0.05). Genes associated with airborne sensitization were enriched in the pathway of endocytosis, while genes associated with food sensitization were enriched in focal adhesion, the bacterial invasion of epithelial cells, and leukocyte migration. Furthermore, 25 DMRs in maternal PBMCs were associated with IgE sensitization to airborne allergens in their children at 5Y, which were functionally annotated to the mTOR (mammalian Target of Rapamycin) signaling pathway. This study supports that DNA methylation is associated with IgE sensitization early in life and revealed new candidate genes for atopy. Moreover, our study provides evidence that maternal DNA methylation levels are associated with IgE sensitization in the child supporting early in utero effects on atopy predisposition.
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Sadafi, A. ; Moya Sans, L.M. ; Makhro, A. ; Livshits, L. ; Navab, N. ; Bogdanova, A. ; Albarqouni, S. ; Marr, C.
In: (2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI), 13-16 April 2021, Nice, France). 2021. 966-970
Hereditary hemolytic anemias are genetic disorders that af-fect the shape and density of red blood cells. Genetic testscurrently used to diagnose such anemias are expensive andunavailable in the majority of clinical labs. Here, we pro-pose a method for identifying hereditary hemolytic anemiasbased on a standard biochemistry method, called Percollgradient, obtained by centrifuging a patient’s blood. Our hy-brid approach consists on using spatial data-driven features,extracted with a convolutional neural network and spectralhandcrafted features obtained from fast Fourier transform.We compare late and early feature fusion with AlexNet andVGG16 architectures. AlexNet with late fusion of spectralfeatures performs better compared to other approaches. Weachieved an average F1-score of 88% on different classes sug-gesting the possibility of diagnosing of hereditary hemolyticanemias from Percoll gradients. Finally, we utilize Grad-CAM to explore the spatial features used for classification.
Yu, Z. ; Han, X. ; Zhao, B. ; Zhuo, Y. ; Ren, Y. ; Xue, X. ; Lamm, L. ; Feng, J. ; Marr, C. ; Shan, F. ; Peng, T. ; Zhang, X.-Y.
Research Square, in press (2021)
Currently, reliable, robust and ready-to-use CT-based tools for prediction of COVID-19 progression are still lacking. To address this problem, we present DABC-Net, a novel deep learning (DL) tool that combines a 2D U-net for intra-slice spatial information processing, and a recurrent LSTM network to leverage inter-slice context, for automatic volumetric segmentation of lung and pneumonia lesions. We evaluate DABC-Net on more than 10,000 radiologists-labeled CT slices from four different cohorts. Compared to state-of-the-art segmentation tools, DABC-Net is much faster, more robust, and able to estimate segmentation uncertainty. Based only on the first two CT scans within 3 days after admission from 656 longitudinal CT scans, the AUC of our DBAC-Net for disease progression prediction reaches 93%. We release our tool as a GUI for patient-specific prediction of pneumonia progression, to provide clinicians with additional assistance to triage patients at early days after the diagnosis and to optimize the assignment of limited medical resources, which is of particular importance in current critical COVID-19 pandemic.
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Meier, F. ; Köhler, N. ; Brunner, A.D. ; Wanka, J.-M.H. ; Voytik, E. ; Strauss, M.T. ; Theis, F.J. ; Mann, M.
Nat. Commun. 12:1185 (2021)
The size and shape of peptide ions in the gas phase are an under-explored dimension for mass spectrometry-based proteomics. To investigate the nature and utility of the peptide collisional cross section (CCS) space, we measure more than a million data points from whole-proteome digests of five organisms with trapped ion mobility spectrometry (TIMS) and parallel accumulation-serial fragmentation (PASEF). The scale and precision (CV < 1%) of our data is sufficient to train a deep recurrent neural network that accurately predicts CCS values solely based on the peptide sequence. Cross section predictions for the synthetic ProteomeTools peptides validate the model within a 1.4% median relative error (R > 0.99). Hydrophobicity, proportion of prolines and position of histidines are main determinants of the cross sections in addition to sequence-specific interactions. CCS values can now be predicted for any peptide and organism, forming a basis for advanced proteomics workflows that make full use of the additional information.
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Muus, C. ; Luecken, M. ; Eraslan, G. ; Sikkema, L. ; Waghray, A. ; Heimberg, G. ; Kobayashi, Y. ; Vaishnav, E.D. ; Subramanian, A. ; Smillie, C. ; Jagadeesh, K.A. ; Duong, E.T. ; Fiskin, E. ; Triglia, E.T. ; Ansari, M. ; Cai, P. ; Lin, B. ; Buchanan, J. ; Chen, S. ; Shu, J. ; Haber, A.L. ; Chung, H. ; Montoro, D.T. ; Adams, T. ; Aliee, H. ; Allon, S.J. ; Andrusivova, Z. ; Angelidis, I. ; Ashenberg, O. ; Bassler, K. ; Bécavin, C. ; Benhar, I. ; Bergenstråhle, J. ; Bergenstråhle, L. ; Bolt, L. ; Braun, E. ; Bui, L.T. ; Callori, S. ; Chaffin, M. ; Chichelnitskiy, E. ; Chiou, J. ; Conlon, T.M. ; Cuoco, M.S. ; Cuomo, A.S.E. ; Deprez, M. ; Duclos, G. ; Fine, D. ; Fischer, D.S. ; Ghazanfar, S. ; Gillich, A. ; Giotti, B. ; Gould, J. ; Guo, M. ; Gutierrez, A.J. ; Habermann, A.C. ; Harvey, T. ; He, P. ; Hou, X. ; Hu, L. ; Hu, Y. ; Jaiswal, A. ; Ji, L. ; Jiang, P. ; Kapellos, T.S. ; Kuo, C.S. ; Larsson, L. ; Leney-Greene, M.A. ; Lim, K. ; Litviňuková, M. ; Ludwig, L.S. ; Lukassen, S. ; Luo, W. ; Maatz, H. ; Madissoon, E. ; Mamanova, L. ; Manakongtreecheep, K. ; Leroy, S. ; Mayr, C. ; Mbano, I.M. ; McAdams, A.M. ; Nabhan, A.N. ; Nyquist, S.K. ; Penland, L. ; Poirion, O.B. ; Poli, S. ; Qi, C. ; Queen, R. ; Reichart, D. ; Rosas, I. ; Schupp, J.C. ; Shea, C.V. ; Shi, X. ; Sinha, R. ; Sit, R.V. ; Slowikowski, K. ; Slyper, M. ; Smith, N.P. ; Sountoulidis, A. ; Strunz, M. ; Sullivan, T.B. ; Sun, D. ; Talavera-López, C. ; Tan, P. ; Tantivit, J. ; Travaglini, K.J. ; Tucker, N.R. ; Vernon, K.A. ; Wadsworth, M.H. ; Waldman, J. ; Wang, X. ; Xu, K. ; Yan, W. ; Zhao, W. ; Ziegler, C.G.K.
Nat. Med. 27, 546–559 (2021)
Angiotensin-converting enzyme 2 (ACE2) and accessory proteases (TMPRSS2 and CTSL) are needed for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) cellular entry, and their expression may shed light on viral tropism and impact across the body. We assessed the cell-type-specific expression of ACE2, TMPRSS2 and CTSL across 107 single-cell RNA-sequencing studies from different tissues. ACE2, TMPRSS2 and CTSL are coexpressed in specific subsets of respiratory epithelial cells in the nasal passages, airways and alveoli, and in cells from other organs associated with coronavirus disease 2019 (COVID-19) transmission or pathology. We performed a meta-analysis of 31 lung single-cell RNA-sequencing studies with 1,320,896 cells from 377 nasal, airway and lung parenchyma samples from 228 individuals. This revealed cell-type-specific associations of age, sex and smoking with expression levels of ACE2, TMPRSS2 and CTSL. Expression of entry factors increased with age and in males, including in airway secretory cells and alveolar type 2 cells. Expression programs shared by ACE2+TMPRSS2+ cells in nasal, lung and gut tissues included genes that may mediate viral entry, key immune functions and epithelial-macrophage cross-talk, such as genes involved in the interleukin-6, interleukin-1, tumor necrosis factor and complement pathways. Cell-type-specific expression patterns may contribute to the pathogenesis of COVID-19, and our work highlights putative molecular pathways for therapeutic intervention.
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Scientific Article
Mazein, A. ; Ivanova, O. ; Balaur, I. ; Ostaszewski, M. ; Berzhitskaya, V. ; Serebriyskaya, T. ; Ligon, T. ; Hasenauer, J. ; De Meulder, B. ; Overall, R.W. ; Roy, L. ; Knowles, R.G. ; Wheelock, C.E. ; Dahlen, S.E. ; Chung, K.F. ; Adcock, I.M. ; Roberts, G. ; Djukanovic, R. ; Pellet, J. ; Gawron, P. ; Balling, R. ; Maitland-van der Zee, A.H. ; Schneider, R. ; Sterk, P.J. ; Auffray, C.
J. Allergy Clin. Immunol. 147, 853-856 (2021)
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Thomas, J. ; Wang, R. ; Batra, R. ; Böhner, A. ; Garzorz-Stark, N. ; Eberlein, B. ; Theis, F.J. ; Biedermann, T. ; Schmidt-Weber, C.B. ; Zink, A. ; Eyerich, K. ; Eyerich, S.
J. Invest. Dermatol. 141, 681-685.e6 (2021)
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Huang, J. ; Covic, M. ; Huth, C. ; Rommel, M. ; Adam, J. ; Zukunft, S. ; Prehn, C. ; Wang, L. ; Nano, J. ; Scheerer, M.F. ; Neschen, S. ; Kastenmüller, G. ; Gieger, C. ; Laxy, M. ; Schliess, F. ; Adamski, J. ; Suhre, K. ; Hrabě de Angelis, M. ; Peters, A. ; Wang-Sattler, R.
Metabolites 11:89 (2021)
Biological exploration of early biomarkers for chronic kidney disease (CKD) in (pre)diabetic individuals is crucial for personalized management of diabetes. Here, we evaluated two candidate biomarkers of incident CKD (sphingomyelin (SM) C18:1 and phosphatidylcholine diacyl (PC aa) C38:0) concerning kidney function in hyperglycemic participants of the Cooperative Health Research in the Region of Augsburg (KORA) cohort, and in two biofluids and six organs of leptin receptor-deficient (db/db) mice and wild type controls. Higher serum concentrations of SM C18:1 and PC aa C38:0 in hyperglycemic individuals were found to be associated with lower estimated glomerular filtration rate (eGFR) and higher odds of CKD. In db/db mice, both metabolites had a significantly lower concentration in urine and adipose tissue, but higher in the lungs. Additionally, db/db mice had significantly higher SM C18:1 levels in plasma and liver, and PC aa C38:0 in adrenal glands. This cross-sectional human study confirms that SM C18:1 and PC aa C38:0 associate with kidney dysfunction in pre(diabetic) individuals, and the animal study suggests a potential implication of liver, lungs, adrenal glands, and visceral fat in their systemic regulation. Our results support further validation of the two phospholipids as early biomarkers of renal disease in patients with (pre)diabetes.
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Scientific Article
Obermaier, J.
Colloq. Math. 164, 1-9 (2021)
The Banach space U(mu) of uniformly convergent Fourier series with respect to an orthonormal polynomial sequence with orthogonalization measure mu supported on a compact set S subset of R is studied. For certain measures mu, involving Bernstein-Szego polynomials and certain Jacobi polynomials, it is proven that U(mu) has the Pelczyriski property, and also that U(mu) and U(mu)* have the Dunford-Pettis property.
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Scientific Article
Kunze, S. ; Cecil, A. ; Prehn, C. ; Möller, G. ; Ohlmann, A. ; Wildner, G. ; Thurau, S. ; Unger, K. ; Rößler, U. ; Hölter, S.M. ; Tapio, S. ; Wagner, F. ; Beyerlein, A. ; Theis, F.J. ; Zitzelsberger, H. ; Kulka, U. ; Adamski, J. ; Graw, J. ; Dalke, C.
Int. J. Radiat. Biol. 97, 529-540 (2021)
PURPOSE: The long-term effect of low and moderate doses of ionizing radiation on the lens is still a matter of debate and needs to be evaluated in more detail. MATERIAL AND METHODS: We conducted a detailed histological analysis of eyes from B6C3F1 mice cohorts after acute gamma irradiation (60Co source; 0.063 Gy/min) at young adult age of 10 weeks with doses of 0.063, 0.125 and 0.5 Gy. Sham irradiated (0 Gy) mice were used as controls. To test for genetic susceptibility heterozygous Ercc2 mutant mice were used and compared to wild type mice of the same strain background. Mice of both sexes were included in all cohorts. Eyes were collected 4 hours, 12, 18 and 24 months after irradiation. For a better understanding of the underlying mechanisms, metabolomics analyses were performed in lenses and plasma samples of the same mouse cohorts at 4 and 12 hours as well as 12, 18 and 24 months after irradiation. For this purpose, a targeted analysis was chosen. RESULTS: This analysis revealed histological changes particularly in the posterior part of the lens that rarely can be observed by using Scheimpflug imaging, as we reported previously. We detected a significant increase of posterior subcapsular cataracts 18 and 24 months after irradiation with 0.5 Gy (odds ratio 9.3; 95%-confidence interval 2.1 - 41.3) independent of sex and genotype. Doses below 0.5 Gy (i.e. 0.063 and 0.125 Gy) did not significantly increase the frequency of posterior subcapsular cataracts at any time point. In lenses, we observed a clear effect of sex and aging but not of irradiation or genotype. While metabolomics analyses of plasma from the same mice showed only a sex effect. CONCLUSIONS: This paper demonstrates a significant radiation-induced increase in the incidence of posterior subcapsular cataracts, which could not be identified using Scheimpflug imaging as the only diagnostic tool.
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Böttcher, A. ; Büttner, M. ; Tritschler, S. ; Sterr, M. ; Aliluev, A. ; Oppenländer, L. ; Burtscher, I. ; Sass, S. ; Irmler, M. ; Beckers, J. ; Ziegenhain, C. ; Enard, W. ; Schamberger, A.C. ; Verhamme, F.M. ; Eickelberg, O. ; Theis, F.J. ; Lickert, H.
Nat. Cell Biol. 23, 23-31 (2021)
A detailed understanding of intestinal stem cell (ISC) self-renewal and differentiation is required to treat chronic intestinal diseases. However, the different models of ISC lineage hierarchy1–6 and segregation7–12 are subject to debate. Here, we have discovered non-canonical Wnt/planar cell polarity (PCP)-activated ISCs that are primed towards the enteroendocrine or Paneth cell lineage. Strikingly, integration of time-resolved lineage labelling with single-cell gene expression analysis revealed that both lineages are directly recruited from ISCs via unipotent transition states, challenging the existence of formerly predicted bi- or multipotent secretory progenitors7–12. Transitory cells that mature into Paneth cells are quiescent and express both stem cell and secretory lineage genes, indicating that these cells are the previously described Lgr5+ label-retaining cells7. Finally, Wnt/PCP-activated Lgr5+ ISCs are molecularly indistinguishable from Wnt/β-catenin-activated Lgr5+ ISCs, suggesting that lineage priming and cell-cycle exit is triggered at the post-transcriptional level by polarity cues and a switch from canonical to non-canonical Wnt/PCP signalling. Taken together, we redefine the mechanisms underlying ISC lineage hierarchy and identify the Wnt/PCP pathway as a new niche signal preceding lateral inhibition in ISC lineage priming and segregation.
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Lotta, L.A. ; Pietzner, M. ; Stewart, I.D. ; Wittemans, L.B.L. ; Li, C. ; Bonelli, R. ; Raffler, J. ; Biggs, E.K. ; Oliver-Williams, C. ; Auyeung, V.P.W. ; Luan, J. ; Wheeler, E. ; Paige, E. ; Surendran, P. ; Michelotti, G.A. ; Scott, R.A. ; Burgess, S. ; Zuber, V. ; Sanderson, E. ; Koulman, A. ; Imamura, F. ; Forouhi, N.G. ; Khaw, K.T. ; Bahlo, M. ; Griffin, J.L. ; Kastenmüller, G. ; Gribble, F.M. ; Reimann, F. ; Fauman, E. ; Wareham, N.J. ; Langenberg, C.
Nat. Genet. 53, 54-64 (2021)
In cross-platform analyses of 174 metabolites, we identify 499 associations (P < 4.9 × 10-10) characterized by pleiotropy, allelic heterogeneity, large and nonlinear effects and enrichment for nonsynonymous variation. We identify a signal at GLP2R (p.Asp470Asn) shared among higher citrulline levels, body mass index, fasting glucose-dependent insulinotropic peptide and type 2 diabetes, with β-arrestin signaling as the underlying mechanism. Genetically higher serine levels are shown to reduce the likelihood (by 95%) and predict development of macular telangiectasia type 2, a rare degenerative retinal disease. Integration of genomic and small molecule data across platforms enables the discovery of regulators of human metabolism and translation into clinical insights.
Wissenschaftlicher Artikel
Scientific Article
Mertes, C. ; Scheller, I.F. ; Yépez, V.A. ; Çelik, M.H. ; Liang, Y. ; Kremer, L.S. ; Gusic, M. ; Prokisch, H. ; Gagneur, J.
Nat. Commun. 12:529 (2021)
Aberrant splicing is a major cause of rare diseases.  However, its prediction from genome sequence alone remains in most cases inconclusive. Recently, RNA sequencing has proven to be an effective complementary avenue to detect aberrant splicing. Here, we develop FRASER, an algorithm to detect aberrant splicing from RNA sequencing data. Unlike existing methods, FRASER captures not only alternative splicing but also intron retention events. This typically doubles the number of detected aberrant events and identified a pathogenic intron retention in MCOLN1 causing mucolipidosis. FRASER automatically controls for latent confounders, which are widespread and affect sensitivity substantially. Moreover, FRASER is based on a count distribution and multiple testing correction, thus reducing the number of calls by two orders of magnitude over commonly applied z score cutoffs, with a minor loss of sensitivity. Applying FRASER to rare disease diagnostics is demonstrated by reprioritizing a pathogenic aberrant exon truncation in TAZ from a published dataset. FRASER is easy to use and freely available.
Wissenschaftlicher Artikel
Scientific Article
Yépez, V.A. ; Mertes, C. ; Müller, M.F. ; Wachutka, L. ; Frésard, L. ; Gusic, M. ; Scheller, I.F. ; Goldberg, P.F. ; Prokisch, H. ; Gagneur, J.
Nat. Protoc. 16, 1276–1296 (2021)
RNA sequencing (RNA-seq) has emerged as a powerful approach to discover disease-causing gene regulatory defects in individuals affected by genetically undiagnosed rare disorders. Pioneering studies have shown that RNA-seq could increase the diagnosis rates over DNA sequencing alone by 8-36%, depending on the disease entity and tissue probed. To accelerate adoption of RNA-seq by human genetics centers, detailed analysis protocols are now needed. We present a step-by-step protocol that details how to robustly detect aberrant expression levels, aberrant splicing and mono-allelic expression in RNA-seq data using dedicated statistical methods. We describe how to generate and assess quality control plots and interpret the analysis results. The protocol is based on the detection of RNA outliers pipeline (DROP), a modular computational workflow that integrates all the analysis steps, can leverage parallel computing infrastructures and generates browsable web page reports.
Wissenschaftlicher Artikel
Scientific Article
Deutelmoser, H. ; Scherer, D. ; Brenner, H. ; Waldenberger, M. ; Suhre, K. ; Kastenmüller, G. ; Lorenzo Bermejo, J.
Brief. Bioinform. 22:bbaa230 (2021)
Least absolute shrinkage and selection operator (LASSO) regression is often applied to select the most promising set of single nucleotide polymorphisms (SNPs) associated with a molecular phenotype of interest. While the penalization parameter λ restricts the number of selected SNPs and the potential model overfitting, the least-squares loss function of standard LASSO regression translates into a strong dependence of statistical results on a small number of individuals with phenotypes or genotypes divergent from the majority of the study population-typically comprised of outliers and high-leverage observations. Robust methods have been developed to constrain the influence of divergent observations and generate statistical results that apply to the bulk of study data, but they have rarely been applied to genetic association studies. In this article, we review, for newcomers to the field of robust statistics, a novel version of standard LASSO that utilizes the Huber loss function. We conduct comprehensive simulations and analyze real protein, metabolite, mRNA expression and genotype data to compare the stability of penalization, the cross-iteration concordance of the model, the false-positive and true-positive rates and the prediction accuracy of standard and robust Huber-LASSO. Although the two methods showed controlled false-positive rates ≤2.1% and similar true-positive rates, robust Huber-LASSO outperformed standard LASSO in the accuracy of predicted protein, metabolite and gene expression levels using individual SNP data. The conducted simulations and real-data analyses show that robust Huber-LASSO represents a valuable alternative to standard LASSO in genetic studies of molecular phenotypes.
Wissenschaftlicher Artikel
Scientific Article
Feldmann, K. ; Maurer, C. ; Peschke, K. ; Teller, S. ; Schuck, K. ; Steiger, K. ; Engleitner, T. ; Öllinger, R. ; Nomura, A. ; Wirges, N. ; Papargyriou, A. ; Jahan Sarker, R.S. ; Ranjan, R.A. ; Dantes, Z. ; Weichert, W. ; Rustgi, A.K. ; Schmid, R.M. ; Rad, R. ; Schneider, G. ; Saur, D. ; Reichert, M.
Gastroenterology 160, 346-361.e24 (2021)
Background & Aims: Pancreatic ductal adenocarcinoma (PDAC) is characterized by a fibroblast-rich desmoplastic stroma. Cancer-associated fibroblasts (CAFs) have been shown to display a high degree of interconvertible states including quiescent, inflammatory, and myofibroblastic phenotypes; however, the mechanisms by which this plasticity is achieved are poorly understood. Here, we aim to elucidate the role of CAF plasticity and its impact on PDAC biology. Methods: To investigate the role of mesenchymal plasticity in PDAC progression, we generated a PDAC mouse model in which CAF plasticity is modulated by genetic depletion of the transcription factor Prrx1. Primary pancreatic fibroblasts from this mouse model were further characterized by functional in vitro assays. To characterize the impact of CAFs on tumor differentiation and response to chemotherapy, various coculture experiments were performed. In vivo, tumors were characterized by morphology, extracellular matrix composition, and tumor dissemination and metastasis. Results: Our in vivo findings showed that Prrx1-deficient CAFs remain constitutively activated. Importantly, this CAF phenotype determines tumor differentiation and disrupts systemic tumor dissemination. Mechanistically, coculture experiments of tumor organoids and CAFs showed that CAFs shape the epithelial-to-mesenchymal phenotype and confer gemcitabine resistance of PDAC cells induced by CAF-derived hepatocyte growth factor. Furthermore, gene expression analysis showed that patients with pancreatic cancer with high stromal expression of Prrx1 display the squamous, most aggressive, subtype of PDAC. Conclusions: Here, we define that the Prrx1 transcription factor is critical for tuning CAF activation, allowing a dynamic switch between a dormant and an activated state. This work shows that Prrx1-mediated CAF plasticity has significant impact on PDAC biology and therapeutic resistance.
Wissenschaftlicher Artikel
Scientific Article
Perlmutter, M. ; Sissouno, N. ; Viswantathan, A. ; Iwen, M.
In: (28th European Signal Processing Conference (EUSIPCO), 24-28 August 2020, Amsterdam, Netherlands). 2021. 970-974 ( ; 2021-January)
We present an algorithm which is closely related to direct phase retrieval methods that have been shown to work well empirically [1], [2] and prove that it is guaranteed to recover (up to a global phase) a large class of compactly supported smooth functions from their spectrogram measurements. As a result, we take a first step toward developing a new class of practical phaseless imaging algorithms capable of producing provably accurate images of a given sample after it is masked by just a few shifts of a fixed periodic grating.
Müller, J. ; Kretzschmar, M.
Infect. Dis. Model. 6, 222-231 (2021)
Contact tracing is an effective method to control emerging infectious diseases. Since the 1980's, modellers are developing a consistent theory for contact tracing, with the aim to find effective and efficient implementations, and to assess the effects of contact tracing on the spread of an infectious disease. Despite the progress made in the area, there remain important open questions. In addition, technological developments, especially in the field of molecular biology (genetic sequencing of pathogens) and modern communication (digital contact tracing), have posed new challenges for the modelling community. In the present paper, we discuss modelling approaches for contact tracing and identify some of the current challenges for the field.
Review
Review
Thorand, B. ; Zierer, A. ; Büyüközkan, M. ; Krumsiek, J. ; Bauer, A. ; Schederecker, F. ; Sudduth-Klinger, J. ; Meisinger, C. ; Grallert, H. ; Rathmann, W. ; Roden, M. ; Peters, A. ; Koenig, W. ; Herder, C. ; Huth, C.
J. Clin. Endocrinol. Metab. 106, e1647-e1659 (2021)
CONTEXT: Improved strategies to identify persons at high risk of type 2 diabetes are important to target costly preventive efforts to those who will benefit most. OBJECTIVE: To assess whether novel biomarkers improve the prediction of type 2 diabetes beyond non-invasive standard clinical risk factors alone or in combination with HbA1c. DESIGN AND METHODS: We used a population-based case-cohort study for discovery (689 incident cases and 1,850 non-cases) and an independent cohort study (n=262 incident cases, 2,549 non-cases) for validation. An L1-penalized (lasso) Cox model was used to select the most predictive set among 47 serum biomarkers from multiple etiological pathways. All variables available from the non-invasive German Diabetes Risk Score (GDRSadapted) were forced into the models. The C-index and the category-free net reclassification index (cfNRI) were used to evaluate the predictive performance of the selected biomarkers beyond the GDRSadapted model (plus HbA1c). RESULTS: Interleukin-1 receptor antagonist, insulin growth factor binding protein-2, soluble E-selectin, decorin, adiponectin, and high density lipoprotein-cholesterol were selected as most relevant. The simultaneous addition of these six biomarkers significantly improved the predictive performance in both the discovery (C-index [95% CI]: 0.053 [0.039-0.066]; cfNRI [95% CI]: 67.4% [57.3%-79.5%]) and the validation study (0.034 [0.019-0.053]; 48.4% [35.6%-60.8%]). Significant improvements by these biomarkers were also seen on top of the GDRSadapted model plus HbA1c in both studies. CONCLUSION: The addition of six biomarkers significantly improved the prediction of type 2 diabetes when added to a non-invasive clinical model or to a clinical model plus HbA1c.
Wissenschaftlicher Artikel
Scientific Article
Peschel, S. ; Müller, C. ; von Mutius, E. ; Boulesteix, A.L. ; Depner, M.
Brief. Bioinform. 22, DOI: 10.1093/bib/bbaa290 (2021)
MOTIVATION: Estimating microbial association networks from high-throughput sequencing data is a common exploratory data analysis approach aiming at understanding the complex interplay of microbial communities in their natural habitat. Statistical network estimation workflows comprise several analysis steps, including methods for zero handling, data normalization and computing microbial associations. Since microbial interactions are likely to change between conditions, e.g. between healthy individuals and patients, identifying network differences between groups is often an integral secondary analysis step. Thus far, however, no unifying computational tool is available that facilitates the whole analysis workflow of constructing, analysing and comparing microbial association networks from high-throughput sequencing data. RESULTS: Here, we introduce NetCoMi (Network Construction and comparison for Microbiome data), an R package that integrates existing methods for each analysis step in a single reproducible computational workflow. The package offers functionality for constructing and analysing single microbial association networks as well as quantifying network differences. This enables insights into whether single taxa, groups of taxa or the overall network structure change between groups. NetCoMi also contains functionality for constructing differential networks, thus allowing to assess whether single pairs of taxa are differentially associated between two groups. Furthermore, NetCoMi facilitates the construction and analysis of dissimilarity networks of microbiome samples, enabling a high-level graphical summary of the heterogeneity of an entire microbiome sample collection. We illustrate NetCoMi's wide applicability using data sets from the GABRIELA study to compare microbial associations in settled dust from children's rooms between samples from two study centers (Ulm and Munich). AVAILABILITY: R scripts used for producing the examples shown in this manuscript are provided as supplementary data. The NetCoMi package, together with a tutorial, is available at https://github.com/stefpeschel/NetCoMi. CONTACT: Tel:+49 89 3187 43258; stefanie.peschel@mail.de. SUPPLEMENTARY INFORMATION: Supplementary data are available at Briefings in Bioinformatics online.
Wissenschaftlicher Artikel
Scientific Article
Karlina, R. ; Lutter, D. ; Miok, V. ; Fischer, D.S. ; Altun, I. ; Schöttl, T. ; Schorpp, K.K. ; Israel, A. ; Cero, C. ; Johnson, J.W. ; Kapser-Fischer, I. ; Böttcher, A. ; Keipert, S. ; Feuchtinger, A. ; Graf, E. ; Strom, T.M. ; Walch, A.K. ; Lickert, H. ; Walzthoeni, T. ; Heinig, M. ; Theis, F.J. ; García-Cáceres, C. ; Cypess, A.M. ; Ussar, S.
Life Sci. All. 4:e202000924 (2021)
Brown adipose tissue (BAT) plays an important role in the regulation of body weight and glucose homeostasis. Although increasing evidence supports white adipose tissue heterogeneity, little is known about heterogeneity within murine BAT. Recently, UCP1 high and low expressing brown adipocytes were identified, but a developmental origin of these subtypes has not been studied. To obtain more insights into brown preadipocyte heterogeneity, we use single-cell RNA sequencing of the BAT stromal vascular fraction of C57/BL6 mice and characterize brown preadipocyte and adipocyte clonal cell lines. Statistical analysis of gene expression profiles from brown preadipocyte and adipocyte clones identify markers distinguishing brown adipocyte subtypes. We confirm the presence of distinct brown adipocyte populations in vivo using the markers EIF5, TCF25, and BIN1. We also demonstrate that loss of Bin1 enhances UCP1 expression and mitochondrial respiration, suggesting that BIN1 marks dormant brown adipocytes. The existence of multiple brown adipocyte subtypes suggests distinct functional properties of BAT depending on its cellular composition, with potentially distinct functions in thermogenesis and the regulation of whole body energy homeostasis.
Wissenschaftlicher Artikel
Scientific Article
Kappelmann, N. ; Knauer-Arloth, J. ; Georgakis, M.K. ; Czamara, D. ; Rost, N. ; Ligthart, S. ; Khandaker, G.M. ; Binder, E.B.
JAMA psychiatry 78, 161-170 (2021)
This genetic correlation and 2-sample mendelian randomization study uses large-scale genome-wide association data sources to explore the genetic overlap and associations between inflammatory activity, metabolic dysregulation, and individual depressive symptoms.Importance Observational studies highlight associations of C-reactive protein (CRP), a general marker of inflammation, and interleukin 6 (IL-6), a cytokine-stimulating CRP production, with individual depressive symptoms. However, it is unclear whether inflammatory activity is associated with individual depressive symptoms and to what extent metabolic dysregulation underlies the reported associations. Objective To explore the genetic overlap and associations between inflammatory activity, metabolic dysregulation, and individual depressive symptoms. GWAS Data Sources Genome-wide association study (GWAS) summary data of European individuals, including the following: CRP levels (204402 individuals); 9 individual depressive symptoms (3 of which did not differentiate between underlying diametrically opposite symptoms [eg, insomnia and hypersomnia]) as measured with the Patient Health Questionnaire 9 (up to 117;907 individuals); summary statistics for major depression, including and excluding UK Biobank participants, resulting in sample sizes of 500 199 and up to 230 214 individuals, respectively; insomnia (up to 386533 individuals); body mass index (BMI) (up to 322154 individuals); and height (up to 253280 individuals). Design In this genetic correlation and 2-sample mendelian randomization (MR) study, linkage disequilibrium score (LDSC) regression was applied to infer single-nucleotide variant-based heritability and genetic correlation estimates. Two-sample MR tested potential causal associations of genetic variants associated with CRP levels, IL-6 signaling, and BMI with depressive symptoms. The study dates were November 2019 to April 2020. Results Based on large GWAS data sources, genetic correlation analyses revealed consistent false discovery rate (FDR)-controlled associations (genetic correlation range, 0.152-0.362; FDR P = .006 to P < .001) between CRP levels and depressive symptoms that were similar in size to genetic correlations of BMI with depressive symptoms. Two-sample MR analyses suggested that genetic upregulation of IL-6 signaling was associated with suicidality (estimate [SE], 0.035 [0.010]; FDR plus Bonferroni correction P = .01), a finding that remained stable across statistical models and sensitivity analyses using alternative instrument selection strategies. Mendelian randomization analyses did not consistently show associations of higher CRP levels or IL-6 signaling with other depressive symptoms, but higher BMI was associated with anhedonia, tiredness, changes in appetite, and feelings of inadequacy. Conclusions and Relevance This study reports coheritability between CRP levels and individual depressive symptoms, which may result from the potentially causal association of metabolic dysregulation with anhedonia, tiredness, changes in appetite, and feelings of inadequacy. The study also found that IL-6 signaling is associated with suicidality. These findings may have clinical implications, highlighting the potential of anti-inflammatory approaches, especially IL-6 blockade, as a putative strategy for suicide prevention.Question Do inflammatory pathways share a genetic background with individual depressive symptoms, and do they potentially causally contribute to them? Findings Based on large genome-wide association study data sources, this genetic correlation and 2-sample mendelian randomization study found genetic overlap between a higher C-reactive protein (CRP) level, a broad marker of inflammation, and 9 depressive symptoms; upregulated interleukin-6 signaling, a major stimulator of CRP, emerged as a potential causal risk factor for suicidality. Body mass index, but not interleukin 6 or CRP, was potentially causally associated with 4 other depressive symptoms. Meaning Interleukin 6 overactivity could be associated with suicidality; interleukin-6 blockade may be a novel treatment target that warrants future research.
Wissenschaftlicher Artikel
Scientific Article
Wörheide, M. ; Krumsiek, J. ; Kastenmüller, G. ; Arnold, M.
Anal. Chim. Acta 1141, 144-162 (2021)
Recent advances in high-throughput technologies have enabled the profiling of multiple layers of a biological system, including DNA sequence data (genomics), RNA expression levels (transcriptomics), and metabolite levels (metabolomics). This has led to the generation of vast amounts of biological data that can be integrated in so-called multi-omics studies to examine the complex molecular underpinnings of health and disease. Integrative analysis of such datasets is not straightforward and is particularly complicated by the high dimensionality and heterogeneity of the data and by the lack of universal analysis protocols. Previous reviews have discussed various strategies to address the challenges of data integration, elaborating on specific aspects, such as network inference or feature selection techniques. Thereby, the main focus has been on the integration of two omics layers in their relation to a phenotype of interest. In this review we provide an overview over a typical multi-omics workflow, focusing on integration methods that have the potential to combine metabolomics data with two or more omics. We discuss multiple integration concepts including data-driven, knowledge-based, simultaneous and step-wise approaches. We highlight the application of these methods in recent multi-omics studies, including large-scale integration efforts aiming at a global depiction of the complex relationships within and between different biological layers without focusing on a particular phenotype.
Review
Review
Efendiyev, M.A. ; Vougalter, V.
J. Differ. Equations 271, 280-300 (2021)
We study solvability of some linear nonhomogeneous elliptic problems and establish that under reasonable technical conditions the convergence in L2(Rd) of their right sides implies the existence and the convergence in H4(Rd) of the solutions. The problems contain the squares of the sums of second order non-Fredholm differential operators and we use the methods of the spectral and scattering theory for Schrödinger type operators. We especially emphasize that here we deal with the fourth order operators in contrast to the second order operators in [29] and investigate the dependence of the solvability conditions on the dimension of our problem when the constant a=0. We also consider the case of solvability with a single potential in an arbitrary dimension.
Wissenschaftlicher Artikel
Scientific Article
Krautenbacher, N. ; Kabesch, M. ; Horak, E. ; Braun-Fahrländer, C. ; Genuneit, J. ; Boznanski, A. ; von Mutius, E. ; Theis, F.J. ; Fuchs, C. ; Ege, M.J. ; GABRIELA, PASTURE study groups
Pediatr. Allergy Immunol. 32, 295-304 (2021)
Background: The asthma syndrome is influenced by hereditary and environmental factors. With the example of farm exposure, we study whether genetic and environmental factors interact for asthma. Methods: Statistical learning approaches based on penalized regression and decision trees were used to predict asthma in the GABRIELA study with 850 cases (9% farm children) and 857 controls (14% farm children). Single-nucleotide polymorphisms (SNPs) were selected from a genome-wide dataset based on a literature search or by statistical selection techniques. Prediction was assessed by receiver operating characteristics (ROC) curves and validated in the PASTURE cohort. Results: Prediction by family history of asthma and atopy yielded an area under the ROC curve (AUC) of 0.62 [0.57-0.66] in the random forest machine learning approach. By adding information on demographics (sex and age) and 26 environmental exposure variables, the quality of prediction significantly improved (AUC = 0.65 [0.61-0.70]). In farm children, however, environmental variables did not improve prediction quality. Rather SNPs related to IL33 and RAD50 contributed significantly to the prediction of asthma (AUC = 0.70 [0.62-0.78]). Conclusions: Asthma in farm children is more likely predicted by other factors as compared to non-farm children though in both forms, family history may integrate environmental exposure, genotype and degree of penetrance.
Wissenschaftlicher Artikel
Scientific Article
Combettes, P.L. ; Müller, C.
Stat. Biosci. 13, 217–242 (2021)
Compositional data sets are ubiquitous in science, including geology, ecology, and microbiology. In microbiome research, compositional data primarily arise from high-throughput sequence-based profiling experiments. These data comprise microbial compositions in their natural habitat and are often paired with covariate measurements that characterize physicochemical habitat properties or the physiology of the host. Inferring parsimonious statistical associations between microbial compositions and habitat- or host-specific covariate data is an important step in exploratory data analysis. A standard statistical model linking compositional covariates to continuous outcomes is the linear log-contrast model. This model describes the response as a linear combination of log-ratios of the original compositions and has been extended to the high-dimensional setting via regularization. In this contribution, we propose a general convex optimization model for linear log-contrast regression which includes many previous proposals as special cases. We introduce a proximal algorithm that solves the resulting constrained optimization problem exactly with rigorous convergence guarantees. We illustrate the versatility of our approach by investigating the performance of several model instances on soil and gut microbiome data analysis tasks.
Wissenschaftlicher Artikel
Scientific Article
2020
Scherb, H.
J. Womens Health Care Manage. 2:113 (2020)
Background: On August 31, 2010, a radiological INES-2 grade incident occurred at the Swiss nuclear power plant Leibstadt (NPPL). The question arises whether this event or its contemporary concomitants had any impact on the birth sex odds near the site from 2011 onward?Method: Focus is on the annual live births sex odds within 5 km from NPPL during the symmetrical period of 9 years before and 9 years after the INES-2 incident in 2010. A time trend analysis based on logistic regression was carried out. A possible level-shift in the sex odds trend from 2011 onward was estimated and tested.Result: The sex odds trend from 2002 to 2019 reveals a significant jump in 2011 with sex odds ratio (SOR) 1.484, 95% CI [1.155, 1.907], p-value 0.0020.Conclusion: This observation corroborates previous findings of increased sex odds near nuclear facilities, especially after distinct radiological events.
Wissenschaftlicher Artikel
Scientific Article
Amrhein, L. ; Fuchs, C.
In: (Proceedings of the 35th International Workshop on Statistical Modelling (IWSM) 2020). 2020. accepted
Busen, H. ; Fuchs, C.
In: (Proceedings of the 35th International Workshop on Statistical Modelling (IWSM) 2020). 2020. accepted
Scherb, H. ; Hayashi, K.
Environ. Health 19:123 (2020)
We thank Sani Rachman Soleman et al. for three specific points of criticism concerning our investigation of the ecological association between low birth weight (LBW) and radioactive contamination in Japan after the Fukushima Daiichi Nuclear Power Plant (FDNPP) accidents:1.Ecological variables are not justified enough to adjust potential confounding.2.The spatiotemporal regression model does not consider temporal reduction in radiation dose rate.3.Dose-response plot between dose rates and odds ratios overestimates R2and underestimates p-value. This criticism is a good starting point to explain some of the technical backgrounds of our approach in more detail.
Letter to the Editor
Letter to the Editor
Ebert, K. ; Zwingenberger, G. ; Barbaria, E. ; Keller, S. ; Heck, C. ; Arnold, R. ; Hollerieth, V. ; Mattes, J. ; Geffers, R. ; Raimundez-Alvarez, E. ; Hasenauer, J. ; Luber, B.
BMC Cancer 20:1127 (2020)
Following publication of the original article [1], the authors reported an error in the labeling of Table 5. The corrected Table 5 is given below.
Radon, K. ; Saathoff, E. ; Pritsch, M. ; Guggenbühl Noller, J.M. ; Kroidl, I. ; Olbrich, L. ; Thiel, V. ; Diefenbach, M. ; Riess, F. ; Förster, F. ; Theis, F.J. ; Wieser, A. ; Hoelscher, M. ; the KoCo19 collaboration group (Hasenauer, J. ; Fuchs, C. ; Castelletti, N. ; Zeggini, E. ; Laxy, M. ; Leidl, R. ; Schwettmann, L.)
BMC Public Health 20:1335 (2020)
An amendment to this paper has been published and can be accessed via the original article.
Sadafi, A. ; Makhro, A. ; Bogdanova, A. ; Navab, N. ; Peng, T. ; Albarqouni, S. ; Marr, C.
In:. 2020. 246-256 (Lect. Notes Comput. Sc. ; 12265 LNCS)
Red blood cells are highly deformable and present in various shapes. In blood cell disorders, only a subset of all cells is morphologically altered and relevant for the diagnosis. However, manually labeling of all cells is laborious, complicated and introduces inter-expert variability. We propose an attention based multiple instance learning method to classify blood samples of patients suffering from blood cell disorders. Cells are detected using an R-CNN architecture. With the features extracted for each cell, a multiple instance learning method classifies patient samples into one out of four blood cell disorders. The attention mechanism provides a measure of the contribution of each cell to the overall classification and significantly improves the networks classification accuracy as well as its interpretability for the medical expert.
Peng, T. ; Lamm, L. ; Loeffler, D. ; Ahmed, N. ; Navab, N. ; Schroeder, T. ; Marr, C.
In:. 2020. 174-183 (Lect. Notes Comput. Sc. ; 12265 LNCS)
Due to the inherent imperfections in the optical path, microscopy images, particularly fluorescence microscopy images, are often skewed by uneven illumination and hence have spurious intensity variation, also known as shading or vignetting effect. Besides spatial intensity inhomogeneity, time-lapse microscopy imaging further suffers from background variation in time, mostly due to photo-bleaching of the background medium. Moreover, the temporal background variation is often experiment-specific and hence cannot be easily corrected, in contrast to shading, where a prospective calibration method can be used. Existing retrospective illumination correction methods, ranging from simple multi-image averaging to sophisticated optimisation based methods such as CIDRE and BaSiC, all assume that the foreground of all images is uncorrelated between each other. However, this assumption is violated in e.g. long-term time-lapse microscopy imaging of adherent stem cells, in which a strong foreground correlation is observed from frame to frame. In this paper, we propose a new illumination and background correction method for time-lapse imaging, based on low-rank and sparse decomposition. We incorporate binary segmentation masks that inform the weighting scheme of our reweighted L1 norm minimisation about foreground vs background pixels in the image. This yields a better separation of the low-rank and sparse component, hence improving the estimation of illumination profiles. Experiments on both simulated and real time-lapse data demonstrate that our approach is superior to existing illumination correction methods and improves single cell quantification.
Schuh, L. ; Loos, C. ; Pokrovsky, D. ; Imhof, A. ; Rupp, R.A.W. ; Marr, C.
Cell Syst. 11, 653-662.e8 (2020)
H4K20me kinetics in normal and cell-cycle-arrested Xenopus embryos. This quantitative model invokes specific methylation and unspecific demethylation and correctly predicts cell-cycle durations and cell-cycle dependencies. Active demethylation is not required to explain H4K20me kinetics of cycling cells, suggesting that overall H4K20me dilution through DNA replication is dominant. So only once cells stop cycling during embryogenesis, active H4K20 demethylation may contribute to shape histone methylation.
Wissenschaftlicher Artikel
Scientific Article
Hulstaert, E. ; Morlion, A. ; Avila Cobos, F. ; Verniers, K. ; Nuytens, J. ; Vanden Eynde, E. ; Yigit, N. ; Anckaert, J. ; Geerts, A. ; Hindryckx, P. ; Jacques, P. ; Brusselle, G. ; Bracke, K.R. ; Maes, T. ; Malfait, T. ; Derveaux, T. ; Ninclaus, V. ; Van Cauwenbergh, C. ; Roelens, K. ; Roets, E. ; Hemelsoet, D. ; Tilleman, K. ; Brochez, L. ; Kuersten, S. ; Simon, L.M. ; Karg, S. ; Kautzky-Willers, A. ; Leutner, M. ; Nöhammer, C. ; Slaby, O. ; Prins, R.W. ; Koster, J. ; Lefever, S. ; Schroth, G.P. ; Vandesompele, J. ; Mestdagh, P.
Cell Rep. 33:108552 (2020)
Extracellular RNAs present in biofluids have emerged as potential biomarkers for disease. Where most studies focus on blood-derived fluids, other biofluids may be more informative. We present an atlas of messenger, circular, and small RNA transcriptomes of a comprehensive collection of 20 human biofluids. By means of synthetic spike-in controls, we compare RNA content across biofluids, revealing a 10,000-fold difference in concentration. The circular RNA fraction is increased in most biofluids compared to tissues. Each biofluid transcriptome is enriched for RNA molecules derived from specific tissues and cell types. Our atlas enables an informed selection of the most relevant biofluid to monitor particular diseases. To verify the biomarker potential in these biofluids, four validation cohorts representing a broad spectrum of diseases were profiled, revealing numerous differential RNAs between case and control subjects. Spike-normalized data are publicly available in the R2 web portal for further exploration.
Wissenschaftlicher Artikel
Scientific Article
Pietzner, M. ; Wheeler, E. ; Carrasco-Zanini, J. ; Raffler, J. ; Kerrison, N.D. ; Oerton, E. ; Auyeung, V.P.W. ; Luan, J. ; Finan, C. ; Casas, J.P. ; Ostroff, R. ; Williams, S.A. ; Kastenmüller, G. ; Ralser, M. ; Gamazon, E.R. ; Wareham, N.J. ; Hingorani, A.D. ; Langenberg, C.
Nat. Commun. 11:6397 (2020)
Understanding the genetic architecture of host proteins interacting with SARS-CoV-2 or mediating the maladaptive host response to COVID-19 can help to identify new or repurpose existing drugs targeting those proteins. We present a genetic discovery study of 179 such host proteins among 10,708 individuals using an aptamer-based technique. We identify 220 host DNA sequence variants acting in cis (MAF 0.01-49.9%) and explaining 0.3-70.9% of the variance of 97 of these proteins, including 45 with no previously known protein quantitative trait loci (pQTL) and 38 encoding current drug targets. Systematic characterization of pQTLs across the phenome identified protein-drug-disease links and evidence that putative viral interaction partners such as MARK3 affect immune response. Our results accelerate the evaluation and prioritization of new drug development programmes and repurposing of trials to prevent, treat or reduce adverse outcomes. Rapid sharing and detailed interrogation of results is facilitated through an interactive webserver (https://omicscience.org/apps/covidpgwas/).
Wissenschaftlicher Artikel
Scientific Article
Suarez, A. ; Lahti, J. ; Lahti-Pulkkinen, M. ; Girchenko, P. ; Czamara, D. ; Knauer-Arloth, J. ; Malmberg, A.L. ; Hämäläinen, E. ; Kajantie, E. ; Laivuori, H. ; Villa, P.M. ; Reynolds, R.M. ; Provençal, N. ; Binder, E.B. ; Räikkönen, K.
Neurobiol. Stress 13:100275 (2020)
Background: Maternal depression and anxiety during pregnancy may enhance fetal exposure to glucocorticoids (GCs) and harm neurodevelopment. We tested whether a novel cross-tissue polyepigenetic biomarker indicative of in utero exposure to GC is associated with mental and behavioral disorders and their severity in children, possibly mediating the associations between maternal prenatal depressive and anxiety symptoms and these child outcomes. Methods: Children (n = 814) from the Prediction and Prevention of Preeclampsia and Intrauterine Growth Restriction (PREDO) study were followed-up from birth to age 7.1–10.7 years. A weighted polyepigenetic GC exposure score was calculated based on the methylation profile of 24 CpGs from umbilical cord blood. Child diagnosis of mental and behavioral disorder (n = 99) and its severity, defined as the number of days the child had received treatment (all 99 had received outpatient treatment and 8 had been additionally in inpatient treatment) for mental or behavioral disorder as the primary diagnosis, came from the Care Register for Health Care. Mothers (n = 408) reported on child total behavior problems at child's age of 2.3–5.8 years and their own depressive and anxiety symptoms during pregnancy (n = 583). Results: The fetal polyepigenetic GC exposure score at birth was not associated with child hazard of mental and behavioral disorder (HR = 0.82, 95% CI 0.54; 1.24, p = 0.35) or total behavior problems (unstandardized beta = −0.10, 95% CI -0.31; 0.10, p = 0.33). However, for one standard deviation decrease in the polyepigenetic score, the child had spent 2.94 (95%CI 1.59; 5.45, p < 0.001) more days in inpatient or outpatient treatment with any mental and behavioral disorder as the primary diagnosis. Criteria for mediation tests were not met. Conclusions: These findings suggest that fetal polyepigenetic GC exposure score at birth was not associated with any mental or behavioral disorder diagnosis or mother-rated total behavior problems, but it may contribute to identifying children at birth who are at risk for more severe mental or behavioral disorders.
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Scientific Article
Ott, R. ; Pawlow, X. ; Weiss, A. ; Hofelich, A. ; Herbst, M. ; Hummel, N. ; Prehn, C. ; Adamski, J. ; Römisch-Margl, W. ; Kastenmüller, G. ; Ziegler, A.-G. ; Hummel, S.
Int. J. Mol. Sci. 21:9647 (2020)
Shared metabolomic patterns at delivery have been suggested to underlie the mother-to-child transmission of adverse metabolic health. This study aimed to investigate whether mothers with gestational diabetes mellitus (GDM) and their offspring show similar metabolomic patterns several years postpartum. Targeted metabolomics (including 137 metabolites) was performed in plasma samples obtained during an oral glucose tolerance test from 48 mothers with GDM and their offspring at a cross-sectional study visit 8 years after delivery. Partial Pearson’s correlations between the area under the curve (AUC) of maternal and offspring metabolites were calculated, yielding so-called Gaussian graphical models. Spearman’s correlations were applied to investigate correlations of body mass index (BMI), Matsuda insulin sensitivity index (ISI-M), dietary intake, and physical activity between generations, and correlations of metabolite AUCs with lifestyle variables. This study revealed that BMI, ISI-M, and the AUC of six metabolites (carnitine, taurine, proline, SM(-OH) C14:1, creatinine, and PC ae C34:3) were significantly correlated between mothers and offspring several years postpartum. Intergenerational metabolite correlations were independent of shared BMI, ISI-M, age, sex, and all other metabolites. Furthermore, creatinine was correlated with physical activity in mothers. This study suggests that there is long-term metabolic programming in the offspring of mothers with GDM and informs us about targets that could be addressed by future intervention studies.
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Scientific Article
Chlis, N.-K. ; Rausch, L. ; Brocker, T. ; Kranich, J. ; Theis, F.J.
Nucleic Acids Res. 48, 11335-11346 (2020)
High-content imaging and single-cell genomics are two of the most prominent high-throughput technologies for studying cellular properties and functions at scale. Recent studies have demonstrated that information in large imaging datasets can be used to estimate gene mutations and to predict the cell-cycle state and the cellular decision making directly from cellular morphology. Thus, high-throughput imaging methodologies, such as imaging flow cytometry can potentially aim beyond simple sorting of cellpopulations. We introduce IFC-seq, a machine learning methodology for predicting the expression profile of every cell in an imaging flow cytometry experiment. Since it is to-date unfeasible to observe singlecell gene expression and morphology in flow, we integrate uncoupled imaging data with an independent transcriptomics dataset by leveraging common surface markers. We demonstrate that IFC-seq successfully models gene expression of a moderate number of key gene-markers for two independent imaging flow cytometry datasets: (i) human blood mononuclear cells and (ii) mouse myeloid progenitor cells. In the case of mouse myeloid progenitor cells IFC-seq can predict gene expression directly from brightfield images in a label-free manner, using a convolutional neural network. The proposed method promises to add gene expression information to existing and new imaging flow cytometry datasets, at no additional cost.
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Scientific Article
Kiwitz, K. ; Schiffer, C. ; Spitzer, H. ; Dickscheid, T. ; Amunts, K.
Sci. Rep. 10:22039 (2020)
The distribution of neurons in the cortex (cytoarchitecture) differs between cortical areas and constitutes the basis for structural maps of the human brain. Deep learning approaches provide a promising alternative to overcome throughput limitations of currently used cytoarchitectonic mapping methods, but typically lack insight as to what extent they follow cytoarchitectonic principles. We therefore investigated in how far the internal structure of deep convolutional neural networks trained for cytoarchitectonic brain mapping reflect traditional cytoarchitectonic features, and compared them to features of the current grey level index (GLI) profile approach. The networks consisted of a 10-block deep convolutional architecture trained to segment the primary and secondary visual cortex. Filter activations of the networks served to analyse resemblances to traditional cytoarchitectonic features and comparisons to the GLI profile approach. Our analysis revealed resemblances to cellular, laminar- as well as cortical area related cytoarchitectonic features. The networks learned filter activations that reflect the distinct cytoarchitecture of the segmented cortical areas with special regard to their laminar organization and compared well to statistical criteria of the GLI profile approach. These results confirm an incorporation of relevant cytoarchitectonic features in the deep convolutional neural networks and mark them as a valid support for high-throughput cytoarchitectonic mapping workflows.
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Scientific Article
Melnyk, O. ; Forstner, A. ; Krahmer, F. ; Sissouno, N.
In: (28th European Signal Processing Conference (EUSIPCO), 24-28 August 2020). IEEE, 2020. 975-979 ( ; 2021-January)
In this paper, we consider a special case of the phase retrieval problem called ptychography. Its is a popular technique of imaging, based on local illuminations of a specimen and further reconstruction from the far field diffraction patterns. The stability and success of the recovery process is heavily based on the choice of the illumination function commonly called a window. It describes the distribution of the light along the measured region. While for some windows the conditioning can be controlled, many important classes of windows, such as Gaussian windows, were not covered. We present a subspace completion method, which allows for a well-conditioned reconstruction for a much wider choice of windows, including Gaussian windows.
Zhu, H. ; Blahnová, V.H. ; Perale,G. ; Xiao, J. ; Betge, F. ; Boniolo, F ; Filová, E. ; Lyngstadaas, S.B. ; Haugen, H.J.
Front. Cell Dev. Biol. 8:619111 (2020)
Bone defect is a noteworthy health problem and is the second most transplanted tissue after blood. Numerous bone grafts are designed and applied in clinics. Limitations, however, from different aspects still exist, including limited supply, mechanical strength, and bioactivity. In this study, two biomimetic peptides (P2 and P6) are incorporated into a composite bioactive xeno hybrid bone graft named SmartBonePep®, with the aim to increase the bioactivity of the bone graft. The results, which include cytotoxicity, proliferation rate, confocal microscopy, gene expression, and protein qualification, successfully prove that the SmartBonePep® has multi-modal biological effects on human mesenchymal stem cells from bone marrow. The effective physical entrapment of P6 into a composite xeno-hybrid bone graft, withstanding manufacturing processes including exposure to strong organic solvents and ethylene oxide sterilization, increases the osteogenic potential of the stem cells as well as cell attachment and proliferation. P2 and P6 both show a strong biological potential and may be future candidates for enhancing the clinical performance of bone grafts.
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Scientific Article
Lotfollahi, M. ; Naghipourfar, M. ; Theis, F.J. ; Wolf, F.A.
Bioinformatics 36, 2, i610-i617 (2020)
MOTIVATION: While generative models have shown great success in sampling high-dimensional samples conditional on low-dimensional descriptors (stroke thickness in MNIST, hair color in CelebA, speaker identity in WaveNet), their generation out-of-distribution poses fundamental problems due to the difficulty of learning compact joint distribution across conditions. The canonical example of the conditional variational autoencoder (CVAE), for instance, does not explicitly relate conditions during training and, hence, has no explicit incentive of learning such a compact representation. RESULTS: We overcome the limitation of the CVAE by matching distributions across conditions using maximum mean discrepancy in the decoder layer that follows the bottleneck. This introduces a strong regularization both for reconstructing samples within the same condition and for transforming samples across conditions, resulting in much improved generalization. As this amount to solving a style-transfer problem, we refer to the model as transfer VAE (trVAE). Benchmarking trVAE on high-dimensional image and single-cell RNA-seq, we demonstrate higher robustness and higher accuracy than existing approaches. We also show qualitatively improved predictions by tackling previously problematic minority classes and multiple conditions in the context of cellular perturbation response to treatment and disease based on high-dimensional single-cell gene expression data. For generic tasks, we improve Pearson correlations of high-dimensional estimated means and variances with their ground truths from 0.89 to 0.97 and 0.75 to 0.87, respectively. We further demonstrate that trVAE learns cell-type-specific responses after perturbation and improves the prediction of most cell-type-specific genes by 65%. AVAILABILITY AND IMPLEMENTATION: The trVAE implementation is available via github.com/theislab/trvae. The results of this article can be reproduced via github.com/theislab/trvae_reproducibility.
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Scientific Article
Dorigatti, E. ; Schubert, B.
Bioinformatics 36, 2, i643-i650 (2020)
MOTIVATION: Conceptually, epitope-based vaccine design poses two distinct problems: (i) selecting the best epitopes to elicit the strongest possible immune response and (ii) arranging and linking them through short spacer sequences to string-of-beads vaccines, so that their recovery likelihood during antigen processing is maximized. Current state-of-the-art approaches solve this design problem sequentially. Consequently, such approaches are unable to capture the inter-dependencies between the two design steps, usually emphasizing theoretical immunogenicity over correct vaccine processing, thus resulting in vaccines with less effective immunogenicity in vivo. RESULTS: In this work, we present a computational approach based on linear programming, called JessEV, that solves both design steps simultaneously, allowing to weigh the selection of a set of epitopes that have great immunogenic potential against their assembly into a string-of-beads construct that provides a high chance of recovery. We conducted Monte Carlo cleavage simulations to show that a fixed set of epitopes often cannot be assembled adequately, whereas selecting epitopes to accommodate proper cleavage requirements substantially improves their recovery probability and thus the effective immunogenicity, pathogen and population coverage of the resulting vaccines by at least 2-fold. AVAILABILITY AND IMPLEMENTATION: The software and the data analyzed are available at https://github.com/SchubertLab/JessEV. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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Scientific Article
Wang, D. ; Hensman, J. ; Kutkaite, G. ; Toh, T.S. ; Galhoz, A. ; Dry, J.R. ; Saez-Rodriguez, J. ; Garnett, M.J. ; Menden, M. ; Dondelinger, F.
eLife 9:e60352 (2020)
High-throughput testing of drugs across molecular-characterised cell lines can identify candidate treatments and discover biomarkers. However, the cells' response to a drug is typically quantified by a summary statistic from a best-fit dose-response curve, whilst neglecting the uncertainty of the curve fit and the potential variability in the raw readouts. Here, we model the experimental variance using Gaussian Processes, and subsequently, leverage uncertainty estimates to identify associated biomarkers with a new Bayesian framework. Applied to in vitro screening data on 265 compounds across 1074 cancer cell lines, our models identified 24 clinically established drug-response biomarkers, and provided evidence for six novel biomarkers by accounting for association with low uncertainty. We validated our uncertainty estimates with an additional drug screen of 26 drugs, 10 cell lines with 8 to 9 replicates. Our method is applicable to any dose-response data without replicates, and improves biomarker discovery for precision medicine.
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Scientific Article
Fuetterer, C. ; Augustin, T. ; Fuchs, C.
Adv. Data Anal. Classif. 14, 885-896 (2020)
The analysis of single-cell RNA sequencing data is of great importance in health research. It challenges data scientists, but has enormous potential in the context of personalized medicine. The clustering of single cells aims to detect different subgroups of cell populations within a patient in a data-driven manner. Some comparison studies denote single-cell consensus clustering (SC3), proposed by Kiselev et al. (Nat Methods 14(5):483–486, 2017), as the best method for classifying single-cell RNA sequencing data. SC3 includes Laplacian eigenmaps and a principal component analysis (PCA). Our proposal of unsupervised adapted single-cell consensus clustering (adaSC3) suggests to replace the linear PCA by diffusion maps, a non-linear method that takes the transition of single cells into account. We investigate the performance of adaSC3 in terms of accuracy on the data sets of the original source of SC3 as well as in a simulation study. A comparison of adaSC3 with SC3 as well as with related algorithms based on further alternative dimension reduction techniques shows a quite convincing behavior of adaSC3.
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Scientific Article
Litviňuková, M. ; Talavera-López, C. ; Maatz, H. ; Reichart, D. ; Worth, C.L. ; Lindberg, E.L. ; Kanda, M. ; Polanski, K. ; Heinig, M. ; Lee, M. ; Nadelmann, E.R. ; Roberts, K. ; Tuck, L. ; Fasouli, E.S. ; DeLaughter, D.M. ; McDonough, B. ; Wakimoto, H. ; Gorham, J.M. ; Samari, S. ; Mahbubani, K.T. ; Saeb-Parsy, K. ; Patone, G. ; Boyle, J.J. ; Zhang, H. ; Viveiros, A. ; Oudit, G.Y. ; Bayraktar, O.A. ; Seidman, J.G. ; Seidman, C.E. ; Noseda, M. ; Hubner, N. ; Teichmann, S.A.
Nature 588, 466-472 (2020)
Cardiovascular disease is the leading cause of death worldwide. Advanced insights into disease mechanisms and therapeutic strategies require a deeper understanding of the molecular processes involved in the healthy heart. Knowledge of the full repertoire of cardiac cells and their gene expression profiles is a fundamental first step in this endeavour. Here, using state-of-the-art analyses of large-scale single-cell and single-nucleus transcriptomes, we characterize six anatomical adult heart regions. Our results highlight the cellular heterogeneity of cardiomyocytes, pericytes and fibroblasts, and reveal distinct atrial and ventricular subsets of cells with diverse developmental origins and specialized properties. We define the complexity of the cardiac vasculature and its changes along the arterio-venous axis. In the immune compartment, we identify cardiac-resident macrophages with inflammatory and protective transcriptional signatures. Furthermore, analyses of cell-to-cell interactions highlight different networks of macrophages, fibroblasts and cardiomyocytes between atria and ventricles that are distinct from those of skeletal muscle. Our human cardiac cell atlas improves our understanding of the human heart and provides a valuable reference for future studies.
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Scientific Article
Kranich, J. ; Chlis, N.-K. ; Rausch, L. ; Latha, A. ; Schifferer, M. ; Kurz, T. ; Foltyn-Arfa Kia, A. ; Simons, M. ; Theis, F.J. ; Brocker, T.
J. Extra. Vesicles 9:1792683 (2020)
The in vivo detection of dead cells remains a major challenge due to technical hurdles. Here, we present a novel method, where injection of fluorescent milk fat globule-EGF factor 8 protein (MFG-E8) in vivo combined with imaging flow cytometry and deep learning allows the identification of dead cells based on their surface exposure of phosphatidylserine (PS) and other image parameters. A convolutional autoencoder (CAE) was trained on defined pictures and successfully used to identify apoptotic cells in vivo. However, unexpectedly, these analyses also revealed that the great majority of PS+ cells were not apoptotic, but rather live cells associated with PS+ extracellular vesicles (EVs). During acute viral infection apoptotic cells increased slightly, while up to 30% of lymphocytes were decorated with PS+ EVs of antigen-presenting cell (APC) exosomal origin. The combination of recombinant fluorescent MFG-E8 and the CAE-method will greatly facilitate analyses of cell death and EVs in vivo.
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Scientific Article
Fiorentino, J. ; Torres-Padilla, M.E. ; Scialdone, A.
Annu. Rev. Genet. 54, 167-187 (2020)
Cellular heterogeneity is a property of any living system; however, its relationship with cellular fate decision remains an open question. Recent technological advances have enabled valuable insights, especially in complex systems such as the mouse embryo. In this review, we discuss recent studies that characterize cellular heterogeneity at different levels during mouse development, from the two-cell stage up to gastrulation. In addition to key experimental findings, we review mathematical modeling approaches that help researchers interpret these findings. Disentangling the role of heterogeneity in cell fate decision will likely rely on the refined integration of experiments, large-scale omics data, and mathematical modeling, complemented by the use of synthetic embryos and gastruloids as promising in vitro models.
Review
Review
Matek, C. ; Spiekermann, K. ; Marr, C.
Tumordiagnos. Ther. 41, 666-668 (2020)
Review
Review
Lupperger, V. ; Marr, C. ; Chapouton, P.
PLoS Biol. 18:e3000708 (2020)
Regulation of quiescence and cell cycle entry is pivotal for the maintenance of stem cell populations. Regulatory mechanisms, however, are poorly understood. In particular, it is unclear how the activity of single stem cells is coordinated within the population or if cells divide in a purely random fashion. We addressed this issue by analyzing division events in an adult neural stem cell (NSC) population of the zebrafish telencephalon. Spatial statistics and mathematical modeling of over 80,000 NSCs in 36 brain hemispheres revealed weakly aggregated, nonrandom division patterns in space and time. Analyzing divisions at 2 time points allowed us to infer cell cycle and S-phase lengths computationally. Interestingly, we observed rapid cell cycle reentries in roughly 15% of newly born NSCs. In agent-based simulations of NSC populations, this redividing activity sufficed to induce aggregated spatiotemporal division patterns that matched the ones observed experimentally. In contrast, omitting redivisions leads to a random spatiotemporal distribution of dividing cells. Spatiotemporal aggregation of dividing stem cells can thus emerge solely from the cell's history.
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Scientific Article
Langenau, J. ; Oluwagbemigun, K. ; Brachem, C. ; Lieb, W. ; di Giuseppe, R. ; Artati, A. ; Kastenmüller, G. ; Weinhold, L. ; Schmid, M. ; Nöthlings, U.
Metabolites 10:468 (2020)
Metabolomics can be a tool to identify dietary biomarkers. However, reported food-metabolite associations have been inconsistent, and there is a need to explore further associations. Our aims were to confirm previously reported food-metabolite associations and to identify novel food-metabolite associations. We conducted a cross-sectional analysis of data from 849 participants (57% men) of the PopGen cohort. Dietary intake was obtained using FFQ and serum metabolites were profiled by an untargeted metabolomics approach. We conducted a systematic literature search to identify previously reported food-metabolite associations and analyzed these associations using linear regression. To identify potential novel food-metabolite associations, datasets were split into training and test datasets and linear regression models were fitted to the training datasets. Significant food-metabolite associations were evaluated in the test datasets. Models were adjusted for covariates. In the literature, we identified 82 food-metabolite associations. Of these, 44 associations were testable in our data and confirmed associations of coffee with 12 metabolites, of fish with five, of chocolate with two, of alcohol with four, and of butter, poultry and wine with one metabolite each. We did not identify novel food-metabolite associations; however, some associations were sex-specific. Potential use of some metabolites as biomarkers should consider sex differences in metabolism.
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Scientific Article
Chlis, N.-K. ; Karlas, A. ; Fasoula, N.-A. ; Kallmayer, M. ; Eckstein, H.H. ; Theis, F.J. ; Ntziachristos, V. ; Marr, C.
Photoacoustics 20:100203 (2020)
Multispectral Optoacoustic Tomography (MSOT) resolves oxy- (HbO2) and deoxy-hemoglobin (Hb) to perform vascular imaging. MSOT suffers from gradual signal attenuation with depth due to light-tissue interactions: an effect that hinders the precise manual segmentation of vessels. Furthermore, vascular assessment requires functional tests, which last several minutes and result in recording thousands of images. Here, we introduce a deep learning approach with a sparse-UNET (S-UNET) for automatic vascular segmentation in MSOT images to avoid the rigorous and time-consuming manual segmentation. We evaluated the S-UNET on a test-set of 33 images, achieving a median DICE score of 0.88. Apart from high segmentation performance, our method based its decision on two wavelengths with physical meaning for the task-at-hand: 850 nm (peak absorption of oxy-hemoglobin) and 810 nm (isosbestic point of oxy-and deoxy-hemoglobin). Thus, our approach achieves precise data-driven vascular segmentation for automated vascular assessment and may boost MSOT further towards its clinical translation.
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Scientific Article
Philipp, J. ; Le Gleut, R. ; von Toerne, C. ; Subedi, P. ; Azimzadeh, O. ; Atkinson, M.J. ; Tapio, S.
Proteomes 8:30 (2020)
Radiation-induced inflammation leading to the permeability of the endothelial barrier may increase the risk of cardiovascular disease. The aim of this study was to investigate potential mechanisms in vitro at the level of the proteome in human coronary artery endothelial cells (HCECest2) that were exposed to radiation doses of 0, 0.25, 0.5, 2.0 and 10 Gy (60Co-γ). Proteomics analysis was performed using mass spectrometry in a label-free data-independent acquisition mode. The data were validated using bioinformatics and immunoblotting. The low-and moderate-dose-irradiated samples (0.25 Gy, 0.5 Gy) showed only scarce proteome changes. In contrast, an activation of DNA-damage repair, inflammation, and oxidative stress pathways was seen after the high-dose treatments (2 and 10 Gy). The level of the DNA damage response protein DDB2 was enhanced early at the 10 Gy dose. The expression of proteins belonging to the inflammatory response or cGAS-STING pathway (STING, STAT1, ICAM1, ISG15) increased in a dose-dependent manner, showing the strongest effects at 10 Gy after one week. This study suggests a connection between the radiation-induced DNA damage and the induction of inflammation which supports the inhibition of the cGAS-STING pathway in the prevention of radiation-induced cardiovascular disease.
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Scientific Article
zu Castell, W. ; Schrenk, H.
Sci. Rep. 10:18175 (2020)
Gunderson's and Holling's adaptive cycle metaphor provides a qualitative description of the development of a dynamically evolving complex system. According to the metaphor, a complex system alternately passes through phases of stability and predictability and phases of reorganization and stochasticity. So far, there have been no attempts to quantify the underlying notions in a way which is independent of the concrete realization of the system. We propose a method which can be applied in a generic way to estimate a system's position within the adaptive cycle as well as to identify drivers of change. We demonstrate applicability and flexibility of our method by three different case studies: Analyzing data obtained from a simulation of a model of interaction of abstract genotypes, we show that our approach is able to capture the nature of these interactions. We then study European economies as systems of economic state variables to illustrate the ability of system comparison. Finally, we identify drivers of change in a plant ecosystem in the prairie-forest. We hereby confirm the conceptual dynamics of the adaptive cycle and thus underline its usability in understanding system dynamics.
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Scientific Article
Ansari, M. ; Fischer, D.S. ; Theis, F.J.
Lect. Notes Comput. Sc. 12396 LNCS, 105-114 (2020)
Technological advances in the last decade resulted in an explosion of biological data. Sequencing methods in particular provide large-scale data sets as resource for incorporation of machine learning in the biological field. By measuring DNA accessibility for instance, enzymatic hypersensitivity assays facilitate identification of regions of open chromatin in the genome, marking potential locations of regulatory elements. ATAC-seq is the primary method of choice to determine these footprints. It allows measurements on the cellular level, complementing the recent progress in single cell transcriptomics. However, as the method-specific enzymes tend to bind preferentially to certain sequences, the accessibility profile is confounded by binding specificity. The inference of open chromatin should be adjusted for this bias[1]. To enable such corrections, we built a deep learning model that learns the sequence specificity of ATAC-seq’s enzyme Tn5 on naked DNA. We found binding preferences and demonstrate that cleavage patterns specific to Tn5 can successfully be discovered by the means of convolutional neural networks. Such models can be combined with accessibility analysis in the future in order to predict bias on new sequences and furthermore provide a better picture of the regulatory landscape of the genome.
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Scientific Article
Filbir, F. ; Liehr, L.
Front. App. Math. Stat. 6:556585 (2020)
In this study, we are concerned with the effect of certain linear transformations of a signal f on its phase. We are, in particular, interested in phase distortions caused by band-limiting operations. The band-limiting operators serve as a motivation for studying the class of phase-preserving operators. This class will be completely characterized.
Review
Review
Pieschner, S. ; Fuchs, C.
R. Soc. Open Sci. 7:200270 (2020)
Modelling random dynamical systems in continuous time, diffusion processes are a powerful tool in many areas of science. Model parameters can be estimated from time-discretely observed processes using Markov chain Monte Carlo (MCMC) methods that introduce auxiliary data. These methods typically approximate the transition densities of the process numerically, both for calculating the posterior densities and proposing auxiliary data. Here, the Euler-Maruyama scheme is the standard approximation technique. However, the MCMC method is computationally expensive. Using higher-order approximations may accelerate it, but the specific implementation and benefit remain unclear. Hence, we investigate the utilization and usefulness of higher-order approximations in the example of the Milstein scheme. Our study demonstrates that the MCMC methods based on the Milstein approximation yield good estimation results. However, they are computationally more expensive and can be applied to multidimensional processes only with impractical restrictions. Moreover, the combination of the Milstein approximation and the well-known modified bridge proposal introduces additional numerical challenges.
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Hofmeister, B.T. ; Denkena, J. ; Colomé-Tatché, M. ; Shahryary, Y. ; Hazarika, R. ; Grimwood, J. ; Mamidi, S. ; Jenkins, J. ; Grabowski, P.P. ; Sreedasyam, A. ; Shu, S. ; Barry, K. ; Lail, K. ; Adam, C. ; Lipzen, A. ; Sorek, R. ; Kudrna, D. ; Talag, J. ; Wing, R. ; Hall, D.W. ; Jacobsen, D. ; Tuskan, G.A. ; Schmutz, J. ; Johannes, F. ; Schmitz, R.J.
Genome Biol. 21:259 (2020)
BackgroundPlants can transmit somatic mutations and epimutations to offspring, which in turn can affect fitness. Knowledge of the rate at which these variations arise is necessary to understand how plant development contributes to local adaption in an ecoevolutionary context, particularly in long-lived perennials.ResultsHere, we generate a new high-quality reference genome from the oldest branch of a wild Populus trichocarpa tree with two dominant stems which have been evolving independently for 330years. By sampling multiple, age-estimated branches of this tree, we use a multi-omics approach to quantify age-related somatic changes at the genetic, epigenetic, and transcriptional level. We show that the per-year somatic mutation and epimutation rates are lower than in annuals and that transcriptional variation is mainly independent of age divergence and cytosine methylation. Furthermore, a detailed analysis of the somatic epimutation spectrum indicates that transgenerationally heritable epimutations originate mainly from DNA methylation maintenance errors during mitotic rather than during meiotic cell divisions.ConclusionTaken together, our study provides unprecedented insights into the origin of nucleotide and functional variation in a long-lived perennial plant.
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Scientific Article
Shahryary, Y. ; Symeonidi, A. ; Hazarika, R.R. ; Denkena, J. ; Mubeen, T. ; Hofmeister, B. ; Van Gurp, T. ; Colomé-Tatché, M. ; Verhoeven, K.J.F. ; Tuskan, G. ; Schmitz, R.J. ; Johannes, F.
Genome Biol. 21:33023650 (2020)
Stochastic changes in DNA methylation (i.e., spontaneous epimutations) contribute to methylome diversity in plants. Here, we describe AlphaBeta, a computational method for estimating the precise rate of such stochastic events using pedigree-based DNA methylation data as input. We demonstrate how AlphaBeta can be employed to study transgenerationally heritable epimutations in clonal or sexually derived mutation accumulation lines, as well as somatic epimutations in long-lived perennials. Application of our method to published and new data reveals that spontaneous epimutations accumulate neutrally at the genome-wide scale, originate mainly during somatic development and that they can be used as a molecular clock for age-dating trees.
Wissenschaftlicher Artikel
Scientific Article
Benedetti, E. ; Pučić-Baković, M. ; Keser, T. ; Gerstner, N. ; Büyüközkan, M. ; Štambuk, T. ; Selman, M.H.J. ; Rudan, I. ; Polašek, O. ; Hayward, C. ; Al-Amin, H. ; Suhre, K. ; Kastenmüller, G. ; Lauc, G. ; Krumsiek, J.
Nat. Commun. 11:5153 (2020)
Correlation networks are frequently used to statistically extract biological interactions between omics markers. Network edge selection is typically based on the statistical significance of the correlation coefficients. This procedure, however, is not guaranteed to capture biological mechanisms. We here propose an alternative approach for network reconstruction: a cutoff selection algorithm that maximizes the overlap of the inferred network with available prior knowledge. We first evaluate the approach on IgG glycomics data, for which the biochemical pathway is known and well-characterized. Importantly, even in the case of incomplete or incorrect prior knowledge, the optimal network is close to the true optimum. We then demonstrate the generalizability of the approach with applications to untargeted metabolomics and transcriptomics data. For the transcriptomics case, we demonstrate that the optimized network is superior to statistical networks in systematically retrieving interactions that were not included in the biological reference used for optimization.
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Scientific Article
Sieberts, S.K. ; Perumal, T.M. ; Carrasquillo, M.M. ; Allen, M. ; Reddy, J.S. ; Hoffman, G.E. ; Dang, K.K. ; Calley, J. ; Ebert, P.J. ; Eddy, J. ; Wang, X. ; Greenwood, A.K. ; Mostafavi, S. ; Omberg, L. ; Peters, M.A. ; Logsdon, B.A. ; de Jager, P.L. ; Ertekin-Taner, N. ; Mangravite, L.M. ; The AMP-AD Consortium (Arnold, M.)
Sci. Data 7:340 (2020)
The availability of high-quality RNA-sequencing and genotyping data of post-mortem brain collections from consortia such as CommonMind Consortium (CMC) and the Accelerating Medicines Partnership for Alzheimer’s Disease (AMP-AD) Consortium enable the generation of a large-scale brain cis-eQTL meta-analysis. Here we generate cerebral cortical eQTL from 1433 samples available from four cohorts (identifying >4.1 million significant eQTL for >18,000 genes), as well as cerebellar eQTL from 261 samples (identifying 874,836 significant eQTL for >10,000 genes). We find substantially improved power in the meta-analysis over individual cohort analyses, particularly in comparison to the Genotype-Tissue Expression (GTEx) Project eQTL. Additionally, we observed differences in eQTL patterns between cerebral and cerebellar brain regions. We provide these brain eQTL as a resource for use by the research community. As a proof of principle for their utility, we apply a colocalization analysis to identify genes underlying the GWAS association peaks for schizophrenia and identify a potentially novel gene colocalization with lncRNA RP11-677M14.2 (posterior probability of colocalization 0.975).
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Scientific Article
Fischer, C.A, ; Besora-Casals, L. ; Rolland, S.G. ; Haeussler, S. ; Singh, K. ; Duchen, M. ; Conradt, B. ; Marr, C.
iScience 23:101601 (2020)
While the analysis of mitochondrial morphology has emerged as a key tool in the study of mitochondrial function, efficient quantification of mitochondrial microscopy images presents a challenging task and bottleneck for statistically robust conclusions. Here, we present Mitochondrial Segmentation Network (MitoSegNet), a pretrained deep learning segmentation model that enables researchers to easily exploit the power of deep learning for the quantification of mitochondrial morphology. We tested the performance of MitoSegNet against three feature-based segmentation algorithms and the machine-learning segmentation tool Ilastik. MitoSegNet outperformed all other methods in both pixelwise and morphological segmentation accuracy. We successfully applied MitoSegNet to unseen fluorescence microscopy images of mitoGFP expressing mitochondria in wild-type and catp-6ATP13A2 mutant C. elegans adults. Additionally, MitoSegNet was capable of accurately segmenting mitochondria in HeLa cells treated with fragmentation inducing reagents. We provide MitoSegNet in a toolbox for Windows and Linux operating systems that combines segmentation with morphological analysis.
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Scientific Article
Holmberg, O. ; Köhler, N. ; Martins, T. ; Siedlecki, J. ; Herold, T. ; Keidel, L. ; Asani, B. ; Schiefelbein, J. ; Priglinger, S. ; Kortuem, K.U. ; Theis, F.J.
Nat. Mach. Intell. 2, 719-726 (2020)
Access to large, annotated samples represents a considerable challenge for training accurate deep-learning models in medical imaging. Although at present transfer learning from pre-trained models can help with cases lacking data, this limits design choices and generally results in the use of unnecessarily large models. Here we propose a self-supervised training scheme for obtaining high-quality, pre-trained networks from unlabelled, cross-modal medical imaging data, which will allow the creation of accurate and efficient models. We demonstrate the utility of the scheme by accurately predicting retinal thickness measurements based on optical coherence tomography from simple infrared fundus images. Subsequently, learned representations outperformed advanced classifiers on a separate diabetic retinopathy classification task in a scenario of scarce training data. Our cross-modal, three-stage scheme effectively replaced 26,343 diabetic retinopathy annotations with 1,009 semantic segmentations on optical coherence tomography and reached the same classification accuracy using only 25% of fundus images, without any drawbacks, since optical coherence tomography is not required for predictions. We expect this concept to apply to other multimodal clinical imaging, health records and genomics data, and to corresponding sample-starved learning problems.
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Scientific Article
Jiang, D. ; Christ, S. ; Correa-Gallegos, D. ; Ramesh, P. ; Kalgudde Gopal, S. ; Wannemacher, J. ; Mayr, C. ; Lupperger, V. ; Yu, Q. ; Ye, H. ; Mück-Häusl, M. ; Rajendran, V. ; Wan, L. ; Liu, J. ; Mirastschijski, U. ; Volz, T. ; Marr, C. ; Schiller, H. B. ; Rinkevich, Y.
Nat. Commun. 11:5653 (2020)
Scars are more severe when the subcutaneous fascia beneath the dermis is injured upon surgical or traumatic wounding. Here, we present a detailed analysis of fascia cell mobilisation by using deep tissue intravital live imaging of acute surgical wounds, fibroblast lineage-specific transgenic mice, and skin-fascia explants (scar-like tissue in a dish – SCAD). We observe that injury triggers a swarming-like collective cell migration of fascia fibroblasts that progressively contracts the skin and form scars. Swarming is exclusive to fascia fibroblasts, and requires the upregulation of N-cadherin. Both swarming and N-cadherin expression are absent from fibroblasts in the upper skin layers and the oral mucosa, tissues that repair wounds with minimal scar. Impeding N-cadherin binding inhibits swarming and skin contraction, and leads to reduced scarring in SCADs and in animals. Fibroblast swarming and N-cadherin thus provide therapeutic avenues to curtail fascia mobilisation and pathological fibrotic responses across a range of medical settings.
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Scientific Article
Conlon, T.M. ; John-Schuster, G. ; Heide, D. ; Pfister, D. ; Lehmann, M. ; Hu, Y. ; Ertüz, Z. ; López, M.A. ; Ansari, M. ; Strunz, M. ; Mayr, C. ; Ciminieri, C. ; Costa, R. ; Kohlhepp, M.S. ; Guillot, A. ; Güneş, G. ; Jeridi, A. ; Funk, M.C. ; Beroshvili, G. ; Prokosch, S. ; Hetzer, J. ; Verleden, S.E. ; Alsafadi, H.N. ; Lindner, M. ; Burgstaller, G. ; Becker, L. ; Irmler, M. ; Dudek, M. ; Janzen, J. ; Goffin, E. ; Gosens, R. ; Knolle, P. ; Pirotte, B. ; Stöger, T. ; Beckers, J. ; Wagner, D.E. ; Singh, I. ; Theis, F.J. ; Hrabě de Angelis, M. ; O’Connor, T. ; Tacke, F. ; Boutros, M. ; Dejardin, E. ; Eickelberg, O. ; Schiller, H. B. ; Königshoff, M. ; Heikenwalder, M. ; Yildirim, A.Ö.
Nature 588, 151–156 (2020)
Blockade of lymphotoxin beta-receptor (LT beta R) signalling restores WNT signalling and epithelial repair in a model of chronic obstructive pulmonary disease.Lymphotoxin beta-receptor (LT beta R) signalling promotes lymphoid neogenesis and the development of tertiary lymphoid structures(1,2), which are associated with severe chronic inflammatory diseases that span several organ systems(3-6). How LT beta R signalling drives chronic tissue damage particularly in the lung, the mechanism(s) that regulate this process, and whether LT beta R blockade might be of therapeutic value have remained unclear. Here we demonstrate increased expression of LT beta R ligands in adaptive and innate immune cells, enhanced non-canonical NF-kappa B signalling, and enriched LT beta R target gene expression in lung epithelial cells from patients with smoking-associated chronic obstructive pulmonary disease (COPD) and from mice chronically exposed to cigarette smoke. Therapeutic inhibition of LT beta R signalling in young and aged mice disrupted smoking-related inducible bronchus-associated lymphoid tissue, induced regeneration of lung tissue, and reverted airway fibrosis and systemic muscle wasting. Mechanistically, blockade of LT beta R signalling dampened epithelial non-canonical activation of NF-kappa B, reduced TGF beta signalling in airways, and induced regeneration by preventing epithelial cell death and activating WNT/beta-catenin signalling in alveolar epithelial progenitor cells. These findings suggest that inhibition of LT beta R signalling represents a viable therapeutic option that combines prevention of tertiary lymphoid structures(1) and inhibition of apoptosis with tissue-regenerative strategies.
Wissenschaftlicher Artikel
Scientific Article
Huynh, K. ; Lim, W.L.F. ; Giles, C. ; Jayawardana, K.S. ; Salim, A. ; Mellett, N.A. ; Smith, A.A.T. ; Olshansky, G. ; Drew, B.G. ; Chatterjee, P. ; Martins, I. ; Laws, S.M. ; Bush, A.I. ; Rowe, C.C. ; Villemagne, V.L. ; Ames, D. ; Masters, C.L. ; Arnold, M. ; Nho, K. ; Saykin, A.J. ; Baillie, R. ; Han, X. ; Kaddurah-Daouk, R. ; Meikle, P.J.
Nat. Commun. 11:5698 (2020)
Changes to lipid metabolism are tightly associated with the onset and pathology of Alzheimer’s disease (AD). Lipids are complex molecules comprising many isomeric and isobaric species, necessitating detailed analysis to enable interpretation of biological significance. Our expanded targeted lipidomics platform (569 species across 32 classes) allows for detailed lipid separation and characterisation. In this study we examined peripheral samples of two cohorts (AIBL, n = 1112 and ADNI, n = 800). We are able to identify concordant peripheral signatures associated with prevalent AD arising from lipid pathways including; ether lipids, sphingolipids (notably GM3 gangliosides) and lipid classes previously associated with cardiometabolic disease (phosphatidylethanolamine and triglycerides). We subsequently identified similar lipid signatures in both cohorts with future disease. Lastly, we developed multivariate lipid models that improved classification and prediction. Our results provide a holistic view between the lipidome and AD using a comprehensive approach, providing targets for further mechanistic investigation.
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Scientific Article
Ebert, K. ; Zwingenberger, G. ; Barbaria, E. ; Keller, S. ; Heck, C. ; Arnold, R. ; Hollerieth, V. ; Mattes, J. ; Geffers, R. ; Raimundez-Alvarez, E. ; Hasenauer, J. ; Luber, B.
BMC Cancer 20:1039 (2020)
Background: Gastric cancer is the fifth most frequently diagnosed cancer and the third leading cause of cancer death worldwide. The molecular mechanisms of action for anti-HER-family drugs in gastric cancer cells are incompletely understood. We compared the molecular effects of trastuzumab and the other HER-family targeting drugs cetuximab and afatinib on phosphoprotein and gene expression level to gain insights into the regulated pathways. Moreover, we intended to identify genes involved in phenotypic effects of anti-HER therapies. Methods: A time-resolved analysis of downstream intracellular kinases following EGF, cetuximab, trastuzumab and afatinib treatment was performed by Luminex analysis in the gastric cancer cell lines Hs746T, MKN1, MKN7 and NCI-N87. The changes in gene expression after treatment of the gastric cancer cell lines with EGF, cetuximab, trastuzumab or afatinib for 4 or 24 h were analyzed by RNA sequencing. Significantly enriched pathways and gene ontology terms were identified by functional enrichment analysis. Furthermore, effects of trastuzumab and afatinib on cell motility and apoptosis were analyzed by time-lapse microscopy and western blot for cleaved caspase 3. Results: The Luminex analysis of kinase activity revealed no effects of trastuzumab, while alterations of AKT1, MAPK3, MEK1 and p70S6K1 activations were observed under cetuximab and afatinib treatment. On gene expression level, cetuximab mainly affected the signaling pathways, whereas afatinib had an effect on both signaling and cell cycle pathways. In contrast, trastuzumab had little effects on gene expression. Afatinib reduced average speed in MKN1 and MKN7 cells and induced apoptosis in NCI-N87 cells. Following treatment with afatinib, a list of 14 genes that might be involved in the decrease of cell motility and a list of 44 genes that might have a potential role in induction of apoptosis was suggested. The importance of one of these genes (HBEGF) as regulator of motility was confirmed by knockdown experiments. Conclusions: Taken together, we described the different molecular effects of trastuzumab, cetuximab and afatinib on kinase activity and gene expression. The phenotypic changes following afatinib treatment were reflected by altered biological functions indicated by overrepresentation of gene ontology terms. The importance of identified genes for cell motility was validated in case of HBEGF.
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Scientific Article
Ayestaran, I. ; Galhoz, A. ; Spiegel, E ; Sidders, B. ; Dry, J.R. ; Dondelinger, F. ; Bender, A. ; McDermott, U. ; Iorio, F. ; Menden, M.
Patterns 1:100065 (2020)
High-throughput drug screens in cancer cell lines test compounds at low concentrations, thereby enablingthe identification of drug-sensitivity biomarkers, while resistance biomarkers remain underexplored. Dissect-ing meaningful drug responses at high concentrations is challenging due to cytotoxicity, i.e., off-target ef-fects, thus limiting resistance biomarker discovery to frequently mutated cancer genes. To address this,we interrogate subpopulations carrying sensitivity biomarkers and consecutively investigate unexpectedlyresistant (UNRES) cell lines for unique genetic alterations that may drive resistance. By analyzing theGDSC and CTRP datasets, we find 53 and 35 UNRES cases, respectively. For 24 and 28 of them, we highlightputative resistance biomarkers. We find clinically relevant cases such as EGFRT790Mmutation in NCI-H1975or PTEN loss in NCI-H1650 cells, in lung adenocarcinoma treated with EGFR inhibitors. Interrogating the un-derpinnings of drug resistance with publicly available CRISPR phenotypic assays assists in prioritizing resis-tance drivers, offering hypotheses for drug combinations.
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Scientific Article
Dorigatti, E. ; Schubert, B.
PLoS Comput. Biol. 16:e1008237 (2020)
Epitope-based vaccines have revolutionized vaccine research in the last decades. Due to their complex nature, bioinformatics plays a pivotal role in their development. However, existing algorithms address only specific parts of the design process or are unable to provide formal guarantees on the quality of the solution. We present a unifying formalism of the general epitope vaccine design problem that tackles all phases of the design process simultaneously and combines all prevalent design principles. We then demonstrate how to formulate the developed formalism as an integer linear program, which guarantees optimality of the designs. This makes it possible to explore new regions of the vaccine design space, analyze the trade-offs between the design phases, and balance the many requirements of vaccines.Author summaryDiseases such as Cancer, AIDS, Hepatitis C, and Malaria, infect and kill millions of people every year. In spite of all our efforts, a cure for those disease remains elusive. Among all possible approaches, personalized vaccines have shown promising results in several clinical trials. These vaccines must be designed computationally in order to cover the enormous variations existing in the diseases and in the patients themselves. Current methods are lacking in one of several aspects, as they only focus on a specific part of the design problem, on a specific type of vaccine, or are unable to guarantee optimality of the solution. In this work, we present a new method to design vaccines that does not suffer from any of these limitations: through a holistic view on the design problem, it can find the best solution for the given design constraints. The flexibility of our method allows us to tune the balance of the different design criteria, perform accurate and reliable comparisons among different solutions, and properly evaluate the trade-offs involved.
Wissenschaftlicher Artikel
Scientific Article
Stadler, E. ; Müller, J.
Discrete Contin. Dyn. Syst.-Ser. B 25, 4127-4164 (2020)
We study the distribution of autonomously replicating genetic elements, so-called plasmids, in a bacterial population. When a bacterium divides, the plasmids are segregated between the two daughter cells. We analyze a model for a bacterial population structured by their plasmid content. The model contains reproduction of both plasmids and bacteria, death of bacteria, and the distribution of plasmids at cell division. The model equation is a growth-fragmentation-death equation with an integral term containing a singular kernel. As we are interested in the long-term distribution of the plasmids, we consider the associated eigenproblem. Due to the singularity of the integral kernel, we do not have compactness. Thus, standard approaches to show the existence of an eigensolution like the Theorem of Krein-Rutman cannot be applied. We show the existence of an eigensolution using a fixed point theorem and the Laplace transform. The long-term dynamics of the model is analyzed using the Generalized Relative Entropy method.
Wissenschaftlicher Artikel
Scientific Article
Grech, V. ; Scherb, H.
Early Hum. Dev., DOI: 10.1016/j.earlhumdev.2020.105210 (2020)
Introduction: The world continues in the grip of the COVID-19 pandemic. Widespread public health measures and travel restrictions have dampened viral spread but outbreaks are expected as restrictions are raised. This study was carried out in order to devise an approach that may help to predict deaths based on upsurges (spikes or waves) of cases. Methods: Publically available data for daily new cases and deaths from December 2019 to August 2020 was obtained from the Our World In Data website. For the purposes of more detailed analysis, in addition to total global data, three countries were chosen for sub analysis: Italy, Germany and the United States. Results: Delay to death (days) were as follows: World: 20.6 (95% CI: 8.4–32.8); USA: 19.8 (95% CI: 9.3–30.4); Germany: 18.8 (95% CI: 6.1–31.6); Italy: 2.4 (95% CI −10.2–15.0). Discussion: Countries may be able to contain viral resurgence by adhering to WHO advice for reopening from restrictions/lockdowns. However, outbreaks are almost inevitable and deaths are to be expected approximately 20 days after rises in cases. This paper may therefore aid healthcare systems and hospitals for surges in cases as positive COVID-19 swabs increase in any given locality. Italy was an exception in these results as the initial surge and swabs taken represented symptomatic/admitted cases and not community surveillance tracking and tracing.
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Scientific Article
Rajewsky, N. ; Almouzni, G. ; Gorski, S.A. ; Aerts, S. ; Amit, I. ; Bertero, M.G. ; Bock, C. ; Bredenoord, A.L. ; Cavalli, G. ; Chiocca, S. ; Clevers, H. ; de Strooper, B. ; Eggert, A. ; Ellenberg, J. ; Fernández, X.M. ; Figlerowicz, M. ; Gasser, S.M. ; Hubner, N. ; Kjems, J. ; Knoblich, J.A. ; Krabbe, G. ; Lichter, P. ; Linnarsson, S. ; Marine, J.C. ; Marioni, J. ; Marti-Renom, M.A. ; Netea, M.G. ; Nickel, D. ; Nollmann, M. ; Novak, H.R. ; Parkinson, H. ; Piccolo, S. ; Pinheiro, I. ; Pombo, A. ; Popp, C. ; Reik, W. ; Roman-Roman, S. ; Rosenstiel, P. ; Schultze, J.L. ; Stegle, O. ; Tanay, A. ; Testa, G. ; Thanos, D. ; Theis, F.J. ; Torres-Padilla, M.E. ; Valencia, A. ; Vallot, C. ; van Oudenaarden, A. ; Vidal, M. ; Voet, T. ; LifeTime Community (Schiller, H. B.) ; LifeTime Community (Ziegler, A.-G.)
Nature 587, 377–386 (2020)
Here we describe the LifeTime Initiative, which aims to track, understand and target human cells during the onset and progression of complex diseases, and to analyse their response to therapy at single-cell resolution. This mission will be implemented through the development, integration and application of single-cell multi-omics and imaging, artificial intelligence and patient-derived experimental disease models during the progression from health to disease. The analysis of large molecular and clinical datasets will identify molecular mechanisms, create predictive computational models of disease progression, and reveal new drug targets and therapies. The timely detection and interception of disease embedded in an ethical and patient-centred vision will be achieved through interactions across academia, hospitals, patient associations, health data management systems and industry. The application of this strategy to key medical challenges in cancer, neurological and neuropsychiatric disorders, and infectious, chronic inflammatory and cardiovascular diseases at the single-cell level will usher in cell-based interceptive medicine in Europe over the next decade.The LifeTime initiative is an ambitious, multidisciplinary programme that aims to improve healthcare by tracking individual human cells during disease processes and responses to treatment in order to develop and implement cell-based interceptive medicine in Europe.
Review
Review
Lasser, R. ; Obermaier, J.
Acta Sci. Math. 86, 331-342 (2020)
The main purpose of this paper is to use chain sequences to study spectral properties of weighted shift operators A and of tridiagonal operators ReA. Characterizations of chain sequences and relations to Haar sequences are derived. We use these results to compare the spectral radius, the numerical radius and the norm of A and ReA. As an example we study orthogonal polynomials defined by a recursion formula with almost constant coefficients.
Wissenschaftlicher Artikel
Scientific Article
Wang, J. ; Wei, R. ; Xie, G. ; Arnold, M. ; Kueider-Paisley, A. ; Louie, G. ; Mahmoudian Dehkordi, S. ; Blach, C. ; Baillie, R. ; Han, X. ; de Jager, P.L. ; Bennett, D.A. ; Kaddurah-Daouk, R. ; Jia, W.
Sci. Rep. 10:14059 (2020)
The incidence of Alzheimer's disease (AD) increases with age and is becoming a significant cause of worldwide morbidity and mortality. However, the metabolic perturbation behind the onset of AD remains unclear. In this study, we performed metabolite profiling in both brain (n = 109) and matching serum samples (n = 566) to identify differentially expressed metabolites and metabolic pathways associated with neuropathology and cognitive performance and to identify individuals at high risk of developing cognitive impairment. The abundances of 6 metabolites, glycolithocholate (GLCA), petroselinic acid, linoleic acid, myristic acid, palmitic acid, palmitoleic acid and the deoxycholate/cholate (DCA/CA) ratio, along with the dysregulation scores of 3 metabolic pathways, primary bile acid biosynthesis, fatty acid biosynthesis, and biosynthesis of unsaturated fatty acids showed significant differences across both brain and serum diagnostic groups (P-value < 0.05). Significant associations were observed between the levels of differential metabolites/pathways and cognitive performance, neurofibrillary tangles, and neuritic plaque burden. Metabolites abundances and personalized metabolic pathways scores were used to derive machine learning models, respectively, that could be used to differentiate cognitively impaired persons from those without cognitive impairment (median area under the receiver operating characteristic curve (AUC) = 0.772 for the metabolite level model; median AUC = 0.731 for the pathway level model). Utilizing these two models on the entire baseline control group, we identified those who experienced cognitive decline in the later years (AUC = 0.804, sensitivity = 0.722, specificity = 0.749 for the metabolite level model; AUC = 0.778, sensitivity = 0.633, specificity = 0.825 for the pathway level model) and demonstrated their pre-AD onset prediction potentials. Our study provides a proof-of-concept that it is possible to discriminate antecedent cognitive impairment in older adults before the onset of overt clinical symptoms using metabolomics. Our findings, if validated in future studies, could enable the earlier detection and intervention of cognitive impairment that may halt its progression.
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Scientific Article
Fischer, D.S. ; Wu, Y. ; Schubert, B. ; Theis, F.J.
Mol. Syst. Biol. 16:e9416 (2020)
It has recently become possible to simultaneously assay T-cell specificity with respect to large sets of antigens and the T-cell receptor sequence in high-throughput single-cell experiments. Leveraging this new type of data, we propose and benchmark a collection of deep learning architectures to model T-cell specificity in single cells. In agreement with previous results, we found that models that treat antigens as categorical outcome variables outperform those that model the TCR and antigen sequence jointly. Moreover, we show that variability in single-cell immune repertoire screens can be mitigated by modeling cell-specific covariates. Lastly, we demonstrate that the number of bound pMHC complexes can be predicted in a continuous fashion providing a gateway to disentangle cell-to-dextramer binding strength and receptor-to-pMHC affinity. We provide these models in the Python package TcellMatch to allow imputation of antigen specificities in single-cell RNA-seq studies on T cells without the need for MHC staining.
Wissenschaftlicher Artikel
Scientific Article
Strunz, M. ; Simon, L. ; Ansari, M. ; Kathiriya, J.J. ; Angelidis, I. ; Mayr, C. ; Tsidiridis, G. ; Lange, M. ; Mattner, L. ; Yee, M. ; Ogar, P. ; Sengupta, A. ; Kukhtevich, I. ; Schneider, R. ; Zhao, Z. ; Voss, C. ; Stöger, T. ; Neumann, J.H.L. ; Hilgendorff, A. ; Behr, J. ; O'Reilly, M. ; Lehmann, M. ; Burgstaller, G. ; Königshoff, M. ; Chapman, H.A. ; Theis, F.J. ; Schiller, H. B.
Nat. Commun. 11:3559 (2020)
The cell type specific sequences of transcriptional programs during lung regeneration have remained elusive. Using time-series single cell RNA-seq of the bleomycin lung injury model, we resolved transcriptional dynamics for 28 cell types. Trajectory modeling together with lineage tracing revealed that airway and alveolar stem cells converge on a unique Krt8+transitional stem cell state during alveolar regeneration. These cells have squamous morphology, feature p53 and NFkB activation and display transcriptional features of cellular senescence. The Krt8+ state appears in several independent models of lung injury and persists in human lung fibrosis, creating a distinct cell-cell communication network with mesenchyme and macrophages during repair. We generated a model of gene regulatory programs leading to Krt8+transitional cells and their terminal differentiation to alveolar type-1 cells. We propose that in lung fibrosis, perturbed molecular checkpoints on the way to terminal differentiation can cause aberrant persistence of regenerative intermediate stem cell states. Injury repair is characterized by the generation of transient cell states important for tissue recovery. Here, the authors present a single cell RNA-seq map of recovery from bleomycin lung injury in mice and uncover a Krt8+ transitional stem cell state that precedes the regeneration of AT1 cells and persists in human lung fibrosis.
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Scientific Article
Spriewald, S. ; Stadler, E. ; Hense, B.A. ; Münch, P.C. ; McHardy, A.C. ; Weiss, A.S. ; Obeng, N. ; Müller, J. ; Stecher, B.
mBio 11:e00912-20 (2020)
Colicins are toxins produced and released by Enterobacteriaceae to kill competitors in the gut. While group A colicins employ a division of labor strategy to liberate the toxin into the environment via colicin-specific lysis, group B colicin systems lack cognate lysis genes. In Salmonella enterica serovar Typhimurium (S. Tm), the group B colicin lb (Collb) is released by temperate phage-mediated bacteriolysis. Phage-mediated Collb release promotes S. Tm fitness against competing Escherichia coll. It remained unclear how prophage-mediated lysis is realized in a clonal population of Collb producers and if prophages contribute to evolutionary stability of toxin release in S. Tm. Here, we show that prophage-mediated lysis occurs in an S. Tm subpopulation only, thereby introducing phenotypic heterogeneity to the system. We established a mathematical model to study the dynamic interplay of S. Tm, Collb, and a temperate phage in the presence of a competing species. Using this model, we studied long-term evolution of phage lysis rates in a fluctuating infection scenario. This revealed that phage lysis evolves as bet-hedging strategy that maximizes phage spread, regardless of whether colicin is present or not. We conclude that the Collb system, lacking its own lysis gene, is making use of the evolutionary stable phage strategy to be released. Prophage lysis genes are highly prevalent in nontyphoidal Salmonella genomes. This suggests that the release of Collb by temperate phages is widespread. In conclusion, our findings shed new light on the evolution and ecology of group B colicin systems.IMPORTANCE Bacteria are excellent model organisms to study mechanisms of social evolution. The production of public goods, e.g., toxin release by cell lysis in clonal bacterial populations, is a frequently studied example of cooperative behavior. Here, we analyze evolutionary stabilization of toxin release by the enteric pathogen Salmonella. The release of colicin lb (Collb), which is used by Salmonella to gain an edge against competing microbiota following infection, is coupled to bacterial lysis mediated by temperate phages. Here, we show that phage-dependent lysis and subsequent release of colicin and phage particles occurs only in part of the Collbexpressing Salmonella population. This phenotypic heterogeneity in lysis, which represents an essential step in the temperate phage life cycle, has evolved as a bethedging strategy under fluctuating environments such as the gastrointestinal tract. Our findings suggest that prophages can thereby evolutionarily stabilize costly toxin release in bacterial populations.
Wissenschaftlicher Artikel
Scientific Article
Schmiester, L. ; Weindl, D. ; Hasenauer, J.
J. Math. Biol. 81, 603–623 (2020)
Quantitative dynamical models facilitate the understanding of biological processes and the prediction of their dynamics. These models usually comprise unknown parameters, which have to be inferred from experimental data. For quantitative experimental data, there are several methods and software tools available. However, for qualitative data the available approaches are limited and computationally demanding. Here, we consider the optimal scaling method which has been developed in statistics for categorical data and has been applied to dynamical systems. This approach turns qualitative variables into quantitative ones, accounting for constraints on their relation. We derive a reduced formulation for the optimization problem defining the optimal scaling. The reduced formulation possesses the same optimal points as the established formulation but requires less degrees of freedom. Parameter estimation for dynamical models of cellular pathways revealed that the reduced formulation improves the robustness and convergence of optimizers. This resulted in substantially reduced computation times. We implemented the proposed approach in the open-source Python Parameter EStimation TOolbox (pyPESTO) to facilitate reuse and extension. The proposed approach enables efficient parameterization of quantitative dynamical models using qualitative data.
Wissenschaftlicher Artikel
Scientific Article
Storath, M. ; Weinmann, A.
Multiscale Model. Simul. 18, 674-706 (2020)
n this paper, we consider the sparse regularization of manifold-valued data with respect to an interpolatory wavelet/multiscale transform. We propose and study variational models for this task and provide results on their well-posedness. We present algorithms for a numerical realization of these models in the manifold setup. Further, we provide experimental results to show the potential of the proposed schemes for applications.
Wissenschaftlicher Artikel
Scientific Article
Ostaszewski, M. ; Mazein, A. ; Gillespie, M.E. ; Kuperstein, I. ; Niarakis, A. ; Hermjakob, H. ; Pico, A.R. ; Willighagen, E.L. ; Evelo, C.T. ; Hasenauer, J. ; Schreiber, F. ; Dräger, A. ; Demir, E. ; Wolkenhauer, O. ; Furlong, L.I. ; Barillot, E. ; Dopazo, J. ; Orta-Resendiz, A. ; Messina, F. ; Valencia, A. ; Funahashi, A. ; Kitano, H. ; Auffray, C. ; Balling, R. ; Schneider, R.
Sci. Data 7:247 (2020)
An amendment to this paper has been published and can be accessed via a link at the top of the paper.
Behzadi, S. ; Müller, N.S. ; Plant, C. ; Böhm, C.
Int. J. Data Sci. Anal. 10, 233–248 (2020)
Most clustering algorithms have been designed only for pure numerical or pure categorical data sets, while nowadays many applications generate mixed data. It raises the question how to integrate various types of attributes so that one could efficiently group objects without loss of information. It is already well understood that a simple conversion of categorical attributes into a numerical domain is not sufficient since relationships between values such as a certain order are artificially introduced. Leveraging the natural conceptual hierarchy among categorical information, concept trees summarize the categorical attributes. In this paper, we introduce the algorithm ClicoT (CLustering mixed-type data Including COncept Trees) as reported by Behzadi et al. (Advances in Knowledge Discovery and Data Mining, Springer, Cham, 2019) which is based on the minimum description length principle. Profiting of the conceptual hierarchies, ClicoT integrates categorical and numerical attributes by means of a MDL-based objective function. The result of ClicoT is well interpretable since concept trees provide insights into categorical data. Extensive experiments on synthetic and real data sets illustrate that ClicoT is noise-robust and yields well-interpretable results in a short runtime. Moreover, we investigate the impact of concept hierarchies as well as various data characteristics in this paper.
Review
Review
Bergen, V. ; Lange, M. ; Peidli, S. ; Wolf, F.A. ; Theis, F.J.
Nat. Biotechnol. 38, 1408–1414 (2020)
scVelo reconstructs transient cell states and differentiation pathways from single-cell RNA-sequencing data.RNA velocity has opened up new ways of studying cellular differentiation in single-cell RNA-sequencing data. It describes the rate of gene expression change for an individual gene at a given time point based on the ratio of its spliced and unspliced messenger RNA (mRNA). However, errors in velocity estimates arise if the central assumptions of a common splicing rate and the observation of the full splicing dynamics with steady-state mRNA levels are violated. Here we present scVelo, a method that overcomes these limitations by solving the full transcriptional dynamics of splicing kinetics using a likelihood-based dynamical model. This generalizes RNA velocity to systems with transient cell states, which are common in development and in response to perturbations. We apply scVelo to disentangling subpopulation kinetics in neurogenesis and pancreatic endocrinogenesis. We infer gene-specific rates of transcription, splicing and degradation, recover each cell's position in the underlying differentiation processes and detect putative driver genes. scVelo will facilitate the study of lineage decisions and gene regulation.
Wissenschaftlicher Artikel
Scientific Article
Scherb, H. ; Hayashi, K.
Environ. Health 19:82 (2020)
Background Perinatal mortality increased in contaminated prefectures after the Fukushima Daichi Nuclear Power Plant (FDNPP) accidents in Japan in 2011. Elevated counts of surgeries for cryptorchidism and congenital heart malformations were observed throughout Japan from 2012 onward. The thyroid cancer detection rate (2011 to 2016) was associated with the dose-rate at the municipality level in the Fukushima prefecture. Since the birth weight is a simple and objective indicator for gestational development and pregnancy outcome, the question arises whether the annual birth weight distribution was distorted in a dose-rate-dependent manner across Japan after Fukushima. Methods The Japanese Ministry of Health, Labour, and Welfare provides prefecture-specific annual counts for 26.158 million live births from 1995 to 2018, of which 2.366 million births (9.04%) with weights < 2500 g. Prefecture-specific spatiotemporal trends of the low birth weight proportions were analyzed. Logistic regression allowing for level-shifts from 2012 onward was employed to test whether those level-shifts were proportional to the prefecture-specific dose-rates derived from Cs-137 deposition in the 47 Japanese prefectures. Results The overall trend of the low birth weight prevalence (LBWp) in Japan discloses a jump in 2012 with a jump odds ratio (OR) 1.020, 95%-confidence interval (1.003,1.037),p-value 0.0246. A logistic regression of LBWp on the additional dose-rate after the FDNPP accidents adjusted for prefecture-specific spatiotemporal base-line trends yields an OR per mu Sv/h of 1.098 (1.058, 1.139),p-value < 0.0001. Further adjusting the logistic regression for the annual population size and physician density of the prefectures, as well as for the counts of the dead, the missing, and the evacuees due to earthquake and tsunami (as surrogate measures for medical infrastructure and stress) yields an OR per mu Sv/h of 1.109 (1.032, 1.191),p-value 0.0046. Conclusions This study shows increased low birth weight prevalence related to the Cs-137 deposition and the corresponding additional dose-rate in Japan from 2012 onward. Previous evidence suggesting compromised gestational development and pregnancy outcome under elevated environmental ionizing radiation exposure is corroborated.
Wissenschaftlicher Artikel
Scientific Article
Beyerlein, A. ; Lack, N. ; Maier, W.
PLoS ONE 15:e0236020 (2020)
Background We investigated associations of area-level deprivation with obstetric and perinatal outcomes in a large population-based routine dataset. Methods We used the data of n = 827,105 deliveries who were born in hospitals between 2009 to 2016 in Bavaria, Germany. The Bavarian Index of Multiple Deprivation (BIMD) on district level was assigned to each mother by the zip code of her residential address. We calculated odds ratios (ORs) with 95% confidence intervals (CIs) for preterm deliveries, Caesarian sections (CS), stillbirths, small for gestational age (SGA) births and low 5-minute Apgar scores by BIMD quintiles with and without adjustment for potential confounders. Results We observed a significantly increased risk for preterm deliveries in mothers from the most deprived compared to the least deprived districts (e.g. OR [95% CI] for highest compared to lowest deprivation quintile: 1.06 [1.03, 1.09]) in adjusted analyses. Increased deprivation was also associated with higher SGA and secondary CS rates, but with lower proportions of stillbirths, primary CS and low Apgar scores. When one large clinic with an unusually high stillbirth rate was excluded, the association of BIMD with stillbirths was attenuated and almost disappeared. Conclusions We found that area-level deprivation in Bavaria was positively associated with preterm and SGA births, confirming previous studies. In contrast, the finding of an inverse association between deprivation and both stillbirth rates and low Apgar score came somewhat surprising. However, we conclude that the stillbirths finding is spurious and reflects regional bias due to a clinic which seems to specialize in termination of pregnancies.
Wissenschaftlicher Artikel
Scientific Article
Noordam, R. ; van Heemst, D. ; Suhre, K. ; Krumsiek, J. ; Mook-Kanamori, D.O.
Arch. Biochem. Biophys. 689:108476 (2020)
Background: Proteomics is expected to provide novel insights in the underlying pathophysiology of type 2 diabetes mellitus. In the present study, we aimed to identify and biochemically characterize proteins associated with diabetes mellitus in a Qatari population.Methods: In a diabetes case-control study (175 cases, 164 controls; Arab, South Asian and Philippine ethnicities), we conducted a discovery study to screen 1141 blood protein levels for associations with diabetes mellitus. Additional analyses were done in controls in relation to Hb1Ac, and biochemical characterization of the main findings was performed with metabolomics (501 metabolites). We performed two-sample Mendelian Randomization to provide evidence of potential causality using data from European descent of the DIAGRAM consortium (74,124 cases of diabetes mellitus and 824,006 controls) for the identified proteins for T2D and Hb1Ac.Results: After accounting for multiple testing, 30 protein levels were different (p-values < 8.6e(-5)) between cases and controls. Of these, a higher Hb1Ac in controls was associated with a lower IGFBP-2 level (p-value=4.1e(-6)). IGFBP-2 protein level was found lower among cases compared with controls across all ethnicities. In controls, IGFBP-2 was associated with 21 metabolite levels, but specifically connected to the metabolite citrulline in network analyses. We observed no evidence, however, that the association between IGFBP-2 and diabetes mellitus was causal.Conclusions: We specifically identified IGFBP-2 to be associated with diabetes mellitus, although with no evidence for causality, which was specifically connected to citrulline metabolism.
Wissenschaftlicher Artikel
Scientific Article
Schälte, Y. ; Hasenauer, J.
Bioinformatics 36, 1, 551-559 (2020)
Motivation: Approximate Bayesian computation (ABC) is an increasingly popular method for likelihood-free parameter inference in systems biology and other fields of research, as it allows analyzing complex stochastic models. However, the introduced approximation error is often not clear. It has been shown that ABC actually gives exact inference under the implicit assumption of a measurement noise model. Noise being common in biological systems, it is intriguing to exploit this insight. But this is difficult in practice, as ABC is in general highly computationally demanding. Thus, the question we want to answer here is how to efficiently account for measurement noise in ABC.Results: We illustrate exemplarily how ABC yields erroneous parameter estimates when neglecting measurement noise. Then, we discuss practical ways of correctly including the measurement noise in the analysis. We present an efficient adaptive sequential importance sampling-based algorithm applicable to various model types and noise models. We test and compare it on several models, including ordinary and stochastic differential equations, Markov jump processes and stochastically interacting agents, and noise models including normal, Laplace and Poisson noise. We conclude that the proposed algorithm could improve the accuracy of parameter estimates for a broad spectrum of applications.
Wissenschaftlicher Artikel
Scientific Article
Juárez-Saldivar, A. ; Schroeder, M. ; Salentin, S. ; Haupt, V.J. ; Saavedra, E. ; Vázquez, C. ; Reyes-Espinosa, F. ; Herrera-Mayorga, V. ; Villalobos-Rocha, J.C. ; Garcia Perez, C. ; Campillo, N.E. ; Rivera, G.
Int. J. Mol. Sci. 21:4270 (2020)
Chagas disease, caused byTrypanosoma cruzi(T. cruzi), affects nearly eight million people worldwide. There are currently only limited treatment options, which cause several side effects and have drug resistance. Thus, there is a great need for a novel, improved Chagas treatment. Bifunctional enzyme dihydrofolate reductase-thymidylate synthase (DHFR-TS) has emerged as a promising pharmacological target. Moreover, some human dihydrofolate reductase (HsDHFR) inhibitors such as trimetrexate also inhibitT. cruziDHFR-TS (TcDHFR-TS). These compounds serve as a starting point and a reference in a screening campaign to search for newTcDHFR-TS inhibitors. In this paper, a novel virtual screening approach was developed that combines classical docking with protein-ligand interaction profiling to identify drug repositioning opportunities againstT. cruziinfection. In this approach, some food and drug administration (FDA)-approved drugs that were predicted to bind with high affinity toTcDHFR-TS and whose predicted molecular interactions are conserved among known inhibitors were selected. Overall, ten putativeTcDHFR-TS inhibitors were identified. These exhibited a similar interaction profile and a higher computed binding affinity, compared to trimetrexate. Nilotinib, glipizide, glyburide and gliquidone were tested onT. cruziepimastigotes and showed growth inhibitory activity in the micromolar range. Therefore, these compounds could lead to the development of new treatment options for Chagas disease.
Wissenschaftlicher Artikel
Scientific Article
Benedetti, E. ; Gerstner, N. ; Pučić-Baković, M. ; Keser, T. ; Reiding, K.R. ; Ruhaak, L.R. ; Štambuk, T. ; Selman, M.H.J. ; Rudan, I. ; Polašek, O. ; Hayward, C. ; Beekman, M. ; Slagboom, E. ; Wuhrer, M. ; Dunlop, M.G. ; Lauc, G. ; Krumsiek, J.
Metabolites 10:271 (2020)
Glycomics measurements, like all other high-throughput technologies, are subject to technical variation due to fluctuations in the experimental conditions. The removal of this non-biological signal from the data is referred to as normalization. Contrary to other omics data types, a systematic evaluation of normalization options for glycomics data has not been published so far. In this paper, we assess the quality of different normalization strategies for glycomics data with an innovative approach. It has been shown previously that Gaussian Graphical Models (GGMs) inferred from glycomics data are able to identify enzymatic steps in the glycan synthesis pathways in a data-driven fashion. Based on this finding, here, we quantify the quality of a given normalization method according to how well a GGM inferred from the respective normalized data reconstructs known synthesis reactions in the glycosylation pathway. The method therefore exploits a biological measure of goodness. We analyzed 23 different normalization combinations applied to six large-scale glycomics cohorts across three experimental platforms: Liquid Chromatography – ElectroSpray Ionization-Mass Spectrometry (LC-ESI-MS), Ultra High Performance Liquid Chromatography with Fluorescence Detection (UHPLC-FLD), and Matrix Assisted Laser Desorption Ionization – Furier Transform Ion Cyclotron Resonance – Mass Spectrometry (MALDI-FTICR-MS). Based on our results, we recommend normalizing glycan data using the ‘Probabilistic Quotient’ method followed by log-transformation, irrespective of the measurement platform. This recommendation is further supported by an additional analysis, where we ranked normalization methods based on their statistical associations with age, a factor known to associate with glycomics measurements.
Wissenschaftlicher Artikel
Scientific Article
Stegelmann, F. ; Wille, K. ; Busen, H. ; Fuchs, C. ; Schauer, S. ; Sadjadian, P. ; Becker, T. ; Kolatzki, V. ; Döhner, H. ; Stadler, R. ; Döhner, K. ; Griesshammer, M.
Leukemia, DOI: 10.1038/s41375-020-0945-3 (2020)
Wissenschaftlicher Artikel
Scientific Article
Haimerl, P. ; Bernhardt, U. ; Schindela, S. ; Henkel, F. ; Lechner, A. ; Zissler, U.M. ; Pastor, X. ; Thomas, D. ; Cecil, A. ; Ge, Y. ; Haid, M. ; Prehn, C. ; Tokarz, J. ; Heinig, M. ; Adamski, J. ; Schmidt-Weber, C.B. ; Chaker, A. ; Esser-von Bieren, J.
J. Allergy Clin. Immunol. 147, 587-599 (2020)
Background: Nonsteroidal anti-inflammatory drug–exacerbated respiratory disease (N-ERD) is a chronic inflammatory condition, which is driven by an aberrant arachidonic acid metabolism. Macrophages are major producers of arachidonic acid metabolites and subject to metabolic reprogramming, but they have been neglected in N-ERD. Objective: This study sought to elucidate a potential metabolic and epigenetic macrophage reprogramming in N-ERD. Methods: Transcriptional, metabolic, and lipid mediator profiles in macrophages from patients with N-ERD and healthy controls were assessed by RNA sequencing, Seahorse assays, and LC-MS/MS. Metabolites in nasal lining fluid, sputum, and plasma from patients with N-ERD (n = 15) and healthy individuals (n = 10) were quantified by targeted metabolomics analyses. Genome-wide methylomics were deployed to define epigenetic mechanisms of macrophage reprogramming in N-ERD. Results: This study shows that N-ERD monocytes/macrophages exhibit an overall reduction in DNA methylation, aberrant metabolic profiles, and an increased expression of chemokines, indicative of a persistent proinflammatory activation. Differentially methylated regions in N-ERD macrophages included genes involved in chemokine signaling and acylcarnitine metabolism. Acylcarnitines were increased in macrophages, sputum, nasal lining fluid, and plasma of patients with N-ERD. On inflammatory challenge, N-ERD macrophages produced increased levels of acylcarnitines, proinflammatory arachidonic acid metabolites, cytokines, and chemokines as compared to healthy macrophages. Conclusions: Together, these findings decipher a proinflammatory metabolic and epigenetic reprogramming of macrophages in N-ERD.
Wissenschaftlicher Artikel
Scientific Article
Radon, K. ; Saathoff, E. ; Pritsch, M. ; Guggenbühl Noller, J.M. ; Kroidl, I. ; Olbrich, L. ; Thiel, V. ; Diefenbach, M. ; Riess, F. ; Förster, F. ; Theis, F.J. ; Wieser, A. ; Hoelscher, M. ; the KoCo19 collaboration group (Hasenauer, J. ; Castelletti, N. ; Zeggini, E. ; Laxy, M. ; Leidl, R. ; Schwettmann, L.) ; the KoCo19 collaboration group (Fuchs, C.)
BMC Public Health 20:1036 (2020)
BackgroundDue to the SARS-CoV-2 pandemic, public health interventions have been introduced globally in order to prevent the spread of the virus and avoid the overload of health care systems, especially for the most severely affected patients. Scientific studies to date have focused primarily on describing the clinical course of patients, identifying treatment options and developing vaccines. In Germany, as in many other regions, current tests for SARS-CoV2 are not conducted on a representative basis and in a longitudinal design. Furthermore, knowledge about the immune status of the population is lacking. Nonetheless, these data are needed to understand the dynamics of the pandemic and hence to appropriately design and evaluate interventions. For this purpose, we recently started a prospective population-based cohort in Munich, Germany, with the aim to develop a better understanding of the state and dynamics of the pandemic.MethodsIn 100 out of 755 randomly selected constituencies, 3000 Munich households are identified via random route and offered enrollment into the study. All household members are asked to complete a baseline questionnaire and subjects >= 14years of age are asked to provide a venous blood sample of <= 3ml for the determination of SARS-CoV-2 IgG/IgA status. The residual plasma and the blood pellet are preserved for later genetic and molecular biological investigations. For twelve months, each household member is asked to keep a diary of daily symptoms, whereabouts and contacts via WebApp. If symptoms suggestive for COVID-19 are reported, family members, including children <14years, are offered a pharyngeal swab taken at the Division of Infectious Diseases and Tropical Medicine, LMU University Hospital Munich, for molecular testing for SARS-CoV-2. In case of severe symptoms, participants will be transferred to a Munich hospital. For one year, the study teams re-visits the households for blood sampling every six weeks.DiscussionWith the planned study we will establish a reliable epidemiological tool to improve the understanding of the spread of SARS-CoV-2 and to better assess the effectiveness of public health measures as well as their socio-economic effects. This will support policy makers in managing the epidemic based on scientific evidence.
Wissenschaftlicher Artikel
Scientific Article
Naulaerts, S. ; Menden, M. ; Ballester, P.J.
Biomolecules 10:963 (2020)
In silico models to predict which tumors will respond to a given drug are necessary for Precision Oncology. However, predictive models are only available for a handful of cases (each case being a given drug acting on tumors of a specific cancer type). A way to generate predictive models for the remaining cases is with suitable machine learning algorithms that are yet to be applied to existing in vitro pharmacogenomics datasets. Here, we apply XGBoost integrated with a stringent feature selection approach, which is an algorithm that is advantageous for these high-dimensional problems. Thus, we identified and validated 118 predictive models for 62 drugs across five cancer types by exploiting four molecular profiles (sequence mutations, copy-number alterations, gene expression, and DNA methylation). Predictive models were found in each cancer type and with every molecular profile. On average, no omics profile or cancer type obtained models with higher predictive accuracy than the rest. However, within a given cancer type, some molecular profiles were overrepresented among predictive models. For instance, CNA profiles were predictive in breast invasive carcinoma (BRCA) cell lines, but not in small cell lung cancer (SCLC) cell lines where gene expression (GEX) and DNA methylation profiles were the most predictive. Lastly, we identified the best XGBoost model per cancer type and analyzed their selected features. For each model, some of the genes in the selected list had already been found to be individually linked to the response to that drug, providing additional evidence of the usefulness of these models and the merits of the feature selection scheme.
Wissenschaftlicher Artikel
Scientific Article
Huang, S.S.Y. ; Makhlouf, M. ; AbouMoussa, E.H. ; Ruiz Tejada Segura, M.L. ; Mathew, L.S. ; Wang, K. ; Leung, M.C. ; Chaussabel, D. ; Logan, D.W. ; Scialdone, A. ; Garand, M. ; Saraiva, L.R.
Mol. Metab. 40:101038 (2020)
Objective: Fasting regimens can promote health, mitigate chronic immunological disorders, and improve age-related pathophysiological parameters in animals and humans. Several ongoing clinical trials are using fasting as a potential therapy for various conditions. Fasting alters metabolism by acting as a reset for energy homeostasis, but the molecular mechanisms underlying the beneficial effects of short-term fasting (STF) are not well understood, particularly at the systems or multiorgan level.Methods: We performed RNA-sequencing in nine organs from mice fed ad libitum (0 h) or subjected to fasting five times (2-22 h). We applied a combination of multivariate analysis, differential expression analysis, gene ontology, and network analysis for an in-depth understanding of the multiorgan transcriptome. We used literature mining solutions, LitLab (TM) and Gene Retriever (TM), to identify the biological and biochemical terms significantly associated with our experimental gene set, which provided additional support and meaning to the experimentally derived gene and inferred protein data.Results: We cataloged the transcriptional dynamics within and between organs during STF and discovered differential temporal effects of STF among organs. Using gene ontology enrichment analysis, we identified an organ network sharing 37 common biological pathways perturbed by STF. This network incorporates the brain, liver, interscapular brown adipose tissue, and posterior-subcutaneous white adipose tissue; hence, we named it the brain-liver-fats organ network. Using Reactome pathways analysis, we identified the immune system, dominated by T cell regulation processes, as a central and prominent target of systemic modulations during STF in this organ network. The changes we identified in specific immune components point to the priming of adaptive immunity and parallel the fine-tuning of innate immune signaling.Conclusions: Our study provides a comprehensive multiorgan transcriptomic profiling of mice subjected to multiple periods of STF and provides new insights into the molecular modulators involved in the systemic immunotranscriptomic changes that occur during short-term energy loss.
Wissenschaftlicher Artikel
Scientific Article
Höllbacher, B. ; Balazs, K. ; Heinig, M. ; Uhlenhaut, N.H.
Comp. Struc. Biotech. J. 18, 1330-1341 (2020)
Advancements in the field of next generation sequencing lead to the generation of ever-more data, with the challenge often being how to combine and reconcile results from different OMICs studies such as genome, epigenome and transcriptome. Here we provide an overview of the standard processing pipelines for ChIP-seq and RNA-seq as well as common downstream analyses. We describe popular multi-omics data integration approaches used to identify target genes and co-factors, and we discuss how machine learning techniques may predict transcriptional regulators and gene expression.
Review
Review
Müller, J.B. ; Geyer, P.E. ; Colaço, A.R. ; Treit, P.V. ; Strauss, M.T. ; Oroshi, M. ; Doll, S. ; Virreira Winter, S. ; Bader, J.M. ; Koehler, N. ; Theis, F.J. ; Santos, A. ; Mann, M.
Nature 582, 592–596 (2020)
Proteins carry out the vast majority of functions in all biological domains, but for technological reasons their large-scale investigation has lagged behind the study of genomes. Since the first essentially complete eukaryotic proteome was reported(1), advances in mass-spectrometry-based proteomics(2)have enabled increasingly comprehensive identification and quantification of the human proteome(3-6). However, there have been few comparisons across species(7,8), in stark contrast with genomics initiatives(9). Here we use an advanced proteomics workflow-in which the peptide separation step is performed by a microstructured and extremely reproducible chromatographic system-for the in-depth study of 100 taxonomically diverse organisms. With two million peptide and 340,000 stringent protein identifications obtained in a standardized manner, we double the number of proteins with solid experimental evidence known to the scientific community. The data also provide a large-scale case study for sequence-based machine learning, as we demonstrate by experimentally confirming the predicted properties of peptides fromBacteroides uniformis. Our results offer a comparative view of the functional organization of organisms across the entire evolutionary range. A remarkably high fraction of the total proteome mass in all kingdoms is dedicated to protein homeostasis and folding, highlighting the biological challenge of maintaining protein structure in all branches of life. Likewise, a universally high fraction is involved in supplying energy resources, although these pathways range from photosynthesis through iron sulfur metabolism to carbohydrate metabolism. Generally, however, proteins and proteomes are remarkably diverse between organisms, and they can readily be explored and functionally compared at www.proteomesoflife.org.
Wissenschaftlicher Artikel
Scientific Article
Fischer, A. ; Koopmans, T. ; Ramesh, P. ; Christ, S. ; Strunz, M. ; Wannemacher, J. ; Aichler, M. ; Feuchtinger, A. ; Walch, A.K. ; Ansari, M. ; Theis, F.J. ; Schorpp, K.K. ; Hadian, K. ; Neumann, P.A. ; Schiller, H. B. ; Rinkevich, Y.
Nat. Commun. 11:3068 (2020)
Surgical adhesions are bands of scar tissues that abnormally conjoin organ surfaces. Adhesions are a major cause of post-operative and dialysis-related complications, yet their patho-mechanism remains elusive, and prevention agents in clinical trials have thus far failed to achieve efficacy. Here, we uncover the adhesion initiation mechanism by coating beads with human mesothelial cells that normally line organ surfaces, and viewing them under adhesion stimuli. We document expansive membrane protrusions from mesothelia that tether beads with massive accompanying adherence forces. Membrane protrusions precede matrix deposition, and can transmit adhesion stimuli to healthy surfaces. We identify cytoskeletal effectors and calcium signaling as molecular triggers that initiate surgical adhesions. A single, localized dose targeting these early germinal events completely prevented adhesions in a preclinical mouse model, and in human assays. Our findings classifies the adhesion pathology as originating from mesothelial membrane bridges and offer a radically new therapeutic approach to treat adhesions.
Wissenschaftlicher Artikel
Scientific Article
Banga, J. ; Frappart, L. ; Hasenauer, J. ; Herault, Y. ; Jonkers, J. ; Koubi, D. ; Lange, B. ; Lines, G.T. ; Plouidou, A. ; Rinner, O.
Cancer Res. 80, 35-35 (2020)
Meeting abstract
Meeting abstract
Hulstaert, E. ; Morlion, A. ; Cobos, F.A. ; Verniers, K. ; Nuytens, J. ; Eynde, E.V. ; Yigit, N. ; Anckaert, J. ; Geerts, A. ; Hindryckx, P. ; Jacques, P. ; Brusselle, G. ; Bracke, K. ; Maes, T. ; Malfait, T. ; Derveaux, T. ; Ninclaus, V. ; Van Cauwenbergh, C. ; Roelens, K. ; Roets, E. ; Hemelsoet, D. ; Tilleman, K. ; Brochez, L. ; Kuersten, S. ; Simon, L. ; Karg, S. ; Nohammer, C. ; Kautzky-Willers, A. ; Leutner, M. ; Slaby, O. ; Schroth, G. ; Vandesompele, J. ; Mestdagh, P.
Clin. Cancer Res. 26, 33-34 (2020)
Meeting abstract
Meeting abstract
Bernath, M.M. ; Bhattacharyya, S. ; Nho, K. ; Barupal, D.K. ; Fiehn, O. ; Baillie, R. ; Risacher, S.L. ; Arnold, M. ; Jacobson, T. ; Trojanowski, J.Q. ; Shaw, L.M. ; Weiner, M.W. ; Doraiswamy, P.M. ; Kaddurah-Daouk, R. ; Saykin, A.J.
Neurology 94, E2088-E2098 (2020)
ObjectiveTo investigate the association of triglyceride (TG) principal component scores with Alzheimer disease (AD) and the amyloid, tau, neurodegeneration, and cerebrovascular disease (A/T/N/V) biomarkers for AD.MethodsSerum levels of 84 TG species were measured with untargeted lipid profiling of 689 participants from the Alzheimer's Disease Neuroimaging Initiative cohort, including 190 cognitively normal older adults (CN), 339 with mild cognitive impairment (MCI), and 160 with AD. Principal component analysis with factor rotation was used for dimension reduction of TG species. Differences in principal components between diagnostic groups and associations between principal components and AD biomarkers (including CSF, MRI and [F-18]fluorodeoxyglucose-PET) were assessed with a generalized linear model approach. In both cases, the Bonferroni method of adjustment was used to correct for multiple comparisons.ResultsThe 84 TGs yielded 9 principal components, 2 of which, consisting of long-chain, polyunsaturated fatty acid-containing TGs (PUTGs), were significantly associated with MCI and AD. Lower levels of PUTGs were observed in MCI and AD compared to CN. PUTG principal component scores were also significantly associated with hippocampal volume and entorhinal cortical thickness. In participants carrying the APOE epsilon 4 allele, these principal components were significantly associated with CSF beta -amyloid(1-42) values and entorhinal cortical thickness.ConclusionThis study shows that PUTG component scores were significantly associated with diagnostic group and AD biomarkers, a finding that was more pronounced in APOE epsilon 4 carriers. Replication in independent larger studies and longitudinal follow-up are warranted.
Wissenschaftlicher Artikel
Scientific Article
Radzikowska, U. ; Ding, M. ; Tan, G. ; Zhakparov, D. ; Peng, Y. ; Wawrzyniak, P. ; Wang, M. ; Li, S. ; Morita, H. ; Altunbulakli, C. ; Reiger, M. ; Neumann, A.U. ; Lunjani, N. ; Traidl-Hoffmann, C. ; Nadeau, K. ; O'Mahony, L. ; Akdis, C.A. ; Sokolowska, M.
Allergy 75, 2829-2845 (2020)
Background Morbidity and mortality from COVID-19 caused by novel coronavirus SARS-CoV-2 is accelerating worldwide, and novel clinical presentations of COVID-19 are often reported. The range of human cells and tissues targeted by SARS-CoV-2, its potential receptors and associated regulating factors are still largely unknown. The aim of our study was to analyze the expression of known and potential SARS-CoV-2 receptors and related molecules in the extensive collection of primary human cells and tissues from healthy subjects of different age and from patients with risk factors and known comorbidities of COVID-19. Methods We performed RNA sequencing and explored available RNA-Seq databases to study gene expression and co-expression of ACE2, CD147 (BSG), and CD26 (DPP4) and their direct and indirect molecular partners in primary human bronchial epithelial cells, bronchial and skin biopsies, bronchoalveolar lavage fluid, whole blood, peripheral blood mononuclear cells (PBMCs), monocytes, neutrophils, DCs, NK cells, ILC1, ILC2, ILC3, CD4(+)and CD8(+)T cells, B cells, and plasmablasts. We analyzed the material from healthy children and adults, and from adults in relation to their disease or COVID-19 risk factor status. Results ACE2andTMPRSS2were coexpressed at the epithelial sites of the lung and skin, whereas CD147 (BSG), cyclophilins (PPIAandPPIB), CD26 (DPP4), and related molecules were expressed in both epithelium and in immune cells. We also observed a distinct age-related expression profile of these genes in the PBMCs and T cells from healthy children and adults. Asthma, COPD, hypertension, smoking, obesity, and male gender status generally led to the higher expression of ACE2- and CD147-related genes in the bronchial biopsy, BAL, or blood. Additionally, CD147-related genes correlated positively with age and BMI. Interestingly, we also observed higher expression of CD147-related genes in the lesional skin of patients with atopic dermatitis. Conclusions Our data suggest different receptor repertoire potentially involved in the SARS-CoV-2 infection at the epithelial barriers and in the immune cells. Altered expression of these receptors related to age, gender, obesity and smoking, as well as with the disease status, might contribute to COVID-19 morbidity and severity patterns.
Wissenschaftlicher Artikel
Scientific Article
Bheda, P. ; Aguilar-Gomez, D. ; Becker, N.B. ; Becker, J. ; Stavrou, E. ; Kukhtevich, I. ; Höfer, T. ; Maerkl, S. ; Charvin, G. ; Marr, C. ; Kirmizis, A. ; Schneider, R.
Mol. Cell 78, 915-925 (2020)
Transcriptional memory of gene expression enables adaptation to repeated stimuli across many organisms. However, the regulation and heritability of transcriptional memory in single cells and through divisions remains poorly understood. Here, we combined microfluidics with single-cell live imaging to monitor Saccharomyces cerevisiae galactokinase 1 (GAL1) expression over multiple generations. By applying pedigree analysis, we dissected and quantified the maintenance and inheritance of transcriptional reinduction memory in individual cells through multiple divisions. We systematically screened for loss- and gain-of-memory knockouts to identify memory regulators in thousands of single cells. We identified new loss-of-memory mutants, which affect memory inheritance into progeny. We also unveiled a gain-of-memory mutant, elp6 Delta, and suggest that this new phenotype can be mediated through decreased histone occupancy at the GAL1 promoter. Our work uncovers principles of maintenance and inheritance of gene expression states and their regulators at the single-cell level.
Wissenschaftlicher Artikel
Scientific Article
Yang, M. ; Jaaks, P. ; Dry, J. ; Garnett, M. ; Menden, M. ; Saez-Rodriguez, J.
NPJ Syst. Biol. Appl. 6:16 (2020)
Drug combinations can expand therapeutic options and address cancer's resistance. However, the combinatorial space is enormous precluding its systematic exploration. Therefore, synergy prediction strategies are essential. We here present an approach to prioritise drug combinations in high-throughput screens and to stratify synergistic responses. At the core of our approach is the observation that the likelihood of synergy increases when targeting proteins with either strong functional similarity or dissimilarity. We estimate the similarity applying a multitask machine learning approach to basal gene expression and response to single drugs. We tested 7 protein target pairs (representing 29 combinations) and predicted their synergies in 33 breast cancer cell lines. In addition, we experimentally validated predicted synergy of the BRAF/insulin receptor combination (Dabrafenib/BMS-754807) in 48 colorectal cancer cell lines. We anticipate that our approaches can be used for prioritization of drug combinations in large scale screenings, and to maximize the efficacy of drugs already known to induce synergy, ultimately enabling patient stratification.
Wissenschaftlicher Artikel
Scientific Article
Becker, M. ; Noll-Puchta, H. ; Amend, D. ; Nolte, F. ; Fuchs, C. ; Jeremias, I. ; Braun, C.J.
Nucleic Acids Res. 48:e78 (2020)
The systematic perturbation of genomes using CRISPR/Cas9 deciphers gene function at an unprecedented rate, depth and ease. Commercially available sgRNA libraries typically contain tens of thousands of pre-defined constructs, resulting in a complexity challenging to handle. In contrast, custom sgRNA libraries comprise gene sets of self-defined content and size, facilitating experiments under complex conditions such as in vivo systems. To streamline and upscale cloning of custom libraries, we present CLUE, a bioinformatic and wetlab pipeline for the multiplexed generation of pooled sgRNA libraries. CLUE starts from lists of genes or pasted sequences provided by the user and designs a single synthetic oligonucleotide pool containing various libraries. At the core of the approach, a barcoding strategy for unique primer binding sites allows amplifying different user-defined libraries from one single oligonucleotide pool. We prove the approach to be straightforward, versatile and specific, yielding uniform sgRNA distributions in all resulting libraries, virtually devoid of cross-contaminations. For in silico library multiplexing and design, we established an easy-to-use online platform at www. crispr-clue.de. All in all, CLUE represents a resourcesaving approach to produce numerous high quality custom sgRNA libraries in parallel, which will foster their broad use across molecular biosciences.
Wissenschaftlicher Artikel
Scientific Article
Ostaszewski, M. ; Mazein, A. ; Gillespie, M.E. ; Kuperstein, I. ; Niarakis, A. ; Hermjakob, H. ; Pico, A.R. ; Willighagen, E.L. ; Evelo, C.T. ; Hasenauer, J. ; Schreiber, F. ; Dräger, A. ; Demir, E. ; Wolkenhauer, O. ; Furlong, L.I. ; Barillot, E. ; Dopazo, J. ; Orta-Resendiz, A. ; Messina, F. ; Valencia, A. ; Funahashi, A. ; Kitano, H. ; Auffray, C. ; Balling, R. ; Schneider, R.
Sci. Data 7:136 (2020)
Researchers around the world join forces to reconstruct the molecular processes of the virus-host interactions aiming to combat the cause of the ongoing pandemic.
Sonstiges: Meinungsartikel
Other: Opinion
Filbir, F. ; Occorsio, D. ; Themistoclakis, W.
Mathematics 8:542 (2020)
In the present paper, we propose a numerical method for the simultaneous approximation of the finite Hilbert and Hadamard transforms of a given function f, supposing to know only the samples of f at equidistant points. As reference interval we consider [-1,1] and as approximation tool we use iterated Boolean sums of Bernstein polynomials, also known as generalized Bernstein polynomials. Pointwise estimates of the errors are proved, and some numerical tests are given to show the performance of the procedures and the theoretical results.
Wissenschaftlicher Artikel
Scientific Article
Zhao, N. ; Ren, Y. ; Yamazaki, Y. ; Qiao, W. ; Li, F. ; Felton, L.M. ; MahmoudianDehkordi, S. ; Kueider-Paisley, A. ; Sonoustoun, B. ; Arnold, M. ; Shue, F. ; Zheng, J. ; Attrebi, O.N. ; Martens, Y.A. ; Li, Z. ; Bastea, L. ; Meneses, A.D. ; Chen, K. ; Thompson, J.W. ; St John-Williams, L. ; Tachibana, M. ; Aikawa, T. ; Oue, H. ; Job, L. ; Yamazaki, A. ; Liu, C.C. ; Storz, P. ; Asmann, Y.W. ; Ertekin-Taner, N. ; Kanekiyo, T. ; Kaddurah-Daouk, R. ; Bu, G.
Neuron 106, 727-742 (2020)
Evidence suggests interplay among the three major risk factors for Alzheimer's disease (AD): age, APOE genotype, and sex. Here, we present comprehensive datasets and analyses of brain transcriptomes and blood metabolomes from human apoE2-, apoE3-, and apoE4-targeted replacement mice across young, middle, and old ages with both sexes. We found that age had the greatest impact on brain transcriptomes highlighted by an immune module led by Trem2 and Tyrobp, whereas APOE4 was associated with upregulation of multiple Serpina3 genes. Importantly, these networks and gene expression changes were mostly conserved in human brains. Finally, we observed a significant interaction between age, APOE genotype, and sex on unfolded protein response pathway. In the periphery, APOE2 drove distinct blood metabolome profile highlighted by the upregulation of lipid metabolites. Our work identifies unique and interactive molecular pathways underlying AD risk factors providing valuable resources for discovery and validation research in model systems and humans.
Wissenschaftlicher Artikel
Scientific Article
Matek, C. ; Schwarz, S. ; Spiekermann, K. ; Marr, C.
In: Bildverarbeitung für die Medizin 2020. 2020. 53-54 (Inf. aktuell)
Reliable recognition and microscopic differentiation of malignant and non-malignant leukocytes from peripheral blood smears is a key task of cytological diagnostics in hematology [1]. Having been practised for well over a century, cytomorphological analysis is still today routinely performed by human examiners using optical microscopes, a process that can be tedious, time-consuming, and suffering from considerable intra-and inter-rater variability [2]. Our work aims to provide a more quantitative and robust decision-aid for the differentiation of single blood cells in general and recognition of blast cells characteristic for Acute Myeloid Leukemia (AML) in particular.
Herkt, C.E. ; Caffrey, B.E. ; Surmann, K. ; Blankenburg, S. ; Gesell Salazar, M. ; Jung, A.L. ; Herbel, S.M. ; Hoffmann, K. ; Schulte, L.N. ; Chen, W. ; Sittka-Stark, A. ; Völker, U. ; Vingron, M. ; Marsico, A. ; Bertrams, W. ; Schmeck, B.
mBio 11:e03155-19 (2020)
Legionella pneumophila is an important cause of pneumonia. It invades alveolar macrophages and manipulates the immune response by interfering with signaling pathways and gene transcription to support its own replication. MicroRNAs (miRNAs) are critical posttranscriptional regulators of gene expression and are involved in defense against bacterial infections. Several pathogens have been shown to exploit the host miRNA machinery to their advantage. We therefore hypothesize that macrophage miRNAs exert positive or negative control over Legionella intracellular replication. We found significant regulation of 85 miRNAs in human macrophages upon L. pneurnophila infection. Chromatin immunoprecipitation and sequencing revealed concordant changes of histone acetylation at the putative promoters. Interestingly, a trio of miRNAs (miR-125b, miR-221, and miR-579) was found to significantly affect intracellular L. pneumophila replication in a cooperative manner. Using proteome-analysis, we pinpointed this effect to a concerted downregulation of galectin-8 (LGALS8), DExD/H-box helicase 58 (DDX58), tumor protein P53 (TP53), and then MX dynamin-like GTPase 1 (MX1) by the three miRNAs. In summary, our results demonstrate a new miRNA-controlled immune network restricting Legionella replication in human macrophages.IMPORTANCE Cases of Legionella pneumophila pneumonia occur worldwide, with potentially fatal outcome. When causing human disease, Legionella injects a plethora of virulence factors to reprogram macrophages to circumvent immune defense and create a replication niche. By analyzing Legionella-induced changes in miRNA expression and genomewide chromatin modifications in primary human macrophages, we identified a cell-autonomous immune network restricting Legionella growth. This network comprises three miRNAs governing expression of the cytosolic RNA receptor DDX58/RIG-1, the tumor suppressor TP53, the antibacterial effector LGALS8, and MX1, which has been described as an antiviral factor. Our findings for the first time link TP53, LGALS8, DDX58, and MX1 in one miRNA-regulated network and integrate them into a functional node in the defense against L. pneumophila.
Wissenschaftlicher Artikel
Scientific Article
Ziegler, C.G.K. ; Allon, S.J. ; Nyquist, S.K. ; Mbano, I.M. ; Miao, V.N. ; Tzouanas, C.N. ; Cao, Y. ; Yousif, A.S. ; Bals, J. ; Hauser, B.M. ; Feldman, J. ; Muus, C. ; Wadsworth, M.H. ; Kazer, S.W. ; Hughes, T.K. ; Doran, B. ; Gatter, G.J. ; Vukovic, M. ; Taliaferro, F. ; Mead, B.E. ; Guo, Z. ; Wang, J.P. ; Gras, D. ; Plaisant, M. ; Ansari, M. ; Angelidis, I. ; Adler, H. ; Sucre, J.M.S. ; Taylor, C.J. ; Lin, B. ; Waghray, A. ; Mitsialis, V. ; Dwyer, D.F. ; Buchheit, K.M. ; Boyce, J.A. ; Barrett, N.A. ; Laidlaw, T.M. ; Carroll, S.L. ; Colonna, L. ; Tkachev, V. ; Peterson, C.W. ; Yu, A. ; Zheng, H.B. ; Gideon, H.P. ; Winchell, C.G. ; Lin, P.L. ; Bingle, C.D. ; Snapper, S.B. ; Kropski, J.A. ; Theis, F.J. ; Schiller, H. B. ; Zaragosi, L.E. ; Barbry, P. ; Leslie, A. ; Kiem, H.P. ; Flynn, J.L. ; Fortune, S.M. ; Berger, B. ; Finberg, R.W. ; Kean, L.S. ; Garber, M. ; Schmidt, A.G. ; Lingwood, D. ; Shalek, A.K. ; Ordovas-Montanes, J.
Cell 181, 1016-1035 (2020)
There is pressing urgency to understand the pathogenesis of the severe acute respiratory syndrome coronavirus clade 2 (SARS-CoV-2), which causes the disease COVID-19. SARS-CoV-2 spike (S) protein binds angiotensin-converting enzyme 2 (ACE2), and in concert with host proteases, principally transmembrane serine protease 2 (TMPRSS2), promotes cellular entry. The cell subsets targeted by SARS-CoV-2 in host tissues and the factors that regulate ACE2 expression remain unknown. Here, we leverage human, non-human primate, and mouse single-cell RNA-sequencing (scRNA-seq) datasets across health and disease to uncover putative targets of SARS-CoV-2 among tissue-resident cell subsets. We identify ACE2 and TMPRSS2 co-expressing cells within lung type II pneumocytes, ileal absorptive enterocytes, and nasal goblet secretory cells. Strikingly, we discovered that ACE2 is a human interferon-stimulated gene (ISG) in vitro using airway epithelial cells and extend our findings to in vivo viral infections. Our data suggest that SARS-CoV-2 could exploit species-specific interferon-driven upregulation of ACE2, a tissue-protective mediator during lung injury, to enhance infection.
Wissenschaftlicher Artikel
Scientific Article
Solovey, M. ; Scialdone, A.
Bioinformatics 36, 4296-4300 (2020)
MOTIVATION: Intercellular communication plays an essential role in multicellular organisms and several algorithms to analyze it from single-cell transcriptional data have been recently published, but the results are often hard to visualize and interpret. RESULTS: We developed Cell cOmmunication exploration with MUltiplex NETworks (COMUNET), a tool that streamlines the interpretation of the results from cell-cell communication analyses. COMUNET uses multiplex networks to represent and cluster all potential communication patterns between cell types. The algorithm also enables the search for specific patterns of communication and can perform comparative analysis between two biological conditions. To exemplify its use, here we apply COMUNET to investigate cell communication patterns in single-cell transcriptomic datasets from mouse embryos and from an acute myeloid leukemia patient at diagnosis and after treatment. AVAILABILITY AND IMPLEMENTATION: Our algorithm is implemented in an R package available from https://github.com/ScialdoneLab/COMUNET, along with all the code to perform the analyses reported here. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Wissenschaftlicher Artikel
Scientific Article
Schuh, L. ; Saint-Antoine, M. ; Sanford, E.M. ; Emert, B.L. ; Singh, A. ; Marr, C. ; Raj, A. ; Goyal, Y.
Cell Syst. 10, 363-378.e12 (2020)
Non-genetic transcriptional variability is a potential mechanism for therapy resistance in melanoma. Specifically, rare subpopulations of cells occupy a transient pre-resistant state characterized by coordinated high expression of several genes and survive therapy. How might these rare states arise and disappear within the population? It is unclear whether the canonical models of probabilistic transcriptional pulsing can explain this behavior, or if it requires special, hitherto unidentified mechanisms. We show that a minimal model of transcriptional bursting and gene interactions can give rise to rare coordinated high expression states, These states occur more frequently in networks with low connectivity and depend on three parameters. While entry into these states is initiated by a long transcriptional burst that also triggers entry of other genes, the exit occurs through independent inactivation of individual genes. Together, we demonstrate that established principles of gene regulation are sufficient to describe this behavior and argue for its more general existence. A record of this paper's transparent peer review process is included in the Supplemental Information.
Wissenschaftlicher Artikel
Scientific Article
Lopez Garcia, A. ; Tran, V. ; Alic, A.S. ; Caballer, M. ; Plasencia, I.C. ; Costantini, A. ; Dlugolinsky, S. ; Duma, D.C. ; Donvito, G. ; Gomes, J. ; Heredia Cacha, I. ; De Lucas, J.M. ; Ito, K. ; Kozlov, V.Y. ; Nguyen, G. ; Orviz Fernandez, P. ; Sustr, Z. ; Wolniewicz, P. ; Antonacci, M. ; zu Castell, W. ; David, M. ; Hardt, M. ; Lloret Iglesias, L. ; Molto, G. ; Plociennik, M.
IEEE Access 8, 18681-18692 (2020)
In this paper we propose a distributed architecture to provide machine learning practitioners with a set of tools and cloud services that cover the whole machine learning development cycle: ranging from the models creation, training, validation and testing to the models serving as a service, sharing and publication. In such respect, the DEEP-Hybrid-DataCloud framework allows transparent access to existing e-Infrastructures, effectively exploiting distributed resources for the most compute-intensive tasks coming from the machine learning development cycle. Moreover, it provides scientists with a set of Cloud-oriented services to make their models publicly available, by adopting a serverless architecture and a DevOps approach, allowing an easy share, publish and deploy of the developed models.
Wissenschaftlicher Artikel
Scientific Article
Efendiyev, M.A. ; Otani, M. ; Eberl, H.J.
SIAM J. Math. Anal. 52, 543-569 (2020)
The model that we investigate here is motivated by the mitochondria' swelling process controlled by calcium ions, the spatial dynamics of which is described by degenerate diffusion. We analyze the well-posedness and the long-term behavior of this PDE-ODE coupled system using a combination of variational methods with super- and subsolution arguments and properties of sublinear elliptic equations, and Lusin's theorem. We find that in order to be able to capture partial swelling in the long term the new model requires fewer structural assumptions on the nonlinear swelling rates than were required for a model with linear diffusion. Furthermore, if the nonlinear diffusion effects for calcium ions dominate over their production, in the long term all mitochondria will either be still intact or have completed swelling. On the other hand, if the calcium ion production dominates the nonlinear diffusion effects, some mitochodria will also remain in the intermediate state where swelling has been initiated but not completed.
Wissenschaftlicher Artikel
Scientific Article
Deering, K. ; Spiegel, E. ; Quaisser, C. ; Nowak, D. ; Rakete, S. ; Garí, M. ; Bose-O'Reilly, S.
Environ. Res. 184:109271 (2020)
Chemical compounds such as arsenic, mercury and organochlorine pesticides have been extensively used as preventive and curative conservation treatments for cultural and biological collections to protect them from pest and mold infestations. Most of the aforementioned compounds have been classified as carcinogenic, mutagenic and teratogenic and represent a health risk for members of staff exposed to contaminated objects. The present study addresses the internal exposure of 28 museum employees in Museum fur Naturkunde Berlin by measuring arsenic species and mercury in urine as well as hexachlorocyclohexane isomers (alpha-HCH, beta-HCH, gamma-HCH), hex- achlorobenzene (HCB), dichlorodiphenyltrichloroethane (4,4'-DDT) and its main metabolite, di-chlorodiphenyldichloroethylene (4,4'-DDE), and pentachlorophenol (PCP) in blood serum. This study was carried out in order to assess the internal exposure of Natural History Museum staff members to toxic metals and organochlorine pesticides.During a working week, two blood samples and five urine samples were taken from each participant, involving 8 women and 20 men. Information about work activity and exposure related factors such as dust development through work, use of personal protective equipment, as well as a nutrition diary were obtained through a questionnaire. Information on fish and seafood intakes as well as amalgam fillings was also available. The results of the study showed that the museum staff members had quantified concentrations of arsenic (median of 6.4 mu g/l; maximum of 339 mu g/l), mercury (median of 0.20 mu g/l; max of 2.6 mu g/l), beta-HCH (median of 0.12 mu g/l; max of 0.39 mu g/l) and 4,4'-DDT (median of 0.050 mu g/l; max of 0.82 mu g/l). Despite that all the concentrations were below the established reference values, multivariate regression models were able to show that museum staff members are currently exposed to the aforementioned compounds while handling museum objects. To validate our findings, further studies are required.
Wissenschaftlicher Artikel
Scientific Article
Rondina, M.T. ; Voora, D. ; Simon, L. ; Schwertz, H. ; Harper, J.F. ; Lee, O. ; Bhatlekar, S.C. ; Li, Q. ; Eustes, A.S. ; Montenont, E. ; Campbell, R.A. ; Tolley, N.D. ; Kosaka, Y. ; Weyrich, A.S. ; Bray, P.F. ; Rowley, J.W.
Circ. Res. 126, 501-516 (2020)
Rationale:Longitudinal studies are required to distinguish within versus between-individual variation and repeatability of gene expression. They are uniquely positioned to decipher genetic signal from environmental noise, with potential application to gene variant and expression studies. However, longitudinal analyses of gene expression in healthy individuals-especially with regards to alternative splicing-are lacking for most primary cell types, including platelets.Objective:To assess repeatability of gene expression and splicing in platelets and use repeatability to identify novel platelet expression quantitative trait loci (QTLs) and splice QTLs.Methods and Results:We sequenced the transcriptome of platelets isolated repeatedly up to 4 years from healthy individuals. We examined within and between individual variation and repeatability of platelet RNA expression and exon skipping, a readily measured alternative splicing event. We find that platelet gene expression is generally stable between and within-individuals over time-with the exception of a subset of genes enriched for the inflammation gene ontology. We show an enrichment among repeatable genes for associations with heritable traits, including known and novel platelet expression QTLs. Several exon skipping events were also highly repeatable, suggesting heritable patterns of splicing in platelets. One of the most repeatable was exon 14 skipping of SELP. Accordingly, we identify rs6128 as a platelet splice QTL and define an rs6128-dependent association between SELP exon 14 skipping and race. In vitro experiments demonstrate that this single nucleotide variant directly affects exon 14 skipping and changes the ratio of transmembrane versus soluble P-selectin protein production.Conclusions:We conclude that the platelet transcriptome is generally stable over 4 years. We demonstrate the use of repeatability of gene expression and splicing to identify novel platelet expression QTLs and splice QTLs. rs6128 is a platelet splice QTL that alters SELP exon 14 skipping and soluble versus transmembrane P-selectin protein production.
Wissenschaftlicher Artikel
Scientific Article
Sungnak, W. ; Huang, N. ; Bécavin, C. ; Berg, M. ; Queen, R. ; Litvinukova, M. ; Talavera-López, C. ; Maatz, H. ; Reichart, D. ; Sampaziotis, F. ; Worlock, K.B. ; Yoshida, M. ; Barnes, J.L. ; HCA Lung Biological Network (Schiller, H. B. ; Theis, F.J.)
Nat. Med. 26, 681–687 (2020)
We investigated SARS-CoV-2 potential tropism by surveying expression of viral entry-associated genes in single-cell RNA-sequencing data from multiple tissues from healthy human donors. We co-detected these transcripts in specific respiratory, corneal and intestinal epithelial cells, potentially explaining the high efficiency of SARS-CoV-2 transmission. These genes are co-expressed in nasal epithelial cells with genes involved in innate immunity, highlighting the cells’ potential role in initial viral infection, spread and clearance. The study offers a useful resource for further lines of inquiry with valuable clinical samples from COVID-19 patients and we provide our data in a comprehensive, open and user-friendly fashion at www.covid19cellatlas.org.
Wissenschaftlicher Artikel
Scientific Article
Sachs, S. ; Bastidas-Ponce, A. ; Tritschler, S. ; Bakhti, M. ; Böttcher, A. ; Sánchez-Garrido, M.A. ; Tarquis Medina, M. ; Kleinert, M. ; Fischer, K. ; Jall, S. ; Harger, A. ; Bader, E. ; Roscioni, S. ; Ussar, S. ; Feuchtinger, A. ; Yesildag, B. ; Neelakandhan, A. ; Jensen, C.B. ; Cornu, M. ; Yang, B. ; Finan, B. ; DiMarchi, R.D. ; Tschöp, M.H. ; Theis, F.J. ; Hofmann, S.M. ; Müller, T.D. ; Lickert, H.
Nat. Metab. 2, 380 (2020)
An amendment to this paper has been published and can be accessed via a link at the top of the paper.
Jiang, D. ; Ramesh, P. ; Christ, S. ; Correa-Gallegos, D. ; Gopal, S.K. ; Yu, Q. ; Lupperger, V. ; Marr, C. ; Rinkevich, Y.
Wound Repair Regen. 28, A16-A16 (2020)
Meeting abstract
Meeting abstract
Kozak, E.L. ; Palit, S. ; Miranda Rodriguez, J.R. ; Janjic, A. ; Böttcher, A. ; Lickert, H. ; Enard, W. ; Theis, F.J. ; López-Schier, H.
Curr. Biol. 30, 1142-1151 (2020)
Most plane-polarized tissues are formed by identically oriented cells [1, 2]. A notable exception occurs in the vertebrate vestibular system and lateral-line neuromasts, where mechanosensory hair cells orient along a single axis but in opposite directions to generate bipolar epithelia [3-5]. In zebrafish neuromasts, pairs of hair cells arise from the division of a non-sensory progenitor [6, 7] and acquire opposing planar polarity via the asymmetric expression of the polarity-determinant transcription factor Emx2 [8-11]. Here, we reveal the initial symmetry-breaking step by decrypting the developmental trajectory of hair cells using single-cell RNA sequencing (scRNA-seq), diffusion pseudotime analysis, lineage tracing, and mutagenesis. We show that Emx2 is absent in non-sensory epithelial cells, begins expression in hair-cell progenitors, and is downregulated in one of the sibling hair cells via signaling through the Notch1a receptor. Analysis of Emx2-deficient specimens, in which every hair cell adopts an identical direction, indicates that Emx2 asymmetry does not result from auto-regulatory feedback. These data reveal a two-tiered mechanism by which the symmetric monodirectional ground state of the epithelium is inverted by deterministic initiation of Emx2 expression in hair-cell progenitors and a subsequent stochastic repression of Emx2 in one of the sibling hair cells breaks directional symmetry to establish planar bipolarity.
Wissenschaftlicher Artikel
Scientific Article
Efendiyev, M.A. ; Vougalter, V.
Osaka J. Math. 57, 247-265 (2020)
We prove the existence in the sense of sequences of solutions for some integro-differential type equations involving the drift term in the appropriate H-2 spaces using the fixed point technique when the elliptic problems contain second order differential operators with and without Fredholm property. It is shown that, under the reasonable technical conditions, the convergence in L-1 of the integral kernels yields the existence and convergence in H-2 of solutions.
Wissenschaftlicher Artikel
Scientific Article
Lähnemann, D. ; Köster, J. ; Szczurek, E. ; McCarthy, D.J. ; Hicks, S.C. ; Robinson, M.D. ; Vallejos, C.A. ; Campbell, K.R. ; Beerenwinkel, N. ; Mahfouz, A. ; Pinello, L. ; Skums, P. ; Stamatakis, A. ; Attolini, C.S.O. ; Aparicio, S. ; Baaijens, J. ; Balvert, M. ; Barbanson, B.d. ; Cappuccio, A. ; Corleone, G. ; Dutilh, B.E. ; Florescu, M. ; Guryev, V. ; Holmer, R. ; Jahn, K. ; Lobo, T.J. ; Keizer, E.M. ; Khatri, I. ; Kielbasa, S.M. ; Korbel, J.O. ; Kozlov, A.M. ; Kuo, T.H. ; Lelieveldt, B.P.F. ; Mandoiu, I.I. ; Marioni, J.C. ; Marschall, T. ; Mölder, F. ; Niknejad, A. ; Raczkowski, L. ; Reinders, M. ; Ridder, J.d. ; Saliba, A.E. ; Somarakis, A. ; Stegle, O. ; Theis, F.J. ; Yang, H. ; Zelikovsky, A. ; McHardy, A.C. ; Raphael, B.J. ; Shah, S.P. ; Schönhuth, A.
Genome Biol. 21:31 (2020)
The recent boom in microfluidics and combinatorial indexing strategies, combined with low sequencing costs, has empowered single-cell sequencing technology. Thousands - or even millions - of cells analyzed in a single experiment amount to a data revolution in single-cell biology and pose unique data science problems. Here, we outline eleven challenges that will be central to bringing this emerging field of single-cell data science forward. For each challenge, we highlight motivating research questions, review prior work, and formulate open problems. This compendium is for established researchers, newcomers, and students alike, highlighting interesting and rewarding problems for the coming years.
Review
Review
Strunz, M. ; Simon, L. ; Ansari, M. ; Mattner, L. ; Angelidis, I. ; Mayr, C. ; Kathiriya, J. ; Yee, M. ; Ogar, P. ; Voss, C. ; Stöger, T. ; Kukhtevich, I. ; Schneider, R. ; Lehmann, M. ; Koenigshoff, M. ; Burgstaller, G. ; O'Reilly, M. ; Chapman, H. ; Theis, F.J. ; Schiller, H. B.
Wound Repair Regen. 28, A7-A7 (2020)
Meeting abstract
Meeting abstract
van der Wijst, M. ; de Vries, D.H. ; Groot, H.E. ; Trynka, G. ; Hon, C.C. ; Bonder, M.J. ; Stegle, O. ; Nawijn, M.C. ; Idaghdour, Y. ; van der Harst, P. ; Ye, C.J. ; Powell, J. ; Theis, F.J. ; Mahfouz, A. ; Heinig, M. ; Franke, L.
eLife 9:e52155 (2020)
In recent years, functional genomics approaches combining genetic information with bulk RNA-sequencing data have identified the downstream expression effects of disease-associated genetic risk factors through so-called expression quantitative trait locus (eQTL) analysis. Single-cell RNA-sequencing creates enormous opportunities for mapping eQTLs across different cell types and in dynamic processes, many of which are obscured when using bulk methods. Rapid increase in throughput and reduction in cost per cell now allow this technology to be applied to large-scale population genetics studies. To fully leverage these emerging data resources, we have founded the single-cell eQTLGen consortium (sc-eQTLGen), aimed at pinpointing the cellular contexts in which disease-causing genetic variants affect gene expression. Here, we outline the goals, approach and potential utility of the sc-eQTLGen consortium. We also provide a set of study design considerations for future single-cell eQTL studies.
Wissenschaftlicher Artikel
Scientific Article
Combettes, P.L. ; Müller, C.
Electron. J. Statist. 14, 207-238 (2020)
We introduce a flexible optimization model for maximum likelihood-type estimation (M-estimation) that encompasses and generalizes a large class of existing statistical models, including Huber’s concomitant M-estimator, Owen’s Huber/Berhu concomitant estimator, the scaled lasso, support vector machine regression, and penalized estimation with structured sparsity. The model, termed perspective M-estimation, leverages the observation that convex M-estimators with concomitant scale as well as various regularizers are instances of perspective functions, a construction that extends a convex function to a jointly convex one in terms of an additional scale variable. These nonsmooth functions are shown to be amenable to proximal analysis, which leads to principled and provably convergent optimization algorithms via proximal splitting. We derive novel proximity operators for several perspective functions of interest via a geometrical approach based on duality. We then devise a new proximal splitting algorithm to solve the proposed M-estimation problem and establish the convergence of both the scale and regression iterates it produces to a solution. Numerical experiments on synthetic and real-world data illustrate the broad applicability of the proposed framework.
Wissenschaftlicher Artikel
Scientific Article
Otto, L. ; Budde, K. ; Kastenmüller, G. ; Kaul, A. ; Völker, U. ; Völzke, H. ; Adamski, J. ; Kühn, J.P. ; Krumsiek, J. ; Artati, A. ; Nauck, M. ; Friedrich, N. ; Pietzner, M.
Sci. Rep. 10:1487 (2020)
Obesity is one of the major risk factor for cardiovascular and metabolic diseases. A disproportional accumulation of fat at visceral (VAT) compared to subcutaneous sites (SAT) has been suspected as a key detrimental event. We used non-targeted metabolomics profiling to reveal metabolic pathways associated with higher VAT or SAT amount among subjects free of metabolic diseases to identify possible contributing metabolic pathways. The study population comprised 491 subjects [mean (standard deviation): age 44.6yrs (13.0), body mass index 25.4kg/m(2) (3.6), 60.1% females] without diabetes, hypertension, dyslipidemia, the metabolic syndrome or impaired renal function. We associated MRI-derived fat amounts with mass spectrometry-derived metabolites in plasma and urine using linear regression models adjusting for major confounders. We tested for sex-specific effects using interactions terms and performed sensitivity analyses for the influence of insulin resistance on the results. VAT and SAT were significantly associated with 155 (101 urine) and 49 (29 urine) metabolites, respectively, of which 45 (27 urine) were common to both. Major metabolic pathways were branched-chain amino acid metabolism (partially independent of insulin resistance), surrogate markers of oxidative stress and gut microbial diversity, and cortisol metabolism. We observed a novel positive association between VAT and plasma levels of the potential pharmacological agent piperine. Sex-specific effects were only a few, e.g. the female-specific association between VAT and O-methylascorbate. In brief, higher VAT was associated with an unfavorable metabolite profile in a sample of healthy, mostly non-obese individuals from the general population and only few sex-specific associations became apparent.
Wissenschaftlicher Artikel
Scientific Article
Angerer, P. ; Fischer, D.S. ; Theis, F.J. ; Scialdone, A. ; Marr, C.
Bioinformatics 36, 4291-4295 (2020)
MOTIVATION: Dimensionality reduction is a key step in the analysis of single-cell RNA-sequencing data. It produces a low-dimensional embedding for visualization and as a calculation base for downstream analysis. Nonlinear techniques are most suitable to handle the intrinsic complexity of large, heterogeneous single-cell data. However, with no linear relation between gene and embedding coordinate, there is no way to extract the identity of genes driving any cell's position in the low-dimensional embedding, making it difficult to characterize the underlying biological processes. RESULTS: In this article, we introduce the concepts of local and global gene relevance to compute an equivalent of principal component analysis loadings for non-linear low-dimensional embeddings. Global gene relevance identifies drivers of the overall embedding, while local gene relevance identifies those of a defined sub-region. We apply our method to single-cell RNA-seq datasets from different experimental protocols and to different low-dimensional embedding techniques. This shows our method's versatility to identify key genes for a variety of biological processes. AVAILABILITY AND IMPLEMENTATION: To ensure reproducibility and ease of use, our method is released as part of destiny 3.0, a popular R package for building diffusion maps from single-cell transcriptomic data. It is readily available through Bioconductor. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Wissenschaftlicher Artikel
Scientific Article
Alabert, C. ; Loos, C. ; Voelker-Albert, M. ; Graziano, S. ; Forné, I. ; Reveron-Gomez, N. ; Schuh, L. ; Hasenauer, J. ; Marr, C. ; Imhof, A. ; Groth, A.
Cell Rep. 30, 1223-1234 (2020)
Chromatin states must be maintained during cell proliferation to uphold cellular identity and genome integrity. Inheritance of histone modifications is central in this process. However, the histone modification landscape is challenged by incorporation of new unmodified histones during each cell cycle, and the principles governing heritability remain unclear. We take a quantitative computational modeling approach to describe propagation of histone H3K27 and H3K36 methylation states. We measure combinatorial H3K27 and H3K36 methylation patterns by quantitative mass spectrometry on subsequent generations of histones. Using model comparison, we reject active global demethylation and invoke the existence of domains defined by distinct methylation endpoints. We find that H3K27me3 on pre-existing histones stimulates the rate of de novo H3K27me3 establishment, supporting a read-write mechanism in timely chromatin restoration. Finally, we provide a detailed quantitative picture of the mutual antagonism between H3K27 and H3K36 methylation and propose that it stabilizes epigenetic states across cell division.
Wissenschaftlicher Artikel
Scientific Article
Haffner, I. ; Schierle, K. ; Maier, D. ; Geier, B. ; Raimundez, E. ; Hasenauer, J. ; Luber, B. ; Kretzschmar, A.K. ; von Weikersthal, L.F. ; Ahlborn, M. ; Riera, J. ; Rau, B. ; Siegler, G. ; Fuxius, S. ; Decker, T. ; Wittekind, C. ; Lordick, F.
Oncol. Res. Treat. 43, 65-65 (2020)
Meeting abstract
Meeting abstract
Schukken, K.M. ; Lin, Y.-C. ; Bakker, P.L. ; Schubert, M. ; Preuss, S.F. ; Simon, J.E. ; van den Bos, H. ; Storchova, Z. ; Colomé-Tatché, M. ; Bastians, H. ; Spierings, D.C. ; Foijer, F.
Life Sci. All. 3:e201900499 (2020)
Chromosomal instability (CIN) and aneuploidy are hallmarks of cancer. As most cancers are aneuploid, targeting aneuploidy or CIN may be an effective way to target a broad spectrum of cancers. Here, we perform two small molecule compound screens to identify drugs that selectively target cells that are aneuploid or exhibit a CIN phenotype. We find that aneuploid cells are much more sensitive to the energy metabolism regulating drug ZLN005 than their euploid counterparts. Furthermore, cells with an ongoing CIN phenotype, induced by spindle assembly checkpoint (SAC) alleviation, are significantly more sensitive to the Src kinase inhibitor SKI606. We show that inhibiting Src kinase increases microtubule polymerization rates and, more generally, that deregulating microtubule polymerization rates is particularly toxic to cells with a defective SAC. Our findings, therefore, suggest that tumors with a dysfunctional SAC are particularly sensitive to microtubule poisons and, vice versa, that compounds alleviating the SAC provide a powerful means to treat tumors with deregulated microtubule dynamics.
Wissenschaftlicher Artikel
Scientific Article
Raimundez-Alvarez, E. ; Keller, S. ; Ebert, K. ; Hug, S. ; Theis, F.J. ; Maier, D. ; Luber, B. ; Hasenauer, J.
PLoS Comput. Biol. 16:e1007147 (2020)
Author summaryUnraveling the causal differences between drug responders and non-responders is an important challenge. The information can help to understand molecular mechanisms and to guide the selection and design of targeted therapies. Here, we approach this problem for cetuximab treatment for gastric cancer using mechanistic mathematical modeling. The proposed model describes responder and non-responder gastric cancer cell lines and can predict the response in several validation experiments. Our analysis provides a differentiated view on mutations and explains, for instance, the relevance of MET mutations and the insignificance of PIK3CA mutation in the considered cell lines. The model might potentially provide the basis for understanding the recent failure of several clinical studies.Targeted cancer therapies are powerful alternatives to chemotherapies or can be used complementary to these. Yet, the response to targeted treatments depends on a variety of factors, including mutations and expression levels, and therefore their outcome is difficult to predict. Here, we develop a mechanistic model of gastric cancer to study response and resistance factors for cetuximab treatment. The model captures the EGFR, ERK and AKT signaling pathways in two gastric cancer cell lines with different mutation patterns. We train the model using a comprehensive selection of time and dose response measurements, and provide an assessment of parameter and prediction uncertainties. We demonstrate that the proposed model facilitates the identification of causal differences between the cell lines. Furthermore, our study shows that the model provides predictions for the responses to different perturbations, such as knockdown and knockout experiments. Among other results, the model predicted the effect of MET mutations on cetuximab sensitivity. These predictive capabilities render the model a basis for the assessment of gastric cancer signaling and possibly for the development and discovery of predictive biomarkers.
Wissenschaftlicher Artikel
Scientific Article
Trivedi, A. ; Mehrotra, A. ; Baum, C.E. ; Lewis, B. ; Basuroy, T. ; Blomquist, T. ; Trumbly, R. ; Filipp, F.V. ; Setaluri, V. ; de la Serna, I.L.
Epigenetics Chromatin 13:14 (2020)
Background Pharmacologic inhibition of bromodomain and extra-terminal (BET) proteins is currently being explored as a new therapeutic approach in cancer. Some studies have also implicated BET proteins as regulators of cell identity and differentiation through their interactions with lineage-specific factors. However, the role of BET proteins has not yet been investigated in melanocyte differentiation. Melanocyte inducing transcription factor (MITF) is the master regulator of melanocyte differentiation, essential for pigmentation and melanocyte survival. In this study, we tested the hypothesis that BET proteins regulate melanocyte differentiation through interactions with MITF. Results Here we show that chemical inhibition of BET proteins prevents differentiation of unpigmented melanoblasts into pigmented melanocytes and results in de-pigmentation of differentiated melanocytes. BET inhibition also slowed cell growth, without causing cell death, increasing the number of cells in G1. Transcriptional profiling revealed that BET inhibition resulted in decreased expression of pigment-specific genes, including many MITF targets. The expression of pigment-specific genes was also down-regulated in melanoma cells, but to a lesser extent. We found that RNAi depletion of the BET family members, bromodomain-containing protein 4 (BRD4) and bromodomain-containing protein 2 (BRD2) inhibited expression of two melanin synthesis enzymes, TYR and TYRP1. Both BRD4 and BRD2 were detected on melanocyte promoters surrounding MITF-binding sites, were associated with open chromatin structure, and promoted MITF binding to these sites. Furthermore, BRD4 and BRD2 physically interacted with MITF. Conclusion These findings indicate a requirement for BET proteins in the regulation of pigmentation and melanocyte differentiation. We identified changes in pigmentation specific gene expression that occur upon BET inhibition in melanoblasts, melanocytes, and melanoma cells.
Wissenschaftlicher Artikel
Scientific Article
Dwyer, D.B. ; Kalman, J.L. ; Budde, M. ; Kambeitz, J. ; Ruef, A. ; Antonucci, L.A. ; Kambeitz-Ilankovic, L. ; Hasan, A. ; Kondofersky, I. ; Anderson-Schmidt, H. ; Gade, K. ; Reich-Erkelenz, D. ; Adorjan, K. ; Senner, F. ; Schaupp, S. ; Andlauer, T.F.M. ; Comes, A.L. ; Schulte, E.C. ; Klöhn-Saghatolislam, F. ; Gryaznova, A. ; Hake, M. ; Bartholdi, K. ; Flatau-Nagel, L. ; Reitt, M. ; Quast, S. ; Stegmaier, S. ; Meyers, M. ; Emons, B. ; Haußleiter, I.S. ; Juckel, G. ; Nieratschker, V. ; Dannlowski, U. ; Yoshida, T. ; Schmauß, M. ; Zimmermann, J. ; Reimer, J. ; Wiltfang, J. ; Reininghaus, E. ; Anghelescu, I.G. ; Arolt, V. ; Baune, B.T. ; Konrad, C. ; Thiel, A. ; Fallgatter, A.J. ; Figge, C. ; von Hagen, M. ; Koller, M. ; Lang, F.U. ; Wigand, M.E. ; Becker, T. ; Jäger, M. ; Dietrich, D.E. ; Scherk, H. ; Spitzer, C. ; Folkerts, H. ; Witt, S.H. ; Degenhardt, F. ; Forstner, A.J. ; Rietschel, M. ; Nöthen, M.M. ; Müller, N.S. ; Papiol, S. ; Heilbronner, U. ; Falkai, P. ; Schulze, T.G. ; Koutsouleris, N.
JAMA psychiatry 77, 523-533 (2020)
This cohort study aims to detect psychosis subgroups and examine their illness courses over 1.5 years and their polygenic scores for schizophrenia, bipolar disorder, major depression disorder, and educational achievement.Question Will data-driven clustering using high-dimensional clinical data reveal psychosis subgroups with relevance to prognoses and polygenic risk? Findings In this cohort study including 1223 individuals, in the discovery sample of 765 individuals with predominantly bipolar and schizophrenia diagnoses, 5 subgroups were detected with different clinical signatures, illness trajectories, and genetic scores for educational attainment. Results were validated in a sample of 458 individuals. Meaning New data-driven clustering paired with rigorous validation may offer a means to extend symptom-based psychosis taxonomies toward functional outcomes, genetic markers, and trajectory-based stratifications.Importance Identifying psychosis subgroups could improve clinical and research precision. Research has focused on symptom subgroups, but there is a need to consider a broader clinical spectrum, disentangle illness trajectories, and investigate genetic associations. Objective To detect psychosis subgroups using data-driven methods and examine their illness courses over 1.5 years and polygenic scores for schizophrenia, bipolar disorder, major depression disorder, and educational achievement. Design, Setting, and Participants This ongoing multisite, naturalistic, longitudinal (6-month intervals) cohort study began in January 2012 across 18 sites. Data from a referred sample of 1223 individuals (765 in the discovery sample and 458 in the validation sample) with DSM-IV diagnoses of schizophrenia, bipolar affective disorder (I/II), schizoaffective disorder, schizophreniform disorder, and brief psychotic disorder were collected from secondary and tertiary care sites. Discovery data were extracted in September 2016 and analyzed from November 2016 to January 2018, and prospective validation data were extracted in October 2018 and analyzed from January to May 2019. Main Outcomes and Measures A clinical battery of 188 variables measuring demographic characteristics, clinical history, symptoms, functioning, and cognition was decomposed using nonnegative matrix factorization clustering. Subtype-specific illness courses were compared with mixed models and polygenic scores with analysis of covariance. Supervised learning was used to replicate results in validation data with the most reliably discriminative 45 variables. Results Of the 765 individuals in the discovery sample, 341 (44.6%) were women, and the mean (SD) age was 42.7 (12.9) years. Five subgroups were found and labeled as affective psychosis (n = 252), suicidal psychosis (n = 44), depressive psychosis (n = 131), high-functioning psychosis (n = 252), and severe psychosis (n = 86). Illness courses with significant quadratic interaction terms were found for psychosis symptoms (R-2 = 0.41; 95% CI, 0.38-0.44), depression symptoms (R-2 = 0.28; 95% CI, 0.25-0.32), global functioning (R-2 = 0.16; 95% CI, 0.14-0.20), and quality of life (R-2 = 0.20; 95% CI, 0.17-0.23). The depressive and severe psychosis subgroups exhibited the lowest functioning and quadratic illness courses with partial recovery followed by reoccurrence of severe illness. Differences were found for educational attainment polygenic scores (mean [SD] partial eta(2) = 0.014 [0.003]) but not for diagnostic polygenic risk. Results were largely replicated in the validation cohort. Conclusions and Relevance Psychosis subgroups were detected with distinctive clinical signatures and illness courses and specificity for a nondiagnostic genetic marker. New data-driven clinical approaches are important for future psychosis taxonomies. The findings suggest a need to consider short-term to medium-term service provision to restore functioning in patients stratified into the depressive and severe psychosis subgroups.
Wissenschaftlicher Artikel
Scientific Article
Ricci, W.A. ; Lu, Z. ; Ji, L. ; Marand, A.P. ; Ethridge, C.L. ; Murphy, N.G. ; Noshay, J.M. ; Galli, M. ; Mejía-Guerra, M.K. ; Colomé-Tatché, M. ; Johannes, F. ; Rowley, M.J. ; Corces, V.G. ; Zhai, J. ; Scanlon, M.J. ; Buckler, E.S. ; Gallavotti, A. ; Springer, N.M. ; Schmitz, R.J. ; Zhang, X.
Nat. Plants 6:328 (2020)
An amendment to this paper has been published and can be accessed via a link at the top of the paper.
Knauer-Arloth, J. ; Eraslan, G. ; Andlauer, T.F.M. ; Martins, J. ; Iurato, S. ; Kühnel, B. ; Waldenberger, M. ; Frank, J. ; Gold, R. ; Hemmer, B. ; Luessi, F. ; Nischwitz, S. ; Paul, F. ; Wiendl, H. ; Gieger, C. ; Heilmann-Heimbach, S. ; Kacprowski, T. ; Laudes, M. ; Meitinger, T. ; Peters, A. ; Rawal, R. ; Strauch, K. ; Lucae, S. ; Müller-Myhsok, B. ; Rietschel, M. ; Theis, F.J. ; Binder, E.B. ; Müller, N.S.
PLoS Comput. Biol. 16:e1007616 (2020)
Genome-wide association studies (GWAS) identify genetic variants associated with traits or diseases. GWAS never directly link variants to regulatory mechanisms. Instead, the functional annotation of variants is typically inferred by post hoc analyses. A specific class of deep learning-based methods allows for the prediction of regulatory effects per variant on several cell type-specific chromatin features. We here describe "DeepWAS", a new approach that integrates these regulatory effect predictions of single variants into a multivariate GWAS setting. Thereby, single variants associated with a trait or disease are directly coupled to their impact on a chromatin feature in a cell type. Up to 61 regulatory SNPs, called dSNPs, were associated with multiple sclerosis (MS, 4,888 cases and 10,395 controls), major depressive disorder (MDD, 1,475 cases and 2,144 controls), and height (5,974 individuals). These variants were mainly non-coding and reached at least nominal significance in classical GWAS. The prediction accuracy was higher for DeepWAS than for classical GWAS models for 91% of the genome-wide significant, MS-specific dSNPs. DSNPs were enriched in public or cohort-matched expression and methylation quantitative trait loci and we demonstrated the potential of DeepWAS to generate testable functional hypotheses based on genotype data alone. DeepWAS is available at https://github.com/cellmapslab/DeepWAS.
Wissenschaftlicher Artikel
Scientific Article
Okolie, A. ; Müller, J.
Math. Biosci. 321:108320 (2020)
We consider a stochastic susceptible-infected-recovered (SIR) model with contact tracing on random trees and on the configuration model. On a rooted tree, where initially all individuals are susceptible apart from the root which is infected, we are able to find exact formulas for the distribution of the infectious period. Thereto, we show how to extend the existing theory for contact tracing in homogeneously mixing populations to trees. Based on these formulas, we discuss the influence of randomness in the tree and the basic reproduction number. We find the well known results for the homogeneously mixing case as a limit of the present model (tree-shaped contact graph). Furthermore, we develop approximate mean field equations for the dynamics on trees, and - using the message passing method - also for the configuration model. The interpretation and implications of the results are discussed.
Review
Review
Sachs, S. ; Bastidas-Ponce, A. ; Tritschler, S. ; Bakhti, M. ; Böttcher, A. ; Sánchez-Garrido, M.A. ; Tarquis Medina, M. ; Kleinert, M. ; Fischer, K. ; Jall, S. ; Harger, A. ; Bader, E. ; Roscioni, S. ; Ussar, S. ; Feuchtinger, A. ; Yesildag, B. ; Neelakandhan, A. ; Jensen, C.B. ; Cornu, M. ; Yang, B. ; Finan, B. ; DiMarchi, R.D. ; Tschöp, M.H. ; Theis, F.J. ; Hofmann, S.M. ; Müller, T.D. ; Lickert, H.
Nat. Metab. 2, 192-209 (2020)
Dedifferentiation of insulin-secreting β cells in the islets of Langerhans has been proposed to be a major mechanism of β-cell dysfunction. Whether dedifferentiated β cells can be targeted by pharmacological intervention for diabetes remission, and ways in which this could be accomplished, are unknown as yet. Here we report the use of streptozotocin-induced diabetes to study β-cell dedifferentiation in mice. Single-cell RNA sequencing (scRNA-seq) of islets identified markers and pathways associated with β-cell dedifferentiation and dysfunction. Single and combinatorial pharmacology further show that insulin treatment triggers insulin receptor pathway activation in β cells and restores maturation and function for diabetes remission. Additional β-cell selective delivery of oestrogen by Glucagon-like peptide-1 (GLP-1-oestrogen conjugate) decreases daily insulin requirements by 60%, triggers oestrogen-specific activation of the endoplasmic-reticulum-associated protein degradation system, and further increases β-cell survival and regeneration. GLP-1-oestrogen also protects human β cells against cytokine-induced dysfunction. This study not only describes mechanisms of β-cell dedifferentiation and regeneration, but also reveals pharmacological entry points to target dedifferentiated β cells for diabetes remission.
Wissenschaftlicher Artikel
Scientific Article
Hoksza, D. ; Gawron, P. ; Ostaszewski, M. ; Hasenauer, J. ; Schneider, R.
Brief. Bioinform. 22, 608 (2020)
The first version of this article listed one of its authors as Jan Hausenauer rather than Jan Hasenauer. This has now been corrected. The authors regret the error.
Ahmed, A.T. ; MahmoudianDehkordi, S. ; Bhattacharyya, S. ; Arnold, M. ; Liu, D. ; Neavin, D. ; Moseley, M.A. ; Thompson, J.W. ; Williams, L.S.J. ; Louie, G. ; Skime, M.K. ; Wang, L. ; Riva-Posse, P. ; McDonald, W.M. ; Bobo, W.V. ; Craighead, W.E. ; Krishnan, R. ; Weinshilboum, R.M. ; Dunlop, B.W. ; Millington, D.S. ; Rush, A.J. ; Frye, M.A. ; Kaddurah-Daouk, R.
J. Affect. Disord. 264, 90-97 (2020)
Background: Acylcarnitines have important functions in mitochondrial energetics and beta-oxidation, and have been implicated to play a significant role in metabolic functions of the brain. This retrospective study examined whether plasma acylcarnitine profiles can help biochemically distinguish the three phenotypic subtypes of major depressive disorder (MDD): core depression (CD+), anxious depression (ANX+), and neurovegetative symptoms of melancholia (NVSM+).Methods: Depressed outpatients (n = 240) from the Mayo Clinic Pharmacogenomics Research Network were treated with citalopram or escitalopram for eight weeks. Plasma samples collected at baseline and after eight weeks of treatment with citalopram or escitalopram were profiled for short-, medium- and long-chain acylcarnitine levels using AbsoluteIDQ (R) p180-Kit and LC-MS. Linear mixed effects models were used to examine whether acylcarnitine levels discriminated the clinical phenotypes at baseline or eight weeks post-treatment, and whether temporal changes in acylcarnitine profiles differed between groups.Results: Compared to ANX+, CD+ and NVSM+ had significantly lower concentrations of short- and long-chain acylcarnitines at both baseline and week 8. In NVSM+, the medium- and long-chain acylcarnitines were also significantly lower in NVSM+ compared to ANX+. Short-chain acylcarnitine levels increased significantly from baseline to week 8 in CD+ and ANX+, whereas medium- and long-chain acylcarnitines significantly decreased in CD+ and NVSM+.Conclusions: In depressed patients treated with SSRIs, beta-oxidation and mitochondrial energetics as evaluated by levels and changes in acylcarnitines may provide the biochemical basis of the clinical heterogeneity of MDD, especially when combined with clinical characteristics.
Wissenschaftlicher Artikel
Scientific Article
Cartis, C. ; Gould, N.I.M. ; Lange, M.
BIT Num. Math. 60, 583–589 (2020)
We show that the minimizers of regularized quadratic functions restricted to their natural Krylov spaces increase in Euclidean norm as the spaces expand.
Wissenschaftlicher Artikel
Scientific Article
Loos, C. ; Hasenauer, J.
J. Theor. Biol. 488:110118 (2020)
Cellular heterogeneity is known to have important effects on signal processing and cellular decision making. To understand these processes, multiple classes of mathematical models have been introduced. The hierarchical population model builds a novel class which allows for the mechanistic description of heterogeneity and explicitly takes into account subpopulation structures. However, this model requires a parametric distribution assumption for the cell population and, so far, only the normal distribution has been employed. Here, we incorporate alternative distribution assumptions into the model, assess their robustness against outliers and evaluate their influence on the performance of model calibration in a simulation study and a real-world application example. We found that alternative distributions provide reliable parameter estimates even in the presence of outliers, and can in fact increase the convergence of model calibration. (C) 2019 Elsevier Ltd. All rights reserved.
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Scientific Article
Sissouno, N. ; Boßmann, F. ; Filbir, F. ; Iwen, M. ; Kahnt, M. ; Saab, R. ; Schroer, C. ; zu Castell, W.
Math. Comput. Simul. 176, 292-300 (2020)
Measurements achieved with ptychographic imaging are a special case of diffraction measurements. They are generated by illuminating small parts of a sample with, e.g., a focused X-ray beam. By shifting the sample, a set of far-field diffraction patterns of the whole sample is then obtained. From a mathematical point of view those measurements are the squared modulus of the windowed Fourier transform of the sample. Thus, we have a phase retrieval problem for local Fourier measurements. A direct solver for this problem was introduced by Iwen, Viswanathan and Wang in 2016 and improved by Iwen, Preskitt, Saab and Viswanathan in 2018. Motivated by the applied perspective of ptychographic imaging, we present a generalization of this method and compare the different versions in numerical experiments. The new method proposed herein turns out to be more stable, particularly in the case of missing data. (C) 2019 International Association for Mathematics and Computers in Simulation (IMACS). Published by Elsevier B.V. All rights reserved.
Wissenschaftlicher Artikel
Scientific Article
Porubsky, D. ; Sanders, A.D. ; Taudt, A. ; Colomé-Tatché, M. ; Lansdorp, P.M. ; Guryev, V.
Bioinformatics 36, 1260-1261 (2020)
MOTIVATION: Strand-seq is a specialized single-cell DNA sequencing technique centered around the directionality of single-stranded DNA. Computational tools for Strand-seq analyses must capture the strand-specific information embedded in these data. RESULTS: Here we introduce breakpointR, an R/Bioconductor package specifically tailored to process and interpret single-cell strand-specific sequencing data obtained from Strand-seq. We developed breakpointR to detect local changes in strand directionality of aligned Strand-seq data, to enable fine-mapping of sister chromatid exchanges, germline inversion and to support global haplotype assembly. Given the broad spectrum of Strand-seq applications we expect breakpointR to be an important addition to currently available tools and extend the accessibility of this novel sequencing technique. AVAILABILITY: R/Bioconductor package https://bioconductor.org/packages/breakpointR.
Wissenschaftlicher Artikel
Scientific Article
Kiefer, L. ; Storath, M. ; Weinmann, A.
IEEE Trans. Image Process. 29, 921-933 (2020)
We propose an algorithm to efficiently compute approximate solutions of the piecewise affine Mumford-Shah model. The algorithm is based on a novel reformulation of the underlying optimization problem in terms of Taylor jets. A splitting approach leads to linewise segmented jet estimation problems for which we propose an exact and efficient solver. The proposed method has the combined advantages of prior algorithms: it directly yields a partition, it does not need an initialization procedure, and it is highly parallelizable. The experiments show that the algorithm has lower computation times and that the solutions often have lower functional values than the state-of-the-art.
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Scientific Article
Lauffer, F. ; Jargosch, M. ; Baghin, V. ; Krause, L. ; Kempf, W. ; Absmaier-Kijak, M. ; Morelli, M. ; Madonna, S. ; Marsais, F. ; Lepescheux, L. ; Albanesi, C. ; Müller, N.S. ; Theis, F.J. ; Schmidt-Weber, C.B. ; Eyerich, S. ; Biedermann, T. ; Vandeghinste, N. ; Steidl, S. ; Eyerich, K.
J. Eur. Acad. Dermatol. Venereol. 34, 800-809 (2020)
Background: Key pathogenic events of psoriasis and atopic eczema (AE) are misguided immune reactions of the skin. IL-17C is an epithelial-derived cytokine, whose impact on skin inflammation is unclear. Objective: We sought to characterize the role of IL-17C in human ISD. Methods: IL-17C gene and protein expression was assessed by immunohistochemistry and transcriptome analysis. Primary human keratinocytes were stimulated and expression of cytokines chemokines was determined by qRT-PCR and luminex assay. Neutrophil migration towards supernatant of stimulated keratinocytes was assessed. IL-17C was depleted using a new IL-17C-specific antibody (MOR106) in murine models of psoriasis (IL-23 injection model) and AE (MC903 model) as well as in human skin biopsies of psoriasis and AE. Effects on cell influx (mouse models) and gene expression (human explant cultures) were determined. Results: Expression of IL-17C mRNA and protein was elevated in various ISD. We demonstrate that IL-17C potentiates the expression of innate cytokines, antimicrobial peptides (IL-36G, S100A7 and HBD2) and chemokines (CXCL8, CXCL10, CCL5 and VEGF) and the autocrine induction of IL-17C in keratinocytes. Cell-free supernatant of keratinocytes stimulated with IL-17C was strongly chemotactic for neutrophils, thus demonstrating a critical role for IL-17C in immune cell recruitment. IL-17C depletion significantly reduced cell numbers of T cells, neutrophils and eosinophils in murine models of psoriasis and AE and led to a significant downregulation of inflammatory mediators in human skin biopsies of psoriasis and AE ex vivo. Conclusion: IL-17C amplifies epithelial inflammation in Th2 and Th17 dominated skin inflammation and represents a promising target for the treatment of ISD.
Wissenschaftlicher Artikel
Scientific Article
Schubert, M. ; Colomé-Tatché, M. ; Foijer, F.
Biochim. Biophys. Acta-Gene Regul. Mech. 1863:194444 (2020)
Gene regulatory network inference is a standard technique for obtaining structured regulatory information from, for instance, gene expression measurements. Methods performing this task have been extensively evaluated on synthetic, and to a lesser extent real data sets. In contrast to these test evaluations, applications to gene expression data of human cancers are often limited by fewer samples and more potential regulatory links, and are biased by copy number aberrations as well as cell mixtures and sample impurities. Here, we take networks inferred from TCGA cohorts as an example to show that (1) transcription factor annotations are essential to obtain reliable networks, and (2) even for state of the art methods, we expect that between 20 and 80% of edges are caused by copy number changes and cell mixtures rather than transcription factor regulation.
Review
Review
Cordero-Martínez, J. ; Flores-Alonso, J.C. ; Aguirre-Alvarado, C. ; Oviedo, N. ; Alcántara-Farfán, V. ; Garcia Perez, C. ; Bermúdez-Ruiz, K.F. ; Jiménez-Gutiérrez, G.E. ; Rodríguez-Páez, L.
J. Ethnopharmacol. 248, DOI: 10.1016/j.jep.2019.112321 (2020)
Ethnopharmacology relevance: In traditional Mexican medicine, Echeveria gibbiflora DC has been used as a vaginal post-coital rinse to prevent pregnancy. The aqueous crude extract (OBACE) induces sperm immobilization/agglutination and a hypotonic-like effect, likely attributed to the high concentration of calcium bis-(hydrogen-1-malate) hexahydrate [Ca2+ (C4H5O5)(2)center dot 6H(2)O]. Likewise, OBACE impedes the increase of [Ca2+]i during capacitation.Aim of the study: Evaluate the effect of OBACE on sperm energy metabolism and the underlying mechanism of action on sperm-specific channel.Material and methods: In vitro, we quantified the mouse sperm immobilization effect and the antifertility potential of OBACE. The energetic metabolism status was also evaluated by assessing the ATP levels, general mitochondrial activity, mitochondrial membrane potential, and enzymatic activity of three key enzymes of energy metabolism. Furthermore, the effect of the ion efflux of Cl- and K+, as well as the pHi, were investigated in order to elucidate which channel is suitable to perform an in silico study.Results: Total and progressive motility notably decreased, as did fertility rates. ATP levels, mitochondrial activity and membrane potential were reduced. Furthermore, the activities of the three enzymes decreased. Neither Cl- or K+ channels activities were affected at low concentrations of OBACE; nevertheless, pHi did not alkalinize. Finally, an in silica analysis was performed between the Catsper channel and calcium bis-(hydrogen-1-malate) hexahydrate, which showed a possible blockade of this sperm cation channel.Conclusion: The results were useful to elucidate the effect of OBACE and to propose it as a future male contraceptive.
Wissenschaftlicher Artikel
Scientific Article
Scherb, H. ; Grech, V.
Early Hum. Dev. 141:104869 (2020)
Introduction: The human sex ratio or sex odds at birth (M/F) are influenced by many factors. Radiation is the only stressor known to elevate the ratio while dropping total births. The Mainz research nuclear reactor (FRMZ) underwent extensive refurbishment commencing in 1992 and with further upgrading in 2011. This study was carried out in order to investigate any possible effects of these events on M/F.Methods: Annual municipality-specific births by sex were obtained from official government sources. Statistical methods used included ordinary linear logistic regression and Poisson regression.Results: M/F rose significantly in 1993 only close to the FRMZ (< 10 km) with sex odds ratio (SOR) 1.023 (p = 0.0074) and this rise was associated with numerically equivalent drops in male births of 4.01% (p = 0.0251) and female births of 6.17% (p = 0.0005). No such effects were seen beyond 10 km.Discussion: These findings add to the corpus of evidence that man-made radiation may have significant effects on total births and on M/F with a skew toward male births. While the authors are certain that suitable precautions were taken when the reactor in Mainz was handled, the findings imply that these may not have been sufficient. Perhaps even greater care and even more stringent precautions need to be employed when dealing with radioactive elements. It clearly behoves humanity to exercise extreme caution when handling, processing, and storing radioactive materials and waste.
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Scientific Article
Schmiester, L. ; Schälte, Y. ; Fröhlich, F. ; Hasenauer, J. ; Weindl, D.
Bioinformatics 36, 594-602 (2020)
Motivation: Mechanistic models of biochemical reaction networks facilitate the quantitative understanding of biological processes and the integration of heterogeneous datasets. However, some biological processes require the consideration of comprehensive reaction networks and therefore large-scale models. Parameter estimation for such models poses great challenges, in particular when the data are on a relative scale.Results: Here, we propose a novel hierarchical approach combining (i) the efficient analytic evaluation of optimal scaling, offset and error model parameters with (ii) the scalable evaluation of objective function gradients using adjoint sensitivity analysis. We evaluate the properties of the methods by parameterizing a pan-cancer ordinary differential equation model (>1000 state variables, >4000 parameters) using relative protein, phosphoprotein and viability measurements. The hierarchical formulation improves optimizer performance considerably. Furthermore, we show that this approach allows estimating error model parameters with negligible computational overhead when no experimental estimates are available, providing an unbiased way to weight heterogeneous data. Overall, our hierarchical formulation is applicable to a wide range of models, and allows for the efficient parameterization of large-scale models based on heterogeneous relative measurements.
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Scientific Article
Guala, D. ; Ogris, C. ; Müller, N.S. ; Sonnhammer, E.L.L.
Brief. Bioinform. 21, 1224-1237 (2020)
The vast amount of experimental data from recent advances in the field of high-throughput biology begs for integration into more complex data structures such as genome-wide functional association networks. Such networks have been used for elucidation of the interplay of intra-cellular molecules to make advances ranging from the basic science understanding of evolutionary processes to the more translational field of precision medicine. The allure of the field has resulted in rapid growth of the number of available network resources, each with unique attributes exploitable to answer different biological questions. Unfortunately, the high volume of network resources makes it impossible for the intended user to select an appropriate tool for their particular research question. The aim of this paper is to provide an overview of the underlying data and representative network resources as well as to mention methods of integration, allowing a customized approach to resource selection. Additionally, this report will provide a primer for researchers venturing into the field of network integration.
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Hoksza, D. ; Gawron, P. ; Ostaszewski, M. ; Hasenauer, J. ; Schneider, R.
Brief. Bioinform. 21, 1249-1260 (2020)
The understanding of complex biological networks often relies on both a dedicated layout and a topology. Currently, there are three major competing layout-aware systems biology formats, but there are no software tools or software libraries supporting all of them. This complicates the management of molecular network layouts and hinders their reuse and extension. In this paper, we present a high-level overview of the layout formats in systems biology, focusing on their commonalities and differences, review their support in existing software tools, libraries and repositories and finally introduce a new conversion module within the MINERVA platform. The module is available via a REST API and offers, besides the ability to convert between layout-aware systems biology formats, the possibility to export layouts into several graphical formats. The module enables conversion of very large networks with thousands of elements, such as disease maps or metabolic reconstructions, rendering it widely applicable in systems biology.
Review
Review
Förster, K. ; Ertl-Wagner, B. ; Ehrhardt, H. ; Busen, H. ; Sass, S. ; Pomschar, A. ; Naehrlich, L. ; Schulze, A. ; Flemmer, A.W. ; Hübener, C. ; Eickelberg, O. ; Theis, F.J. ; Dietrich, O. ; Hilgendorff, A.
Thorax 75, 184-187 (2020)
We developed a MRI protocol using transverse (T2) and longitudinal (T1) mapping sequences to characterise lung structural changes in preterm infants with bronchopulmonary dysplasia (BPD). We prospectively enrolled 61 infants to perform 3-Tesla MRI of the lung in quiet sleep. Statistical analysis was performed using logistic Group Lasso regression and logistic regression. Increased lung T2 relaxation time and decreased lung T1 relaxation time indicated BPD yielding an area under the curve (AUC) of 0.80. Results were confirmed in an independent study cohort (AUC 0.75) and mirrored by lung function testing, indicating the high potential for MRI in future BPD diagnostics.
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Scientific Article
Pitea, A. ; Kondofersky, I. ; Sass, S. ; Theis, F.J. ; Müller, N.S. ; Unger, K.
Brief. Bioinform. 21, 272-281 (2020)
Copy number aberrations (CNAs) are known to strongly affect oncogenes and tumour suppressor genes. Given the critical role CNAs play in cancer research, it is essential to accurately identify CNAs from tumour genomes. One particular challenge in finding CNAs is the effect of confounding variables. To address this issue, we assessed how commonly used CNA identification algorithms perform on SNP 6.0 genotyping data in the presence of confounding variables. We simulated realistic synthetic data with varying levels of three confounding variables-the tumour purity, the length of a copy number region and the CNA burden (the percentage of CNAs present in a profiled genome)-and evaluated the performance of OncoSNP, ASCAT, GenoCNA, GISTIC and CGHcall. Furthermore, we implemented and assessed CGHcall*, an adjusted version of CGHcall accounting for high CNA burden. Our analysis on synthetic data indicates that tumour purity and the CNA burden strongly influence the performance of all the algorithms. No algorithm can correctly find lost and gained genomic regions across all tumour purities. The length of CNA regions influenced the performance of ASCAT, CGHcall and GISTIC. OncoSNP, GenoCNA and CGHcall* showed little sensitivity. Overall, CGHcall* and OncoSNP showed reasonable performance, particularly in samples with high tumour purity. Our analysis on the HapMap data revealed a good overlap between CGHcall, CGHcall* and GenoCNA results and experimentally validated data. Our exploratory analysis on the TCGA HNSCC data revealed plausible results of CGHcall, CGHcall* and GISTIC in consensus HNSCC CNA regions.
Wissenschaftlicher Artikel
Scientific Article
2019
Melnyk, O. ; Filbir, F. ; Krahmer, F.
In: (Mathematics in Imaging 2019, 24–27 June 2019, Munich, Germany). 2019. ( ; Part F158-MATH 2019)
Motivated by applications in ptychography, we generalize a recent method for phase retrieval from local correlation measurements with unit length shifts to any fixed length. Our algorithm is complemented by recovery guarantees.
Melnyk, O. ; Filbir, F. ; Krahmer, F.
In: (13th International Conference on Sampling Theory and Applications, SampTA 2019, 8-12 July 2019, Bordeaux, France). 2019.:9030967
Driven by ptychography, we consider an extension of the phase retrieval problem from local correlation measurements with shifts of length one [1], [2], [3] to any fixed shift length. We provide an algorithm and recovery guarantees for the extended model.
Lines, G.T. ; Paszkowski, L. ; Schmiester, L. ; Weindl, D. ; Stapor, P. ; Hasenauer, J.
IFAC PapersOnline 52, 32-37 (2019)
In systems and computational biology, ordinary differential equations are used for the mechaÂnistic modelling of biochemical networks. These models can easily have hundreds of states and parameters. Typically most parameters are unknown and estimated by fitting model output to observation. During parameter estimation the model needs to be solved repeatedly, sometimes millions of times. This can then be a computational bottleneck, and limits the employment of such models. In many situations the experimental data provides information about the steady state of the biochemical reaction network. In such cases one only needs to obtain the equilibrium state for a given set of model parameters. In this paper we exploit this fact and solve the steady state problem directly rather than integrating the ODE forward in time until steady state is reached. We use Newton's method-like some previous studies- A nd develop several improvements to achieve robust convergence. To address the reliance of Newtons method on good initial guesses, we propose a continuation method. We show that the method works robustly in this setting and achieves a speed up of up to 100 compared to using ODE solves.
Wissenschaftlicher Artikel
Scientific Article
Kapfer, E.M. ; Stapor, P. ; Hasenauer, J.
IFAC PapersOnline 52, 58-64 (2019)
Mathematical models based on ordinary differential equations have been employed with great success to study complex biological systems. With soaring data availability, more and more models of increasing size are being developed. When working with these large-scale models, several challenges arise, such as high computation times or poor identifiability of model parameters. In this work, we review and illustrate the most common challenges using a published model of cellular metabolism. We summarize currently available methods to deal with some of these challenges while focusing on reproducibility and reusability of models, efficient and robust model simulation and parameter estimation.
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Scientific Article
Villaverde, A.F. ; Raimundez-Alvarez, E. ; Hasenauer, J. ; Banga, J.R.
IFAC PapersOnline 52, 45-51 (2019)
The parameters of dynamical models of biological processes always possess some degree of uncertainty. This parameter uncertainty translates into an uncertainty of model predictions. The trajectories of unmeasured state variables are examples of such predictions. Quantifying the uncertainty associated with a given prediction is an important problem for model developers and users. However, the nonlinearity and complexity of most dynamical models renders it nontrivial. Here, we evaluate three state-of-the-art approaches for prediction uncertainty quantification using two models of different sizes and computational complexities. We discuss the trade-offs between applicability and statistical interpretability of the different methods, and provide guidelines for their application.
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Scientific Article
Wang, D. ; Stapor, P. ; Hasenauer, J.
IFAC PapersOnline 52, 200-206 (2019)
Mixed effect modeling is widely used to study cell-to-cell and patient-to-patient variability. The population statistics of mixed effect models is usually approximated using Dirac mixture distributions obtained using Monte-Carlo, quasi Monte-Carlo, and sigma point methods. Here, we propose the use of a method based on the Cramér-von Mises Distance, which has been introduced in the context of filtering. We assess the accuracy of the different methods using several problems and provide the first scalability study for the Cramér-von Mises Distance method. Our results indicate that for a given number of points, the method based on the modified Cramér-von Mises Distance method tends to achieve a better approximation accuracy than Monte-Carlo and quasi Monte-Carlo methods. In contrast to sigma-point methods, the method based on the modified Cramér-von Mises Distance allows for a flexible number of points and a more accurate approximation for nonlinear problems.
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Scientific Article
Lee, J. ; Ahmidi, N. ; Srinivasan, R. ; Alejo, D. ; Dinatale, J. ; Schena, S. ; Whitman, G. ; Sussman, M. ; Shpitser, I.
Eur. Heart J. 40, 3575-3575 (2019)
Meeting abstract
Meeting abstract
Gutiérrez-Reyes, E. ; García-Segundo, C. ; García-Valenzuela, A. ; Ortega, R. ; Buj, C. ; Filbir, F.
J. Phys. Commun. 3:085007 (2019)
In this work, we solve the problem of modeling the generation of an acoustic pulse produced by the incidence of a pulsed laser light upon an elastic material. Our concern is about the heat transport during the absorption of electromagnetic radiation. We assume that the pulse duration is of the order of nanoseconds, and asses if under these conditions the contribution of the heat transport in the sample is an essential consideration in the description of the phenomena or if we can ignore it in the model. We begin with the energy balance analysis over the initial interaction of radiation with matter in the context of the formulation Meixner-Prigonine which is called the linear irreversible thermodynamics to describe the induced temperature field. Then we carry a momentum balance which yields the macroscopic elasticity equations with a heat source for the induced pressure field. Once established the equations for temperature and displacement fields, we solve them for the one-dimensional case, showing that the induced pressure has two components, one fast component and one slow component which is due to heat transport in the sample, which is one of the main contributions of the paper.
Wissenschaftlicher Artikel
Scientific Article
Sterr, M. ; Aliluev, A. ; Tritschler, S. ; Cernilogar, F.M. ; Irmler, M. ; Beckers, J. ; Schotta, G. ; Böttcher, A. ; Lickert, H.
Poster: Intestinal organoids - from stem cells to metabolism and microbiome interactions, 29 September 2019, Kopenhagen. (2019)
Cruceanu, C. ; Dony, L. ; Kontira, A.C. ; Fischer, D.S. ; Roeh, S. ; DiGiaimo, R. ; Cappello, S. ; Theis, F.J. ; Binder, E.B.
Eur. Neuropsychopharmacol. 29, S7-S8 (2019)
Meeting abstract
Meeting abstract
Argelaguet, R. ; Clark, S.J. ; Mohammed, H. ; Stapel, L.C. ; Krueger, C. ; Kapourani, C.A. ; Imaz-Rosshandler, I. ; Lohoff, T. ; Xiang, Y. ; Hanna, C.W. ; Smallwood, S. ; Ibarra-Soria, X. ; Buettner, F. ; Sanguinetti, G. ; Xie, W. ; Krueger, F. ; Göttgens, B. ; Rugg-Gunn, P.J. ; Kelsey, G. ; Dean, W. ; Nichols, J. ; Stegle, O. ; Marioni, J.C. ; Reik, W.
Nature 576, 487-491 (2019)
Formation of the three primary germ layers during gastrulation is an essential step in the establishment of the vertebrate body plan and is associated with major transcriptional changes(1-5). Global epigenetic reprogramming accompanies these changes(6-8), but the role of the epigenome in regulating early cell-fate choice remains unresolved, and the coordination between different molecular layers is unclear. Here we describe a single-cell multi-omics map of chromatin accessibility, DNA methylation and RNA expression during the onset of gastrulation in mouse embryos. The initial exit from pluripotency coincides with the establishment of a global repressive epigenetic landscape, followed by the emergence of lineage-specific epigenetic patterns during gastrulation. Notably, cells committed to mesoderm and endoderm undergo widespread coordinated epigenetic rearrangements at enhancer marks, driven by ten-eleven translocation (TET)-mediated demethylation and a concomitant increase of accessibility. By contrast, the methylation and accessibility landscape of ectodermal cells is already established in the early epiblast. Hence, regulatory elements associated with each germ layer are either epigenetically primed or remodelled before cell-fate decisions, providing the molecular framework for a hierarchical emergence of the primary germ layers.
Wissenschaftlicher Artikel
Scientific Article
Filipp, F.V.
Curr. Genet. Med. Rep. 7, 208-213 (2019)
Purpose of Review: We critically evaluate the future potential of machine learning (ML), deep learning (DL), and artificial intelligence (AI) in precision medicine. The goal of this work is to show progress in ML in digital health, to exemplify future needs and trends, and to identify any essential prerequisites of AI and ML for precision health. Recent Findings: High-throughput technologies are delivering growing volumes of biomedical data, such as large-scale genome-wide sequencing assays; libraries of medical images; or drug perturbation screens of healthy, developing, and diseased tissue. Multi-omics data in biomedicine is deep and complex, offering an opportunity for data-driven insights and automated disease classification. Learning from these data will open our understanding and definition of healthy baselines and disease signatures. State-of-the-art applications of deep neural networks include digital image recognition, single-cell clustering, and virtual drug screens, demonstrating breadths and power of ML in biomedicine. Summary: Significantly, AI and systems biology have embraced big data challenges and may enable novel biotechnology-derived therapies to facilitate the implementation of precision medicine approaches.
Review
Review
Tsepilov, Y.A. ; Sharapov, S.Z. ; Zaytseva, O.O. ; Krumsiek, J. ; Prehn, C. ; Adamski, J. ; Kastenmüller, G. ; Wang-Sattler, R. ; Strauch, K. ; Gieger, C. ; Aulchenko, Y.S.
GigaScience 8:giz162 (2019)
Guo, T. ; Luna, A. ; Rajapakse, V.N. ; Koh, C.C. ; Wu, Z. ; Liu, W. ; Sun, Y. ; Gao, H. ; Menden, M. ; Xu, C. ; Calzone, L. ; Martignetti, L. ; Auwerx, C. ; Buljan, M. ; Banaei-Esfahani, A. ; Ori, A. ; Iskar, M. ; Gillet, L. ; Bi, R. ; Zhang, J. ; Zhang, H. ; Yu, C. ; Zhong, Q. ; Varma, S. ; Schmitt, U. ; Qiu, P. ; Zhang, Q. ; Zhu, Y. ; Wild, P.J. ; Garnett, M.J. ; Bork, P. ; Beck, M. ; Liu, K. ; Saez-Rodriguez, J. ; Elloumi, F. ; Reinhold, W.C. ; Sander, C. ; Pommier, Y. ; Aebersold, R.
iScience 21, 664-680 (2019)
Here we describe a proteomic data resource for the NCI-60 cell lines generated by pressure cycling technology and SWATH mass spectrometry. We developed the DIA-expert software to curate and visualize the SWATH data, leading to reproducible detection of over 3,100 SwissProt proteotypic proteins and systematic quantification of pathway activities. Stoichiometric relationships of interacting proteins for DNA replication, repair, the chromatin remodeling NuRD complex, β-catenin, RNA metabolism, and prefoldins are more evident than that at the mRNA level. The data are available in CellMiner (discover.nci.nih.gov/cellminercdb and discover.nci.nih.gov/cellminer), allowing casual users to test hypotheses and perform integrative, cross-database analyses of multi-omic drug response correlations for over 20,000 drugs. We demonstrate the value of proteome data in predicting drug response for over 240 clinically relevant chemotherapeutic and targeted therapies. In summary, we present a novel proteome resource for the NCI-60, together with relevant software tools, and demonstrate the benefit of proteome analyses.
Wissenschaftlicher Artikel
Scientific Article
Frank, U. ; Kublik, S. ; Mayer, D. ; Engel, M. ; Schloter, M. ; Durner, J. ; Gaupels, F.
BMC Plant Biol. 19:539 (2019)
Background: Nitrogen dioxide (NO2) triggers hypersensitive response (HR)-like cell death in Arabidopsis thaliana. A high-throughput mutant screen was established to identify genes involved in this type of programmed cell death.Results: Altogether 14,282 lines of SALK T-DNA insertion mutants were screened. Growing 1000 pooled mutant lines per tray and simultaneous NO2 fumigation of 4 trays in parallel facilitated high-throughput screening. Candidate mutants were selected based on visible symptoms. Sensitive mutants showed lesions already after fumigation for 1 h with 10 ppm (ppm) NO2 whereas tolerant mutants were hardly damaged even after treatment with 30 ppm NO2. Identification of T-DNA insertion sites by adapter ligation-mediated PCR turned out to be successful but rather time consuming. Therefore, next generation sequencing after T-DNA-specific target enrichment was tested as an alternative screening method. The targeted genome sequencing was highly efficient due to (1.) combination of the pooled DNA from 124 candidate mutants in only two libraries, (2.) successful target enrichment using T-DNA border-specific 70mer probes, and (3.) stringent filtering of the sequencing reads. Seventy mutated genes were identified by at least 3 sequencing reads. Ten corresponding mutants were re-screened of which 8 mutants exhibited NO2-sensitivity or -tolerance confirming that the screen yielded reliable results. Identified candidate genes had published functions in HR, pathogen resistance, and stomata regulation.Conclusions: The presented NO2 dead-or-alive screen combined with next-generation sequencing after T-DNAspecific target enrichment was highly efficient. Two researchers finished the screen within 3 months. Moreover, the target enrichment approach was cost-saving because of the limited number of DNA libraries and sequencing runs required. The experimental design can be easily adapted to other screening approaches e.g. involving high-throughput treatments with abiotic stressors or phytohormones.
Wissenschaftlicher Artikel
Scientific Article
Loos, C. ; Hasenauer, J.
Curr. Opin. Syst. Biol. 16, 17-24 (2019)
Cellular signaling is essential in information processing and decision-making. Therefore, a variety of experimental approaches have been developed to study signaling on bulk and single-cell level. Single-cell measurements of signaling molecules demonstrated a substantial cell-to-cell variability, raising questions about its causes and mechanisms and about how cell populations cope with or exploit cellular heterogeneity. To gain insights from single-cell signaling data, analysis and modeling approaches have been introduced. This review discusses these modeling approaches, with a focus on recent advances in the development and calibration of mechanistic models. Additionally, it outlines current and future challenges.
Review
Review
Thomas, J. ; Küpper, M. ; Batra, R. ; Jargosch, M. ; Atenhan, A. ; Baghin, V. ; Krause, L. ; Lauffer, F. ; Biedermann, T. ; Theis, F.J. ; Eyerich, K. ; Schmidt-Weber, C.B. ; Eyerich, S. ; Garzorz-Stark, N.
J. Eur. Acad. Dermatol. Venereol. 33, 2380-2380 (2019)
Authorship correction on Is the humoral immunity dispensable for the pathogenesis of psoriasis? Thomas J, Küpper M, Batra R, Jargosch M, Atenhan A, Baghin V, Krause L, Lauffer F, Biedermann T, Theis FJ, Eyerich K, Eyerich S, Garzorz-Stark N. J Eur Acad Dermatol Venereol. 2019 Jan; 33(1): 115–122. https://doi.org/10.1111/jdv.15101. Epub 2018 Jul 2. This corrigendum is to note that the name of Prof. Carsten Schmidt-Weber was inadvertently omitted as an author in the initial version of the paper. Schmidt-Weber CB has been added for his participation and contributions in this project.
Theis, F.J. ; Ludwig, T.
Inf.-Spektrum, DOI: 10.1007/s00287-019-01220-y (2019)
Sonstiges: Meinungsartikel
Other: Opinion
Ricci, W.A. ; Lu, Z. ; Ji, L. ; Marand, A.P. ; Ethridge, C.L. ; Murphy, N.G. ; Noshay, J.M. ; Galli, M. ; Mejía-Guerra, M.K. ; Colomé-Tatché, M. ; Johannes, F. ; Rowley, M.J. ; Corces, V.G. ; Zhai, J. ; Scanlon, M.J. ; Buckler, E.S. ; Gallavotti, A. ; Springer, N.M. ; Schmitz, R.J. ; Zhang, X.
Nat. Plants 5, 1237-1249 (2019)
Genetic mapping studies on crops suggest that agronomic traits can be controlled by gene–distal intergenic loci. Despite the biological importance and the potential agronomic utility of these loci, they remain virtually uncharacterized in all crop species to date. Here, we provide genetic, epigenomic and functional molecular evidence to support the widespread existence of gene–distal (hereafter, distal) loci that act as long-range transcriptional cis-regulatory elements (CREs) in the maize genome. Such loci are enriched for euchromatic features that suggest their regulatory functions. Chromatin loops link together putative CREs with genes and recapitulate genetic interactions. Putative CREs also display elevated transcriptional enhancer activities, as measured by self-transcribing active regulatory region sequencing. These results provide functional support for the widespread existence of CREs that act over large genomic distances to control gene expression.
Wissenschaftlicher Artikel
Scientific Article
Peng, T. ; Boxberg, M. ; Weichert, W. ; Navab, N. ; Marr, C.
Lect. Notes Comput. Sc. 11764 LNCS, 676-684 (2019)
Deep neural networks have achieved tremendous success in image recognition, classification and object detection. However, deep learning is often criticised for its lack of transparency and general inability to rationalise its predictions. The issue of poor model interpretability becomes critical in medical applications: a model that is not understood and trusted by physicians is unlikely to be used in daily clinical practice. In this work, we develop a novel multi-task deep learning framework for simultaneous histopathology image classification and retrieval, leveraging on the classic concept of k-nearest neighbours to improve model interpretability. For a test image, we retrieve the most similar images from our training databases. These retrieved nearest neighbours can be used to classify the test image with a confidence score, and provide a human-interpretable explanation of our classification. Our original framework can be built on top of any existing classification network (and therefore benefit from pretrained models), by (i) combining a triplet loss function with a novel triplet sampling strategy to compare distances between samples and (ii) adding a Cauchy hashing loss function to accelerate neighbour searching. We evaluate our method on colorectal cancer histology slides and show that the confidence estimates are strongly correlated with model performance. Nearest neighbours are intuitive and useful for expert evaluation. They give insights into understanding possible model failures, and can support clinical decision making by comparing archived images and patient records with the actual case.
Wissenschaftlicher Artikel
Scientific Article
Sadafi, A. ; Koehler, N. ; Makhro, A. ; Bogdanova, A. ; Navab, N. ; Marr, C. ; Peng, T.
Lect. Notes Comput. Sc. 11764 LNCS, 685-693 (2019)
The recent success of deep learning approaches relies partly on large amounts of well annotated training data. For natural images object annotation is easy and cheap. For biomedical images however, annotation crucially depends on the availability of a trained expert whose time is typically expensive and scarce. To ensure efficient annotation, only the most relevant objects should be presented to the expert. Currently, no approach exists that allows to select those for a multiclass detection problem. Here, we present an active learning framework that identifies the most relevant samples from a large set of not annotated data for further expert annotation. Applied to brightfield images of red blood cells with seven subtypes, we train a faster R-CNN for single cell identification and classification, calculate a novel confidence score using dropout variational inference and select relevant images for annotation based on (i) the confidence of the single cell detection and (ii) the rareness of the classes contained in the image. We show that our approach leads to a drastic increase of prediction accuracy with already few annotated images. Our original approach improves classification of red blood cell subtypes and speeds up the annotation. This important step in diagnosing blood diseases will profit from our framework as well as many other clinical challenges that suffer from the lack of annotated training data.
Wissenschaftlicher Artikel
Scientific Article
Matek, C. ; Schwarz, S. ; Spiekermann, K. ; Marr, C.
Nat. Mach. Intell. 1, 538-544 (2019)
Reliable recognition of malignant white blood cells is a key step in the diagnosis of haematologic malignancies such as acute myeloid leukaemia. Microscopic morphological examination of blood cells is usually performed by trained human examiners, making the process tedious, time-consuming and hard to standardize. Here, we compile an annotated image dataset of over 18,000 white blood cells, use it to train a convolutional neural network for leukocyte classification and evaluate the network’s performance by comparing to inter- and intra-expert variability. The network classifies the most important cell types with high accuracy. It also allows us to decide two clinically relevant questions with human-level performance: (1) if a given cell has blast character and (2) if it belongs to the cell types normally present in non-pathological blood smears. Our approach holds the potential to be used as a classification aid for examining much larger numbers of cells in a smear than can usually be done by a human expert. This will allow clinicians to recognize malignant cell populations with lower prevalence at an earlier stage of the disease.
Wissenschaftlicher Artikel
Scientific Article
Sethunath, V. ; Hu, H. ; de Angelis, C. ; Veeraraghavan, J. ; Qin, L. ; Wang, N. ; Simon, L. ; Wang, T. ; Fu, X. ; Nardone, A. ; Pereira, R. ; Nanda, S. ; Griffith, O.L. ; Tsimelzon, A. ; Shaw, C. ; Chamness, G.C. ; Reis-Filho, J.S. ; Weigelt, B. ; Heiser, L.M. ; Hilsenbeck, S.G. ; Huang, S. ; Rimawi, M.F. ; Gray, J.W. ; Osborne, C.K. ; Schiff, R.
Mol. Cancer Res. 17, 2318-2330 (2019)
Despite effective strategies, resistance in HER2(+) breast cancer remains a challenge. While the mevalonate pathway (MVA) is suggested to promote cell growth and survival, including in HER2(+) models, its potential role in resistance to HER2-targeted therapy is unknown. Parental HER2(+) breast cancer cells and their lapatinib-resistant and lapatinib + trastuzumab-resistant derivatives were used for this study. MVA activity was found to be increased in lapatinib-resistant and lapatinib + trastuzumab-resistant cells. Specific blockade of this pathway with lipophilic but not hydrophilic statins and with the N-bisphosphonate zoledronic acid led to apoptosis and substantial growth inhibition of R cells. Inhibition was rescued by mevalonate or the intermediate metabolites farnesyl pyrophosphate or geranylgeranyl pyrophosphate, but not cholesterol. Activated Yes-associated protein (YAP)/transcriptional coactivator with PDZ-binding motif (TAZ) and mTORC1 signaling, and their downstream target gene product Survivin, were inhibited by MVA blockade, especially in the lapatinib-resistant/lapatinib + trastuzumab-resistant models. Overexpression of constitutively active YAP rescued Survivin and phosphorylated-S6 levels, despite blockade of the MVA. These results suggest that the MVA provides alternative signaling leading to cell survival and resistance by activating YAP/TAZ-mTORC1-Survivin signaling when HER2 is blocked, suggesting novel therapeutic targets. MVA inhibitors including lipophilic statins and N-bisphosphonates may circumvent resistance to anti-HER2 therapy warranting further clinical investigation.
Wissenschaftlicher Artikel
Scientific Article
Brown, P. ; RELISH Consortium (Filipp, F.V.) ; RELISH Consortium (Roobol, M.J.) ; Zhou, Y.
Database 2019, 1-67 (2019)
Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical science.
Wissenschaftlicher Artikel
Scientific Article
Quagliarini, F. ; Mir, A.A. ; Balazs, K. ; Wierer, M. ; Dyar, K.A. ; Jouffe, C. ; Makris, K. ; Hawe, J. ; Heinig, M. ; Filipp, F.V. ; Barish, G.D. ; Uhlenhaut, N.H.
Mol. Cell 76, 531-545.e5 (2019)
The glucocorticoid receptor (GR) is a potent metabolic regulator and a major drug target. While GR is known to play integral roles in circadian biology, its rhythmic genomic actions have never been characterized. Here we mapped GR's chromatin occupancy in mouse livers throughout the day and night cycle. We show how GR partitions metabolic processes by time-dependent target gene regulation and controls circulating glucose and triglycerides differentially during feeding and fasting. Highlighting the dominant role GR plays in synchronizing circadian amplitudes, we find that the majority of oscillating genes are bound by and depend on GR. This rhythmic pattern is altered by high-fat diet in a ligand-independent manner. We find that the remodeling of oscillatory gene expression and postprandial GR binding results from a concomitant increase of STAT5 co-occupancy in obese mice. Altogether, our findings highlight GR's fundamental role in the rhythmic orchestration of hepatic metabolism.
Wissenschaftlicher Artikel
Scientific Article
Sellinger, T. ; Müller, J. ; Hösel, V. ; Tellier, A.
Math. Biosci. 318:108272 (2019)
Despite the wealth of empirical and theoretical studies, the origin and maintenance of cooperation is still an evolutionary riddle. In this context, ecological life-history traits which affect the efficiency of selection may play a role despite being often ignored. We consider here species such as bacteria, fungi, invertebrates and plants which exhibit resting stages in the form of a quiescent state or a seed bank. When quiescent, individuals are inactive and reproduce upon activation, while under seed bank parents produce offspring remaining dormant for different amount of time. We assume weak frequency-dependent selection modeled using game-theory and the prisoner's dilemma (cooperation/defect) as payoff matrix. The cooperators and defectors are allowed to evolve different quiescence or dormancy times. By means of singular perturbation theory we reduce the model to a one-dimensional equation resembling the well known replicator equation, in which the gain functions are scaled with lumped parameters reflecting the time scale of the resting state of the cooperators and defectors. If both time scales are identical cooperation cannot persist in a homogeneous population. If, however, the time scale of the cooperator is distinctively different from that of the defector, cooperation may become a locally asymptotically stable strategy. Interestingly enough, in the seed bank case the cooperator needs to become active faster than the defector, while in the quiescent case the cooperator has to be slower. We use adaptive dynamics to identify situations where cooperation may evolve and form a convergent stable ESS. We conclude by highlighting the relevance of these results for many non-model species and the maintenance of cooperation in microbial, invertebrate or plant populations.
Wissenschaftlicher Artikel
Scientific Article
Jankowska, A. ; Polańska, K. ; Koch, H.M. ; Pälmke, C. ; Waszkowska, M. ; Stańczak, A. ; Wesołowska, E. ; Hanke, W. ; Bose-O'Reilly, S. ; Calamandrei, G. ; Garí, M.
Environ. Res. 179:108829 (2019)
Some phthalates are known endocrine disrupting chemicals (EDC). They are widely present in the environment thus their impact on children's health is of particular scientific interest. The aim of the study was to evaluate the association between phthalate exposure and neurodevelopmental outcomes, in particular behavioral, cognitive and psychomotor development, in 250 early school age children from the Polish Mother and Child Cohort (REPRO_PL). Urine samples were collected at the time of children's neurodevelopmental assessment and were analysed for 21 metabolites of 11 parent phthalates. Behavioral and emotional problems were assessed by the Strengths and Difficulties Questionnaire (SDQ) filled in by the mothers. To assess children's cognitive and psychomotor development, Polish adaptation of the Intelligence and Development Scales (IDS) was administered. The examination was performed by trained psychologists. Dimethyl phthalate (DMP) and di-n-butyl phthalate (DnBP) were the two phthalates showing the highest statistically significant associations, with higher total difficulties scores (beta = 1.5, 95% CI 0.17; 2.7; beta = 1.5, 95% CI 0.25; 2.8, respectively) as well as emotional symptoms and hyperactivity/inattention problems for DnBP (beta = 0.46, 95% CI -0.024; 0.94; beta = 0.72, 95% CI 0.065; 1.4, respectively), and peer relationships problems for DMP (beta = 0.37, 95% CI -0.013; 0.76). In addition, DnBP and DMP have been found to be negatively associated with fluid IQ (beta = -0.14, 95% CI -0.29; 0.0041) and crystallized IQ (beta = -0.16, 95% CI -0.29; -0.025), respectively. In the case of mathematical skills, three phthalates, namely DMP (beta = -0.17, 95% CI -0.31; -0.033), DEP (beta = -0.16, 95% CI -0.29; -0.018) and DnBP (beta = -0.14, 95% CI -0.28; 0.0012), have also shown statistically significant associations. This study indicates that exposure to some phthalates seems to be associated with adverse effects on behavioral and cognitive development of early school age children. Further action including legislation, educational and interventional activities to protect this vulnerable population is still needed.
Wissenschaftlicher Artikel
Scientific Article
Holmberg, O. ; Kortuem, K.U. ; Koehler, N. ; Theis, F.J.
Invest. Ophthalmol. Vis. Sci. 60 (2019)
Meeting abstract
Meeting abstract
Hanna, C.W. ; Pérez-Palacios, R. ; Gahurova, L. ; Schubert, M. ; Krueger, F. ; Biggins, L. ; Andrews, S. ; Colomé-Tatché, M. ; Bourc'his, D. ; Dean, W. ; Kelsey, G.
Genome Biol. 20:225 (2019)
Background: Genomic imprinting is an epigenetic phenomenon that allows a subset of genes to be expressed mono-allelically based on the parent of origin and is typically regulated by differential DNA methylation inherited from gametes. Imprinting is pervasive in murine extra-embryonic lineages, and uniquely, the imprinting of several genes has been found to be conferred non-canonically through maternally inherited repressive histone modification H3K27me3. However, the underlying regulatory mechanisms of non-canonical imprinting in postimplantation development remain unexplored.Results: We identify imprinted regions in post-implantation epiblast and extra-embryonic ectoderm (ExE) by assaying allelic histone modifications (H3K4me3, H3K36me3, H3K27me3), gene expression, and DNA methylation in reciprocal C57BL/6 and CAST hybrid embryos. We distinguish loci with DNA methylation-dependent (canonical) and independent (non-canonical) imprinting by assaying hybrid embryos with ablated maternally inherited DNA methylation. We find that non-canonical imprints are localized to endogenous retrovirus-K (ERVK) long terminal repeats (LTRs), which act as imprinted promoters specifically in extra-embryonic lineages. Transcribed ERVK LTRs are CpG-rich and located in close proximity to gene promoters, and imprinting status is determined by their epigenetic patterning in the oocyte. Finally, we show that oocyte-derived H3K27me3 associated with non-canonical imprints is not maintained beyond pre-implantation development at these elements and is replaced by secondary imprinted DNA methylation on the maternal allele in post-implantation ExE, while being completely silenced by bi-allelic DNA methylation in the epiblast.Conclusions: This study reveals distinct epigenetic mechanisms regulating non-canonical imprinted gene expression between embryonic and extra-embryonic development and identifies an integral role for ERVK LTR repetitive elements.
Wissenschaftlicher Artikel
Scientific Article
Hibbah, E.H. ; El Maroufy, H. ; Fuchs, C. ; Ziad, T.
J. Appl. Stat. 47, 1354-1374 (2019)
State-dependent regime switching diffusion processes or hybrid switching diffusion (HSD) processes are hard to simulate with classical methods which leads us to adopt a Markov chain Monte Carlo (MCMC) Bayesian approach very convenient to estimate complicated models such as the HSD one. In the HSD, the diffusion component is dependent on the switching discrete hidden regimes and the transition rates of the regime switching are dependent on the diffusion observations. Since in reality phenomena are only observed in discrete times, data imputation is called for to create more observations so as to have good approximations for the density of the diffusion process. Three categories of entities will be computed in a Bayesian context: The latent imputed observations, the regime switching states, and the parameters of the models. The latent imputed data is updated at random time intervals in block using a Metropolis Hastings algorithm. The switching states are computed by an adaptation of a forward filtering backward smoothing algorithm to the HSD model. The parameters are estimated after prior specifications and conditional posterior densities formulation using Gibbs sampler or Metropolis Hastings algorithm.
Wissenschaftlicher Artikel
Scientific Article
Sorg, T. ; Herault, Y. ; Jonkers, J. ; Ploubidou, A. ; Frappart, L. ; Hasenauer, J. ; Banga, J. ; Rinner, O. ; Naumova, V. ; Koubi, D. ; Lange, B.
Eur. J. Hum. Genet. 27, 571-572 (2019)
Meeting abstract
Meeting abstract
Garí, M. ; Grimalt, J.O. ; Vizcaino, E. ; Tardón, A. ; Fernández-Somoano, A.
Environ. Int. 133:105241 (2019)
Background: Breastfed children absorb persistent and toxic chemicals such as organohalogen compounds (OHCs) during the entire lactation period. Nursing is a main contributor to the burden of these pollutants in the first years of life, hence further assessments on the OHC load processes are needed. Objectives: To identify the determinants of OHC increase in children at four years of age, considering concentration gains, maternal venous concentrations and breastfeeding time. Methods: Concentrations of 19 organochlorine compounds (OCs) and 14 polybrominated diphenyl ethers (PBDEs) were analyzed in maternal venous (n = 466), cord blood (n = 326) and children venous serum at four years of age (n = 272) in the Asturias INMA cohort representing the Spanish general population. Data were evaluated considering the socio-demographic and individual information collected at recruitment and follow up surveys, as well as the OHC physical-chemical constants. Results: The four years-old children concentration gains of the most abundant OHCs showed strong correlations (R2 = 0.65–0.93) with the maternal concentrations during pregnancy and lactation period. The child gain/maternal transfer rates of most correlated pollutants were similar. Discussion: Between 65 and 93% of the variance of OCs in four years-old children was explained by the maternal concentrations during pregnancy and the lactation period. The compounds with log(Kow) > 3.7 (hydrophobic) showed analogous child gain/maternal transfer rates indicating similar processes of membrane lipid dissolution and passive diffusion from the epithelial cells into the milk. Molecular weight of these pollutants did not influence on these rates. Compounds with low log(Koa) such as hexachlorobenzene are more volatile and less retained, involving lower child gain/maternal transfer rates. These results may be useful to anticipate the increase of the concentrations of OCs in children using the maternal concentration of these compounds during pregnancy and the planned lactation period and to implement prophylactic measures in mothers with high venous pollutant concentrations.
Wissenschaftlicher Artikel
Scientific Article
Esposito, M. ; Hennersperger, C. ; Göbl, R. ; Demaret, L. ; Storath, M. ; Navab, N. ; Baust, M. ; Weinmann, A.
IEEE Trans. Med. Imaging 38, 2245-2258 (2019)
Three-dimensional freehand imaging techniques are gaining wider adoption due to their flexibility and cost efficiency. Typical examples for such a combination of a tracking system with an imaging device are freehand SPECT or freehand 3D ultrasound. However, the quality of the resulting image data is heavily dependent on the skill of the human operator and on the level of noise of the tracking data. The latter aspect can introduce blur or strong artifacts, which can significantly hamper the interpretation of image data. Unfortunately, the most commonly used tracking systems to date, i.e., optical and electromagnetic, present a trade-off between invading the surgeon's workspace (due to line-of-sight requirements) and higher levels of noise and sensitivity due to the interference of surrounding metallic objects. In this paper, we propose a novel approach for total variation regularization of data from tracking systems (which we term pose signals) based on a variational formulation in the manifold of Euclidean transformations. The performance of the proposed approach was evaluated using synthetic data as well as real ultrasound sweeps executed on both a Lego phantom and human anatomy, showing significant improvement in terms of tracking data quality and compounded ultrasound images. Source code can be found at http://github.com/IFL-CAMP/pose_regularization.
Wissenschaftlicher Artikel
Scientific Article
Böttcher, A. ; Tritschler, S. ; Yang, K. ; Theis, F.J. ; Lickert, H. ; Wolf, E. ; Kemter, E.
Xenotransplantation 26 (2019)
Meeting abstract
Meeting abstract
Knauer-Arloth, J. ; Eraslan, G. ; Andlauer, T. ; Gieger, C. ; Gold, R. ; Heilmann-Heimbach, S. ; Kacprowski, T. ; Meitinger, T. ; Laudes, M. ; Luessi, F. ; Müller-Myhsok, B. ; Nischwitz, S. ; Peters, A. ; Paul, F. ; Rawal, R. ; Strauch, K. ; Wiendl, H. ; Hemmer, B. ; Theis, F.J. ; Binder, E. ; Müller, N.S.
Mult. Scler. J. 25, 906-907 (2019)
Meeting abstract
Meeting abstract
Gestaut, D. ; Roh, S.H. ; Ma, B. ; Pintile, G. ; Joachimiak, L. ; Leitner, A. ; Walzotheini, T. ; Aebersold, R. ; Chiu, W. ; Frydman, J.
Protein Sci. 28, 44-44 (2019)
Meeting abstract
Meeting abstract
Johnson, R.K. ; Vanderlinden, L. ; DeFelice, B.C. ; Kechris, K. ; Uusitalo, U. ; Fiehn, O. ; Sontag, M. ; Crume, T. ; Beyerlein, A. ; Lernmark, Å. ; Toppari, J. ; Ziegler, A.-G. ; She, J.X. ; Hagopian, W. ; Rewers, M. ; Akolkar, B. ; Krischer, J. ; Virtanen, S.M. ; Norris, J.M. ; Teddy Study Group
Sci. Rep. 9:14819 (2019)
The role of diet in type 1 diabetes development is poorly understood. Metabolites, which reflect dietary response, may help elucidate this role. We explored metabolomics and lipidomics differences between 352 cases of islet autoimmunity (IA) and controls in the TEDDY (The Environmental Determinants of Diabetes in theYoung) study. We created dietary patterns reflecting pre-IA metabolite differences between groups and examined their association with IA. Secondary outcomes included IA cases positive for multiple autoantibodies (mAb+). The association of 853 plasma metabolites with outcomes was tested at seroconversion to IA, just prior to seroconversion, and during infancy. Key compounds in enriched metabolite sets were used to create dietary patterns reflecting metabolite composition, which were then tested for association with outcomes in the nested case-control subset and the full TEDDY cohort. Unsaturated phosphatidylcholines, sphingomyelins, phosphatidylethanolamines, glucosylceramides, and phospholipid ethers in infancy were inversely associated with mAb+ risk, while dicarboxylic acids were associated with an increased risk. An infancy dietary pattern representing higher levels of unsaturated phosphatidylcholines and phospholipid ethers, and lower sphingomyelins was protective for mAb+ in the nested case-control study only. Characterization of this high-risk infant metabolomics profile may help shape the future of early diagnosis or prevention efforts.
Wissenschaftlicher Artikel
Scientific Article
Kimura, R.H. ; Wang, L. ; Shen, B. ; Huo, L. ; Tummers, W. ; Filipp, F.V. ; Guo, H.H. ; Haywood, T. ; Abou-Elkacem, L. ; Baratto, L. ; Habte, F. ; Devulapally, R. ; Witney, T.H. ; Cheng, Y. ; Tikole, S. ; Chakraborti, S. ; Nix, J. ; Bonagura, C.A. ; Hatami, N. ; Mooney, J.J. ; Desai, T. ; Turner, S. ; Gaster, R.S. ; Otte, A. ; Visser, B.C. ; Poultsides, G.A. ; Norton, J. ; Park, W. ; Stolowitz, M. ; Lau, K. ; Yang, E. ; Natarajan, A. ; Ilovich, O. ; Srinivas, S. ; Srinivasan, A. ; Paulmurugan, R. ; Willmann, J. ; Chin, F.T. ; Cheng, Z. ; Iagaru, A. ; Li, F. ; Gambhir, S.S.
Nat. Commun. 10:4673 (2019)
Advances in precision molecular imaging promise to transform our ability to detect, diagnose and treat disease. Here, we describe the engineering and validation of a new cystine knot peptide (knottin) that selectively recognizes human integrin αvβ6 with single-digit nanomolar affinity. We solve its 3D structure by NMR and x-ray crystallography and validate leads with 3 different radiolabels in pre-clinical models of cancer. We evaluate the lead tracer’s safety, biodistribution and pharmacokinetics in healthy human volunteers, and show its ability to detect multiple cancers (pancreatic, cervical and lung) in patients at two study locations. Additionally, we demonstrate that the knottin PET tracers can also detect fibrotic lung disease in idiopathic pulmonary fibrosis patients. Our results indicate that these cystine knot PET tracers may have potential utility in multiple disease states that are associated with upregulation of integrin αvβ6.
Wissenschaftlicher Artikel
Scientific Article
Waibel, D.J.E. ; Tiemann, U. ; Lupperger, V. ; Semb, H. ; Marr, C.
In:. 2019. 184-186 (Lect. Notes Comput. Sc. ; 11729 LNCS)
Fluorescent markers are commonly used to characterize single cells and to uncover molecular properties. Unfortunately, fluorescent staining is laborious and costly, it damages tissue and suffers from inconsistencies. Recently deep learning approaches have been successfully applied to predict fluorescent markers from bright-field images [1–3]. These approaches can save costs and time and speed up the classification of tissue properties. However, it is currently not clear how different image channels can be meaningfully combined to improve prediction accuracy. Thus, we investigated the benefits of multi channel input for predicting a specific transcription factor antibody staining. Our image dataset consists of three channels: bright-field, fluorescent GFP reporter and transcription factor antibody staining. Fluorescent GFP is constantly expressed in the genetically modified cells from a particular differentiation step onwards. The cells are additionally stained with a specific transcription factor antibody that marks a subtype of GFP positive cells. For data acquisition we used a Leica SP8 and a Zeiss LSM780 microscope with 20x objectives. We trained a deep neural network, a modified U-Net [4], to predict the transcription factor antibody staining from bright-field and GFP channels. To this end, we trained on 2432 three-dimensional images containing roughly 7600 single cells and compared the accuracy for prediction of the transcription factor antibody staining using bright-field only, GFP only, and both channels together on a test-set of 576 images with approximately 1800 single cells. The same training- and test-set was used for all experiments (Fig. 1). The prediction error, measured as the mean relative pixel-wise error over the test-set, was calculated to 61% for prediction from bright-field, 55% for prediction from GFP and 51% for prediction both bright-field and GFP images. The median pixel-wise Pearson correlation coefficient, increases from 0.12 for prediction from bright-field channels to 0.17 for prediction from GFP channels, to 0.31 for prediction from bright-field and GFP channels (Fig. 2). Our work demonstrates that prediction performance can be increased by combining multiple channels for in-silico prediction of stainings. We anticipate this research to be a starting point for further investigations on which stainings could be predicted from other stainings using deep learning. These approaches bear a huge potential in saving laborious and costly work for researchers and clinical technicians and could reveal biological relationships between fluorescent markers.
Schneider, M. ; Wang, L. ; Marr, C.
Lect. Notes Comput. Sc. 11728 LNCS, 673-686 (2019)
Most machine learning algorithms require that training data are identically distributed to ensure effective learning. In biological studies, however, even small variations in the experimental setup can lead to substantial deviations. Domain adaptation offers tools to deal with this problem. It is particularly useful for cases where only a small amount of training data is available in the domain of interest, while a large amount of training data is available in a different, but relevant domain. We investigated to what extent domain adaptation was able to improve prediction accuracy for complex biological data. To that end, we used simulated data and time-lapse movies of differentiating blood stem cells in different cell cycle stages from multiple experiments and compared three commonly used domain adaptation approaches. EasyAdapt, a simple technique of structured pooling of related data sets, was able to improve accuracy when classifying the simulated data and cell cycle stages from microscopic images. Meanwhile, the technique proved robust to the potential negative impact on the classification accuracy that is common in other techniques that build models with heterogeneous data. Despite its implementation simplicity, EasyAdapt consistently produced more accurate predictions compared to conventional techniques. Domain adaptation is therefore able to substantially reduce the amount of work required to create a large amount of annotated training data in the domain of interest necessary whenever the domain changes even a little, which is common not only in biological experiments, but universally exists in almost all data collection routines.
Wissenschaftlicher Artikel
Scientific Article
Keshava, N. ; Toh, T.S. ; Yuan, H. ; Yang, B. ; Menden, M. ; Wang, D.
NPJ Syst. Biol. Appl. 5:36 (2019)
Personalised medicine has predominantly focused on genetically altered cancer genes that stratify drug responses, but there is a need to objectively evaluate differential pharmacology patterns at a subpopulation level. Here, we introduce an approach based on unsupervised machine learning to compare the pharmacological response relationships between 327 pairs of cancer therapies. This approach integrated multiple measures of response to identify subpopulations that react differently to inhibitors of the same or different targets to understand mechanisms of resistance and pathway cross-talk. MEK, BRAF, and PI3K inhibitors were shown to be effective as combination therapies for particular BRAF mutant subpopulations. A systematic analysis of preclinical data for a failed phase III trial of selumetinib combined with docetaxel in lung cancer suggests potential indications in pancreatic and colorectal cancers with KRAS mutation. This data-informed study exemplifies a method for stratified medicine to identify novel cancer subpopulations, their genetic biomarkers, and effective drug combinations.
Wissenschaftlicher Artikel
Scientific Article
Schulte-Sasse, R. ; Budach, S. ; Hnisz, D. ; Marsico, A.
Lect. Notes Comput. Sc. 11731 LNCS, 658-668 (2019)
Despite the vast increase of high-throughput molecular data, the prediction of important disease genes and the underlying molecular mechanisms of multi-factorial diseases remains a challenging task. In this work we use a powerful deep learning classifier, based on Graph Convolutional Networks (GCNs) to tackle the task of cancer gene prediction across different cancer types. Compared to previous cancer gene prediction methods, our GCN-based model is able to combine several heterogeneous omics data types with a graph representation of the data into a single predictive model and learn abstract features from both data types. The graph formalizes relations between genes which work together in regulatory cellular pathways. GCNs outperform other state-of-the-art methods, such as network propagation algorithms and graph attention networks in the prediction of cancer genes. Furthermore, they demonstrate that including the interaction network topology greatly helps to characterize novel cancer genes, as well as entire disease modules. In this work, we go one step forward and enable the interpretation of our deep learning model to answer the following question: what is the molecular cause underlying the prediction of a disease genes and are there differences across samples?.
Wissenschaftlicher Artikel
Scientific Article
Tetko, I.V. ; Theis, F.J. ; Karpov, P. ; Kůrková, V.
Lect. Notes Comput. Sc. 11731 LNCS, v-vii (2019)
Editorial
Editorial
Mishra, M. ; Schmitt, S. ; Zischka, H. ; Strasser, M. ; Navab, N. ; Marr, C. ; Peng, T.
Lect. Notes Comput. Sc. 11731 LNCS, 289-298 (2019)
Mitochondria are the main source of cellular energy and thus essential for cell survival. Pathological conditions like cancer, can cause functional alterations and lead to mitochondrial dysfunction. Indeed, electron micrographs of mitochondria that are isolated from cancer cells show a different morphology as compared to mitochondria from healthy cells. However, the description of mitochondrial morphology and the classification of the respective samples are so far qualitative. Furthermore, large intra-class variability and impurities such as mitochondrial fragments and other organelles in the micrographs make a clear separation between healthy and cancerous samples challenging. In this study, we propose a deep-learning based model to quantitatively assess the status of each intact mitochondrion with a continuous score, which measures its closeness to the healthy/tumor classes based on its morphology. This allows us to describe the structural transition from healthy to cancerous mitochondria. Methodologically, we train two USK networks, one to segment individual mitochondria from an electron micrograph, and the other to softly classify each image pixel as belonging to (i) healthy mitochondrial, (ii) cancerous mitochondrial and (iii) non-mitochondrial (image background & impurities) tissue. Our combined model outperforms each network alone in both pixel classification and object segmentation. Moreover, our model can quantitatively assess the mitochondrial heterogeneity within and between healthy samples and different tumor types, hence providing insightful information of mitochondrial alterations in cancer development.
Wissenschaftlicher Artikel
Scientific Article
Rausch, L. ; Kranich, J. ; Chlis, N.-K. ; Schifferer, M. ; Simons, M. ; Theis, F.J. ; Brocker, T.
Eur. J. Immunol. 49, 88-88 (2019)
Meeting abstract
Meeting abstract
Musumeci, A. ; Lutz, K. ; Dursun, E. ; Sie, C. ; Ziegenhain, C. ; Bagnoli, J. ; Luecken, M. ; Korn, T. ; Enard, W. ; Theis, F.J. ; Krug, A.
Eur. J. Immunol. 49, 48-48 (2019)
Meeting abstract
Meeting abstract
Bakhti, M. ; Scheibner, K. ; Tritschler, S. ; Bastidas-Ponce, A. ; Tarquis-Medina, M. ; Theis, F.J. ; Lickert, H.
Mol. Metab. 30, 16-29 (2019)
Objective: Translation of basic research from bench-to-bedside relies on a better understanding of similarities and differences between mouse and human cell biology, tissue formation, and organogenesis. Thus, establishing ex vivo modeling systems of mouse and human pancreas development will help not only to understand evolutionary conserved mechanisms of differentiation and morphogenesis but also to understand pathomechanisms of disease and design strategies for tissue engineering.Methods: Here, we established a simple and reproducible Matrigel-based three-dimensional (3D) cyst culture model system of mouse and human pancreatic progenitors (PPs) to study pancreatic epithelialization and endocrinogenesis ex vivo. In addition, we reanalyzed previously reported single-cell RNA sequencing (scRNA-seq) of mouse and human pancreatic lineages to obtain a comprehensive picture of differential expression of key transcription factors (TFs), cell-cell adhesion molecules and cell polarity components in PPs during endocrinogenesis.Results: We generated mouse and human polarized pancreatic epithelial cysts derived from PPs. This system allowed to monitor establishment of pancreatic epithelial polarity and lumen formation in cellular and sub-cellular resolution in a dynamic time-resolved fashion. Furthermore, both mouse and human pancreatic cysts were able to differentiate towards the endocrine fate. This differentiation system together with scRNA-seq analysis revealed how apical-basal polarity and tight and adherens junctions change during endocrine differentiation.Conclusions: We have established a simple 3D pancreatic cyst culture system that allows to tempo-spatial resolve cellular and subcellular processes on the mechanistical level, which is otherwise not possible in vivo.
Wissenschaftlicher Artikel
Scientific Article
Kiefer, L. ; Weinmann, A.
Numer. Math. 143, 423-460 (2019)
Minimizing the Mumford-Shah functional is frequently used for smoothing signals or time series with discontinuities. A significant limitation of the standard Mumford-Shah model is that linear trends-and in general polynomial trends-in the data are not well preserved. This can be improved by building on splines of higher order which leads to higher order Mumford-Shah models. In this work, we study these models in the univariate situation: we discuss important differences to the first order Mumford-Shah model, and we obtain uniqueness results for their solutions. As a main contribution, we derive fast minimization algorithms for Mumford-Shah models of arbitrary orders. We show that the worst case complexity of all proposed schemes is quadratic in the length of the signal. Remarkably, they thus achieve the worst case complexity of the fastest solver for the piecewise constant Mumford-Shah model (which is the simplest model of the class). Further, we obtain stability results for the proposed algorithms. We complement these results with a numerical study. Our reference implementation processes signals with more than 10,000 elements in less than 1 s.
Wissenschaftlicher Artikel
Scientific Article
Thomas, J. ; Quaranta, M. ; Krause, L. ; Atenhan, A. ; Buters, J.T.M. ; Ohnmacht, C. ; de Jong, R.J. ; Schmidt-Weber, C.B. ; Eyerich, S.
Eur. J. Immunol. 49, 282-283 (2019)
Meeting abstract
Meeting abstract
Haimerl, P. ; Bernhard, U. ; Chaker, A.M. ; Zissler, U.M. ; Pastor, X. ; Cecil, A. ; Schindela, S. ; Prehn, C. ; Schmidt-Weber, C.B. ; Esser-von Bieren, J.
Eur. J. Immunol. 49, 200-200 (2019)
Meeting abstract
Meeting abstract
Tetko, I.V. ; Theis, F.J. ; Karpov, P. ; Kůrková, V.
Lect. Notes Comput. Sc. 11727 LNCS, v-vii (2019)
Editorial
Editorial
Tetko, I.V. ; Theis, F.J. ; Karpov, P. ; Kůrková, V.
Lect. Notes Comput. Sc. 11728 LNCS, v-vii (2019)
Editorial
Editorial
Tetko, I.V. ; Theis, F.J. ; Karpov, P. ; Kůrková, V.
Lect. Notes Comput. Sc. 11729 LNCS, v-vii (2019)
Editorial
Editorial
Vlot, A.H.C. ; Aniceto, N. ; Menden, M. ; Ulrich-Merzenich, G. ; Bender, A.
Drug Discov. Today 24, 2286-2298 (2019)
Synergistic drug combinations are commonly sought to overcome monotherapy resistance in cancer treatment. To identify such combinations, high-throughput cancer cell line combination screens are performed; and synergy is quantified using competing models based on fundamentally different assumptions. Here, we compare the behaviour of four synergy models, namely Loewe additivity, Bliss independence, highest single agent and zero interaction potency, using the Merck oncology combination screen. We evaluate agreements and disagreements between the models and investigate putative artefacts of each model's assumptions. Despite at least moderate concordance between scores (Pearson's r >0.32, Spearman's rho > 0.34), multiple instances of strong disagreement were observed. Those disagreements are driven by, among others, large differences in tested concentrations, maximum response values and median effective concentrations.
Review
Review
Miller, M. ; Sabrautzki, S. ; Beyerlein, A. ; Brielmeier, M.