Diabetes type 2: New biomarkers for patient classification and intervention prediction identified
Type 2 diabetes disease progression and successful intervention depend on individual’s unique clinical, genetic, genomic, and environmental information partly represented by gene expression patterns. An international team of researchers around Helmholtz Munich researchers Dominik Lutter and Susanna Hofmann investigated associations of muscle and intermuscular adipose tissue (IMAT) gene expression with insulin resistance and diabetes. In their study, they were able to identify novel potential biomarkers with potential for patient classification and prediction of intervention response. The results were now published in Diabetologia.
Insulin resistance often leads to type 2 diabetes mellitus. However, its early stages often remain undetected in patients. This reduces the likelihood of successful prevention and intervention. In addition, the effectiveness of treatment is influenced by the genetics of the individual patient. In a new study, researchers around Dominik Lutter from the Computational Discovery Research group at Institute for Diabetes and Obesity (IDO) at Helmholtz Munich and the German Center for Diabetes Research (DZD) and Susanna Hofmann from the Institute of Diabetes and Regeneration Research (IDR-H) at Helmholtz Munich and from the Ludwig Maximilians University (LMU), used gene expression profiles from a cross-sectional study to identify potential candidate genes for predicting diabetes risk and response to intervention.
Using a multivariate regression model – a statistical tool that uses multiple variables to forecast outcomes – the researchers linked gene expression profiles of human skeletal muscle and IMAT with insulin resistance and diabetes. Based on the expression patterns of key predictive genes, they characterized and compared individual gene expressions with clinical classifications. Thereby, the team could identify novel potential biomarkers with potential for patient classification.
The results of the study confirm that disease progression and a successful intervention depend on individual gene expression states. The new insights will lead to a better understanding and prediction of individual diabetes risk and help to develop individualized intervention strategies.
Original publication
Lutter et al. (2023) Skeletal muscle and intermuscular adipose tissue gene expression profiling identifies new biomarkers with prognostic significance for insulin resistance progression and intervention response. Diabetologia. Doi: https://doi.org/10.1007/s00125-023-05874-y
About the scientists
Dr. Dominik Lutter, Group leader at the Institute for Diabetes and Obesity (IDO) at Helmholtz Munich and the German Center for Diabetes Research (DZD).
Contact: dominik.lutter@helmholtz-muenchen.de
Prof. Susanna Hofmann, Head of the Independent Research Group “Women and Diabetes” at the Institute of Diabetes and Regeneration Research (IDR) at Helmholtz Munich and W2 Professor of Lipid Metabolism and Metabolic Diseases at the Medical Faculty of the Ludwig Maximilians University (LMU)
