DNA Helix Lila Pink

What Our Genetic Information Tells Us About Type 2 Diabetes Risk and Complications

New Research Findings Diabetes Computational Health ITG

The genetic information in our cells harbors secrets about the risks, progression, and complications of many diseases. With hundreds of millions of patients worldwide, identifying and understanding genetic risk for type 2 diabetes is of particular interest. In collaboration with an international team of scientists, Prof. Eleftheria Zeggini from Helmholtz Munich and the Technical University of Munich (TUM) has conducted a comprehensive study with data from millions of individuals. Their research unveiled over 600 disease-associated genetic loci and generated risk scores for diabetes complications. The insights from the largest type 2 diabetes genome-wide association study to date are now published in Nature.

The prevalence of diabetes continues to increase significantly. According to the WHO, over 400 million people worldwide are living with type 2 diabetes (T2D), a disease with various symptoms and causes. Even though effective treatment options are becoming available, the option for precision medicine is still limited. For many patients, treatment strategies still rely on trial and error. Importantly, T2D can lead to numerous secondary health issues, and there is a critical need for a deeper comprehension of the disease mechanisms to predict the risk of T2D complications and intervene early.

Largest Study on Genetic Risk for Diabetes Now Published

Collaboration among scientists is essential for evaluating vast patient data and achieving a comprehensive understanding of genomic risk variants. Helmholtz Munich scientists are part of the newly formed Type 2 Diabetes Global Genomics Initiative (T2D-GGI). The first outcome of the initiative is the largest genome-wide association study (GWAS) to date. GWAS is a scientific method used to find genetic variation associated with a disease.

The new study encompasses over 2.5 million individuals (428,452 with T2D). Eleftheria Zeggini, senior corresponding author of the study, remarks: “We have carried out the largest genome-wide association study for type 2 diabetes as a collaborative achievement of hundreds of researchers from across the globe. We have found novel genetic risk loci for the disease and have constructed genetic risk scores that are associated with harmful complications.”

The authors used cutting-edge computational approaches to integrate data across multiple -omics modalities. They identified eight distinct mechanistic clusters of genetic variants associated with T2D and discovered associations between individual clusters and diabetes complications.

“Our work leads to an improved understanding of disease-causing biological mechanisms. Better knowledge of progression risk for T2D complications can help put in place early interventions to delay or even prevent these debilitating medical conditions,” says Eleftheria Zeggini.

Original publication

Suzuki et al. (2024): Genetic drivers of heterogeneity in type 2 diabetes pathophysiology. Nature. DOI: 10.1038/s41586-024-07019-6

About the scientists

Prof. Dr. Eleftheria Zeggini, Director at the Institute of Translational Genomics at Helmholtz Munich, Liesel Beckman Distinguished Professor of Translational Genomics at TUM

Eleftheria Zeggini Portrait
Eleftheria Zeggini

Director, Institute of Translational Genomics

View profile

Related news

Portrait Ele Zeggini

Awards & Grants, Computational Health, ITG,

Eleftheria Zeggini Appointed to ERC Scientific Council

The European Commission has appointed Prof. Eleftheria Zeggini, Director of the Institute of Translational Genomics at Helmholtz Munich, to the Scientific Council of the European Research Council (ERC). Alongside five newly selected members, she will…

["AdobeStock_TEelMh.jpg","AdobeStock_791921363.jpeg"]

New Research Findings, Computational Health, ING,

Restless Legs Syndrome: Genetic Discoveries Advance Treatment and Risk Prediction

Researchers at Helmholtz Munich and the Technical University of Munich (TUM) together with international collaborators have conducted the largest genetic investigation of the restless legs syndrome to date. Their findings, published in Nature…

HMGU_Icon_Computat_Health

Featured Publication, Computational Health, ITG,

Understanding Multimorbidity: The Link between Type 2 Diabetes and Osteoarthritis

The coexistence of multiple chronic diseases in a single individual, defined as multimorbidity, poses a significant challenge in healthcare as the global population ages. In a collaborative effort, researchers investigated the link between type 2…

Big genomic data visualization

Computational Health, ITG,

Big Data at Your Bedside

Analysis of genes can help in detecting diseases at an early stage as well as in determining new drug targets for therapy. Thanks to extremely powerful data processing, the field holds great promise for advancement. Helmholtz Munich is particularly…

Eleftheria Zeggini

Awards & Grants, Computational Health, ITG,

Eleftheria Zeggini Awarded EMBO Membership

Eleftheria Zeggini, founding director of the Institute of Translational Genomics at Helmholtz Zentrum München, has been elected a member of the European Molecular Biology Organization (EMBO). Today, EMBO announced the names of the international…