Genetic Clusters Linked to Type 2 Diabetes and Complications

A researcher from UMass Amherst co-leads global initiatives to comprehend the relationship between genetic variations and disease in order to create novel medications and therapies.

Genetic Clusters Linked to Type 2 Diabetes and Complications Revealed
Genetic epidemiologist Cassandra Spracklen is an Assistant Professor of Biostatistics and Epidemiology at the UMass Amherst School of Public Health and Health Sciences. Image Credit: UMass Amherst.

A team of international researchers, co-led by a genetic epidemiologist from the University of Massachusetts Amherst, has located 1,289 genetic markers associated with Type 2 diabetes (145 of which are newly identified) and generated risk scores for diabetes complications in the largest genome-wide association study on Type 2 diabetes to date.

Researchers employed state-of-the-art computational techniques to identify eight different mechanistic clusters of genetic variants linked to Type 2 diabetes.

Their findings, which were published in the journal Nature, provide new insights into the inheritability of the disease. Additionally, they found links between specific clusters and complications related to diabetes.

We tried to figure out some of the mechanisms for how these genetic variants are working – and we did.

Cassandra Spracklen, Co-Senior and First Author and Assistant Professor, Biostatistics and Epidemiology, School of Public Health and Health Sciences

The ultimate objective, according to the International Diabetes Federation, is to find possible genetic targets for the treatment or even a cure of the chronic metabolic disease that impacts and occasionally incapacitates over 400 million adults globally.

Around 428,452 of the more than 2.5 million people in the highly diverse group included in the study - which was the result of the recently established Type 2 Diabetes Global Genomics Initiative -have Type 2 diabetes.

We found eight clusters of Type 2 diabetes-associated variants that have also been associated with other diabetes risk factors – such as obesity and liver-lipid metabolism – suggesting the mechanisms for how the variants may be acting to cause diabetes. Then we asked if these clusters were also associated with Type 2 diabetes complications? And we found that several of them to also associated with vascular complications, such as coronary artery disease and end-stage diabetic nephropathy.”

Cassandra Spracklen, Co-Senior and First Author and Assistant Professor, Biostatistics and Epidemiology, School of Public Health and Health Sciences

For Type 2 diabetes, there are now effective treatments available, but there are still few options for personalized precision medicine. Treatment approaches still mostly depend on trial and error for a large number of patients. It will be possible to predict a person's risk of Type 2 diabetes and initiate early intervention if the disease mechanisms are better understood.

Spracklen says, “We’re trying to understand how diabetes develops.”

Spracklen added that the new research includes data from cohorts not available in an earlier genome-wide association study published in 2022 in Nature Genetics.

Spracklen says, “And we’re trying to better understand how these genetic variants are actually working within a biological tissue or at the cellular level, which can ultimately lead to new drug targets and treatments.”

Eleftheria Zeggini, a Professor at the Technical University of Munich and the Director of the Institute of Translational Genomics at Helmholtz Munich, is a senior corresponding author. Zeggini points out that a thorough understanding of genomic risk variants and the evaluation of large patient data depend on scientific collaboration.

The genetic information in our cells harbors secrets about the risks, progression, and complications of many diseases. Our work leads to an improved understanding of disease-causing biological mechanisms. Better knowledge of progression risk for Type 2 diabetes complications can help put in place early interventions to delay or even prevent these debilitating medical conditions.”

Eleftheria Zeggini, Professor, Study Senior Corresponding Author, and Director, Technical University of Munich, Institute of Translational Genomics, Helmholtz Munich

The paper concludes, “Our findings … may offer a route to optimize global access to genetically informed diabetes care.”

Journal reference:

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


The opinions expressed here are the views of the writer and do not necessarily reflect the views and opinions of AZoLifeSciences.
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