The University of Massachusetts Amherst

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Research

UMass Amherst Researchers Help Uncover Hidden Genetic Drivers of Diabetes

Study shows key Type 2 diabetes genes act outside blood, highlighting role of pancreas, liver and muscle

An international study co-led by researchers from the University of Massachusetts Amherst and Helmholtz Munich in Germany has uncovered hundreds of genes and proteins likely to play a causal role in Type 2 diabetes, many of which would have been missed by studies relying on blood samples alone.

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Cassandra Spracklen
Cassandra Spracklen

The study, published in Nature Metabolism, shows that the biological mechanisms underlying Type 2 diabetes are highly tissue-specific and that genetic diversity across populations is critical for identifying disease drivers.

The research team treated genetic data from more than 2.5 million people worldwide as a “natural experiment” to prioritize genes and proteins involved in Type 2 diabetes. Researchers compared results across seven diabetes-relevant tissues and four global ancestry groups, demonstrating that analyses limited to blood samples capture only a fraction of disease biology.

“We’ve known for some time now that tissue context is important to consider when trying to understand the mechanisms underlying the development of Type 2 diabetes,” says Cassandra Spracklen, associate professor of epidemiology at UMass Amherst and co-senior author of the paper. “But this work demonstrates just how important that context truly is.”

Blood is the most accessible tissue for many molecular studies, but Type 2 diabetes arises from a network of organs, including adipose (fatty) tissue, the liver, skeletal muscle and the insulin-producing cells of the pancreas. The analysis shows that attempts to explain disease mechanisms using blood data alone provide an incomplete picture.

Across seven tissues central to diabetes biology, the researchers identified causal evidence for 676 genes. Only 18% of genes with a causal effect in a primary diabetes tissue, such as the pancreas, also showed a corresponding signal in blood. Conversely, 85% of gene effects detected in diabetes-relevant tissues did not appear in blood. 

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Chi “Josh” Zhao
Chi “Josh” Zhao

“By revealing both shared and tissue-specific mechanisms, our findings move us closer to improving strategies for Type 2 diabetes prevention and treatments that may be more effective across global populations,” adds Chi “Josh” Zhao, a doctoral student in epidemiology at UMass Amherst and co-first author of the study.

The work builds on data from the Type 2 Diabetes Global Genomics Initiative, an international consortium that includes substantial representation from non-European populations. Using genome-wide association studies, the initiative has identified thousands of DNA variants linked to diabetes risk.

In the new analysis, researchers examined how these variants influence gene activity and protein levels across populations from Europe, Africa, the Americas and East Asia. The study focused on genetic variants located near genes that affect gene expression or protein abundance and tested more than 20,000 genes and 1,630 proteins.

The results provide strong evidence that genetically predicted levels of 335 genes and 46 proteins influence Type 2 diabetes risk. Some associations were consistent across ancestry groups, while others emerged only when data from historically underrepresented populations were included.

The findings lay out a roadmap for future research aimed at understanding the biological pathways underlying Type 2 diabetes and developing more effective treatments.

Related

cassandra spracklen

In the largest genome-wide association study to date on Type 2 diabetes, a team of international researchers, co-led by Cassandra Spracklen, has located 1,289 genetic markers associated with Type 2 diabetes and generated risk scores for diabetes complications. 

Elderly person wearing a smart watch while sleeping. Credit: Getty Images

The work by Joyita Dutta, supported by a $3.9 million grant from the National Institutes of Health, could serve as an "early warning system" for flagging at-risk individuals.