How human evolutionary history affects risk for conditions like adult-onset diabetes
Leveraging human evolutionary history to improve our understanding of complex disease architecture
Researchers will use large genetic and health-record datasets from diverse ancestry groups to make genetic risk predictions more accurate for people at risk of adult-onset diabetes.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Minnesota NIH-funded |
| Lab location | 1 site (Minneapolis, United States) |
| Project ID | NIH-11019675 on NIH RePORTER |
What this research studies
You should know this project looks at how population history—like ancestry mixing and family relatedness—changes what genetic tests tell us about disease risk. The team will run computer simulations and analyze large datasets (for example, UK Biobank and the Penn Medicine Biobank) to find and correct biases in common genetic risk methods. They will test whether mismatches between mitochondrial and nuclear DNA influence disease risk in African American patients and study how endogamy and consanguinity affect disease architecture in Pakistani groups. Most of the work uses existing genetic and electronic health record data rather than new clinical procedures.
Who could benefit from this research
Good fit: Adults with or at risk for adult-onset diabetes—particularly African American and South Asian/Pakistani ancestry individuals who can contribute genetic data and medical records—are the most relevant for these findings.
Not a fit: People whose ancestries are not represented in the analyzed datasets, those without genetic or medical-record data, and patients seeking immediate treatment changes are unlikely to see direct benefit soon.
Why it matters
Potential benefit: If successful, this work could make genetic risk scores more reliable for people from diverse ancestries, supporting better-targeted prevention or monitoring for diabetes.
How similar studies have performed: Previous research shows polygenic risk scores often work well in European ancestry groups but perform worse in other populations, so this project builds on known limitations while testing less-proven ideas like mito-nuclear mismatch.
Where this research is happening
Minneapolis, United States
- University of Minnesota — Minneapolis, United States (Active)
Researchers
- Principal investigator: Zaidi, Syed Arslan Abbas — University of Minnesota
- Study coordinator: Zaidi, Syed Arslan Abbas
About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page below.