How human population mixing shaped our genes and health
Deciphering The Evolutionary and Biological Impact of Human Admixture
['FUNDING_OTHER'] · UNIVERSITY OF MICHIGAN AT ANN ARBOR · NIH-11182662
This project uses new computer methods to trace how mixing between human groups changed genes that affect health, especially in underrepresented ancestries like East Asian and South American populations.
Quick facts
| Phase | ['FUNDING_OTHER'] |
|---|---|
| Study type | Nih_funding |
| Sex | All |
| Sponsor | UNIVERSITY OF MICHIGAN AT ANN ARBOR (nih funded) |
| Locations | 1 site (ANN ARBOR, UNITED STATES) |
| Trial ID | NIH-11182662 on ClinicalTrials.gov |
What this research studies
Researchers will analyze DNA from diverse human populations using machine learning and population-genetics simulations to find traces of ancient and recent mixing events. They will search for evidence of archaic or 'ghost' hominin DNA in East Asian genomes and follow adaptive gene regions in South American groups to rebuild population histories. The team will also model how recent admixture influences complex traits by combining computational tools with available biobank and genetic data. The work aims to reduce gaps caused by underrepresentation of non-European populations so genetic findings are more relevant across ancestries.
Who could benefit from this research
Good fit: Ideal participants are people with admixed ancestry (for example, mixed East Asian or South American heritage) who are willing to share genetic information or join population-genetics studies.
Not a fit: People whose health concerns are unrelated to genetic variation or who are from ancestries already well represented in genetic databases may see little direct benefit.
Why it matters
Potential benefit: If successful, this work could make genetic risk predictions more accurate and equitable for people from admixed and underrepresented ancestries.
How similar studies have performed: Previous research has shown that archaic DNA and admixture can influence traits, but this project applies new machine-learning approaches and focuses on understudied populations, so parts are novel.
Where this research is happening
ANN ARBOR, UNITED STATES
- UNIVERSITY OF MICHIGAN AT ANN ARBOR — ANN ARBOR, UNITED STATES (ACTIVE)
Researchers
- Principal investigator: ZHANG, XINJUN — UNIVERSITY OF MICHIGAN AT ANN ARBOR
- Study coordinator: ZHANG, XINJUN
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.