Improving genetic risk prediction for underrepresented groups

Improving PGS Prediction for Underrepresented Groups Through Transfer Learning

NIH-funded research Henry Ford Health + Michigan State University Health Sciences · NIH-10983102

This study is working to make genetic risk predictions more accurate for people from underrepresented backgrounds, like African Americans, so they can get better insights into their health risks based on their unique genetics.

Quick facts

Grant typeR01 grant
Study typeNIH-funded research
Funding institutionHenry Ford Health + Michigan State University Health Sciences NIH-funded
Lab location1 site (East Lansing, United States)
Project IDNIH-10983102 on NIH RePORTER

What this research studies

This research aims to enhance the accuracy of genetic risk predictions, known as Polygenic Scores (PGS), specifically for individuals from underrepresented ancestry groups, such as African Americans. By utilizing a technique called Transfer Learning, the researchers will develop new algorithms that leverage existing data to improve predictions for these populations. The study will involve creating and testing advanced statistical models that can better account for genetic variations in non-European individuals, ultimately aiming to provide more reliable health risk assessments. Patients may benefit from more accurate predictions of disease risk based on their genetic background.

Who could benefit from this research

Good fit: Ideal candidates for this research are individuals of African American descent who are interested in understanding their genetic risk for various diseases.

Not a fit: Patients of European descent may not receive direct benefits from this research as it focuses on improving predictions for underrepresented groups.

Why it matters

Potential benefit: If successful, this research could lead to more accurate health risk assessments for patients from underrepresented groups, improving personalized medicine.

How similar studies have performed: Other research has shown promise in using Transfer Learning to improve predictive models in genomics, indicating that this approach could be effective.

Where this research is happening

East Lansing, United States

Researchers

About this research

  1. This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
  2. Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
  3. For full project details, budget, and progress reports, visit the official NIH RePORTER page below.
Last reviewed 2026-06-09 by the Find a Trial editorial team. Information on this page is for educational purposes and is not medical advice. Always consult qualified healthcare professionals about clinical trial participation.