Ancestry Calibration of Polygenic Risk Scores Improves Risk Stratification and Effect Estimation in African American
Luciana B Vargas1, Mariah C Meyer1, Iain R Konigsberg1
1Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
Medrxiv : the Preprint Server for Health Sciences
|June 30, 2025
Summary
Calibrating polygenic risk scores (PRS) using genetic ancestry improves their accuracy for type 2 diabetes and height prediction in African Americans. This method enhances risk assessment by accounting for population-specific genetic variations.
Area of Science:
- Genetics
- Population Genetics
- Biostatistics
Background:
- Polygenic risk scores (PRS) exhibit varying distributions across diverse populations, posing challenges for accurate risk assessment.
- Genetic ancestry influences PRS performance, necessitating methods to account for population-specific genetic backgrounds.
Purpose of the Study:
- To evaluate the impact of post-hoc PRS calibration, based on individualized genetic ancestry estimates, on PRS performance.
- To assess the effectiveness of calibrating PRS for type 2 diabetes (PRS_T2D) and height (PRS_height) in African American individuals.
Main Methods:
- Utilized PRS_T2D and PRS_height in 8,841 African American participants from the REGARDS study.
- Calibrated PRS using genetic similarity to the Yoruba (GSYRI) cohort.
- Assessed changes in PRS performance and reclassification rates after calibration.
Main Results:
- Uncalibrated PRS showed significant skewness related to GSYRI.
- Calibration improved PRS_T2D performance, increasing the odds ratio (OR) from 7.97 to 10.77 in the top decile.
- Calibration enhanced PRS_height correlation with height (0.24 to 0.32) and increased mean height in the top decile.
- Found that uncalibrated PRS adjusted for GSYRI in regression models yields unstable effect size estimates.
Conclusions:
- Post-hoc PRS calibration by genetic ancestry significantly improves PRS performance in multi-ethnic cohorts.
- Calibration is crucial for accurate PRS risk assessment, particularly in ancestrally diverse populations.
- Adjusting for genetic ancestry without proper calibration can lead to biased results.
Keywords:
admixtureancestry calibrationgenetic similarityheightpolygenic risk scores (PRS)risk predictiontype 2 diabetesMore Related Videos
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