Ancestry Calibration of Polygenic Risk Scores Improves Risk Stratification and Effect Estimation in African American Adults

基于祖源的基因风险评分校准可改善非裔美国成年人的风险分层和效应估计

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Abstract

Polygenic risk score (PRS) distributions vary across populations, complicating PRS risk assessment. We evaluated the impact of post-hoc PRS calibration according to individualized genetic ancestry estimates on PRS performance using two large multi-ethnic PRS for type 2 diabetes (T2D) (PRS(T2D)) and height (PRS(height)), in 8,841 African American (AA) individuals from the Reasons for Geographic and Racial Differences in Stroke (REGARDS) study. We calibrated each participant's score as a function of estimated genetic similarity to the Yoruba (GSYRI) cohort in the 1000 Genomes Project. Uncalibrated PRSs were significantly skewed by GSYRI. After calibration, 33.6% of individuals in the top decile of PRS(T2D) were reclassified and performance in the top PRS(T2D) decile improved from an OR of 7.97 [6.31-10.13] to 10.77 [8.41-13.91] when compared to the lowest decile. Similarly, 55.0% of individuals in the top PRS(height) decile were reclassified with GSYRI calibration. The calibrated PRS(height) showed higher correlation with height (from 0.24 to 0.32, p<10(-7)), and increased mean height in the top PRS(height) decile (p=5.7×10(-5)) when compared to the uncalibrated PRS(height). Lastly, we show that evaluating uncalibrated PRS while adjusting for GSYRI in regression models can lead to inflated and unstable effect size estimates for both the PRS and GSYRI.

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