Large uncertainty in individual polygenic risk score estimation impacts PRS-based risk stratification.

Abstract

While the cohort level accuracy of polygenic risk score has been widely assessed, uncertainty in PRS—estimates of genetic value at the individual level remains underexplored. Here we show that Bayesian PRS methods can estimate the variance of an individual’s PRS and can yield well-calibrated credible intervals with posterior sampling. For real traits in the UK Biobank (N=291,273 unrelated “white British”) we observe large variance in individual PRS estimates which impacts interpretation of PRS-based stratification; averaging across 13 traits, only 0.8% (s.d. 1.6%) of individuals with PRS point estimates in the top decile have their entire 95% credible intervals fully contained in the top decile. We provide an analytical estimator for expected individual PRS variance—a function of SNP-heritability, number of causal SNPs, and sample size. Our results showcase the importance of incorporating uncertainty in individual PRS estimates into subsequent analyses.