Polygenic Risk Scores for Incident Dementia in the Multi‐Ethnic Study of Atherosclerosis

ABSTRACT

Over 75 Alzheimer's disease (AD) and dementia‐associated variants have been identified through genome‐wide association studies, but the utility of polygenic risk scores (PRS) for predicting AD and dementia in diverse and admixed populations remains unclear. We compared how PRS approaches differing in p ‐value thresholds, variant weights, and source ancestry perform in predicting dementia in 6338 African American, Chinese, Hispanic, and White individuals from the Multi‐Ethnic Study of Atherosclerosis. We tested clumping and thresholding (C+T) methods with varying parameters against Bayesian approaches (PRS‐CS, PRS‐CSx). We compared the ability of each method to predict incident dementia in all participants and in groups stratified by self‐reported race/ethnicity. We additionally analyzed performance across groups stratified by estimated proportion of non‐Finnish European (NFE)‐like ancestry. Including more variants does not improve performance. We found comparable associations between dementia and PRS when comparing a C+T method with only 15 SNPs and PRS derived from Bayesian models that include > 800,000 SNPs (HR _5e‐08 = 1.18, 95% CI: 1.08–1.28; HR _CSx = 1.17, 95% CI: 1.07−1.27). The p  < 5e‐08 C+T method was more strongly associated with incident dementia in populations genetically dissimilar from the source data (HR _lowNFE _ _5e‐08 = 1.27, 95% CI: 1.08−1.50; HR _lowNFE _ _CSx = 1.12, 95% CI: 0.94−1.33). More selective PRS models using genome‐wide significant SNPs may be preferable for dementia prediction in diverse populations.