Alzheimer's Polygenic Risk Scores Are Not Interchangeable: Evidence from 1,752 Models

Abstract

Introduction: Polygenic risk scores (PRS) may improve Alzheimer's disease (AD) risk prediction before symptom onset, yet choosing an appropriate model can be challenging. Methods: Using the standardized GenoPred pipeline, 1,752 PRS models (9 algorithms; 584 configurations; 3 genome-wide association studies) were evaluated and stratified by genetic ancestry and APOE diplotype. PRS models were evaluated using 11,200 clinical or autopsy-confirmed AD cases and 19,321 controls age >=65 from the Alzheimer's Disease Sequencing Project Release 5. Results: PRS results were not consistent across methodologies (Spearman's {rho}: -0.49 to 1), with >95% of individuals having PRS in both the top and bottom risk deciles. Top-performing PRS were effective at stratifying AD risk across ancestries (AFR: P=2.04x10^-26; AMR: P=4.57x10^-21; EAS: P=6.21x10^-40; EUR: P=7.90x10^-187). Discussion: PRS parameters should be optimized for each ancestry. Contradictory signals across methodologies underscore the need for carefully choosing suitable PRS methods and fine-tuning algorithmic parameters to ensure accuracy and consistency.