Impact of SNP Space on Polygenic Risk Modeling for Alzheimer’s Disease

Abstract

Background: Polygenic risk scores (PRS) are widely used to predict Alzheimer’s disease (AD) risk. Most models use millions of genome‐wide SNPs, including many in non‐coding regions. However, this can increase computational cost and reduce interpretability, with limited gains in predictive performance.