Multi-ancestry transcriptome-wide association study reveals shared and population-specific genetic effects in Alzheimer disease

Alzheimer disease (AD) risk differs across ancestral populations, yet most genetic studies have focused on non-Hispanic White (NHW) cohorts. We conducted a multi-population transcriptome-wide association study (TWAS) using whole-blood RNA sequencing (RNA-seq) and genotype data from NHW ( n = 235), African American (AA; n = 224), and Hispanic (HISP; n = 292) Multi-Ancestry Genomics, Epigenomics, and Transcriptomics of Alzheimer’s (MAGENTA) participants. Using sum of shared single effects (SuShiE) for multi-population cis -eQTL fine-mapping, we identified credible sets for 8,748 genes, improving fine-mapping precision relative to analyses using fewer populations. cis -eQTL effects were largely shared across populations, with a subset showing population-specific regulation. We performed population-stratified TWAS of AD and inverse-variance-weighted meta-analysis, followed by gene-level TWAS fine-mapping (MA-FOCUS), prioritizing nine genes (false discovery rate [FDR] <0.05, posterior inclusion probability [PIP] >0.8), including established AD loci ( BIN1 , PTK2B , DMPK ) with broadly consistent effects across populations. At BIN1 , fine-mapped cis -eQTL variants used in the TWAS prediction model highlighted rs11682128, which is only modestly correlated with the genome-wide association study (GWAS) index SNP rs6733839 ( r ² ≈ 0.34), demonstrating how integrating eQTL fine-mapping with TWAS can refine signals beyond sentinel GWAS variants. We also identified an association between COG4 expression and AD in NHW, implicating Golgi-related pathways. Using independent SuShiE-derived models from TOPMed MESA (PBMC), several signals replicated directionally across ancestries, with the strongest statistical support in NHW. Overall, multi-population eQTL fine-mapping improves model interpretability and helps resolve shared and population-specific regulatory mechanisms relevant to AD.