Multi-ancestry Transcriptome-Wide Association Study Reveals Shared and Population-Specific Genetic Effects in Alzheimer's Disease
Xinyu SuniD, Makaela MewsiD, Nicholas R. WheeleriD, Penelope H. BenchekiD, Tianjie GuiD, Lissette Gomez, Nicholas R. RayiD, Christiane ReitziD, Adam Christian NajiD, Jennifer Elizabeth BelowiD, Giuseppe TostoiD, Mario Cornejo‐OlivasiD, Goldie S. ByrdiD, Briseida E. Feliciano‐AstacioiD, Katrina Celis, Farid RajabliiD, Brian W. KunkleiD, Margaret Ann Pericak‐VanceiD, Jonathan L. HainesiD, Anthony J. GriswoldiD, William S. BushiD
Abstract
Alzheimers 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-seq and genotype data from NHW (n=235), African American (AA; n=224), and Hispanic (HISP; n=292) MAGENTA participants. Using 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 (FDR0.8), 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 GWAS index SNP rs6733839 (r2 {approx} 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.
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