Multi-ancestry transcriptome-wide association study reveals shared and population-specific genetic effects in Alzheimer disease
Sun X, Mews M, Wheeler NR, Benchek P, Gu T, Gomez L, Ray N, Reitz C, Naj AC, Below JE, Tosto G, Cornejo-Olivas M, et al.. American Journal of Human Genetics, 2026-04-30
Topic: Amyloid, tau and blood-test diagnosis
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] 0.8), 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.
Key findings
- Overall, multi-population eQTL fine-mapping improves model interpretability and helps resolve shared and population-specific regulatory mechanisms relevant to AD.
Why it matters
This study combined genetic and gene activity data across White, African American, and Hispanic participants and prioritized nine genes, including known Alzheimer's loci BIN1, PTK2B, and DMPK. It shows that including multiple populations can improve the precision of genetic studies and help resolve shared and population-specific regulatory mechanisms.
New to this subject? Start with our plain-English guide: Genetics →
Study details
- Study designcross-sectional
- Participants751
- Evidence strengthEarly
Limitations
Whole blood may not reflect brain-specific regulation and brain eQTL data from diverse populations are scarce; GWAS sample sizes differ greatly between populations so significant signals were driven mainly by the non-Hispanic White group; multi-ancestry fine-mapping analyses only SNPs shared across populations, which can exclude ancestry-unique variants.
How this study scored 50/100
Published in a peer-reviewed journal, and it is a snapshot of people at one point in time. Scored zero for effect reported and randomised / blinded because the record does not state it. We have no data on free to read, so that was left out: it earned 49 of the 98 points we could judge it on, which is 50 out of 100.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (American Journal of Human Genetics) |
| Journal's citation record | 3 / 4 | The American Journal of Human Genetics: journal h-index 385 (OpenAlex, 2026-10-29) |
| Study design | 4 / 12 | A snapshot of people at one point in time |
| Strength of evidence | 2 / 5 | Rated “early” in our summary |
| Peer-review validation | 10 / 10 | Peer-reviewed. Published as an article in a named peer-reviewed journal. |
| How recent | 5 / 5 | 2026 — within 1 year(s) of the newest study here |
| Sample size | 2 / 4 | 751 participants |
| Effect reported | 0 / 3 | No effect size reported — scores zero (not stated in the record — scored 0) |
| Studied in people | 3 / 3 | Studied in people (participant count stated) |
| Randomised / blinded | 0 / 2 | No randomisation or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | 1 / 7 | Cited 1 times (OpenAlex, 2026-10-10) |
| Citations per year | 0 / 5 | 0.5 citations a year over 2 year(s) since 2026 |
| Impact for its field and year | 3 / 6 | Cited 4.0× the average for papers of its field and year (OpenAlex FWCI) |
| Cited by studies here | 0 / 6 | No other study in this library cites it |
| Still being cited | 0 / 4 | Cited 1 times in 2024–2026 (2026 still in progress; OpenAlex) |
| Senior author's track record | 3 / 4 | Last-listed author William S. Bush: h-index 50 (OpenAlex, whole career) |
| Institution's track record | 2 / 3 | University of Pennsylvania: institution h-index 1,859 (OpenAlex) |
| Multi-centre collaboration | 2 / 3 | OpenAlex lists 9 institution(s) in 3 countries |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 42066773) |
| Free to read | — / 2 | Access not recorded — left out of this score |
| Points | 49 / 98 | Scored on 19 of 20 parts. We have no data for the rest, so they are left out: 49 of the 98 points we could judge it on is 50 out of 100. |
| Total | 50 / 100 | — |
What each of these 20 components measures, and what this score is not →
Read the original
Full text: free to read — PubMed Central lists this copy as free to read: the link above (checked 10 Oct 2026).
Cite this study APA, Vancouver, BibTeX · download .bib or .ris
Built from the record alzhub holds for this paper, not looked up. Volume, issue and page numbers are not held in the record. The record's author list ends in “et al.”, so not every author is named. Check the citation against the original before you use it.
APA 7th
Sun, X., Mews, M., Wheeler, N. R., Benchek, P., Gu, T., Gomez, L., et al. (2026). Multi-ancestry transcriptome-wide association study reveals shared and population-specific genetic effects in Alzheimer disease. American Journal of Human Genetics. https://doi.org/10.1016/j.ajhg.2026.04.007
Vancouver
Sun X, Mews M, Wheeler NR, Benchek P, Gu T, Gomez L, et al. Multi-ancestry transcriptome-wide association study reveals shared and population-specific genetic effects in Alzheimer disease. American Journal of Human Genetics. 2026. doi:10.1016/j.ajhg.2026.04.007. PMID: 42066773.
BibTeX
@article{sun2026-42066773,
author = {Sun, X. and Mews, M. and Wheeler, N. R. and Benchek, P. and Gu, T. and Gomez, L. and Ray, N. and Reitz, C. and Naj, A. C. and Below, J. E. and Tosto, G. and Cornejo-Olivas, M. and others},
title = {{Multi-ancestry transcriptome-wide association study reveals shared and population-specific genetic effects in Alzheimer disease}},
journal = {American Journal of Human Genetics},
year = {2026},
doi = {10.1016/j.ajhg.2026.04.007},
pmid = {42066773},
url = {https://doi.org/10.1016/j.ajhg.2026.04.007}
}
Studies this one cites
Referenced by this study and also in the alzhub library, so you can read them here.