Evidence map›Paper›PMID 42331779›Full record

ArticleTranslational psychiatry2026

Immune cell-specific genetic architecture of Alzheimer's disease revealed by multi-omics analysis for therapeutic target discovery and prioritization.

Tian-Long Gao, Shan Geng, Jia Chen, Liu Yang, Yun-Juan Nie, Haitao Yu, Gao-Shang Chai

Abstract read
In one paragraph

Article in Translational psychiatry, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Tian-Long Gao *Department of Fundamental Medicine, Wuxi School of Medicine, Jiangnan University, Wuxi, Jiangsu, 214122, P. R. China.ORCID http://orcid.org/0009-0009-9909-7036
Shan Geng *Department of Fundamental Medicine, Wuxi School of Medicine, Jiangnan University, Wuxi, Jiangsu, 214122, P. R. China.
Jia ChenDepartment of Fundamental Medicine, Wuxi School of Medicine, Jiangnan University, Wuxi, Jiangsu, 214122, P. R. China.
Liu YangDepartment of Fundamental Medicine, Wuxi School of Medicine, Jiangnan University, Wuxi, Jiangsu, 214122, P. R. China.
Yun-Juan NieDepartment of Fundamental Medicine, Wuxi School of Medicine, Jiangnan University, Wuxi, Jiangsu, 214122, P. R. China.
Haitao YuDepartment of Fundamental Medicine, Wuxi School of Medicine, Jiangnan University, Wuxi, Jiangsu, 214122, P. R. China. yu_haitao@jiangnan.edu.cn.
Gao-Shang ChaiDepartment of Fundamental Medicine, Wuxi School of Medicine, Jiangnan University, Wuxi, Jiangsu, 214122, P. R. China. chaigaoshang@jiangnan.edu.cn.ORCID http://orcid.org/0000-0002-1943-3717

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Alzheimer's disease (AD) is a multifactorial neurodegenerative condition in which accumulating genetic and molecular evidence implicates dysregulation of peripheral immune processes in disease pathogenesis. Nevertheless, the contribution of distinct peripheral immune cell subsets and associated gene regulatory landscapes to AD risk remains incompletely defined. To address this gap, we integrated single-cell expression quantitative trait loci (sc‑eQTL) data from the OneK1K cohort with AD GWAS summary statistics. We systematically interrogated immune cell-specific genes for their contributions to AD risk by integrating genetic causal inference with Bayesian colocalization analyses, and identified 24 eGenes that passed both the MR significance threshold (P < 0.05) and the criterion for strong shared genetic signals (PP.H4 > 0.8). Notable candidates included GATS, HLA-DOB, HLA-DQA1, PM20D1, and others, with each gene demonstrating a cell-type-specific association restricted to its corresponding immune cell type, such as monocytes, CD8

Indexed as

Alzheimer DiseaseGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansMultiomicsQuantitative Trait Loci

Identifiers

PMID42331779
PMCPMC13538538

What OpenQuestion holds

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.