Evidence map›Paper›PMID 40533815›Full record

ArticleAlzheimer's research & therapy2025

Proteome-wide association studies using summary pQTL data of brain, CSF, and plasma identify 30 risk genes of Alzheimer's disease dementia.

Tingyang Hu, Qiang Liu, Qile Dai, Aron S Buchman, David A Bennett, Shinya Tasaki, Yanling Wang, Nicholas T Seyfried, Philip L De Jager, Michael P Epstein and 1 more

Abstract read
In one paragraph

Article in Alzheimer's research & therapy, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors.

Tingyang Hu *Center for Computational and Quantitative Genetics, Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, 30322, USA.
Qiang Liu *Center for Computational and Quantitative Genetics, Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, 30322, USA.
Qile DaiCenter for Computational and Quantitative Genetics, Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, 30322, USA.
Aron S BuchmanRush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, 60612, USA.
David A BennettRush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, 60612, USA.
Shinya TasakiRush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, 60612, USA.
Yanling WangRush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, 60612, USA.
Nicholas T SeyfriedDepartment of Biochemistry, Emory University School of Medicine, Atlanta, GA, 30322, USA.
Philip L De JagerCenter for Translational and Computational Neuroimmunology, Department of Neurology and Taub Institute for Research On Alzheimer's Disease and the Aging Brain, Columbia University Irving Medical Center, New York, NY10032, USA.
Michael P EpsteinCenter for Computational and Quantitative Genetics, Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, 30322, USA.
Jingjing YangCenter for Computational and Quantitative Genetics, Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, 30322, USA. jingjing.yang@emory.edu.

Funding

SUPPLEMENT TO RUSH ALZHEIMERS DISEASE CENTER COREP30AG010161 · NIA · RUSH UNIVERSITY MEDICAL CENTER · PI BENNETT, DAVID ALAN · 1991 to 2020
$49.1M
Quantitative Genetic Models for Exploring Missing Heritability of Alzheimer's DiseaseRF1AG071170 · NIA · EMORY UNIVERSITY · PI CUTLER, DAVID JOSEPH, EPSTEIN, MICHAEL PHILIP · 2020 to 2020
$2.9M
Novel Bayesian statistical tools for integrating multi-omics data to help elucidate the genomic etiology of complex phenotypesR35GM138313 · NIGMS · EMORY UNIVERSITY · PI YANG, JINGJING · 2020 to 2024
$1.9M
NIA NIH HHS AG071170NIA NIH HHS P30 AG010161NIA NIH HHS RF1 AG071170NIGMS NIH HHS R35 GM138313NIGMS NIH HHS R35GM138313NIH HHS P30AG10161
6 · The paper itself

Abstract

backgroundA proteome-wide association study (PWAS) that integrates proteomic data with genome-wide association study (GWAS) summary data is a powerful tool for studying Alzheimer's disease (AD) dementia. Existing PWAS analyses of AD often rely on the availability of individual-level proteomic and genetic data of a reference panel. Leveraging summary protein quantitative trait loci (pQTL) reference data of multiple AD-relevant tissues is expected to improve PWAS findings of AD dementia.

methodsWe conducted PWAS by integrating publicly available summary pQTL data of three tissues including brain, cerebrospinal fluid (CSF), and plasma, with the latest GWAS summary data of AD dementia. For each target protein per tissue, we employed our recently published OTTERS tool to obtain omnibus PWAS p-value, testing whether the genetically regulated protein abundance in the corresponding tissue is associated with AD dementia. Protein-protein interactions and enriched pathways of identified significant PWAS risk genes were analyzed by STRING. The potential causal effects of these PWAS risk genes were assessed by probabilistic Mendelian Randomization analyses.

resultsWe identified 30 unique significant PWAS risk genes for AD dementia, including 11 for brain, 10 for CSF, and 16 for plasma tissues. Five of these were shared by at least two tissues, and gene MAPK3 was found in all three tissues. We found that 11 of these PWAS risk genes were associated with AD dementia or AD pathology traits in GWAS Catalog; 18 of these were detected by transcriptome-wide association studies (TWAS) in dorsolateral prefrontal cortex brain tissue; and 25 of these, including 8 out of 9 novel genes, were interconnected within a protein-protein interaction network involving the well-known AD risk gene APOE. These PWAS risk genes were enriched in immune response, glial cell proliferation, and high-density lipoprotein particle clearance pathways. Mediated causal effects were validated for 13 PWAS risk genes (43.3%).

conclusionsOur findings provide novel insights into the genetic mechanisms of AD dementia in brain, CSF, and plasma, and provide targets for developing new therapies. This study also demonstrates the effectiveness of integrating summary pQTL and GWAS data for mapping risk genes of complex human diseases.

Indexed as

Alzheimer DiseaseBrainProteomeQuantitative Trait LociGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansProteomicsProteomeAD dementiaAlzheimer’s diseaseGWASOTTERSpQTLPWASTWAS

Identifiers

PMID40533815
PMCPMC12175411

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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 Socratic graph.