Evidence map›Paper›PMID 34589742›Full record

ArticleBrain, behavior, & immunity - health2021

Differentially expressed genes in Alzheimer's disease highlighting the roles of microglia genes including OLR1 and astrocyte gene CDK2AP1.

Qingqin S Li, Louis De Muynck

Open access · goldAbstract read
In one paragraph

Article in Brain, behavior, & immunity - health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
39citing papers in PubMed, 4 pooled it
10.7field-weighted citation impact, top 1% of its field
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

39 citing papers in PubMed, 4 syntheses or guidelines pooled it, 71 citations in OpenAlex.

  1. Pooled it
  2. Systematic review and meta-analysis of bulk RNAseq studies in human Alzheimer's disease brain tissue.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025
    Pooled it
  3. Pooled it
  4. Pooled it
  5. Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article
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

2 authors at 2 institutions in 2 countries.

Qingqin S LiNeuroscience Department, Janssen Research & Development, LLC, 1125 Trenton-Harbourton Road, Titusville, NJ, 08560, USA.
Louis De MuynckNeuroscience Department, Janssen Research & Development, a Division of Janssen Pharmaceutica NV, 2340, Beerse, Belgium.
Janssen (Belgium) · BEJanssen (United States) · US

Funding

Vascular Structure and Function in Cognitive AgingP01AG003949 · NIA · YESHIVA UNIVERSITY · PI Charles B Hall · 1985 to 2026
$73.9M
Alzheimer's Disease Genetics ConsortiumU01AG032984 · NIA · UNIVERSITY OF PENNSYLVANIA · PI SCHELLENBERG, GERARD DAVID · 2009 to 2024
$60.4M
SUPPLEMENT TO ALZHEIMERS DISEASE PATIENT REGISTRYU01AG006786 · NIA · MAYO CLINIC ROCHESTER · PI GRAFF-RADFORD, JONATHAN, JACK, CLIFFORD R. · 1986 to 2023
$49.6M
SUPPLEMENT TO RUSH ALZHEIMERS DISEASE CENTER COREP30AG010161 · NIA · RUSH UNIVERSITY MEDICAL CENTER · PI LEURGANS, SUE E. · 1991 to 2020
$49.1M
EPIDEMIOLOGY OF NEURAL RESERVE AND NEUROBIOLOGY IN AGINGR01AG017917 · NIA · RUSH UNIVERSITY MEDICAL CENTER · PI BENNETT, DAVID ALAN · 2001 to 2023
$43.3M
THE PGRN/TDP-43 AXIS IN ALZHEIMER?S DISEASE AND NEURODEGENERATIONP50AG016574 · NIA · MAYO CLINIC ROCHESTER · PI PETERSEN, RONALD C · 1999 to 2018
$36.9M
Research Education ComponentP30AG019610 · NIA · SUN HEALTH RESEARCH INSTITUTE · PI REIMAN, ERIC MICHAEL · 2001 to 2020
$32.5M
Integrating the exposome and methylome to inform brain molecular changes in ADRD across established diverse cohorts.U01AG046139 · NIA · UNIVERSITY OF FLORIDA · PI ERTEKIN-TANER, NILUFER, FUNK, CORY · 2013 to 2022
$24.6M
RISK FACTORS, PATHOLOGY, AND CLINICAL EXPRESSIONS OF ADR01AG015819 · NIA · RUSH UNIVERSITY MEDICAL CENTER · PI BENNETT, DAVID ALAN · 1998 to 2024
$21.4M
Pathway discovery, validation and compound identification for Alzheimer's disease - SupplementU01AG046152 · NIA · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI BENNETT, DAVID ALAN, DE JAGER, PHILIP L · 2013 to 2017
$13.6M
TRANSGENIC MODELING OF TAUOPATHYP01AG017216 · NIA · MAYO CLINIC JACKSONVILLE · PI DICKSON, DENNIS WILLIAM · 1999 to 2011
$12.0M
PREDICTORS OF THE RATE OF COGNITIVE DECLINE IN ELDERLY SUBJECTSP50AG025711 · NIA · UNIVERSITY OF SOUTH FLORIDA · PI POTTER, HUNTINGTON · 2005 to 2010
$8.2M
NIA NIH HHS P01 AG003949NIA NIH HHS P01 AG017216NIA NIH HHS P30 AG010161NIA NIH HHS P30 AG019610NIA NIH HHS P50 AG016574NIA NIH HHS P50 AG025711NIA NIH HHS R01 AG015819NIA NIH HHS R01 AG017917NIA NIH HHS R01 AG018023NIA NIH HHS R01 AG030146NIA NIH HHS R01 AG032990NIA NIH HHS R01 AG036836NIA NIH HHS U01 AG006786NIA NIH HHS U01 AG032984NIA NIH HHS U01 AG046139NIA NIH HHS U01 AG046152NINDS NIH HHS R01 NS080820NINDS NIH HHS U24 NS072026
6 · The paper itself

Abstract

backgroundAlzheimer's disease (AD) is associated with abnormal tau and amyloid-β accumulation in the brain, leading to neurofibrillary tangles, neuropil threads and extracellular amyloid-β plaques. Treatment is limited to symptom management, a disease-modifying therapy is not available. To advance search of therapy approaches, there is a continued need to identify targets for disease intervention both by confirming existing hypotheses and generating new hypotheses.

methodsWe conducted a mRNA-seq study to identify genes associated with AD in post-mortem brain samples from the superior temporal gyrus (STG, n ​= ​76), and inferior frontal gyrus (IFG, n ​= ​65) brain regions. Differentially expressed genes (DEGs) were identified correcting for gender and surrogate variables to capture hidden variation not accounted for by pre-planned covariates. The results from this study were compared with the transcriptome studies from the Accelerated Medicine Partnership - Alzheimer's Disease (AMP-AD) initiative. Over-representation and gene set enrichment analysis (GSEA) was used to identify disease-associated pathways. Protein-protein interaction (PPI) and weighted gene co-expression network analysis (WGCNA) analyses were carried out and co-expressed gene modules and their hub genes were identified and associated with additional phenotypic traits of interest.

resultsSeveral hundred mRNAs were differentially expressed between AD cases and cognitively normal controls in the STG, while no and few transcripts met the same criteria (adjusted p less than 0.05 and fold change greater than 1.2) in the IFG. The findings were consistent at the gene set level with two out of three cohorts from AMP-AD. PPI analysis suggested that the DEGs were enriched in protein-protein interactions than expected by random chance. Over-representation and GSEA analysis suggested genes playing roles in neuroinflammation, amyloid-β, autophagy and trafficking being important for the AD disease process. At the gene level, 10 genes from the STG that were consistently differentially expressed in this study and in the MSBB study (one of the three cohorts within the AMP-AD initiative) were enriched in microglial genes (TREM2, C3AR1, ITGAX, OLR1, CD74, and HLA-DRA), but also included genes with a broader cell type expression pattern such as CDK2AP1. Among the DEGs with supporting evidence from an independent study, CDK2AP1 (most abundantly expressed in astrocyte) was the transcript with strongest association with antemortem cognitive measure (last Mini-Mental State Examination score) and neurofibril tangle burden but also associated with amyloid plaque burden, while OLR1 was the transcript with strongest association with amyloid plaque burden. GSEA and over-representation analyses revealed gene sets related to immune processes including neutrophil degranulation, interleukin 10 signaling, and interferon gamma signaling, complement and coagulation cascades, phosphatidylinositol signaling system, phagosome and neurotransmitter receptors and postsynaptic signal transmission were enriched from this study and replicated in an independent study.

conclusionThis study identified differential gene sets, common with two out of three AMP-AD cohorts (ROSMAP and MSBB) and highlights microglia and astrocyte as the key cell-types with DGEs associated with AD clinical diagnosis, and/or antemortem cognitive measure as well as neuropathological indices. Future meta-analysis and causal inferential analysis will be helpful in pinpointing the most relevant pathways and genes to intervene.

Indexed as

Alzheimer’s diseaseDifferentially expressed gene (DEG)IFGSTG

Identifiers

PMID34589742
PMCPMC8474442
OpenAlexW3131795490

What OpenQuestion 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 OpenQuestion graph.