Integrative genomics approach identifies conserved transcriptomic networks in Alzheimer's disease.
Adolescent
Adult
Aged
Aged, 80 and over
Aging
/ genetics
Alzheimer Disease
/ genetics
Brain
/ metabolism
Computational Biology
DNA Methylation
/ genetics
Gene Expression Profiling
Gene Regulatory Networks
/ genetics
Genome-Wide Association Study
Genomics
Humans
Microglia
/ metabolism
Middle Aged
Transcriptome
/ genetics
Young Adult
Journal
Human molecular genetics
ISSN: 1460-2083
Titre abrégé: Hum Mol Genet
Pays: England
ID NLM: 9208958
Informations de publication
Date de publication:
10 10 2020
10 10 2020
Historique:
received:
06
05
2020
revised:
10
07
2020
accepted:
27
07
2020
pubmed:
18
8
2020
medline:
25
8
2021
entrez:
18
8
2020
Statut:
ppublish
Résumé
Alzheimer's disease (AD) is a devastating neurological disorder characterized by changes in cell-type proportions and consequently marked alterations of the transcriptome. Here we use a data-driven systems biology meta-analytical approach across three human AD cohorts, encompassing six cortical brain regions, and integrate with multi-scale datasets comprising of DNA methylation, histone acetylation, transcriptome- and genome-wide association studies and quantitative trait loci to further characterize the genetic architecture of AD. We perform co-expression network analysis across more than 1200 human brain samples, identifying robust AD-associated dysregulation of the transcriptome, unaltered in normal human aging. We assess the cell-type specificity of AD gene co-expression changes and estimate cell-type proportion changes in human AD by integrating co-expression modules with single-cell transcriptome data generated from 27 321 nuclei from human postmortem prefrontal cortical tissue. We also show that genetic variants of AD are enriched in a microglial AD-associated module and identify key transcription factors regulating co-expressed modules. Additionally, we validate our results in multiple published human AD gene expression datasets, which can be easily accessed using our online resource (https://swaruplab.bio.uci.edu/consensusAD).
Identifiants
pubmed: 32803238
pii: 5892988
doi: 10.1093/hmg/ddaa182
pmc: PMC7566321
doi:
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
2899-2919Informations de copyright
© The Author(s) 2020. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
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