期刊
HUMAN MOLECULAR GENETICS
卷 29, 期 17, 页码 2899-2919出版社
OXFORD UNIV PRESS
DOI: 10.1093/hmg/ddaa182
关键词
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资金
- University of California Irvine startup funds
- American Federation of Aging Research (AFAR)
- National Institute on Aging [P30AG10161, R01AG15819, R01AG17917, R01AG30146, R01AG36836, U01AG3 2984, U01AG46152, AG016574, R01 AG032990, U01 AG046139, R01 AG018023, U01 AG006576, U01 AG006786, R01 AG025711, R01 AG017216, R01 AG003949, P30 AG19610]
- National Institute of Neurological Disorders and Stroke [R01 NS080820, U24 NS072026]
- Mayo Foundation
- Arizona Department of Health Services (Arizona Alzheimer's Research Center) [211002]
- Arizona Biomedical Research Commission [4001, 0011, 05-901, 1001]
- Michael J. Fox Foundation for Parkinson's Research
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).
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