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Cited by 74Alzheimer's disease research and treatmentsDementia and Cognitive Impairment ResearchBioinformatics and Genomic Networks

Integrative genomics approach identifies conserved transcriptomic networks in Alzheimer’s disease

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Morabito, Samuel, Miyoshi, Emily, Michael, Neethu, Swarup, Vivek·2020·Human Molecular Genetics
DOI 10.1093/hmg/ddaa182PMC PMC7566321

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Abstract

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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  • Elevated brain SPI1 transcript level is associated with Alzheimer's disease.

    “elevated brain SPI1 transcript level is associated with AD [8]”

    From Association of SPI1 haplotypes with altered SPI1 gene expression and Alzheimer’s disease risk (2022) · cites this paper as [8]

    The Results sections on glial co-expression changes and genetic risk report that an upregulated, AD-associated microglial module contains SPI1. They do not establish that SPI1 transcript levels themselves are elevated in AD brain tissue; a module-level association does not demonstrate the direction of change for every member gene. (LLM, conf=0.82)

    Experimental — accuracy not yet measured

  • The previous study performed consensus network analysis across the different brain regions.

    “The AMP-AD study from Wan et al.63 performed network analysis separately from each brain region, while, in our previous study,56 we performed consensus network analysis across the different brain regions.”

    From hdWGCNA identifies co-expression networks in high-dimensional transcriptomics data (2023) · cites this paper as [56]

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Cited by

Sorted by citations

Authors
Morabito, S., Miyoshi, E., Michael, N., & Swarup, V.
Affiliations
University of California, Irvine (US)
Corresponding author
Swarup, Vivek
ORCID
Venue
Human Molecular Genetics
Publisher
Oxford University Press (OUP)
Published
2020-08-17
Volume
29
Issue
17
Pages
2899-2919
ISSN
  • 0964-6906 (ISSN-L)
  • 1460-2083
DOI
10.1093/hmg/ddaa182
PMC
PMC7566321
OpenAlex
W3057137925
Cited by
74
References
29
Citations by year
2026: 9 · 2025: 9 · 2024: 14 · 2023: 12 · 2022: 13 · 2021: 14 · 2020: 3
FWCI
6.32
Type
journal article
Language
en
Open access
Licence
Locations
  • Human Molecular Genetics (publishedVersion, cc-by-nc)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
  • PubMed Central (publishedVersion, cc-by-nc)
  • PubMed (publishedVersion)
Funders
  • National Institute on Aging (P30AG10161, R01AG15819, R01AG17917, R01AG30146, R01AG36836, U01AG32984, U01AG46152, AG016574, R01 AG032990, U01 AG046139, R01 AG018023, U01 AG006576, U01 AG006786, R01 AG025711, R01 AG017216, R01 AG003949)
  • Illinois Department of Public Health
  • Translational Genomics Research Institute
  • National Institute of Neurological Disorders and Stroke (R01 NS080820, U24 NS072026)
Topics
  • Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
  • Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
Keywords
Alzheimer's disease, transcriptomic networks, gene co-expression, cell type proportions, microglia, prefrontal cortex, DNA methylation, histone acetylation, genetic architecture, transcription factors, single-cell transcriptomics, postmortem brain, quantitative trait loci, genome-wide association study
MeSH terms
Adolescent, Adult, Aged, Aged, 80 and over, Aging, Alzheimer Disease, Brain, Humans, Middle Aged, Microglia, DNA Methylation, Computational Biology, Gene Expression Profiling, Genomics, Gene Regulatory Networks, Genome-Wide Association Study, Young Adult, Transcriptome

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