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Cited by 22Alzheimer's disease research and treatmentsDementia and Cognitive Impairment ResearchBioinformatics and Genomic Networks

Artificial intelligence-driven meta-analysis of brain gene expression identifies novel gene candidates and a role for mitochondria in Alzheimer’s disease

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Finney, Caitlin A., Delerue, Fabien, Gold, Wendy A., Brown, David A., Shvetcov, Artur·2023·Computational and Structural Biotechnology Journal
DOI 10.1016/j.csbj.2022.12.018PMC PMC9798142

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Abstract

Alzheimer's disease (AD) is the most common form of dementia. There is no treatment and AD models have focused on a small subset of genes identified in familial AD. Microarray studies have identified thousands of dysregulated genes in the brains of patients with AD yet identifying the best gene candidates to both model and treat AD remains a challenge. We performed a meta-analysis of microarray data from the frontal cortex (n = 697) and cerebellum (n = 230) of AD patients and healthy controls. A two-stage artificial intelligence approach, with both unsupervised and supervised machine learning, combined with a functional network analysis was used to identify functionally connected and biologically relevant novel gene candidates in AD. We found that in the frontal cortex, genes involved in mitochondrial energy, ATP, and oxidative phosphorylation, were the most significant dysregulated genes. In the cerebellum, dysregulated genes were involved in mitochondrial cellular biosynthesis (mitochondrial ribosomes). Although there was little overlap between dysregulated genes between the frontal cortex and cerebellum, machine learning models comprised of this overlap. A further functional network analysis of these genes identified that two downregulated genes, ATP5L and ATP5H, which both encode subunits of ATP synthase (mitochondrial complex V) may play a role in AD. Combined, our results suggest that mitochondrial dysfunction, particularly a deficit in energy homeostasis, may play an important role in AD.

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Cited by

Sorted by citations

Authors
Finney, C. A., Delerue, F., Gold, W. A., Brown, D. A., & Shvetcov, A.
Affiliations
  • The University of Sydney (AU)
  • Macquarie University (AU)
  • Black Dog Institute (AU)
Corresponding author
  • Finney, Caitlin A.
  • Shvetcov, Artur
ORCID
Venue
Computational and Structural Biotechnology Journal
Publisher
American Association for the Advancement of Science (AAAS)
Published
2022-12-21
Volume
21
Pages
388-400
ISSN
2001-0370 (ISSN-L)
DOI
10.1016/j.csbj.2022.12.018
PMC
PMC9798142
OpenAlex
W4311512487
Cited by
22
References
9
Citations by year
2026: 3 · 2025: 3 · 2024: 9 · 2023: 4 · 2022: 3
FWCI
0.65
Type
journal article
Language
en
Open access
Licence
Locations
  • Computational and Structural Biotechnology Journal (publishedVersion, cc-by-nc-nd)
  • medRxiv (acceptedVersion)
  • PubMed Central (publishedVersion, cc-by-nc-nd)
  • PubMed (publishedVersion)
  • Digital Commons-TMC (Texas Medical Center) (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
Macquarie University (5224420)
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, brain gene expression, mitochondrial dysfunction, oxidative phosphorylation, ATP synthase, frontal cortex, cerebellum, dysregulated genes, candidate genes, functional network analysis

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