ArticleFrontiers in molecular neuroscience2023
Exploring molecular signatures related to the mechanism of aging in different brain regions by integrated bioinformatics.
Article in Frontiers in molecular neuroscience, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 6 citations in OpenAlex.
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- Age-dependent transcriptomic effects of morphine in the frontal cortex of female mice.Neuropharmacology · 2026Article
- Calorie Restriction Effects on Aging, Learning Performance, and Transcription in Aged Aplysia californica.Genes, brain, and behavior · 2026Article
- Identification and validation of key genes related to apoptosis in multiple organ dysfunction syndrome.European journal of medical research · 2025Article
- Mechanism of action and therapeutic potential of S100A8/A9 in neuroinflammation and cognitive impairment: From molecular target to clinical application (Review).International journal of molecular medicine · 2025Review
- Paracrine Bone-Derived Senescent Secretome Induces Spatially Patterned ECM and Biomechanical Vulnerability in Human Brain Organoids.bioRxiv : the preprint server for biology · 2025Article
- Sex as a Determinant of Age-Related Changes in the Brain.International journal of molecular sciences · 2024Review
Corrections and comments
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The mechanism of brain aging is not fully understood. Few studies have attempted to identify molecular changes using bioinformatics at the subregional level in the aging brain. This study aimed to identify the molecular signatures and key genes involved in aging, depending on the brain region. Differentially expressed genes (DEGs) associated with aging of the cerebral cortex (CX), hippocampus (HC), and cerebellum (CB) were identified based on five datasets from the Gene Expression Omnibus (GEO). The molecular signatures of aging were explored using functional and pathway analyses. Hub genes of each brain region were determined by protein-protein interaction network analysis, and commonly expressed DEGs (co-DEGs) were also found. Gene-microRNAs (miRNAs) and gene-disease interactions were constructed using online databases. The expression levels and regional specificity of the hub genes and co-DEGs were validated using animal experiments. In total, 32, 293, and 141 DEGs were identified in aging CX, HC, and CB, respectively. Enrichment analysis indicated molecular changes related to leukocyte invasion, abnormal neurotransmission, and impaired neurogenesis due to inflammation as the major signatures of the CX, HC, and CB. Itgax is a hub gene of cortical aging. Zfp51 and Zfp62 were identified as hub genes involved in hippocampal aging. Itgax and Cxcl10 were identified as hub genes involved in cerebellar aging. S100a8 was the only co-DEG in all three regions. In addition, a series of molecular changes associated with inflammation was observed in all three brain regions. Several miRNAs interact with hub genes and S100a8. The change in gene levels was further validated in an animal experiment. Only the upregulation of Zfp51 and Zfp62 was restricted to the HC. The molecular signatures of aging exhibit regional differences in the brain and seem to be closely related to neuroinflammation. Itgax, Zfp51, Zfp62, Cxcl10, and S100a8 may be key genes and potential targets for the prevention of brain aging.
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