ArticleFrontiers in aging neuroscience2018
Gene Expression Analysis Reveals Novel Gene Signatures Between Young and Old Adults in Human Prefrontal Cortex.
Article in Frontiers in aging neuroscience, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed.
- Article
- Article
- Are Hippocampal Hypoperfusion and ATP Depletion Prime Movers in the Genesis of Alzheimer's Disease? A Review of Recent Pertinent Observations from Molecular Biology.International journal of molecular sciences · 2025Review
- Comparative transcriptomics identifies genes underlying growth performance of the Pacific black-lipped pearl oyster Pinctada margaritifera.BMC genomics · 2024Article
- Comprehensive transcriptome analysis reveals altered mRNA splicing and post-transcriptional changes in the aged mouse brain.Nucleic acids research · 2024Article
- Genome-wide transcriptome profiling and development of age prediction models in the human brain.Aging · 2024Article
- Identifying possible hub genes and biological mechanisms shared between bladder cancer and inflammatory bowel disease using machine learning and integrated bioinformatics.Journal of cancer research and clinical oncology · 2023Article
- Longitudinal APOE4- and amyloid-dependent changes in the blood transcriptome in cognitively intact older adults.Alzheimer's research & therapy · 2023Article
- Proteome-Wide Discovery of Cortical Proteins That May Provide Motor Resilience to Offset the Negative Effects of Pathologies in Older Adults.The journals of gerontology. Series A, Biological sciences and medical sciences · 2023Article
- Prioritization of risk genes for Alzheimer's disease: an analysis framework using spatial and temporal gene expression data in the human brain based on support vector machine.Frontiers in genetics · 2023Article
- Identification of key genes involved in secondary metabolite biosynthesis in Digitalis purpurea.PloS one · 2023Article
- Comprehensive analysis of omics data identifies relevant gene networks for Attention-Deficit/Hyperactivity Disorder (ADHD).Translational psychiatry · 2022Article
- Brain Epitranscriptomic Analysis Revealed Altered A-to-I RNA Editing in Septic Patients.Frontiers in genetics · 2022Article
- Identification of Five Hub Genes as Key Prognostic Biomarkers in Liver Cancer via Integrated Bioinformatics Analysis.Biology · 2021Article
- Article
- Gene Expression Analysis Reveals Age and Ethnicity Signatures Between Young and Old Adults in Human PBMC.Frontiers in aging · 2021Article
- Identification of differentially expressed genomic repeats in primary hepatocellular carcinoma and their potential links to biological processes and survival.Turkish journal of biology = Turk biyoloji dergisi · 2021Article
- Colorectal Cancer Prediction Based on Weighted Gene Co-Expression Network Analysis and Variational Auto-Encoder.Biomolecules · 2020Article
- Gene biomarker discovery at different stages of Alzheimer using gene co-expression network approach.Scientific reports · 2020Article
- Widespread Dysregulation of Long Noncoding Genes Associated With Fatty Acid Metabolism, Cell Division, and Immune Response Gene Networks in Xenobiotic-exposed Rat Liver.Toxicological sciences : an official journal of the Society of Toxicology · 2020Article
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Human neurons function over an entire lifetime, yet the molecular mechanisms which perform their functions and protecting against neurodegenerative disease during aging are still elusive. Here, we conducted a systematic study on the human brain aging by using the weighted gene correlation network analysis (WGCNA) method to identify meaningful modules or representative biomarkers for human brain aging. Significantly, 19 distinct gene modules were detected based on the dataset GSE53890; among them, six modules related to the feature of brain aging were highly preserved in diverse independent datasets. Interestingly, network feature analysis confirmed that the blue modules demonstrated a remarkably correlation with human brain aging progress. Besides, the top hub genes including PPP3CB, CAMSAP1, ACTR3B, and GNG3 were identified and characterized by high connectivity, module membership, or gene significance in the blue module. Furthermore, these genes were validated in mice of different ages. Mechanically, the potential regulators of blue module were investigated. These findings highlight an important role of the blue module and its affiliated genes in the control of normal brain aging, which may lead to potential therapeutic interventions for brain aging by targeting the hub genes.
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