Browsing by Subject "Weighted gene co‐expression network analysis (WGCNA)"

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    Integrative analysis of DNA methylation and gene expression identifies genes associated with biological aging in Alzheimer's disease
    (Wiley, 2022-09-20) Kim, Bo-Hyun; Vasanthakumar, Aparna; Li, Qingqin S.; Nudelman, Kelly N.H.; Risacher, Shannon L.; Davis, Justin W.; Idler, Kenneth; Lee, Jong-Min; Seo, Sang Won; Waring, Jeffrey F.; Saykin, Andrew J.; Nho, Kwangsik; Alzheimer’s Disease Neuroimaging Initiative (ADNI); Radiology and Imaging Sciences, School of Medicine
    Introduction: The acceleration of biological aging is a risk factor for Alzheimer's disease (AD). Here, we performed weighted gene co-expression network analysis (WGCNA) to identify modules and dysregulated genes involved in biological aging in AD. Methods: We performed WGCNA to identify modules associated with biological clocks and hub genes of the module with the highest module significance. In addition, we performed differential expression analysis and association analysis with AD biomarkers. Results: WGCNA identified five modules associated with biological clocks, with the module designated as "purple" showing the strongest association. Functional enrichment analysis revealed that the purple module was related to cell migration and death. Ten genes were identified as hub genes in purple modules, of which CX3CR1 was downregulated in AD and low levels of CX3CR1 expression were associated with AD biomarkers. Conclusion: Network analysis identified genes associated with biological clocks, which suggests the genetic architecture underlying biological aging in AD. Highlights: Examine links between Alzheimer's disease (AD) peripheral transcriptome and biological aging changes. Weighted gene co-expression network analysis (WGCNA) found five modules related to biological aging. Among the hub genes of the module, CX3CR1 was downregulated in AD. The CX3CR1 expression level was associated with cognitive performance and brain atrophy.