Journal of Cellular Biochemistry · 2019 · 13 citations · 35 references
Life SciencesBioinformaticsMolecular BiologyGene ExpressionGenomicsNetwork BiologyDifferential Expression AnalysisDifferential Gene Expression AnalysisGene Coexpression NetworksGene Expression ProfilingSpinal Cord InjurySpinal Cord PathologyCoexpression ModulesCoexpression Network AnalysisGene Expression Network AnalysisHub Gene IdentificationModule DetectionNatural Killer Cell CytotoxicityProtein-protein Interaction Network AnalysisWeighted Gene Coexpression Network Analysis
Spinal cord injury (SCI) is characterized by dramatic neurons loss and axonal regeneration suppression. The underlying mechanism associated with SCI-induced immune suppression is still unclear. Weighted gene coexpression network analysis (WGCNA) is now widely applied for the identification of the coexpressed modules, hub genes, and pathways associated with clinic traits of diseases. We performed this study to identify hub genes associated with SCI development. Gene Expression Omnibus (GEO) data sets GSE45006 and GSE20907 were downloaded and the significant correlativity and connectivity between them were detected using WGCNA. Three significant consensus modules, including 567 eigengenes, were identified from the master GSE45006 data following the preconditions of approximate scale-free topology for WGCNA. Further bioinformatics analysis showed these eigengenes were involved in inflammatory and immune responses in SCI. Three hub genes Rac2, Itgb2, and Tyrobp and one pathway "natural killer cell-mediated cytotoxicity" were identified following short time-series expression miner, protein-protein interaction network, and functional enrichment analysis. Gradually upregulated expression patterns of Rac2, Itgb2, and Tyrobp genes at 0, 3, 7, and 14 days after SCI were confirmed based on GSE45006 and GSE20907 data set. Finally, we found that Rac2, Itgb2, and Tyrobp genes might take crucial roles in SCI development through the "natural killer cell-mediated cytotoxicity" pathway.
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