Identification and experimental validation of hub genes underlying depressive-like behaviors induced by chronic social defeat stress - Chen, Yexiang; Jiang, Yunhao; Jiang, Xingcong; Zhai, Caiyu; Wang, Yifei; Xu, Chi (Frontiers in Pharmacology, 2024)
Major depressive disorder (MDD), marked by severe neuropsychiatric conditions and profound cognitive deficits, continues to pose both etiological and therapeutic challenges. Through transcriptomic profiling, biomarkers associated with MDD have been identified, enabling the prediction of clinical outcomes. This research sought to identify key diagnostic genes and explore their potential role in MDD. The Gene Expression Omnibus (GEO) repository was leveraged to obtain gene expression data related to MDD. Differentially expressed genes (DEGs) were discovered and analyzed for enrichment using Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Subsequently, the associated gene modules were analyzed through integrated weighted gene co-expression network analysis. The analysis revealed three key genes, namely AGA, FBXO38, and RGS5, through the application of the Least Absolute Shrinkage and Selection Operator (LASSO) approach, the Random Forest (RF) algorithm, and the Support Vector Machine with Recursive Feature Elimination (SVM-RFE) technique. Chronic social defeat stress (CSDS), which could effectively emulate depressive-like behavior was employed for depressive-like behavior model construction. AGA, FBXO38, and RGS5 genes in the dorsolateral prefrontal cortex (dlPFC) were detected by qPCR and Western bolt after CSDS, and the results were consistent with the analyses from the datasets (GSE53987 and GSE54568). Based on our research, AGA, FBXO38, and RGS5 are potential biomarkers for MDD, and these key genes could be advantageous for MDD risk prediction.