Identification and Validation of Pivotal Genes in Osteoarthritis Combined with WGCNA Analysis - Yang C; Chen X; Liu J; Wang W; Sun L; Xie Y; Chang Q (Journal of Inflammation Research)
Chengzhuo Yang,1,* Xinhua Chen,1,* Jin Liu,1 Wenhao Wang,1 Lihua Sun,2 Youhong Xie,1 Qing Chang1,* 1Department of The Affiliated Rehabilitation Hospital of Chongqing Medical University, Chongqing, People’s Republic of China; 2Department of Rehabilitation Medicine, The First Affiliated Hospital of Chongqing Medical University, Chongqing, People’s Republic of China*These authors contributed equally to this workCorrespondence: Youhong Xie; Qing Chang, Email 172763320@qq.com; 651733149@qq.comIntroduction: The prevalence of osteoarthritis (OA), the most common chronic joint condition, is increasing due to the aging population and escalating obesity rates, leading to a significant impact on human health and well-being. Thus, analyzing the key targets of OA through bioinformatics can help discover new biomarkers to improve its diagnosis.Methods: The microarray and RNA-seq results were screened from the Gene Expression Omnibus (GEO) database. Functional enrichment analyses, protein-protein interaction (PPI) analysis, and weighted gene co-expression network analysis (WGCNA) of the DEGs were performed. RT-qPCR and WB were further performed to verify the hub gene expression in OA rat.Results: In this study, 35 key genes were identified through differential expression analysis and weighted gene co-expression network analysis (WGCNA) using the GSE169077 and GSE114007 datasets. Enrichment analysis revealed that these key genes were predominantly enriched in the HIF-1 signaling pathway, ECM-receptor interaction, and FoxO signaling pathway. Through the integration of protein-protein interaction (PPI) analysis, validation in animal models and ROC curve analysis, four pivotal genes (GADD45B, CLDN5, HILPDA and CDKN1B) were finally identified.Conclusion: In conclusion, these identified key genes could serve as novel targets for predicting and treating OA, offering fresh insights into its etiology and pathogenesis.Keywords: osteoarthritis, bioinformatics analysis, WGCNA, GSE data