Weighted gene co-expression network analysis reveals specific modules and hub genes related to immune infiltration of osteoarthritis

BACKGROUND: The incidence of osteoarthritis (OA), a chronic degenerative disease, is increasing every year. There is no effective clinical treatment for OA and the pathological mechanism remains unclear. Early diagnosis is an effective strategy to control the progress of OA. In this study, we aimed to identify potential early diagnostic biomarkers. METHODS: We downloaded the gene expression profile dataset, GSE51588 and GSE55235, from the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO) public database. The differentially expressed genes (DEGs) were screened out using the “limma” R package. Weighted gene co-expression network analysis (WGCNA) was utilized to build the co-expression network between the normal and OA samples. A Venn diagram was constructed to detect the hub genes. Potential molecular mechanisms and signaling pathways were enriched by gene set variation analysis (GSVA). Single sample gene set enrichment analysis (ssGSEA) was used to identify the immune infiltration of OA. RESULTS: We screened out three hub genes based on WGCNA and DEGs in this study. GSVA results showed that nuclear factor interleukin-3 (NFIL3) was related to tumor necrosis factor alpha (TNF-α) signaling via nuclear factor kappa-B (NF-κB), the reactive oxygen species pathway, and myelocytomatosis (MYC) targets v2. Highly-expressed ADM (adrenomedullin) pathways included TNF-α signaling via NF-κB, the reactive oxygen species pathway, and ultraviolet (UV) response up. OGN (osteoglycin)-enriched pathways included epithelial mesenchymal transition, coagulation, and peroxisome. CONCLUSIONS: We identified three hub genes (NFIL3, ADM, and OGN) that were correlated to the development and progression of OA, which may provide new biomarkers for early diagnosis.