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Osteoarthritis (OA) is one of the most prevalent causes of joint disease. However, the pathological mechanisms of OA have remained to be completely elucidated, and further investigation into the underlying mechanisms of OA development and the identification of novel therapeutic targets are urgently required. In the present study, the dataset GSE114007 was downloaded from the Gene Expression Omnibus database. Based on weighted gene co-expression network analysis (WGCNA) and the identification of differentially expressed genes (DEGs), the microarray data were further analyzed to identify hub genes, key transcription factors (TFs) and pivotal signaling pathways involved in the pathogenesis of OA. A total of 1,898 genes were identified to be differentially expressed between OA samples and normal samples. Based on WGCNA, the present study identified 5 hub modules closely associated with OA, and the potential key TFs for hub modules were further explored based on CisTargetX. The results demonstrated that B-Cell Lymphoma 6, Myelin Gene Expression Factor 2, Activating Transcription Factor 3, CCAAT Enhancer Binding Protein γ, Nuclear Factor Interleukin-3-Regulated, FOS Like Antigen-2, FOS-Like Antigen-1, Fos Proto-Oncogene, JunD Proto-Oncogene, Transcription Factor CP2 Like 1, RELA proto-oncogene NF-kB subunit, SRY-box transcription factor 3, V-Ets Avian Erythroblastosis Virus E26 Oncogene Homolog 2, Interferon Regulatory Factor 4 and REL proto-oncogene, NF-kB subunit were the potential key TFs. In addition, osteoclast differentiation, FoxO, MAPK and PI3K/Akt signaling pathways were revealed to be imperative for the pathogenesis of OA, as these 4 pivotal signaling pathways were observed to be tightly linked through 4 key TFs Fos Proto-Oncogene, JUN, JunD Proto-Oncogene and MYC, and 4 DEGs Vascular Endothelial Growth Factor A, Growth Arrest and DNA Damage Inducible α, Growth Arrest and DNA Damage Inducible β and Cyclin D1. The present study identified a set of potential key genes and signaling pathways, and provided an important opportunity to advance the current understanding of OA.

Identification of key gene modules and transcription factors for human osteoarthritis by weighted gene co‑expression network analysis