Construction of a comprehensive protein-protein interaction network to identify key genes associated with osteoarthritis.

This research aims to identify key genes and therapeutic targets for osteoarthritis (OA) through bioinformatics, addressing the condition's significant impact on patients' lives and healthcare systems. Current treatments are often ineffective, underscoring the need for a deeper understanding of OA's molecular mechanisms. We investigate cell death mechanisms like pyroptosis and autophagy in OA, using gene expression omnibus datasets to identify differentially expressed genes and develop a protein-protein interaction network highlighting 7 critical genes, including gap junction alpha-1 protein (GJA1) as a potential biomarker. We also created a diagnostic model validated through receiver operating characteristic analysis, which could enhance OA detection and improve patient outcomes. Experimental results from quantitative real-time polymerase chain reaction confirmed the downregulation of GJA1 in the OA group. Significant downregulation of GJA1 expression in patients diagnosed with OA was confirmed. GJA1 may function as a novel regulatory factor in the onset and progression of OA, with potential applications as a diagnostic biomarker for the condition.