Identification of pivotal genes and pathways in the synovial tissue of patients with rheumatoid arthritis and osteoarthritis through integrated bioinformatic analysis

Rheumatoid arthritis (RA) and osteoarthritis (OA) are the two most common debilitating joint disorders and although both share similar clinical manifestations, the pathogenesis of each is different and remains relatively unclear. The present study aimed to use bioinformatic analysis to identify pivotal genes and pathways involved in the pathogenesis of RA. Microarray datasets from patients with RA and OA were obtained from the Gene Expression Omnibus (GEO) database and differentially expressed genes (DEGs) were identified using GEO2R software; Gene Ontology analysis and pathway enrichment were analyzed using the Database for Annotation, Visualization and Integrated Discovery and the Kyoto Encylopedia for Genes and Genomes, respectively; and protein-protein interaction networks of DEGs were constructed using the Search Tool for the Retrieval of Interacting Genes database, and module analysis and pathway crosstalk of the PPI network was visualized using plugins of Cytoscape. In addition, the prediction of target mRNAs for differentially expressed microRNAs (DEMs) was performing using the starBase database and the identified pivotal genes were verified using reverse-transcription quantitative PCR in synovial tissue from patients with RA. A total of 566 DEGs were identified in GSE55457, GSE55235 while 23 DEMs were identified in the GSE72564 dataset. Upregulated DEGs were found to be mostly enriched in the 'Cytokine-cytokine receptor interaction' pathway, whereas downregulated DEGs were discovered to be enriched in the 'PPAR signaling pathway'. The top 25 DEGs were mostly enriched in the 'Chemokine signaling pathway'. In addition, six of the miRNA target genes were selected as potential biomarkers and a total of 24 genes were selected as potential hub genes. Experimental validation demonstrated that the expression levels of Cytotoxic T-Lymphocyte Associated Protein 4 (CTLA4), Zeta-chain-associated protein kinase 70 (ZAP70) and LCK proto-oncogene (LCK) were significantly increased, whereas HGF expression levels were decreased in RA synovial tissue. In conclusion, these findings suggest that the identified DEGs and pivotal genes in the present study may further enhance our knowledge of the underlying pathways in the pathogenesis of RA. These genes may also serve as diagnostic biomarkers and therapeutic targets for RA; however, further experimental validation is necessary following the bioinformatic analysis to determine our conclusions.