ObjectiveTo study the differentially expressed genes (DEGs) between osteoarthritis (OA) patients and healthy control by bioinformatics, and to identify new targets for the diagnosis and treatment of OA. MethodsThe microarray datasets GSE55457, GSE55235 and GSE12021 were downloaded from the GEO database, and the DEGs of each dataset was screened by GEO2R online analysis tool and the intersection was found. The David online analysis tool was used for GO function enrichment and KEGG pathway enrichment analysis. Based on the information of STRING database, the protein-protein interaction (PPI) of DEGs was analyzed, and the PPI network was constructed by using Cytoscape software to find the hub genes. ResultsA total of 126 DEGs were screened. GO analysis showed that they were mainly involved in the biological processes, including cell response to corticotropin-releasing hormone stimulation, mRNA splicing through mRNA splicer, negative regulation of gene expression, positive regulation of monocyte aggregation and positive regulation of fibroblast proliferation, etc. KEGG was mainly enriched in MAPK, EB virus infection and human T-cell leukemia virus type Ⅰ infection, proteoglycan molecular in cancer, malignant tumor molecular, osteoclast differentiation factor, PI3K/Akt, insulin signal transduction, miRNAs in tumor, ErbB, HIF-1, bladder cancer signal pathways. Four core subnetworks were constructed by STRING and Cytoscape analysis, and 10 hub genes with the highest degree were found, including JUN, BTG2, ATF3, DUSP1, HNRNPA1, SF1, SRSF7, TRA2B, TRA2A, PPP1R15A. ConclusionJUN, BTG2, ATF3, DUSP1, HNRNPA1, SF1, SRSF7, TRA2B, TRA2A and PPP1R15A may be the new biomarkers in the pathogenesis of OA.

无