Screening of potential biomarkers of osteoarthritis: a bioinformatics analysis.

Background: Osteoarthritis (OA) is the most common joint disease worldwide, with an age-associated increasing in both incidence and prevalence. However, early diagnosis of OA is a challenge due to the lack of effective biomarkers. This study aimed to identify new biomarkers and mechanisms of OA.

Methods: Microarray expression data of synovial tissues from osteoarthritic and healthy populations were downloaded from the Gene Expression Omnibus (GEO) database, and differentially expressed genes (DEGs) were identified using GEO2R. Functions and enrichment pathways of DEGs were explained by enrichment analysis and construction of protein-protein interaction (PPI) networks, and hub genes were identified.

Results: By performing Venn analysis on the DEGs obtained from the two datasets, 28 upregulated and 84 downregulated DEGs were gained. JUN, activating transcription factor 3 (ATF3), and Dual-specificity phosphatase 1 (DUSP1), which play important roles in OA, were screened using PPI network construction. The receiver operating characteristic (ROC) curve of JUN, ATF3, and DUSP1 revealed satisfactory diagnostic value for OA. hsa-mir-26b-5p interacts with JUN, ATF3, and DUSP1.

Conclusion: The expression of JUN, ATF3, and DUSP1 was reduced in patients with OA and the three genes mentioned above could be used as potential markers for the diagnosis of OA. hsa-mir-26b-5p may play an important role in the pathogenesis of OA and may be a potential therapeutic target. Key Points • JUN, ATF3, and DUSP1 could be used as potential markers for the diagnosis of OA. • hsa-mir-26b-5p may play an important role in the pathogenesis of OA.