Background: Osteoarthritis (OA) is a kind of chronic disease relating to joints, which
seriously affectsthe daily life activities of the elderly and can also lead to disability. However, the
pathogenesis of OA is still unclear, which leads to limited treatment and the therapeutic effect far
from people's expectations. This study aims to filter out key genes in the pathogenesis of OA and
explore their potential role in the occurrence and development of OA.
Methods: The dataset of GSE117999 was obtained and analyzed in order to identify the
differentially expressed genes (DEGs), hub genes and key genes. We also identified potential
miRNAs which may play a major role in the pathogenesis of OA, and verified their difference in
OA by real-time quantitative PCR (RT-qPCR). DGldb was found to serve as an indicator to
identify drugs with potential therapeutic effects on key genes and Receiver Operating
Characteristic (ROC) analysis was used for identifying underlying biomarkers of OA.
Results: We identified ten key genes, including MDM2, RB1, EGFR, ESR1, UBE2E3, WWP1,
BCL2, OAS2, TYMS and MSH2. Then, we identified hsa-mir-3613-3p, hsa-mir-548e-5p and hsamir-
5692a to be potentially related to key genes. In addition, RT-qPCR confirmed the differential
expression of identified genes in mouse cartilage with or without OA. We then identified
Etoposide and Everolimus, which were potentially specific to the most key genes. Finally, we
speculated that ESR1 might be a potential biomarker of OA.
Conclusion: In this study, potential key genes related to OA and their biological functions were
identified, and their potential application value in the diagnosis and treatment of OA has been
demonstrated, which will help us to improve the therapeutic effect of OA.