Background: Osteoarthritis (OA) is a degenerative joint disease that seriously affects
the quality of life of elderly. Regrettably, the pathological mechanism for OA has not yet been fully
Methods: This study is committed to distinguishing key genes and the underlying mechanisms for
OA. Raw data was acquired from the Gene Expression Omnibus (GEO) database. We identified differentially
expressed genes (DEGs), hub genes, and key genes through bioinformatics analysis.
Subsequently, we predicted the microRNAs (miRNAs) and circular RNAs (circRNAs) associated
with these key genes that may play key roles in OA using web tools. We also constructed a protein-
drug network and found potentially effective drugs by analyzing the relationships between the
drugs and the key genes.
Results: The analysis revealed 360 DEGs, 24 hub genes, and 15 key genes enriched in many categories
potentially related to the pathological mechanism of OA. hsa-miR-29a-3p, hsa-miR-29b-3p,
and hsa-miR-29c-3p were predicted to be important miRNAs for OA, while hsa_circ_0025119,
hsa_circ_0025113, hsa_circ_0009897, and hsa_circ_0002447 were predicted to be the most important
circRNAs. Further studies indicated that Ocriplasmin and Collagenase clostridium histolyticum
may be effective drugs for the treatment of OA. Finally, CD34 and VWF were inferred to
be the most meaningful biomarkers for OA.
Conclusion: In conclusion, we determined the underlying key genes, miRNAs, and circRNAs for
OA, predicted potentially effective drugs, and identified the most meaningful biomarkers for the
disease. Our findings may provide insight into the pathological mechanism of OA and guide future