Abstract
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 elucidated.
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 research.
Keywords: Osteoarthritis, drugs, MicroRNA (miRNA), CircRNA, bioinformatics analysis, gene expression omnibus.
Related Journals
Current Computer-Aided Drug Design
48