Screening for Differentially Expressed Circular RNAs in the Cartilage of Osteoarthritis Patients for Their Diagnostic Value

Osteoarthritis (OA) is the most prevalent osteoarticular disease, which typically involves chronic cartilage degeneration and synovitis. The latest research shows that circular RNAs (circRNAs) play a role in the development of a variety of diseases, including osteoarthrosis. The aim of this study was to explore the expression of circRNAs in OA chondrocytes and predict biomarkers for diagnosis. The circRNA expression profile was analyzed through use of the Gene Spring software V13.0; differentially expressed circRNAs were screened by comparing OA chondrocytes and normal articular chondrocytes. We validated the microarray data by quantitative real-time polymerase chain reaction analyses of OA chondrocytes and chondrocytes from normal controls. TargetScan software and miRanda software were used to predict networks of circRNA-miRNA interactions in cartilage. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene Ontology (GO) analyses were applied to predict the functions of differentially expressed circRNAs. Overall, 1380 circRNAs were differentially expressed between OA chondrocytes and normal articular chondrocytes (fold-change ≥2, p ≤ 0.05), including 215 that were upregulated and 1165 that were downregulated circRNAs. After analyzing the differentially expressed circRNA genes, the top 20 enriched GO entries and KEGG pathways were annotated. The hsa_circrna_0032131 was identified for further analysis. A circRNA-miRNA network was constructed to represent the 10 most likely target genes associated with the validated circRNA. Our research suggests that some of the differentially expressed circRNAs in OA chondrocytes compared to normal chondrocytes are etiologically associated with the pathological process of OA. It was found that hsa_circRNA_0032131 likely participates in the initiation and progression of OA and has potential as a diagnostic marker. To analyze the difference of circRNA expression profiles between OA and normal controls and explore biomarkers for diagnosis.