Wang Ying, Wu Cuiyan, Zhang Feng, Zhang Yanan, Ren Zhiwei, Lammi Mikko J, Guo Xiong
Department of Orthopedics, the First Affiliated Hospital of Xi'an Jiao Tong University, Xi'an, Shaanxi, People's Republic of China.
School of Public Health, Xi'an Jiaotong University Health Science Center, Key Laboratory of Trace Elements and Endemic Diseases, National Health and Family Planning Commission, Xi'an, Shaanxi, People's Republic of China.
Genet Test Mol Biomarkers. 2019 Oct;23(10):706-716. doi: 10.1089/gtmb.2019.0108. Epub 2019 Sep 9.
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, ≤ 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.
骨关节炎（OA）是最常见的骨关节疾病，通常涉及慢性软骨退变和滑膜炎。最新研究表明，环状RNA（circRNA）在包括骨关节炎在内的多种疾病的发生发展中发挥作用。本研究旨在探讨circRNA在OA软骨细胞中的表达情况，并预测诊断生物标志物。通过使用Gene Spring软件V13.0分析circRNA表达谱；通过比较OA软骨细胞和正常关节软骨细胞筛选差异表达的circRNA。我们通过对OA软骨细胞和正常对照软骨细胞进行定量实时聚合酶链反应分析来验证微阵列数据。使用TargetScan软件和miRanda软件预测软骨中circRNA-miRNA相互作用网络。应用京都基因与基因组百科全书（KEGG）通路和基因本体论（GO）分析来预测差异表达circRNA的功能。总体而言，OA软骨细胞和正常关节软骨细胞之间有1380个circRNA差异表达（倍数变化≥2，≤0.05），其中215个上调，1165个下调。在分析差异表达的circRNA基因后，注释了前20个富集的GO条目和KEGG通路。鉴定出hsa_circrna_0032131进行进一步分析。构建了一个circRNA-miRNA网络，以代表与验证的circRNA相关的10个最可能的靶基因。我们的研究表明，与正常软骨细胞相比，OA软骨细胞中一些差异表达的circRNA在病因上与OA的病理过程相关。发现hsa_circRNA_0032131可能参与OA的发生和发展，并有作为诊断标志物的潜力。分析OA与正常对照之间circRNA表达谱的差异，并探索诊断生物标志物。
