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基于生物信息学的人类膝关节骨关节炎关键基因、信号通路及微小RNA的综合分析

Comprehensive Analysis of Key Genes, Signaling Pathways and miRNAs in Human Knee Osteoarthritis: Based on Bioinformatics.

作者信息

Chang Liang, Yao Hao, Yao Zhi, Ho Kevin Ki-Wai, Ong Michael Tim-Yun, Dai Bingyang, Tong Wenxue, Xu Jiankun, Qin Ling

机构信息

Musculoskeletal Research Laboratory, Department of Orthopedics and Traumatology, The Chinese University of Hong Kong, Hong Kong, Hong Kong, SAR China.

Innovative Orthopaedic Biomaterial and Drug Translational Research Laboratory, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, Hong Kong, SAR China.

出版信息

Front Pharmacol. 2021 Aug 23;12:730587. doi: 10.3389/fphar.2021.730587. eCollection 2021.

Abstract

Osteoarthritis (OA) is one of the main causes of disability in the elderly population, accompanied by a series of underlying pathologic changes, such as cartilage degradation, synovitis, subchondral bone sclerosis, and meniscus injury. The present study aimed to identify key genes, signaling pathways, and miRNAs in knee OA associated with the entire joint components, and to explain the potential mechanisms using computational analysis. The differentially expressed genes (DEGs) in cartilage, synovium, subchondral bone, and meniscus were identified using the Gene Expression Omnibus 2R (GEO2R) analysis based on dataset from GSE43923, GSE12021, GSE98918, and GSE51588, respectively and visualized in Volcano Plot. Venn diagram analyses were performed to identify the overlapping DEGs (overlapping DEGs) that expressed in at least two types of tissues mentioned above. Gene Ontology (GO) enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, protein-protein interaction (PPI) analysis, and module analysis were conducted. Furthermore, qRT-PCR was performed to validate above results using our clinical specimens. As a result, a total of 236 overlapping DEGs were identified, of which 160 were upregulated and 76 were downregulated. Through enrichment analysis and constructing the PPI network and miRNA-mRNA network, knee OA-related key genes, such as , , , , and were identified. Clinical validation by qRT-PCR experiments further supported above computational results. In addition, knee OA-related key miRNAs such as miR-101, miR-181a, miR-29, miR-9, and miR-221, and pathways such as Wnt signaling, HIF-1 signaling, PI3K-Akt signaling, and axon guidance pathways were also identified. Among above identified knee OA-related key genes, pathways and miRNAs, genes such as , , , , and , pathways like axon guidance, and miRNAs such as miR-17, miR-21, miR-155, miR-185, and miR-1 are lack of research and worthy for future investigation. The present informatic study for the first time provides insight to the potential therapeutic targets of knee OA by comprehensively analyzing the overlapping genes differentially expressed in multiple joint components and their relevant signaling pathways and interactive miRNAs.

摘要

骨关节炎(OA)是老年人群残疾的主要原因之一,伴有一系列潜在的病理变化,如软骨降解、滑膜炎、软骨下骨硬化和半月板损伤。本研究旨在识别与整个关节组件相关的膝骨关节炎中的关键基因、信号通路和微小RNA(miRNA),并通过计算分析解释其潜在机制。分别基于来自GSE43923、GSE12021、GSE98918和GSE51588的数据集,使用基因表达综合数据库2R(GEO2R)分析确定软骨、滑膜、软骨下骨和半月板中的差异表达基因(DEG),并在火山图中可视化。进行韦恩图分析以识别在上述至少两种组织中表达的重叠DEG(重叠差异表达基因)。进行基因本体(GO)富集分析、京都基因与基因组百科全书(KEGG)分析、蛋白质-蛋白质相互作用(PPI)分析和模块分析。此外,使用我们的临床标本进行qRT-PCR以验证上述结果。结果,共鉴定出236个重叠DEG,其中160个上调,76个下调。通过富集分析以及构建PPI网络和miRNA-mRNA网络,鉴定出与膝骨关节炎相关的关键基因,如……。qRT-PCR实验的临床验证进一步支持了上述计算结果。此外,还鉴定出与膝骨关节炎相关的关键miRNA,如miR-101、miR-181a、miR-29、miR-9和miR-221,以及Wnt信号通路、缺氧诱导因子-1(HIF-1)信号通路、磷脂酰肌醇-3激酶-蛋白激酶B(PI3K-Akt)信号通路和轴突导向通路等信号通路。在上述鉴定出的与膝骨关节炎相关的关键基因、信号通路和miRNA中,……等基因、轴突导向等信号通路以及miR-17、miR-21、miR-155、miR-185和miR-1等miRNA缺乏研究,值得未来进一步研究。本信息学研究首次通过全面分析在多个关节组件中差异表达的重叠基因及其相关信号通路和相互作用的miRNA,为膝骨关节炎的潜在治疗靶点提供了见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3c42/8419250/5a445b2a8abf/fphar-12-730587-g001.jpg

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