Network Analyses of Differentially Expressed Genes in Osteoarthritis to Identify Hub Genes

利用网络分析骨关节炎中差异表达基因来识别枢纽基因

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作者:Zhaoyan Li,Lei Zhong,Zhenwu Du,Gaoyang Chen,Jing Shang,Qiwei Yang,Qingyu Wang,Yang Song,Guizhen Zhang

Abstract

Background: Osteoarthritis (OA) is the most common degenerative disease in orthopedics. However, the cause and underlying molecular mechanisms are not clear. This study aims to identify the hub genes and pathways involved in the occurrence of osteoarthritis. Methods: The raw data of GSE89408 were downloaded from the Gene Expression Omnibus (GEO) database, and the differentially expressed genes (DEGs) were identified by R software. The DAVID database was used for pathway and gene ontology analysis, and p<0.05 and gene count >2 were set as the cut-off point. Moreover, protein-protein interaction (PPI) network construction was applied for exploring the hub genes in osteoarthritis. The expression levels of the top ten hub genes in knee osteoarthritis synovial membranes and controls were detected by quantitative real-time PCR system. Results: A total of 229 DEGs were identified in osteoarthritis synovial membranes compared with normal synovial membranes, including 145 upregulated and 84 downregulated differentially expressed genes. The KEGG pathway analysis results showed that up-DEGs were enriched in proteoglycans in cytokine-cytokine receptor interaction, chemokine signaling pathway, rheumatoid arthritis, and TNF signaling pathway, whereas down-DEGs were enriched in the PPAR signaling pathway and AMPK signaling pathway. The qRT-PCR results showed that the expression levels of ADIPOQ, IL6, and CXCR1 in the synovium of osteoarthritis were significantly increased (p <0.05).

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