Journal of Shandong University (Health Sciences) ›› 2021, Vol. 59 ›› Issue (3): 10-17.doi: 10.6040/j.issn.1671-7554.0.2020.1075

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Bioinformatic analysis of genes and molecular pathways associated with osteoarthritis synovitis

HUA Fang1,2, ZHANG Weiwei1,2, LYU Bo1,2, XIN Wei1,2   

  1. 1. Department of Clinical Laboratory;
    2. Department of Central Laboratory, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan 250021, Shandong, China
  • Published:2021-04-06

Abstract: Objective To identify the differentially expressed genes(DEGs)associated with the progression of osteoarthritis synovitis by bioinformatic analysis. Methods The gene expression profiles of GSE55457, GSE55235 and GSE12021 were downloaded from the Gene Expression Omnibus(GEO)to screen related genes in the pathogenesis of osteoarthritis. After the DEGs were identified, heatmaps were drawn, and functional enrichment of GO and KEGG was analyzed. The protein-protein interaction network(PPI)was constructed with STRING and Cytoscape, top module was screened with MCODE plug-in unit, and hub genes were screened with cytoHubba plug-in unit. Results There were 72 upregulated genes and 151 downregulated genes in the GSE55457, GSE55235 and GSE12021 gene expression profiles. GO analysis showed DEGs were involved in leukocyte migration, response to glucocorticoid, glycosaminoglycan binding, endoplasmic reticulum lumen, and nuclear outer membrane. KEGG analysis revealed DEGs were involved in MAPK signaling pathway, osteoclast differentiation and TNF signaling pathway. The cytoHubba screened out 10 key genes, including IL6, TLR7, SELE, VEGFA, LDLR, JUN, MYC, CD44, SNAI1 and hnRNA1. Conclusion Bioinformatic analysis can help to discover the molecular mechanism and key genes of synovitis in patients with osteoarthritis.

Key words: Osteoarthritis, Bioinformatics, Differentially expressed genes

CLC Number: 

  • R684.3
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