Identification of key biomarkers and immune infiltration in the synovial tissue of osteoarthritis by bioinformatics analysis

• Published in: PeerJ (San Francisco, CA) Vol. 8; p. e8390
• Main Authors: Cai, Weisong, Li, Haohuan, Zhang, Yubiao, Han, Guangtao
• Format: Journal Article
• Language: English
• Published: United States PeerJ. Ltd 17.01.2020; PeerJ, Inc; PeerJ Inc
• Subjects: Algorithms; Antigens; Arthritis; B cells; Biochemistry; Bioinformatics; Bioinformatics analysis; Biological markers; Biomarkers; Bone growth; Cartilage diseases; CD4 antigen; Cell Biology; Chemotaxis; Computational biology; Cytokines; Degeneration; Dendritic cells; Gene expression; Genes; Genetics; Hyperplasia; Immune infiltration; Immunological memory; Immunoregulation; Interdisciplinary subjects; Interleukin 17; Joint diseases; Killer cells; Leukocytes (eosinophilic); Lymphocytes; Lymphocytes B; Lymphocytes T; Mast cells; Memory cells; Molecular Biology; Molecular modelling; Ontology; Orthopedics; Osteoarthritis; Polymerase chain reaction; Principal components analysis; Protein interaction; Protein-protein interactions; Rheumatoid arthritis; Rheumatoid factor; Signal transduction; Software; Stenosis; Synovial; Synovitis; T cells; Bioinformatics analysis; Synovial; Osteoarthritis; Immune infiltration
• ISSN: 2167-8359; 2167-8359
• DOI: 10.7717/peerj.8390

Osteoarthritis (OA) is the most common chronic degenerative joint disease and is mainly characterized by cartilage degeneration, subcartilage bone hyperplasia, osteophyte formation and joint space stenosis. Recent studies showed that synovitis might also be an important pathological change of OA. However, the molecular mechanisms of synovitis in OA are still not well understood. This study was designed to identify key biomarkers and immune infiltration in the synovial tissue of osteoarthritis by bioinformatics analysis. The gene expression profiles of GSE12021, GSE55235 and GSE55457 were downloaded from the GEO database. The differentially expressed genes (DEGs) were identified by the LIMMA package in Bioconductor, and functional enrichment analyses were performed. A protein-protein interaction network (PPI) was constructed, and module analysis was performed using STRING and Cytoscape. The CIBERSORT algorithm was used to analyze the immune infiltration of synovial tissue between OA and normal controls. A total of 106 differentially expressed genes, including 68 downregulated genes and 38 upregulated genes, were detected. The PPI network was assessed, and the most significant module containing 14 hub genes was identified. Gene Ontology analysis revealed that the hub genes were significantly enriched in immune cell chemotaxis and cytokine activity. KEGG pathway analysis showed that the hub genes were significantly enriched in the rheumatoid arthritis signaling pathway, IL-17 signaling pathway and cytokine-cytokine receptor interaction signaling pathway. The immune infiltration profiles varied significantly between osteoarthritis and normal controls. Compared with normal tissue, OA synovial tissue contained a higher proportion of memory B cells, naive CD4+ T cells, regulatory T cells, resting dendritic cells and resting mast cells, while naive CD4+ T cells, activated NK cells, activated mast cells and eosinophils contributed to a relatively lower portion (  > 0.05). Finally, the expression levels of 11 hub genes were confirmed by RT-PCR. The hub genes and the difference in immune infiltration in synovial tissue between osteoarthritis and normal controls might provide new insight for understanding OA development.