Gene expression profiles in osteoarthritis: a bioinformatic analysis

doi:10.3969/j.issn.2095-4344.0797

Abstract

Abstract:

BACKGROUND: Osteoarthritis is a threat for middle-aged and older adults. The development and occurrence of osteoarthritis is regulated by various genes, however, the signaling pathways remain unclear.
OBJECTIVE: To investigate the gene expression profiles of osteoarthritis based on a bioinformatics analysis.
METHODS: Totally 158 differentially expressed genes during the process of osteoarthritis were obtained from the analysis of synovial tissue data downloaded from the Gene Expression Omnibus database. The functional annotation of gene expression difference was analyzed by DAVID online database. The protein-protein interactions were evaluated by STRING online database.
RESULTS AND CONCLUSION: Total 158 differentially expressed genes were identified, including 12 up-regulated genes and 146 down-regulated genes. The Gene Ontology annotation analysis and the KEGG pathway enrichment analysis were performed on DAVID online database, and the results showed that these differentially expressed genes were mainly involved in positive regulation of osteoclast differentiation and cell-cell adhesion, and these pathways were mainly involved in MAPK signaling pathway, P13K-Akt signaling pathway and ECM receptor. The protein-protein interactions of target genes were analyzed and the hub genes such as VEGFA, JUN, PRKACA, PXN and SPTAN1 were identified. In summary, the interaction of these genes may be involved in the process of osteoarthritis, and the network provides a potential target for the diagnosis and treatment of osteoarthritis.

中国组织工程研究杂志出版内容重点：组织构建；骨细胞；软骨细胞；细胞培养；成纤维细胞；血管内皮细胞；骨质疏松；组织工程

Key words: Tissue Engineering, Gene Regulatory Networks, Computational Biology

CLC Number:

R445

Dong Zhengquan1, Wei Lei2. Gene expression profiles in osteoarthritis: a bioinformatic analysis [J]. Chinese Journal of Tissue Engineering Research, 2019, 23(3): 335-340.

Figures/Tables 5

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