Eur Rev Med Pharmacol Sci 2015; 19 (5): 736-744

Identification of genes and pathways associated with osteoarthritis by bioinformatics analyses

Z. Feng, K.-J. Lian

Fujian University of Traditional Chinese Medicine 2010; Dr Fractures of Traditional Chinese Medicine Science, Fujian Fuzhou, China; Guangxi University of Chinese Medicine, Affiliated Hospital Orthopedics, Nanning, Guangxi, China. liankjse@163.com


OBJECTIVE: This study aimed to explore the molecular mechanism of osteoarthritis (OA) development and discover underlying genes associated with OA.

DATA AND METHODS: Gene expression profile GSE48556 including 106 peripheral blood mononuclear cells (PBMCs) of osteoarthritis patients and 33 PBMCs of healthy controls was downloaded from the Gene Expression Omnibus database. The limma package was used to identify the differentially expressed genes (DEGs) by paired t-test. The functional enrichment analyses of DEGs was performed, followed by the construction of protein-protein interaction (PPI) network.

RESULTS: Total 432 DEGs including 178 up-regulated DEGs and 254 down-regulated DEGs were identified. Pathways of cytokine-cytokine receptor interaction and T cell receptor signaling pathway were significantly up-regulated in OA. Biological processes of negative regulation of transcription from RNA polymerase II promoter and negative regulation of transcription, DNA-dependent were significantly down-regulated in OA. The platelet-derived growth factor receptor, beta polypeptide (PDGFRB), interferon, gamma (IFNG), early growth response 1 (EGR1), Fas ligand (TNF superfamily, member 6) (FASLG), H3 histone, family 3B (H3.3B) (H3F3B) and so on had higher connectivity degree in the PPI networks.

CONCLUSIONS: DEGs of OA were mainly enriched in the pathways associated with cytokine-cytokine receptor interaction and T cell receptor signaling pathway. The DEGs such as PDGFRB, IFNG, EGR1, FASLG and H3F3B may be the potential targets for OA diagnosis and treatment.

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To cite this article

Z. Feng, K.-J. Lian
Identification of genes and pathways associated with osteoarthritis by bioinformatics analyses

Eur Rev Med Pharmacol Sci
Year: 2015
Vol. 19 - N. 5
Pages: 736-744