ORIGINAL ARTICLE   

Journal of Neurosurgical Sciences 2018 February;62(1):16-23

DOI: 10.23736/S0390-5616.16.03326-9

Copyright © 2015 EDIZIONI MINERVA MEDICA

language: English

Bioinformatics analysis of the gene expression profiles in human intervertebral disc degeneration associated with inflammatory cytokines

Chao LIU ¹, Jie-Feng ZHANG ², Zhong-Yi SUN ¹, Ji-Wei TIAN ³ ✉

¹ Shanghai Jiao Tong University School of Medicine, Shanghai Jiaotong University Affiliated First People’s Hospital, Shanghai, China; ² Department of Orthopedics and Trauma, the Central Hospital of Tai'an, Tai'an, China; ³ Department of Orthopedics, Shanghai Jiaotong University Affiliated First People’s Hospital, Shanghai, China

BACKGROUND: To investigate the microarray data on the gene expression profiles of intervertebral disc degeneration related to cytokine exposure. The purpose of the study was to identify the key genes that were differentially expressed in these disc cells compared to cells without inflammatory cytokine treatment, using bioinformatics analyses, and to explore the related signaling pathways and interaction networks, providing clues to the molecular mechanisms of disc degeneration for future experimental studies.
METHODS: The gene expression profiles data were obtained using the same microarray platform for two groups of patients suffering from degenerative disc diseases: GSE41883 (Human annulus disc cells exposed to TNF-a; 4 samples) and GSE27494 (Human annulus disc cells exposed to IL-1β; 4 samples). The genes that were differentially expressed in these two datasets compared to control disc cells (without cytokine exposure; 4 samples each) were identified using the R language, and were pooled using the Excel software program to select the common differentially expressed genes in the two datasets. The initial functional clustering, signaling pathways and protein-protein interaction relationship analyses were conducted using the DAVID and STRING software programs.
RESULTS: Of the 255 concomitantly and differentially expressed genes identified after respective treatment with TNF-α and IL-1β, 141 were up-regulated and 114 were down-regulated. The gene ontology annotation analysis showed that these differentially expressed genes were primarily associated with cytokine activity, growth factor activity, the inflammatory reaction and the response to injury. The signaling pathway analysis showed that these differentially expressed genes were mainly related to the interactions of cytokines, apoptosis and NOD-like receptor signaling pathways. The interaction network analysis indicated that PTGS2, ICAM1, NOV and other genes may play a role in disc degeneration.
CONCLUSIONS: We found that ICAM1 and other genes may play a role in the development of disc degeneration induced by inflammatory reactions using a bioinformatics analysis of the gene expression profiles of degenerative intervertebral disc cells stimulated with inflammatory factors, suggesting that bioinformatics methods can be used to identify potential target for intervertebral disc degeneration.

KEY WORDS: Intervertebral disc degeneration - Gene expression profiling - Computational biology - Microarray analysis