Bioinformatics of gene expression profile in human intervertebral disc degeneration associated with inflammatory cytokine

Objective To investigate the microarray data on the gene expression profiles of intervertebral disc degeneration related to cytokine exposure using a bioinformatics analysis, and to explore the related signaling pathways and interaction networks, providing clues to the molecular mechanisms of disc degeneration. Methods The data of gene expression profiles were obtained using the same microarray platform for two groups of patients suffering from degenerative disc diseases: GSE41883 [Human annulus disc cells exposed to tumor necrosis factor-α (TNF-α)] and GSE27494 [Human annulus disc cells exposed to interleukin-1β (IL-1β)]. The genes that were differentially expressed in these two datasets compared to control disc cells 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 prostaglandin 2 (PTGS2), intercellular adhesion molecule 1 (ICAM1), nephroblastoma overexpressed gene (NOV) and other genes may play a role in disc degeneration. Conclusion 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 on 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: Disc degeneration; Inflammatory factors; Gene expression profiling; Bioinformatics