BACKGROUND: Our study intended to identify potential long non-coding RNAs (lncRNAs) and genes, and to elucidate the underlying mechanisms of intervertebral disc degeneration (IDD).

MATERIAL AND METHODS: The microarray of GSE56081 was downloaded from the Gene Expression Omnibus database, including 5 human control nucleus pulposus tissues and 5 degenerative nucleus pulposus tissues, which was on the basis of GPL15314 platform. Identification of differentially expressed lncRNAs and mRNAs were performed between the 2 groups. Then, gene ontology (GO) and pathway enrichment analyses were performed to analyze the biological functions and pathways for the differentially expressed mRNAs. Simultaneously, lncRNA-mRNA weighted coexpression network was constructed using the WGCNA package, followed by GO and KEGG pathway enrichment analyses for the genes in the modules. Finally, the protein-protein interaction (PPI) network was visualized.

RESULTS: A total of 135 significantly up- and 170 down-regulated lncRNAs and 2133 significantly up- and 1098 down-regulated mRNAs were identified. Additionally, UBA52 (ubiquitin A-52 residue ribosomal protein fusion product 1), with the highest connectivity degree in PPI network, was remarkably enriched in the pathway of metabolism of proteins. Eight lncRNAs – LINC00917, CTD-2246P4.1, CTC-523E23.5, RP4-639J15.1, RP11-363G2.4, AC005082.12, MIR132, and RP11-38F22.1 – were observed in the modules of lncRNA-mRNA weighted coexpression network. Moreover, SPHK1 in the green-yellow module was significantly enriched in positive regulation of cell migration.

CONCLUSIONS: LncRNAs LINC00917, CTD-2246P4.1, CTC-523E23.5, RP4-639J15.1, RP11-363G2.4, AC005082.12, MIR132, and RP11-38F22.1 were differentially expressed and might play important roles in the development of IDD. Key genes, such as UBA52 and SPHK1, may be pivotal biomarkers for IDD.

Keywords: Biomarkers - metabolism, Databases, Genetic, Gene Expression Regulation, gene ontology, Intervertebral Disc Degeneration - genetics, Oligonucleotide Array Sequence Analysis, Protein Interaction Mapping, RNA, Long Noncoding - genetics, RNA, Messenger - metabolism