BACKGROUND: Osteoarthritis (OA) of the knee is a common disease that is associated with chronic pain. This study aimed to identify and investigate the functional role of biomarkers associated with long noncoding RNA (lncRNA) in the progression of OA of the knee by lncRNA-associated competing endogenous RNA (ceRNA) integrated network analysis.

MATERIAL AND METHODS: High-quality microRNA (miRNA)-lncRNA and miRNA-mRNA interactions and lncRNA and mRNA expression profiles for patients with OA of the knee with mild and severe pain were obtained from the Gene Expression Omnibus (GEO) database (GSE99662). A three-step computational method was used to construct the lncRNA-associated ceRNA interaction network in OA by integrating miRNA-lncRNA/mRNA interactions and lncRNA/mRNA expression profiles in patients with OA with mild and severe pain.

RESULTS: A total of 1,870 dysregulated lncRNA-mRNA interactions were obtained in the lncRNA-associated ceRNA network in OA, including 476 gain and 1,394 loss interactions, covering 131 lncRNAs and 1,251 mRNAs. Characterization of the lncRNA-associated ceRNA network in OA indicated that lncRNAs had roles in the network. Further differential expression analysis identified eight lncRNA biomarkers, which could distinguish between patients with OA with mild pain and severe pain. These lncRNA-associated interactions showed significantly different co-expression patterns in samples from patients with OA of the knee associated with mild pain.

CONCLUSIONS: Integrated network analysis of lncRNA-associated ceRNA identified eight lncRNA molecular biomarkers associated with the progression of OA of the knee.

Keywords: Biological Markers, Osteoarthritis, Computational Biology, Databases, Genetic, Disease Progression, Gene Expression Profiling, Gene Regulatory Networks, Knee Joint, Osteoarthritis, Knee, RNA, Messenger