Insight into osteoarthritis through integrative analysis of metabolomics and transcriptomics

Lack of clinically specific biomarkers has impeded the diagnosis of osteoarthritis (OA) and limited understanding of pathogenesis for OA has also restrained the enhancement of therapeutic measures. In the study, plasma untargeted metabolomics of twelve OA patients and twenty healthy controls (HC) were analyzed by gas chromatography coupled with quadrupole time-of-flight mass spectrometry (GC/Q-TOF-MS). The differential metabolites (DMs) between OA and HC were evaluated by multivariate analysis and Bayes discriminant analysis was employed to discover potential diagnosis biomarkers. Meanwhile a transcriptomic dataset GSE55235 was downloaded from GEO database to explore the differentially expressed genes (DEGs) between OA and HC by R/Bioconductor project. Finally, an integrative analysis of DMs and DEGs was performed to investigate the possible molecular mechanisms of OA. As a result, a panel of three metabolites including succinic acid, xanthurenic acid and L-tryptophan was revealed to potentially act as biomarker for the diagnosis of OA. Furthermore, the integrated analysis of metabolomics and transcriptomics showed the top three enrichment in the T cell receptor signaling pathway, Fc epsilon RI (FcεRI) signaling pathway, and thermogenesis, explaining the inflammation, joint destruction and energy metabolism disorders in OA.