Metabolomics in rheumatic diseases: The potential of an emerging methodology for improved patient diagnosis, prognosis, and treatment efficacy

Metabolomics belongs to the family of -omics sciences, also comprised of genomics, transcriptomics, and proteomics, all of which share the advantage of a non-targeted approach for identifying biomarkers and profiling the patient. This means that they do not require a preliminary knowledge of the substances to be studied. Moreover, even small quantities of biological fluids or tissues may be utilized for analysis. Metabolomic procedure has become feasible only recently with the advent and accessibility of new high-throughput technologies, including mass spectrometry and nuclear magnetic resonance. The methodology generally involves three defining steps: 1) the acquisition of experimental data, 2) the multivariate statistical analysis, and 3) the projection of the acquired information (profiles) to construct the patient map. Metabolomic analysis has been applied to several disorders: as far as rheumatic diseases are concerned, a few studies have focused on rheumatoid arthritis, spondyloarthritis, systemic lupus erythematosus, and osteoarthritis. Both murine models and clinical data have shown the potential of this novel tool to contribute to deciding a diagnosis, discriminate between patients based on disease activity, and even predict the response to a particular treatment. The present review fully reports these findings and offers a critical view of the challenges still to be met.