RT Journal Article T1 Urine metabolome profiling of immune-mediated inflammatory diseases. A1 Alonso, Arnald A1 Julià, Antonio A1 Vinaixa, Maria A1 Domènech, Eugeni A1 Fernández-Nebro, Antonio A1 Cañete, Juan D A1 Ferrándiz, Carlos A1 Tornero, Jesús A1 Gisbert, Javier P A1 Nos, Pilar A1 Gutiérrez Casbas, Ana A1 Puig, Lluís A1 González-Álvaro, Isidoro A1 Pinto-Tasende, José A A1 Blanco, Ricardo A1 Rodríguez, Miguel A A1 Beltran, Antoni A1 Correig, Xavier A1 Marsal, Sara K1 Metabolomics K1 Urine biomarkers K1 Disease activity K1 Autoimmune diseases K1 Inflammatory diseases K1 Artritis psoriásica K1 Artritis reumatoide K1 Biomarcadores K1 Ciclo del ácido cítrico K1 Enfermedad de crohn K1 Glicina K1 Humanos K1 Enfermedades inflamatorias del intestino K1 Modelos lineales K1 Lupus eritematoso sistémico K1 Espectroscopía de resonancia magnética K1 Metaboloma K1 Fenilalanina K1 Psoriasis K1 Serina AB BACKGROUNDImmune-mediated inflammatory diseases (IMIDs) are a group of complex and prevalent diseases where disease diagnostic and activity monitoring is highly challenging. The determination of the metabolite profiles of biological samples is becoming a powerful approach to identify new biomarkers of clinical utility. In order to identify new metabolite biomarkers of diagnosis and disease activity, we have performed the first large-scale profiling of the urine metabolome of the six most prevalent IMIDs: rheumatoid arthritis, psoriatic arthritis, psoriasis, systemic lupus erythematosus, Crohn's disease, and ulcerative colitis.METHODSUsing nuclear magnetic resonance, we analyzed the urine metabolome in a discovery cohort of 1210 patients and 100 controls. Within each IMID, two patient subgroups were recruited representing extreme disease activity (very high vs. very low). Metabolite association analysis with disease diagnosis and disease activity was performed using multivariate linear regression in order to control for the effects of clinical, epidemiological, or technical variability. After multiple test correction, the most significant metabolite biomarkers were validated in an independent cohort of 1200 patients and 200 controls.RESULTSIn the discovery cohort, we identified 28 significant associations between urine metabolite levels and disease diagnosis and three significant metabolite associations with disease activity (P FDR < 0.05). Using the validation cohort, we validated 26 of the diagnostic associations and all three metabolite associations with disease activity (P FDR < 0.05). Combining all diagnostic biomarkers using multivariate classifiers we obtained a good disease prediction accuracy in all IMIDs and particularly high in inflammatory bowel diseases. Several of the associated metabolites were found to be commonly altered in multiple IMIDs, some of which can be considered as hub biomarkers. The analysis of the metabolic reactions connecting the IMID-associated metabolites showed an over-representation of citric acid cycle, phenylalanine, and glycine-serine metabolism pathways.CONCLUSIONSThis study shows that urine is a source of biomarkers of clinical utility in IMIDs. We have found that IMIDs show similar metabolic changes, particularly between clinically similar diseases and we have found, for the first time, the presence of hub metabolites. These findings represent an important step in the development of more efficient and less invasive diagnostic and disease monitoring methods in IMIDs. PB Biomed Central YR 2016 FD 2016-09-08 LK http://hdl.handle.net/10668/2510 UL http://hdl.handle.net/10668/2510 LA en NO Alonso A, Julià A, Vinaixa M, Domènech E, Fernández-Nebro A, Cañete JD, et al. Urine metabolome profiling of immune-mediated inflammatory diseases. BMC Med. 2016; 14(1):133 NO Journal Article; DS RISalud RD Feb 14, 2025