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oai:repisalud.isciii.es:20.500.12105/171542024-11-28T14:56:51Zcom_20.500.12105_15322com_20.500.12105_2051col_20.500.12105_16927col_20.500.12105_16961col_20.500.12105_16980col_20.500.12105_16985col_20.500.12105_16987

00925njm 22002777a 4500 dc Alonso, Arnald author Julià, Antonio author Vinaixa, Maria author Domènech, Eugeni author Fernández-Nebro, Antonio author Cañete, Juan D author Ferrándiz, Carlos author Tornero, Jesús author Gisbert, Javier P author Nos, Pilar author Gutiérrez Casbas, Ana author Puig, Lluís author González-Álvaro, Isidoro author Pinto-Tasende, José A author Blanco, Ricardo author Rodríguez, Miguel A author Beltran, Antoni author Correig, Xavier author Marsal, Sara author 2016-09-08 BACKGROUND: Immune-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. METHODS: Using 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. RESULTS: In 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. CONCLUSIONS: This 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. 10.1186/s12916-016-0681-8 1741-7015 BMC Medicine http://hdl.handle.net/10668/2510 27609333 http://hdl.handle.net/20.500.12105/17154 Metabolomics Urine biomarkers Disease activity Autoimmune diseases Inflammatory diseases Artritis psoriásica Artritis reumatoide Biomarcadores Ciclo del ácido cítrico Enfermedad de crohn Glicina Humanos Enfermedades inflamatorias del intestino Modelos lineales Lupus eritematoso sistémico Espectroscopía de resonancia magnética Metaboloma Fenilalanina Psoriasis Serina Urine metabolome profiling of immune-mediated inflammatory diseases.