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Urine metabolome profiling of immune-mediated inflammatory diseases
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 biomarker...
Autores principales: | , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5016926/ https://www.ncbi.nlm.nih.gov/pubmed/27609333 http://dx.doi.org/10.1186/s12916-016-0681-8 |
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author | Alonso, Arnald Julià, Antonio Vinaixa, Maria Domènech, Eugeni Fernández-Nebro, Antonio Cañete, Juan D. Ferrándiz, Carlos Tornero, Jesús Gisbert, Javier P. Nos, Pilar Casbas, Ana Gutiérrez Puig, Lluís González-Álvaro, Isidoro Pinto-Tasende, José A. Blanco, Ricardo Rodríguez, Miguel A. Beltran, Antoni Correig, Xavier Marsal, Sara |
author_facet | Alonso, Arnald Julià, Antonio Vinaixa, Maria Domènech, Eugeni Fernández-Nebro, Antonio Cañete, Juan D. Ferrándiz, Carlos Tornero, Jesús Gisbert, Javier P. Nos, Pilar Casbas, Ana Gutiérrez Puig, Lluís González-Álvaro, Isidoro Pinto-Tasende, José A. Blanco, Ricardo Rodríguez, Miguel A. Beltran, Antoni Correig, Xavier Marsal, Sara |
author_sort | Alonso, Arnald |
collection | PubMed |
description | 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12916-016-0681-8) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5016926 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-50169262016-09-10 Urine metabolome profiling of immune-mediated inflammatory diseases Alonso, Arnald Julià, Antonio Vinaixa, Maria Domènech, Eugeni Fernández-Nebro, Antonio Cañete, Juan D. Ferrándiz, Carlos Tornero, Jesús Gisbert, Javier P. Nos, Pilar Casbas, Ana Gutiérrez Puig, Lluís González-Álvaro, Isidoro Pinto-Tasende, José A. Blanco, Ricardo Rodríguez, Miguel A. Beltran, Antoni Correig, Xavier Marsal, Sara BMC Med Research Article 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12916-016-0681-8) contains supplementary material, which is available to authorized users. BioMed Central 2016-09-08 /pmc/articles/PMC5016926/ /pubmed/27609333 http://dx.doi.org/10.1186/s12916-016-0681-8 Text en © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Alonso, Arnald Julià, Antonio Vinaixa, Maria Domènech, Eugeni Fernández-Nebro, Antonio Cañete, Juan D. Ferrándiz, Carlos Tornero, Jesús Gisbert, Javier P. Nos, Pilar Casbas, Ana Gutiérrez Puig, Lluís González-Álvaro, Isidoro Pinto-Tasende, José A. Blanco, Ricardo Rodríguez, Miguel A. Beltran, Antoni Correig, Xavier Marsal, Sara Urine metabolome profiling of immune-mediated inflammatory diseases |
title | Urine metabolome profiling of immune-mediated inflammatory diseases |
title_full | Urine metabolome profiling of immune-mediated inflammatory diseases |
title_fullStr | Urine metabolome profiling of immune-mediated inflammatory diseases |
title_full_unstemmed | Urine metabolome profiling of immune-mediated inflammatory diseases |
title_short | Urine metabolome profiling of immune-mediated inflammatory diseases |
title_sort | urine metabolome profiling of immune-mediated inflammatory diseases |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5016926/ https://www.ncbi.nlm.nih.gov/pubmed/27609333 http://dx.doi.org/10.1186/s12916-016-0681-8 |
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