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Non-targeted urine metabolomics and associations with prevalent and incident type 2 diabetes

Better risk prediction and new molecular targets are key priorities in type 2 diabetes (T2D) research. Little is known about the role of the urine metabolome in predicting the risk of T2D. We aimed to use non-targeted urine metabolomics to discover biomarkers and improve risk prediction for T2D. Uri...

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Autores principales: Salihovic, Samira, Broeckling, Corey D., Ganna, Andrea, Prenni, Jessica E., Sundström, Johan, Berne, Christian, Lind, Lars, Ingelsson, Erik, Fall, Tove, Ärnlöv, Johan, Nowak, Christoph
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7536211/
https://www.ncbi.nlm.nih.gov/pubmed/33020500
http://dx.doi.org/10.1038/s41598-020-72456-y
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author Salihovic, Samira
Broeckling, Corey D.
Ganna, Andrea
Prenni, Jessica E.
Sundström, Johan
Berne, Christian
Lind, Lars
Ingelsson, Erik
Fall, Tove
Ärnlöv, Johan
Nowak, Christoph
author_facet Salihovic, Samira
Broeckling, Corey D.
Ganna, Andrea
Prenni, Jessica E.
Sundström, Johan
Berne, Christian
Lind, Lars
Ingelsson, Erik
Fall, Tove
Ärnlöv, Johan
Nowak, Christoph
author_sort Salihovic, Samira
collection PubMed
description Better risk prediction and new molecular targets are key priorities in type 2 diabetes (T2D) research. Little is known about the role of the urine metabolome in predicting the risk of T2D. We aimed to use non-targeted urine metabolomics to discover biomarkers and improve risk prediction for T2D. Urine samples from two community cohorts of 1,424 adults were analyzed by ultra-performance liquid chromatography/mass spectrometry (UPLC-MS). In a discovery/replication design, three out of 62 annotated metabolites were associated with prevalent T2D, notably lower urine levels of 3-hydroxyundecanoyl-carnitine. In participants without diabetes at baseline, LASSO regression in the training set selected six metabolites that improved prediction of T2D beyond established risk factors risk over up to 12 years' follow-up in the test sample, from C-statistic 0.866 to 0.892. Our results in one of the largest non-targeted urinary metabolomics study to date demonstrate the role of the urine metabolome in identifying at-risk persons for T2D and suggest urine 3-hydroxyundecanoyl-carnitine as a biomarker candidate.
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spelling pubmed-75362112020-10-06 Non-targeted urine metabolomics and associations with prevalent and incident type 2 diabetes Salihovic, Samira Broeckling, Corey D. Ganna, Andrea Prenni, Jessica E. Sundström, Johan Berne, Christian Lind, Lars Ingelsson, Erik Fall, Tove Ärnlöv, Johan Nowak, Christoph Sci Rep Article Better risk prediction and new molecular targets are key priorities in type 2 diabetes (T2D) research. Little is known about the role of the urine metabolome in predicting the risk of T2D. We aimed to use non-targeted urine metabolomics to discover biomarkers and improve risk prediction for T2D. Urine samples from two community cohorts of 1,424 adults were analyzed by ultra-performance liquid chromatography/mass spectrometry (UPLC-MS). In a discovery/replication design, three out of 62 annotated metabolites were associated with prevalent T2D, notably lower urine levels of 3-hydroxyundecanoyl-carnitine. In participants without diabetes at baseline, LASSO regression in the training set selected six metabolites that improved prediction of T2D beyond established risk factors risk over up to 12 years' follow-up in the test sample, from C-statistic 0.866 to 0.892. Our results in one of the largest non-targeted urinary metabolomics study to date demonstrate the role of the urine metabolome in identifying at-risk persons for T2D and suggest urine 3-hydroxyundecanoyl-carnitine as a biomarker candidate. Nature Publishing Group UK 2020-10-05 /pmc/articles/PMC7536211/ /pubmed/33020500 http://dx.doi.org/10.1038/s41598-020-72456-y Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Salihovic, Samira
Broeckling, Corey D.
Ganna, Andrea
Prenni, Jessica E.
Sundström, Johan
Berne, Christian
Lind, Lars
Ingelsson, Erik
Fall, Tove
Ärnlöv, Johan
Nowak, Christoph
Non-targeted urine metabolomics and associations with prevalent and incident type 2 diabetes
title Non-targeted urine metabolomics and associations with prevalent and incident type 2 diabetes
title_full Non-targeted urine metabolomics and associations with prevalent and incident type 2 diabetes
title_fullStr Non-targeted urine metabolomics and associations with prevalent and incident type 2 diabetes
title_full_unstemmed Non-targeted urine metabolomics and associations with prevalent and incident type 2 diabetes
title_short Non-targeted urine metabolomics and associations with prevalent and incident type 2 diabetes
title_sort non-targeted urine metabolomics and associations with prevalent and incident type 2 diabetes
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7536211/
https://www.ncbi.nlm.nih.gov/pubmed/33020500
http://dx.doi.org/10.1038/s41598-020-72456-y
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