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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...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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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. |
format | Online Article Text |
id | pubmed-7536211 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
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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