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Urinary biomarker panel for diagnosing patients with depression and anxiety disorders
Available data indicate that patients with depression and anxiety disorders are likely to be at greater risk for suicide. Therefore, it is important to correctly diagnose patients with depression and anxiety disorders. However, there are still no empirical laboratory methods to objectively diagnose...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6145889/ https://www.ncbi.nlm.nih.gov/pubmed/30232320 http://dx.doi.org/10.1038/s41398-018-0245-0 |
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author | Chen, Jian-jun Bai, Shun-Jie Li, Wen-wen Zhou, Chan-juan Zheng, Peng Fang, Liang Wang, Hai-yang Liu, Yi-yun Xie, Peng |
author_facet | Chen, Jian-jun Bai, Shun-Jie Li, Wen-wen Zhou, Chan-juan Zheng, Peng Fang, Liang Wang, Hai-yang Liu, Yi-yun Xie, Peng |
author_sort | Chen, Jian-jun |
collection | PubMed |
description | Available data indicate that patients with depression and anxiety disorders are likely to be at greater risk for suicide. Therefore, it is important to correctly diagnose patients with depression and anxiety disorders. However, there are still no empirical laboratory methods to objectively diagnose these patients. In this study, the multiple metabolomics platforms were used to profile the urine samples from 32 healthy controls and 32 patients with depression and anxiety disorders for identifying differential metabolites and potential biomarkers. Then, 16 healthy controls and 16 patients with depression and anxiety disorders were used to independently validate the diagnostic performance of the identified biomarkers. Finally, a panel consisting of four biomarkers—N-methylnicotinamide, aminomalonic acid, azelaic acid and hippuric acid—was identified. This panel was capable of distinguishing patients with depression and anxiety disorders from healthy controls with an area under the receiver operating characteristic curve of 0.977 in the training set and 0.934 in the testing set. Meanwhile, we found that these identified differential metabolites were mainly involved in three metabolic pathways and five molecular and cellular functions. Our results could lay the groundwork for future developing a urine-based diagnostic method for patients with depression and anxiety disorders. |
format | Online Article Text |
id | pubmed-6145889 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-61458892018-09-21 Urinary biomarker panel for diagnosing patients with depression and anxiety disorders Chen, Jian-jun Bai, Shun-Jie Li, Wen-wen Zhou, Chan-juan Zheng, Peng Fang, Liang Wang, Hai-yang Liu, Yi-yun Xie, Peng Transl Psychiatry Article Available data indicate that patients with depression and anxiety disorders are likely to be at greater risk for suicide. Therefore, it is important to correctly diagnose patients with depression and anxiety disorders. However, there are still no empirical laboratory methods to objectively diagnose these patients. In this study, the multiple metabolomics platforms were used to profile the urine samples from 32 healthy controls and 32 patients with depression and anxiety disorders for identifying differential metabolites and potential biomarkers. Then, 16 healthy controls and 16 patients with depression and anxiety disorders were used to independently validate the diagnostic performance of the identified biomarkers. Finally, a panel consisting of four biomarkers—N-methylnicotinamide, aminomalonic acid, azelaic acid and hippuric acid—was identified. This panel was capable of distinguishing patients with depression and anxiety disorders from healthy controls with an area under the receiver operating characteristic curve of 0.977 in the training set and 0.934 in the testing set. Meanwhile, we found that these identified differential metabolites were mainly involved in three metabolic pathways and five molecular and cellular functions. Our results could lay the groundwork for future developing a urine-based diagnostic method for patients with depression and anxiety disorders. Nature Publishing Group UK 2018-09-19 /pmc/articles/PMC6145889/ /pubmed/30232320 http://dx.doi.org/10.1038/s41398-018-0245-0 Text en © The Author(s) 2018 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Chen, Jian-jun Bai, Shun-Jie Li, Wen-wen Zhou, Chan-juan Zheng, Peng Fang, Liang Wang, Hai-yang Liu, Yi-yun Xie, Peng Urinary biomarker panel for diagnosing patients with depression and anxiety disorders |
title | Urinary biomarker panel for diagnosing patients with depression and anxiety disorders |
title_full | Urinary biomarker panel for diagnosing patients with depression and anxiety disorders |
title_fullStr | Urinary biomarker panel for diagnosing patients with depression and anxiety disorders |
title_full_unstemmed | Urinary biomarker panel for diagnosing patients with depression and anxiety disorders |
title_short | Urinary biomarker panel for diagnosing patients with depression and anxiety disorders |
title_sort | urinary biomarker panel for diagnosing patients with depression and anxiety disorders |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6145889/ https://www.ncbi.nlm.nih.gov/pubmed/30232320 http://dx.doi.org/10.1038/s41398-018-0245-0 |
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