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Identification of Potential Biomarkers for Urine Metabolomics of Polycystic Ovary Syndrome Based on Gas Chromatography-Mass Spectrometry

BACKGROUND: Polycystic ovary syndrome (PCOS) is a complex endocrine and metabolic disorder, and it's diagnosis is difficult. The aim of this study was to investigate the metabolic profiles of PCOS patients by analyzing urine samples and identify useful biomarkers for diagnosis of PCOS. METHODS:...

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Autores principales: Zou, Ying, Zhu, Fu-Fan, Fang, Chao-Ying, Xiong, Xi-Yue, Li, Hong-Yun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Medknow Publications & Media Pvt Ltd 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5912061/
https://www.ncbi.nlm.nih.gov/pubmed/29664055
http://dx.doi.org/10.4103/0366-6999.229899
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author Zou, Ying
Zhu, Fu-Fan
Fang, Chao-Ying
Xiong, Xi-Yue
Li, Hong-Yun
author_facet Zou, Ying
Zhu, Fu-Fan
Fang, Chao-Ying
Xiong, Xi-Yue
Li, Hong-Yun
author_sort Zou, Ying
collection PubMed
description BACKGROUND: Polycystic ovary syndrome (PCOS) is a complex endocrine and metabolic disorder, and it's diagnosis is difficult. The aim of this study was to investigate the metabolic profiles of PCOS patients by analyzing urine samples and identify useful biomarkers for diagnosis of PCOS. METHODS: This study was carried out in the Department of Obstetrics and Gynecology of the Maternal and Child Health Hospital of Hunan Province from December 2014 to July 2016. In this study, the urine samples of 21 women with PCOS and 16 healthy controls were assessed through gas chromatography-mass spectrometry to investigate the urine metabolite characteristics of PCOS and identify useful biomarkers for the diagnosis of this disorder. The Student's t-test and rank sum test were applied to validate the statistical significance of the between the two groups. RESULTS: In total, 35 urine metabolites were found to be significantly different between the PCOS patients and the controls. In particular, a significant increase in the levels of lactose (10.01 [0,13.99] mmol/mol creatinine vs. 2.35 [0.16, 3.26] mmol/mol creatinine, P = 0.042), stearic acid (2.35 [1.47, 3.14] mmol/mol creatinine vs. 0.05 [0, 0.14] mmol/mol creatinine, P < 0.001), and palmitic acid (2.13 [1.07, 2.79] mmol/mol creatinine vs. 0 [0, 0] mmol/mol creatinine, P < 0.001) and a decrease in the levels of succinic acid (0 [0, 0] mmol/mol creatinine vs. 38.94 [4.16, 51.30] mmol/mol creatinine, P < 0.001) were found in the PCOS patients compared with the controls. It was possible to cluster the PCOS patients and the healthy controls into two distinct regions based on a principal component analysis model. Of the differentially expressed metabolites, four compounds, including stearic acid, palmitic acid, benzoylglycine, and threonine, were selected as potential biomarkers. CONCLUSIONS: This study offers new insight into the pathogenesis of PCOS, and the discriminating urine metabolites may provide a prospect for the diagnosis of PCOS.
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spelling pubmed-59120612018-05-03 Identification of Potential Biomarkers for Urine Metabolomics of Polycystic Ovary Syndrome Based on Gas Chromatography-Mass Spectrometry Zou, Ying Zhu, Fu-Fan Fang, Chao-Ying Xiong, Xi-Yue Li, Hong-Yun Chin Med J (Engl) Original Article BACKGROUND: Polycystic ovary syndrome (PCOS) is a complex endocrine and metabolic disorder, and it's diagnosis is difficult. The aim of this study was to investigate the metabolic profiles of PCOS patients by analyzing urine samples and identify useful biomarkers for diagnosis of PCOS. METHODS: This study was carried out in the Department of Obstetrics and Gynecology of the Maternal and Child Health Hospital of Hunan Province from December 2014 to July 2016. In this study, the urine samples of 21 women with PCOS and 16 healthy controls were assessed through gas chromatography-mass spectrometry to investigate the urine metabolite characteristics of PCOS and identify useful biomarkers for the diagnosis of this disorder. The Student's t-test and rank sum test were applied to validate the statistical significance of the between the two groups. RESULTS: In total, 35 urine metabolites were found to be significantly different between the PCOS patients and the controls. In particular, a significant increase in the levels of lactose (10.01 [0,13.99] mmol/mol creatinine vs. 2.35 [0.16, 3.26] mmol/mol creatinine, P = 0.042), stearic acid (2.35 [1.47, 3.14] mmol/mol creatinine vs. 0.05 [0, 0.14] mmol/mol creatinine, P < 0.001), and palmitic acid (2.13 [1.07, 2.79] mmol/mol creatinine vs. 0 [0, 0] mmol/mol creatinine, P < 0.001) and a decrease in the levels of succinic acid (0 [0, 0] mmol/mol creatinine vs. 38.94 [4.16, 51.30] mmol/mol creatinine, P < 0.001) were found in the PCOS patients compared with the controls. It was possible to cluster the PCOS patients and the healthy controls into two distinct regions based on a principal component analysis model. Of the differentially expressed metabolites, four compounds, including stearic acid, palmitic acid, benzoylglycine, and threonine, were selected as potential biomarkers. CONCLUSIONS: This study offers new insight into the pathogenesis of PCOS, and the discriminating urine metabolites may provide a prospect for the diagnosis of PCOS. Medknow Publications & Media Pvt Ltd 2018-04-20 /pmc/articles/PMC5912061/ /pubmed/29664055 http://dx.doi.org/10.4103/0366-6999.229899 Text en Copyright: © 2018 Chinese Medical Journal http://creativecommons.org/licenses/by-nc-sa/4.0 This is an open access journal, and articles are distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as appropriate credit is given and the new creations are licensed under the identical terms.
spellingShingle Original Article
Zou, Ying
Zhu, Fu-Fan
Fang, Chao-Ying
Xiong, Xi-Yue
Li, Hong-Yun
Identification of Potential Biomarkers for Urine Metabolomics of Polycystic Ovary Syndrome Based on Gas Chromatography-Mass Spectrometry
title Identification of Potential Biomarkers for Urine Metabolomics of Polycystic Ovary Syndrome Based on Gas Chromatography-Mass Spectrometry
title_full Identification of Potential Biomarkers for Urine Metabolomics of Polycystic Ovary Syndrome Based on Gas Chromatography-Mass Spectrometry
title_fullStr Identification of Potential Biomarkers for Urine Metabolomics of Polycystic Ovary Syndrome Based on Gas Chromatography-Mass Spectrometry
title_full_unstemmed Identification of Potential Biomarkers for Urine Metabolomics of Polycystic Ovary Syndrome Based on Gas Chromatography-Mass Spectrometry
title_short Identification of Potential Biomarkers for Urine Metabolomics of Polycystic Ovary Syndrome Based on Gas Chromatography-Mass Spectrometry
title_sort identification of potential biomarkers for urine metabolomics of polycystic ovary syndrome based on gas chromatography-mass spectrometry
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5912061/
https://www.ncbi.nlm.nih.gov/pubmed/29664055
http://dx.doi.org/10.4103/0366-6999.229899
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