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Endometrium metabolomic profiling reveals potential biomarkers for diagnosis of endometriosis at minimal-mild stages
BACKGROUND: The sensitivity and specificity of non-invasive diagnostic methods for endometriosis, especially at early stages, are not optimal. The clinical diagnostic indicator cancer antigen 125 (CA125) performs poorly in the diagnosis of minimal endometriosis, with a sensitivity of 24%. Therefore,...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5928574/ https://www.ncbi.nlm.nih.gov/pubmed/29712562 http://dx.doi.org/10.1186/s12958-018-0360-z |
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author | Li, Jingjie Guan, Lihuan Zhang, Huizhen Gao, Yue Sun, Jiahong Gong, Xiao Li, Dongshun Chen, Pan Liang, Xiaoyan Huang, Min Bi, Huichang |
author_facet | Li, Jingjie Guan, Lihuan Zhang, Huizhen Gao, Yue Sun, Jiahong Gong, Xiao Li, Dongshun Chen, Pan Liang, Xiaoyan Huang, Min Bi, Huichang |
author_sort | Li, Jingjie |
collection | PubMed |
description | BACKGROUND: The sensitivity and specificity of non-invasive diagnostic methods for endometriosis, especially at early stages, are not optimal. The clinical diagnostic indicator cancer antigen 125 (CA125) performs poorly in the diagnosis of minimal endometriosis, with a sensitivity of 24%. Therefore, it is urgent to explore novel diagnostic biomarkers. We evaluated the metabolomic profile variation of the eutopic endometrium between minimal-mild endometriosis patients and healthy women by ultra-high-performance liquid chromatography coupled with electrospray ionization high-resolution mass spectrometry (UHPLC-ESI-HRMS). METHODS: Our study comprised 29 patients with laparoscopically confirmed endometriosis at stages I-II and 37 infertile women who underwent diagnostic laparoscopy combined with hysteroscopy from January 2014 to January 2015. Eutopic endometrium samples were collected by pipelle endometrial biopsy. The metabolites were quantified by UHPLC-ESI-HRMS. The best combination of biomarkers was then selected by performing step-wise logistic regression analysis with backward elimination. RESULTS: Twelve metabolites were identified as endometriosis-associated biomarkers. The eutopic endometrium metabolomic profile of the endometriosis patients was characterized by a significant increase in the concentration of hypoxanthine, L-arginine, L-tyrosine, leucine, lysine, inosine, omega-3 arachidonic acid, guanosine, xanthosine, lysophosphatidylethanolamine and asparagine. In contrast, the concentration of uric acid was decreased. Metabolites were filtered by step-wise logistic regression with backward elimination, and a model containing uric acid, hypoxanthine, and lysophosphatidylethanolamine was constructed. Receiver-operating characteristic (ROC) analysis confirmed the prognostic value of these parameters for the diagnosis of minimal/mild endometriosis with a sensitivity of 66.7% and a specificity of 90.0%. CONCLUSIONS: Metabolomics analysis of the eutopic endometrium in endometriosis was effectively characterized by UHPLC-ESI-HRMS-based metabolomics. Our study supports the importance of purine and amino acid metabolites in the pathophysiology of endometriosis and provides potential biomarkers for semi-invasive diagnosis of early-stage endometriosis. |
format | Online Article Text |
id | pubmed-5928574 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-59285742018-05-01 Endometrium metabolomic profiling reveals potential biomarkers for diagnosis of endometriosis at minimal-mild stages Li, Jingjie Guan, Lihuan Zhang, Huizhen Gao, Yue Sun, Jiahong Gong, Xiao Li, Dongshun Chen, Pan Liang, Xiaoyan Huang, Min Bi, Huichang Reprod Biol Endocrinol Research BACKGROUND: The sensitivity and specificity of non-invasive diagnostic methods for endometriosis, especially at early stages, are not optimal. The clinical diagnostic indicator cancer antigen 125 (CA125) performs poorly in the diagnosis of minimal endometriosis, with a sensitivity of 24%. Therefore, it is urgent to explore novel diagnostic biomarkers. We evaluated the metabolomic profile variation of the eutopic endometrium between minimal-mild endometriosis patients and healthy women by ultra-high-performance liquid chromatography coupled with electrospray ionization high-resolution mass spectrometry (UHPLC-ESI-HRMS). METHODS: Our study comprised 29 patients with laparoscopically confirmed endometriosis at stages I-II and 37 infertile women who underwent diagnostic laparoscopy combined with hysteroscopy from January 2014 to January 2015. Eutopic endometrium samples were collected by pipelle endometrial biopsy. The metabolites were quantified by UHPLC-ESI-HRMS. The best combination of biomarkers was then selected by performing step-wise logistic regression analysis with backward elimination. RESULTS: Twelve metabolites were identified as endometriosis-associated biomarkers. The eutopic endometrium metabolomic profile of the endometriosis patients was characterized by a significant increase in the concentration of hypoxanthine, L-arginine, L-tyrosine, leucine, lysine, inosine, omega-3 arachidonic acid, guanosine, xanthosine, lysophosphatidylethanolamine and asparagine. In contrast, the concentration of uric acid was decreased. Metabolites were filtered by step-wise logistic regression with backward elimination, and a model containing uric acid, hypoxanthine, and lysophosphatidylethanolamine was constructed. Receiver-operating characteristic (ROC) analysis confirmed the prognostic value of these parameters for the diagnosis of minimal/mild endometriosis with a sensitivity of 66.7% and a specificity of 90.0%. CONCLUSIONS: Metabolomics analysis of the eutopic endometrium in endometriosis was effectively characterized by UHPLC-ESI-HRMS-based metabolomics. Our study supports the importance of purine and amino acid metabolites in the pathophysiology of endometriosis and provides potential biomarkers for semi-invasive diagnosis of early-stage endometriosis. BioMed Central 2018-04-30 /pmc/articles/PMC5928574/ /pubmed/29712562 http://dx.doi.org/10.1186/s12958-018-0360-z Text en © The Author(s). 2018 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 Li, Jingjie Guan, Lihuan Zhang, Huizhen Gao, Yue Sun, Jiahong Gong, Xiao Li, Dongshun Chen, Pan Liang, Xiaoyan Huang, Min Bi, Huichang Endometrium metabolomic profiling reveals potential biomarkers for diagnosis of endometriosis at minimal-mild stages |
title | Endometrium metabolomic profiling reveals potential biomarkers for diagnosis of endometriosis at minimal-mild stages |
title_full | Endometrium metabolomic profiling reveals potential biomarkers for diagnosis of endometriosis at minimal-mild stages |
title_fullStr | Endometrium metabolomic profiling reveals potential biomarkers for diagnosis of endometriosis at minimal-mild stages |
title_full_unstemmed | Endometrium metabolomic profiling reveals potential biomarkers for diagnosis of endometriosis at minimal-mild stages |
title_short | Endometrium metabolomic profiling reveals potential biomarkers for diagnosis of endometriosis at minimal-mild stages |
title_sort | endometrium metabolomic profiling reveals potential biomarkers for diagnosis of endometriosis at minimal-mild stages |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5928574/ https://www.ncbi.nlm.nih.gov/pubmed/29712562 http://dx.doi.org/10.1186/s12958-018-0360-z |
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