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Characterizing semen abnormality male infertility using non-targeted blood plasma metabolomics

Semen abnormality (SA) male infertility has become a worldwide reproductive health problem. The invasive tests (e.g., testicular biopsy) and labor-intensive methods of semen collection severely inhibit diagnosis of male infertility. In addition, the pathogenesis and biological interpretation of male...

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Autores principales: Ma, Pan, Zhang, Zhimin, Zhou, Xinyi, Luo, Jiekun, Lu, Hongmei, Wang, Yang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6611580/
https://www.ncbi.nlm.nih.gov/pubmed/31276533
http://dx.doi.org/10.1371/journal.pone.0219179
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author Ma, Pan
Zhang, Zhimin
Zhou, Xinyi
Luo, Jiekun
Lu, Hongmei
Wang, Yang
author_facet Ma, Pan
Zhang, Zhimin
Zhou, Xinyi
Luo, Jiekun
Lu, Hongmei
Wang, Yang
author_sort Ma, Pan
collection PubMed
description Semen abnormality (SA) male infertility has become a worldwide reproductive health problem. The invasive tests (e.g., testicular biopsy) and labor-intensive methods of semen collection severely inhibit diagnosis of male infertility. In addition, the pathogenesis and biological interpretation of male infertility are still obscure. In this report, a total of 84 semen abnormality (SA) patients, diagnosed as teratozoospermia (TE, n = 21), asthenozoospermia (AS, n = 23), oligozoospermia (OL, n = 20), azoospermia (AZ, n = 20), and age-matched healthy controls (HC, n = 29) were analyzed by GC-MS for discrimination analysis and discovery of potential biomarkers. Twenty-three biomarkers were obtained by multivariate statistical method (partial least squares-discriminant analysis, PLS-DA) and univariate statistical method (analysis of variance, ANOVA) with comparisons of TE versus HC, AS versus HC, OL versus HC and AZ versus HC. Based on those biomarkers, the most relevant pathways were mainly associated with the metabolism of carbohydrates, amino acids, and lipids. The principal metabolic alternations in SA male infertility included increased levels of energy-related metabolisms, such as tricarboxylic acid cycle, pyruvate metabolism, glyoxylate and dicarboxylate metabolism, glycine, serine, threonine metabolism and saturated fatty acid metabolism. Furthermore, increased levels of glutathione metabolism were related to oxidative stress. Finally, decreased levels of arginine and proline metabolism and inositol phosphate metabolism were observed. In conclusion, blood plasma metabolomics is powerful for characterizing metabolic disturbances in SA male infertility. From metabolic pathway analysis, energy production, oxidation stress and the released enzyme during spermatogenesis take the primary responsibilities for SA male infertility.
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spelling pubmed-66115802019-07-12 Characterizing semen abnormality male infertility using non-targeted blood plasma metabolomics Ma, Pan Zhang, Zhimin Zhou, Xinyi Luo, Jiekun Lu, Hongmei Wang, Yang PLoS One Research Article Semen abnormality (SA) male infertility has become a worldwide reproductive health problem. The invasive tests (e.g., testicular biopsy) and labor-intensive methods of semen collection severely inhibit diagnosis of male infertility. In addition, the pathogenesis and biological interpretation of male infertility are still obscure. In this report, a total of 84 semen abnormality (SA) patients, diagnosed as teratozoospermia (TE, n = 21), asthenozoospermia (AS, n = 23), oligozoospermia (OL, n = 20), azoospermia (AZ, n = 20), and age-matched healthy controls (HC, n = 29) were analyzed by GC-MS for discrimination analysis and discovery of potential biomarkers. Twenty-three biomarkers were obtained by multivariate statistical method (partial least squares-discriminant analysis, PLS-DA) and univariate statistical method (analysis of variance, ANOVA) with comparisons of TE versus HC, AS versus HC, OL versus HC and AZ versus HC. Based on those biomarkers, the most relevant pathways were mainly associated with the metabolism of carbohydrates, amino acids, and lipids. The principal metabolic alternations in SA male infertility included increased levels of energy-related metabolisms, such as tricarboxylic acid cycle, pyruvate metabolism, glyoxylate and dicarboxylate metabolism, glycine, serine, threonine metabolism and saturated fatty acid metabolism. Furthermore, increased levels of glutathione metabolism were related to oxidative stress. Finally, decreased levels of arginine and proline metabolism and inositol phosphate metabolism were observed. In conclusion, blood plasma metabolomics is powerful for characterizing metabolic disturbances in SA male infertility. From metabolic pathway analysis, energy production, oxidation stress and the released enzyme during spermatogenesis take the primary responsibilities for SA male infertility. Public Library of Science 2019-07-05 /pmc/articles/PMC6611580/ /pubmed/31276533 http://dx.doi.org/10.1371/journal.pone.0219179 Text en © 2019 Ma et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Ma, Pan
Zhang, Zhimin
Zhou, Xinyi
Luo, Jiekun
Lu, Hongmei
Wang, Yang
Characterizing semen abnormality male infertility using non-targeted blood plasma metabolomics
title Characterizing semen abnormality male infertility using non-targeted blood plasma metabolomics
title_full Characterizing semen abnormality male infertility using non-targeted blood plasma metabolomics
title_fullStr Characterizing semen abnormality male infertility using non-targeted blood plasma metabolomics
title_full_unstemmed Characterizing semen abnormality male infertility using non-targeted blood plasma metabolomics
title_short Characterizing semen abnormality male infertility using non-targeted blood plasma metabolomics
title_sort characterizing semen abnormality male infertility using non-targeted blood plasma metabolomics
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6611580/
https://www.ncbi.nlm.nih.gov/pubmed/31276533
http://dx.doi.org/10.1371/journal.pone.0219179
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