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Preterm birth is associated with xenobiotics and predicted by the vaginal metabolome
Spontaneous preterm birth (sPTB) is a leading cause of maternal and neonatal morbidity and mortality, yet its prevention and early risk stratification are limited. Previous investigations have suggested that vaginal microbes and metabolites may be implicated in sPTB. Here we performed untargeted met...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9894755/ https://www.ncbi.nlm.nih.gov/pubmed/36635575 http://dx.doi.org/10.1038/s41564-022-01293-8 |
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author | Kindschuh, William F. Baldini, Federico Liu, Martin C. Liao, Jingqiu Meydan, Yoli Lee, Harry H. Heinken, Almut Thiele, Ines Thaiss, Christoph A. Levy, Maayan Korem, Tal |
author_facet | Kindschuh, William F. Baldini, Federico Liu, Martin C. Liao, Jingqiu Meydan, Yoli Lee, Harry H. Heinken, Almut Thiele, Ines Thaiss, Christoph A. Levy, Maayan Korem, Tal |
author_sort | Kindschuh, William F. |
collection | PubMed |
description | Spontaneous preterm birth (sPTB) is a leading cause of maternal and neonatal morbidity and mortality, yet its prevention and early risk stratification are limited. Previous investigations have suggested that vaginal microbes and metabolites may be implicated in sPTB. Here we performed untargeted metabolomics on 232 second-trimester vaginal samples, 80 from pregnancies ending preterm. We find multiple associations between vaginal metabolites and subsequent preterm birth, and propose that several of these metabolites, including diethanolamine and ethyl glucoside, are exogenous. We observe associations between the metabolome and microbiome profiles previously obtained using 16S ribosomal RNA amplicon sequencing, including correlations between bacteria considered suboptimal, such as Gardnerella vaginalis, and metabolites enriched in term pregnancies, such as tyramine. We investigate these associations using metabolic models. We use machine learning models to predict sPTB risk from metabolite levels, weeks to months before birth, with good accuracy (area under receiver operating characteristic curve of 0.78). These models, which we validate using two external cohorts, are more accurate than microbiome-based and maternal covariates-based models (area under receiver operating characteristic curve of 0.55–0.59). Our results demonstrate the potential of vaginal metabolites as early biomarkers of sPTB and highlight exogenous exposures as potential risk factors for prematurity. |
format | Online Article Text |
id | pubmed-9894755 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-98947552023-02-04 Preterm birth is associated with xenobiotics and predicted by the vaginal metabolome Kindschuh, William F. Baldini, Federico Liu, Martin C. Liao, Jingqiu Meydan, Yoli Lee, Harry H. Heinken, Almut Thiele, Ines Thaiss, Christoph A. Levy, Maayan Korem, Tal Nat Microbiol Article Spontaneous preterm birth (sPTB) is a leading cause of maternal and neonatal morbidity and mortality, yet its prevention and early risk stratification are limited. Previous investigations have suggested that vaginal microbes and metabolites may be implicated in sPTB. Here we performed untargeted metabolomics on 232 second-trimester vaginal samples, 80 from pregnancies ending preterm. We find multiple associations between vaginal metabolites and subsequent preterm birth, and propose that several of these metabolites, including diethanolamine and ethyl glucoside, are exogenous. We observe associations between the metabolome and microbiome profiles previously obtained using 16S ribosomal RNA amplicon sequencing, including correlations between bacteria considered suboptimal, such as Gardnerella vaginalis, and metabolites enriched in term pregnancies, such as tyramine. We investigate these associations using metabolic models. We use machine learning models to predict sPTB risk from metabolite levels, weeks to months before birth, with good accuracy (area under receiver operating characteristic curve of 0.78). These models, which we validate using two external cohorts, are more accurate than microbiome-based and maternal covariates-based models (area under receiver operating characteristic curve of 0.55–0.59). Our results demonstrate the potential of vaginal metabolites as early biomarkers of sPTB and highlight exogenous exposures as potential risk factors for prematurity. Nature Publishing Group UK 2023-01-12 2023 /pmc/articles/PMC9894755/ /pubmed/36635575 http://dx.doi.org/10.1038/s41564-022-01293-8 Text en © The Author(s) 2023, corrected publication 2023 https://creativecommons.org/licenses/by/4.0/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/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Kindschuh, William F. Baldini, Federico Liu, Martin C. Liao, Jingqiu Meydan, Yoli Lee, Harry H. Heinken, Almut Thiele, Ines Thaiss, Christoph A. Levy, Maayan Korem, Tal Preterm birth is associated with xenobiotics and predicted by the vaginal metabolome |
title | Preterm birth is associated with xenobiotics and predicted by the vaginal metabolome |
title_full | Preterm birth is associated with xenobiotics and predicted by the vaginal metabolome |
title_fullStr | Preterm birth is associated with xenobiotics and predicted by the vaginal metabolome |
title_full_unstemmed | Preterm birth is associated with xenobiotics and predicted by the vaginal metabolome |
title_short | Preterm birth is associated with xenobiotics and predicted by the vaginal metabolome |
title_sort | preterm birth is associated with xenobiotics and predicted by the vaginal metabolome |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9894755/ https://www.ncbi.nlm.nih.gov/pubmed/36635575 http://dx.doi.org/10.1038/s41564-022-01293-8 |
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