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First-trimester vaginal microbiome diversity: A potential indicator of preterm delivery risk

Preterm birth is a leading cause of global neonate mortality. Hospitalization costs associated with preterm deliveries present a huge economic burden. Existing physical/biochemical markers for predicting preterm birth risk are mostly suited for application at mid/late pregnancy stages, thereby leavi...

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Autores principales: Haque, Mohammed Monzoorul, Merchant, Mitali, Kumar, Pinna Nishal, Dutta, Anirban, Mande, Sharmila S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5700938/
https://www.ncbi.nlm.nih.gov/pubmed/29170495
http://dx.doi.org/10.1038/s41598-017-16352-y
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author Haque, Mohammed Monzoorul
Merchant, Mitali
Kumar, Pinna Nishal
Dutta, Anirban
Mande, Sharmila S.
author_facet Haque, Mohammed Monzoorul
Merchant, Mitali
Kumar, Pinna Nishal
Dutta, Anirban
Mande, Sharmila S.
author_sort Haque, Mohammed Monzoorul
collection PubMed
description Preterm birth is a leading cause of global neonate mortality. Hospitalization costs associated with preterm deliveries present a huge economic burden. Existing physical/biochemical markers for predicting preterm birth risk are mostly suited for application at mid/late pregnancy stages, thereby leaving very short time (between diagnosis and delivery) for adopting appropriate intervention strategies. Recent studies indicating correlations between pre/full-term delivery and the composition of vaginal microbiota in pregnant women have opened new diagnostic possibilities. In this study, we performed a thorough meta-analysis of vaginal microbiome datasets to evaluate the utility of popular diversity and inequality measures for predicting, at an early stage, the risk of preterm delivery. Results indicate significant differences (in diversity measures) between ‘first-trimester’ vaginal microbiomes obtained from women with term and preterm outcomes, indicating the potential diagnostic utility of these measures. In this context, we introduce a novel diversity metric that has significantly better diagnostic ability as compared to established diversity measures. The metric enables ‘early’ and highly accurate prediction of preterm delivery outcomes, and can potentially be deployed in clinical settings for preterm birth risk-assessment. Our findings have potentially far reaching implications in the fight against neonatal deaths due to preterm birth.
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spelling pubmed-57009382017-11-30 First-trimester vaginal microbiome diversity: A potential indicator of preterm delivery risk Haque, Mohammed Monzoorul Merchant, Mitali Kumar, Pinna Nishal Dutta, Anirban Mande, Sharmila S. Sci Rep Article Preterm birth is a leading cause of global neonate mortality. Hospitalization costs associated with preterm deliveries present a huge economic burden. Existing physical/biochemical markers for predicting preterm birth risk are mostly suited for application at mid/late pregnancy stages, thereby leaving very short time (between diagnosis and delivery) for adopting appropriate intervention strategies. Recent studies indicating correlations between pre/full-term delivery and the composition of vaginal microbiota in pregnant women have opened new diagnostic possibilities. In this study, we performed a thorough meta-analysis of vaginal microbiome datasets to evaluate the utility of popular diversity and inequality measures for predicting, at an early stage, the risk of preterm delivery. Results indicate significant differences (in diversity measures) between ‘first-trimester’ vaginal microbiomes obtained from women with term and preterm outcomes, indicating the potential diagnostic utility of these measures. In this context, we introduce a novel diversity metric that has significantly better diagnostic ability as compared to established diversity measures. The metric enables ‘early’ and highly accurate prediction of preterm delivery outcomes, and can potentially be deployed in clinical settings for preterm birth risk-assessment. Our findings have potentially far reaching implications in the fight against neonatal deaths due to preterm birth. Nature Publishing Group UK 2017-11-23 /pmc/articles/PMC5700938/ /pubmed/29170495 http://dx.doi.org/10.1038/s41598-017-16352-y Text en © The Author(s) 2017 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
Haque, Mohammed Monzoorul
Merchant, Mitali
Kumar, Pinna Nishal
Dutta, Anirban
Mande, Sharmila S.
First-trimester vaginal microbiome diversity: A potential indicator of preterm delivery risk
title First-trimester vaginal microbiome diversity: A potential indicator of preterm delivery risk
title_full First-trimester vaginal microbiome diversity: A potential indicator of preterm delivery risk
title_fullStr First-trimester vaginal microbiome diversity: A potential indicator of preterm delivery risk
title_full_unstemmed First-trimester vaginal microbiome diversity: A potential indicator of preterm delivery risk
title_short First-trimester vaginal microbiome diversity: A potential indicator of preterm delivery risk
title_sort first-trimester vaginal microbiome diversity: a potential indicator of preterm delivery risk
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5700938/
https://www.ncbi.nlm.nih.gov/pubmed/29170495
http://dx.doi.org/10.1038/s41598-017-16352-y
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