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Connections between the human gut microbiome and gestational diabetes mellitus

The human gut microbiome can modulate metabolic health and affect insulin resistance, and it may play an important role in the etiology of gestational diabetes mellitus (GDM). Here, we compared the gut microbial composition of 43 GDM patients and 81 healthy pregnant women via whole-metagenome shotgu...

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Autores principales: Kuang, Ya-Shu, Lu, Jin-Hua, Li, Sheng-Hui, Li, Jun-Hua, Yuan, Ming-Yang, He, Jian-Rong, Chen, Nian-Nian, Xiao, Wan-Qing, Shen, Song-Ying, Qiu, Lan, Wu, Ying-Fang, Hu, Cui-Yue, Wu, Yan-Yan, Li, Wei-Dong, Chen, Qiao-Zhu, Deng, Hong-Wen, Papasian, Christopher J., Xia, Hui-Min, Qiu, Xiu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5597849/
https://www.ncbi.nlm.nih.gov/pubmed/28873967
http://dx.doi.org/10.1093/gigascience/gix058
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author Kuang, Ya-Shu
Lu, Jin-Hua
Li, Sheng-Hui
Li, Jun-Hua
Yuan, Ming-Yang
He, Jian-Rong
Chen, Nian-Nian
Xiao, Wan-Qing
Shen, Song-Ying
Qiu, Lan
Wu, Ying-Fang
Hu, Cui-Yue
Wu, Yan-Yan
Li, Wei-Dong
Chen, Qiao-Zhu
Deng, Hong-Wen
Papasian, Christopher J.
Xia, Hui-Min
Qiu, Xiu
author_facet Kuang, Ya-Shu
Lu, Jin-Hua
Li, Sheng-Hui
Li, Jun-Hua
Yuan, Ming-Yang
He, Jian-Rong
Chen, Nian-Nian
Xiao, Wan-Qing
Shen, Song-Ying
Qiu, Lan
Wu, Ying-Fang
Hu, Cui-Yue
Wu, Yan-Yan
Li, Wei-Dong
Chen, Qiao-Zhu
Deng, Hong-Wen
Papasian, Christopher J.
Xia, Hui-Min
Qiu, Xiu
author_sort Kuang, Ya-Shu
collection PubMed
description The human gut microbiome can modulate metabolic health and affect insulin resistance, and it may play an important role in the etiology of gestational diabetes mellitus (GDM). Here, we compared the gut microbial composition of 43 GDM patients and 81 healthy pregnant women via whole-metagenome shotgun sequencing of their fecal samples, collected at 21–29 weeks, to explore associations between GDM and the composition of microbial taxonomic units and functional genes. A metagenome-wide association study identified 154 837 genes, which clustered into 129 metagenome linkage groups (MLGs) for species description, with significant relative abundance differences between the 2 cohorts. Parabacteroides distasonis, Klebsiella variicola, etc., were enriched in GDM patients, whereas Methanobrevibacter smithii, Alistipes spp., Bifidobacterium spp., and Eubacterium spp. were enriched in controls. The ratios of the gross abundances of GDM-enriched MLGs to control-enriched MLGs were positively correlated with blood glucose levels. A random forest model shows that fecal MLGs have excellent discriminatory power to predict GDM status. Our study discovered novel relationships between the gut microbiome and GDM status and suggests that changes in microbial composition may potentially be used to identify individuals at risk for GDM.
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spelling pubmed-55978492017-09-19 Connections between the human gut microbiome and gestational diabetes mellitus Kuang, Ya-Shu Lu, Jin-Hua Li, Sheng-Hui Li, Jun-Hua Yuan, Ming-Yang He, Jian-Rong Chen, Nian-Nian Xiao, Wan-Qing Shen, Song-Ying Qiu, Lan Wu, Ying-Fang Hu, Cui-Yue Wu, Yan-Yan Li, Wei-Dong Chen, Qiao-Zhu Deng, Hong-Wen Papasian, Christopher J. Xia, Hui-Min Qiu, Xiu Gigascience Research The human gut microbiome can modulate metabolic health and affect insulin resistance, and it may play an important role in the etiology of gestational diabetes mellitus (GDM). Here, we compared the gut microbial composition of 43 GDM patients and 81 healthy pregnant women via whole-metagenome shotgun sequencing of their fecal samples, collected at 21–29 weeks, to explore associations between GDM and the composition of microbial taxonomic units and functional genes. A metagenome-wide association study identified 154 837 genes, which clustered into 129 metagenome linkage groups (MLGs) for species description, with significant relative abundance differences between the 2 cohorts. Parabacteroides distasonis, Klebsiella variicola, etc., were enriched in GDM patients, whereas Methanobrevibacter smithii, Alistipes spp., Bifidobacterium spp., and Eubacterium spp. were enriched in controls. The ratios of the gross abundances of GDM-enriched MLGs to control-enriched MLGs were positively correlated with blood glucose levels. A random forest model shows that fecal MLGs have excellent discriminatory power to predict GDM status. Our study discovered novel relationships between the gut microbiome and GDM status and suggests that changes in microbial composition may potentially be used to identify individuals at risk for GDM. Oxford University Press 2017-07-31 /pmc/articles/PMC5597849/ /pubmed/28873967 http://dx.doi.org/10.1093/gigascience/gix058 Text en © The Author 2017. Published by Oxford University Press. 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 reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research
Kuang, Ya-Shu
Lu, Jin-Hua
Li, Sheng-Hui
Li, Jun-Hua
Yuan, Ming-Yang
He, Jian-Rong
Chen, Nian-Nian
Xiao, Wan-Qing
Shen, Song-Ying
Qiu, Lan
Wu, Ying-Fang
Hu, Cui-Yue
Wu, Yan-Yan
Li, Wei-Dong
Chen, Qiao-Zhu
Deng, Hong-Wen
Papasian, Christopher J.
Xia, Hui-Min
Qiu, Xiu
Connections between the human gut microbiome and gestational diabetes mellitus
title Connections between the human gut microbiome and gestational diabetes mellitus
title_full Connections between the human gut microbiome and gestational diabetes mellitus
title_fullStr Connections between the human gut microbiome and gestational diabetes mellitus
title_full_unstemmed Connections between the human gut microbiome and gestational diabetes mellitus
title_short Connections between the human gut microbiome and gestational diabetes mellitus
title_sort connections between the human gut microbiome and gestational diabetes mellitus
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5597849/
https://www.ncbi.nlm.nih.gov/pubmed/28873967
http://dx.doi.org/10.1093/gigascience/gix058
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