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Integrative Analysis Toward Different Glucose Tolerance-Related Gut Microbiota and Diet
Objective: There is evidence that type 2 diabetes (T2DM) is affected by gut microbiota, and gut microbiota diversity modified by diet. To investigate its modifications in Uyghur patients with different glucose tolerance, we enrolled 561 subjects: newly diagnosed T2DM (n = 145), impaired glucose regu...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6546033/ https://www.ncbi.nlm.nih.gov/pubmed/31191448 http://dx.doi.org/10.3389/fendo.2019.00295 |
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author | Nuli, Rebiya Cai, Junxiu Kadeer, Aizhatiguli Zhang, Yangyi Mohemaiti, Patamu |
author_facet | Nuli, Rebiya Cai, Junxiu Kadeer, Aizhatiguli Zhang, Yangyi Mohemaiti, Patamu |
author_sort | Nuli, Rebiya |
collection | PubMed |
description | Objective: There is evidence that type 2 diabetes (T2DM) is affected by gut microbiota, and gut microbiota diversity modified by diet. To investigate its modifications in Uyghur patients with different glucose tolerance, we enrolled 561 subjects: newly diagnosed T2DM (n = 145), impaired glucose regulation (IGR) patients (n = 138) and in normal control (NC) population (n = 278). Methods: The nutrient intake in food frequency questionnaire was calculated by R language. The regions V3-V4 of 16S ribosomal RNA were sequenced by using Illumina Miseq platform. Sequences were clustered by operational taxonomy units, gut microbiota composition, and diversity was analyzed. Correlations between bacterial composition at different level and dietary factors were evaluated. Results: The α-diversity was highest in NC, followed by T2DM and IGR; β-diversity distinguished between patients and NC. Compared to NC, Saccharibacteria was significantly increased in T2DM and IGR. Deferribacteres was significantly increased in T2DM compared to NC and IGR. Veillonella, Pasteurellaceae, and Haemophilus were over-represented in IGR. Abundance of Bacteroidetes was negatively correlated with LDL-C; Abundance of Tenericutes was negatively correlated with hip circumference and total cholesterol, positively correlated with HDL-C and cake intake; Actinobacteria was positively correlated with BMI and folic acid intake, negatively correlated with oil intake. Firmicutes was negatively correlated with beverage and alcohol intake. Spirochaetae was negatively correlated with fungus, fruits, beans, vitamin C, dietary fiber, and calcium. Fusobacteria was positively correlated with beans intake, and was negatively correlated with fat intake. Proteobacteria was positively correlated with tuber crops intake. Synergistetes was positively correlated with cholesterol, nicotinic acid, and selenium intake. Deferribacteres was negatively correlated with magnesium intake. Conclusions: At the phylum and genus level, the structure and diversity of intestinal microbiota of T2DM and IGR was altered, the number of OTUs, the relative abundance, and diversity were all decreased. The gut microbiota of the newly diagnosed T2DM, IGR, and NC were related to age, blood lipids, BMI, blood pressure, and dietary nutrient intake. Unbalanced nutrient intake in the three groups may affect the structure and abundance of the gut microbiota, which may play a role in the occurrence and development of T2DM. |
format | Online Article Text |
id | pubmed-6546033 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-65460332019-06-12 Integrative Analysis Toward Different Glucose Tolerance-Related Gut Microbiota and Diet Nuli, Rebiya Cai, Junxiu Kadeer, Aizhatiguli Zhang, Yangyi Mohemaiti, Patamu Front Endocrinol (Lausanne) Endocrinology Objective: There is evidence that type 2 diabetes (T2DM) is affected by gut microbiota, and gut microbiota diversity modified by diet. To investigate its modifications in Uyghur patients with different glucose tolerance, we enrolled 561 subjects: newly diagnosed T2DM (n = 145), impaired glucose regulation (IGR) patients (n = 138) and in normal control (NC) population (n = 278). Methods: The nutrient intake in food frequency questionnaire was calculated by R language. The regions V3-V4 of 16S ribosomal RNA were sequenced by using Illumina Miseq platform. Sequences were clustered by operational taxonomy units, gut microbiota composition, and diversity was analyzed. Correlations between bacterial composition at different level and dietary factors were evaluated. Results: The α-diversity was highest in NC, followed by T2DM and IGR; β-diversity distinguished between patients and NC. Compared to NC, Saccharibacteria was significantly increased in T2DM and IGR. Deferribacteres was significantly increased in T2DM compared to NC and IGR. Veillonella, Pasteurellaceae, and Haemophilus were over-represented in IGR. Abundance of Bacteroidetes was negatively correlated with LDL-C; Abundance of Tenericutes was negatively correlated with hip circumference and total cholesterol, positively correlated with HDL-C and cake intake; Actinobacteria was positively correlated with BMI and folic acid intake, negatively correlated with oil intake. Firmicutes was negatively correlated with beverage and alcohol intake. Spirochaetae was negatively correlated with fungus, fruits, beans, vitamin C, dietary fiber, and calcium. Fusobacteria was positively correlated with beans intake, and was negatively correlated with fat intake. Proteobacteria was positively correlated with tuber crops intake. Synergistetes was positively correlated with cholesterol, nicotinic acid, and selenium intake. Deferribacteres was negatively correlated with magnesium intake. Conclusions: At the phylum and genus level, the structure and diversity of intestinal microbiota of T2DM and IGR was altered, the number of OTUs, the relative abundance, and diversity were all decreased. The gut microbiota of the newly diagnosed T2DM, IGR, and NC were related to age, blood lipids, BMI, blood pressure, and dietary nutrient intake. Unbalanced nutrient intake in the three groups may affect the structure and abundance of the gut microbiota, which may play a role in the occurrence and development of T2DM. Frontiers Media S.A. 2019-05-27 /pmc/articles/PMC6546033/ /pubmed/31191448 http://dx.doi.org/10.3389/fendo.2019.00295 Text en Copyright © 2019 Nuli, Cai, Kadeer, Zhang and Mohemaiti. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Endocrinology Nuli, Rebiya Cai, Junxiu Kadeer, Aizhatiguli Zhang, Yangyi Mohemaiti, Patamu Integrative Analysis Toward Different Glucose Tolerance-Related Gut Microbiota and Diet |
title | Integrative Analysis Toward Different Glucose Tolerance-Related Gut Microbiota and Diet |
title_full | Integrative Analysis Toward Different Glucose Tolerance-Related Gut Microbiota and Diet |
title_fullStr | Integrative Analysis Toward Different Glucose Tolerance-Related Gut Microbiota and Diet |
title_full_unstemmed | Integrative Analysis Toward Different Glucose Tolerance-Related Gut Microbiota and Diet |
title_short | Integrative Analysis Toward Different Glucose Tolerance-Related Gut Microbiota and Diet |
title_sort | integrative analysis toward different glucose tolerance-related gut microbiota and diet |
topic | Endocrinology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6546033/ https://www.ncbi.nlm.nih.gov/pubmed/31191448 http://dx.doi.org/10.3389/fendo.2019.00295 |
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