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...

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Main Authors: Rebiya Nuli, Junxiu Cai, Aizhatiguli Kadeer, Yangyi Zhang, Patamu Mohemaiti
Format: Article
Language:English
Published: Frontiers Media S.A. 2019-05-01
Series:Frontiers in Endocrinology
Subjects:
Online Access:https://www.frontiersin.org/article/10.3389/fendo.2019.00295/full
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spelling doaj-b8397f6c251245409d235e97225d7d352020-11-25T01:09:30ZengFrontiers Media S.A.Frontiers in Endocrinology1664-23922019-05-011010.3389/fendo.2019.00295450340Integrative Analysis Toward Different Glucose Tolerance-Related Gut Microbiota and DietRebiya Nuli0Rebiya Nuli1Junxiu Cai2Aizhatiguli Kadeer3Yangyi Zhang4Patamu Mohemaiti5School of Public Health, Xinjiang Medical University, Ürümqi, ChinaCollege of Basic Medical Science, Xinjiang Medical University, Ürümqi, ChinaMedical Department, The Fifth Affiliated Hospital of Xinjiang Medical University, Ürümqi, ChinaSchool of Public Health, Xinjiang Medical University, Ürümqi, ChinaHealth Management Institute, The First Affiliated Hospital of Xinjiang Medical University, Ürümqi, ChinaSchool of Public Health, Xinjiang Medical University, Ürümqi, ChinaObjective: 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.https://www.frontiersin.org/article/10.3389/fendo.2019.00295/fullgut microbiota16S rRNAimpaired glucose regulationtype 2 diabetesUyghurdietary survey
collection DOAJ
language English
format Article
sources DOAJ
author Rebiya Nuli
Rebiya Nuli
Junxiu Cai
Aizhatiguli Kadeer
Yangyi Zhang
Patamu Mohemaiti
spellingShingle Rebiya Nuli
Rebiya Nuli
Junxiu Cai
Aizhatiguli Kadeer
Yangyi Zhang
Patamu Mohemaiti
Integrative Analysis Toward Different Glucose Tolerance-Related Gut Microbiota and Diet
Frontiers in Endocrinology
gut microbiota
16S rRNA
impaired glucose regulation
type 2 diabetes
Uyghur
dietary survey
author_facet Rebiya Nuli
Rebiya Nuli
Junxiu Cai
Aizhatiguli Kadeer
Yangyi Zhang
Patamu Mohemaiti
author_sort Rebiya Nuli
title 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_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_sort integrative analysis toward different glucose tolerance-related gut microbiota and diet
publisher Frontiers Media S.A.
series Frontiers in Endocrinology
issn 1664-2392
publishDate 2019-05-01
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.
topic gut microbiota
16S rRNA
impaired glucose regulation
type 2 diabetes
Uyghur
dietary survey
url https://www.frontiersin.org/article/10.3389/fendo.2019.00295/full
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