Association of Insulin Resistance and Type 2 Diabetes With Gut Microbial Diversity

胰岛素抵抗 2型糖尿病 人口 微生物群 糖尿病 混淆 生物 β多样性 医学 老年学 人口学 内科学 生态学 物种丰富度 环境卫生 生物信息学 内分泌学 社会学
作者
Zhangling Chen,Djawad Radjabzadeh,Lianmin Chen,Alexander Kurilshikov,Maryam Kavousi,Fariba Ahmadizar,M. Arfan Ikram,André G. Uitterlinden,Alexandra Zhernakova,Jingyuan Fu,Robert Kraaij,Trudy Voortman
出处
期刊:JAMA network open [American Medical Association]
卷期号:4 (7): e2118811-e2118811 被引量:127
标识
DOI:10.1001/jamanetworkopen.2021.18811
摘要

Previous studies have indicated that gut microbiome may be associated with development of type 2 diabetes. However, these studies are limited by small sample size and insufficient for confounding. Furthermore, which specific taxa play a role in the development of type 2 diabetes remains unclear.To examine associations of gut microbiome composition with insulin resistance and type 2 diabetes in a large population-based setting controlling for various sociodemographic and lifestyle factors.This cross-sectional analysis included 2166 participants from 2 Dutch population-based prospective cohorts: the Rotterdam Study and the LifeLines-DEEP study.The 16S ribosomal RNA method was used to measure microbiome composition in stool samples collected between January 1, 2012, and December 31, 2013. The α diversity (Shannon, richness, and Inverse Simpson indexes), β diversity (Bray-Curtis dissimilarity matrix), and taxa (from domain to genus level) were identified to reflect gut microbiome composition.Associations among α diversity, β diversity, and taxa with the Homeostatic Model Assessment of Insulin Resistance (HOMA-IR) and with type 2 diabetes were examined. Glucose and insulin were measured to calculate the HOMA-IR. Type 2 diabetes cases were identified based on glucose levels and medical records from January 2012 to December 2013. Analyses were adjusted for technical covariates, lifestyle, sociodemographic, and medical factors. Data analysis was performed from January 1, 2018, to December 31, 2020.There were 2166 participants in this study: 1418 from the Rotterdam Study (mean [SD] age, 62.4 [5.9] years; 815 [57.5%] male) and 748 from the LifeLines-DEEP study (mean [SD] age, 44.7 [13.4] years; 431 [57.6%] male); from this total, 193 type 2 diabetes cases were identified. Lower microbiome Shannon index and richness were associated with higher HOMA-IR (eg, Shannon index, -0.06; 95% CI, -0.10 to -0.02), and patients with type 2 diabetes had a lower richness than participants without diabetes (odds ratio [OR], 0.93; 95% CI, 0.88-0.99). The β diversity (Bray-Curtis dissimilarity matrix) was associated with insulin resistance (R2 = 0.004, P = .001 in the Rotterdam Study and R2 = 0.005, P = .002 in the LifeLines-DEEP study). A total of 12 groups of bacteria were associated with HOMA-IR or type 2 diabetes. Specifically, a higher abundance of Christensenellaceae (β = -0.08; 95% CI, -0.12 to -0.03: P < .001), Christensenellaceae R7 group (β = -0.07; 95% CI, -0.12 to -0.03; P < .001), Marvinbryantia (β = -0.07; 95% CI, -0.11 to -0.03; P < .001), Ruminococcaceae UCG005 (β = -0.09; 95% CI, -0.13 to -0.05; P < .001), Ruminococcaceae UCG008 (β = -0.07; 95% CI, -0.11 to -0.03; P < .001), Ruminococcaceae UCG010 (β = -0.08; 95% CI, -0.12 to -0.04; P < .001), or Ruminococcaceae NK4A214 group (β = -0.09; 95% CI, -0.13 to -0.05; P < .001) was associated with lower HOMA-IR. A higher abundance of Clostridiaceae 1 (OR, 0.51; 95% CI, 0.41-0.65; P < .001), Peptostreptococcaceae (OR, 0.56; 95% CI, 0.45-0.70; P < .001), C sensu stricto 1 (OR, 0.51; 95% CI, 0.40-0.65; P < .001), Intestinibacter (OR, 0.60; 95% CI, 0.48-0.76; P < .001), or Romboutsia (OR, 0.55; 95% CI, 0.44-0.70; P < .001) was associated with less type 2 diabetes. These bacteria are all known to produce butyrate.In this cross-sectional study, higher microbiome α diversity, along with more butyrate-producing gut bacteria, was associated with less type 2 diabetes and with lower insulin resistance among individuals without diabetes. These findings could help provide insight into the etiology, pathogenesis, and treatment of type 2 diabetes.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
FartKing完成签到,获得积分10
刚刚
咩咩羊发布了新的文献求助10
1秒前
1秒前
量子星尘发布了新的文献求助10
3秒前
kjinm完成签到,获得积分20
3秒前
Hoolyshit发布了新的文献求助10
3秒前
聪慧小霜应助Impurity采纳,获得10
4秒前
CCC发布了新的文献求助10
5秒前
FartKing发布了新的文献求助10
5秒前
5秒前
科研通AI2S应助杜儒采纳,获得10
5秒前
柚子完成签到,获得积分10
7秒前
面包小狗完成签到,获得积分10
9秒前
narthon发布了新的文献求助10
9秒前
9秒前
HuanChen完成签到,获得积分10
10秒前
肆_完成签到 ,获得积分10
10秒前
汉堡大王关注了科研通微信公众号
10秒前
f冯完成签到,获得积分10
11秒前
我是老大应助z猪猪采纳,获得10
11秒前
11秒前
12秒前
面包小狗发布了新的文献求助10
12秒前
www完成签到,获得积分10
13秒前
Owen应助czy0818采纳,获得10
13秒前
guan完成签到,获得积分10
13秒前
思源应助xiaoguai4545采纳,获得10
15秒前
15秒前
biomds完成签到,获得积分10
16秒前
sresr完成签到,获得积分10
16秒前
17秒前
量子星尘发布了新的文献求助10
17秒前
酷波er应助Sugar采纳,获得10
18秒前
CCC完成签到,获得积分10
19秒前
JamesPei应助跳跃采纳,获得10
19秒前
guan发布了新的文献求助20
21秒前
Sarahminn发布了新的文献求助10
21秒前
Tata应助斯文懿轩采纳,获得10
23秒前
华仔应助喜悦念柏采纳,获得20
24秒前
26秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
计划经济时代的工厂管理与工人状况(1949-1966)——以郑州市国营工厂为例 500
INQUIRY-BASED PEDAGOGY TO SUPPORT STEM LEARNING AND 21ST CENTURY SKILLS: PREPARING NEW TEACHERS TO IMPLEMENT PROJECT AND PROBLEM-BASED LEARNING 500
The Pedagogical Leadership in the Early Years (PLEY) Quality Rating Scale 410
Modern Britain, 1750 to the Present (第2版) 300
Writing to the Rhythm of Labor Cultural Politics of the Chinese Revolution, 1942–1976 300
Lightning Wires: The Telegraph and China's Technological Modernization, 1860-1890 250
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 物理化学 基因 催化作用 遗传学 冶金 电极 光电子学
热门帖子
关注 科研通微信公众号,转发送积分 4601983
求助须知:如何正确求助?哪些是违规求助? 4011438
关于积分的说明 12419208
捐赠科研通 3691523
什么是DOI,文献DOI怎么找? 2035123
邀请新用户注册赠送积分活动 1068423
科研通“疑难数据库(出版商)”最低求助积分说明 952869