Microbiome and metabolome dysbiosis analysis in impaired glucose tolerance for the prediction of progression to diabetes mellitus

被引:6
|
作者
Zhang, Boxun [1 ]
Zhang, Xuan [2 ,3 ]
Luo, Zhen [4 ]
Ren, Jixiang [5 ]
Yu, Xiaotong [6 ]
Zhao, Haiyan [7 ]
Wang, Yitian [8 ]
Zhang, Wenhui [3 ,9 ]
Tian, Weiwei [7 ]
Wei, Xiuxiu [10 ]
Ding, Qiyou [1 ]
Yang, Haoyu [1 ]
Jin, Zishan [1 ,10 ]
Tong, Xiaolin [1 ,11 ]
Wang, Jun [3 ,9 ]
Zhao, Linhua [1 ]
机构
[1] China Acad Chinese Med Sci, Guanganmen Hosp, Inst Metab Dis, Beijing 100053, Peoples R China
[2] Baotou Teachers Coll, Fac Biol Sci & Technol, Baotou 014030, Inner Mongolia, Peoples R China
[3] Chinese Acad Sci, Inst Microbiol, CAS Key Lab Pathogen Microbiol & Immunol, Beijing 100101, Peoples R China
[4] Infinitus China Co Ltd, Guangzhou 510405, Guangdong, Peoples R China
[5] Changchun Univ Chinese Med, Affiliated Hosp, Changchun 130021, Jilin, Peoples R China
[6] China Acad Chinese Med Sci, Guanganmen Hosp, Dept Endocrinol, Beijing 100053, Peoples R China
[7] Xinjiekou Community Hlth Serv Ctr Xicheng Dist, Beijing 100035, Peoples R China
[8] Shenzhen Tradit Chinese Med Hosp, Dept Spleen & Stomach, Shenzhen 518033, Guangdong, Peoples R China
[9] Univ Chinese Acad Sci, Beijing 100049, Peoples R China
[10] Beijing Univ Chinese Med, Beijing 100105, Peoples R China
[11] Changchun Univ Chinese Med, Northeast Asia Inst Tradit Chinese Med, Changchun 130117, Jilin, Peoples R China
基金
中国国家自然科学基金;
关键词
Impaired glucose tolerance; Diabetes mellitus; Gut microbiota; Metabolomics; METAGENOME-WIDE ASSOCIATION; GUT MICROBIOTA; TYPE-2; PREVENTION; VALIDATION; RISK;
D O I
10.1016/j.jgg.2023.08.005
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Gut microbiota and circulating metabolite dysbiosis predate important pathological changes in glucose metabolic disorders; however, comprehensive studies on impaired glucose tolerance (IGT), a diabetes mellitus (DM) precursor, are lacking. Here, we perform metagenomic sequencing and metabolomics on 47 pairs of individuals with IGT and newly diagnosed DM and 46 controls with normal glucose tolerance (NGT); patients with IGT are followed up after 4 years for progression to DM. Analysis of baseline data reveals significant differences in gut microbiota and serum metabolites among the IGT, DM, and NGT groups. In addition, 13 types of gut microbiota and 17 types of circulating metabolites showed significant differences at baseline before IGT progressed to DM, including higher levels of Eggerthella unclassified, Coprobacillus unclassified, Clostridium ramosum, L-valine, L-norleucine, and L-isoleucine, and lower levels of Eubacterium eligens, Bacteroides faecis, Lachnospiraceae bacterium 3_1_46FAA, Alistipes senegalensis, Megaspaera elsdenii, Clostridium perfringens, a-linolenic acid, 10E,12Z-octadecadienoic acid, and dodecanoic acid. A random forest model based on differential intestinal microbiota and circulating metabolites can predict the progression from IGT to DM (AUC 1/4 0.87). These results suggest that microbiome and metabolome dysbiosis occur in individuals with IGT and have important predictive values and potential for intervention in preventing IGT from progressing to DM. Copyright (c) 2023, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, and Genetics Society of China. Published by Elsevier Limited and Science Press. All rights reserved.
引用
收藏
页码:75 / 86
页数:12
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