期刊
COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL
卷 18, 期 -, 页码 2596-2609出版社
ELSEVIER
DOI: 10.1016/j.csbj.2020.09.026
关键词
Gut microbiome; Obesity; Visceral fat; Laparoscopic sleeve gastrectomy; Metagenomics
资金
- National Key RAMP
- D Program of China [2016YFA0502003]
Purpose: Visceral fat is an independent risk factor for metabolic and cardiovascular disease. The study aimed to investigate the associations between gut microbiome and visceral fat. Methods: We recruited 32 obese adults and 30 healthy controls at baseline. Among the obese subjects, 14 subjects underwent laparoscopic sleeve gastrectomy (LSG) and were followed 6 months after surgery. Abdominal visceral fat area (VFA) and subcutaneous fat area (SFA) were measured by magnetic resonance imaging. Waist, hipline, waist-to-hip ratio (WHR) and body mass index (BMI) were included as simple obese parameters. Gut microbiome was analyzed by metagenomic sequencing. Results: Among the obese parameters, VFA had the largest number of correlations with the species that were differentially enriched between obese and healthy subjects, following by waist, WHR, BMI, hipline, and SFA. Within the species negatively correlated with VFA, Eubacterium eligens had the strongest correlation, following by Clostridium citroniae, C symbiosum, Bacteroides uniformis, E. ventriosum, Ruminococcaceae bacterium D16, C. hathewayi, etc. C. hathewayi and C. citroniae were increased after LSG. Functional analyses showed that among all the obese parameters, VFA had strongest correlation coefficients with the obesity-related microbial pathways. Microbial pathways involved in carbohydrate fermentation and biosynthesis of L-glutamate and L-glutamine might contribute to visceral fat accumulation. Conclusions: Visceral fat was more closely correlated with gut microbiome compared with subcutaneous fat, suggesting an intrinsic connection between gut microbiome and metabolic cardiovascular diseases. Specific microbial species and pathways which were closely associated with visceral fat accumulation might contribute to new targeted therapies for metabolic disorders. (C) 2020 The Author(s). Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据