Microbiome connections with host metabolism and habitual diet from 1,098 deeply phenotyped individuals

餐后 微生物群 普雷沃菌属 生物 肠道微生物群 肠道菌群 疾病 基因组 生理学 医学 内科学 糖尿病 生物信息学 免疫学 内分泌学 遗传学 细菌 基因
作者
Francesco Asnicar,Sarah Berry,Ana M. Valdes,Long H. Nguyen,Gianmarco Piccinno,David A. Drew,Emily R. Leeming,Rachel Gibson,Caroline Le Roy,Haya Al Khatib,Lucy Francis,Mohsen Mazidi,Olatz Mompeó,Mireia Valles‐Colomer,Adrian Tett,Francesco Beghini,Léonard Dubois,Davide Bazzani,Andrew Maltez Thomas,Chloe Mirzayi
出处
期刊:Nature Medicine [Nature Portfolio]
卷期号:27 (2): 321-332 被引量:950
标识
DOI:10.1038/s41591-020-01183-8
摘要

The gut microbiome is shaped by diet and influences host metabolism; however, these links are complex and can be unique to each individual. We performed deep metagenomic sequencing of 1,203 gut microbiomes from 1,098 individuals enrolled in the Personalised Responses to Dietary Composition Trial (PREDICT 1) study, whose detailed long-term diet information, as well as hundreds of fasting and same-meal postprandial cardiometabolic blood marker measurements were available. We found many significant associations between microbes and specific nutrients, foods, food groups and general dietary indices, which were driven especially by the presence and diversity of healthy and plant-based foods. Microbial biomarkers of obesity were reproducible across external publicly available cohorts and in agreement with circulating blood metabolites that are indicators of cardiovascular disease risk. While some microbes, such as Prevotella copri and Blastocystis spp., were indicators of favorable postprandial glucose metabolism, overall microbiome composition was predictive for a large panel of cardiometabolic blood markers including fasting and postprandial glycemic, lipemic and inflammatory indices. The panel of intestinal species associated with healthy dietary habits overlapped with those associated with favorable cardiometabolic and postprandial markers, indicating that our large-scale resource can potentially stratify the gut microbiome into generalizable health levels in individuals without clinically manifest disease.
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