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

Nature Medicine – 2021


Francesco Asnicar, Sarah E. Berry, Ana M. Valdes, Long H. Nguyen,5 Gianmarco Piccinno, David A. Drew, Emily Leeming, Rachel Gibson, Caroline Le Roy, Haya Al Khatib, Lucy Francis,7Mohsen Mazidi, Olatz Mompeo, Mireia Valles-Colomer, Adrian Tett, Francesco Beghini, Léonard Dubois,1 Davide Bazzani, Andrew Maltez Thomas, Chloe Mirzayi, Asya Khleborodova, Sehyun Oh, Rachel Hine, Christopher Bonnett, Joan Capdevila Pujol, Serge Danzanvilliers, Francesca Giordano, Ludwig Geistlinger, Levi Waldron, Richard Davies, George Hadjigeorgiou, Jonathan Wolf, José M. Ordovás, Christopher Gardner, Paul W. Franks, Andrew T. Chan, Curtis Huttenhower,, Tim D. Spector, and Nicola Segata


Nature Medicine




The gut microbiome is shaped by diet and influences host metabolism, but these links are complex and can be unique to each individual. We performed deep metagenomic sequencing of >1,100 gut microbiomes from individuals with detailed long-term diet information, as well as hundreds of fasting and same-meal postprandial cardiometabolic blood marker measurements. We found strong associations between microbes and specific nutrients, foods, food groups, and general dietary indices, driven especially by the presence and diversity of healthy and plant-based foods. Microbial biomarkers of obesity were reproducible across cohorts, and blood markers of cardiovascular disease and impaired glucose tolerance were more strongly associated with microbiome structure. While some microbes such as Prevotella copri and Blastocystis spp., were indicators of favorable postprandial glucose metabolism, several species were more directly predictive of postprandial triglycerides and C-peptide. The panel of intestinal species associated with healthy dietary habits overlapped with those associated with favourable cardiometabolic and postprandial markers, indicating our large-scale resource can potentially stratify the gut microbiome into generalizable health levels among individuals without clinically manifest disease.