Microbiome connections with host metabolism and habitual diet from 1,098 deeply phenotyped individuals PMID: 33432175

Target-related Cytokines

2026-09-23

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

Nat Med. 2021 Feb;27(2):321-332. doi: 10.1038/s41591-020-01183-8.

Francesco Asnicar ^# ¹ , Sarah E Berry ^# ² , Ana M Valdes ³ ⁴ , Long H Nguyen ⁵ , Gianmarco Piccinno ¹ , David A Drew ⁵ , Emily Leeming ⁶ , Rachel Gibson ⁷ , Caroline Le Roy ⁶ , Haya Al Khatib ⁸ , Lucy Francis ⁸ , Mohsen Mazidi ⁶ , Olatz Mompeo ⁶ , Mireia Valles-Colomer ¹ , Adrian Tett ¹ , Francesco Beghini ¹ , Léonard Dubois ¹ , Davide Bazzani ¹ , Andrew Maltez Thomas ¹ , Chloe Mirzayi ⁹ , Asya Khleborodova ⁹ , Sehyun Oh ⁹ , Rachel Hine ⁸ , Christopher Bonnett ⁸ , Joan Capdevila ⁸ , Serge Danzanvilliers ⁸ , Francesca Giordano ⁸ , Ludwig Geistlinger ⁹ , Levi Waldron ⁹ , Richard Davies ⁸ , George Hadjigeorgiou ⁸ , Jonathan Wolf ⁸ , José M Ordovás ¹⁰ ¹¹ , Christopher Gardner ¹² , Paul W Franks ¹³ ¹⁴ , Andrew T Chan ⁵ ¹⁴ ¹⁵ , Curtis Huttenhower ¹⁴ ¹⁵ , Tim D Spector ⁶ , Nicola Segata ¹⁶ ¹⁷

Affiliations

1. Department of Cellular, Computational and Integrative Biology, University of Trento, Trento, Italy.
2. Department of Nutritional Sciences, King's College London, London, UK. [email protected].
3. School of Medicine, University of Nottingham, Nottingham, UK.
4. Nottingham National Institute for Health Research Biomedical Research Centre, Nottingham, UK.
5. Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
6. Department of Twin Research, King's College London, London, UK.
7. Department of Nutritional Sciences, King's College London, London, UK.
8. Zoe Global Ltd, London, UK.
9. City University of New York, New York, NY, USA.
10. Jean Mayer-United States Department of Agriculture-Human Nutrition Research Center on Aging, Tufts University, Boston, MA, USA.
11. Institutos Madrileño de Estudios Avanzados Food Institute, Campus of International Excellence Universidad Autónoma de Madrid & Consejo Superior de Investigaciones Científicas, Madrid, Spain.
12. Stanford University, Stanford, CA, USA.
13. Department of Clinical Sciences, Lund University, Malmö, Sweden.
14. Harvard T.H. Chan School of Public Health, Boston, MA, USA.
15. The Broad Institute of MIT and Harvard, Cambridge, MA, USA.
16. Department of Cellular, Computational and Integrative Biology, University of Trento, Trento, Italy. [email protected].
17. European Institute of Oncology Scientific Institute for Research, Hospitalization and Healthcare, Milan, Italy. [email protected].
# Contributed equally.

Abstract

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.