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An In Vitro Batch-culture Model to Estimate the Effects of Interventional Regimens on Human Fecal Microbiota
Published on: July 31, 2019
Faecal metabolites as a readout of habitual diet capture dietary interactions with the gut microbiome
Robert Pope1, Alessia Visconti1,2, Xinyuan Zhang1
1Department of Twin Research & Genetic Epidemiology, King's College London, London, UK.
Abstract:
The interplay between diet and gut microbiome composition is complex. Faecal metabolites, the end products of human and microbial metabolism, provide insights into these interactions. Here, we integrate faecal metabolomics, metagenomics, and habitual dietary data from 1810 individuals from the TwinsUK and 837 from the ZOE PREDICT1 cohorts. Using machine learning models, we find that faecal metabolites accurately predict reported intakes of 20 food groups (area under the curve (AUC) > 0.80 for meat, nuts and seeds, wholegrains, tea and coffee, and alcohol) and adherence to seven dietary patterns (AUC from 0.71 for the Plant-based Diet Index to 0.83 for the Dietary Approaches to Stop Hypertension score). Notably, the faecal metabolome is a stronger predictor of atherosclerotic cardiovascular disease risk (AUC = 0.86) than the Dietary Approaches to Stop Hypertension score (AUC = 0.66). We identify 414 associations between 19 food groups and 211 metabolites, that significantly correlate with microbial α-diversity and 217 species. Our findings reveal that faecal metabolites capture mediations between diet and the gut microbiome, advancing our understanding of diet-related disease risk and informing metabolite-based interventions.
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