ArticleNature communications2025
Faecal metabolites as a readout of habitual diet capture dietary interactions with the gut microbiome.
Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed.
- Review
- FoodScribe: an open-source semantic framework for nutrient estimation from free-text dietary records.medRxiv : the preprint server for health sciences · 2026Article
- Decoding the Gut-Fat-Heart Axis: From Molecular Communication Networks to Clinical Translation Strategies.International journal of molecular sciences · 2026Review
- Carnitine dysregulation in diabetic kidney disease: from pathogenic mechanism to precision biomarker.Journal of translational medicine · 2026Review
- Development of a multi-targeted metabolomics platform for semi-quantification of faecal metabolites: a proof-of-concept analysis in human faeces.Microbiome research reports · 2026Article
- Precision nutrition through diet-gut microbiome interactions: Emerging insights driven by artificial intelligence, microbiome health metrics, and mechanistic modeling.Gut microbes reports · 2026Review
Corrections and comments
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Authors and funding
18 authors.
Funding
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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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.