TY - JOUR
T1 - Metagenomic estimation of dietary intake from human stool
AU - Diener, Christian
AU - Holscher, Hannah D.
AU - Filek, Klara
AU - Corbin, Karen D.
AU - Moissl-Eichinger, Christine
AU - Gibbons, Sean M.
N1 - Research reported in this publication was supported by the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) of the NIH under award number R01DK133468 (to S.M.G.) and by a Global Grants for Gut Health Award from Nature Portfolio and Yakult (to S.M.G.). This research was funded in part by the Austrian Science Fund (FWF): grant Cluster of Excellence CoE7 (to C.D. and C.M.-E.) and SFB ImmunoMetabolism 10.55776/F8300 (to C.M.-E.). Computational resources for this work were provided by the MedBioNode High-Performance Computing cluster at the Medical University of Graz. H.D.H. acknowledges funding for the PATH study from the Foundation for Food and Agriculture Research (FFAR) New Innovator Award and Hass Avocado Board.
The authors report no financial or non-financial competing interests relevant to the work presented in this paper. S.M.G. received funding from a Global Grants for Gut Health Award from Nature Portfolio and Yakult. However, the funders were not involved in conducting the research, drafting the paper or reviewing the work.
PY - 2025/3
Y1 - 2025/3
N2 - Dietary intake is tightly coupled to gut microbiota composition, human metabolism and the incidence of virtually all major chronic diseases. Dietary and nutrient intake are usually assessed using self-reporting methods, including dietary questionnaires and food records, which suffer from reporting biases and require strong compliance from study participants. Here, we present Metagenomic Estimation of Dietary Intake (MEDI): a method for quantifying food-derived DNA in human faecal metagenomes. We show that DNA-containing food components can be reliably detected in stool-derived metagenomic data, even when present at low abundances (more than ten reads). We show how MEDI dietary intake profiles can be converted into detailed metabolic representations of nutrient intake. MEDI identifies the onset of solid food consumption in infants, shows significant agreement with food frequency questionnaire responses in an adult population and shows agreement with food and nutrient intake in two controlled-feeding studies. Finally, we identify specific dietary features associated with metabolic syndrome in a large clinical cohort without dietary records, providing a proof-of-concept for detailed tracking of individual-specific, health-relevant dietary patterns without the need for questionnaires.
AB - Dietary intake is tightly coupled to gut microbiota composition, human metabolism and the incidence of virtually all major chronic diseases. Dietary and nutrient intake are usually assessed using self-reporting methods, including dietary questionnaires and food records, which suffer from reporting biases and require strong compliance from study participants. Here, we present Metagenomic Estimation of Dietary Intake (MEDI): a method for quantifying food-derived DNA in human faecal metagenomes. We show that DNA-containing food components can be reliably detected in stool-derived metagenomic data, even when present at low abundances (more than ten reads). We show how MEDI dietary intake profiles can be converted into detailed metabolic representations of nutrient intake. MEDI identifies the onset of solid food consumption in infants, shows significant agreement with food frequency questionnaire responses in an adult population and shows agreement with food and nutrient intake in two controlled-feeding studies. Finally, we identify specific dietary features associated with metabolic syndrome in a large clinical cohort without dietary records, providing a proof-of-concept for detailed tracking of individual-specific, health-relevant dietary patterns without the need for questionnaires.
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U2 - 10.1038/s42255-025-01220-1
DO - 10.1038/s42255-025-01220-1
M3 - Article
C2 - 39966520
AN - SCOPUS:85218137165
SN - 2522-5812
VL - 7
SP - 617
EP - 630
JO - Nature Metabolism
JF - Nature Metabolism
IS - 3
M1 - 875143
ER -