Journal
NATURE FOOD
Volume 1, Issue 6, Pages 355-+Publisher
NATURE PORTFOLIO
DOI: 10.1038/s43016-020-0092-z
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Funding
- UK National Institute for Health Research (NIHR)
- Medical Research Council (MRC)
- NIHR Career Development Research Fellowship [NIHR-CDF-2017-10-032]
- Rutherford Fund Fellowship at Health Data Research (HDR) UK [MR/S004033/1]
- NIHR Senior Investigator award
- MRC grant entitled 'Metabolomics for Monitoring Dietary Exposure' [MR/J010308/1]
- Department of Jobs, Tourism, Science and Innovation, Government of Western Australian through the Premier's Science Fellowship Program
- NIHR/Wellcome Trust Imperial Clinical Research Facility
- MRC
- UK Biotechnology and Biological Sciences Research Council
- NIHR
- Integrative Mammalian Biology (IMB) Capacity Building Award
- NutriTech consortium (European Union Framework 7 programme) [289511]
- Egg Nutrition Center -American Egg Board
- Australian Medical Research Futures Fund
- MRC [MR/S004033/1, MR/J010308/1] Funding Source: UKRI
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Habitual consumption of poor quality diets is linked directly to risk factors for many non-communicable diseases. This has resulted in the vast majority of countries and the World Health Organization developing policies for healthy eating to reduce the prevalence of non-communicable diseases in the population. However, there is mounting evidence of variability in individual metabolic responses to any dietary intervention. We have developed a method for applying a pipeline for understanding interindividual differences in response to diet, based on coupling data from highly controlled dietary studies with deep metabolic phenotyping. In this feasibility study, we create an individual Dietary Metabotype Score (DMS) that embodies interindividual variability in dietary response and captures consequent dynamic changes in concentrations of urinary metabolites. We find an inverse relationship between the DMS and blood glucose concentration. There is also a relationship between the DMS and urinary metabolic energy loss. Furthermore, we use a metabolic entropy approach to visualize individual and collective responses to dietary interventions. Potentially, the DMS offers a method to target and to enhance dietary response at the individual level, thereby reducing the burden of non-communicable diseases at the population level. Variability in the individual response to dietary interventions has been reported. Here a Dietary Metabotype Score is developed to embody those interindividual responses by coupling data from highly controlled dietary studies with urinary metabolic phenotypes. This score may offer a method to target and to enhance dietary response at the individual level, thereby reducing the burden of diet-related disease at the population level.
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