In this section
@article{Garcia:2020:10.1038/s43016-020-0092-z,
author = {Garcia, Perez I and Posma, JM and Chambers, E and Mathers, J and Draper, J and Beckmann, M and Nicholson, J and Holmes, E and Frost, G},
doi = {10.1038/s43016-020-0092-z},
journal = {Nature Food},
pages = {355--364},
title = {Dietary metabotype modelling predicts individual responses to dietary interventions},
url = {http://dx.doi.org/10.1038/s43016-020-0092-z},
volume = {1},
year = {2020}
}
TY - JOUR
AB - Habitual consumption of poor quality diets is linked directly to risk factors for many non-communicable disease. This has resulted in the vast majority of countries globally and the World Health Organisation developing policies for healthy eating to reduce the prevalence of non communicable disease 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 inter-individual 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 inter-individual 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 employ a metabolic entropy approach to visualize individual and collective responses to dietary. Potentially, the DMS offers a method to target and to enhance dietary response at an individual level therefore reducing burden of non communicable diseases at a population level.
AU - Garcia,Perez I
AU - Posma,JM
AU - Chambers,E
AU - Mathers,J
AU - Draper,J
AU - Beckmann,M
AU - Nicholson,J
AU - Holmes,E
AU - Frost,G
DO - 10.1038/s43016-020-0092-z
EP - 364
PY - 2020///
SN - 2662-1355
SP - 355
TI - Dietary metabotype modelling predicts individual responses to dietary interventions
T2 - Nature Food
UR - http://dx.doi.org/10.1038/s43016-020-0092-z
UR - https://rdcu.be/b40Yw
UR - https://www.nature.com/articles/s43016-020-0092-z
UR - http://hdl.handle.net/10044/1/80100
VL - 1
ER -
Georgia Levey
Centre for Translational Nutrition and Food Research Coordinator
Commonwealth Building
Hammersmith Campus
