RETRACTED ARTICLE: Dietary metabotype modelling predicts individual responses to dietary interventions.

Isabel Garcia-Perez,John C Mathers,Edward S Chambers,John Draper,Elaine Holmes,Joram M Posma,Manfred Beckmann,Jeremy K Nicholson,Gary Frost

doi:10.1038/s43016-020-0092-z

Abstract

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.

Highlights

One in five deaths are directly attributable to poor diet[1,2]
Evidence from large interventions demonstrates that risk of type 2 diabetes and coronary artery disease is reduced by a healthier lifestyle, which includes consumption of a high-quality diet, and population based national and international dietary guidelines for non-communicable disease (NCD) prevention have been developed
It is of interest that the urinary metabolic phenotype of participants after following Diet 1 are consistent with phenotypes previously associated with lean individuals, for example higher levels of hippurate and vitamin-related compounds such as niacin; whereas the Diet 4 metabolic phenotype reflects that reported for obese individuals[19]

Summary

Introduction

One in five deaths are directly attributable to poor diet[1,2]. Evidence from large interventions demonstrates that risk of type 2 diabetes and coronary artery disease is reduced by a healthier lifestyle, which includes consumption of a high-quality diet, and population based national and international dietary guidelines for non-communicable disease (NCD) prevention have been developed. Recent evidence demonstrates that individuals respond differently to the same diet in terms of impact on metabolism and clinical outcomes[3,4,5,6,7,8,9,10,11,12,13,14] Exploitation of this heterogeneity in dietary response has given rise to the concept of precision nutrition[14,15], the ambition of which is to optimise individual responses to dietary intervention on the basis of understanding the determinants of these individual responses to nutritional intakes. Recent evidence indicates that matching diet to genotype produces no further benefit in dietary response over personalised dietary advice[17] This highlights the need for new technical approaches for understanding the individual’s metabolic response to a dietary intervention

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