在这项可行性研究中，创建了个体的饮食代谢类型评分（Dietary metabotype Score，DMS），体现了饮食反应的个体间差异性，并捕获了尿液中代谢物浓度的动态变化。研究发现饮食代谢类型评分与血糖浓度之间成反比关系。饮食代谢类型评分与尿液代谢能量损失之间也存在关系。此外，研究利用代谢熵法来可视化个体和群体对饮食干预的反应。饮食代谢类型评分可能会在个体水平上提供一种靶向且提高饮食反应的方法，从而在群体水平上减少非传染性疾病的负担。
Abstract
Dietary metabotype modelling predicts individual responses to dietary interventions
Isabel Garcia-Perez, Joram M. Posma, Jeremy K. Nicholson, Elaine Holmes, Gary Frost
Division of Digestive Diseases, Department of metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London, UK
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.
