van Velzen Ewoud J J, Westerhuis Johan A, van Duynhoven John P M, van Dorsten Ferdi A, Grün Christian H, Jacobs Doris M, Duchateau Guus S M J E, Vis Daniël J, Smilde Age K
Biosystems Data Analysis, Swammerdam Institute for Life Sciences, Universiteit van Amsterdam, Nieuwe Achtergracht 166, 1018 WV Amsterdam, The Netherlands.
J Proteome Res. 2009 Jul;8(7):3317-30. doi: 10.1021/pr801071p.
An integration of metabolomics and pharmacokinetics (or nutrikinetics) is introduced as a concept to describe a human study population with different metabolic phenotypes following a nutritional intervention. The approach facilitates an unbiased analysis of the time-response of body fluid metabolites from crossover designed intervention trials without prior knowledge of the underlying metabolic pathways. The method is explained for the case of a human intervention study in which the nutrikinetic analysis of polyphenol-rich black tea consumption was performed in urine over a period of 48 h. First, multilevel PLS-DA analysis was applied to the urinary 1H NMR profiles to select the most differentiating biomarkers between the verum and placebo samples. Then, a one-compartment nutrikinetic model with first-order excretion, a lag time, and a baseline function was fitted to the time courses of these selected biomarkers. The nutrikinetic model used here fully exploits the crossover structure in the data by fitting the data from both the treatment period and the placebo period simultaneously. To demonstrate the procedure, a selected set of urinary biomarkers was used in the model fitting. These metabolites include hippuric acid, 4-hydroxyhippuric acid and 1,3-dihydroxyphenyl-2-O-sulfate and derived from microbial fermentation of polyphenols in the gut. Variations in urinary excretion between- and within the subjects were observed, and used to provide a phenotypic description of the test population.
本文引入了代谢组学与药代动力学(或营养动力学)相结合的概念,用于描述营养干预后具有不同代谢表型的人类研究群体。该方法有助于对交叉设计的干预试验中体液代谢物的时间响应进行无偏分析,而无需事先了解潜在的代谢途径。本文以一项人体干预研究为例进行说明,该研究对富含多酚的红茶饮用进行了48小时的尿液营养动力学分析。首先,将多级PLS-DA分析应用于尿液1H NMR谱,以选择在真实样本和安慰剂样本之间最具区分性的生物标志物。然后,将具有一级排泄、滞后时间和基线函数的单室营养动力学模型拟合到这些选定生物标志物的时间进程中。这里使用的营养动力学模型通过同时拟合治疗期和安慰剂期的数据,充分利用了数据中的交叉结构。为了演示该过程,在模型拟合中使用了一组选定的尿液生物标志物。这些代谢物包括马尿酸、4-羟基马尿酸和1,3-二羟基苯基-2-O-硫酸盐,它们来源于肠道中多酚的微生物发酵。观察到受试者之间和受试者内部尿液排泄的差异,并用于提供受试人群的表型描述。