Menni Cristina, Zhai Guangju, Macgregor Alexander, Prehn Cornelia, Römisch-Margl Werner, Suhre Karsten, Adamski Jerzy, Cassidy Aedin, Illig Thomas, Spector Tim D, Valdes Ana M
Department of Twin Research & Genetic Epidemiology, King's College London, St Thomas Hospital, London, SE17EH UK.
Metabolomics. 2013 Apr;9(2):506-514. doi: 10.1007/s11306-012-0469-6. Epub 2012 Oct 6.
Nutrition plays an important role in human metabolism and health. Metabolomics is a promising tool for clinical, genetic and nutritional studies. A key question is to what extent metabolomic profiles reflect nutritional patterns in an epidemiological setting. We assessed the relationship between metabolomic profiles and nutritional intake in women from a large cross-sectional community study. Food frequency questionnaires (FFQs) were applied to 1,003 women from the TwinsUK cohort with targeted metabolomic analyses of serum samples using the Biocrates Absolute-IDQ™ Kit p150 (163 metabolites). We analyzed seven nutritional parameters: coffee intake, garlic intake and nutritional scores derived from the FFQs summarizing fruit and vegetable intake, alcohol intake, meat intake, hypo-caloric dieting and a "traditional English" diet. We studied the correlation between metabolite levels and dietary intake patterns in the larger population and identified for each trait between 14 and 20 independent monozygotic twins pairs discordant for nutritional intake and replicated results in this set. Results from both analyses were then meta-analyzed. For the metabolites associated with nutritional patterns, we calculated heritability using structural equation modelling. 42 metabolite nutrient intake associations were statistically significant in the discovery samples (Bonferroni < 4 × 10) and 11 metabolite nutrient intake associations remained significant after validation. We found the strongest associations for fruit and vegetables intake and a glycerophospholipid (Phosphatidylcholine diacyl C38:6, = 1.39 × 10) and a sphingolipid (Sphingomyeline C26:1, = 6.95 × 10). We also found significant associations for coffee (confirming a previous association with C10 reported in an independent study), garlic intake and hypo-caloric dieting. Using the twin study design we find that two thirds the metabolites associated with nutritional patterns have a significant genetic contribution, and the remaining third are solely environmentally determined. Our data confirm the value of metabolomic studies for nutritional epidemiologic research.
营养在人体新陈代谢和健康中起着重要作用。代谢组学是临床、遗传和营养研究中一种很有前景的工具。一个关键问题是代谢组学特征在多大程度上反映了流行病学背景下的营养模式。我们在一项大型横断面社区研究中评估了女性代谢组学特征与营养摄入之间的关系。对来自双胞胎英国队列的1003名女性应用食物频率问卷（FFQ），并使用Biocrates Absolute-IDQ™ Kit p150（163种代谢物）对血清样本进行靶向代谢组学分析。我们分析了七个营养参数：咖啡摄入量、大蒜摄入量以及从FFQ得出的总结水果和蔬菜摄入量、酒精摄入量、肉类摄入量、低热量节食和“传统英式”饮食的营养得分。我们研究了较大人群中代谢物水平与饮食摄入模式之间的相关性，并为每个特征确定了14至20对营养摄入不一致的独立同卵双胞胎对，并在该组中重复了结果。然后对两项分析的结果进行荟萃分析。对于与营养模式相关的代谢物，我们使用结构方程模型计算遗传力。42种代谢物与营养摄入的关联在发现样本中具有统计学意义（Bonferroni < 4×10），11种代谢物与营养摄入的关联在验证后仍然显著。我们发现水果和蔬菜摄入量与一种甘油磷脂（磷脂酰胆碱二酰基C38:6，= 1.39×10）和一种鞘脂（鞘磷脂C26:1，= 6.95×10）之间的关联最强。我们还发现咖啡（证实了之前在一项独立研究中报道的与C10的关联）、大蒜摄入量和低热量节食之间存在显著关联。使用双胞胎研究设计，我们发现与营养模式相关的三分之二的代谢物具有显著的遗传贡献，其余三分之一仅由环境决定。我们的数据证实了代谢组学研究在营养流行病学研究中的价值。
