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用于定义复杂基因-环境相互作用所产生表型的系统水平营养方法。

Systems-Level Nutrition Approaches to Define Phenotypes Resulting from Complex Gene-Environment Interactions.

作者信息

Kaput Jim

出版信息

Nestle Nutr Inst Workshop Ser. 2016;84:1-13. doi: 10.1159/000436947. Epub 2016 Jan 14.

Abstract

High-throughput metabolomic, proteomic, and genomic technologies have delivered 21st-century data showing that humans cannot be randomized into groups: individuals are genetically and biochemically distinct. Gene-environment interactions caused by unique dietary and lifestyle factors contribute to the heterogeneity in physiologies observed in human studies. The risk factors determined for populations (i.e. the population-attributable risk) cannot be applied to the individual. Developing individual risk/benefit factors in light of the genetic diversity of human populations, the complexity of foods, culture and lifestyle, and the variety in metabolic processes that lead to health or disease are significant challenges for personalizing dietary advice for healthy or diseased individuals.

摘要

高通量代谢组学、蛋白质组学和基因组学技术提供了21世纪的数据,表明人类不能被随机分组:个体在基因和生化方面是不同的。由独特的饮食和生活方式因素引起的基因-环境相互作用导致了人类研究中观察到的生理异质性。为群体确定的风险因素(即人群归因风险)不能应用于个体。鉴于人类群体的遗传多样性、食物的复杂性、文化和生活方式以及导致健康或疾病的代谢过程的多样性,制定个体风险/受益因素是为健康或患病个体提供个性化饮食建议的重大挑战。

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