通过代谢组学定义个人营养和代谢健康。

S Rezzi, F-P J Martin, S Kochhar
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引用次数: 17

摘要

现代营养学的一个主要章程是为不同食物选择导致的健康结果提供分子基础,以及如何设计这些食物以保持个人健康免受疾病的影响。营养基因组学技术已经发展到产生不同层次的生物组织信息,即基因、蛋白质和代谢物。在这个框架内,代谢组学通过代谢谱分析来针对生命系统的分子特征。利用基于多元统计的复杂数据挖掘技术探索代谢谱,可以恢复关键的代谢信息,进一步将其与生化过程和生理事件联系起来。代谢组学的力量依赖于其独特的能力来评估复杂生物体代谢的功能变化,这些变化源于多种影响,如生活方式和环境因素。特别是,代谢谱包含了复杂生物体中共生伙伴(即肠道微生物群)代谢活动的信息,这是营养和健康的主要决定因素。因此,代谢组学在营养科学中的应用导致了营养代谢组学方法用于人群饮食反应的分类和优化或个性化营养管理的可能性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Defining personal nutrition and metabolic health through metabonomics.

A major charter for modern nutrition is to provide a molecular basis for health outcome resulting from different food choices and how this could be designed to maintain individual health free of disease. Nutrigenomic techniques have been developed to generate information at various levels of biological organization, i.e. genes, proteins, and metabolites. Within this frame, metabonomics targets the molecular characterization of a living system through metabolic profiling. The metabolic profiles are explored with sophisticated data mining techniques mainly based on multivariate statistics, which can recover key metabolic information to be further linked to biochemical processes and physiological events. The power of metabonomics relies on its unique ability to assess functional changes in the metabolism of complex organisms stemming from multiple influences such as lifestyle and environmental factors. In particular, metabolic profiles encapsulate information on the metabolic activity of symbiotic partners, i.e. gut microflora, in complex organisms, which represent major determinant in nutrition and health. Therefore, applications of metabonomics to nutrition sciences led to the nutrimetabonomics approach for the classification of dietary responses in populations and the possibility of optimized or personalized nutritional management.

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