Department of Health Sciences, Northeastern University, Boston, MA 02115, USA.
Annu Rev Nutr. 2013;33:349-71. doi: 10.1146/annurev-nutr-072610-145203. Epub 2013 Apr 29.
The field of nutrigenomics shows tremendous promise for improved understanding of the effects of dietary intake on health. The knowledge that metabolic pathways may be altered in individuals with genetic variants in the presence of certain dietary exposures offers great potential for personalized nutrition advice. However, although considerable resources have gone into improving technology for measurement of the genome and biological systems, dietary intake assessment remains inadequate. Each of the methods currently used has limitations that may be exaggerated in the context of gene × nutrient interaction in large multiethnic studies. Because of the specificity of most gene × nutrient interactions, valid data are needed for nutrient intakes at the individual level. Most statistical adjustment efforts are designed to improve estimates of nutrient intake distributions in populations and are unlikely to solve this problem. An improved method of direct measurement of individual usual dietary intake that is unbiased across populations is urgently needed.
营养基因组学领域在增进对饮食摄入对健康影响的理解方面展现出巨大的前景。在存在某些饮食暴露的情况下,个体的代谢途径可能会因遗传变异而改变,这为个性化营养建议提供了巨大的潜力。然而,尽管已经投入了大量资源来改进基因组和生物系统的测量技术,但饮食摄入评估仍然不足。目前使用的每种方法都有局限性,在大型多民族研究中基因与营养相互作用的情况下,这些局限性可能会被夸大。由于大多数基因与营养相互作用的特异性,需要个体水平的营养素摄入量的有效数据。大多数统计调整工作旨在改善人群中营养素摄入量分布的估计值,不太可能解决这个问题。迫切需要一种改进的、针对个体通常饮食摄入的直接测量方法,该方法在人群中是无偏的。