Article

Nutrient-gene interaction: metabolic genotype-phenotype relationship.

Department of Medicine, David Geffen School of Medicine at UCLA, University of California-Los Angeles, CA 90095, USA.
Journal of Nutrition (Impact Factor: 4.23). 01/2006; 135(12 Suppl):3016S-3020S.
Source: PubMed

ABSTRACT The U.S. Department of Health and Human Services (DHHS)/USDA Dietary Guidelines for Americans is a science and population evidence-based guide on diet and physical activity, providing advice and recommendations to promote a healthier lifestyle and reduce the risk of chronic diseases, including cancer. These recommendations are supported by the comprehensive evidence-based review on diet and cancer prevention conducted by the American Institute for Cancer Research, National Cancer Institute, World Health Organization/International Agency for Research on Cancer, and others. However, influencing dietary effects are the individual genetic predispositions that are the basis for considerable interindividual variations in cancer risk within the population and in nutrient homeostasis, which is maintained by genomic-nutrient and metabolic-phenotype interactions. Although genetics is an important component, it accounts for only a portion of this variation. An individual's overall phenotype, including health status, is achieved and maintained by the sum of metabolic activities functioning under differing circumstances within the life cycle and the complex interactions among genotype, metabolic phenotype, and the environment. In this postgenomic era, high-throughput groups of technologies in genomics, proteomics, and metabolomics measure and analyze DNA sequences, RNA transcripts, proteins, and nutrient-metabolic fluxes in a single experiment. These advances have transformed biomarker studies on nutrient-gene interactions from a reductionist concept into a holistic practice in which many regulated genes involved in metabolism, along with its metabolic phenotypes, can be measured through functional genomics and metabolic profiling. The overall integration of data and information from the building blocks of metabolism-based nutrient-gene interaction can lead to future individualized dietary recommendations to diminish cancer risk.

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