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Current Pharmacogenomics and Personalized Medicine


ISSN (Print): 1875-6921
ISSN (Online): 1875-6913

Nutrient-By-Genotype Interactions and Personalized Diet: What Can We Learn From Drosophila and Evolutionary Biology?

Author(s): D. M. Ruden, P. Rasouli, L. Wang and X. Lu

Volume 7, Issue 3, 2009

Page: [189 - 204] Pages: 16

DOI: 10.2174/1875692110907030189

Price: $65


While human nutrigenomics research and efforts for targeted nutritional interventions intensified over the past few years, there are fundamental lessons to be learned from Drosophila and evolutionary biology for human nutrient-gene interactions. With the advent of inexpensive whole genome sequencing, single-nucleotide polymorphisms (SNPs) and insertions-deletions (INDELs) can now be associated with specific nutrient-by-genotype interactions that affect the lifespan and health of Drosophila. Because of the increase in statistical power in using inbred Drosophila lines that are freely available to investigators rather than outbred humans, the SNP and INDEL information should be invaluable to anyone interested in personal genomes and personalized medicine and nutrition. This preclinical model offers a unique opportunity to move beyond the artificial barriers among genomics, proteomics and metabolomics to integrate information from diverse omics biomarker research streams. Drosophila life span also allows an evolutionary biology perspective to forecast the long term impact of personalized nutritional interventions based on individual genetic make-up, before costly prospective clinical studies in humans are initiated. The aim of this paper is to present a critical synthesis of the ongoing work in the field of evolutionary biology in Drosophila models as a complement to human nutrigenomics. In addition, we present and synthesize several key promises and challenges in extrapolation of data from Drosophila to humans, and identify specific strategies to optimize this timely confluence of preclinical and clinical nutrigenomics research.

Keywords: Personal Genomes, Drosophila, Whole-genome SNP analysis, Nutrigenomics, Evolutionary biology

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