Individual metabolism should guide agriculture toward foods for improved health and nutrition

Am J Clin Nutr. 2001 Sep;74(3):283-6. doi: 10.1093/ajcn/74.3.283.

Abstract

Genomics and bioinformatics have the vast potential to identify genes that cause disease by investigating whole-genome databases. Comparison of an individual's geno-type with a genomic database will allow the prescription of drugs to be tailored to an individual's genotype. This same bioinformatic approach, applied to the study of human metabolites, has the potential to identify and validate targets to improve personalized nutritional health and thus serve to define the added value for the next generation of foods and crops. Advances in high-throughput analytic chemistry and computing technologies make the creation of a vast database of metabolites possible for several subsets of metabolites, including lipids and organic acids. In creating integrative databases of metabolites for bioinformatic investigation, the current concept of measuring single biomarkers must be expanded to 3 dimensions to 1) include a highly comprehensive set of metabolite measurements (a profile) by multiparallel analyses, 2) measure the metabolic profile of individuals over time rather than simply in the fasted state, and 3) integrate these metabolic profiles with genomic, expression, and proteomic databases. Application of the knowledge of individual metabolism will revolutionize the ability of nutrition to deliver health benefits through food in the same way that knowledge of genomics will revolutionize individual treatment of dis-ease with pharmaceuticals.

Publication types

  • Research Support, U.S. Gov't, Non-P.H.S.
  • Research Support, U.S. Gov't, P.H.S.
  • Review

MeSH terms

  • Biomarkers / analysis
  • Crops, Agricultural / standards*
  • Databases, Factual
  • Diet / standards*
  • Energy Metabolism / genetics*
  • Food / standards*
  • Genetic Engineering
  • Genetics, Medical
  • Genome, Human
  • Humans
  • Nutritional Physiological Phenomena / physiology*
  • Phenotype

Substances

  • Biomarkers