A network biology model of micronutrient related health

Abstract

Micronutrients are involved in specific biochemical pathways and have dedicated functions in the body, but they are also interconnected in complex metabolic networks, such as oxidative-reductive and inflammatory pathways and hormonal regulation, in which the overarching function is to optimise health. Post-genomic technologies, in particular metabolomics and proteomics, both of which are appropriate for plasma samples, provide a new opportunity to study the metabolic effects of micronutrients in relation to optimal health. The study of micronutrient-related health status requires a combination of data on markers of dietary exposure, markers of target function and biological response, health status metabolites, and disease parameters. When these nutrient-centred and physiology/health-centred parameters are combined and studied using a systems biology approach with bioinformatics and multivariate statistical tools, it should be possible to generate a micronutrient phenotype database. From this we can explore external factors that define the phenotype, such as lifestage and lifestyle, and the impact of genotype, and the results can also be used to define micronutrient requirements and provide dietary advice. New mechanistic insights have already been developed using biological network models, for example genes and protein-protein interactions in the aetiology of type 2 diabetes mellitus. It is hoped that the challenge of applying this approach to micronutrients will, in time, result in a change from micronutrient oriented to a health oriented views and provide a more holistic understanding of the role played by multiple micronutrients in the maintenance of homeostasis and prevention of chronic disease, for example through their involvement in oxidation and inflammation.