Harnessing Metabolomics for Nutrition Research

Michael      A. Zulyniak; David      M. Mutch

doi:10.2174/138920111795909113

Abstract

Comprehensive analytical technologies are rapidly becoming a cornerstone of modern nutritional sciences. Two of these technologies, mass spectrometry (MS) and nuclear magnetic resonance (NMR), have proven highly informative for the global analysis of metabolites, commonly referred to as metabolomics. Metabolomics provides a powerful approach to study small molecules in order to better understand the implications and subtle perturbations in metabolism triggered by nutrients. By studying how dietary molecules can modulate the metabolome, researchers have begun to elucidate the molecular pathways by which nutrients affect health and disease, expand the current state of knowledge regarding how inter-individual variability contributes to differences in nutrient metabolism, and develop novel avenues of research for nutritional sciences. Although metabolomics has been more commonly used to study disease states, its use in the nutritional sciences is gaining momentum. The current review is written for the clinical researcher wishing to incorporate metabolomics into dietary intervention studies. This review will highlight the importance and benefit of identifying biomarkers that accurately reflect changes in nutrient intake and metabolism, and present numerous issues that can introduce variability into a dataset and confound a study's biological interpretation, including sample population demographics, the biological specimen selected, diurnal variation, collection methods, and sample storage parameters. Considering these important areas at the experimental design stage will ensure that metabolomics provides a comprehensive and accurate assessment of the molecular impact of a dietary intervention.

Keywords: Biomarkers, dietary interventions, mass spectrometry, metabolite variability, metabotype, nuclear magnetic resonance, nutritional sciences, Comprehensive analytical technologies, metabolism, sample population demographics