4.6 Review

Metabolomics Meets Nutritional Epidemiology: Harnessing the Potential in Metabolomics Data

Journal

METABOLITES
Volume 11, Issue 10, Pages -

Publisher

MDPI
DOI: 10.3390/metabo11100709

Keywords

metabolomics; dietary intake; biomarkers; dietary patterns; metabolites

Funding

  1. US-Tri-partite grant (HRB) [USIRL-2019-1]
  2. European Research Council [647783]
  3. [1U2CDK129670]
  4. [HL60712]
  5. [DK112940]
  6. [R01DK120870]
  7. [R01DK119268]
  8. [R01ES022981]

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Nutritional epidemiology traditionally studies the link between diet and health at a population level, but now it incorporates newer methods like metabolomics to gain better insights. By using biomarkers of food intake and metabolite measurements, limitations of traditional approaches can be addressed, but challenges such as biomarker validation and metabolite identification methods need to be overcome for the full potential of metabolomics to be realized.
Traditionally, nutritional epidemiology is the study of the relationship between diet and health and disease in humans at the population level. Commonly, the exposure of interest is food intake. In recent years, nutritional epidemiology has moved from a black box approach to a systems approach where genomics, metabolomics and proteomics are providing novel insights into the interplay between diet and health. In this context, metabolomics is emerging as a key tool in nutritional epidemiology. The present review explores the use of metabolomics in nutritional epidemiology. In particular, it examines the role that food-intake biomarkers play in addressing the limitations of self-reported dietary intake data and the potential of using metabolite measurements in assessing the impact of diet on metabolic pathways and physiological processes. However, for full realisation of the potential of metabolomics in nutritional epidemiology, key challenges such as robust biomarker validation and novel methods for new metabolite identification need to be addressed. The synergy between traditional epidemiologic approaches and metabolomics will facilitate the translation of nutritional epidemiologic evidence to effective precision nutrition.

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