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Nutrigenomics: lessons learned and future perspectives
Author(s) -
Lorraine Brennan,
Baukje de Roos
Publication year - 2020
Publication title -
american journal of clinical nutrition
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.608
H-Index - 336
eISSN - 1938-3207
pISSN - 0002-9165
DOI - 10.1093/ajcn/nqaa366
Subject(s) - nutrigenomics , metagenomics , data science , omics , metabolomics , proteomics , psychological intervention , systems biology , microbiology and biotechnology , computational biology , computer science , biology , bioinformatics , medicine , biochemistry , psychiatry , gene
The omics technologies of metabolomics, transcriptomics, proteomics, and metagenomics are playing an increasingly important role in nutrition science. With the emergence of the concept of precision nutrition and the need to understand individual responses to dietary interventions, it is an opportune time to examine the impact of these tools to date in human nutrition studies. Advances in our mechanistic understanding of dietary interventions were realized through incorporation of metabolomics, proteomics, and, more recently, metagenomics. A common observation across the studies was the low intra-individual variability of the omics measurements and the high inter-individual variation. Harnessing this data for use in the development of precision nutrition will be important. Metabolomics in particular has played a key role in the development of biomarkers of food intake in an effort to enhance the accuracy of dietary assessments. Further work is needed to realize the full potential of such biomarkers and to demonstrate integration with current strategies, with the goal of overcoming the well-established limitations of self-reported approaches. Although many of the nutrigenomic studies performed to date were labelled as proof-of-concept or pilot studies, there is ample evidence to support the use of these technologies in nutrition science. Incorporating omic technologies from the start of study designs will ensure that studies are sufficiently powered for such data. Furthermore, multi-disciplinary collaborations are likely to become even more important to aid analyses and interpretation of the data.

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