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• W2022042057 abstract "Technologic advances now make it possible to collect large amounts of genetic, epigenetic, metabolomic and gut microbiome data. These data have the potential to transform approaches towards nutrition counselling by allowing us to recognise and embrace the metabolic, physiologic and genetic differences among individuals. The ultimate goal is to be able to integrate these multi-dimensional data so as to characterise the health status and disease risk of an individual and to provide personalised recommendations to maximise health. To this end, accurate and predictive systems-based measures of health are needed that incorporate molecular signatures of genes, transcripts, proteins, metabolites and microbes. Although we are making progress within each of these omics arenas, we have yet to integrate effectively multiple sources of biologic data so as to provide comprehensive phenotypic profiles. Observational studies have provided some insights into associative interactions between genetic or phenotypic variation and diet and their impact on health; however, very few human experimental studies have addressed these relationships. Dietary interventions that test prescribed diets in well-characterised study populations and that monitor system-wide responses (ideally using several omics platforms) are needed to make correlation–causation connections and to characterise phenotypes under controlled conditions. Given the growth in our knowledge, there is the potential to develop personalised dietary recommendations. However, developing these recommendations assumes that an improved understanding of the phenotypic complexities of individuals and their responses to the complexities of their diets will lead to a sustainable, effective approach to promote health and prevent disease – therein lies our challenge." @default.
• W2022042057 created "2016-06-24" @default.
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• W2022042057 date "2013-02-07" @default.
• W2022042057 modified "2023-10-13" @default.
• W2022042057 title "Inter-individual differences in response to dietary intervention: integrating omics platforms towards personalised dietary recommendations" @default.
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• W2022042057 doi "https://doi.org/10.1017/s0029665113000025" @default.
• W2022042057 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/3694579" @default.
• W2022042057 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/23388096" @default.
• W2022042057 hasPublicationYear "2013" @default.
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