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首页> 外文期刊>Proceedings of the Nutrition Society >Inter-individual differences in response to dietary intervention: integrating omics platforms towards personalised dietary recommendations.
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Inter-individual differences in response to dietary intervention: integrating omics platforms towards personalised dietary recommendations.

机译:饮食干预的个体差异:将组学平台与个性化饮食建议结合起来。

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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
机译:现在,技术的进步使收集大量的遗传,表观遗传学,代谢组学和肠道微生物组数据成为可能。这些数据使我们能够认识并接受个体之间的代谢,生理和遗传差异,从而有可能改变营养咨询的方法。最终目标是能够整合这些多维数据,以表征个人的健康状况和疾病风险,并提供个性化建议以最大程度地提高健康水平。为此,需要基于基因的准确,可预测的健康测量方法,该方法应结合基因,转录本,蛋白质,代谢物和微生物的分子特征。尽管我们在每个组学领域都取得了进展,但我们尚未有效整合多种生物学数据来源,以提供全面的表型概况。观察性研究为遗传或表型变异与饮食之间的关联相互作用及其对健康的影响提供了一些见识。但是,很少有人类实验研究能够解决这些关系。需要进行饮食干预,以测试特征明确的研究人群中的规定饮食并监测系统范围的反应(理想情况下使用多个组学平台),以建立相关原因联系并在受控条件下表征表型。随着我们知识的增长,有可能发展个性化的饮食建议。然而,制定这些建议的前提是,对个体表型复杂性及其对饮食复杂性的反应的更好理解将导致可持续,有效的方法来促进健康和预防疾病-这是我们面临的挑战

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