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Abstract：
Metabolic diversity leads to differences in nutrient requirements and responses to diet and medication between individuals. Using the concept of metabotyping - that is, grouping metabolically similar individuals - tailored and more efficient recommendations may be achieved. The aim of this study was to review the current literature on metabotyping and to explore its potential for better targeted dietary intervention in subjects with and without metabolic diseases. A comprehensive literature search was performed in PubMed, Google and Google Scholar to find relevant articles on metabotyping in humans including healthy individuals, population-based samples and patients with chronic metabolic diseases. A total of thirty-four research articles on human studies were identified, which established more homogeneous subgroups of individuals using statistical methods for analysing metabolic data. Differences between studies were found with respect to the samples/populations studied, the clustering variables used, the statistical methods applied and the metabotypes defined. According to the number and type of the selected clustering variables, the definitions of metabotypes differed substantially; they ranged between general fasting metabotypes, more specific fasting parameter subgroups like plasma lipoprotein or fatty acid clusters and response groups to defined meal challenges or dietary interventions. This demonstrates that the term \'metabotype\' has a subjective usage, calling for a formalised definition. In conclusion, this literature review shows that metabotyping can help identify subgroups of individuals responding differently to defined nutritional interventions. Targeted recommendations may be given at such metabotype group levels. Future studies should develop and validate definitions of generally valid metabotypes by exploiting the increasingly available metabolomics data sets.
摘要：
代谢多样性导致个体之间的营养需求以及对饮食和药物的反应差异。使用代谢分型的概念-也就是说，将代谢相似的个体分组-可以实现定制和更有效的建议。这项研究的目的是回顾目前关于代谢分型的文献，并探索其在有和没有代谢性疾病的受试者中更好的针对性饮食干预的潜力。在PubMed进行了全面的文献检索，谷歌和谷歌学者找到有关人类包括健康个体的代谢分型的相关文章，以人群为基础的样本和慢性代谢性疾病患者。共确定了三十四篇有关人体研究的研究文章,它使用统计方法分析代谢数据建立了更同质的个体亚组。在研究的样本/群体方面发现了研究之间的差异，使用的聚类变量，应用的统计方法和定义的代谢型。根据所选择的聚类变量的数量和类型，代谢型的定义大不相同；它们介于一般禁食代谢型之间，更具体的空腹参数亚组，如血浆脂蛋白或脂肪酸簇，以及对定义的膳食挑战或饮食干预的反应组。这表明术语“元型”具有主观用法，需要一个正式的定义。总之,这篇文献综述显示,代谢分型可以帮助识别对确定的营养干预措施有不同反应的个体亚组.可以在这样的元型组水平给出有针对性的推荐。未来的研究应该通过利用日益可用的代谢组学数据集来开发和验证普遍有效的代谢型的定义。
