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Metabotyping and its application in targeted nutrition: an overview
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| Zeitschriftentitel: | British Journal of Nutrition |
|---|---|
| Personen und Körperschaften: | , , , , |
| In: | British Journal of Nutrition, 117, 2017, 12, S. 1631-1644 |
| Format: | E-Article |
| Sprache: | Englisch |
| veröffentlicht: |
Cambridge University Press (CUP)
|
| Schlagwörter: |
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Riedl, Anna Gieger, Christian Hauner, Hans Daniel, Hannelore Linseisen, Jakob Riedl, Anna Gieger, Christian Hauner, Hans Daniel, Hannelore Linseisen, Jakob |
|---|---|
| author |
Riedl, Anna Gieger, Christian Hauner, Hans Daniel, Hannelore Linseisen, Jakob |
| spellingShingle |
Riedl, Anna Gieger, Christian Hauner, Hans Daniel, Hannelore Linseisen, Jakob British Journal of Nutrition Metabotyping and its application in targeted nutrition: an overview Nutrition and Dietetics Medicine (miscellaneous) |
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riedl, anna |
| spelling |
Riedl, Anna Gieger, Christian Hauner, Hans Daniel, Hannelore Linseisen, Jakob 0007-1145 1475-2662 Cambridge University Press (CUP) Nutrition and Dietetics Medicine (miscellaneous) http://dx.doi.org/10.1017/s0007114517001611 <jats:title>Abstract</jats:title><jats:p>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.</jats:p> Metabotyping and its application in targeted nutrition: an overview British Journal of Nutrition |
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Metabotyping and its application in targeted nutrition: an overview |
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Metabotyping and its application in targeted nutrition: an overview |
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Metabotyping and its application in targeted nutrition: an overview |
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Metabotyping and its application in targeted nutrition: an overview |
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Metabotyping and its application in targeted nutrition: an overview |
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Metabotyping and its application in targeted nutrition: an overview |
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metabotyping and its application in targeted nutrition: an overview |
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Nutrition and Dietetics Medicine (miscellaneous) |
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2017 |
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<jats:title>Abstract</jats:title><jats:p>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.</jats:p> |
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| description | <jats:title>Abstract</jats:title><jats:p>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.</jats:p> |
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| spelling | Riedl, Anna Gieger, Christian Hauner, Hans Daniel, Hannelore Linseisen, Jakob 0007-1145 1475-2662 Cambridge University Press (CUP) Nutrition and Dietetics Medicine (miscellaneous) http://dx.doi.org/10.1017/s0007114517001611 <jats:title>Abstract</jats:title><jats:p>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.</jats:p> Metabotyping and its application in targeted nutrition: an overview British Journal of Nutrition |
| spellingShingle | Riedl, Anna, Gieger, Christian, Hauner, Hans, Daniel, Hannelore, Linseisen, Jakob, British Journal of Nutrition, Metabotyping and its application in targeted nutrition: an overview, Nutrition and Dietetics, Medicine (miscellaneous) |
| title | Metabotyping and its application in targeted nutrition: an overview |
| title_full | Metabotyping and its application in targeted nutrition: an overview |
| title_fullStr | Metabotyping and its application in targeted nutrition: an overview |
| title_full_unstemmed | Metabotyping and its application in targeted nutrition: an overview |
| title_short | Metabotyping and its application in targeted nutrition: an overview |
| title_sort | metabotyping and its application in targeted nutrition: an overview |
| title_unstemmed | Metabotyping and its application in targeted nutrition: an overview |
| topic | Nutrition and Dietetics, Medicine (miscellaneous) |
| url | http://dx.doi.org/10.1017/s0007114517001611 |