Nutrigenomics: exploiting systems biology in the nutrition and health arena

Ommen, Ben van; Stierum, Rob

doi:10.1016/s0958-1669(02)00349-x

Cited by 196 publications

(131 citation statements)

References 25 publications

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“…Systems biology is an inter-disciplinary study of genomics, transcriptomics, proteomics, metabolomics and bioinformatics (van Ommen and Stierum, 2002). Systems biology is concerned with understanding the dynamic outcome of molecular interactions among biomolecules at the pathway, cellular network, cell, tissue and organismal levels.…”

Section: The Different Levels Of Systems Biologymentioning

confidence: 99%

“…This paradigm shift involves the study of actual genomic regions and their effects or associations with performance, in contrast to current methods that rely on the statistical analysis of large quantities of phenotypic data. Systems biology is an inter-disciplinary study of genomics, transcriptomics, proteomics, metabolomics and bioinformatics (van Ommen and Stierum, 2002). However, often omitted from this description is arguably the most important discipline, the definition of the phenotype (i.e.…”

Section: Introductionmentioning

confidence: 99%

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The integration of ‘omic’ disciplines and systems biology in cattle breeding

Berry

Meade

Mullen

et al. 2011

Animal

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Enormous progress has been made in the selection of animals, including cattle, for specific traits using traditional quantitative genetics approaches. Nevertheless, considerable variation in phenotypes remains unexplained, and therefore represents potential additional gain for animal production. In addition, the paradigm shift in new disciplines now being applied to animal breeding represents a powerful opportunity to prise open the 'black box' underlying the response to selection and fully understand the genetic architecture controlling the traits of interest. A move away from traditional approaches of animal breeding toward systems approaches using integrative analysis of data from the 'omic' disciplines represents a multitude of exciting opportunities for animal breeding going forward as well as providing alternatives for overcoming some of the limitations of traditional approaches such as the expressed phenotype being an imperfect predictor of the individual's true genetic merit, or the phenotype being only expressed in one gender or late in the lifetime of an animal. This review aims to discuss these opportunities from the perspective of their potential application and contribution to cattle breeding. Harnessing the potential of this paradigm shift also poses some new challenges for animal scientists -and they will also be discussed.

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Section: The Different Levels Of Systems Biologymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The integration of ‘omic’ disciplines and systems biology in cattle breeding

Berry

Meade

Mullen

et al. 2011

Animal

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“…Concentrations of one or more metabolites, genetic variations, and alterations in dietary intake may have specific patterns associated with physiological outcomes and responses to treatments. Examples of these interconnections among RNA, protein, and metabolite levels have been published [76]. The goal is to use one or more dimensionality reduction methods to discover interactions and patterns among these datasets that explain complex traits, including health and disease.…”

Section: The Analytical Challenge: Finding the Patterns In High-dimenmentioning

confidence: 99%

Complexity of type 2 diabetes mellitus data sets emerging from nutrigenomic research: A case for dimensionality reduction?

Kaput

Dawson

2007

Mutation Research/Fundamental and Molecular Mechanisms of Mutag

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Nutrigenomics promises personalized nutrition and an improvement in preventing, delaying, and reducing the symptoms of chronic diseases such as diabetes. Nutritional genomics is the study of how foods affect the expression of genetic information in an individual and how an individual's genetic makeup affects the metabolism and response to nutrients and other bioactive components in food. The path to those promises has significant challenges, from experimental designs that include analysis of genetic heterogeneity to the complexities of food and environmental factors. One of the more significant complications in developing the knowledge base and potential applications is how to analyze high-dimensional datasets of genetic, nutrient, metabolomic (clinical), and other variables influencing health and disease processes. Type 2 diabetes mellitus (T2DM) is used as an illustration of the challenges in studying complex phenotypes with nutrigenomics concepts and approaches.

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“…Nutrigenomics is the convergence of three areas of researchhealth, diet, and genomics -and has been reviewed by numerous researchers (Bauer et al, 2004;Chadwick, 2004;Fenech, 2005;Gillies, 2003;Junien and Gallou, 2004;Kaput and Rodriguez, 2004;Muller and Kersten, 2003;Ommen and Groten, 2004;Ordovas and Mooser, 2004;Peregrin, 2001;Ruden et al, 2005;Trayhurn, 2003;van Ommen, 2004;van Ommen and Stierum, 2002). Health and diet converge in the field of nutrition, diet and genomics converge in the emerging fields of expression profiling, proteomics, and metabolomics, whereas health and genomics converge in the field of identifying biomarkers to classify and understand diseases .…”

Section: Nutrigenomics Approaches Nutrigenomics Approaches Nutrigenommentioning

confidence: 99%

Evolutionary conservation of metabolism explains howDrosophila nutrigenomics can help us understand human nutrigenomics

Ruden

2006

Genes Nutr

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Nutrigenomics: exploiting systems biology in the nutrition and health arena

Cited by 196 publications

References 25 publications

The integration of ‘omic’ disciplines and systems biology in cattle breeding

The integration of ‘omic’ disciplines and systems biology in cattle breeding

Complexity of type 2 diabetes mellitus data sets emerging from nutrigenomic research: A case for dimensionality reduction?

Evolutionary conservation of metabolism explains howDrosophila nutrigenomics can help us understand human nutrigenomics

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