Metabolomics as a Tool in Nutrition Research

<ul> <li>List of contributors</li> <li>Woodhead Publishing Series in Food Science, Technology and Nutrition</li> <li>Preface</li> <li>Part One: Principles<ul><li>1. Challenges in nutritional metabolomics: from experimental design to interpretation of data sets<ul><li>Abstract</li> <li>1.1 Introduction</li> <li>1.2 The experimental design</li> <li>1.3 The analytical platform</li> <li>1.4 Extraction of data sets and statistical analyses</li> <li>1.5 Metabolite identification</li> <li>1.6 Biological interpretations</li> <li>1.7 Conclusion: do we need standardisation procedures and repositories?</li></ul></li> <li>2. Metabolic profiling as a tool in nutritional research: key methodological issues<ul><li>Abstract</li> <li>2.1 Introduction</li> <li>2.2 Key issues in nutritional research</li> <li>2.3 The role of genomics, proteomics, metabolomics, and metagenomics in nutritional research</li> <li>2.4 Applications of metabolomics in nutrition-related research</li> <li>2.5 The use of metabolomics to assess the effects of diet on health</li> <li>2.6 Methods for mapping dietary patterns</li> <li>2.7 Observational and interventional studies into the effects of diet and nutrition on health</li> <li>2.8 Analytical methods</li> <li>2.9 Issues in analysing samples</li></ul></li> <li>3. Chemometrics methods for the analysis of genomics, transcriptomics, proteomics, metabolomics, and metagenomics datasets<ul><li>Abstract</li> <li>3.1 Introduction</li> <li>3.2 Unsupervised and supervised pattern recognition methods</li> <li>3.3 Multivariate calibration methods for developing predictive models</li> <li>3.4 Statistical data integration methods</li> <li>3.5 Data integration: multiblock strategies</li> <li>3.6 Data integration: calibration transfer methods</li> <li>3.7 Data integration: multiway/multimodal analysis methods</li> <li>3.8 Data integration: correlation-based approaches</li> <li>3.9 Data integration: techniques for analysing different types of genomics datasets</li> <li>3.10 Statistical data integration of different sample types</li> <li>3.11 Statistical data integration of different molecular components in samples</li> <li>3.12 Modelling relationships between molecular components</li> <li>3.13 Conclusion and future trends</li></ul></li></ul></li> <li>Part Two: Applications in nutrition research<ul><li>4. Application of lipidomics in nutrition research<ul><li>Abstract</li> <li>Acknowledgement</li> <li>4.1 Introduction</li> <li>4.2 Lipids</li> <li>4.3 Lipidomics</li> <li>4.4 Lipidomics in nutrition research</li> <li>4.5 Conclusion and future trends</li></ul></li> <li>5. Analysing human metabolic networks using metabolomics: understanding the impact of diet on health<ul><li>Abstract</li> <li>Acknowledgements</li> <li>5.1 Introduction</li> <li>5.2 Metabolic network reconstruction</li> <li>5.3 Human metabolic networks</li> <li>5.4 Linking metabolomics data and metabolic network elements</li> <li>5.5 Metabolism modelling, from pathways to network</li> <li>5.6 Subnetwork extraction between identified metabolites</li> <li>5.7 Conclusion and future directions</li></ul></li> <li>6. Using metabolomics to analyse the role of gut microbiota in nutrition and disease<ul><li>Abstract</li> <li>6.1 Introduction: gut microbiota and human health</li> <li>6.2 Metagenomics of gut microbiota</li> <li>6.3 Metabolomics: uncovering complex host–microbe interactions</li> <li>6.4 The marriage of metagenomics and metabolomics: microbiome–metabolome interactions</li> <li>6.5 Future perspectives: personalised nutrition</li></ul></li> <li>7. Metabotyping: moving towards personalised nutrition<ul><li>Abstract</li> <li>7.1 Introduction</li> <li>7.2 The concept of the metabotype</li> <li>7.3 Examples of metabotyping with a focus on nutrition</li> <li>7.4 Extension of metabotypes to include markers of dietary origin</li> <li>7.5 Conclusion and future trends</li> <li>7.6 Sources of further information and advice</li></ul></li> <li>8. Using metabolomics to identify biomarkers for metabolic diseases: analytical methods and applications<ul><li>Abstract</li> <li>8.1 Introduction</li> <li>8.2 Using metabolomics to understand the relationship between nutrition and chronic metabolic diseases</li> <li>8.3 Cohort studies and biomarker identification</li> <li>8.4 Isolating in situ biomarkers</li> <li>8.5 Conclusions and future trends</li></ul></li> <li>9. Using metabolomics to evaluate food intake: applications in nutritional epidemiology<ul><li>Abstract</li> <li>9.1 Introduction</li> <li>9.2 Biomarkers as a complementary approach to questionnaires</li> <li>9.3 Definition of the food metabolome</li> <li>9.4 Metabolomics as a tool for dietary biomarker discovery</li> <li>9.5 Dietary patterns and metabolomic profiles: potential use of nutritypes</li> <li>9.6 Validation of putative biomarkers</li> <li>9.7 The future of metabolomics in dietary assessment</li> <li>9.8 Conclusion</li></ul></li> <li>10. Metabolomics and nutritional challenge tests: what can we learn?<ul><li>Abstract</li> <li>10.1 Introduction</li> <li>10.2 Application of metabolomics to challenge tests</li> <li>10.3 Conclusion and future trends</li></ul></li> <li>11. Using metabolomics to describe food in detail<ul><li>Abstract</li> <li>11.1 Introduction</li> <li>11.2 Using metabolomics to assess the effects of genetic selection and modification</li> <li>11.3 Using metabolomics to assess the effects of organic versus conventional farming</li> <li>11.4 Using metabolomics to identify the geographical origin of food products</li> <li>11.5 Using metabolomics to assess the effects of rearing conditions on the quality of meat, eggs, and fish</li> <li>11.6 Using metabolomics to assess the effects of processing on food quality</li> <li>11.7 Using metabolomics to assess the effects of digestion on nutrient intake from particular foods</li> <li>11.8 Conclusion</li> <li>Appendix: abbreviations</li></ul></li> <li>12. Future perspectives for metabolomics in nutrition research: a nutritionist’s view<ul><li>Abstract</li> <li>12.1 Introduction</li> <li>12.2 Metabolites identification and biological relevance</li> <li>12.3 In vivo metabolomics</li> <li>12.4 Conclusion</li></ul></li></ul></li> <li>Index</li></ul>