Metabolomics as a Tool in Nutrition Research. Woodhead Publishing Series in Food Science, Technology and Nutrition

Table of Contents

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

Authors