1. An Introduction and Overview of Nutritional Genomics: Application to Type 2 Diabetes and International Nutrigenomics (Jim Kaput).
Understanding T2DM: the current view of T2DM and treatment options.
Understanding T2DM: begin before conception.
Understanding T2DM: genetic complexity.
Understanding T2DM: QTLs in humans.
Understanding T2DM: from birth onward.
Understanding T2DM: metabolomics.
Understanding T2DM: environmental influences.
Understanding T2DM: environment is more than diet.
Understanding T2DM: data acquisition and analyses.
Bioinformatics and biocomputation.
Converting science into practice.
Research ethics and genetic privacy.
Public and international policies.
2. The Pursuit of Optimal Diets: A Progress Report (Walter C. Willett).
2.2 Considerations in defining an optimal diet.
2.3 Dietary fat and specific fatty acids.
2.6 Vegetables and fruits.
2.7 Calcium and dairy products.
2.8 Salt and processed meats.
2.10 Vitamin and mineral supplements.
2.11 The potential impact of optimal diet and lifestyle changes.
3. Gene - Environment Interactions: Defining the Playfield (Jose M. Ordovas and Dolores Corella).
3.1 Genetic variability.
3.2 How to detect genetic variability?.
3.3 What to analyze?.
3.4 Environmental factors.
3.5 Gene-environment interactions: focus on diet.
3.6 Common genetic variants and their interaction with dietary factors.
3.7 Gene X Microorganisms interactions.
3.8 The microbiome (microbiota).
3.9 Bringing all together.
4. Metabolomics: Bringing Nutrigenomics to Practice in Individualized Health Asssessment (J. Bruce German, Cora J. Dillard, S. Luke Hillyard, Matthew C. Lange, Jennifer T. Smilowitz, Robert E. Ward, and Angela M. Zivkovic).
4.2 Opportunities for foods and health.
4.3 Tools of metabolomics.
4.4 The future of metabolomics.
4.6 Metabolome assembly and annotation.
4.7 Bioinformatics: knowledge management from genomics and metabolomics to health assessment.
5. Genetic and molecular buffering of phenotypes (John L. Hartman, IV).
5.2 Examples of buffering.
5.3 Experimental concepts for genetic buffering analysis.
5.4 Experimental platforms for global genetic interaction analysis.
6. Gene - Gene Epistasis and Gene - Environment Interactions Influence Diabetes and Obesity (Sally Chiu, Adam L. Diament, Janis S. Fisler, and Craig H. Warden).
6.1 Gene - gene and gene - environment interactions.
6.2 Epistasis and gene - environment interactions in obesity and diabetes.
6.3 Animal models for detecting gene interactions.
6.4 Gene - gene interaction in obesity and diabetes.
6.5 Dietary fat in obesity and diabetes.
6.6 Maternal effects.
6.7 Future directions and conclusions.
7. Nutrients and Gene Expression (Gertrud U. Schuster).
7.2 SREBPs and ChREBP: transcription factors, influenced by dietary lipids and glucose.
7.3 Superfamily of nuclear receptors.
7.4 Nuclear receptors- -structure and function.
7.5 Nuclear receptors as metabolic sensor.
7.7 Phytoesterogens - nutrients mimicking estrogens .
7.9 Concluding remarks.
8. Green Tea Polyphenols and Cancer Prevention (Shangqin Guo and Gail Sonenshein).
8.2 Green tea and cancer epidemiology.
8.3 Animal models.
8.4 Mechanisms of green tea action: molecular signaling pathways and gene targets.
8.5 Clinical studies and the promise of tea in combinatorial therapy.
8.6 Future directions and concluding remarks.
9. Molecular Mechanisms of Longevity Regulation and Calorie Restriction (Su - Ju Lin).
9.1 A conserved longevity factor, Sir2.
9.2 Molecular mechanisms of calorie reduction.
9.3 Role of NAD/NADH ratio in aging and human diseases.
9.4 Possible CR mimetics - small molecules that regulate Sir2 activity.
9.5 The molecular targets of Sir2 proteins in mammals.
9.6 A possibly conserved longevity pathway.
9.7 Applications to nutritional genomics.
10. Maternal Nutrition: Nutrients and Control of Expression (Craig A. Cooney).
10.1 Methyl metabolism.
10.2 DNA methylation, epigenetics, and imprinting.
10.3 Endogenous retroviruses and genome integrity.
10.4 Epigenetics and nutrition can greatly modulate genetic predispositions.
10.5 Yellow mouse models of epigenetic regulation.
10.6 A variety of maternal effects are seen in mice.
10.7 Rat models of maternal effects leading to diabetes.
10.8 Maternal effects on memory and aging.
10.9 Epigenetic effects in foxes.
10.10 Epigenetic effects related to reproduction in humans.
10.11 Nutrients and compounds that may affect early development and epigenetics.
11. Nutrient - Gene Interactions Involving Soy Peptide and Chemopreventive Genes in Prostate Epithelial Cells (Mark Jesus M. Magbanua, Kevin Dawson, Liping Huang, Wasyl Malyj, Jeff Gregg, Alfredo Galvez, and Raymond L. Rodriguez).
11.2 Lunasin structure and function.
11.3 Lunasin treatment of prostate cancer and gene expression profiling.
11.4 Lunasin - induced gene expression profiles.
11.5 Genes for apoptosis.
11.6 Genes involved in suppression of cell proliferation.
11.7 Mitotic checkpoint genes.
11.8 Genes involved in protein degradation.
11.9 Connexin 43 gene for the gap junction protein.
11.10 Target verification using RT - PCR.
12. Enzymes Lose Binding Affinity (increase Km) for Coenzymes and Substrates with Age: A Strategy for Remediation (Bruce N. Ames, Jung H. Suh, and Jiankang Liu).
12.2 Remediation by high B vitamin intake of variant enzymes with poor binding affinity (Km) for coenzymes.
12.3 Deformation of proteins in mitochondria with aging.
12.4 Non - mitochondrial enzymes that are deformed with age.
13. Dietary and Genetic Effects on Atherogenic Dyslipidemia (Ronald M. Krauss, MD, and Patty W. Siri, PhD, MS).
13.1 LDL represent a heterogeneous population.
13.2 LDL subclasses are influenced by genes and the environment.
14. Genistein And Polythenols in the Study of Cancer Prevention: Chemistry, Biology, Statistics and Experimental Design (Stephen Barnes, David B. Allison, Grier P. Page, Mark Carpenter, Gary L. Gadbury, Sreelatha Meleth, Pamela Horn-Ross, Helen Kim, Coral A. Lamartinere, and Clinton J. Grubbs).
14.2 Diet and cancer.
14.3 Chemistry of the polyphenols.
14.4 Uptake, distribution, metabolism, and excretion of the polyphenols.
14.5 Polyphenols and cancer prevention.
14.6 Mechanisms of action of polyphenols.
14.7 Importance of timing exposure to polyphenols.
14.8 Assessing events leading to cancer-low dimensional approaches.
14.9 Statistical consequences of high dimensional approaches.
14.10 High dimensional systems and the importance of the false discovery rate.
14.11 DNA microarray analysis-high dimensional research into gene expression.
14.12 Proteomics analysis-an even bigger challenge.
14.13 Statistical problems with fold-change in DNA microarray and proteomics analyses.
14.14 Design in experiments involving DNA microarray and proteomics analysis.
14.15 The design.
14.16 Role of the computer in high dimensional analysis.
15. Susceptibility to Exposure to Heterocyclic Amines from Cooked Food: Role of UDP-glucuronosyltransferases (Michael A. Malfatti and James S. Felton).
15.2 Genetic susceptibility.
15.4 UDP-glucuronosyltransferase biochemistry.
15.5 UDP-glucuronosyltransferase gene structure.
15.6 Substrate specificity and selectivity.
15.7 Tissue distribution of UPD-glucuronosyltransferase.
15.8 Gene regulation.
15.9 Genetic variation.
15.10 UDP-glucuronosyltransferase and cancer susceptibility.
15.11 Heterocyclic amine carcinogens in food.
15.12 Carcinogenicity of PhIP.
15.13 Metabolism of PhIP.
15.14 UDP - glucuronosyltransferase and PhIP risk susceptibility.
16. The Informatics and Bioinformatics Infrastructure of a Nutrigenomics Biobank (Warren A. Kibbe).
16.2 Next generation biobanks.
16.3 Intended audience for this chapter.
16.4 Regulatory and policy environment.
16.5 HIPAA Health Insurance Portability and Accountability Act of 1996.
16.6 GMPs, GLPs and GCPs.
16.7 Funding of biobanks.
16.8 Biobanking in clinical trials.
16.9 Data standards/semantic interoperability.
16.10 Other Standards Bodies: CDISC.
16.11 Informatics infrastructure.
16.12 System architecture.
16.13 Separation of the clinical trial/patient identity management from the genotype/phenotype repository.
16.14 Database architecture/ data modeling.
16.15 Design practices.
16.16 Pulling it all together.
17. Biocomputation and the Analysis of Complex Datasets in Nutritional Genomics (Kevin Dawson, Raymond L. Rodriguez, Wayne Chris Hawkes, and Wasyl Malyj).
17.2 Nutritional genomics is part of high - throughput biology.
17.3 Gene expression arrays.
17.4 Proteomics and metabolomics data.
17.5 Sources of complexity in nutritional genomics.
17.6 Data sets in nutritional genomics.
17.7 The level of complexity in gene expression experiments.
17.8 Dimensionality reduction methods.
17.9 Case study (microarray experiment of a dietary - intervention).
18. Cultural Humility: A Contribution to Health Professional Education in Nutrigenomics (Melanie Tervalon).
18.2 Cultural Humility.
18.4 Goals and objectives: curriculum content.
18.5 Goals and objectives: curriculum design.
18.6 Curriculum structure and content: didactics, small groups and videotaping.
18.7 The teaching staff.
19. Nutrients and Norms: Ethical Issues in Nutritional Genomics (David Castle, Cheryl Cline, Abdallah S. Daar, Charoula Tsamis, and Peter A. Singer).
19.1 Proactive ethics and nutritional genomics.
19.2 Claims of health benefits arising from nutrigenomics.
19.3 Managing nutrigenomic information.
19.4 Methods for delivering nutrigenomic services.
19.5 Nutrigenomic products.
19.6 Access to nutrigenomics.
"…academic libraries with strong medical and genetic departments would do well to purchase this text." (E-STREAMS, September 2007)
"...there is much valuable information here for the interested reader. I would recommend the book to students and colleagues..." (Doody's Health Services)