The document discusses nutrigenomics and nutrigenetics, emphasizing the dynamic relationship between nutrition and the human genome, including the role of dietary signatures in health and disease risk. It highlights the need for personalized nutrition approaches based on individual genetic variability and the implications for developing targeted dietary interventions. Additionally, it explores methodologies and findings related to the effects of specific nutrients on gene expression and metabolic responses.

1. NUTRIGENOMICS
More Sachin C.

2. "If we could give every individual the right amount
of nourishment and exercise, not too little and not
too much, we would have found the safest way to
health.”
"Leave your drugs in the chemist's pot if you can
heal the patient with food."
- Hippocrates

3. Balanced Diet Pyramid

5. Family Health at Risk

6. Nutrients acts as dietary signals
Nutritional factors
Transcription factors
Gene transcription
Energy Cell
homeostasis proliferation
Nutrient
absorption

7. What are dietary signatures/profiles?
Patterns of gene expression, protein expression
and metabolite production in response to particular
nutrients or nutritional regimes can be viewed as
'dietary signatures
How can these dietary signatures been used in
Nutrigenomics research?
Nutrigenomics seeks to examine these dietary
signatures in specific cells, tissues and organisms,
and to understand how nutrition influences
homeostasis. Dietary signatures can be used to
identify (early) molecular biomarkers

8. Nutritional Genomics
• Nutrigenomics studies modulating effects of
nutrients on gene structure and expression; related
science of Nutrigenetics researches patients’ unique
responses-caused by specific genetic variations-to
macro- and micronutrients
(Desiere, 2004)
• “… the interface between the nutritional environment
and cellular/ genetic processes”
(Kaput and Rodriguez, 2004)
• Next frontier in the post genomic age
• Off shoot of HGP

9. Health effects of the nutrient and non-nutrient components
of food relates specific molecular interactions
(Ommen et al., 2004)

10. Two sub definitions
• Two sides of a coin
• Dynamic cause–effect
relationship
between nutrition and
the human genome
(Mutch et al., 2005)

11. Nutrigenomics Nutrigenetics
 Aims to study the genome- wide  Concerned with how genetic
influence of nutrition variation determines an
individual’s disease risk,
nutrient requirements,
metabolic response and
 Concerned with the functional
responsiveness to a bioactive
effect of nutrient or non-nutrient dietary components or
food components on the genome, nutritional therapy
transcriptome, proteome and
metabolome
(Muller and Kersten, 2003) (DeBusk et al., 2005)

12. Two-way interaction between nutrition and the
human genome
(Roche, 2004)

13. The direct and indirect effects of nutrients
(Muller and Kersten, 2003)

14. Challenge
• Common, polygenic, diet-related diseases which
are composite of multiple genetic variants
interacting with multiple environmental factors
• To develop and apply a robust nutritional genomics
research approach that is sensitive enough to
take account of both genetic heterogeneity and
diverse nutrient exposure

15. Nutrigenomics – A Systems Biology Approach

16. Bioactive food components influence genetic and
epigenetic events

17. Dietary factors and the regulation of DNA
methylation

18. “omics” of nutrition to identify how dietary factors
contribute to phenotype

19. Implications of approach
• New way of dealing with nutrigenomics data aims
to integrate all of the gene expression and/or
proteomic data and present this information as a
‘complete’ biological process
• Multivariate analytical approach
• Key to our understanding of nutrition and health

20. Health Effect of Dietary Fatty
Acids and TFs
• Fatty acids had important metabolic effects with
respect to energy homeostasis, lipoprotein
metabolism, glucose homeostasis and
inflammation
• Potent cellular molecules that interact with several
transcription factors, which in turn explains the
diverse health effect of altered dietary fat intake

21. Lipid sensitive transcription factors

22. Cross talk between lipid sensitive TFs
PPARα activation
inhibits
LXR binding
regulation
Expression of SREBP-1c & other
downstream lipogenic genes
(Clarke et al., 1999)

23. Metabolomics – The Newest Tool
• Utilizes analytical chemistry technologies,
1) NMR
2) MS
• Help Capture Data On Complete Metabolome
• May provide the comprehensive biomarker of
multiple metabolites to asses nutrient status
metabolic responses and disease predispositions

24. Metabolism approach
• n-6 PUFA and n-3 PUFA interventions
• Hepatic transcriptome and lipid metabolome
completed
• Diets supplemented with AA or EPA or fish oil
• Studied down-regulation of hepatic SCD1 and not
SCD2 or SCD3
• SCD1 potential therapeutic target to protect against
CVD and diet-induced obesity

25. Nutrigenetics – Individual Genetic
Variability And Responsiveness
• Human genome 99.9% identical
• 0.1% variation principally due to SNPs, responsible
for 90% variation among individuals
• Functional and Non-functional SNPs
• Gene-Nutrient interaction concept important
• Standard “one-size-fits-all” strategy is no longer
considered to be good practice

26. Interrelationships Among Specific Nutrients,
Genes and Health Outcomes
• Green Tea (Camellia sinensis)
- Potent antioxidants-prevent certain cancers and
heart disease
- Some women appear to show a reduction in
breast cancer
- Have gene variant that produces less active form
of gene enzyme COMT inactivating carcinogenic
compounds

27. Contd…
• Curcumin:
-yellow pigment from turmeric (Curcuma longa) -
basic ingredient in Curries
-produce suppressing genes for enzymes that
produce inflammatory prostaglandins
e.g. cyclooxygenase-2 (COX-2)
• Prostaglandins linked to colon cancer, heart
disease, arthritis, and Alzheimer’s disease
• “curry-eating people of India have the world’s lowest
incidence of Alzheimer’s disease”
- Sally A. Frautschy,
Professor of Neurology,
University of California

28. PERSONALIZED NUTRITION
• Pioneer worker in Nutrigenomics
• Talks about virtual lab
Senior Scientist Jose Ordovas
Tufts' Human Nutrition • Personalized nutrition for
Research Center on Aging everyone in cost effective manner
and behavioral guidelines for each
individual depending on ones
health status to reduce disease
predisposition
• To be cautious regarding
interpretations we need to move
step-by-step like solving puzzle to
create big picture

29. Step 1
Collecting (patient) information
• Physical examination
• Questionnaire
 Diet
 Disease history
 Lifestyle

30. Step 2
Looking for genetic differences that mirror physical
differences in patients
– PCR
– Gel electrophoresis
– DNA sequencing

31. Step 3
Examining the foods
You can separate the different chemicals that make
up a food using their different properties by:
– Different solubility
– Chromatography

32. Step 4
Test the effect of the food components on cells
• Cell lines (luminescence)

33. Step 5
Test the food components of the cells in vivo
• Animal models (micro-arrays)

34. What happens next?
• Make individualised dietary recommendations to
patients?
• Produce dietary supplements to enhance individual
genetic potential?
• Produce dietary supplements to suppress gene
activity?

35. Commercialization
• http://www.mycellf.com/MyCellfProgram.aspx
• Sciona Inc. (www.sciona.com)
• Genelex Inc. (www.genelex.com)

36. CASE STUDIES

38. INTRODUCTION
• (PPARs), α and Ƴ ligand-activated transcriptional factors
regulating lipid and lipoprotein metabolism; glucose homeostasis,
and inflammation
• PPAR α- Expressed in liver
-promotes microsomal ω-oxidation and peroxisomal β-
oxidation of Fatty acids
Ligands- Fatty acids and FFs
• PPAR Ƴ- Expressed in Adipose tissue
-Ligands- UFAs
• Isohumulones generated from humulones in Hops imparting bitter
taste to beer
• Dual Agonists of both PPAR TFs
(Yajimi et al., 2004)

39. Research Methodology
• Materials: IHE by extracting hops with supercritical co2;
isomerised in alkaline condition
• Animals and Diets:
-C57BL/6NCrj and PPAR α-/- /129S4/SvJae mice
-AIN-76A Diet
• DNA Microarray analysis:
-RNA extraction
-cDNA labelling Cy3 or Cy5
• QPCR: primers designed with primer3 software
• Statistical Analysis: One way ANOVA

40. Results and Discussion
Biochemical parameters in male mice
Effect of IHE and FF :

41. Plasma Total
cholesterol HDL cholesterol
Triglycerides Non esterified FFA

42. Transcriptional profiling and QPCR analyses in
male C57BL/6N mice
• 8245 genes analysed out of which approx.1200
shown enough signal intensity
• IHE-20 and FF-100 genes: 2 fold or more expression
• No significant difference when diet supplemented
with Cholesterol

44. Dose-dependent induction of representative PPARα
target genes in liver, by IHE

45. Gender differences in IHE-induced hepatic
gene expression.

46. Conclusion
• Data showed IHE increased the
expression of hepatic PPARα target
genes
• Effect similar to FF
• IHE modulated blood lipid status by
activating PPARα
• So IHE may be potentially therapeutic for
preventing T2DM and Atherosclerosis
• Beer consumption might actually help to
prevent alcoholic liver disease ‼

48. Introduction
• UVA exposure cause skin aging by singlet oxygen
(1O2)-dependent pathways
• Gene regulation through TF AP-2.
• β-carotene (βC) can protect skin since:
1. 1O2 quencher
2. scavenges ROS
3. Mildly reduces sunburns
• HaCaT human keratinocytes used.(2 d, 1.5 µM)

49. Research Methodology
• βC and UVA Treatment of keratinocytes
• Affymetrix GeneChip Analysis:
Five independent, factorially designed cell
irradiation experiments analyzed by microarray
hybridization.
• QRT-PCR to confirm key gene regulations in three
independent cell irradiation experiments at different
βC concentrations.(0.5, 1.5 and 3 µM)
• Apoptosis Assay : Caspase 3-activity 5 h after
irradiation using CaspACE Assay System

50. Results and Discussion
• Cellular uptake of βC confirmed by HPLC
• 1458 genes significantly regulated by at least one
treatment:
a) βC regulated 381 genes
b) UVA influenced 568 genes
c) UVA / βC regulated 1142 genes
d) not regulated by single treatment 610 genes

51. βC effects in unirradiated keratinocytes
Differential
regulation
Genes up
regulated
Genes down
regulated Receptor innate immunity
Key process-
skin aging
Marker genes
Shown RA-independent effects

52. Down regulation
βC concentration dependently
induced caspase-3 activity in
ultraviolet light A (UVA)-irradiated
keratinocytes.
βC promoted keratinocyte
differentiation but not
terminal steps

53. Ultraviolet light A (UVA) effects in keratinocytes

54. βC effects in UVA-irradiated keratinocytes
Differentially regulated
Quenched by proinflammatory genes
βC
Enhanced
tanning
supplemented
UVA
βC supplementation may indeed reduce wrinkling.
(Battistutta et al., 2000)

55. Contd…
• RA target genes down regulated by UVA
• Further promoted differentiation in irradiated
keratinocytes
• This may render combined UVA / βC treatment a
promising therapy for skin disorders associated
with disturbed differentiation. e.g. Psoriasis.

56. Proposed relationship of the modes of action
of β -carotene to its influence on ultraviolet
light A-induced biological processes.

57. Conclusion

58. Discussion