Towards the Sixth Framework Programme

1
Obesity The Metabolic Syndrome All in the genes
or what we eat?
Helen M Roche Nutrigenomics Research Group UCD
School of Public Health UCD Conway
Institute University College Dublin Ireland
2
Obesity The Metabolic Syndrome All in the genes
or what we eat?

• Introduction to Nutrigenomics The Metabolic
  Syndrome
• Core concepts - metabolic syndrome nutritional
  genomics
• Progressive phenotype - Multiple metabolic
  pathways
• Nutrient derived metabolic inflammatory
  stressors
• Diet, Genes The Metabolic Syndrome
• Genetic determinants of the metabolic syndrome
• Interactions between dietary fatty acids
  genetic markers of MS
• Insights from the LIPGENE Human Dietary
  Intervention Study

3
Nutritional Genomics A Novel Tool for Nutrition
Research

• Good nutrition promotes health and quality of
  life
• Human Genome Project
• New genetic information polygenic / diet-related
  diseases
• Genetic variation SNPs Environmental factors
• Nutrition is a key environmental factor which
  interacts with the genome
• Dietary signals influence the metabolic
  programming of cells
• Nutrient derived metabolic stressors can alter
  cellular homeostasis
• Aim of Nutrigenomics is to understand how
  nutrients interact with the genome, identify
  novel nutrient sensitive molecular targets
• Enhance the expression of genes that promote
  metabolic health
• Suppress those that predispose to the MetS, T2DM
  CVD.

4
Nutrigenomics
Genomics
DNA
Disease
Health
Nutrients
RNA
Metabolism
Protein
Proteomics
Transcriptomics
Metabolomics
5
NutrigenomicsGene-Nutrient Nutrient-Gene
Interactions
Health Disease
Transcription Translation Metabolism
The Human Genome
Environmental Factors
Nutrient Requirements
Nutrient Intake
6
NutrigenomicsGene-Nutrient Nutrient-Gene
Interactions
Metabolic Syndrome
Transcription Translation Metabolism
The Human Genome
Environmental Factors
Nutrient Intake
Nutrient Requirements
7
The Metabolic Syndrome
WHO definition
Diabet Med 199815539-53
8
Prevalence of the Metabolic Syndrome

• Increasing prevalence of obesity
• Significant health socioeconomic consequences
• Metabolic Syndrome Type 2 Diabetes Mellitus
• By 2010
• 31m Europeans 239m people worldwide
• Will require treatment for T2DM related
  complications
• Need to identify effective dietary therapies
• Reduce the risk of the Metabolic Syndrome
• Attenuate the impact of the modifiable risk
  factors

9
The Metabolic Syndrome
Sensitive Genotype
Molecular mechanisms
Metabolic Stress
Inflammation
Progressive phenotype
Obesity
Insulin Resistance
Glucose Intolerance
Metabolic Syndrome
T 2 DM
10
Obesity is a pro-inflammatory stateMacrophage
infiltration in adipose tissue

• Adipocytes secrete low levels of TNF-a
• Stimulates pre-adipocyte and endothelial cell
  MCP-1
• Other adipocytokines and FFA may stimulate
  oxidative stress promoting monocyte infiltration
  and MO recruitment.
• Pro-inflammatory state, impaired adipocyte
  function insulin resistance.

11
Dietary Fatty Acids, Genetic Background The
Metabolic Syndrome

• Introduction to Nutrigenomics The Metabolic
  Syndrome
• Core concepts - metabolic syndrome nutritional
  genomics
• Progressive phenotype - Multiple metabolic
  pathways
• Nutrient derived metabolic inflammatory
  stressors
• Diet, Genes The Metabolic Syndrome
• Genetic determinants of the metabolic syndrome
• Interactions between dietary fatty acids
  genetic markers of MS
• Insights from the LIPGENE Human Dietary
  Intervention Study

12

• LIPGENE
• Diet, genomics and the metabolic syndromean
  integrated nutrition, agro-food, social and
  economic analysis
• Sixth Framework Programme
• Priority 1.1.5
• Food Quality and Safety

Trinity College Dublin
13
LIPGENE Partners

• Economic Science
• LMC International
• Consumer Science
• University of Ulster
• University of Porto
• Dissemination
• British Nutrition Foundation

• Human Nutrition
• Trinity College Dublin
• University of Reading
• University of Oslo
• University of Bergen
• INSERM
• University of Cordoba
• Maastricht University
• Uppsala University
• University of Krakow
• Unilever Best Foods
• Hitachi, Europe Limited

• Animal Nutrition
• University of Reading
• Rowett Research Institute
• MTT Agrifood Finland
• INRA
• Plant Biotechnology
• BASF Plant Science GmbH
• University of York
• Rothamsted Research

14
Economic Science
Consumer Science
Dissemination
Human Nutrition
Management Training
Animal Nutrition
Plant Biotec
15
Human Nutrition Work Programme

• Prospective case control genetic study
• SUIVIMAX cohort (n13,000). Baseline metabolic
  and dietary information
• 750-1,000 metabolic syndrome cases and controls
• Genotype and plasma fatty acid composition
• Human dietary intervention study
• Multi-centre, trans-EU intervention study in
  subjects with the MS
• Dietary fat quantity and quality LF v HF,
  substitute SFA with MUFA
• Biochemical markers of MS IVGT, lipoproteins,
  fatty acid composition, etc.
• Genetic polymorphisms of MS
• Functional / molecular studies
• Cell culture animal models of insulin
  resistance.
• Target organs adipose tissue, skeletal muscle,
  vascular endothelium

16
Basic hypothesis Dietary fat composition
genotype Metabolic syndrome

• Proof of concept gene-nutrient interactions
• Apo E cholesterol metabolism
• MTHFR folate requirements/metabolism
• PPARg, fatty acids insulin sensitivity
• Metabolic Syndrome
• Several candidate gene-nutrient interactions
• PPARg, PPARd, SREBP-1c, LXRs, etc.
• Insulin signalling glucose transport
• Apolipoproteins

17
Obesity The Metabolic Syndrome All in the genes
or what we eat?

• Genetic susceptibility / Environmental
  interactions
• Polygenic disorder multiple genetic markers,
  increase risk /- confer protection.
• Familial studies sibling relative risk 3.5
  4.0
• Twin studies
• Heritability of glucose intolerance, obesity
  HDL greater in MZ twins
• Low heritability estimates for hyperinsulinaemia,
  hypertension hypertriacylglycerolaemia
• Genotype relative risk, frequency, population
  attributable risk
• Has not changed in the last 5 - 10 - 20 years.
• Gene-Gene, Gene-Nutrient, Gene-Nutrient-Lifestyle
  Interactions.
• Genetic Determinants of Dietary Responsiveness

18
Gene-nutrient Interactions The Metabolic
Syndrome

• PPARg (Peroxisome proliferator activator
  receptor g)
• Strong candidate - transcription factor
• Biological role in adipogenesis, lipid and
  glucose metabolism
• Common PPARg2 variant (Pro12Ala)
• 75 population carry Pro12 allele
• Higher BMI, insulin and glucose concentrations
  reduced insulin sensitivity.
• Increased risk of MS T2DM (RR 1.25 fold)
• In man loss of function mutations - insulin
  resistance, hypertension T2DM
• Modest impact on individuals, but a dramatic
  effect at the population level
• PPARg Gene - Nutrient Interactions
• Dietary Fat Composition - Metabolic Syndrome
  T2DM
• Genetic Determinants of Dietary
  Responsiveness????

19
A Pro12Ala substitution in PPARg2 associated with
decreased receptor activity, lower body mass
index and improved insulin sensitivity Samir S.
Deeb1, Lluis Fajas2, Masami Nemoto1, Jussi
Pihlajamäki3, Leena Mykkänen3, Johanna Kuusisto3,
Markku Laakso3, Wilfred Fujimoto1 Johan Auwerx2

• 3 year follow up BMI, insulin, HDL TAG

Nat Genet. 1998 20(3)284-187
20
A Pro12Ala substitution in PPARg2 associated with
decreased receptor activity, lower body mass
index and improved insulin sensitivity Samir S.
Deeb1, Lluis Fajas2, Masami Nemoto1, Jussi
Pihlajamäki3, Leena Mykkänen3, Johanna Kuusisto3,
Markku Laakso3, Wilfred Fujimoto1 Johan Auwerx2

• PPARg2 Ala variants
• Less efficient transcriptional activator
• 2 fold lower affinity to the PPRE
• Less efficient activation of PPRE
• in response to PPARg ligands
• Protective against development
• of MS / T2DM

Nat Genet. 1998 20(3)284-187
21

• Study Details
• Evaluated 16 genetic association studies
• (n3,000 individuals)
• Modest (GRR 1.25) but significant increase in
  diabetes risk associated with PPARg Pro12Ala
  polymorphism
• Main Findings
• Common allele (85 population)
• Modest effect in individuals (1.25 fold)
• Large population attributable risk
• influencing 25 of T2DM in the population.

Nat Genet. 2000 26(1)76-80
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Dietary fatty acid composition the Metabolic
Syndrome

• Epidemiological data Nurses Health Study
• Investigate the relationship between dietary fat,
  cholesterol and CVD risk among women with T2DM
• 5272 women from the NHS with T2DM, of which 619
  new CVD cases
• Key Results Nurses Health Study
• Saturated fat, but not total fat, increased CVD
  risk in women with T2DM
• Relative risk of CVD for each 5 energy SFA was
  1.29 (P0.04)
• PS ratio was inversely associated with CVD risk
• Replacement of 5 of energy with
• carbohydrates or MUFA,
• reduced CVD risk by 22 and 37.
• Am J Clin Nutr. 2004
  79 999

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KANWU STUDY - Substituting dietary SFA for MUFA
impairs insulin sensitivity

• Controlled multi-centre isocaloric dietary
  intervention study
• 162 middle aged individuals
• Substitution SFA for MUFA for 90 days
• 37 fat diet SFA MUFA PUFA
• SFA Diet 17 14 6
• MUFA Diet 2 23 6
• N-3 PUFA supplementation
• 3.6 g n-3 PUFA /d
• Intravenous glucose tolerance test
• Insulin sensitivity index (SI)
• First phase insulin response (0-8 min)
• Diabetologia 2001 44 312

26
KANWU STUDY - Substituting dietary SFA for MUFA
impairs insulin sensitivity

• The beneficial effect of fat quality on insulin
  sensitivity was not seen in individuals with a
  high-fat intake (gt37)

Diabetologia 2001 44 312
27
KANWU STUDY - Substituting dietary SFA for MUFA
impairs insulin sensitivity
Diabetologia 2001 44 312
28
A Mediterranean high-carbohydrate diet improves
glucose metabolism in health young persons

• Randomised crossover dietary intervention study
• 59 young healthy subjects
• Initial SFA diet 28 days MUFA or high CHO diet
  for 28 days
• SFA MUFA PUFA
• SFA Diet 20 12 6
• MUFA Diet 10 22 6
• CHO Diet 10 12 6
• Modified insulin suppression test
• Steady state plasma glucose (SSPG)
• Steady state plasma insulin (SSPI)
• In vitro glucose disposal
• Insulin stimulated glucose uptake in monocytes
• 
  
  
  Diabetologia 2001 44 2038

29
A Mediterranean high-carbohydrate diet improves
glucose metabolism in health young persons

• Diabetologia 2001 44 2038

30
Effect of diets enriched in SFA, MUFA or trans-FA
on insulin sensitivity substrate oxidation in
health adults

• Randomised double-blind, crossover dietary
  intervention study
• 25 young healthy subjects
• Three controlled 4-week diets (27 Fat 58 CHO
  15 P)
• SFA MUFA PUFA trans-FA
• SFA Diet 12.2 9.3 6.4 -
• MUFA Diet 5.8 15.2 6.3 -
• Trans-FA Diet 7.3 8.4 4.0 7.3
• Intravenous glucose tolerance test
• Minimal model to assess insulin sensitivity
• Results
• No effect of dietary fatty acids on insulin
  sensitivity
• Low-fat nature of the intervention diet
• Observed a greater decrease in SI on the S diet
  in overweight individuals
• 
  
  Diabetes Care 2002 25 1288

31
N-3 PUFA Insulin Sensitivity

• Epidemiological studies
• High fish intake is inversely associated with
  glucose intolerance and T2DM
• Animal studies
• n-3 PUFA improves glucose insulin metabolism in
  T2DM MS models
• Human supplementation studies
• n-3 PUFA supplementation improves insulin
  sensitivity in individuals with impaired glucose
  tolerance and diabetes
  
  (Fasching et al. 1991 Popp-Snijders et al. 1987)
  
• No effect of n-3 PUFA on insulin
  sensitivity (Vessby et al, 2001
  Eritsland et al 1994 Toft et al. 1995)
• No interaction between background dietary n-6
  PUFA and n-3 PUFA supplementation on insulin
  sensitivity in Indian Asians
• 
  (Brady et al. 2004)

32
Basic hypothesis Dietary fat composition
genotype Insulin resistance in the Metabolic
Syndrome
Gene - nutrient interactions molecular
mechanisms in man
33
Human Dietary Intervention Study

• To determine the relative efficacy of reducing
  dietary SFA consumption, by altering quality of
  dietary fat and reducing the quantity of dietary
  fat, on multiple metabolic and molecular risk
  factors of the metabolic syndrome.
• To determine if common genetic polymorphisms
  associated with increased risk of the metabolic
  syndrome play a causal role in determining an
  individuals responsiveness to dietary therapy.

34
Human Dietary Intervention Study

• To determine the relative efficacy of reducing
  dietary SFA consumption, by altering quality of
  dietary fat and reducing the quantity of dietary
  fat, on multiple metabolic and molecular risk
  factors of the metabolic syndrome.
• To determine if common genetic polymorphisms
  associated with increased risk of the metabolic
  syndrome play a causal role in determining an
  individuals responsiveness to dietary therapy.

35
Human Dietary Intervention Study

• Multi-centre, trans-EU intervention study in 480
  subjects with the MS
• Randomly assigned to 1 of 4 dietary treatments
  for 12 weeks
• Control, high-fat, SFA-rich diet (38
  energy 16 SFA, 12 MUFA, 6 PUFA)
• High-fat, MUFA-rich diet (38
  energy 8 SFA, 20 MUFA, 6 PUFA)
• Isocaloric LF high-complex CHO diet (28 energy
  8 SFA, 11 MUFA, 6 PUFA)
• Isocaloric LF high-complex CHO diet. Plus 1.2 g
  LC n-3 PUFA daily.
• Multiple biochemical and molecular markers of
  insulin sensitivity
• IVGTT, lipoproteins, fatty acid composition,
  inflammatory, coagulation markers, etc.
• Genetic markers of insulin resistance
  gene-nutrient interactions, dietary responders /
  non-responders.
• Adipose and skeletal muscle biopsies, PBMC
  molecular mechanisms.
• Transcriptomics, proteomics, metabolomics.

36
Strategy for fat substitution

• Remove fat from diet by
• Spreads
• Oils
• Dairy foods - milk, cheese
• Biscuits
• Replace with experimental products
• Spreads
• Oils
• Baking fats
• Biscuits (baked with baking fat)
• Mayonnaise
• LIPGENE Dietary Intervention
• Eight centres large food preference variation
• Individualised dietary advice
• Isocaloric
• Weight maintenance

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Production delivery of spreads, oils, fats
mayonnaise
39

• WP 1.2 Description of Activity

Figure 1 LIPGENE Dietary Intervention Study
Screening, Recruitment and Randomization of
subjects with the metabolic syndrome for the
LIPGENE Dietary Intervention Study

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Screening Characteristics of Volunteers assigned
to Diets
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LIPGENE Defining the Metabolic Phenotype

• Pre-and post- intervention, 12 h overnight fast
• Insulin sensitivity
• IVGTT, insulin, c-peptide and glucose
  concentrations.
• Lipoprotein metabolism
• Plasma cholesterol, TAG, NEFA, apo AI, apo B, apo
  CII, apo CIII, apo E. VLDL TAG, cholesterol, apo
  B, apo CII, apo CIII, apo E. HDL sub-fraction
  cholesterol, LDL cholesterol
• Lipid peroxidation
• Urinary F2isoprostanes (8-iso-PGF2alpha)
• Inflammatory / adipocytokine biomarkers
• Leptin, resistin, adiponectin, CRP, IL-6, TNFa,
  sICAM, sVCAM, P-selectin, urinary
  15keto-dihydro-PGF2alpha
• Markers of coagulation / fibrinolysis
• PAI-1, tPA, fibrinogen.

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Dietary AnalysisPre-Intervention
43
Dietary AnalysisPost-Intervention
44
Change Oleic Acid
Diet Intervention Interaction P0.0001 Oleic
acid levels greater after diet B (high-MUFA diet)
compared to all other diets
1.00 Diet A 2.00 Diet B 3.00 Diet C 4.00
Diet D
45
Change EPA
Diet Intervention Interaction P0.0001 EPA
levels greater after diet D (Low-fat, LC n-3 PUFA
diet) compared to all other diets
1.00 Diet A 2.00 Diet B 3.00 Diet C 4.00
Diet D
46
Effect of dietary fat modification on
anthropometric variables of subjects who
completed the LIPGENE Human Dietary Intervention
Study
47
Effect of dietary fat modification on IVGTT
markers of insulin sensitivity in the LIPGENE
Human Dietary Intervention Study
48
Effects of Dietary Fat Intake on Insulin
Sensitivity was dependent upon Pre-intervention
Total Fat Intake.

• Dietary fat intake insulin sensitivity key
  component of LIPGENE
• Split cohort according to habitual dietary fat
  intake (pre-intervention)
• The effects of the four dietary treatments were
  analysed in volunteers with a total fat intake
  pre-intervention, above and below the median.
• High- versus low-fat diet determined outcome

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Habitual Total Fat Intake lt36
plt0.05
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Habitual Total Fat Intake lt36
plt0.05
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Habitual Total Fat Intake lt36
plt0.05
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Habitual Total Fat Intake gt36
plt0.05
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Effect of dietary fat modification on lipid
metabolism in subjects who completed the LIPGENE
Human Dietary Intervention Study
54
Effect of dietary fat modification on lipid
metabolism in subjects who completed the LIPGENE
Human Dietary Intervention Study
55
Effect of dietary fat modification on lipid
metabolism more pronounced in males
56
LIPGENE Human Intervention StudyOverall effects
of dietary fat modification

• Improvements in insulin sensitivity
• Determined by habitual dietary fat intake
• Females respond better than males
• Lipid metabolism
• Significant modification of TAG and NEFA
  metabolism
• Males respond better than females
• Inflammation coagulation
• No significant effect overall
• Not determined effect of habitual dietary fat /
  gender

57
Gene Nutrient Interactions AdiponectinJane
Ferguson
58
Analytical methods

• 11 inflammatory genes (55 SNPs)
• ACDC, ADIPOR1/2, C3, IL6, LTA, NOS3, RETN, STAT3,
  TGFB, TNF
• Insulin sensitivity
• fasting glucose, fasting insulin, HOMA, QUICKI,
  Si, Sg, AIRg, DI
• Inflamamtion
• C-Peptide, CRP, IL-6, TNFa, sICAM, sVCAM ,
  Resistin, Adiponectin, PAI-1, tPA, Fibrinogen and
  Leptin
• Plasma and dietary fatty acid composition
• SFA, MUFA, PUFA, n-6 PUFA, n-3PUFA and SFAMUFA
  ratios.

59
Adiponectin Gene and Fasting Insulin

• Mean levels of fasting insulin in the cohort
  split by genotype at rs266729 in ACDC, and
  separated by plasma levels of SFA above or below
  the median.
• Both CC and GG homozygotes have significantly
  higher fasting insulin when their plasma SFA
  levels are above the median (p0.001).
  Additionally, CC homozygotes with high plasma SFA
  have significantly higher insulin levels than the
  other genotype groups with similar SFA levels
  (p0.009, p0.022).

CC n 38 CG n 156 GG n 236
SNP rs266729 is in the 5 near-gene region of
ACDC
The homozygotes may have more modifiable
phenotypes.
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Adiponectin Receptor Gene (ADIPOR1) and Fasting
Insulin

• Mean levels of fasting insulin in the cohort
  split by genotype at rs10920533 in ADIPOR1, and
  separated by plasma levels of SFA above or below
  the median.
• Both homozygote groups have significantly lower
  fasting insulin when their plasma SFA levels are
  below the median. Additionally, these individuals
  have significantly lower insulin levels than the
  heterozygote group, who does not exhibit the
  insulin-reduction afforded by low SFA.

AA n 32 AG n 185 GG n 214
The homozygotes may have more modifiable
phenotypes.
rs10920533 is in intron 1 of ADIPOR1
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Combination of ACDC and ADIPOR1 SNPs
Modifiable haplotype CC or GG for rs266729 AND
AA or GG for rs10920533 Non-modifiable CG for
rs266729 AND AG for rs10920533
These 2 SNPs can explain almost 14 of the
variation in fasting insulin levels

• Modifiable n152
• Non-modifiable n278

62
Current Understanding of Nutrition Health The
Metabolic Syndrome Dietary Fats Genetic
Background

• Genetic Determinants of Susceptibility
• Polygenic disorder multiple genetic markers,
  increase risk /- confer protection.
• Gene-Nutrient Interactions Insulin Resistance
• PPARg modest impact on individuals, but a
  dramatic effect at the population level
• PPARg and Dietary Fat Composition - Type 2
  diabetes mellitus
• Inflammatory Genes Insulin Resistance
• TNFa promoter G-308A mutation associated with
  increased TNFa 1.8 fold risk of T2DM.
• IL-6 promoter C-124G mutation increases the risk
  of insulin resistance T2DM
• Genetic Determinants of Dietary Responsiveness
• Dietary responders and non-responders dietary
  compliers and non-compliers
• Gene-Gene, Gene-Nutrient, Gene-Nutrient-Lifestyle
  Interactions.

63
Acknowledgements

• Economic Science
• LMC International
• Consumer Science
• University of Ulster
• University of Porto
• Dissemination
• British Nutrition Foundation

• Animal Nutrition
• University of Reading
• Rowett Research Institute
• MTT Agrifood Finland
• INRA
• Plant Biotechnology
• BASF Plant Science GmbH
• University of York
• Rothamsted Research

• Human Nutrition
• University College Dublin
• University of Reading
• University of Oslo
• University of Bergen
• INSERM U476 Marseille
• INSERM U557 Paris
• Maastricht University
• University of Córdoba
• University of Krakow
• Uppsala University
• Unilever Best Foods
• Hitachi Europe Ltd

• EU Framework 6
• Food Quality Safety Programme