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Michael Müller
Nutrigenomics: Providing Early Warning Molecular Biomarkers For
Nutrient-Induced Changes to Homeostasis
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Outline
Nutrigenomics: From complex problems to simple questionsFree fatty acids as a “need for glucose” signal“Metabolic stress” and its signaturesHuman studies and the use of PBMCsConclusions
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Nutrigenomics
Target GenesMechanisms
Pathways
SignaturesProfiles
Biomarkers
FoodsNutrition
Molecular Nutrition& Genomics
NutritionalSystems Biology
•Identification of dietary signals•Identification of dietary sensors•Identification of target genes•Reconstruction of signaling pathways
•Measurement of stress signatures•Identification of early biomarkers
Small research groupsSmall budgets
Large research consortiaBig money
Complexity
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Nutrigenomics
Complex ProblemsComplex Problems
Simple QuestionsSimple Questions
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Transcription-factor pathwaysmediating nutrient-gene interaction
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“Molecular Nutrition & Genomics”The strategy of Nutrigenomics
80-100000proteins
20-25000 genes
100000 transcripts
50000 (?)metabolites
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Functions of PPARs
“Fat sensors”
PPARα PPARγ PPARβ
-Nutrient metabolism (lipid, glucose, AAs)
- Proliferation
- Inflammation
- Lipid and glucosemetabolism
- Cell cycle control
- Inflammation
- Lipid metabolism
- Keratinocytedifferentiation
- Inflammation
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Role of PPARα in the hepatic response to fasting
Liver
FFAFFAElucidation by employing:1) k.o.-mice2) specific ligands3) transcriptome analysis4) In vitro studies (Promoter
studies, ChIP, etc)
Elucidation by employing:1) k.o.-mice2) specific ligands3) transcriptome analysis4) In vitro studies (Promoter
studies, ChIP, etc)
CMLS, Cell. Mol. Life Sci. 61 (2004) 393–416CMLS, Cell. Mol. Life Sci. 61 (2004) 393–416
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The role of free fatty acids
.00
.20
.40
.60
.80
0 6 12 18 24
mmol/L
2
4
6
8
10mmol/Lfree fatty acid
blood glucose
“Hunger” signal or“Need for glucose” signal
time (hours)
• During fasting• During long
endurance activity
• In obese people
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Factors influencing the development of metabolic syndrome
MSX
13
Diabetes
ObesityHypertension
Inflammation Hyperlipidemia
2
Pharma
Nutrition
0
20
40
60
80
100
120
TIME (months/years)
DIS
EA
SE
STA
TE
HomeostasisHealth
Complex Disease
Different targets
Metabolic stress
Metabolic syn
drome
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Signatures of health & stress -The “two hits”: Metabolic and pro-inflammatory stress
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Mouse study: 45% High Fat versus 10% Low Fat
05
1015202530354045
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
Time on diet (weeks)
Wei
ght (
gram
)
C57Bl/6 10% fat
C57Bl/6 45% fat
-5
0
5
10
15
20
25
0 15 30 45 60 90 150
Time (minutes)
Cha
nge
in g
luco
se (m
mol
/L)
10% fat / 9 wk (n=12)45% fat / 9 wk (n=11)10% fat / 15 wk (n=6)45% fat / 15 wk (n=6)
Mean weight per mouseGlucose tolerance test C57Bl/6 mice
IntestineLiverMuscleWAT
+ “omics” analysis
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Hierarchical Clustering ‘Liver and Intestine’Liver Intestine
-0.281 1
1 3057 3 13 63
SL_W1H_L SL_W2_HL SL_W3_HL SL_W4_HL SL_10_HL SL_16_HL
-0.255 1
1 2636 3 14 63
SL_W1H_L SL_W2_H_ SL_W3_H_ SL_W4HH_ SL_10_H_ SL_16_H_
Weeks 1 2 3 4 10 16 Weeks 1 2 3 4 10 16
Clustering method: UPGMA (unweighted average)Similarity measure: CorrelationOrdering function: Average value
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Pathway analysis supports searches for common regulators
Liver data weeks 1,2,3,4,10 + 16 HF vs LF –0.5<SLR> 0.5
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Human Studies “Fasting signatures”
Person 1
Person 2
Person 3
Person 4
0h 24h 48h 0h 24h 48h
DesignDecember February
Blood samples Blood samples
4 pm: meal 5 pm 5 pm 5 pm
Person 1
Person 2
Person 3
Person 44 pm: meal 5 pm 5 pm 5 pm
Get insight in basic gene expression of human PBMCs (inter- and intra-individual variation)Explore the possibilities of using PBMCs as markers for nutritional statusFocus on fatty acid dependent gene expression signatures
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Clustering method: UPGMA (unweighted average)Similarity measure: Euclidean distanceOrdering function: Average valueHierarchical Clustering
N3_24N3_0
N11_0N10_0
N11_24
N10_24
N1_0N1_48
N11_48
N10_48
N3_48 0 h 48 h
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“Zoom-in”: Common regulators (slr>0.5 or <-0.5)
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Conclusions• Nutrigenomics is the application of high-throughput genomics tools
in nutrition research. • Applied wisely, it will promote an increased understanding of how
nutrition influences metabolic pathways and homeostatic control,how this regulation is disturbed in the early phase of a diet-related disease and to what extent individual sensitizing genotypes contribute to such diseases.
• Ultimately, nutrigenomics will allow effective dietary-intervention strategies to recover normal homeostasis and to prevent diet-related diseases.
• However, huge efforts (money + smart ideas) are needed to solve already identified and future problems:– Extract biological relevant data from nutrigenomics datasets (“signal
versus noise”)– Translate animal data to the human situation (in particular for complex
diseases)– Is nutritional “systems biology” the method to identify biomarkers?– How tailored-made can nutrition be in the future?
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Collaboration - Linking to EU programs
LIPGENLipids & genes
(EU, 14M€)
DIOGENESobesity
(EU, 12M€)
Innovative Cluster NutrigenomicsChronic metabolic stress
(Dutch, 21M€)
EARNESTearly life nutrition
(EU, 14M€)
Lipid metabolism
Life stage nutritionRisk Benefit analysis
Metabolic health
ProliferationDifferentiation
Apoptosis
Inflammation
Muscle insulin resistance
Nutrigenetics
Early biomarkers
Periconceptualnutrition
Nuclear transcription
factors
Systems biology
Host-microbeinteraction
Gut Health
Absorption
Genetic epidemiology
Toxicogenomics
Metabolic stress
Adipocytefat oxidation
Diabetes II
Carotenoids
Lipid metabolism
Life stage nutritionRisk Benefit analysis
Metabolic health
ProliferationDifferentiation
Apoptosis
Inflammation
Muscle insulin resistance
Nutrigenetics
Early biomarkers
Periconceptualnutrition
Nuclear transcription
factors
Systems biology
Host-microbeinteraction
Gut Health
Absorption
Genetic epidemiology
Toxicogenomics
Metabolic stress
Adipocytefat oxidation
Diabetes II
Carotenoids
NuGO
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Thanks to:
Members of the Division of Human Nutrition
Wageningen University
Ben van Ommen
Christian Trautwein
Diabetes-fondsNWO
IOP-Genomics
Members of the IOP Genomics “Gut Health”
Centre for Human NutrigenomicsNutrigenomics Consortium/WCFS
Annibale BiggeriMarta Blangiardo
(NUGO)