View
215
Download
0
Category
Tags:
Preview:
Citation preview
M&G 15 dec 2006 1
Toxicogenomics and Toxicogenetics
Maastricht UniversityJ. van Delft, D. van Leeuwen, H.
Ketelslegers, R. Vlietinck, J. Kleinjans
M&G 15 dec 2006 2
General concept
toxicogenomicstoxicogenetics
M&G 15 dec 2006 3
Goals
Development, validation and application of:1. biomarkers of effect as health indicator for
exposure to carcinogenic compounds2. biomarkers for genetic susceptibility related to
those indicators
Based on the newest genomic technologies:1. Gene expression profiles as biomarker for
effect, by Danitsja van Leeuwen2. Multiplex genotyping as biomarker for genetic
susceptibility, Hans Ketelslegers
M&G 15 dec 2006 4
Phases Toxicogenomics
Studies to select genes using DNA microarrays:
1. In vitro studies in human peripheral blood cells exposed to carcinogenic compounds
2. Small scale field study in monozygotic twins disconcordant in smoking
Application in Environment & Health field study of “Luik III” on adults by quantitative RT-PCR
M&G 15 dec 2006 5
Example of a DNA microarray
M&G 15 dec 2006 6
Human 600 Toxarrays of Phase-1 Molecular Toxicology
Gene Categories Types of Genes in CategoryApoptosis Caspases, BAK, Bax, Fas, Cyclins,
TNFsCell Cycle Cyclins, DNA Binding Protein, Waf 1Cell Proliferation Kinases, Transcription Factors,
Growth Factors and Receptors, Connexins
DNA Damage/ Repair DNA Repair Genes, ERCC’s, GADDs, Helicases, Topoisomerases
Inflammation Serum Amyloids, Interleukins, Adhesion Molecules, Chemokines
Metabolism P450s, Glucuronidation Enzymes, Glutathione Enzymes, Methyltransferases, Redox Enzymes
Oxidative Stress O2 Response Genes, Superoxide Dimutase, Redox Enzymes
Peroxisome Proliferators Peroxisomal EnzymesTransport Multi-drug Resistance Proteins,
Organic Anion and Cation Transporters
Cell-Environment Connexins, Integrins, Selectins, Cadherins
M&G 15 dec 2006 7
In vitro study in human peripheral blood cells
Model carcinogenic compounds:o Cigarette smoke condensateo Benzo[a]pyreneo Tabaco specific nitrosamine (NNK)o 4-amino biphenyl
o H2O2
Possible biomarker genes:o Deregulated by all compoundso Correlating with DNA adducts
M&G 15 dec 2006 8
Deregulated by CSC
CSC
-6
-4
-2
0
2
4
6
IL1β
*
IL6*
CS
F1R
*
CX
CL2
*
SP
P1*
SE
RP
INB
2*
TG
M2*
XR
CC
1*
PT
GS
2
AT
F3
AC
O1
EN
O1
VE
GF
MM
P12
Diff
eren
ce (l
og2)
lowmediumhigh
M&G 15 dec 2006 9
Deregulated by all compoundsCSC 169
H2O2 49
BaP68
4-ABP 51
NNK 78
109
87
95 91
50
50
48 4816
38
19
26 2534
19
2554
34
ATF4GLULGSTA2GAPDVMP1HPRTIL1IL6
CXCL2MMP12VDAC2MIG2PECAM1SATF3COPEB34
5226
M&G 15 dec 2006 10
Small scale field study
Monozygotic twins discordant in smokingo Total peripheral blood cellso Analysis of:
Gene expressionDNA adducts (post labelling) Plasma cotinin levels
Data analyses of gene expression :o Smokers vs non-smokerso Correlations with DNA-adductso Validation with RT-PCR
M&G 15 dec 2006 11
Differentially expressed genes in smokers vs non-smokers
WILCOXON 2 RELATED SAMPLES TEST
p<0.05
CONFIDENCE ANALYSIS (>99%,
regulation level >0.1)
SIGNAL-TO-NOISEratio >0.5
ATF4BNIP2CANXCASP4CATIFRD1MAPK14MCL1MRPS11
OATPLATPLEKHC1PTENPXNS100A9SERPINA1SOD2VDAC2
WILCOXON 2 RELATED SAMPLES TEST
p<0.05
CONFIDENCE ANALYSIS (>99%,
regulation level >0.1)
SIGNAL-TO-NOISEratio >0.5
ATF4BNIP2CANXCASP4CATIFRD1MAPK14MCL1MRPS11
OATPLATPLEKHC1PTENPXNS100A9SERPINA1SOD2VDAC2
M&G 15 dec 2006 12
Validation with RT-PCR
M&G 15 dec 2006 13
Czech study
Another relevant field study, though not related to current program
Compared children from polluted versus clean area in Czech republic
Identified:o Differentially expressed genes o Genes correlating with micronuclei
M&G 15 dec 2006 14
Deregulated and correlating genes
Microarray Real-time PCR
Gene Difference
Correlation
Difference
Correlation
CXCL1 0.52 (6.7*10-5)
0.37 (0.011)
0.60 (0.0009)
0.36 (0.014)
PINK1 0.34 (2.3*10-5)
0.30 (0.038)
0.37 (0.009)
0.16(0.27)
DGAT2 0.43 (1.5*10-4)
0.32 (0.027)
0.78 (0.005)
0.25(0.09)
TIGD3 0.033 (1.9*10-4)
0.41 (0.004)
0.52 (0.008)
0.39 (0.008)
M&G 15 dec 2006 15
Genes selected for field study
M&G 15 dec 2006 16
Gene name (abbreviation)1 Biological summary1
Cytochrome p450 1B1 (CYP1B1) Catalyzes many reactions involved in drug metabolism; metabolism of procarcinogens, e.g. polycyclic aromatic hydrocarbons (PAHs).
Superoxide dismutase 2 (SOD2) Associated with oxidative stress; encodes a mitochondrial protein that binds to the superoxide byproducts of oxidative phosphorylation and converts them to hydrogen peroxide and diatomic oxygen.
Activating transcription factor 4 (ATF4)
Encodes a transcription factor that belongs to a family of DNA-binding proteins, including the AP-1 family of transcription factors, cAMP-response element binding proteins (CREBs) and CREB-like proteins.
Mitogen-activated protein kinase 14 (MAPK14)
Activated by various environmental stressors and proinflammatory cytokines. Integration point for multiple biochemical signals, involved in a wide variety of cellular processes such as proliferation, differentiation, transcription regulation and development. The substrates of this kinase include transcription regulator ATF2, MEF2C, and MAX, cell cycle regulator CDC25B, and tumor suppressor p53, which suggest the roles of this kinase in stress related transcription and cell cycle regulation, as well as in genotoxic stress response.
Chemokine (C-X-C motif) ligand 1 (melanoma growth stimulating activity, alpha) (CXCL1)
Regulate cell trafficking of various types of leukocytes through interactions with a subset of 7-transmembrane, G protein-coupled receptors. Chemokines also play fundamental roles in the development, homeostasis, and function of the immune system, and have effects on cells of the central nervous system as well as on endothelial cells involved in angiogenesis or angiostasis.
PTEN-induced putative kinase-1 (PINK1)
Gene Ontology: ATP binding, magnesium ion binding, nucleotide binding, protein serine/threonine kinase activity, transferase activity, protein kinase cascade, response to stress.
Diacylglycerol O-acyltransferase homolog 2 (mouse) (DGAT2)
DGAT is responsible for the synthesis of triglycerides. It catalyzes a reaction in which diacylglycerol is covalently joined to long chain fatty acyl-CoAs.
Tigger transpo-sable element derived 3 (TIGD3)
The protein encoded by this gene belongs to the tigger subfamily of the pogo superfamily of DNA-mediated transposons in humans. These proteins are related to DNA transposons found in fungi and nematodes, and more distantly to the Tc1 and mariner transposases. They are also very similar to the major mammalian centromere protein B. The exact function of this gene is not known.
1) See NCBI at http://www.ncbi.nlm.nih.gov/Gene
Based on smokers study with MZ twins
CYP1B1
SOD2
ATF4
MAPK14
Based on Czech air pollution study
CXCL1
PINK1
DGAT2
TIGD3
M&G 15 dec 2006 17
Field study on elderly people
aged 50-65 years, n = 398RNA from total peripheral blood cellsQuantitative RT-PCR of 8 genes vs 2
house keeping genesReference RNA sample: pool from 20
randomly selected individualsCompared data with:
o COMET o MN frequencieso 8-OH-dGin urineo Tumor markers in serum (p53, CEA, PSA)
M&G 15 dec 2006 18
Effect of region
Antwerp
-0,6
-0,4
-0,2
0,0
0,2
0,4
0,6
0,8
CYP1B1
ATF4
MAPK14
SOD2
CXCL1
DGAT2
TIGD3
PINK1
Harbor
-0,6
-0,4
-0,2
0,0
0,2
0,4
0,6
0,8
CYP1B1
ATF4
MAPK14
SOD2
CXCL1
DGAT2
TIGD3
PINK1
Fruit
-0,6
-0,4
-0,2
0,0
0,2
0,4
0,6
0,8
CYP1B1
ATF4
MAPK14
SOD2
CXCL1
DGAT2
TIGD3
PINK1
Olen
-0,6
-0,4
-0,2
0,0
0,2
0,4
0,6
0,8
CYP1B1
ATF4
MAPK14
SOD2
CXCL1
DGAT2
TIGD3
PINK1
Gent
-0,6
-0,4
-0,2
0,0
0,2
0,4
0,6
0,8
CYP1B1
ATF4
MAPK14
SOD2
CXCL1
DGAT2
TIGD3
PINK1
Incinerators
-0,6
-0,4
-0,2
0,0
0,2
0,4
0,6
0,8
CYP1B1
ATF4
MAPK14
SOD2
CXCL1
DGAT2
TIGD3
PINK1
Rural
-0,6
-0,4
-0,2
0,0
0,2
0,4
0,6
0,8
CYP1B1
ATF4
MAPK14
SOD2
CXCL1
DGAT2
TIGD3
PINK1
Canal
-0,6
-0,4
-0,2
0,0
0,2
0,4
0,6
0,8
CYP1B1
ATF4
MAPK14
SOD2
CXCL1
DGAT2
TIGD3
PINK1
Never + former smokers
Never + former +current smokers
Antwerp
-0,6
-0,4
-0,2
0,0
0,2
0,4
0,6
0,8
CYP1B1
ATF4
MAPK14
SOD2
CXCL1
DGAT2
TIGD3
PINK1
Harbor
-0,6
-0,4
-0,2
0,0
0,2
0,4
0,6
0,8
CYP1B1
ATF4
MAPK14
SOD2
CXCL1
DGAT2
TIGD3
PINK1
Fruit
-0,6
-0,4
-0,2
0,0
0,2
0,4
0,6
0,8
CYP1B1
ATF4
MAPK14
SOD2
CXCL1
DGAT2
TIGD3
PINK1
Olen
-0,6
-0,4
-0,2
0,0
0,2
0,4
0,6
0,8
CYP1B1
ATF4
MAPK14
SOD2
CXCL1
DGAT2
TIGD3
PINK1
Gent
-0,6
-0,4
-0,2
0,0
0,2
0,4
0,6
0,8
CYP1B1
ATF4
MAPK14
SOD2
CXCL1
DGAT2
TIGD3
PINK1
Incinerators
-0,6
-0,4
-0,2
0,0
0,2
0,4
0,6
0,8
CYP1B1
ATF4
MAPK14
SOD2
CXCL1
DGAT2
TIGD3
PINK1
Rural
-0,6
-0,4
-0,2
0,0
0,2
0,4
0,6
0,8
CYP1B1
ATF4
MAPK14
SOD2
CXCL1
DGAT2
TIGD3
PINK1
Canal
-0,6
-0,4
-0,2
0,0
0,2
0,4
0,6
0,8
CYP1B1
ATF4
MAPK14
SOD2
CXCL1
DGAT2
TIGD3
PINK1
Antwerp
-0,6
-0,4
-0,2
0,0
0,2
0,4
0,6
0,8
CYP1B1
ATF4
MAPK14
SOD2
CXCL1
DGAT2
TIGD3
PINK1
Harbor
-0,6
-0,4
-0,2
0,0
0,2
0,4
0,6
0,8
CYP1B1
ATF4
MAPK14
SOD2
CXCL1
DGAT2
TIGD3
PINK1
Fruit
-0,6
-0,4
-0,2
0,0
0,2
0,4
0,6
0,8
CYP1B1
ATF4
MAPK14
SOD2
CXCL1
DGAT2
TIGD3
PINK1
Olen
-0,6
-0,4
-0,2
0,0
0,2
0,4
0,6
0,8
CYP1B1
ATF4
MAPK14
SOD2
CXCL1
DGAT2
TIGD3
PINK1
Gent
-0,6
-0,4
-0,2
0,0
0,2
0,4
0,6
0,8
CYP1B1
ATF4
MAPK14
SOD2
CXCL1
DGAT2
TIGD3
PINK1
Incinerators
-0,6
-0,4
-0,2
0,0
0,2
0,4
0,6
0,8
CYP1B1
ATF4
MAPK14
SOD2
CXCL1
DGAT2
TIGD3
PINK1
Rural
-0,6
-0,4
-0,2
0,0
0,2
0,4
0,6
0,8
CYP1B1
ATF4
MAPK14
SOD2
CXCL1
DGAT2
TIGD3
PINK1
Canal
-0,6
-0,4
-0,2
0,0
0,2
0,4
0,6
0,8
CYP1B1
ATF4
MAPK14
SOD2
CXCL1
DGAT2
TIGD3
PINK1
Never + former smokers
Never + former +current smokers
Never + former smokers
Never + former +current smokers
Non-smokers
All subjects
M&G 15 dec 2006 19
Effect of seasonCYP1B1
-1,0
-0,5
0,0
0,5
1,0
1,5
0 5 10 15 20 25
A H F O G I R C
March 22nd 2005 - June 6th 2005
Sep 27th 2004 - Dec 21st 2004
Dec 22nd 2004 - March 21st 2005
ATF4
-1,0
-0,5
0,0
0,5
1,0
1,5
A H F OG
I R C
MAPK14
-1,0
-0,5
0,0
0,5
1,0
1,5
A H F O G I R C
SOD2
-1,5
-1,0
-0,5
0,0
0,5
1,0
1,5
0 5 10
15
20
25
A H F O G I R C
CXCL1
-1,0
-0,5
0,0
0,5
1,0
1,5
A H F O G I R C
DGAT2
-1,0
-0,5
0,0
0,5
1,0
1,5
A H F O G I R C
TIGD3
-1,0
-0,5
0,0
0,5
1,0
1,5
A H F O G I R C
SUM
-5,0
-4,0
-3,0
-2,0
-1,0
0,0
1,0
2,0
3,0
4,0
5,0
0 5 10 15 20 25
A H F O G I R C
PINK1
-1,0
-0,5
0,0
0,5
1,0
1,5
0 5 10 15 20 25
A H F O G I R C
M&G 15 dec 2006 20
Comparison of regions
Incinerato
rs
Ca
na
l
Ru
ral
Fru
it
An
twe
rp
Ole
n
Ge
nt
Ha
rbor
A
Incinerato
rs
Ca
na
l
Ru
ral
Fru
it
An
twe
rp
Ole
n
Ge
nt
Ha
rbor
Incinerato
rs
Ca
na
l
Ru
ral
Fru
it
An
twe
rp
Ole
n
Ge
nt
Ha
rbor
Incinerato
rs
Ca
na
l
Ru
ral
Fru
it
An
twe
rp
Ole
n
Ge
nt
Ha
rbor
A
Incin
era
tors
Ca
na
l
Ru
ral
Fru
it
An
twe
rp
Ole
n
Ge
nt
Ha
rbor
B
Incin
era
tors
Ca
na
l
Ru
ral
Fru
it
An
twe
rp
Ole
n
Ge
nt
Ha
rbor
B
M&G 15 dec 2006 21
Correlations with effect biomarkers
ATF4MAPK14 SOD2
CXCL1 DGAT2TIGD3PINK1 SUM
CYP1B1
B
PSA p53COMET
countCEA
COMET P90
ATF4MAPK14 SOD2
CXCL1 DGAT2TIGD3PINK1 SUM
CYP1B1
B
PSA p53COMET
countCEA
COMET P90
M&G 15 dec 2006 22
Comparison with classical biomarkers
Majority of gene expressions differed significantly between 2 or more regions
Classical biomarkers did not always differ and if so, with lower significance
Magnitude of differences o gene expression: 1.2 (DGAT2) – 2.0 (ATF4) o classical biomarkers: 1.10 (COMET count) – 2.43
(COMET median)
Smoking significantly affected:o CYP1B1 and ATF4o MN, CEA and p53
Correlations with exposure markers not yet done
M&G 15 dec 2006 23
Conclusions
Gene expression profiling as possible biomarker has been developed and applied
More in-dept analyses are required in order to establish relevance:o Exposure markerso Effect markerso Susceptibility markerso Confounding factors
Gene expression profiling is promising for molecular epidemiology on the risks of environmental exposures for humans
M&G 15 dec 2006 24
General concept
toxicogenomicstoxicogenetics
M&G 15 dec 2006 25
Phases Toxicogenetics
Select genes and polymorphism to be included
Develop and validate methods for multiplex genotyping
Apply in Environment & Health field studies of “Luik III” on newborns, adolescents, elderly
M&G 15 dec 2006 26
Selection criteria of genes and polymorphisms
Genes must be relevant for endpoints / biomarkers in filed studies:o Asthma and allergyo Cancer
Polymorphisms must be relevant:o Highly frequent (>5%)o Cause a phenotypic effect (proven or highly
likely)
M&G 15 dec 2006 27
SNP Database: Database: 66 SNPs in 41 genes
Biotransformation (Set 1&7)o E.g. CYP1A1, -1A2, -1B1, GSTs, NATs, mEH
etc.
DNA repair (Set 2)o E.g. XRCC, XPD, BRCA2, OGG1 etc.
Oxidative stress related (Set 3)o E.g. CAT, SOD, NQO, GPX etc.
Inflammation (Set 4&5)o E.g. Interleukins, TNFα, PAFAH etc.
Apoptosis & Cell Cycle control (Set 6)o E.g. p53, p21, Cylin D, CDKs etc.
M&G 15 dec 2006 28
Examples
Allele Nucleotide change
Amino Acid Change
Allele frequency (%)
Phenotype Disease Association
SOD2*1 C47T Val16Ala
C:38.5;T:61.5
Altered expression
Ala variant: incr. Risk for breast cancer
NQO1*2 C609T Pro187Ser
C:80; T:20
Less mRNA, no protein or activity
CC: higher risk for smoking related bladder cancer
MPO*1 G-463A
G:74.5; A:25.5
AA:lower transcription, mRNA and protein
Lung , larynx and esophageal cancer, CAD and alzheimer
XPA*1 A23G +/- 50 GG: decr. risk for lung cancer
mEH*2 C/T Tyr113His
C:36.1; T:63.9
40% decrease in hydrolase activity
His: protective against colon cancer
mEH*3 A/G His139Arg
A:80.1; G:19..9
25% increase in hydrolase activity
No relationship
M&G 15 dec 2006 29
Examples for genotyping by Single Base Extension
1 4 5 6 7 8 92 3
C/C
C/C G/A G/G
G/G C/A
C/C
A/AA/0
0/0
C/TG/A A/AA/0
A/AA0
C/C G/G
G/GC/T
C/T
1 4 5 6 7 8 92 31 4 5 6 7 8 92 3
C/C
C/C G/A G/G
G/G C/A
C/C
A/AA/0
0/0
C/TG/A A/AA/0
A/AA0
C/C G/G
G/GC/T
C/T
M&G 15 dec 2006 30
Validation of genotyping method (1)
SNP N % OK Alternativ method CYP1A2*1C 10 100 sequencing
CYP1A2*1F 20 100 PCR-RFLP
GSTM1*0 68 100 PCR
GSTT1*0 68 100 PCR
GSTP1*2 20 100 PCR-RFLP
NAT2*5 68 100 PCR-RFLP (+ sequencing)
NAT2*6 10 100 PCR-RFLP
NAT2*7 10 100 PCR-RFLP
M&G 15 dec 2006 31
Validation of genotyping method(2)
M&G 15 dec 2006 32
Adolescent study Population: +/- 450
adolescents (age: 16 years old)
Biomarkers: o Effect: Comet Analysis (DNA
damage)o Exposure: 1-OHP (PAHs), PCBs,
DDE, Cd, Pb
Genotyping: Biotransformation, DNA repair and oxidative stress related
M&G 15 dec 2006 33
Statistical approaches
Univariate analyses: e.g. Mann Whitney or Kruskall Wallis
NAT2*6: p=0,006
M&G 15 dec 2006 34
Statistical approaches
Multivariate analyses: e.g. Multiple Linear Regression, Discriminant Analyses or Binary Logistic Regression
M&G 15 dec 2006 35
Exposure Marker
(Confounding) Effect of Smoking?
Remove Smokers from Analysis
In Non-Smokers
Relationship Exposure with Effect Marker?
Dose-Response
2 groups based on Regression Line: 0 & 1
Logistic RegressionGroup as Dependent;
Sex, Cig/Day*, Smoking Y/N*, SNPs as Independents
Most important
predictors?
+-
Total Population
M&G 15 dec 2006 36
Linear Relationships-Adolescents
Smoker Y/N Comet tt-MAp'p'DDE p=0.858 p=0.521HCB p=0.343 p=0.552Cd114 p=0.000 p=0.822 (0.353)*Cd_Crea p=0.209 p=0.146Pb p=0.375 p=0.080PCB p=0.548 p=0.7551OHP p=0.013 p=0.580 (0.303)*ttMA p=0.256 p=0.602Benzene p=0.165 p=0.462 p=0.808ClBenzene p=0.837 p=0.046 p=0.747EthylBenzene p=0.808 p=0.022 p=0.892Comet p=0.032 *** p=0.602
* Non-Smokers
M&G 15 dec 2006 37
Ethylbenzene * CometLinear Regression
M&G 15 dec 2006 38
Ethylbenzene * CometLogistic Regression
P=0.201 P=0.131
Catalase (p=0.027) GSTT1 (p=0.035)
M&G 15 dec 2006 39
Adult study Population: +/- 400
adolescents (age: 65 years old) Biomarkers:
o Effect: Comet Analysis (DNA damage), 8-OHdG, PSA, CEA, p53
o Exposure: 1-OHP (PAHs), PCBs, DDE, Cd, Pb
Genotyping: Biotransformation, DNA repair and oxidative stress related
M&G 15 dec 2006 40
Linear Relationships-Adults
Smoker Y/N Comet 8-OHdG PSA CEA p53PCB p=0.544 p=0.676 p=0.755 p=0.843 p=0.520 p=0.230HCB p=0.517 p=0.239 p=0.003 p=0.623 p=0.546 p=0.082p'p'DDE p=0.562 p=0.651 p=0.613 p=0.873 p=0.836 p=0.150Cd114 p=0.000 p=0.380 (0.156)* p=0.355 (0.666)* p=0.091 (0.139)* p=0.000 (0.530)* p=0.463 (0.908)*Cd_Crea p=0.000 p=0.816 (0.790)* p=0.004 (0.007)* p=0.943 (0.158)* p=0.000 (0.546)* p=0.102 (0.030)*Pb p=0.510 p=0.438 p=0.088 p=0.663 p=0.004 p=0.3561OHP p=0.000 p=0.313 (0.777)* p=0.007 (0.029)* p=0.256 (0.078)* p=0.000 (0.371)* p=0.375 (0.680)*Comet p=0.400 *** p=0.683 p=0.122 p=0.141 p=0.6948-OHdG p=0.887 p=0.683 *** p=0.861 p=0.136 p=0.703PSA p=0.358 p=0.122 p=0.861CEA p=0.000 p=0.141 (0.248)* p=0.136 (0.859)*p53 p=0.004 p=0.694 (0.514)* p=0.703 (0.620)*
* Non-Smokers: Significant Relationship: Only Significant in Total Population: Only Significant in Non-Smokers
M&G 15 dec 2006 41
Cadmium (Urine) * 8-OHdG Linear Regression non-smokers
M&G 15 dec 2006 42
Cadmium (Urine) * 8-OHdGLogistic Regression
P=0.224
GSTT1 (p=0.041)
M&G 15 dec 2006 43
1-OH-pyrene (Urine) * 8-OHdGLinear Regression non-smokers
M&G 15 dec 2006 44
Adults: 1-OH-pyrene (Urine) * 8-OHdGLogistic Regression
P=0.003 P=0.035 P=0.098
Gender CYP1A1*m4 mEH*3 (p=0.001) (p=0.05) (p=0.023)
M&G 15 dec 2006 45
Comparison with classical biomarkers
Majority of gene expressions differed significantly between 2 or more regions
Classical biomarkers did not always differ and if so, with lower significance
Magnitude of differences o gene expression: 1.2 (DGAT2) – 2.0 (ATF4) o classical biomarkers: 1.10 (COMET count) – 2.43
(COMET median)
Smoking significantly affected:o CYP1B1 and ATF4o MN, CEA and p53
Correlations with exposure markers not yet done
M&G 15 dec 2006 46
Conclusions
Genetic polymorphisms affect susceptibility for effect biomarkers related to exposure
Sensitive populations can be genotyping for relevant polymorphisms
More in-dept analyses are required on order to establish relevance:o Interactions between genotypeso Univariate analyseso Effect of / interaction with smokingo Relations with gene expression
Genotyping enables to identify sensitive populations for specific exposure – effect relations
M&G 15 dec 2006 47
Demonstrated the value for molecular epidemiology
toxicogenomicstoxicogenetics
Recommended