The NIEHS Environmental Genome Project: Enabling Studies of Gene-Environment Interaction

1. The NIEHS Environmental Genome Project: Enabling Studies of Gene-Environment Interaction Douglas A. Bell, Ph.D. Environmental Genomics Section National Institute of Environmental Health Sciences Professor, Dept of Epidemiology UNC School of Public Health

2. NIEHS’s Environmental Genome ProjectResequencing of ~500 Candidate Genes Potentially Involved in Environmental Disease • Concept and rationale • Examples of gene-environment interaction • Resequencing studies, accomplishments, and accessing data.

3. Disease Modulation of Response to Exposure Exposure Early Effects Genetic Susceptibility

4. Genetic Modulation of Exposure, Damage, and Biological Response Exposure Target tissue Biological Response Disease • Genetic Variation in: • Metabolism, or distribution, affects dose to the tissue • Detection and repair of damage • Differences in growth and recovery from damage

5. Genetic Modulation of Exposure Risk Resistant Genotype Background Risk Level (low) No Exposure Sensitive Genotype Resistant Genotype 2-Fold Risk Exposure Sensitive Genotype 4-Fold Risk

6. Glutathione HO HO Benzo[a]pyrene Metabolism GST + Glutathione Inactive CYP450 PAH-oxide DNA Reactive

7. Glutathione HO HO Benzo[a]pyrene Metabolism GST + Glutathione Inactive GSTM1 Null CYP450 PAH-oxide DNA Reactive

8. Exposure Risk Genetic Risk Bladder Cancer Risk Associated with Smoking and GSTM1 Null Genotype GSTM1 (+) GSTM1 null 1 1.3 2.2* 4.3* 3.5* 5.9* Nonsmokers 1- 50 Packyears Smoking >50 Packyears Smoking *P<0.001; Bell et al, JNCI 85:1559,1993

9. Examples of Gene-Environment Interaction (gene modifies environmental effect) • Malaria and Sickle Cell gene. • HIV infection and CCR5 receptor variant. • LPS sensitivity and Toll Receptor (TLR4) • Adverse drug response and CYP2D6 poor metabolism. • Alcohol intolerance and aldehyde dehydrogenase. • Smoking, GSTM1 null, NAT2 slow genotypes, and bladder cancer risk .

10. Variation in Risk Estimates in Human Populations Phenotypic variation in response due to: Physiology Metabolism Repair Growth Timing of Exposure Risk Exposure

11. Example: Metabolism Polymorphisms Range of Enzyme Activity in Human Populations No Phenotypic Polymorphism frequency Activity

12. frequency Activity Distribution of Polymorphic Enzyme Activity in a Population Low High High Low +/+ -/- +/- +/+ -/- +/- Activity Examples: N-Acetyltransferase 2, GSTM1, CYP2D6

13. 95% 5% frequency Activity How does frequency of a risk factor impact exposure induced (G x E) risk in the population?

14. 95% 5% frequency Activity Effects of Exposure in High and Low Risk Human Populations Risk 100 High Risk 10 Average Low Risk 0 Exposure

15. How will genetic data be used in public health risk assessment? • Given detailed information on the relationship between genotype and phenotype, more accurate risk assessments may be possible.

16. Human Genetic Susceptibility Exposure Assessment Risk Model (Extrapolation to humans) Animal toxicology (dose/response) Effects in Humans ? Engineering design S R Risk Assessment Process Hazard/Risk Assessment Risk Management More/Less Control Replace default assumptions about variability

17. Incorporating Human Genetic Polymorphism Information Into Risk Assessment Cancer - Yes/No Dose ? Extrapolate to Humans Chemical X • Biochemistry • Mechanism of toxicity • Genes, pathways • Human genetics Susceptible human subgroup?

18. Incorporating Genetics Into Risk Assessment: Issues • A polymorphism may have different effects depending on the chemical, the target organ/ disease, and the population being considered. Thus, a protective allele for one chemical may convey risk for a different chemical. Similarly one organ system may be protected at the risk of another; e.g. immune system response could increase DNA damage or neurotoxicity.

19. Glutathione HO H2C CH2 Glutathione Cl- CH2 + Cl GST Theta 1 (GSTT1) - One gene with 2 effects Detoxication Ethylene oxide Inactive GSTT1 + Glutathione Activation (Unstable) HCHO DNA Methylene chloride GSTT1 + Glutathione DNA Reactive DNA (also Methyl chloride) D.A.Bell NIEHS

20. Activation vs. Detoxication Effects of polymorphism dependent on chemical and toxicity pathway: • Activation- If the activation pathway is missing (null genotypes), some individuals may have zero risk even if they have exposure. • Detoxication- Since this process will never be 100% efficient, both functional and low activity genotypes will exhibit risk associated with exposure.

21. The Effect of GSTT1 Genotype on Metabolism of Methyl Chloride T1 Null No Metabolism Measure exhaled methyl chloride T1 + Metabolism to DNA reactive forms From Lof, A. et al, Pharmacogenetics 10:645, 2000.

22. Smoking, GSTT1 Polymorphism, and Markers of Genotoxicity in Erythrocytes Background: Ethylene oxide –hemoglobin adducts are a good measure of smoking exposure in blood. Experiment: To test if GST genotypes modulated effects of smoking in erythrocytes, we measured ethylene oxide hemoglobin adducts in freshly collected human erythrocytes from nonsmokers and smokers. Results: • Ethylene oxide adducts (HEV) were ~50% higher in GSTT1 null individuals. D.A.Bell NIEHS

23. GSTT1 null genotypes have higher levels of smoking-induced hemoglobin adducts • Study Design: • 16 nonsmokers • 32 smokers • HEVal hemoglobin adducts measure by mass spectrometry • P = 0.001 for difference in slopes; • Nonparametric analysis similar. Fennel et al CEBP 9:705,2000

24. Incorporating Genetics Into Risk Assessment Needs: • Identify genes involved in toxicological response. • Detailed population genetic information including: • Identify polymorphisms. • Determine frequency in populations. • Population-based risk estimates in large studies (n=2000). • Determine functional relationship between genotype and phenotype • Biochemical • In vitro, in vivo quantitative measurements of a cellular phenotype (tumors, adducts, mutation, cell death, gene expression). • Consider role of multiple genes, multiple pathways, etc. • Incorporate kinetic or other functional data into risk model.

25. Environmental Genomics Discovery: Phenotype-directed Genotype-directed Functional Analysis Disease Risk Characterization CTTATGT A/CGGGTAT Effects in Populations Phenotype Genotype Altered Binding

26. Transcription Factors Coding region changes: aa subs, deletions, stops. Regulatory polymorphisms alter transcription factor binding and mRNA/protein level. Polymorphism and Function Exon 1 Exon 2 3’ UTR Promoter Gene Deletions, Duplications e.g. GSTM1, CYP2D6 • Effects of Polymorphism: • Altered function • Quantity of protein

27. Phenotype—Directed Approach to Find SNPs That Alter Gene Expression Level C TGGGCCCCGCCCCCTTATGTAGGGTATAAAGCCC …. CCCGTCACC ATG   SP1/Oct Liu, X. et al

28. Sequence-Directed Approaches to Catalogue All Significant SNPs In The Human Population Resequencing Projects: Describing candidate gene polymorphisms in diverse populations. ~9 million SNPs in dbSNP now, by 2006, expect ~20 million human SNPs. • A SNP every ~100 bases. Haplotype Map: Describing which SNPs occur together on chromosomes in populations (haplotypes).

29. SNP Discovery Projects • The SNP Consortium – ~1 million SNPs across genome • NIEHS – Environmental/toxicology genes • NHLBI – Heart disease genes, inflammation • NIGMS – Pharmacogenetic genes SNP data is entered into the NCBI dbSNP database

37. UCSC Hapmap

39. U Wash EGP Website

43. HapMap Website • Characterize the large scale genetic structure across the genome. • Genotyping SNPs at 1 kb interval across the genome in European, African, and Asian populations.

48. Bioinformatic Tools Available For Picking Haplotype Tagging SNPs • HapMap Website • Seattle SNPs or EGP website • Many other freely available programs

49. NIEHS Environmental Genome Project Resequencing of candidate environmental disease genes Accomplishments: • Total genes sequenced = 437 • Total kilobases sequenced = 11,001 kb • Total SNPs identified = 59,475

50. NIEHS’s Environmental Genome ProjectSummary: • Gene-environment interaction affects disease risk. • Effects of G x E interactions can be complex. • Resequencing projects are providing many new candidate gene polymorphism. • Determining the important functional SNPs that affect disease risk is a difficult challenge.