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Predicting Environmental Disease Susceptibility with Genetic Polymorphism Data: Are We There Yet ? Jun-Yan Hong University of Medicine and Dentistry of.

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Presentation on theme: "Predicting Environmental Disease Susceptibility with Genetic Polymorphism Data: Are We There Yet ? Jun-Yan Hong University of Medicine and Dentistry of."— Presentation transcript:

1 Predicting Environmental Disease Susceptibility with Genetic Polymorphism Data: Are We There Yet ? Jun-Yan Hong University of Medicine and Dentistry of New Jersey 5 th ICOEM, Dujiangyan, April 6-10, 2010

2  Advancement of molecular biology and human genome project provide new opportunities to understand the genetic basis for individual difference in susceptibility to environmental exposure.  Human disease is the consequence of both genetic susceptibility and environmental exposure.  By identifying the genes and allelic variants that affect individual response to environmental toxins, we can better predict health risks and develop environmental policies to protect the most vulnerable subgroups of the population. The Environment Genome Project (NIEHS, NIH, 1997)

3  Small sample size, including low allelic distribution frequenies of given SNPs in certain ethnic groups (statistical power)  While the functions of candidate gene(s) were well known, there was little considerations on the functionality of the related SNPs. Two Major Problems in Early Genetic Susceptibility Studies

4 CYP2A6 Gene Deletion and Lung Cancer Risk There were 246 cases and 201 controls, in total. Information on smoking history was not provided. *significantly different from healthy controls (p<0.05) Miyamoto et al., Biochem. Biophys. Res. Comm., 1999

5 Frequency Distribution among Esophageal Cancer Cases and Controls and Relative Risks Associated with Genotype Variants of CYP2E1 Hildesheim et al 1995

6 Environmental Health Perspectives, 105 (Suppl. 4) , 1997 International Symposium on Environmental Genomics and Pharmacogenetics, May14- 17,2001, Shanghai, China, Sponsored by NIEHS and NCI

7 He XY, Shen J, Hu WY, Ding X, Lu AY, Hong JY. Identification of Val117 and Arg372 as critical amino acid residues for the activity difference between human CYP2A6 and CYP2A13 in coumarin 7-hydroxylation. Arch Biochem Biophys. 2004;427:143. He XY, Shen J, Ding X, Lu AY, Hong JY. Identification of critical amino acid residues of human CYP2A13 for the metabolic activation of 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone, a tobacco-specific carcinogen. Drug Metab Dispos. 2004;32:1516. He XY, Tang L, Wang SL, Cai QS, Wang JS, Hong JY. Efficient activation of aflatoxin B1 by cytochrome P450 2A13, an enzyme predominantly expressed in human respiratory tract. Int J Cancer. 2006;118:2665. Wang SL, He XY, Shen J, Wang JS, Hong JY. The missense genetic polymorphisms of human CYP2A13: functional significance in carcinogen activation and identification of a null allelic variant. Toxicol Sci. 2006;94:38. Han JF, He XY, Herrington JS, White LA, Zhang J, and Hong JY. Metabolism of 2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine (PhIP) by Human CYP1B1 Genetic Variants. Drug Metab Dispos. 2008;36:745.

8 Han JF, Wang SL, He XY, Liu CY, Hong JY. Effect of genetic variation on human cytochrome p450 reductase-mediated paraquat cytotoxicity. Toxicol Sci. 2006;91:42. Wang SL, Han JF, He XY, Wang XR, Hong JY. Genetic variation of human cytochrome p450 reductase as a potential biomarker for mitomycin C-induced cytotoxicity. Drug Metab Dispos. 2007;35:176. You WC, Hong JY, Zhang L, Pan KF, Pee D, Li JY, Ma JL, Rothman N, Caporaso N, Fraumeni JF Jr, Xu GW, Gail MH. Genetic polymorphisms of CYP2E1, GSTT1, GSTP1, GSTM1, ALDH2, and ODC and the risk of advanced precancerous gastric lesions in a Chinese population. Cancer Epidemiol Biomarkers Prev. 2005;14:451. Misra A, Hong JY, Kim S. Multiplex genotyping of cytochrome P450 single-nucleotide polymorphisms by use of MALDI-TOF mass spectrometry. Clin Chem. 2007;53:933.

9 NNK-induced cytotoxicity in CHO cells expressing CYP2A13 and its genetic variants All the cells were treated with NNK for 24 hr.

10 AFB1-induced cytotoxicity in CHO cells expressing CYP2A13 and its genetic variants All the cells were treated with AFB1 for 48 hr.

11 Number of Journal Articles Published Over Time PubMed search using “genetic, susceptibility, and environment” identified a total of 2460 articles (from 1968 to March 16, 2008) Nicholas Roden, 2008, unpublished

12 Total Funding Nicholas Roden, 2008, unpublished Over 500 million in research dollars from Environmental Protection Agency, the National Cancer Institute and the National Institute of Environmental Health Sciences.

13 Recent Progress in Genetic Polymorphism Studies High-throughput/low-cost genotyping and DNA sequencing, e.g. GWAS Knock-in mouse model

14 Computational modeling Arg 64 Lys4 76 Gly 479 Substrat e Binding Site 160 His Heme CYP2A6 Protein Structure Model The first 29 amino acids at N-terminus is not included. The substrate binding pocket is marked by H 2 O molecules (green). Collaborated with Dr. Jian Shen (Aventis)

15 Remaining Challenges Susceptibility genes are common alleles with low penetrance. Functional significance of most SNPs, particularly those localized in non-coding region of the gene. Knowledge of SNP function is always required to provide mechanistic support to association studies, including GWAS. Epigenetics and other non-gentic facotrs that regulate gene expression and/or protein activity Gene-gene interaction

16 Metabolic and Biochemical Issues in the Molecular Epidemiology of Cancer Robert Snyder and Jun-Yan Hong Partricia Buffer et. al., Mechanisms of Carcinogenesis: Contributions of Molecular Epidemiology, 2004, p51-69 For example, a small but statistically significant changes in Km values may have no real importance in human studies.

17 Recent Progress in Exposure Assessment Environmental sensors Genographic information systems Biologic sensors Toxicogenomics Body burden (biologic) measurements

18 Remaining Challenges Feasibility of obtaining accurate and quantitative information on exposure to environmental toxicants (identity, number, and level), particularly in long-term exposure situation. Identification and validation of highly sensive exposure-specific biomarkers.

19 Gene-Environment Interaction The risk is strongly dependent on exposure.

20 Uncertainty Factor in Risk Assessment Accouting for uncertainties in applied extrapolations -10A Experimental Animal to Human -10S Subchronic to Chronic Duration -10L LOAEL to NOAEL -10D Incomplete Data Base (to account for the inability of any single animal study to adequately address all possible adverse outcomes in humans) -10C Children -10H Human to Sensitive Human The actual range for each factor is from 1-10, with 3 and 10 the most commonly applied. From QY Meng’slecture, 2010


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