Background. Human genetic polymorphisms in metabolic activation and detoxification pathways are a major source of inter-individual variation in susceptibility to environmentally induced disease. The group has developed genotyping assays for the at-risk variants of enzymes that protect against carcinogens in cigarette smoke, diet, industrial processes and environmental pollution. Population studies indicate that for these candidate susceptibility genes, the frequency of the at-risk genotypes for glutathione transferase M1 (GSTM1), theta 1 (GSTT1), Pi (GSTP1) and N-acetyltransferase (NAT1 and NAT2), XRCC1, XPD, vary significantly between ethnic groups. Some differences in cancer incidence among groups may be due to genetic metabolic differences as well as exposure differences. Mission: Our long-term goal is to understanding how genes and environment interact to influence risk of environmentally induced disease. To this end we are engaged in Environmental Genomics. This encompasses: 1) identification of candidate environmental response genes, 2) discovery and functional characterization of genetic, epigenetic and phenotypic variation in these genes, and; 3) the analysis in population studies of environmental disease susceptibility associated with functional polymorphisms, acquired susceptibility factors such as epigenetic changes and environmental exposures; and the interactions between these factors. Eventually we hope these genomic approaches may identify biomarkers of exposure and effect, that will be predictive of future risk, and potentially useful in precision medicine. A current primary focus is to look at methylation levels of CpG sites in the human genome in relationship to exposures. Methylation profiles in blood and other tissues have promise as exposure biomarkers, markers of early pathology or perhaps biomarkers of disease. This information will allow us to more carefully determine the bounds of human variability to guide risk assessment and may be useful in developing prevention strategies to reduce disease incidence. In the Genetic Susceptibility Project we take the candidate susceptibility factors from the laboratory genotype/phenotype studies and test them in population studies. We are collaborating with numerous NIH, and university-based epidemiology groups to design and carryout appropriate tests of these factors in population-based epidemiology studies. Progress/accomplishments: 1) The ability of p53 to regulate transcription is crucial for tumor suppression and implies that inherited polymorphisms in functional p53 binding sites could influence cancer. Decades of research has proven that mutations in the p53 stress response pathway affect the incidence of diverse cancers more than mutations in other pathways. However, most evidence is limited to rare inherited, and somatic mutations. Using newly abundant genomic data, we demonstrate that commonly inherited genetic variants and expression quantitative trait loci (eQTLs) in the p53 pathway also affect the incidence of a broad range of cancers more than variants in other pathways. The p53 pathway cancer-associated polymorphisms have strikingly similar characteristics to well-studied p53 pathway mutations. Our results enable insights into p53-mediated tumor suppression in humans and into p53 pathway-based surveillance and treatment strategies. (Stracquadanio et al ). 2) We are examining CpG methylation in cord blood in relation to maternal smoking and in blood of adult smokers. Epigenetic modifications due to in utero exposures may play a critical role in early programming for childhood and adult illness. Examining adult smoking we found that DNA methylation of the Aryl Hydrocarbon receptor Repressor was highly significantly associated with smoking (p<10-129) and that methylation of this gene may link cigarette smoking to subclinical atherosclerosis (Reynolds et al). Changes in DNA methylation may mediate smoking-associated complex diseases through effects on immune cell function. However, knowledge of smoking effects in specific leukocyte subtypes is limited. To better characterize smoking-associated methylation changes in whole blood and leukocyte subtypes, we used Illumina 450K arrays and Reduced Representation Bisulfite Sequencing (RRBS) to assess genome-wide DNA methylation (Su et al 2016). Differential methylation analysis in whole blood DNA from 172 smokers and 81 nonsmokers revealed 738 CpGs, including 616 previously unreported CpGs, genome-wide significantly associated with current smoking (p <1.2x10-7, Bonferroni correction). Several CpGs (MTSS1, NKX6-2, BTG2) were associated with smoking duration among heavy smokers (>22 cigarettes/day, n = 86) which might relate to long-term heavy-smoking pathology. In purified leukocyte subtypes from an independent group of 20 smokers and 14 nonsmokers we further examined methylation and gene expression for selected genes among CD14+ monocytes, CD15+ granulocytes, CD19+ B cells, and CD2+ T cells. In 10 smokers and 10 nonsmokers we used RRBS to fine map differential methylation in CD4+ T cells, CD8+ T cells, CD14+, CD15+, CD19+, and CD56+ natural killer cells. Distinct cell-type differences in smoking-associated methylation and gene expression were identified. AHRR (cg05575921), ALPPL2 (cg21566642), GFI1 (cg09935388), IER3 (cg06126421) and F2RL3 (cg03636183) showed a distinct pattern of significant smoking-associated methylation differences across cell types: granulocytes> monocytes>> B cells. In contrast GPR15 (cg19859270) was highly significant in T and B cells and ITGAL (cg09099830) significant only in T cells. Numerous other CpGs displayed distinctive cell-type responses to tobacco smoke exposure that were not apparent in whole blood DNA. Assessing the overlap between these CpG sites and differential methylated regions (DMRs) with RRBS in 6 cell types, we confirmed cell-type specificity in the context of DMRs. We identified new CpGs associated with current smoking, pack-years, duration, and revealed unique profiles of smoking-associated DNA methylation and gene expression among immune cell types, providing potential clues to hematopoietic lineage-specific effects in disease etiology.
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