Genetics of arsenic metabolism: fine-mapping and rare variant analysis

描述（由申请人提供）：砷污染食品和饮用水是一个严重的全球健康问题，因为砷暴露会增加癌症、心血管疾病、呼吸系统疾病和总体死亡率的风险。对砷毒性的敏感性部分由影响个体代谢砷的能力的遗传因素决定，代谢砷的过程促进砷在尿中的排泄。确定这些遗传因素将使个人分类的基础上的毒性风险和阐明的生物学机制对砷毒性的易感性，为制定干预措施，减少毒性。先前的研究表明，在10q24.32区域（包含砷甲基转移酶基因; AS 3 MT）中至少有两个独立的关联信号。然而，先前的研究一直无法确定该地区的因果变异，这是由于缺乏（1）该地区所有遗传变异的完整数据，（2）来自该地区的大样本量， 多个群体组，和（3）非编码变体的综合功能注释。此外，从未评估过该区域罕见变异的潜在影响。我们建议通过对来自三个砷暴露人群（孟加拉人、美洲原住民和欧洲美洲人）的> 4，500名个体的该区域进行测序来填补这些知识空白。在这些组中的每一组中，我们将评估该区域中的变体与砷甲基化能力之间的关联（即，尿砷代谢物百分比）。不同祖先群体之间的关联模式的变化将使我们能够缩小人群之间共享的因果变异，并检查人群特异性信号的证据。将使用贝叶斯方法评估因果关系的统计学证据。将使用基于局部转录因子结合（ChIP-Seq）、DNaseI超敏反应、染色质标记和顺式基因表达的既往证据的非编码变体注释评估功能性证据。将评估基因-砷相互作用的证据。我们将使用基因水平的关联测试来确定AS 3 MT基因中的罕见编码变异是否共同影响砷甲基化能力。为了评估这些变异对砷相关健康结果的影响，我们将测试目标1-2中确定的10q24.32变异与砷皮肤病变（孟加拉国病例和对照组）和鳞状细胞皮肤癌（欧美病例和对照组）风险之间的关联。识别潜在的致病变异和评估罕见变异的影响是阐明10q24.32突变在砷代谢和毒性中的关键作用的合乎逻辑和必不可少的下一步。我们提出的知识将提高风险预测，指导未来的研究和预防工作的发展，并澄清生物学机制，个体间的差异敏感性砷中毒。

DESCRIPTION (provided by applicant): Contamination of food and drinking water with arsenic is a serious global health issue, as arsenic exposure increases risk for cancer, cardiovascular disease, respiratory conditions, and overall mortality. Susceptibility to arsenic toxicity is partilly determined by genetic factors that influence an individual's capacity to metabolize arsenic, a process that facilitates the excretion of arsenic in urine. Identifying such genetic factors will enable classification of individuals based on toxicity risk and elucidate the biological mechanism underlying susceptibility to arsenic toxicity, informing the development of interventions that reduce toxicity. Prior research has demonstrated that there are at least two independent association signals in the 10q24.32 region (which contains the arsenic methytransferase gene; AS3MT). However, prior studies have been unable to identify the causal variants in this region due to lack of (1) complete data on all genetic variants in the region, (2) large sample sizes from multiple population groups, and (3) comprehensive functional annotation for non-coding variants. Furthermore, the potential effects of rare variants in this region have never been assessed. We propose to fill these knowledge gaps by sequencing this region in >4,500 individuals from three arsenic- exposed population groups: Bangladeshis, Native Americans, and European Americans. Within each of these groups, we will assess associations between variants in this region and arsenic methylation capacity (i.e., urinary arsenic metabolite percentages). Variations in patterns of association across ancestry groups will allow us to narrow-in on causal variants shared across populations and examine evidence for population-specific signals. Statistical evidence of causal association will be assessed using a Bayesian approach. Evidence of functionality will be assessed using annotation of non-coding variants based on prior evidence of local transcription factor binding (ChIP-Seq), DNaseI hypersensitivity, chromatin marks, and cis-gene expression. Evidence for gene-arsenic interaction will be assessed. We will determine if rare coding variants in the AS3MT gene collectively influence arsenic methylation capacity using gene-level association tests. To assess the implications of these variants for arsenic-related health outcomes, we will test associations between the 10q24.32 variants identified in aims 1-2 and risk for arsenical skin lesions (among Bangladeshi cases and controls) and squamous cell skin cancer (among European American cases and controls). Identifying potential causal variants and assessing the effects of rare variants is a logical and essential next step for elucidating the critical role of the 10q24.32 regon in arsenic metabolism and toxicity. The knowledge we are proposing to generate will enhance risk prediction, guide the development future research and prevention efforts, and clarify the biological mechanisms that underlie inter-individual differences in susceptibility to arsenic toxicity.