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

描述(由申请人提供)：食物和饮用水被砷污染是一个严重的全球健康问题，因为接触砷会增加患癌症、心血管疾病、呼吸系统疾病和总死亡率的风险。对砷毒性的易感性部分由遗传因素决定，这些遗传因素影响个体代谢砷的能力，这是一个促进尿砷排泄的过程。识别这些遗传因素将能够根据毒性风险对个体进行分类，并阐明对砷毒性易感性的生物学机制，从而为开发降低毒性的干预措施提供信息。先前的研究已经证明，在10q24.32区域(包含砷甲基转移酶基因AS3MT)至少存在两个独立的关联信号。然而，以前的研究由于缺乏(1)该地区所有遗传变异的完整数据，(2)来自 多群体组，以及(3)非编码变体的全面功能注释。此外，该地区罕见变异的潜在影响从未被评估过。我们建议通过对来自三个砷暴露人群的4500人进行测序来填补这些知识空白：孟加拉人、美洲原住民和欧洲美国人。在每一组中，我们将评估该区域的变异与砷甲基化能力(即尿砷代谢物百分比)之间的关联。不同祖先群体之间的关联模式的变化将使我们能够缩小范围，寻找在不同群体中共享的因果变异，并检查特定于群体的信号的证据。因果关联的统计证据将使用贝叶斯方法进行评估。功能的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先前证据的非编码变体的注释来评估。将对基因-砷相互作用的证据进行评估。我们将通过基因水平的关联测试来确定AS3MT基因中罕见的编码变异是否共同影响砷的甲基化能力。为了评估这些变异对砷相关健康结局的影响，我们将测试AIMS 1-2中确定的10q24.32变异与砷皮肤损害(在孟加拉国病例和对照中)和鳞状细胞皮肤癌(在欧美病例和对照中)风险之间的相关性。确定潜在的因果变异并评估稀有变异的影响是阐明10q24.32基因在砷代谢和毒性中的关键作用的合乎逻辑和必要的下一步。我们提议产生的知识将增强风险预测，指导未来的研究和预防工作的发展，并阐明个体之间对砷毒性易感性差异的生物学机制。

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.