Identifying inherited genetic determinants of arsenic metabolism efficiency and their mechanisms

确定砷代谢效率的遗传决定因素及其机制

• 批准号: 10157648
• 负责人: Meytal Batya Chernoff
• 金额: $ 5.1万
• 依托单位: UNIVERSITY OF CHICAGO
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-04-01 至 2025-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10157648
• 关键词: Address; Affect; Arsenic; Arsenites; Automobile Driving; Bangladesh; Bangladeshi; Biological; Carcinogens; Cardiovascular Diseases; Cells; Chronic; Code; Consumption; DNA Methylation; Data; Data Sources; Diabetes Mellitus; Disease; Enzymes; Excretory function; Exposure to; Future; Gene Expression; Gene Expression Regulation; Genes; Genetic; Genetic Determinism; Genetic Predisposition to Disease; Genetic Variation; Genomics; Genotype; Genotype-Tissue Expression Project; Health; Heart; Individual; Inherited; Knowledge; Linkage Disequilibrium; Longitudinal Studies; Malignant Neoplasms; Malignant neoplasm of lung; Malignant neoplasm of urinary bladder; Measures; Metabolism; Methylation; Methyltransferase; New Hampshire; Pattern; Population; Positioning Attribute; Predisposition; Pregnancy Complications; Probability; Public Health; Quantitative Trait Loci; Reaction; Regulation; Risk; Sample Size; Series; Skin Cancer; Skin Squamous Cell; Squamous cell carcinoma; Subgroup; Testing; Tissues; Toxic effect; Urine; Variant; Work; cancer type; causal variant; cohort; contaminated drinking water; data integration; drinking water; epidemiology study; exposed human population; follow-up; gene environment interaction; genetic variant; genome editing; genome wide association study; health data; high risk; improved; inter-individual variation; nervous system disorder; skin lesion; targeted sequencing; urinary

PROJECT SUMMARY/ABSTRACT This project seeks to identify the causal variants and mechanisms underlying the association between inherited genetic variants in the 10q24.32 region and arsenic metabolism efficiency (AME). Exposure to arsenic- contaminated drinking water impacts approximately 140 million individuals across the globe including 13 million in the U.S and 56 million in Bangladesh. This exposure increases the risk of multiple cancers as well as cardiovascular and neurologic diseases, pregnancy complications, and diabetes. There is considerable inter- individual variation in AME with lower AME associated with a higher risk of arsenic toxicity. A genome-wide association study (GWAS) of AME in a Bangladeshi population conducted by our group identified multiple genetic variants in the 10q24.32 region independently associated with AME (measured as relative concentrations of arsenic metabolites in urine). These variants reside in close proximity to AS3MT, a gene coding for arsenite methyltransferase, a key enzyme involved in arsenic metabolism. However, neither the causal variants in this region nor the mechanisms underlying their effects are known. These gaps in our knowledge are likely due to the small sample size, incomplete genetic data, and single-population focus of many previous studies, as well as a lack of integration of data sources on the potential functional effects of associated variants. To address the limitations of prior studies, we will analyze dense genotyping data from targeted sequencing of the 10q24.32 region for ~4100 individuals from 3 arsenic-exposed cohorts: the Health Effects of Arsenic Longitudinal Study, the Strong Heart Study, and the New Hampshire Skin Cancer Study of Squamous Cell Carcinoma. First, we will use association analysis approaches to identify potential causal variants underlying observed associations between AME and inherited variation in the 10q24.32 region. Our use of targeted sequencing data from three distinct ancestry groups will enable us to leverage differences in their patterns of linkage disequilibrium to identify shared causal variants through Bayesian fine-mapping. Second, we will identify potential mechanisms by which causal variants impact arsenic metabolism efficiency by integrating our association results (from Aim 1) with results from analyses of expression and methylation quantitative trait loci (eQTL, meQTL) in multiple tissue types as well as with expression and methylation data from a Bangladeshi population. Finally, we will determine how AS3MT genotype modifies the association between arsenic-exposure and risk for arsenic-related diseases (i.e., arsenic-induced skin lesions and skin cancer). Our work will be the first to use targeted sequencing to identify potential causal variants and mechanisms underlying the association between the 10q24.32 region and AME. Our results will provide a more complete picture of genetic susceptibility to arsenic toxicity, enabling us to better identify individuals at high risk for arsenic toxicities and improve the focus of public health efforts in arsenic-exposed populations.

项目总结/摘要 该项目旨在确定遗传性之间联系的因果变异和机制 10q24.32区域的遗传变异和砷代谢效率（AME）。接触砷- 受污染的饮用水影响地球仪约1.4亿人，其中包括1300万人 在美国和5600万在孟加拉国。这种接触会增加患多种癌症的风险， 心血管和神经系统疾病、妊娠并发症和糖尿病。有相当大的内部- AME的个体差异与较低的AME与较高的砷中毒风险相关。全基因组 我们的小组在孟加拉国人群中进行的AME相关性研究（GWAS）确定了多个 10q24.32区域中的遗传变异与AME独立相关（以相对 尿中砷代谢物的浓度）。这些变异体与AS 3 MT基因非常接近， 编码亚砷酸盐甲基转移酶，一种参与砷代谢的关键酶。然而，无论是 该区域的致病变异体及其作用机制尚不清楚。这些差距在我们的 知识可能是由于小样本量，不完整的遗传数据，和单一人口的重点， 许多以前的研究，以及缺乏整合的数据来源的潜在功能影响， 相关变种为了解决先前研究的局限性，我们将分析来自 对来自3个砷暴露队列的约4100名个体的10q24.32区域进行靶向测序： 砷的纵向研究、强心研究和新罕布什尔州皮肤癌研究对 鳞状细胞癌首先，我们将使用关联分析方法来识别潜在的因果关系， AME和10q24.32区域遗传变异之间观察到的关联的潜在变异。我们 使用来自三个不同祖先群体的靶向测序数据将使我们能够利用 他们的连锁不平衡模式，以确定通过贝叶斯精细定位共享的因果变异。 其次，我们将确定致病变异体影响砷代谢效率的潜在机制 通过整合我们的关联结果（来自Aim 1）与来自表达和甲基化分析的结果， 多个组织类型中的数量性状基因座（eQTL，meQTL）以及表达和甲基化数据 来自孟加拉国人口。最后，我们将确定AS 3 MT基因型如何改变这种关联， 砷暴露与砷相关疾病风险之间的关系（即，砷引起的皮肤损害和皮肤 癌症）。我们的工作将是第一个使用靶向测序来识别潜在的致病变异， 10q24.32区域和AME之间的关联机制。我们的研究结果将提供一个 更完整地了解砷毒性的遗传易感性，使我们能够更好地识别个体， 砷中毒的高风险，并改善砷暴露人群的公共卫生工作的重点。