Utilizing Interaction to Identify Novel Genetic Factors for Nicotine Dependence

利用相互作用来识别尼古丁依赖的新遗传因素

基本信息

批准号：
8558757
负责人：
Dana B Hancock
金额：
$ 44.65万
依托单位：
RESEARCH TRIANGLE INSTITUTE
依托单位国家：
美国
项目类别：
财政年份：
2013
资助国家：
美国
起止时间：
2013-07-01 至 2016-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8558757
关键词：
15q25 8p11 Accounting African American Alleles Bioinformatics Caucasians Caucasoid Race Chromosomes Chromosomes, Human, Pair 7 Chronic Obstructive Airway Disease Cigarette Collaborations Complex Data Dependence Disease Environment Freedom Genes Genetic Genotype Health Heart Diseases Heritability Joints Linear Regressions Lung diseases Malignant Neoplasms Malignant neoplasm of lung Measures Meta-Analysis Methodology Methods Modeling Nicotine Dependence Nicotinic Receptors Other Genetics Participant Phenotype Physiological Receptor Gene Reporting Risk Sampling Sampling Studies Single Nucleotide Polymorphism Smoking Smoking and Health Research Statistical Methods Stroke Testing United States Variant Withholding Treatment base cigarette smoking database of Genotypes and Phenotypes follow-up gene environment interaction gene interaction genetic association genetic risk factor genetic variant genome wide association study genome-wide method development mortality novel novel strategies public health relevance smoking cessation trait treatment response

项目摘要

DESCRIPTION (provided by applicant): Cigarette smoking is a major contributor to cancer, heartdisease, stroke, and lung disease and is the leading cause of preventable mortality in the United States and worldwide. Genome-wide association studies (GWAS) of nicotine dependence (ND) and other smoking phenotypes have unequivocally identified associations with single nucleotide polymorphisms (SNPs) spanning the nicotinic acetylcholine receptor (nAChR) genes on chromosome 15q25 (CHRNA5-CHRNA3-CHRNB4) and on chromosome 8p11 (CHRNB3- CHRNA6). The functional variants alter cessation treatment response and are independently associated with health consequences of smoking. However, they explain <10% of the phenotypic variability for smoking. In this study, we will move beyond standard GWAS, conducting the first study to apply the joint 2 degree-of- freedom (2df) statistical method using gene-gene interaction. It will be the largest genome-wide study of ND. The newly developed joint 2df method simultaneously considers SNP main and interactive effects but does not focus on detecting interaction per se. Instead, the method leverages interaction to increase power of the SNP association test. It has been used to successfully identify SNP associations missed in standard GWAS for other complex traits when accounting for gene-environment interactions. Here, we will apply the joint 2df method to simultaneously consider SNP main associations and their interactions with the established nAChR variants. We capitalize on existing GWAS data from our Collaborative Genetic Study of ND (COGEND), deCODE Genetics, and other studies available via the Database of Genotypes and Phenotypes (dbGaP) with Fagerstrom Test for Nicotine Dependence (FTND) data: collective size of >23,000 participants. In Aim1, we will obtain genome-wide SNP genotype data from 14 study samples and harmonize their FTND phenotype data. Using COGEND and deCODE Genetics (total N=10,319 Caucasians), we will conduct genome-wide joint 2df meta-analyses of ND, in parallel, accounting for an interaction with either CHRNA5- CHRNA3-CHRNB4 (in Aim 2) or CHRNB3-CHRNA6 (in Aim 3). The top-ranking SNPs from the joint 2df meta-analyses will be prioritized using bioinformatics analyses to evaluate their annotation, functionality, and regulatory potential. In Aim 4a, we will select up to 100 top-ranking SNPs for replication testing in seven independent Caucasian samples from dbGaP (total N=8,913). Replicated SNPs from Aim 4a will be further tested for association with ND in Aim 4b using two of our African American samples and three dbGaP samples (total N=4,145). Our prior GWAS of smoking and others have identified robust, functionally important variants that also contribute to cessation treatment response and smoking-related diseases (e.g., lung cancer). This study leverages these early findings and a new statistical method to discover novel variants contributing to ND, which may similarly add to our understanding of smoking cessation and smoking's health consequences.

描述（由申请人提供）：吸烟是导致癌症、心脏病、中风和肺病的主要原因，也是美国和全世界可预防死亡的主要原因。尼古丁依赖 (ND) 和其他吸烟表型的全基因组关联研究 (GWAS) 明确确定了与染色体 15q25 (CHRNA5-CHRNA3-CHRNB4) 上的烟碱乙酰胆碱受体 (nAChR) 基因的单核苷酸多态性 (SNP) 之间的关联染色体 8p11 (CHRNB3-CHRNA6)。功能变异改变戒烟治疗反应，并与吸烟的健康后果独立相关。然而，他们解释了吸烟导致的表型变异<10%。在本研究中，我们将超越标准 GWAS，开展第一项研究，利用基因-基因相互作用应用联合 2 自由度 (2df) 统计方法。这将是最大的新城疫全基因组研究。新开发的联合2df方法同时考虑了SNP的主要效应和交互作用，但并不专注于检测交互作用本身。相反，该方法利用相互作用来提高 SNP 关联测试的功效。在考虑基因-环境相互作用时，它已被用来成功识别标准 GWAS 中遗漏的其他复杂性状的 SNP 关联。在这里，我们将应用联合 2df 方法来同时考虑 SNP 主要关联及其与已建立的 nAChR 变体的相互作用。我们利用来自 ND 合作遗传学研究 (COGEND)、deCODE Genetics 的现有 GWAS 数据以及通过基因型和表型数据库 (dbGaP) 提供的其他研究以及 Fagerstrom 尼古丁依赖测试 (FTND) 数据：集体规模 >23,000参与者。在 Aim1 中，我们将从 14 个研究样本中获取全基因组 SNP 基因型数据，并协调其 FTND 表型数据。使用 COGEND 和 deCODE Genetics（总共 N=10,319 个白种人），我们将并行对 ND 进行全基因组联合 2df 荟萃分析，解释与 CHRNA5-CHRNA3-CHRNB4（目标 2）或 CHRNB3-CHRNA6 的相互作用（在目标 3 中）。联合 2df 荟萃分析中排名靠前的 SNP 将使用生物信息学分析进行优先排序，以评估其注释、功能和监管潜力。在目标 4a 中，我们将选择到 100 个顶级 SNP，在 dbGaP 的 7 个独立白种人样本中进行复制测试（总 N=8,913）。将使用我们的两个非裔美国人样本和三个 dbGaP 样本（总 N=4,145）进一步测试 Aim 4a 中复制的 SNP 与 Aim 4b 中 ND 的关联。我们之前对吸烟和其他疾病的 GWAS 已经发现了强大的、功能上重要的变异，这些变异也有助于戒烟治疗反应和吸烟相关疾病（例如肺癌）。这项研究利用这些早期发现和新的统计方法来发现导致 ND 的新变异，这可能同样会增加我们对戒烟和吸烟对健康后果的理解。