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：
8990623
负责人：
Dana B Hancock
金额：
$ 10万
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 2017-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8990623
关键词：
15q25 8p11 Accounting African American Bioinformatics Caucasians Chromosomes Chromosomes, Human, Pair 7 Chronic Obstructive Airway Disease Cigarette Collaborations Complex Data Dependence Disease Environment Freedom Genes Genetic Genetic study 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 carrier status 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 genome-wide analysis method development mortality novel novel strategies risk variant 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）：吸烟是癌症，心脏疾病，中风和肺部病的主要因素，是美国和全球可预防死亡率的主要原因。尼古丁依赖性（ND）和其他吸烟表型的全基因组关联研究（GWAS）无明确地鉴定出与跨烟碱乙酰胆碱受体（NACHR）基因上的单核苷酸多态性（SNP）的关联（SNP） chrna6）。功能变异改变了停止治疗反应，并与吸烟的健康后果独立相关。但是，他们解释了吸烟的表型变异性的10％。在这项研究中，我们将超越标准GWAS，进行首次研究，以使用基因 - 基因相互作用应用联合2-自由度（2DF）统计方法。它将是最大的全基因组研究。新开发的关节2DF方法同时考虑了SNP主和交互作用，但并不集中于检测相互作用本身。相反，该方法利用交互来增加SNP关联测试的功率。在考虑基因环境相互作用时，它已被用来成功识别标准GWA中错过的SNP关联。在这里，我们将应用联合2DF方法同时考虑SNP主要关联及其与已建立的NACHR变体的相互作用。我们从ND的合作遗传研究（Cogend），Decode遗传学以及其他通过基因型和表型（DBGAP）数据库（通过Fagerstrom测试烟碱依赖性（FTN）数据）获得的其他研究中利用了现有的GWAS数据：> 23,000名参与者的集体大小。在AIM1中，我们将从14个研究样本中获得全基因组SNP基因型数据，并协调其FTND表型数据。使用Cogend和Decode遗传学（总n = 10,319种高加索人），我们将同时进行ND的全基因组关节2DF荟萃分析，这是与CHRNA5-CHRNA3-CHRNB4（在AIM 2）或CHRNB3-CHRNA6（在AIM 3中）的相互作用。联合2DF荟萃分析的顶级SNP将使用生物信息学分析来优先级，以评估其注释，功能和调节潜力。在AIM 4A中，我们将选择从DBGAP的七个独立的白种样本中进行100个顶级SNP进行复制测试（总n = 8,913）。来自AIM 4A的复制SNP将进一步测试与AIM 4B相关的ND，使用我们的两个非裔美国人样本和三个DBGAP样品（总n = 4,145）。我们先前的吸烟和其他人的GWA已经确定了鲁棒，功能上重要的变体，这些变体也有助于停止治疗反应和与吸烟有关的疾病（例如肺癌）。这项研究利用了这些早期发现和一种新的统计方法来发现促成ND的新型变种，这可能会增加我们对戒烟和吸烟的健康后果的理解。