Novel Analysis of Gene-Gene and Gene-Environment Interactions in Alcoholism

酗酒中基因-基因和基因-环境相互作用的新分析

• 批准号: 8244285
• 负责人: Iryna Lobach
• 金额: $ 18.66万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-09-01 至 2015-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8244285
• 关键词: Accounting; Alcohol abuse; Alcohol consumption; Alcohol dependence; Alcoholism; Case-Control Studies; Comorbidity; Complex; DSM-IV; Data; Data Analyses; Data Set; Dependence; Development; Diagnosis; Disease; Disease Pathway; Drug Addiction; Environment; Environmental Risk Factor; Epidemiology; Equilibrium; Ethanol Metabolism; Evaluation; Gender; Genes; Genetic; Genetic Markers; Genetic Predisposition to Disease; Genetic Risk; Genotype; Goals; Individual; Intervention; Joints; Linkage Disequilibrium; Location; Metabolism; Methodology; Methods; Modeling; Nature; Noise; Onset of illness; Pathway Analysis; Pathway interactions; Pattern; Pharmaceutical Preparations; Policies; Population; Predisposition; Prevention; Proteins; Psyche structure; Public Health; Race; Regression Analysis; Research; Research Personnel; Resistance; Risk; Risk Factors; Signal Transduction; Single Nucleotide Polymorphism; Structure; Subgroup; Substance Addiction; Techniques; Testing; Variant; Work; addiction; alcohol exposure; base; case control; database of Genotypes and Phenotypes; design; environmental stressor; flexibility; gene environment interaction; genetic epidemiology; genetic risk factor; genetic variant; genome-wide; improved; meetings; neurotransmission; novel; public health relevance; research study

DESCRIPTION (provided by applicant): A key component to prevention and control of complex disorders, such as alcohol dependence, is to identify genetic and environmental factors that contribute to their development and progression. The analysis is complicated by the fact that genetic and environmental factors (e.g., gender, environmental stressors) interplay in disorder onset and progression. Further, complex disorders are likely to be caused by an interaction between genetic markers; hence the effect of each individual marker (e.g., single-nucleotide polymorphism (SNP)) on risk of a complex disorder is likely to be relatively small. The goals of this project are 1). provide a framework for the analysis of data from case-control studies with the following features: A. risk factors involving a panel of genetic markers that are likely to interact causing the onset of a complex disorder; B. genetic and environmental factors defining subgroups of population with unusual resistance or susceptibility to disorder onset and progression ; 2). apply the proposed methodology to the data collected as a part of Study of Addiction: Genetics and Environment (SAGE) available through the database of Genotypes and Phenotypes. The main difference of proposed approach from the traditional is that PIs consider groups of markers organized based on their function suggested by biomedical experiments, using various levels of genetic information: (1) linkage disequilibrium patterns; (2) genes; (3) pathways. Given the information about what genes work together to influence various aspects of alcohol use, the project aims to investigate the interaction structure of the genetic markers within each group. PIs develop a novel pathway analysis which offers the opportunity to combine association evidence from multiple genetic variants and thus potentially has a better chance of identifying the association between the pathway and the disease. Moreover, they propose a novel methodology for analysis of data in the presence of complex gene-environment interactions, consisting of two major parts: 1. characterize the relevant dependence structure between genetic and environmental factors, (in the case of alcohol dependency, diplotype effects and gender and environmental stressors); 2. Incorporate the dependence structure into the regression analysis. The proposed approach has the potential to improve understanding of genetic predisposition and environmental risk factors of alcoholism through their joint analysis. The approach is flexible and can be adapted for the analysis of other drug dependence disorders. Moreover, the findings of planned data analysis have the potential to challenge the traditional conceptualizations of environmental risk factors and have implications for public health interventions, evaluations and policies.

描述（由申请人提供）：预防和控制复杂疾病（如酒精依赖）的一个关键组成部分是确定导致其发展和进展的遗传和环境因素。遗传和环境因素（如性别、环境压力）在疾病的发生和发展中相互作用，这一事实使分析变得复杂。此外，复杂的疾病可能是由遗传标记之间的相互作用引起的；因此，每个个体标记（例如，单核苷酸多态性（SNP））对复杂疾病风险的影响可能相对较小。该项目的目标是：1)为病例对照研究的数据分析提供一个框架，该研究具有以下特征：a .涉及一组可能相互作用导致复杂疾病发病的遗传标记的风险因素；B.遗传和环境因素定义了对疾病的发病和进展具有异常抗性或易感性的人群亚群；2)将提出的方法应用于通过基因型和表型数据库收集的作为成瘾研究：遗传与环境（SAGE）的一部分的数据。该方法与传统方法的主要区别在于，pi考虑根据生物医学实验提出的功能组织的标记群，使用不同水平的遗传信息：(1)连锁不平衡模式；(2)基因;(3)通路。鉴于有关哪些基因共同作用影响饮酒的各个方面的信息，该项目旨在调查每个群体中遗传标记的相互作用结构。pi开发了一种新的途径分析，提供了将来自多种遗传变异的关联证据结合起来的机会，从而有可能更好地确定途径与疾病之间的关联。此外，他们提出了一种新的方法来分析存在复杂基因-环境相互作用的数据，包括两个主要部分：1。描述遗传和环境因素之间的相关依赖结构（在酒精依赖的情况下，二倍型效应以及性别和环境压力因素）；2. 将依赖结构纳入回归分析。提出的方法有可能通过他们的联合分析来提高对酒精中毒的遗传易感性和环境风险因素的理解。该方法是灵活的，可适用于其他药物依赖障碍的分析。此外，有计划的数据分析结果有可能挑战传统的环境风险因素概念，并对公共卫生干预、评价和政策产生影响。