The Kinship Risk Score: An Integrative Tool to Prioritize Alcohol and Drug-Addiction Related Genes for Enhanced Risk Prediction

亲属关系风险评分：优先考虑酒精和毒瘾相关基因以增强风险预测的综合工具

• 批准号: 9162597
• 负责人: ROHAN Hugh Craig PALMER
• 金额: $ 46.8万
• 依托单位: EMORY UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-15 至 2022-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9162597
• 关键词: Addictive Behavior; Alcohols; Animals; Bayesian Analysis; Behavior; Behavioral; Biological; Complement; Complex; Data; Dependence; Development; Disease; Drug Addiction; Family Study; Genes; Genetic; Genetic Variation; Genomics; Goals; Health; Human; Individual Differences; Mendelian disorder; Modeling; Molecular; Pathway interactions; Pharmaceutical Preparations; Population; Predisposition; Prevention; Relative Risks; Research; Risk; Specific qualifier value; Substance Addiction; Substance of Abuse; Testing; Tobacco; Twin Studies; Variant; addiction; alcohol and other drug; base; combinatorial; drug of abuse; flexibility; functional genomics; gene interaction; genetic variant; genome-wide; illicit drug use; improved; novel; online resource; psychosocial; tool; trait

PROJECT SUMMARY/ABSTRACT The primary goals of this project are to identify and characterize gene sets that reflect individual differences in the propensity to develop alcohol or other forms of drug addiction and to develop a novel tool to enhance the prediction of drug addiction risk using genome-wide data. Alcohol, tobacco, and illicit drug use and dependence are complex biological and psychosocial problems that can be conceptualized as alternate forms of an underlying behavioral predisposition to the development of generalized drug dependence (DD). Despite the fact that twin and family studies suggest that genetic variation contributes to the preoccupation with alcohol and other multiple substances of abuse, the identification of specific causal loci has been limited. In fact, studies have confirmed that unlike monogenic disorders, alcohol and other drugs of abuse are influenced by numerous genetic variants. While both human and animal studies of addiction have indicated that multiple forms of drug addiction are genetically influenced, the full complement of biological mechanisms and genetic factors are still unknown. The current application proposes a novel framework and tool that integrates Bayesian statistics and functional genomics to enhance the identification of a set(s) of causal genetic factors for alcohol and other drug dependence. In the first component of the framework, we will use Bayesian mixture modeling to identify a set(s) of markers that comprise the additive genetic effect on generalized drug dependence (DD). In the second component, we will identify cross-species-functionally-annotated gene sets for alcohol, tobacco, and other illicit drug use/dependence, determine their relative contribution to variation in DD, and test for enrichment of the Bayesian-derived gene set(s) in (a) gene sets ascertained using cross- species-functional genomic studies of alcohol and other drug addiction, and (b) a range of biological gene sets based on known molecular pathways. In the third component, we will identify combinatorial effects within and between gene sets. In the final component, we develop prediction models, as well as test a novel kinship- based approach to predict the risk for DD given a specified gene set. Each of these components provides novel information that will help to formulate new research hypotheses and prediction models for addictive behaviors and other behaviors/traits.

项目概要/摘要 该项目的主要目标是识别和表征反映个体差异的基因集 发展酒精或其他形式的药物成瘾的倾向，并开发一种新的工具来增强 使用全基因组数据预测吸毒成瘾风险。酒精、烟草和非法药物的使用以及 依赖性是复杂的生物和心理社会问题，可以概念化为替代形式 普遍药物依赖（DD）发展的潜在行为倾向。尽管 事实上，双胞胎和家庭研究表明，遗传变异导致人们对酒精的沉迷 和其他多种滥用药物的情况一样，具体因果位点的确定还很有限。实际上， 研究证实，与单基因疾病不同，酒精和其他滥用药物受到以下因素的影响： 许多遗传变异。虽然人类和动物对成瘾的研究表明，多种 药物成瘾的形式受遗传影响，生物机制和遗传的全面补充 因素仍未知。当前的应用程序提出了一种新颖的框架和工具，集成了 贝叶斯统计和功能基因组学可增强对一组因果遗传因素的识别 用于酒精和其他药物依赖。在框架的第一个组成部分中，我们将使用贝叶斯混合 建模以识别一组标记，这些标记包含对广义药物的加性遗传效应 依赖性（DD）。在第二部分中，我们将识别跨物种功能注释的基因集 对于酒精、烟草和其他非法药物的使用/依赖，确定它们对变化的相对贡献 DD，并测试使用交叉确定的（a）基因集中贝叶斯衍生基因集的富集性 酒精和其他药物成瘾的物种功能基因组研究，以及（b）一系列生物基因组 基于已知的分子途径。在第三个组成部分中，我们将确定内部的组合效应和 基因组之间。在最后一部分中，我们开发预测模型，并测试一种新颖的亲属关系- 基于给定特定基因组的 DD 风险预测方法。每个组件都提供 新颖的信息将有助于制定新的研究假设和成瘾预测模型 行为和其他行为/特征。