Using the Genetic Architecture of Substance Use Disorders to Advance Gene Identification and Understanding of Pathways of Risk

利用药物滥用疾病的遗传结构来推进基因识别和对风险途径的理解

• 批准号: 10674247
• 负责人: DANIELLE M DICK
• 金额: $ 57.01万
• 依托单位: RUTGERS BIOMEDICAL AND HEALTH SCIENCES
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-07-01 至 2025-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10674247
• 关键词: Adolescence; Affect; Age; Alcohols; Area; Behavioral; Bioinformatics; Biological; Complex; Consumption; Data; Data Set; Detection; Development; Environment; Environmental Risk Factor; Foundations; Genes; Genetic; Genetic Risk; Genetic Techniques; Genetic Variation; Genomics; Goals; Health; Human; Individual; Intervention; Lead; Maps; Mediating; Mental disorders; Meta-Analysis; Methods; Multivariate Analysis; National Longitudinal Survey of Adolescent to Adult Health; Opiate Addiction; Outcome; Pathway interactions; Phenotype; Prevention; Process; Psychiatry; Risk; Running; Sample Size; Sampling; Signal Transduction; Structure; Substance Use Disorder; Techniques; Testing; Translating; Twin Multiple Birth; Variant; addiction; alcohol use disorder; behavioral phenotyping; clinical diagnosis; emerging adulthood; gene discovery; genetic architecture; genetic association; genetic variant; genome wide association study; genome-wide; high risk; improved; insight; longitudinal dataset; marijuana use disorder; novel; opioid use disorder; personalized medicine; polygenic risk score; population based; racial and ethnic; sex; substance use; substance use treatment; trait

Project Summary This project has two complementary goals: (1) to advance discovery of genes involved in substance use disorders using new multivariate genomic techniques, and (2) to characterize the risk associated with identified variants in diverse longitudinal samples in order to understand the spectrum of phenotypes associated with identified variants, across development, and in conjunction with the environment. Each of these areas represents critical steps in using genetic data to improve prevention, intervention, and treatment for substance use disorders (SUDs), and will lay the foundation as we move into an era of personalized medicine. Human gene identification efforts for substance use disorders lag behind other areas of psychiatry, in part due to constrained sample sizes of available SUD cases. However, recent meta-analyses of substance-related phenotypes such as age of initiation, consumption and problems, reveal significant genetic correlations across substance use outcomes, as well as with numerous other psychiatric and behavioral traits. These findings map onto twin data demonstrating significant genetic correlations across substance use disorders and other externalizing traits. This project will (Aim 1) apply new multivariate genetic methods to capitalize on genetic sharing between substance use phenotypes and related traits in order to boost power to detect common variants associated with substance use outcomes, and to characterize the latent pathways by which genetic variants operate. Bioinformatic characterization of these identified genetic variants will provide insight into underlying biological risk pathways, and phenotypic characterization of resultant polygenic risk scores will help us understand how risk unfolds across development and in conjunction with the environment. We will apply results from the multivariate analyses to two complementary longitudinal datasets, consisting of a population-based and high-risk sample, in order to (Aim 2a) map the behavioral phenotypes associated with the genetic risk scores identified in Aim 1 across adolescence and emerging adulthood; (Aim 2b) test for pathways of risk specific to sex and racial/ethnic background; and (Aim 2c) test for moderation of genetic risk by key environmental factors. Jointly, these analyses will advance our understanding of how genetic variation contributes to risk for substance use disorders.

项目摘要 该项目有两个互补的目标：（1）进一步发现涉及的基因 使用新的多元基因组技术使用物质使用障碍，（2）表征 与各种纵向样本中确定的变体相关的风险，以了解 与已识别变体，跨发育和中的表型相关的表型 与环境的结合。这些领域中的每一个都代表着使用遗传的关键步骤 改善药物使用障碍（SUD）的预防，干预和治疗的数据， 并将在我们进入个性化医学时代时奠定基础。人基因 识别物质使用障碍的努力滞后于其他精神病学领域，部分部分是 由于可用的SUD病例的样本量受限。但是，最近的荟萃分析 与物质相关的表型，例如启动，消费和问题的年龄揭示 跨物质使用结果以及许多其他物质的遗传相关性 精神病和行为特征。这些发现映射到双数据数据显示出明显的 跨物质使用障碍和其他外部特征的遗传相关性。这个项目 将（目标1）应用新的多元遗传方法来利用遗传共享 物质使用表型和相关性状，以增强能力检测常见变体 与物质使用结果相关，并表征该潜在途径 遗传变异可运行。这些鉴定出的遗传变异的生物信息学表征将 提供有关潜在的生物风险途径的见解，以及表型的表征 由此产生的多基因风险评分将有助于我们了解在开发过程中的风险如何 结合环境。我们将将多元分析的结果应用于两个 互补的纵向数据集，由基于人群和高风险样本组成， 为了（AIM 2A）映射与遗传风险评分相关的行为表型 在青春期和新兴成年期间在AIM 1中确定； （AIM 2B）测试途径 特有性和种族/种族背景的风险； （AIM 2C）测试遗传风险的适度 由关键的环境因素。共同的这些分析将提高我们对如何的理解 遗传变异有助于药物使用障碍的风险。