Project 4 - Human studies to identify genes and characterize risk pathways involved in alcohol related outcomes

项目摘要-项目4 VCU酒精研究中心的项目4将利用人类数据实现两个相辅相成的目标： (1)利用新的多变量基因组推进与酒精相关结果相关基因的发现 技术，以及(2)表征与不同纵向样本中已识别的变异相关的风险，在 为了了解与已识别的变异相关的表型谱，跨越发育阶段，以及 与环境相结合。这些领域中的每一个都代表着利用基因数据 改善酒精使用障碍(AUD)的预防、干预和治疗，并将为 我们进入了一个个性化医疗的时代。人类酒精使用障碍的基因识别工作滞后 落后于精神病学的其他领域，部分原因是现有AUD病例的样本数量有限。然而， 最近对消费和AUD的元分析显示，与许多其他因素存在显著的遗传相关性 精神和行为特征，以及社会和人口统计结果，以及其他生物医学 表型。项目4将(目标1)应用新的多变量遗传方法来利用遗传共享 酒精使用表型与其他精神和行为特征之间的关系，以提高检测能力 与酒精使用结果相关的常见变种，并表征潜在的途径 基因变异起作用。这些已识别的遗传变异结果的生物信息学表征通过 生物信息学和分析(BIA)核心将有助于阐明潜在的生物风险途径。到时候我们会的 将这些多变量分析的结果应用于三个互补的纵向数据集，这三个数据集包括 以人群为基础和高危样本，以便(目标2a)：绘制与以下方面有关的行为表型图 在目标1中确定的青春期和成年初期的遗传风险得分；(目标2b)测试 特定于性别和种族/人种背景的风险途径；以及(目标2c)遗传风险适度测试 受关键环境因素影响。该项目将以多种方式与其他ARC组件对接： 基因发现分析的结果(目标1)将与模型生物结果和 BAI核心中的表达数据(项目1-3)，以创建精细化的多基因风险评分，以便在目标2中进行进一步研究。 项目5将使用双胞胎和流行病学样本来改进结构模型，以进一步表征 遗传影响对酒精相关结果的多变量性质，以迭代地告知和扩展 在目标1中进行的多变量分析。此外，在目标1中确定的遗传变异可以被推进到 通过啮齿动物行为核心在动物模型中的进一步研究。

Project Summary – Project 4 Project 4 of the VCU Alcohol Research Center will utilize human data to accomplish two complementary goals: (1) advancing discovery of genes involved in alcohol-related outcomes using new multivariate genomic techniques, and (2) characterizing 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 represent critical steps in using genetic data to improve prevention, intervention, and treatment for alcohol use disorders (AUDs), and will lay the foundation as we move into an era of personalized medicine. Human gene identification efforts for alcohol use disorders lag behind other areas of psychiatry, in part due to constrained sample sizes of available AUD cases. However, recent meta-analyses of consumption and AUD reveal significant genetic correlations with numerous other psychiatric and behavioral traits, as well as social and demographic outcomes, and other biomedical phenotypes. Project 4 will (Aim 1) apply new multivariate genetic methods to capitalize on genetic sharing between alcohol use phenotypes and other psychiatric and behavioral traits in order to boost power to detect common variants associated with alcohol use outcomes, and to characterize the latent pathways by which genetic variants operate. Bioinformatic characterization of these identified genetic variant results through the Bioinformatics and Analytics (BIA) core will help elucidate underlying biological risk pathways. We will then apply results from these multivariate analyses to three complementary longitudinal datasets, consisting of both population-based and high-risk samples, 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. The project will interface with the other ARC components in multiple ways: results from the gene discovery analyses (Aim 1) will be integrated with model organism results and expression data (Projects 1-3) in the BAI Core to create refined polygenic risk scores for further study in Aim 2. Project 5 will refine structural models using twin and epidemiological samples to further characterize the multivariate nature of genetic influences on alcohol-related outcomes, to iteratively inform and extend the multivariate analyses performed in Aim 1. Further, the genetic variants identified in Aim 1 can be advanced for further study in animal models via the Rodent Behavior Core.