Neurogenetic Pathways to Drug Use in Young Adults

描述(申请人提供)：目前申请的主要目的是测试一种新的模型，即奖励和威胁相关神经回路的相对反应性如何与生活压力相互作用，以预测大量青少年和年轻人的药物使用。该应用程序还旨在识别代表预测这些相互作用的关键神经调节途径中的可变性的基因图谱。为了解决这些具体目标，该应用程序将收集以下指标：1)作为药物使用和滥用风险因素的核心行为过程；2)支持威胁和奖励反应以及行为控制的大脑回路；3)应激生活事件的经历；4)对600名18-22岁本科生的DNA序列变异。所有指标都将利用杜克大学神经遗传学研究现有的广泛研究基础设施进行收集。对个体差异进行建模的创新分析策略将应用于这些数据，以确定调节危险行为变异性的行为、神经生物学、环境和遗传机制。我们的发现对于告知药物使用、滥用和依赖的发展轨迹的预测性效用将通过联合研究进行测试。这些研究正在收集社区样本以及高危患者和个人(例如，低SES、阳性家族史)的纵向样本中的重叠措施。数据联合还将提供复制数据集和/或额外的能力，用于测试神经、遗传和环境变异与精神病理学的出现之间的新关联。此外，现有的与使用人类行为和疾病动物模型的研究人员以及那些进行流行病学基因-环境相互作用研究的研究人员的合作将促进基于我们的发现的独特的翻译项目。这些合作将有助于确定详细的分子机制和更广泛的临床相关性。总的来说，拟议的研究将揭示预测精神病理学的机制和途径，重点是药物使用和向滥用的过渡，这代表了NIDA支持的当前研究的主要主题，并与研究领域标准(RDoC)的重点一致，RDoC强调根据可观察的行为和神经生物学措施对精神病理学进行分类。

DESCRIPTION (provided by applicant): The primary aim of the current application is to test a novel model of how the relative responsiveness of reward- and threat-related neural circuits interact with life stress to predict drug use in a large cohort of adolescents and young adults. The application also aims to identify genetic profiles representing variability in key neuromodulatory pathways that predict these interactions. To address these specific aims the application will collect measures of: 1) core behavioral processes that serve as risk factors for drug use and abuse, 2) brain circuits supporting threat and reward responsiveness as well as behavioral control, 3) the experience of stressful life events and 4) DNA sequence variation in 600 18-22 year old undergraduates. All measures will be collected using the existing extensive research infrastructure of the Duke Neurogenetics Study. Innovative analytic strategies for modeling individual differences will be applied to these data in the service of identifying behavioral, neurobiological, environmental and genetic mechanisms mediating variability in risk behaviors. The predictive utility of our findings for informing developmental trajectories of drug use, abuse, and dependence will be tested through federated studies. These studies are collecting overlapping measures in both community samples as well as longitudinal samples of patients and individuals at high risk (e.g., low SES, positive family history). Data federation wil also provide replication data sets and/or additional power for testing novel associations between neural, genetic, and environmental variation and the emergence of psychopathology. Furthermore, existing collaborations with investigators using animal models of human behavior and disease as well as those conducting epidemiological gene-environment interaction research will facilitate unique translational projects based on our findings. These collaborations will allo for identification of both detailed molecular mechanisms and broader clinical relevance. Collectively, the research proposed will reveal mechanisms and pathways that predict psychopathology with a focus on drug use and the transition to abuse, which represents a major thrust of current research supported by NIDA and is consistent with the Research Domain Criteria (RDoC) emphasis on classifying psychopathology based on dimensions of observable behavior and neurobiological measures.