Varieties of Impulsivity in Opiate and Stimulant Users

项目摘要 冲动已成为发展和发展的主要病因风险因素之一。 成瘾障碍的维持。然而，冲动和上瘾都是高度不同的，这 阻碍了理解两者之间联系的进展。为了解决这种异质性，我们有 在保加利亚开发了一个成瘾研究计划，保加利亚是欧洲主要的合成药物生产中心 由于其战略地理位置，苯丙胺类兴奋剂和海洛因贩运的主要过境国 在巴尔干贩毒路线上的立场。通过与保加利亚同事长达17年的合作，我们已经 主要依靠单一物质依赖(“纯”)海洛因和苯丙胺的稀有人群， 许多人长期禁欲。在父DA021421研究中，我们测试了&gt；800名参与者 临床、个性和神经认知任务冲动性及相关的综合评估组合 外化和内化表型。我们用烟幕阵列对参与者进行了基因分型，并登记了 兄弟姐妹对鸦片和兴奋剂上瘾意见不一。我们结合了理论驱动(例如认知建模、联合 建模)和数据驱动(例如，机器学习(ML))计算方法，这证明了 阿片类药物和刺激性药物成瘾的信息丰富，显示出明显的多变量风险特征 准确度。来自母公司的研究结果为我们的综合多学科提供了重要的信息 框架(Vassileva&Conrod，2019年)，它强调了不同维度的冲动潜在的 为不同类型的成瘾提供临床评估和干预发展的信息。冲动也是一个重要因素 突出地在神经科学为基础的启发式框架的成瘾的神经临床评估(ANA； Kwako等人，2016)，它提出成功的成瘾治疗必须适应异质性 和不同的致病机制，通过进行多维度的评估 关注冲动和强迫症的三个神经功能领域：执行功能(EF)、激励 显著(IS)和消极情绪性(NE)。然而，由于ANA框架主要基于 在酒精使用障碍中的发现，还不能很好地理解这些区域如何推广到其他SUD， 如鸦片类药物和兴奋剂使用障碍。目前的竞争续签申请旨在解决这一问题 与以下具体目标的关键差距：目标1：确定关键个性、神经行为、多基因和 ANA框架下的阿片剂和兴奋剂成瘾的计算标记物，使用全面的 在母公司DA021421中开发的评估单元和计算方法，有250名参与者(100 阿片使用障碍者，兴奋剂使用障碍者100人，健康对照组50人)；目标2：识别大脑 阿片类和兴奋剂成瘾中3个ANA结构域(EF、IS、NE)的特征；探索目标3：结合 来自AIMS 1和AIMS 2的数据，以确定基于ANA领域中牵连的神经回路的成瘾生物类型。

Project Summary Impulsivity has gained prominence as one of the cardinal etiological risk factors for the development and maintenance of addictive disorders. However, both impulsivity and addiction are highly heterogeneous, which has hampered progress in understanding the link between the two. To address this heterogeneity, we have developed a program of addiction research in Bulgaria, a major European center for production of synthetic amphetamine-type stimulants and a key transit country for heroin trafficking, due to its strategic geographical position on the Balkan Drug Route. Through our 17-yearlong collaboration with Bulgarian colleagues, we have accessed rare populations of predominantly monosubstance-dependent (‘pure’) heroin and amphetamine users, many in protracted abstinence. In the parent DA021421 study, we have tested >800 participants with a comprehensive assessment battery of clinical, personality, and neurocognitive tasks of impulsivity and related externalizing and internalizing phenotypes. We genotyped participants with the Smokescreen array and enrolled siblings discordant for opiate and stimulant addictions. We combined theory-driven (e.g. cognitive modeling, joint modeling) with data-driven (e.g. machine learning (ML)) computational approaches, which proved particularly informative and revealed distinct multivariate risk profiles characterizing opiate and stimulant addictions with high degree of accuracy. Findings from the parent study significantly informed our integrative multidisciplinary framework (Vassileva & Conrod, 2019), which highlights the potential for distinct dimensions of impulsivity to inform clinical assessment and intervention development for different types of addictions. Impulsivity also figures prominently in the neuroscience-based heuristic framework for the neuroclinical assessment of addictions (ANA; Kwako et al., 2016), which proposes that successful addiction treatment must accommodate the heterogeneity and different etiological mechanisms implicated in addictions, by performing multidimensional assessments focusing on three neurofunctional domains of impulsivity and compulsivity: executive function (EF), incentive salience (IS), and negative emotionality (NE). However, because the ANA framework is based primarily on findings in alcohol use disorder, it is not well understood how these domains might generalize to other SUD, such as opiate and stimulant use disorders. The current competing renewal application aims to address this critical gap with the following specific aims: Aim 1: Identify key personality, neurobehavioral, polygenic, and computational markers of opiate and stimulant addiction following the ANA framework, using the comprehensive assessment battery and computational methods developed in the parent DA021421 with 250 participants (100 with opiate use disorder, 100 with stimulant use disorder, and 50 healthy controls); Aim 2: Identify the brain signatures of the 3 ANA domains (EF, IS, NE) in opiate and stimulant addictions; Exploratory Aim 3: Combine data from Aims 1 and 2 to identify addiction biotypes based on neurocircuitry implicated in the ANA domains.