EHR Phenotyping and Genomics of Opioid Addiction (Project 1)

项目总结/摘要 药物过量是美国与伤害有关的死亡的主要原因， 美国人正在与某种形式的阿片类药物成瘾（OA）作斗争。值得注意的是，许多患者 OA患者首次使用阿片类药物治疗急性和慢性疼痛。保健 系统也受到阿片类药物流行的严重影响，与阿片类药物相关的住院治疗增加 增加了150%，阿片类药物相关治疗的急诊室就诊次数在过去20至30年间翻了一番。 年因此，使用来自现有卫生系统记录的处方和临床数据， 这是一个提高我们对阿片类药物使用和滥用的认识的机会。几个纵向卫生系统 数百万患者的数据也创建了生物银行，以促进基于电子健康记录（EHR）的 基因组研究和基因组医学的实施。2007年，国家人类基因组 研究所组织了电子病历和基因组学（eMERGE）网络， 医疗疾病的EHR算法，并在2018年扩展到包括精神疾病 （PsycheMERGE）.然而，到目前为止，基于EHR的风险预测和基因组学尚未得到广泛应用。 用于药物滥用研究有证据表明，物质使用障碍是高度 遗传，尽管潜在的遗传风险因素仍然未知。在项目1中，我们将利用两个 强大的卫生系统生物库，使用处方记录和临床 超过500万人的诊断。 我们的目标是（1）验证和协调多种疾病的病例和对照表型，（2） 阿片类药物使用表型的全基因组关联研究（GWAS）和OA的最大GWAS （3）研究阿片类药物使用患者的基因组学和大脑结构之间的相互作用。 这些目标的成功完成将是证明电子健康记录实用性的一个重大进展 资源，以促进我们对OA的理解，并将建立一个多站点阿片类药物研究网络， 不断的科学发现。将项目1整合到集成组学中心的更广泛背景中， 加速阿片类药物成瘾的神经生物学理解（ICAN）创造了多组学协同作用， 扩展实现这些目标的影响，将它们直接与差异基因调控联系起来（项目2） 啮齿类动物模型中关键发现的实验跟踪（项目3），以及基因网络 识别（项目4）。这样，其他ICAN项目将加强对项目1结果的解释， 项目1 GWAS和成像结果将为扩展其他ICAN项目提供机会， 共同实现我们的目标，以确定生物学上有意义的驱动因素OA。

PROJECT SUMMARY/ABSTRACT Drug overdose is the leading cause of injury-related death in the United States, and more than 2 million people in the United States are struggling with some form of opioid addiction (OA). Notably, many patients with OA are first introduced to opioids with a prescription for treatment of acute and chronic pain. Health care systems are also significantly impacted by the opioid epidemic, with opioid-related hospitalizations increasing by 150% and emergency department visits for opioid-related treatment doubling over the past 20 to 30 years. Thus, the use of prescription and clinical data from existing health system records offers a powerful opportunity to improve our understanding of opioid use and abuse. Several health systems with longitudinal data on millions of patients have also created biobanks to facilitate electronic health record (EHR)-based genomic research and implementation of genomic medicine. In 2007, the National Human Genome Research Institute organized the Electronic Medical Records and Genomics (eMERGE) network to develop EHR algorithms for medical disorders, and this was expanded in 2018 to include psychiatric disorders (PsycheMERGE). To date, however, EHR-based risk prediction and genomics have not been widely leveraged for substance abuse research. Evidence suggests that substance use disorders are highly heritable, although the underlying genetic risk factors remain unknown. In Project 1, we will leverage two powerful health system biobanks to develop EHR opioid phenotypes using prescription records and clinical diagnoses on more than 5 million people. We aim to (1) validate and harmonize case and control phenotypes across multiple disorders, (2) complete genome-wide association studies (GWAS) of opioid use phenotypes and the largest GWAS of OA to date, and (3) examine the interaction between genomics and brain structure in opioid-using patients. Successful completion of these aims will represent a major advance in demonstrating the utility of EHR resources for furthering our understanding of OA and will build a multi-site opioid research network for continued scientific discovery. Integrating Project 1 in the broader context of the Integrative Omics Center for Accelerating Neurobiological Understanding of Opioid Addiction (ICAN) creates multi-omic synergy that extends the impact of achieving these aims, linking them directly to differential gene regulation (Project 2) and experimental follow-up of key findings in rodent models (Project 3), as well as gene networks identification (Project 4). In this way, other ICAN Projects will enhance interpretation of Project 1 findings, and Project 1 GWAS and imaging results will provide opportunities to extend the other ICAN Projects, collectively achieving our goal to identify biologically meaningful drivers of OA.