EHR Phenotyping and Genomics of Opioid Addiction (Project 1)

阿片类药物成瘾的 EHR 表型分析和基因组学（项目 1）

基本信息

批准号：
10493705
负责人：
Vanessa Troiani
金额：
$ 47.36万
依托单位：
RESEARCH TRIANGLE INSTITUTE
依托单位国家：
美国
项目类别：
财政年份：
2022
资助国家：
美国
起止时间：
2022-09-15 至 2027-05-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10493705
关键词：
Acute Pain Algorithms Anatomy Autopsy Bioinformatics Brain Brain imaging Brain region Classification Clinical Clinical Data Code Computerized Medical Record Data Data Collection Data Sources Diagnostic Disease Documentation Dose Drug usage Electronic Health Record Electronic Medical Records and Genomics Network Emergency department visit Equation Face Future Gene Expression Gene Expression Regulation Genes Genetic Genetic study Genomic medicine Genomics Genotype Goals Health system Healthcare Systems Heritability Heterogeneity Hospitalization Human Image Link Magnetic Resonance Imaging Measurement Measures Mediator of activation protein Medical Mental disorders Methods Modeling National Human Genome Research Institute Neurobiology Opiate Addiction Opioid Overdose Pathway Analysis Patient imaging Patients Pattern Persons Pharmaceutical Preparations Phenotype Publishing Receptor Gene Recording of previous events Records Research Resources Risk Risk Factors Rodent Model Sampling Series Site Structure Substance Use Disorder Substance abuse problem United States Validation Variant alcohol misuse base biobank brain behavior brain magnetic resonance imaging brain volume case control chronic pain cigarette smoking clinical care clinical diagnosis cohort experimental study follow-up gene network genetic architecture genetic risk factor genome wide association study high dimensionality improved in silico injury-related death insight learning algorithm morphometry mu opioid receptors multiple data types multiple omics novel novel strategies opioid abuse opioid epidemic opioid use psychiatric comorbidity psychogenetics radiological imaging rare variant risk prediction risk variant sex statistics synergism tool unsupervised learning

项目摘要

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.

项目摘要/摘要药物过量是美国与伤害有关的主要原因，超过200万美国的人们正在为某种形式的阿片类药物成瘾（OA）苦苦挣扎。值得注意的是，许多患者首先将OA引入阿片类药物，并带有用于治疗急性和慢性疼痛的处方。卫生保健阿片类药物的流行也会显着影响系统，阿片类药物相关的住院增加在过去的20至30年中，急诊科进行了150％的急诊务访问，对阿片类药物相关的治疗增加了一倍年。因此，从现有卫生系统记录中使用处方和临床数据提供了强大的有机会提高我们对阿片类药物使用和滥用的理解。纵向的几个卫生系统数百万患者的数据还创建了生物库，以促进电子健康记录（EHR）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机构组织了电子病历和基因组学（Emerge）网络来开发 EHR医疗疾病算法，并在2018年扩大了精神疾病（Psychemerge）。但是，迄今为止，基于EHR的风险预测和基因组学尚未广泛利用滥用药物研究。有证据表明，药物使用障碍很高尽管基本的遗传危险因素仍然未知，但可遗传。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控制表型，（2）阿片类药物使用表型和OA的最大GWA的完整全基因组关联研究（GWAS）迄今为止，（3）检查阿片类药物的患者基因组学与大脑结构之间的相互作用。这些目标的成功完成将代表证明EHR实用性的重大进步用于进一步了解OA的资源，并将建立一个多站点的阿片类药物研究网络持续的科学发现。集成项目1在综合法的更广泛背景下加速对阿片类药物成瘾（ICAN）的神经生物学理解创造了多摩变协同作用扩展了实现这些目标的影响，将它们直接与差异基因调节联系起来（项目2）以及啮齿动物模型（项目3）和基因网络中关键发现的实验随访识别（项目4）。这样，其他ICAN项目将增强对项目1的发现的解释，项目1 GWAS和成像结果将提供机会扩展其他ICAN项目，共同实现我们的目标，以确定OA的生物学有意义的驱动因素。