EHR Phenotyping and Genomics of Opioid Addiction (Project 1)

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.