The Electronic Medical Records and Genomics (eMERGE) Network Phase III - Coordinating Center (U01)

As the COVID-19 pandemic emerged in early 2020 and rapidly spread across the US, an urgentneed developed to improve our current understanding of what factors increase infection risk,likelihood of severe illness, or poor outcomes. Early reports suggest genetics, personal healthhistory, socioeconomic factors, and one's environment increases risk of infection or differencesin outcomes, but little is known with high confidence. As there are currently no vaccinations orother preventative treatment, understanding clinical and genetic risk factors would immediatelyimprove our ability to manage the pandemic across populations and deliver precision care at thebedside. The Electronic Medical Records and Genomics (eMERGE) Network has the expertiseand resources to investigate the factors leading to increased COVID disease susceptibility byrapidly compiling data from electronic health records (EHRs) and mining records for gene anddisease associations. To perform this task well, the features of COVID disease course andcharacteristics of patients with COVID-19 and those who serve as controls must be preciselydefined ("ePhenotyped") across different record system. Our experience with phenotyping andimputing genomic and EHR data across large populations will enable us to quickly merge alarge number of COVID-19 patients for future genome and phenome wide association studies,polygenic risk assessments, and candidate gene studies. Our specific aims include first tocreate and deploy ePhenotypes for immediate research use establishing a COVID casedefinition, severity scale, and comorbidities with relation to outcomes. Secondly, we propose tocollect COVID EHR and genomic data centrally for future translational research. Theseresources will be beneficial to the scientific community, necessary to predict comprehensive riskof disease across the lifespan, and have the potential to impact downstream patient care.