Epidemiology and Genetics of Susceptibility to COVID-19 Infection

点击翻译按钮获取中文摘要

Infection by the acute respiratory syndrome coronavirus 2 (SARS-CoV-2) results in the infectious disease syndrome known as coronavirus disease 2019 (COVID-19). SARS-CoV-2 was originally described in late 2019 in Wuhan, China and has since spread throughout the world causing the 2019-2020 COVID-19 pandemic. While many individuals with SARS-CoV-2 infection may have mild or few symptoms, others have life threatening illness including severe pneumonia and multi-organ failure. As of May 12, 2020, there have been 1,342,594 cases and 80,820 deaths in the United States due to COVID-19 (https://cdc.gov). This approximately 6% death rate and lack of effective treatment or prevention measures illustrates the urgent need to understand factors associated with risk of severe COVID-19 disease. Irrespective of the actual rate of severe disease and death, it is clear that there will be enormous numbers of severe cases worldwide and management strategies are desperately needed.This is a multi-disciplinary collaborative project with the primary aim of understanding why some individuals with COVID-19 infection have mild clinical symptoms, while others have very severe disease resulting in respiratory failure, multi-organ failure, and death. The multiple aims of this project utilize the wide-ranging expertise of scientists in the Division of Cancer Epidemiology and Genetics, NCI1) Identify common and rare germline genetic variants associated with risk of COVID-19 infection and outcomes; 2) Identify other biomarkers associated with risk of COVID-19 infection and outcomes; 3) Characterize the contribution of co-morbid conditions, including current or prior cancer to COVID-19 infection and outcomes; 4) Conduct descriptive epidemiology studies aimed at understanding the population-level consequences of COVID-19 on public health and disease; 5) Identify optimal testing strategies to detect and monitor COVID-19 in populations; and 6) Deposit and share data as fast as possible to allow community analyses by bona-fide researchers who seek permission to analyze the data according to NIH data sharing precepts.