The COVID-19 clinical syndrome caused by the SARS-CoV-2 virus has the potential to cause significant morbidity and mortality in previously healthy patients. A significant observation is that although this infection may result in a self-limiting upper respiratory infection or mild pneumonia in some patients, other patients experience progression of respiratory symptoms to requirement of intubation for mechanical respiratory support and death due to severe respiratory failure. This clinical observation strongly suggests that differences in host immunologic response are the determinative factor in clinical outcome. We hypothesize that the proposed systems immunology, biostatistical and computational modeling approaches, coupled with detailed clinical phenotype of hospitalized COVID-19 patients will provide a new framework to interpret the interplay between SARS-CoV-2 virus and the host, and the relationship with clinical outcome. Project 1 will assess the frequency and function of SARS-CoV-2 virus antigen specific T cells and evaluate their breadth and clonality of their TCR repertoire with clinical outcome. Project 2 will determine epigenetic signatures of the immune response to the SARS-CoV-2 virus across short, middle and long-term times and identify DNA methylation- based markers of anti-viral immunity and clinical outcome. With this approach, we will create a unique resource of highly annotated longitudinal data on SARS-CoV-2 virus infection, which will enable the development of novel diagnostic strategies and therapeutics to treat or prevent SARS-CoV-2 virus infection.
Characterization of the immune response to SARS-CoV-2 virus using a set of high-throughput CORE technologies, epigenetics, immune function assays and novel statistical and computational approaches will permit us to advance the field by describing immunologic characteristics that are associated with COVID-19 disease. We will also determine immune correlates of COVID-19 disease severity as reflected by measures of critical illness.
