COVID-19 Variant Network – Implementation of serological and molecular tools to inform COVID‑19 patient management
Severe acute respiratory syndrome coronavirus (SARS-CoV-2) is a novel virus that causes COronaVIrus Disease 2019 (COVID-19). There is considerable variability in symptom severity and outcomes among patients infected by SARS-CoV-2. Linking genome and viral sequencing information to antibody (immune) response and other biological information (sex, age, ancestry, symptom severity, comorbidities, and outcome) may identify characteristics of patients that are associated with poor and favourable outcomes. This study will address three aims. Aim 1: Identify the characteristics of the antibody response that result in maintained immune response and better patient outcomes. Aim 2: Determine impact of genetic differences on COVID‑19 infection severity and immune response. Aim 3: Determine impact of different viral strains on antibody response and patient outcomes. Patients with COVID‑19 will be recruited from Sinai Health System, University Health Network, Baycrest Health Sciences and William Osler Hospital System. Patients seen in the emergency department with mild symptoms as well as hospital in-patients with more severe symptoms will be consented. Blood samples will be collected when patients are in hospital and 6 months and 1 year after COVID‑19 diagnosis. Neutralizing antibody levels will be measured at all time points. Patient and viral genomes will be sequenced. Statistical analysis will be used to test for associations between antibody levels, genetic variation, viral genome variation, and patients’ characteristics including age, sex, ancestry, comorbidities, and symptom severity. This study will link serological, genomic and patient characteristics to provide a comprehensive understanding of factors that contribute to variability in clinical symptoms and outcomes among COVID‑19 patients. Evidence from this study will determine if immune response, viral strain and genome sequencing are effective for the diagnosis, prognosis and management of patients with COVID-19.
