Some COVID-19 patients fare well, experiencing asymptomatic or mild disease, while up to 20% of patients have severe symptoms that can be fatal. Recent studies reveal elevated inflammatory cytokines and a reduced number of T cells in patients with severe disease, indicating that variation in immune responses may underlie differences in disease outcomes. However, features of protective versus pathologic immune responses to SARS- CoV-2 are not well understood. Furthermore, children tend to experience milder symptoms, while elderly individuals are more susceptible to severe disease, but it is not known if this is a function of age-associated differences in immune responses.
In Aim 1, we propose to carry out paired single-cell transcriptomics, proteomics, and TCR repertoire sequencing of longitudinal blood samples from COVID-19 patients of different ages and disease severities in order to comprehensively profile the trajectory of immune responses to SARS- CoV-2 and identify candidate immune signatures that correlate with disease severity and age. Candidate signatures will be tested and refined in a larger patient cohort. Current vaccine efforts are focused on eliciting neutralizing antibodies against SARS-CoV-2. CD4+ T-cell responses are required to activate B cells to produce neutralizing antibodies and to support differentiation of CD8+ T cells, which can promote viral clearance and maintain immunologic memory. However, viral epitopes that activate protective T-cell responses remain unknown.
In Aim 2, we will activate T cells from the longitudinal patient samples used for single-cell profiling in Aim 1 with ?megapools? of overlapping peptides, spanning individual SARS-CoV-2 antigens. Activated T cells will be subjected to single-cell multi-omics analysis, allowing us to identify TCR sequences of clones that respond to each viral protein. Retrospective analysis of datasets from Aim 1 will enable us to follow the natural progression of these individual clones to evaluate frequencies and differentiation over the course of disease. Using these data, we will determine which viral antigens activate specific T-cell clones during effector and memory phases that correlate with favorable outcomes at each age, informing vaccine design. The increased incidence in autoimmune syndromes, such as the Kawasaki-like disease reported in pediatric patients, suggests that SARS- CoV-2 may induce autoimmunity; conversely, patients with autoimmune syndromes may be more susceptible to severe disease due to immune dysregulation.
In Aim 3, we will explore both possibilities. Specifically, we will retrospectively determine if autoimmunity predisposes patients to severe disease and if autoimmune patients have more inflammatory T cell responses to SARS-CoV-2 antigens. We will also evaluate whether autoantigens with high sequence similarity to SARS-CoV-2 peptides activate a higher frequency of T cells in COVID-19 patients versus uninfected controls, and we will determine if COVID-19 patients develop autoantibodies. These studies will identify specific immune correlates of disease severity at each age to stratify patients into risk groups, inform vaccine design, and test links between autoimmunity and COVID-19 for informed clinical care.
Individual variation in immune responses to infection with SARS-CoV-2, the b-coronavirus causing the current COVID-19 pandemic, likely accounts for the wide spectrum of patient disease severities, ranging from asymptomatic/mild disease to severe/critical disease involving inflammatory responses that can be fatal. Here, we will perform comprehensive single-cell multi-omics evaluation of PBMCs from pediatric through geriatric COVID-19 patients to identify specific immune correlates of disease severity at each age and to identify SARS- CoV-2 antigens that elicit protective T-cell responses to inform vaccine design. Additionally, as autoimmune/ autoinflammatory syndromes are increasingly recognized as clinical complications of COVID-19, we will investigate links between SARS-CoV-2 infection and autoimmunity in children and adults.
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