Assessing SARS-CoV-2 Variant Evolution in Patients

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SARS-CoV-2, the cause of the COVID-19 pandemic, emerged from Wuhan, China, and rapidly spread around the world. A feature of the pandemic has been the repeated emergence of SARS-CoV-2 clades and variants of concern, some of which have been shown to have enhanced transmissibility. Other aspects of these lineages, however, remain unclear. The vast majority of the 3.75 million deaths caused by SARS-CoV-2 are the result of severe pneumonia. In these patients, ongoing SARS-CoV-2 viral replication in the lungs leads to slowly progressing pulmonary injury and subsequent respiratory failure. Yet our understanding of the genetic evolution of SARS-CoV-2 in the lungs is limited because of difficulties sampling the pulmonary alveolar space and in linking viral samples to robust and comprehensive clinical data. In this regard, the Successful Clinical Response in Pneumonia Therapy (SCRIPT) Systems Biology Center provides the ideal infrastructure to collect deep-lung viral samples and corresponding immune response and clinical metadata from patients with COVID- 19. We propose to leverage the clinical and research infrastructure of SCRIPT to study SARS-CoV-2 variants and intra-host adaptation. We will expand SCRIPT to link patient phenotypes with virus genotypes. Our hypothesis is that SARS-CoV-2 clades influence the severity of COVID-19 pneumonia and that viral diversity evolves in the lungs of patients experiencing severe pneumonia. To test our hypotheses, we will perform the following specific aims: Aim 1. We will determine whether specific SARS-CoV-2 clades are associated with greater disease severity or altered host response. We will sequence SARS-CoV-2 isolates from a biobank of a general pool of COVID-19 patients at our institution and from BAL samples of intubated patients with severe COVID-19 pneumonia to establish their genotypes. Associations between specific SARS-CoV-2 clades and disease severity and outcomes in both populations will be sought. Aim 2. We will examine the evolution of intra-host SARS-CoV-2 viral sequence changes over time in the lungs of patients with severe COVID-19 pneumonia. In a subset of patients with prolonged respiratory failure, we will sequence viral isolates and examine the host immune response using longitudinally collected serial BAL samples. These data will be used to quantify viral dynamics in the lung, to map the intra-host emergence of viral quasi-species, to characterize the host immune responses elicited by these changes, and to correlate these features with the clinical conditions of the patients. Aim 3. We will generate a computational model that integrates SARS-CoV-2 clade genome information with clinical and host immune response features to predict the severity of COVID-19 infections. Viral clade data will be integrated with measures of the host immune response (BAL fluid flow cytometry and cytokine levels) and patient clinical metadata to develop a comprehensive model that predicts which patients will develop especially severe COVID-19 disease.