Saturday, September 7, 2024
9/7/2024
PROJECT SUMMARY Children infected with SARS-CoV-2 are frequently reported to have co-infection with other respiratory viruses, including respiratory syncytial virus, human rhinovirus/enterovirus, and parainfluenza virus. Respiratory virus co- infection may lead to more severe COVID-19 and worse clinical outcomes, but this is complicated by ascertainment biases in clinical testing algorithms that make co-detection of multiple respiratory pathogens more likely in the most at-risk and severely ill children. Severe COVID-19 outcomes have been previously linked to immune dysregulation following infection, but it is unknown how the host response to SARS-CoV-2 may be influenced by co-infection with another respiratory virus. Likewise, it is unclear what impact co-infection may have on intra-host viral dynamics, including viral load, time to clearance, and viral diversification, all of which may contribute to the evolution of new variants with enhanced immune evasion or antiviral resistance. We hypothesize that children with SARS-CoV-2 experience frequent respiratory virus co-infection, and that this co- infection is associated with more severe disease, increased inflammation and mucosal injury in the upper respiratory tract, and enhanced viral diversity due to increased persistence and viral load. We propose to test this hypothesis in three aims designed to: 1) assess the prevalence of SARS-CoV-2 and respiratory virus co- infection and its association with clinical outcome; 2) characterize the mucosal immune response to SARS-CoV- 2 and how it differs in response to viral co-infection; and 3) determine the influence of co-infection on viral intra- host dynamics and evolution. To achieve this goal, we will leverage our retrospective biobank of residual COVID- 19 diagnostic specimens from Lurie Children’s Hospital (n>6000 specimens collected since March 2020) as well as prospectively collected specimens spanning a total of 6 years. In Aim 1, we will use a combination of multiplex PCR and hybrid-capture sequencing to establish respiratory virus co-infection prevalence over time. Electronic medical record data will be used to examine associations between co-infection, clinical outcomes, and disease severity, adjusting for relevant demographic and clinical cofactors, including treatment, vaccination, and prior infection. In Aim 2, bulk transcriptomic sequencing, cytokine profiling, immune cell profiling, and single-cell RNA sequencing will be used to assess the mucosal immune response in co-infected individuals and controls. Host response data will be modeled in the context of the extracted demographic and clinical metadata to determine association with disease severity and outcomes. In Aim 3, viral whole genome sequencing and quantitative PCR will be used to assess viral load, intra-host quasispecies composition, and genetic diversity. Phylogenetic and phylodynamic models will be used to determine evolutionary rate and selection. Mutations in antiviral drug targets will be assessed for resistance potential. Taken together, these data will clarify the prevalence, clinical impact, and virus-host dynamics underlying SARS-CoV-2 and respiratory virus co-infection in children towards the development of evidence-based guidance to optimize diagnosis/treatment and minimize morbidity.
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