Baseline T cell immune phenotypes predict virologic and disease control upon SARS-CoV infection in Collaborative Cross mice

Jessica B. Graham, Jessica L. Swarts, Sarah R. Leist, Alexandra Schäfer, Vineet D. Menachery, Lisa E. Gralinski, Sophia Jeng, Darla R. Miller, Michael A. Mooney, Shannon K. McWeeney, Martin T. Ferris, Fernando Pardo Manuel de Villena, Mark T. Heise, Ralph S. Baric, Jennifer M. Lund

Research output: Contribution to journalArticlepeer-review

18 Scopus citations

Abstract

The COVID-19 pandemic has revealed that infection with SARS-CoV-2 can result in a wide range of clinical outcomes in humans. An incomplete understanding of immune correlates of protection represents a major barrier to the design of vaccines and therapeutic approaches to prevent infection or limit disease. This deficit is largely due to the lack of prospectively collected, pre-infection samples from individuals that go on to become infected with SARS-CoV-2. Here, we utilized data from genetically diverse Collaborative Cross (CC) mice infected with SARS-CoV to determine whether baseline T cell signatures are associated with a lack of viral control and severe disease upon infection. SARS-CoV infection of CC mice results in a variety of viral load trajectories and disease outcomes. Overall, a dysregulated, pro-inflammatory signature of circulating T cells at baseline was associated with severe disease upon infection. Our study serves as proof of concept that circulating T cell signatures at baseline can predict clinical and virologic outcomes upon SARS-CoV infection. Identification of basal immune predictors in humans could allow for identification of individuals at highest risk of severe clinical and virologic outcomes upon infection, who may thus most benefit from available clinical interventions to restrict infection and disease.

Original languageEnglish (US)
Article numbere1009287
JournalPLoS pathogens
Volume17
Issue number1
DOIs
StatePublished - Jan 29 2021

ASJC Scopus subject areas

  • Parasitology
  • Microbiology
  • Immunology
  • Molecular Biology
  • Genetics
  • Virology

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