Baseline T cell signatures predict clinical outcomes of SARS-CoV infection

Even as the world is reeling under the COVID-19 pandemic and the unprecedented toll it has taken in terms of deaths, long-term health conditions, and economic turmoil, scientists from all over the world are frantically trying to find an effective way to control the spread of disease and treat those who are already affected. Many studies have shown that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection can cause a wide range of symptoms starting from asymptomatic to mild or severe disease in humans requiring mechanical ventilation in worst cases.

The lack of a complete understanding of the immune correlates of the clinical outcomes is a significant barrier to the development of vaccines and drugs that prevent or limit infection. One major roadblock to understanding the immune mechanisms is the lack of pre-infection samples from SARS-CoV-2 patients.

In a recent bioRxiv* preprint paper, researchers from the Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, OR, and Department of Global Health, University of Washington, Seattle, WA, discuss their study in mice that undergo detailed immunophenotyping before getting infected with SARS-CoV.

The team used genetically diverse mice from the Collaborative Cross infected with mouse-adapted SARS-CoV along with thorough pre-infection immunophenotyping to determine baseline immune correlates of severe clinical and virologic outcomes upon infection with SARS-CoV.

"The use of the mouse-adapted SARS-CoV MA15, while not the same as SARS-CoV-2, at the very least allowed us to perform proof-of-concept studies demonstrating that baseline T cell phenotypes can predict infection and disease outcomes following coronavirus infections, though future studies of both mice, as well as human samples using SARS-CoV-2, are required to validate our findings for COVID-19."

The team set out to determine if circulating baseline T cell signatures are linked to a lack of viral control and severity of disease upon SARS-CoV infection.

Circulating T cell signatures correlated with early viral control

The researchers found that SARS-CoV infection in mice leads to many different viral load trajectories and clinical outcomes. Interestingly, early control of the virus in the lung was associated with increased levels of activated CD4 and CD8 T cells and regulatory T cells prior to infection.

Circulating T cell phenotypes at steady state predicted protection from high titers and severe disease upon SARS-CoV MA15 infection. The tendency of T cells to express IFNg and IL17 over TNFa also correlated with early control of the virus. It was clear that a dysregulated, proinflammatory T cell signature at baseline was associated with severe disease upon viral infection.

Although human studies are crucial to validate these findings, according to the team, their study highlights the complexity of inflammation, which can be both protective and detrimental to the infected individual. They hypothesize that specific T cell immunophenotypes may play a crucial role in promoting rapid immunity and limiting immune-mediated damage upon SARS infection. Overall, the results of the study demonstrate that baseline T cell signatures can be predictors of early clinical and virologic outcomes upon SARS-coronavirus infection.

"It stands to reason that such an active innate-like T cell response would need to be subject to immunoregulation in order to limit activity and prevent excess collateral damage."

The authors also predict that bystander-activated T cells may be critical in the early innate immune response to SARS-CoV infection. However, as SARS-CoV-2 elicits more inflammatory responses compared to SARS, the immune correlates of disease and protection for SARS-CoV-2 may vary from those of SARS-CoV. Thus, more studies using mouse-adapted SARS-CoV-2 are critical to validate these results.

Human baseline immune predictors could help identify high-risk individuals

The COVID-19 pandemic has presented enormous challenges to healthcare systems worldwide, as healthcare workers put their own life at risk without adequate access to personal protective equipment (PPE) or a protective vaccine. While several candidate vaccines are undergoing expedited trials in various parts of the globe, it is evident that when new prevention or treatment strategies become available, there will not be enough supply for everyone in need. This emphasizes the need for a strategy to identify individuals at high risk of infection and severe disease outcomes so as to triage new drugs or vaccines as soon as they become available.

The identification of the baseline immune predictors in humans could help identify individuals at high risk of severe clinical outcomes upon SARS-CoV-2 infection, and thus allow them to benefit from the best clinical interventions available to mitigate infection and disease. The identification of immune correlates of clinical outcomes can also help guide vaccine and drug development efforts in the future.

*Important Notice

bioRxiv publishes preliminary scientific reports that are not peer-reviewed and, therefore, should not be regarded as conclusive, guide clinical practice/health-related behavior, or treated as established information.

Journal reference:
  • Baseline T cell immune phenotypes predict virologic and disease control upon SARS-CoV infection Jessica Graham, Jessica Swarts, Sarah R Leist, Alexandra Schafer, Vineet D Menachery, Lisa Gralinski, Sophia Jeng, Darla R Miller, Michael Mooney, Shannon McWeeney, Martin T. Ferris, Fernando Pardo-Manuel de Villena, Mark T. Heise, Ralph S. Baric, Jennifer M Lund bioRxiv 2020.09.21.306837; doi:
Susha Cheriyedath

Written by

Susha Cheriyedath

Susha has a Bachelor of Science (B.Sc.) degree in Chemistry and Master of Science (M.Sc) degree in Biochemistry from the University of Calicut, India. She always had a keen interest in medical and health science. As part of her masters degree, she specialized in Biochemistry, with an emphasis on Microbiology, Physiology, Biotechnology, and Nutrition. In her spare time, she loves to cook up a storm in the kitchen with her super-messy baking experiments.


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