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

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

doi:10.1371/journal.ppat.1009287

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.

Highlights

The SARS-CoV-2 pandemic has led to a massive number of infections worldwide, with an unprecedented combined toll in terms of mortality, long-term health conditions, and economic turmoil [1]
We have previously shown that the Collaborative Cross (CC) is a superior model for the vast diversity in T cell phenotypes present in the human population [27], and used a screen of F1 mice derived from CC crosses (CC recombinant intercross, CC-RIX) infected with three different RNA viruses (H1N1 influenza A virus, SARS-CoV, and West Nile virus) to reveal novel baseline immune correlates that are associated with protection from death upon infection from all of these three viruses [28]
Infection of CC-RIX mice with SARS-CoV MA15 resulted in wide range of average lung viral loads at 2 days postinfection, ranging from below the limit of detection to 4.75x107 PFU (Fig 1C)

Summary

Introduction

The SARS-CoV-2 pandemic has led to a massive number of infections worldwide, with an unprecedented combined toll in terms of mortality, long-term health conditions, and economic turmoil [1]. While large-scale efforts to develop protective vaccines are underway, the human immune response to natural infection and identification of immune correlates of disease outcome and protection is still in process These efforts are likely to help guide such vaccine efforts, as an understanding of the natural immune correlates of protection from disease could assist in the rational design of prophylactic or therapeutic vaccines against SARS-CoV-2, as well as potential immunotherapeutic strategies. Some of the first studies of the human immune response to SARS-CoV-2 infection have examined changes in immune cell populations in peripheral blood from patients with severe disease as compared to healthy controls. Because most studies have been conducted after individuals had been infected with SARS-CoV-2, it is unclear if the identified immune signatures are predictive of severe disease or a manifestation of severe disease

Objectives

Methods

Results

Conclusion