Title

COVID-19 virtual patient cohort suggests immune mechanisms driving disease outcomes

Department(s)

Natural Science

Document Type

Article

Publication Date

7-1-2021

Abstract

To understand the diversity of immune responses to SARS-CoV-2 and distinguish features that predispose individuals to severe COVID-19, we developed a mechanistic, within-host mathematical model and virtual patient cohort. Our results suggest that virtual patients with low production rates of infected cell derived IFN subsequently experienced highly inflammatory disease phenotypes, compared to those with early and robust IFN responses. In these in silico patients, the maximum concentration of IL-6 was also a major predictor of CD8+ T cell depletion. Our analyses predicted that individuals with severe COVID-19 also have accelerated monocyte-to-macrophage differentiation mediated by increased IL-6 and reduced type I IFN signalling. Together, these findings suggest biomarkers driving the development of severe COVID-19 and support early interventions aimed at reducing inflammation.

Publication Title

PLoS Pathogens

ISSN

15537366

E-ISSN

15537374

Volume

17

Issue

7

DOI

10.1371/journal.ppat.1009753

PubMed ID

34260666

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