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COVID-19 virtual patient cohort reveals immune mechanisms driving disease outcomes (preprint)
biorxiv; 2021.
Preprint
in English
| bioRxiv | ID: ppzbmed-10.1101.2021.01.05.425420
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 indicate 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 that was mediated by increased IL-6 and reduced type I IFN signalling. Together, these findings identify biomarkers driving the development of severe COVID-19 and support early interventions aimed at reducing inflammation.
Full text:
Available
Collection:
Preprints
Database:
bioRxiv
Main subject:
COVID-19
/
Inflammation
Language:
English
Year:
2021
Document Type:
Preprint
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