Indexed metadata

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

Adrianne L. Jenner, Rosemary A. Aogo, Sofia Alfonso, Vivienne Crowe, Xiaoyan Deng, Amanda P. Smith, Penelope A. Morel, Courtney L. Davis, Amber M. Smith, Morgan Craig

Source record

Source: Crossref

Published: Jul 14, 2021

DOI: 10.1371/journal.ppat.1009753

Open original source ↗

Source 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.

Evidence graph

No public relationships recorded yet.

Integrity note: This page is a factual metadata record created by deterministic ingestion. It is not a claim that the work moves a mathematical frontier or has been independently verified.

COVID-19 virtual patient cohort suggests immune mechanisms driving disease outcomes — Mathematical Frontier Network