Plasma SARS‐CoV‐2 RNA elimination and RAGE kinetics distinguish COVID‐19 severity

Author:

Deng Xiaoyan12ORCID,Gantner Pierre34,Forestell Julia1,Pagliuzza Amélie34,Brunet‐Ratnasingham Elsa34,Durand Madeleine3,Kaufmann Daniel E3567,Chomont Nicolas34,Craig Morgan12

Affiliation:

1. Research Centre of the Centre Hospitalier Universitaire Sainte‐Justine Montréal QC Canada

2. Département de mathématiques et de statistique Université de Montréal Montréal QC Canada

3. Research Centre of the Centre Hospitalier de l'Université de Montréal (CRCHUM) Montréal QC Canada

4. Département de Microbiologie, Infectiologie et Immunologie Université de Montréal Montréal QC Canada

5. Centre hospitalier de l'Université de Montréal (CHUM) Montréal QC Canada

6. Département de Médecine Université de Montréal Montréal QC Canada

7. Division of Infectious Diseases, Department of Medicine University Hospital and University of Lausanne Lausanne Switzerland

Abstract

AbstractObjectivesIdentifying biomarkers causing differential SARS‐CoV‐2 infection kinetics associated with severe COVID‐19 is fundamental for effective diagnostics and therapeutic planning.MethodsIn this work, we applied mathematical modelling to investigate the relationships between patient characteristics, plasma SARS‐CoV‐2 RNA dynamics and COVID‐19 severity. Using a straightforward mathematical model of within‐host viral kinetics, we estimated key model parameters from serial plasma viral RNA (vRNA) samples from 256 hospitalised COVID‐19+ patients.ResultsOur model predicted that clearance rates distinguish key differences in plasma vRNA kinetics and severe COVID‐19. Moreover, our analyses revealed a strong correlation between plasma vRNA kinetics and plasma receptor for advanced glycation end products (RAGE) concentrations (a plasma biomarker of lung damage), collected in parallel to plasma vRNA from patients in our cohort, suggesting that RAGE can substitute for viral plasma shedding dynamics to prospectively classify seriously ill patients.ConclusionOverall, our study identifies factors of COVID‐19 severity, supports interventions to accelerate viral clearance and underlines the importance of mathematical modelling to better understand COVID‐19.

Funder

Canadian Institutes of Health Research

Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada

Génome Québec

Public Health Agency of Canada

Université de Montréal

Publisher

Wiley

Subject

General Nursing,Immunology,Immunology and Allergy

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