Integrated immunovirological profiling validates plasma SARS-CoV-2 RNA as an early predictor of COVID-19 mortality

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DOI

https://doi.org/10.1126/sciadv.abj5629

Language of the publication
English
Date
2021-11-26
Type
Article
Author(s)
  • Brunet-Ratnasingham, Elsa
  • Anand, Sai Priya
  • Gantner, Pierre
  • Dyachenko, Alina
  • Moquin-Beaudry, Gaël
  • Brassard, Nathalie
  • Beaudoin-Bussières, Guillaume
  • Pagliuzza, Amélie
  • Gasser, Romain
  • Benlarbi, Mehdi
  • Point, Floriane
  • Prévost, Jérémie
  • Laumaea, Annemarie
  • Niessl, Julia
  • Nayrac, Manon
  • Sannier, Gérémy
  • Orban, Catherine
  • Messier-Peet, Marc
  • Butler-Laporte, Guillaume
  • Morrison, David R.
  • Zhou, Sirui
  • Nakanishi, Tomoko
  • Boutin, Marianne
  • Descôteaux-Dinelle, Jade
  • Gendron-Lepage, Gabrielle
  • Goyette, Guillaume
  • Bourassa, Catherine
  • Medjahed, Halima
  • Laurent, Laetitia
  • Rébillard, Rose-Marie
  • Richard, Jonathan
  • Dubé, Mathieu
  • Fromentin, Rémi
  • Arbour, Nathalie
  • Prat, Alexandre
  • Larochelle, Catherine
  • Durand, Madeleine
  • Richards, J. Brent
  • Chassé, Michaël
  • Tétreault, Martine
  • Chomont, Nicolas
  • Finzi, Andrés
  • Kaufmann, Daniel E.
Publisher
American Association for the Advancement of Science

Abstract

Despite advances in COVID-19 management, identifying patients evolving toward death remains challenging. To identify early predictors of mortality within 60 days of symptom onset (DSO), we performed immunovirological assessments on plasma from 279 individuals. On samples collected at DSO11 in a discovery cohort, high severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral RNA (vRNA), low receptor binding domain–specific immunoglobulin G and antibody-dependent cellular cytotoxicity, and elevated cytokines and tissue injury markers were strongly associated with mortality, including in patients on mechanical ventilation. A three-variable model of vRNA, with predefined adjustment by age and sex, robustly identified patients with fatal outcome (adjusted hazard ratio for log-transformed vRNA = 3.5). This model remained robust in independent validation and confirmation cohorts. Since plasma vRNA’s predictive accuracy was maintained at earlier time points, its quantitation can help us understand disease heterogeneity and identify patients who may benefit from new therapies.

Subject

  • Health,
  • Coronavirus diseases

Rights

Pagination

1-16

Peer review

Yes

Open access level

Gold

Identifiers

PubMed ID
34826237
ISSN
2375-2548

Article

Journal title
Science Advances
Journal volume
7
Journal issue
48

Sponsors

This work was supported by American Foundation for AIDS Research (amfAR) grant 110068-68-RGCV (to D.E.K., N.C., and A.F.); Canada’s COVID-19 Immunity Task Force (CITF), in collaboration with the Canadian Institutes of Health Research (CIHR) grant VR2-173203 (to D.E.K. and A.F.); CIHR grants 365825 and 409511 (to J.B.R.); Canada Foundation for Innovation (CFI): Exceptional Fund COVID-19 grant no. 41027 to A.F., D.E.K., and N.C.; CFI leader to J.B.R.; Ministère de l’Économie et de l’Innovation du Québec, Programme de soutien aux organismes de recherche et d’innovation (to A.F.); CRCHUM Foundation; Fonds de recherche Québec-Santé (FRQS) (BQC-19); Génome Québec (BQC-19); Public Health Agency of Canada (BQC-19); FRQS Merit Research Scholar Award (to D.E.K.); FRQS Salary Award (to N.C., M.Dur., M.C., J.B.R., C.L., and M.T.); FRQS Clinical Research Scholarship (to J.B.R.); Canada Research Chair (to A.F. and A.Pr.); COVID-19 excellence scholarship from the Université de Montréal (to E.B.-R.); CIHR fellowships (to S.P.A. and P.G.); Lady Davis Institute of the JGH (to J.B.R.); NIH Foundation (to J.B.R.); and Cancer Research UK (to J.B.R.).

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Communicable diseases

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