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

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dc.contributor.author
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.
dc.date.accessioned
2025-01-27T20:52:35Z
dc.date.available
2025-01-27T20:52:35Z
dc.date.issued
2021-11-26
dc.description.abstract - en
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.
dc.description.sponsorship
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.).
dc.identifier.doi
https://doi.org/10.1126/sciadv.abj5629
dc.identifier.issn
2375-2548
dc.identifier.pubmedID
34826237
dc.identifier.uri
https://open-science.canada.ca/handle/123456789/3367
dc.language.iso
en
dc.publisher - en
American Association for the Advancement of Science
dc.publisher - fr
American Association for the Advancement of Science
dc.rights - en
Creative Commons Attribution 4.0 International (CC BY 4.0)
dc.rights - fr
Creative Commons Attribution 4.0 International (CC BY 4.0)
dc.rights.openaccesslevel - en
Gold
dc.rights.openaccesslevel - fr
Or
dc.rights.uri - en
https://creativecommons.org/licenses/by/4.0/
dc.rights.uri - fr
https://creativecommons.org/licenses/by/4.0/deed.fr
dc.subject - en
Health
Coronavirus diseases
dc.subject - fr
Santé
Maladie à coronavirus
dc.subject.en - en
Health
Coronavirus diseases
dc.subject.fr - fr
Santé
Maladie à coronavirus
dc.title - en
Integrated immunovirological profiling validates plasma SARS-CoV-2 RNA as an early predictor of COVID-19 mortality
dc.type - en
Article
dc.type - fr
Article
local.article.journalissue
48
local.article.journaltitle - en
Science Advances
local.article.journalvolume
7
local.pagination
1-16
local.peerreview - en
Yes
local.peerreview - fr
Oui
local.requestdoi - en
No
local.requestdoi - fr
No
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