Evidence map›Paper›PMID 41832213›Full record

ArticleCommunications medicine2026

Unbiased characterization of COVID-19 endotypes leads to prognostication of high-risk individuals using routine blood tests.

William Ma, Antoine Soulé, Catherine Allard, Madeleine Durand, Karine Tremblay, Simon Rousseau, Amin Emad

Abstract read
In one paragraph

Article in Communications medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

William Ma *Department of Electrical and Computer Engineering, McGill University, Montréal, QC, Canada.ORCID http://orcid.org/0000-0002-7110-4865
Antoine Soulé *Department of Electrical and Computer Engineering, McGill University, Montréal, QC, Canada.ORCID http://orcid.org/0000-0003-4810-4821
Catherine AllardStatistical department, Centre de recherche du Centre hospitalier universitaire de Sherbrooke (CRCHUS), Sherbrooke, Canada.ORCID http://orcid.org/0000-0002-8829-4984
Madeleine DurandCentre de Recherche du centre hospitalier de l'Université de Montréal (CRCHUM), Montréal, QC, Canada.
Karine TremblayPharmacology-physiology Department, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Saguenay, QC, Canada. karine.tremblay@usherbrooke.ca.
Simon RousseauThe Meakins-Christie Laboratories at the Research Institute of the McGill University Heath Centre Research Institute, & Department of Medicine, Faculty of Medicine, McGill University, Montréal, QC, Canada. simon.rousseau@mcgill.ca.ORCID http://orcid.org/0000-0002-8773-575X
Amin EmadDepartment of Electrical and Computer Engineering, McGill University, Montréal, QC, Canada. amin.emad@mcgill.ca.ORCID http://orcid.org/0000-0002-5108-4887

Funding

Fonds de Recherche du Québec - Santé (Fonds de la recherche en sante du Quebec) CMDO initiative inter-centre
6 · The paper itself

Abstract

backgroundOnly a subset of individuals infected with SARS‑CoV‑2 develop severe COVID‑19. Improved tools for early diagnosis and prognostication are needed. We hypothesized that unsupervised analysis of detailed circulating proteomes could reveal biologically meaningful patient endotypes and help identify individuals at elevated risk of severe outcomes.

methodsWe performed unsupervised stratification of the circulating proteome in 731 SARS‑CoV‑2 PCR‑positive participants from the Biobanque québécoise de la COVID‑19 (BQC19), representing a range of disease severities. We also developed a prognostic model based solely on clinical laboratory measurements and applied it to 903 patients recruited across early pandemic waves (2020-2022) to generalize identified endotypes.

resultsSix proteomic endotypes (EPs) emerged. Endotype EP6 showed the highest frequencies of ICU admission, ARDS, and mortality. EP6 was marked by elevated C‑reactive protein, D‑dimer, interleukin‑6, ferritin, soluble fms‑like tyrosine kinase‑1, increased neutrophils, and reduced lymphocyte counts. SHC4 emerged as a protein quantitative trait locus associated with EP6. Among EP6 patients requiring mechanical ventilation, we observed alterations in lipoprotein metabolism, and alpha‑L‑iduronidase levels inversely correlated with duration of ventilation.

conclusionsUnsupervised proteomic analysis identified biologically coherent endotypes that advance understanding of acute lung injury in COVID‑19 and support improved diagnostic and prognostic strategies.

Identifiers

PMID41832213
PMCPMC13133271

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.