Evidence map›Paper›PMID 42315886›Full record

ArticleScientific reports2026

Characterization of IgG N-glycan patterns in COVID-19, sepsis and healthy subjects.

Victoria Paredes-Orejudo, Yosra Helali, Axelle Bourez, Alexandre Rousseau, Pierre Van Antwerpen, Karim Zouaoui Boudjeltia, Michael Piagnerelli, Arnaud Marchant, Cédric Delporte

Abstract read
In one paragraph

Article in Scientific reports, 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

9 authors.

Victoria Paredes-Orejudo *RD3 Unit of Pharmacognosy, Bioanalysis and Drug Discovery, Faculty of Pharmacy, Université libre de Bruxelles, Campus Plaine, CP 205/5, Brussels, 1050, Belgium.
Yosra Helali *CPBL, Crop Production and biostimulation Laboratory, Ecole de Bioingénierie de Bruxelles, Faculté des sciences, Université libre de Bruxelles, Campus Plaine, Brussels, CP 245, 1050, Belgium.
Axelle BourezRD3 Unit of Pharmacognosy, Bioanalysis and Drug Discovery, Faculty of Pharmacy, Université libre de Bruxelles, Campus Plaine, CP 205/5, Brussels, 1050, Belgium.
Alexandre RousseauLaboratory of Experimental Medicine (ULB 222 Unit), CHU Charleroi-Chimay, Université libre de Bruxelles, Charleroi, Belgium.
Pierre Van AntwerpenRD3 Unit of Pharmacognosy, Bioanalysis and Drug Discovery, Faculty of Pharmacy, Université libre de Bruxelles, Campus Plaine, CP 205/5, Brussels, 1050, Belgium.
Karim Zouaoui BoudjeltiaLaboratory of Experimental Medicine (ULB 222 Unit), CHU Charleroi-Chimay, Université libre de Bruxelles, Charleroi, Belgium.
Michael PiagnerelliLaboratory of Experimental Medicine (ULB 222 Unit), CHU Charleroi-Chimay, Université libre de Bruxelles, Charleroi, Belgium.
Arnaud MarchantEuropean Plotkin Institute for Vaccinology, Université libre de Bruxelles, Campus Erasme, Brussels, 1070, Belgium.
Cédric DelporteRD3 Unit of Pharmacognosy, Bioanalysis and Drug Discovery, Faculty of Pharmacy, Université libre de Bruxelles, Campus Plaine, CP 205/5, Brussels, 1050, Belgium. cedric.delporte@ulb.be.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Patients with severe infectious diseases may require admission to intensive care units (ICUs) when the infection progresses to severe forms, as observed in sepsis or, more recently, in COVID-19. Despite advances in critical care, the risk of progression toward severe or fatal outcomes remains difficult to predict, highlighting the need for reliable prognostic biomarkers. Immunoglobulin G (IgG) N-glycosylation has emerged as a key modulator of immune responses and may represent a valuable biomarker for assessing disease severity. In this study, we investigated the IgG N-glycans profiles to evaluate their potential association with clinical outcome in critically ill patients with sepsis or COVID-19. Serum IgG N-glycans were characterized using online hydrophilic interaction liquid chromatography (HILIC) solid-phase extraction, followed by HILIC separation and fluorescence and mass spectrometry detection. The study cohort included healthy controls, ICU patients with sepsis or severe COVID-19, the latter being further stratified according to survival outcome. Distinct IgG N-glycosylation patterns and relative abundances of specific N-glycan structures in serum were associated with disease etiology (sepsis versus COVID-19) as well as with patient outcomes for COVID-19 group. These findings suggest that IgG glycosylation profiling may provide a promising approach for stratifying ICU patients according to their risk of developing severe or fatal diseases.

Indexed as

COVID-19Immunoglobulin GPolysaccharidesSepsisAdultAgedBiomarkersFemaleGlycosylationHumansIntensive Care UnitsMaleMiddle AgedSARS-CoV-2BiomarkersImmunoglobulin GPolysaccharides

Identifiers

PMID42315886
PMCPMC13550543

What OpenQuestion holds

Textmetadata
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.