Evidence map›Paper›PMID 37342334›Full record

ArticleFrontiers in immunology2023

Fucosylated N-glycans as early biomarkers of COVID-19 severity.

Beatrix Paton, Pol Herrero, Joaquim Peraire, Antoni Del Pino, Silvia Chafino, Javier Martinez-Picado, Fréderic Gómez-Bertomeu, Anna Rull, Núria Canela, Manuel Suárez

Open access · goldAbstract read
In one paragraph

Article in Frontiers in immunology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
2.3field-weighted citation impact, top 12% of its field
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

8 citing papers in PubMed, 12 citations in OpenAlex.

  1. Glycan Fingerprint of Malignant Pleural Mesothelioma.International journal of molecular sciences · 2026
    Article
  2. Article
  3. Article
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  5. Review
  6. Review
  7. Article
  8. Total plasmaiScience · 2024
    Article
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

10 authors at 7 institutions in 1 country.

Beatrix PatonEurecat, Centre Tecnològic de Catalunya, Centre for Omic Sciences (Joint Unit Eurecat- Universitat Rovira i Virgili), Unique Scientific and Technical Infrastructure (ICTS), Reus, Spain.
Pol HerreroEurecat, Centre Tecnològic de Catalunya, Centre for Omic Sciences (Joint Unit Eurecat- Universitat Rovira i Virgili), Unique Scientific and Technical Infrastructure (ICTS), Reus, Spain.
Joaquim PeraireHospital Universitari de Tarragona Joan XXIII (HJ23), Tarragona, Spain.
Antoni Del PinoEurecat, Centre Tecnològic de Catalunya, Centre for Omic Sciences (Joint Unit Eurecat- Universitat Rovira i Virgili), Unique Scientific and Technical Infrastructure (ICTS), Reus, Spain.
Silvia ChafinoHospital Universitari de Tarragona Joan XXIII (HJ23), Tarragona, Spain.
Javier Martinez-PicadoCentro de Investigación Biomédica en Red de Enfermedades Infecciosas (CIBERINFEC), Instituto de Salud Carlos III, Madrid, Spain.
Fréderic Gómez-BertomeuHospital Universitari de Tarragona Joan XXIII (HJ23), Tarragona, Spain.
Anna RullHospital Universitari de Tarragona Joan XXIII (HJ23), Tarragona, Spain.
Núria CanelaEurecat, Centre Tecnològic de Catalunya, Centre for Omic Sciences (Joint Unit Eurecat- Universitat Rovira i Virgili), Unique Scientific and Technical Infrastructure (ICTS), Reus, Spain.
Manuel SuárezInstitut Investigació Sanitària Pere Virgili (IISPV), Tarragona, Spain.
Centre for Omic Sciences · ESCentro de Investigación Biomédica en Red · ESHospital Universitari Joan XXIII de Tarragona · ESInstitució Catalana de Recerca i Estudis Avançats · ESInstitut d'Investigació Sanitària Pere Virgili · ESInstituto de Salud Carlos III · ESUniversidad Rovira i Virgili · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The pathological mechanisms of SARS-CoV-2 in humans remain unclear and the unpredictability of COVID-19 progression may be attributed to the absence of biomarkers that contribute to the prognosis of this disease. Therefore, the discovery of biomarkers is needed for reliable risk stratification and to identify patients who are more likely to progress to a critical stage. Methods: Aiming to identify new biomarkers we analysed N-glycan traits in plasma from 196 patients with COVID-19. Samples were classified into three groups according to their severity (mild, severe and critical) and obtained at diagnosis (baseline) and at 4 weeks of follow-up (postdiagnosis), to evaluate their behaviour through disease progression. N-glycans were released with PNGase F and labelled with Rapifluor-MS, followed by their analysis by LC-MS/MS. The Simglycan structural identification tool and Glycostore database were employed to predict the structure of glycans. Results: We determined that plasma from SARS-CoV-2-infected patients display different N-glycosylation profiles depending on the disease severity. Specifically, levels of fucosylation and galactosylation decreased with increasing severity and Fuc1Hex5HexNAc5 was identified as the most suitable biomarker to stratify patients at diagnosis and distinguish mild from critical outcomes. Conclusion: In this study we explored the global plasma glycosignature, reflecting the inflammatory state of the organs during the infectious disease. Our findings show the promising potential of glycans as biomarkers of COVID-19 severity.

Indexed as

COVID-19Tandem Mass SpectrometryBiomarkersChromatography, LiquidGlycosylationHumansPolysaccharidesSARS-CoV-2BiomarkersPolysaccharidesbiomarkerCOVID-19fucosylationLC-MS/MSN-glycosylation

Identifiers

PMID37342334
PMCPMC10278543
OpenAlexW4379469523

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.