Evidence map›Paper›PMID 35386707›Full record

ArticleFrontiers in immunology2022

Immunogenic SARS-CoV-2 S and N Protein Peptide and Cytokine Combinations as Biomarkers for Early Prediction of Fatal COVID-19.

Ekaterina Martynova, Shaimaa Hamza, Maria Markelova, Ekaterina Garanina, Yuriy Davidyuk, Venera Shakirova, Neha Kaushal, Manoj Baranwal, Robert J Stott-Marshall, Toshana L Foster and 2 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in immunology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.3field-weighted citation impact, top 19% 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

6 citing papers in PubMed, 13 citations in OpenAlex.

  1. A Pilot Study of COVID-19 Outcomes in People Living with HIV in Tatarstan.International journal of molecular sciences · 2025
    Article
  2. Predictive Role and Clinical Value of Serum Cytokines in COVID-19.Infectious diseases & clinical microbiology · 2024
    Article
  3. Article
  4. Article
  5. Neutralizing Antibodies in COVID-19 Serum from Tatarstan, Russia.International journal of molecular sciences · 2023
    Article
  6. 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

12 authors at 4 institutions in 3 countries.

Ekaterina MartynovaInstitute of Fundamental Medicine and Biology, Kazan Federal University, Kazan, Russia.
Shaimaa HamzaInstitute of Fundamental Medicine and Biology, Kazan Federal University, Kazan, Russia.
Maria MarkelovaInstitute of Fundamental Medicine and Biology, Kazan Federal University, Kazan, Russia.
Ekaterina GaraninaInstitute of Fundamental Medicine and Biology, Kazan Federal University, Kazan, Russia.
Yuriy DavidyukInstitute of Fundamental Medicine and Biology, Kazan Federal University, Kazan, Russia.
Venera ShakirovaDepartment of Infectious Diseases, Kazan State Medical Academy, Kazan, Russia.
Neha KaushalDepartment of Biotechnology, Thapar Institute of Engineering and Technology, Patiala, India.
Manoj BaranwalDepartment of Biotechnology, Thapar Institute of Engineering and Technology, Patiala, India.
Robert J Stott-MarshallFaculty of Medicine and Health Sciences, School of Veterinary Medicine and Science, Wolfson Centre for Global Virus Research, University of Nottingham, Loughborough, United Kingdom.
Toshana L FosterFaculty of Medicine and Health Sciences, School of Veterinary Medicine and Science, Wolfson Centre for Global Virus Research, University of Nottingham, Loughborough, United Kingdom.
Albert RizvanovInstitute of Fundamental Medicine and Biology, Kazan Federal University, Kazan, Russia.
Svetlana KhaiboullinaInstitute of Fundamental Medicine and Biology, Kazan Federal University, Kazan, Russia.
Kazan Federal University · RUThapar Institute of Engineering & Technology · INUniversity of Nottingham · GBKazan State Medical Academy · RU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Early indications of the likelihood of severe coronavirus disease 2019 COVID-19 can influence treatments and could improve clinical outcomes. However, knowledge on the prediction markers of COVID-19 fatality risks remains limited. Here, we analyzed and quantified the reactivity of serum samples from acute (non-fatal and fatal) and convalescent COVID-19 patients with the spike surface glycoprotein (S protein) and nucleocapsid phosphoprotein (N protein) SARS-CoV-2 peptide libraries. Cytokine activation was also analyzed. We demonstrated that IgM from fatal COVID-19 serum reacted with several N protein peptides. In contrast, IgM from non-fatal serum reacted more with S protein peptides. Further, higher levels of pro-inflammatory cytokines were found in fatal COVID-19 serum compared to non-fatal. Many of these cytokines were pro-inflammatory and chemokines. Differences in IgG reactivity from fatal and non-fatal COVID-19 sera were also demonstrated. Additionally, the longitudinal analysis of IgG reactivity with SARS-CoV-2 S and N protein identified peptides with the highest longevity in humoral immune response. Finally, using IgM antibody reactivity with S and N SARS-CoV-2 peptides and selected cytokines, we have identified a panel of biomarkers specific to patients with a higher risk of fatal COVID-19 compared with that of patients who survive. This panel could be used for the early prediction of COVID-19 fatality risk.

Indexed as

COVID-19Antibodies, ViralBiomarkersCytokinesHumansImmunoglobulin GImmunoglobulin MSARS-CoV-2Spike Glycoprotein, CoronavirusAntibodies, ViralBiomarkersCytokinesImmunoglobulin GImmunoglobulin MSpike Glycoprotein, Coronavirusspike protein, SARS-CoV-2COVID-19cytokinefatalpeptideSARS-CoV-2

Identifiers

PMID35386707
PMCPMC8979210
OpenAlexW4220860281

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.