Evidence map›Paper›PMID 33637823›Full record

ArticleScientific reports2021

Homologies between SARS-CoV-2 and allergen proteins may direct T cell-mediated heterologous immune responses.

Kathrin Balz, Abhinav Kaushik, Meng Chen, Franz Cemic, Vanessa Heger, Harald Renz, Kari Nadeau, Chrysanthi Skevaki

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 1 pooled it
2.6field-weighted citation impact, top 9% 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

21 citing papers in PubMed, 1 synthesis or guideline pooled it, 36 citations in OpenAlex.

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  19. Comparable seasonal pattern for COVID-19 and flu-like illnesses.One health (Amsterdam, Netherlands) · 2021
    Article
  20. How to interpret and use COVID-19 serology and immunology tests.Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases · 2021
    Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors at 4 institutions in 2 countries.

Kathrin Balz *Institute of Laboratory Medicine, Universities of Giessen and Marburg Lung Center (UGMLC), Philipps University Marburg, German Center for Lung Research (DZL), Marburg, Germany.
Abhinav Kaushik *Division of Pulmonary, Allergy and Critical Care Medicine, Sean N. Parker Center for Allergy and Asthma Research at Stanford University, Stanford, CA, USA.
Meng ChenDivision of Pulmonary, Allergy and Critical Care Medicine, Sean N. Parker Center for Allergy and Asthma Research at Stanford University, Stanford, CA, USA.
Franz CemicTH Mittelhessen, Department of Computer Science, University of Applied Sciences Gießen, Gießen, Hessen, Germany.
Vanessa HegerTH Mittelhessen, Department of Computer Science, University of Applied Sciences Gießen, Gießen, Hessen, Germany.
Harald RenzInstitute of Laboratory Medicine, Universities of Giessen and Marburg Lung Center (UGMLC), Philipps University Marburg, German Center for Lung Research (DZL), Marburg, Germany.
Kari Nadeau *Division of Pulmonary, Allergy and Critical Care Medicine, Sean N. Parker Center for Allergy and Asthma Research at Stanford University, Stanford, CA, USA.
Chrysanthi Skevaki *Institute of Laboratory Medicine, Universities of Giessen and Marburg Lung Center (UGMLC), Philipps University Marburg, German Center for Lung Research (DZL), Marburg, Germany. chrysanthi.skevaki@uk-gm.de.
Stanford University · USGerman Center for Lung Research · DETechnische Hochschule Mittelhessen · DEUniversities of Giessen and Marburg Lung Center · DE

Funding

T Cell Reagent Research for Monitoring T Cell in Food AllergyU01AI140498 · NIAID · STANFORD UNIVERSITY · PI NADEAU, KARI C. · 2018 to 2022
$1.8M
Effects of IgE Blockade on T Cells in Food AllergyR01AI140134 · NIAID · STANFORD UNIVERSITY · PI NADEAU, KARI C. · 2018 to 2021
$1.6M
NIAID NIH HHS R01 AI140134NIAID NIH HHS U01 AI140498NIH HHS R01AI140134-01NIH HHS U01AI140498-03
6 · The paper itself

Abstract

The outbreak of the new severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is a public health emergency. Asthma does not represent a risk factor for COVID-19 in several published cohorts. We hypothesized that the SARS-CoV-2 proteome contains T cell epitopes, which are potentially cross-reactive to allergen epitopes. We aimed at identifying homologous peptide sequences by means of two distinct complementary bioinformatics approaches. Pipeline 1 included prediction of MHC Class I and Class II epitopes contained in the SARS-CoV-2 proteome and allergens along with alignment and elaborate ranking approaches. Pipeline 2 involved alignment of SARS-CoV-2 overlapping peptides with known allergen-derived T cell epitopes. Our results indicate a large number of MHC Class I epitope pairs including known as well as de novo predicted allergen T cell epitopes with high probability for cross-reactivity. Allergen sources, such as Aspergillus fumigatus, Phleum pratense and Dermatophagoides species are of particular interest due to their association with multiple cross-reactive candidate peptides, independently of the applied bioinformatic approach. In contrast, peptides derived from food allergens, as well as MHC class II epitopes did not achieve high in silico ranking and were therefore not further investigated. Our findings warrant further experimental confirmation along with examination of the functional importance of such cross-reactive responses.

Indexed as

Immunity, HeterologousAllergensAsthmaComputational BiologyCOVID-19Epitopes, T-LymphocyteHLA AntigensHumansImmunity, CellularSARS-CoV-2T-LymphocytesViral ProteinsAllergensEpitopes, T-LymphocyteHLA AntigensViral Proteins

Identifiers

PMID33637823
PMCPMC7910599
OpenAlexW3133229618

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.