Evidence map›Paper›PMID 38007005›Full record

ArticleMucosal immunology2024

Salivary IgA and vimentin differentiate in vitro SARS-CoV-2 infection: A study of 290 convalescent COVID-19 patients.

Samuel Ellis, Rosie Way, Miranda Nel, Alice Burleigh, Ivan Doykov, Japhette Kembou-Ringert, Maximillian Woodall, Tereza Masonou, Katie-Marie Case, Arturo Torres Ortez and 11 more

Open access · hybridAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Mucosal immunology, 2024. 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
1.6field-weighted citation impact, top 17% 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, 8 citations in OpenAlex.

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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

21 authors at 4 institutions in 1 country.

Samuel EllisUCL Great Ormond Street Institute of Child Health, London, UK.
Rosie WayUCL Great Ormond Street Institute of Child Health, London, UK.
Miranda NelUCL Great Ormond Street Institute of Child Health, London, UK.
Alice BurleighUCL Great Ormond Street Institute of Child Health, London, UK; Centre for Adolescent Rheumatology, University College London, London, UK.
Ivan DoykovUCL Great Ormond Street Institute of Child Health, London, UK.
Japhette Kembou-RingertUCL Great Ormond Street Institute of Child Health, London, UK.
Maximillian WoodallUCL Great Ormond Street Institute of Child Health, London, UK.
Tereza MasonouUCL Great Ormond Street Institute of Child Health, London, UK.
Katie-Marie CaseUCL Great Ormond Street Institute of Child Health, London, UK.
Arturo Torres OrtezUCL Great Ormond Street Institute of Child Health, London, UK.
Timothy D McHughUCL Centre for Clinical Microbiology, Royal Free Hospital, London, UK.
Antonio CasalDepartment of Pharmaceutics, UCL School of Pharmacy, London, UK.
Laura E McCoyInstitute of Immunity and Transplantation, Division of Infection and Immunity, University College London, London, UK.
Sudaxshina MurdanDepartment of Pharmaceutics, UCL School of Pharmacy, London, UK.
Robert E HyndsEpithelial Cell Biology in ENT Research (EpiCENTR) Group, Developmental Biology and Cancer Department, UCL Great Ormond Street Institute of Child Health, London, UK.
Kimberly C GilmourUCL Great Ormond Street Institute of Child Health, London, UK; Great Ormond Street Hospital NHS Foundation Trust, London, UK.
Louis GrandjeanUCL Great Ormond Street Institute of Child Health, London, UK; Great Ormond Street Hospital NHS Foundation Trust, London, UK.
Mario Cortina-BorjaUCL Great Ormond Street Institute of Child Health, London, UK.
Wendy E HeywoodUCL Great Ormond Street Institute of Child Health, London, UK.
Kevin MillsUCL Great Ormond Street Institute of Child Health, London, UK.
Claire M SmithUCL Great Ormond Street Institute of Child Health, London, UK. Electronic address: c.m.smith@ucl.ac.uk.
Great Ormond Street Hospital · GBThe London College · GBThe Royal Free Hospital · GBUniversity College London · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

SARS-CoV-2 initially infects cells in the nasopharynx and oral cavity. The immune system at these mucosal sites plays a crucial role in minimizing viral transmission and infection. To develop new strategies for preventing SARS-CoV-2 infection, this study aimed to identify proteins that protect against viral infection in saliva. We collected 551 saliva samples from 290 healthcare workers who had tested positive for COVID-19, before vaccination, between June and December 2020. The samples were categorized based on their ability to block or enhance infection using in vitro assays. Mass spectrometry and enzyme-linked immunosorbent assay experiments were used to identify and measure the abundance of proteins that specifically bind to SARS-CoV-2 antigens. Immunoglobulin (Ig)A specific to SARS-CoV-2 antigens was detectable in over 83% of the convalescent saliva samples. We found that concentrations of anti-receptor-binding domain IgA >500 pg/µg total protein in saliva correlate with reduced viral infectivity in vitro. However, there is a dissociation between the salivary IgA response to SARS-CoV-2, and systemic IgG titers in convalescent COVID-19 patients. Then, using an innovative technique known as spike-baited mass spectrometry, we identified novel spike-binding proteins in saliva, most notably vimentin, which correlated with increased viral infectivity in vitro and could serve as a therapeutic target against COVID-19.

Indexed as

COVID-19Antibodies, ViralAntigens, ViralHumansImmunoglobulin ASARS-CoV-2VimentinAntibodies, ViralAntigens, ViralImmunoglobulin AVimentinVIM protein, human

Identifiers

PMID38007005
PMCPMC11139657
OpenAlexW4388979262

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.