Evidence map›Paper›PMID 39451653›Full record

ArticleDiagnostics (Basel, Switzerland)2024

Investigation of Long-Term CD4+ T Cell Receptor Repertoire Changes Following SARS-CoV-2 Infection in Patients with Different Severities of Disease.

Emma L Callery, Camilo L M Morais, Jemma V Taylor, Kirsty Challen, Anthony W Rowbottom

Abstract read
In one paragraph

Article in Diagnostics (Basel, Switzerland), 2024. 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
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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

5 authors.

Emma L CalleryDepartment of Immunology, Lancashire Teaching Hospitals NHS Foundation, Preston PR2 9HT, UK.ORCID 0000-0003-0786-9182
Camilo L M MoraisInstitute of Chemistry, Federal University of Rio Grande do Norte, Natal 59072-970, Brazil.ORCID 0000-0003-2573-787X
Jemma V TaylorDepartment of Immunology, Lancashire Teaching Hospitals NHS Foundation, Preston PR2 9HT, UK.ORCID 0000-0001-5106-2875
Kirsty ChallenDepartment of Emergency Medicine, Lancashire Teaching Hospitals NHS Foundation, Preston PR2 9HT, UK.
Anthony W RowbottomDepartment of Immunology, Lancashire Teaching Hospitals NHS Foundation, Preston PR2 9HT, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe difference in the immune response to severe acute respiratory syndrome coro-navirus 2 (SARS-CoV-2) in patients with mild versus severe disease remains poorly understood. Recent scientific advances have recognised the vital role of both B cells and T cells; however, many questions remain unanswered, particularly for T cell responses. T cells are essential for helping the generation of SARS-CoV-2 antibody responses but have also been recognised in their own right as a major factor influencing COVID-19 disease outcomes. The examination of T cell receptor (TCR) family differences over a 12-month period in patients with varying COVID-19 disease severity is crucial for understanding T cell responses to SARS-CoV-2.

methodsWe applied a machine learning approach to analyse TCR vb family responses in COVID-19 patients (

resultsBlood samples from hospital in-patients with moderate, severe, or critical disease could be classified with an accuracy of 94%. Furthermore, we identified significant variances in TCR vb family specificities between disease and control subgroups.

conclusionsOur findings suggest advantageous and disadvantageous TCR repertoire patterns in relation to disease severity. Following validation in larger cohorts, our methodology may be useful in detecting protective immunity and the assessment of long-term outcomes, particularly as we begin to unravel the immunological mechanisms leading to post-COVID complications.

Indexed as

COVID-19flow cytometryimmune responsemachine learningSARS-CoV-2severity modelT cell receptorTCR repertoire

Identifiers

PMID39451653
PMCPMC11507081

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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.