Evidence map›Paper›PMID 34623327›Full record

ArticleThe Journal of clinical investigation2021

Rapid measurement of SARS-CoV-2 spike T cells in whole blood from vaccinated and naturally infected individuals.

Anthony T Tan, Joey Me Lim, Nina Le Bert, Kamini Kunasegaran, Adeline Chia, Martin Dc Qui, Nicole Tan, Wan Ni Chia, Ruklanthi de Alwis, Ding Ying and 9 more

Open access · bronzeAbstract read
In one paragraph

Article in The Journal of clinical investigation, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 74 papers.

0numbers the graph read from it
0cells of the map it votes in
74citing papers in PubMed
7.5field-weighted citation impact, top 2% 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

74 citing papers in PubMed, 126 citations in OpenAlex.

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  17. A rapid method to assess theImmunotherapy advances · 2024
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14 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

19 authors at 7 institutions in 1 country.

Anthony T TanProgramme in Emerging Infectious Diseases, Duke-NUS Medical School, Singapore.
Joey Me LimProgramme in Emerging Infectious Diseases, Duke-NUS Medical School, Singapore.
Nina Le BertProgramme in Emerging Infectious Diseases, Duke-NUS Medical School, Singapore.
Kamini KunasegaranProgramme in Emerging Infectious Diseases, Duke-NUS Medical School, Singapore.
Adeline ChiaProgramme in Emerging Infectious Diseases, Duke-NUS Medical School, Singapore.
Martin Dc QuiProgramme in Emerging Infectious Diseases, Duke-NUS Medical School, Singapore.
Nicole TanProgramme in Emerging Infectious Diseases, Duke-NUS Medical School, Singapore.
Wan Ni ChiaProgramme in Emerging Infectious Diseases, Duke-NUS Medical School, Singapore.
Ruklanthi de AlwisProgramme in Emerging Infectious Diseases, Duke-NUS Medical School, Singapore.
Ding YingNational Centre for Infectious Diseases (NCID), Singapore.
Jean Xy SimDepartment of Infectious Diseases, Singapore General Hospital, Singapore.
Eng Eong OoiProgramme in Emerging Infectious Diseases, Duke-NUS Medical School, Singapore.
Lin-Fa WangProgramme in Emerging Infectious Diseases, Duke-NUS Medical School, Singapore.
Mark I-Cheng ChenNational Centre for Infectious Diseases (NCID), Singapore.
Barnaby E YoungNational Centre for Infectious Diseases (NCID), Singapore.
Li Yang HsuSaw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore.
Jenny Gh LowProgramme in Emerging Infectious Diseases, Duke-NUS Medical School, Singapore.
David C LyeNational Centre for Infectious Diseases (NCID), Singapore.
Antonio BertolettiProgramme in Emerging Infectious Diseases, Duke-NUS Medical School, Singapore.
Duke-NUS Medical School · SGTan Tock Seng Hospital · SGSingapore General Hospital · SGAgency for Science, Technology and Research · SGNational Centre for Infectious Diseases · SGNational University of Singapore · SGSingHealth Duke-NUS Academic Medical Centre · SG

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Defining the correlates of protection necessary to manage the COVID-19 pandemic requires the analysis of both antibody and T cell parameters, but the complexity of traditional tests limits virus-specific T cell measurements. We tested the sensitivity and performance of a simple and rapid SARS-CoV-2 spike protein-specific T cell test based on the stimulation of whole blood with peptides covering the SARS-CoV-2 spike protein, followed by cytokine (IFN-γ, IL-2) measurement in different cohorts including BNT162b2-vaccinated individuals (n = 112), convalescent asymptomatic and symptomatic COVID-19 patients (n = 130), and SARS-CoV-1-convalescent individuals (n = 12). The sensitivity of this rapid test is comparable to that of traditional methods of T cell analysis (ELISPOT, activation-induced marker). Using this test, we observed a similar mean magnitude of T cell responses between the vaccinees and SARS-CoV-2 convalescents 3 months after vaccination or virus priming. However, a wide heterogeneity of the magnitude of spike-specific T cell responses characterized the individual responses, irrespective of the time of analysis. The magnitude of these spike-specific T cell responses cannot be predicted from the neutralizing antibody levels. Hence, both humoral and cellular spike-specific immunity should be tested after vaccination to define the correlates of protection necessary to evaluate current vaccine strategies.

Indexed as

COVID-19SARS-CoV-2Spike Glycoprotein, CoronavirusT-LymphocytesAdultBNT162 VaccineCOVID-19 VaccinesFemaleHumansImmunity, CellularMaleMiddle AgedBNT162 VaccineCOVID-19 VaccinesSpike Glycoprotein, Coronavirusspike protein, SARS-CoV-2Adaptive immunityCOVID-19CytokinesImmunologyT cells

Identifiers

PMID34623327
PMCPMC8409582
OpenAlexW3197591755

What OpenQuestion holds

Textmetadata
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.