Evidence map›Paper›PMID 33269369›Full record

ArticlemedRxiv : the preprint server for health sciences2020

T cell and antibody functional correlates of severe COVID-19.

Krystle K Q Yu, Stephanie Fischinger, Malisa T Smith, Caroline Atyeo, Deniz Cizmeci, Caitlin R Wolf, Erik D Layton, Jennifer K Logue, Melissa S Aguilar, Kiel Shuey and 11 more

Open access · greenAbstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed, 10 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

21 authors at 6 institutions in 2 countries.

Krystle K Q YuDepartment of Medicine, University of Washington School of Medicine, Seattle, WA, USA.
Stephanie FischingerRagon Institute of MGH, MIT and Harvard, Boston, MA, USA.
Malisa T SmithDepartment of Medicine, University of Washington School of Medicine, Seattle, WA, USA.
Caroline AtyeoRagon Institute of MGH, MIT and Harvard, Boston, MA, USA.
Deniz CizmeciRagon Institute of MGH, MIT and Harvard, Boston, MA, USA.
Caitlin R WolfDepartment of Medicine, University of Washington School of Medicine, Seattle, WA, USA.
Erik D LaytonDepartment of Medicine, University of Washington School of Medicine, Seattle, WA, USA.
Jennifer K LogueDepartment of Medicine, University of Washington School of Medicine, Seattle, WA, USA.
Melissa S AguilarDepartment of Medicine, University of Washington School of Medicine, Seattle, WA, USA.
Kiel ShueyDepartment of Medicine, University of Washington School of Medicine, Seattle, WA, USA.
Carolin LoosRagon Institute of MGH, MIT and Harvard, Boston, MA, USA.
Jingyou YuCenter for Virology and Vaccine Research, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02215, USA.
Nicholas FrankoDepartment of Medicine, University of Washington School of Medicine, Seattle, WA, USA.
Robert Y ChoiProvidence Medical Group, Everett, WA, USA.
Anna WaldDepartment of Medicine, University of Washington School of Medicine, Seattle, WA, USA.
Dan H BarouchRagon Institute of MGH, MIT and Harvard, Boston, MA, USA.
David M KoelleDepartment of Medicine, University of Washington School of Medicine, Seattle, WA, USA.
Douglas LauffenburgerDepartment of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.
Helen Y ChuDepartment of Medicine, University of Washington School of Medicine, Seattle, WA, USA.
Galit AlterRagon Institute of MGH, MIT and Harvard, Boston, MA, USA.
Chetan SeshadriDepartment of Medicine, University of Washington School of Medicine, Seattle, WA, USA.
University of Washington · USRagon Institute of MGH, MIT and Harvard · USBeth Israel Deaconess Medical Center · USHarvard University · USMassachusetts Institute of Technology · USProvidence Regional Medical Center Everett · US

Funding

Qualification of Assays to Measure Human T-cell Responses Against Mycobacterial Lipid AntigensR01AI125189 · NIAID · UNIVERSITY OF WASHINGTON · PI SESHADRI, CHETAN · 2016 to 2020
$3.1M
Doris Duke Charitable Foundation 2016103NCEZID CDC HHS U01 CK000490NIAID NIH HHS HHSN272201400049CNIAID NIH HHS R01 AI125189
6 · The paper itself

Abstract

Comorbid medical illnesses, such as obesity and diabetes, are associated with more severe COVID-19, hospitalization, and death. However, the role of the immune system in mediating these clinical outcomes has not been determined. We used multi-parameter flow cytometry and systems serology to comprehensively profile the functions of T cells and antibodies targeting spike, nucleocapsid, and envelope proteins in a convalescent cohort of COVID-19 subjects who were either hospitalized (n=20) or not hospitalized (n=40). To avoid confounding, subjects were matched by age, sex, ethnicity, and date of symptom onset. Surprisingly, we found that the magnitude and functional breadth of virus-specific CD4 T cell and antibody responses were consistently higher among hospitalized subjects, particularly those with medical comorbidities. However, an integrated analysis identified more coordination between polyfunctional CD4 T-cells and antibodies targeting the S1 domain of spike among subjects that were not hospitalized. These data reveal a functionally diverse and coordinated response between T cells and antibodies targeting SARS-CoV-2 which is reduced in the presence of comorbid illnesses that are known risk factors for severe COVID-19. Our data suggest that isolated measurements of the magnitudes of spike-specific immune responses are likely insufficient to anticipate vaccine efficacy in high-risk populations.

Identifiers

PMID33269369
PMCPMC7709190
OpenAlexW3108976746

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.