Evidence map›Paper›PMID 39131351›Full record

ArticlebioRxiv : the preprint server for biology2024

Using virtual patient cohorts to uncover immune response differences in cancer and immunosuppressed COVID-19 patients.

Sonia Gazeau, Xiaoyan Deng, Elsa Brunet-Ratnasingham, Daniel E Kaufmann, Catherine Larochelle, Penelope A Morel, Jane M Heffernan, Courtney L Davis, Amber M Smith, Adrianne L Jenner and 1 more

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 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
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors.

Sonia GazeauSainte-Justine University Hospital Research Centre, Montréal, Québec, Canada.
Xiaoyan DengSainte-Justine University Hospital Research Centre, Montréal, Québec, Canada.
Elsa Brunet-RatnasinghamUniversity of California, San Francisco, California, USA.
Daniel E KaufmannResearch Centre of the Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, Québec, Canada.
Catherine LarochelleResearch Centre of the Centre Hospitalier de l'Université de Montréal (CRCHUM), Montréal, Québec, Canada.
Penelope A MorelDepartment of Immunology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
Jane M HeffernanCentre for Disease Modelling, Department of Mathematics & Statistics, York University, Toronto, Ontario, Canada.
Courtney L DavisNatural Science Division, Pepperdine University, Malibu, California, USA.
Amber M SmithDepartment of Pediatrics, University of Tennessee Health Science Center, Memphis, Tennessee, USA.
Adrianne L JennerSchool of Mathematical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia.
Morgan CraigSainte-Justine University Hospital Research Centre, Montréal, Québec, Canada.ORCID 0000-0003-4852-4770

Funding

Virtual Patient Cohorts to Illuminate Immunologic Drivers of Influenza SeverityR01AI170115 · NIAID · UNIVERSITY OF TENNESSEE HEALTH SCI CTR · PI SMITH, AMBER M · 2022 to 2025
$2.8M
NIAID NIH HHS R01 AI170115
6 · The paper itself

Abstract

The COVID-19 pandemic caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) resulted in millions of deaths globally. Adults with immunosuppression (e.g., solid organ transplant recipients) and those undergoing active cancer treatments experience worse infections and more severe COVID-19. It is difficult to conduct clinical studies in these populations, resulting in a restricted amount of data that can be used to relate mechanisms of immune dysfunction to COVID-19 outcomes in these vulnerable groups. To study immune dynamics after infection with SARS-CoV-2 and to investigate drivers of COVID-19 severity in individuals with cancer and immunosuppression, we adapted our mathematical model of the immune response during COVID-19 and generated virtual patient cohorts of cancer and immunosuppressed patients. The cohorts of plausible patients recapitulated available longitudinal clinical data collected from patients in Montréal, Canada area hospitals. Our model predicted that both cancer and immunosuppressed virtual patients with severe COVID-19 had decreased CD8+ T cells, elevated interleukin-6 concentrations, and delayed type I interferon peaks compared to those with mild COVID-19 outcomes. Additionally, our results suggest that cancer patients experience higher viral loads (however, with no direct relation with severity), likely because of decreased initial neutrophil counts (i.e., neutropenia), a frequent toxic side effect of anti-cancer therapy. Furthermore, severe cancer and immunosuppressed virtual patients suffered a high degree of tissue damage associated with elevated neutrophils. Lastly, parameter values associated with monocyte recruitment by infected cells were found to be elevated in severe cancer and immunosuppressed patients with respect to the COVID-19 reference group. Together, our study highlights that dysfunction in type I interferon and CD8+ T cells are key drivers of immune dysregulation in COVID-19, particularly in cancer patients and immunosuppressed individuals.

Identifiers

PMID39131351
PMCPMC11312602

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.