Evidence map›Paper›PMID 35075453›Full record

ArticleResearch square2022

Integrated cell-free DNA and cytokine analysis uncovers distinct tissue injury and immune response patterns in solid organ transplant recipients with COVID-19.

Temesgen E Andargie, Weiqiang Zhou, Andrew H Karaba, Taibo Li, Fayaz Seifuddin, Alex G Rittenhouse, Hyesik Kong, Komudi Singh, Robert Woodward, Aldo Iacono and 6 more

Open access · greenAbstract readPreprint
In one paragraph

Article in Research square, 2022. 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, 5 citations in OpenAlex.

  1. Review
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

16 authors at 5 institutions in 1 country.

Temesgen E AndargieGenomic Research Alliance for Transplantation (GRAfT) and Laboratory of Applied Precision Omics, National Heart, Lung, and Blood Institute (NHLBI), NIH, Bethesda, MD.
Weiqiang ZhouDepartment of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD.
Andrew H KarabaDepartment of Medicine, Johns Hopkins University, School of Medicine, Baltimore, MD.
Taibo LiDepartment of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD.ORCID 0000-0002-6624-9293
Fayaz SeifuddinBioinformatics and Computation Core, NHLBI, MD.
Alex G RittenhouseDepartment of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD.
Hyesik KongGenomic Research Alliance for Transplantation (GRAfT) and Laboratory of Applied Precision Omics, National Heart, Lung, and Blood Institute (NHLBI), NIH, Bethesda, MD.
Komudi SinghBioinformatics and Computation Core, NHLBI, MD.ORCID 0000-0002-6413-541X
Robert WoodwardCareDx, Brisbane, CA.
Aldo IaconoDepartment of Medicine, University of Maryland, College Park, MD.
Robin K AveryDepartment of Medicine, Johns Hopkins University, School of Medicine, Baltimore, MD.
Mehdi PiroozniaBioinformatics and Computation Core, NHLBI, MD.ORCID 0000-0002-4210-6458
Moon Kyoo JangGenomic Research Alliance for Transplantation (GRAfT) and Laboratory of Applied Precision Omics, National Heart, Lung, and Blood Institute (NHLBI), NIH, Bethesda, MD.
Hongkai JiDepartment of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD.ORCID 0000-0002-6480-0141
Andrea L CoxDepartment of Medicine, Johns Hopkins University, School of Medicine, Baltimore, MD.
Sean Agbor-EnohGenomic Research Alliance for Transplantation (GRAfT) and Laboratory of Applied Precision Omics, National Heart, Lung, and Blood Institute (NHLBI), NIH, Bethesda, MD.ORCID 0000-0002-9380-9161
Johns Hopkins University · USNational Institutes of Health · USNational Heart Lung and Blood Institute · USPAX Scientific (United States) · USUniversity of Maryland, College Park · US

Funding

Medical Scientist Training ProgramT32GM136577 · NIGMS · JOHNS HOPKINS UNIVERSITY · PI ANDREA L COX · 2020 to 2026
$13.4M
Cell-free DNA to detect transplant rejectionZIAHL006268 · NHLBI · NATIONAL HEART, LUNG, AND BLOOD INSTITUTE · PI AGBOR-ENOH, SEAN · 2021 to 2025
$8.8M
NIGMS NIH HHS T32 GM136577
6 · The paper itself

Abstract

COVID-19 pathogenesis is associated with an exuberant inflammatory response. However, the tissue injury pattern and immune response in solid-organ transplant recipients (SOTRs) taking immunosuppressive therapy have not been well characterized. Here, we perform both cfDNA and cytokine profiling on plasma samples to map tissue damage, including allograft injury and delineate underlying immunopathology. We identified injuries from multiple-tissue types, including hematopoietic cells, vascular endothelium, hepatocyte, adipocyte, pancreas, kidney, heart, and lung in SOTRs with COVID-19 that correlates with disease severity. SOTRs with COVID-19 have higher plasma levels of cytokines such as IFN-λ1, IFN-γ, IL-15, IL-18 IL-1RA, IL-6, MCP-2, and TNF-α as compared to healthy controls, and the levels of GM-CSF, IL-15, IL-6, IL-8, and IL-10 were associated with disease severity in SOTRs. Strikingly, IFN-λ and IP-10 were markedly increased in SOTRs compared to immunocompetent patients with COVID-19. Correlation analyses showed a strong association between monocyte-derived cfDNA and inflammatory cytokines/chemokines in SOTRs with COVID-19. Moreover, compared to other respiratory viral infections, COVID-19 induced pronounced injury in hematopoietic, vascular endothelial and endocrine tissues. Allograft injury, measured as donor-derived cfDNA was elevated in SOTRs with COVID-19, including allografts distant from the primary site of infection. Allograft injury correlated with inflammatory cytokines and cfDNA from immune cells. Furthermore, longitudinal analysis identified a gradual decrease of cfDNA and inflammatory cytokine levels in patients with a favorable outcome. Our findings highlight distinct tissue injury and cytokine features in SOTRs with COVID-19 that correlate with disease severity.

Identifiers

PMID35075453
PMCPMC8786231
OpenAlexW4206210970

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.