Evidence map›Paper›PMID 33651717›Full record

ArticleJCI insight2021

Cell-free DNA maps COVID-19 tissue injury and risk of death and can cause tissue injury.

Temesgen E Andargie, Naoko Tsuji, Fayaz Seifuddin, Moon Kyoo Jang, Peter St Yuen, Hyesik Kong, Ilker Tunc, Komudi Singh, Ananth Charya, Kenneth Wilkins and 5 more

Open access · goldAbstract readMulticenter Study
In one paragraph

Article in JCI insight, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 101 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
101citing papers in PubMed, 3 pooled it
11.4field-weighted citation impact, top 1% 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

101 citing papers in PubMed, 3 syntheses or guidelines pooled it, 149 citations in OpenAlex.

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  20. Mitochondrial DNA signals driving immune responses: Why, How, Where?Cell communication and signaling : CCS · 2025
    Review

41 more citing papers are in PubMed but not listed here.

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

15 authors at 7 institutions in 2 countries.

Temesgen E AndargieGenomic Research Alliance for Transplantation (GRAfT) and Laboratory of Applied Precision Omics, National Heart, Lung, and Blood Institute (NHLBI), NIH, Bethesda, Maryland, USA.
Naoko TsujiRenal Diagnostics and Therapeutics Unit, National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), NIH, Bethesda, Maryland, USA.
Fayaz SeifuddinBioinformatics and Computation Core, NHLBI, Maryland, USA.
Moon Kyoo JangGenomic Research Alliance for Transplantation (GRAfT) and Laboratory of Applied Precision Omics, National Heart, Lung, and Blood Institute (NHLBI), NIH, Bethesda, Maryland, USA.
Peter St YuenRenal Diagnostics and Therapeutics Unit, National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), NIH, Bethesda, Maryland, USA.
Hyesik KongGenomic Research Alliance for Transplantation (GRAfT) and Laboratory of Applied Precision Omics, National Heart, Lung, and Blood Institute (NHLBI), NIH, Bethesda, Maryland, USA.
Ilker TuncBioinformatics and Computation Core, NHLBI, Maryland, USA.
Komudi SinghBioinformatics and Computation Core, NHLBI, Maryland, USA.
Ananth CharyaGenomic Research Alliance for Transplantation (GRAfT) and Laboratory of Applied Precision Omics, National Heart, Lung, and Blood Institute (NHLBI), NIH, Bethesda, Maryland, USA.
Kenneth WilkinsOffice of the Director, NIDDK, NIH, Bethesda, Maryland, USA.
Steven NathanAdvanced Lung Disease and Transplant Program, Inova Fairfax Hospital, Fairfax, Virginia, USA.
Andrea CoxDepartment of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
Mehdi PiroozniaBioinformatics and Computation Core, NHLBI, Maryland, USA.
Robert A StarRenal Diagnostics and Therapeutics Unit, National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), NIH, Bethesda, Maryland, USA.
Sean Agbor-EnohGenomic Research Alliance for Transplantation (GRAfT) and Laboratory of Applied Precision Omics, National Heart, Lung, and Blood Institute (NHLBI), NIH, Bethesda, Maryland, USA.
Bioinformatics Institute · RUNational Heart Lung and Blood Institute · USNational Institute of Diabetes and Digestive and Kidney Diseases · USJohns Hopkins University · USHoward University · USInova Fairfax Hospital · USOffice of the Director · US

Funding

Inhibition Of Renal InjuryZIADK043403 · NIDDK · NATIONAL INSTITUTE OF DIABETES AND DIGESTIVE AND KIDNEY DISEASES · PI STAR, ROBERT A · 2009 to 2025
$15.5M
Early Detection Of Renal InjuryZIADK043400 · NIDDK · NATIONAL INSTITUTE OF DIABETES AND DIGESTIVE AND KIDNEY DISEASES · PI STAR, ROBERT A · 2009 to 2025
$9.5M
Bioinformatics CoreZICHL006228 · NHLBI · NATIONAL HEART, LUNG, AND BLOOD INSTITUTE · PI PIROOZNIA, MEHDI · 2017 to 2021
$6.6M
6 · The paper itself

Abstract

INTRODUCTIONThe clinical course of coronavirus 2019 (COVID-19) is heterogeneous, ranging from mild to severe multiorgan failure and death. In this study, we analyzed cell-free DNA (cfDNA) as a biomarker of injury to define the sources of tissue injury that contribute to such different trajectories.METHODSWe conducted a multicenter prospective cohort study to enroll patients with COVID-19 and collect plasma samples. Plasma cfDNA was subject to bisulfite sequencing. A library of tissue-specific DNA methylation signatures was used to analyze sequence reads to quantitate cfDNA from different tissue types. We then determined the correlation of tissue-specific cfDNA measures to COVID-19 outcomes. Similar analyses were performed for healthy controls and a comparator group of patients with respiratory syncytial virus and influenza.RESULTSWe found markedly elevated levels and divergent tissue sources of cfDNA in COVID-19 patients compared with patients who had influenza and/or respiratory syncytial virus and with healthy controls. The major sources of cfDNA in COVID-19 were hematopoietic cells, vascular endothelium, hepatocytes, adipocytes, kidney, heart, and lung. cfDNA levels positively correlated with COVID-19 disease severity, C-reactive protein, and D-dimer. cfDNA profile at admission identified patients who subsequently required intensive care or died during hospitalization. Furthermore, the increased cfDNA in COVID-19 patients generated excessive mitochondrial ROS (mtROS) in renal tubular cells in a concentration-dependent manner. This mtROS production was inhibited by a TLR9-specific antagonist.CONCLUSIONcfDNA maps tissue injury that predicts COVID-19 outcomes and may mechanistically propagate COVID-19-induced tissue injury.FUNDINGIntramural Targeted Anti-COVID-19 grant, NIH.

Indexed as

Cell-Free Nucleic AcidsCOVID-19Multiple Organ FailureSARS-CoV-2BiomarkersCohort StudiesDNA MethylationFemaleHumansMaleMiddle AgedOrgan SpecificityOutcome Assessment, Health CarePrognosisProspective StudiesReproducibility of ResultsBiomarkersCell-Free Nucleic AcidsBioinformaticsCOVID-19InflammationMolecular genetics

Identifiers

PMID33651717
PMCPMC8119224
OpenAlexW3134426305

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.