Go to The Journal of Clinical Investigation
  • About
  • Editors
  • Consulting Editors
  • For authors
  • Publication ethics
  • Transfers
  • Advertising
  • Job board
  • Contact
  • Current issue
  • Past issues
  • By specialty
    • COVID-19
    • Cardiology
    • Immunology
    • Metabolism
    • Nephrology
    • Oncology
    • Pulmonology
    • All ...
  • Videos
  • Collections
    • Resource and Technical Advances
    • Clinical Medicine
    • Reviews
    • Editorials
    • Perspectives
    • Top read articles
  • JCI This Month
    • Current issue
    • Past issues

  • Current issue
  • Past issues
  • Specialties
  • In-Press Preview
  • Editorials
  • Viewpoint
  • Top read articles
  • About
  • Editors
  • Consulting Editors
  • For authors
  • Publication ethics
  • Transfers
  • Advertising
  • Job board
  • Contact

Usage Information

Circulating mitochondrial DNA is an early indicator of severe illness and mortality from COVID-19
Davide Scozzi, … , Hrishikesh S. Kulkarni, Andrew E. Gelman
Davide Scozzi, … , Hrishikesh S. Kulkarni, Andrew E. Gelman
Published January 14, 2021
Citation Information: JCI Insight. 2021;6(4):e143299. https://doi.org/10.1172/jci.insight.143299.
View: Text | PDF
Clinical Medicine COVID-19 Immunology

Circulating mitochondrial DNA is an early indicator of severe illness and mortality from COVID-19

  • Text
  • PDF
Abstract

Background Mitochondrial DNA (MT-DNA) are intrinsically inflammatory nucleic acids released by damaged solid organs. Whether circulating cell-free MT-DNA quantitation could be used to predict the risk of poor COVID-19 outcomes remains undetermined.Methods We measured circulating MT-DNA levels in prospectively collected, cell-free plasma samples from 97 subjects with COVID-19 at hospital presentation. Our primary outcome was mortality. Intensive care unit (ICU) admission, intubation, vasopressor, and renal replacement therapy requirements were secondary outcomes. Multivariate regression analysis determined whether MT-DNA levels were independent of other reported COVID-19 risk factors. Receiver operating characteristic and area under the curve assessments were used to compare MT-DNA levels with established and emerging inflammatory markers of COVID-19.Results Circulating MT-DNA levels were highly elevated in patients who eventually died or required ICU admission, intubation, vasopressor use, or renal replacement therapy. Multivariate regression revealed that high circulating MT-DNA was an independent risk factor for these outcomes after adjusting for age, sex, and comorbidities. We also found that circulating MT-DNA levels had a similar or superior area under the curve when compared against clinically established measures of inflammation and emerging markers currently of interest as investigational targets for COVID-19 therapy.Conclusion These results show that high circulating MT-DNA levels are a potential early indicator for poor COVID-19 outcomes.Funding Washington University Institute of Clinical Translational Sciences COVID-19 Research Program and Washington University Institute of Clinical Translational Sciences (ICTS) NIH grant UL1TR002345.

Authors

Davide Scozzi, Marlene Cano, Lina Ma, Dequan Zhou, Ji Hong Zhu, Jane A. O’Halloran, Charles Goss, Adriana M. Rauseo, Zhiyi Liu, Sanjaya K. Sahu, Valentina Peritore, Monica Rocco, Alberto Ricci, Rachele Amodeo, Laura Aimati, Mohsen Ibrahim, Ramsey Hachem, Daniel Kreisel, Philip A. Mudd, Hrishikesh S. Kulkarni, Andrew E. Gelman

×

Usage data is cumulative from December 2022 through December 2023.

Usage JCI PMC
Text version 2,204 514
PDF 115 126
Figure 134 9
Table 109 0
Supplemental data 62 11
Citation downloads 41 0
Totals 2,665 660
Total Views 3,325
(Click and drag on plot area to zoom in. Click legend items above to toggle)

Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.

Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.

Advertisement

Copyright © 2023 American Society for Clinical Investigation
ISSN 2379-3708

Sign up for email alerts