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Usage Information

Autoantibodies stabilize neutrophil extracellular traps in COVID-19
Yu Zuo, … , Yogendra Kanthi, Jason S. Knight
Yu Zuo, … , Yogendra Kanthi, Jason S. Knight
Published June 24, 2021
Citation Information: JCI Insight. 2021;6(15):e150111. https://doi.org/10.1172/jci.insight.150111.
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Research Article COVID-19

Autoantibodies stabilize neutrophil extracellular traps in COVID-19

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Abstract

The release of neutrophil extracellular traps (NETs) by hyperactive neutrophils is recognized to play an important role in the thromboinflammatory milieu inherent to severe presentations of COVID-19. At the same time, a variety of functional autoantibodies have been observed in individuals with severe COVID-19, where they likely contribute to immunopathology. Here, we aimed to determine the extent to which autoantibodies might target NETs in COVID-19 and, if detected, to elucidate their potential functions and clinical associations. We measured anti-NET antibodies in 328 individuals hospitalized with COVID-19 alongside 48 healthy controls. We found high anti-NET activity in the IgG and IgM fractions of 27% and 60% of patients, respectively. There was a strong correlation between anti–NET IgG and anti–NET IgM. Both anti–NET IgG and anti–NET IgM tracked with high levels of circulating NETs, impaired oxygenation efficiency, and high circulating D-dimer. Furthermore, patients who required mechanical ventilation had a greater burden of anti-NET antibodies than did those not requiring oxygen supplementation. Levels of anti–NET IgG (and, to a lesser extent, anti–NET IgM) demonstrated an inverse correlation with the efficiency of NET degradation by COVID-19 sera. Furthermore, purified IgG from COVID-19 sera with high levels of anti-NET antibodies impaired the ability of healthy control serum to degrade NETs. In summary, many individuals hospitalized with COVID-19 have anti-NET antibodies, which likely impair NET clearance and may potentiate SARS-CoV-2–mediated thromboinflammation.

Authors

Yu Zuo, Srilakshmi Yalavarthi, Sherwin A. Navaz, Claire K. Hoy, Alyssa Harbaugh, Kelsey Gockman, Melanie Zuo, Jacqueline A. Madison, Hui Shi, Yogendra Kanthi, Jason S. Knight

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Usage data is cumulative from September 2022 through September 2023.

Usage JCI PMC
Text version 952 422
PDF 78 84
Figure 168 3
Table 24 0
Supplemental data 42 4
Citation downloads 49 0
Totals 1,313 513
Total Views 1,826

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.

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