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Usage Information

CXCL12 ameliorates neutrophilia and disease severity in SARS-CoV-2 infection
Jian Zheng, … , Jun Yan, Stanley Perlman
Jian Zheng, … , Jun Yan, Stanley Perlman
Published January 7, 2025
Citation Information: J Clin Invest. 2025;135(4):e188222. https://doi.org/10.1172/JCI188222.
View: Text | PDF
Research Article Infectious disease

CXCL12 ameliorates neutrophilia and disease severity in SARS-CoV-2 infection

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Abstract

Neutrophils, particularly low-density neutrophils (LDNs), are believed to contribute to acute COVID-19 severity. Here, we showed that neutrophilia can be detected acutely and even months after SARS-CoV-2 infection in patients and mice, while neutrophil depletion reduced disease severity in mice. A key factor in neutrophilia and severe disease in infected mice was traced to the chemokine CXCL12 secreted by bone marrow cells and unexpectedly, endothelial cells. CXCL12 levels were negatively correlated with LDN numbers in longitudinal analyses of patient blood samples. CXCL12 blockade in SARS-CoV-2–infected mice increased blood/lung neutrophil numbers, thereby accelerating disease progression without changing lung virus titers. The exaggerated mortality caused by CXCL12 blockade could be reversed by neutrophil depletion. In addition, blocking interactions between SARS-CoV-2 and angiotensin-converting enzyme 2 (ACE2) reduced CXCL12 levels, suggesting a signal transduction from virus-mediated ACE2 ligation to increased CXCL12 secretion. Collectively, these results demonstrate a previously unappreciated role of CXCL12 in diminishing neutrophilia, including low-density neutrophilia, and its deleterious effects in SARS-CoV-2 infections. The results also support the involvement of SARS-CoV-2–endothelial cell interactions in viral pathogenesis.

Authors

Jian Zheng, Hima Dhakal, Enya Qing, Rejeena Shrestha, Anne E. Geller, Samantha M. Morrissey, Divyasha Saxena, Xiaoling Hu, Hong Li, Haiyan Li, Kevin Wilhelmsen, Linder H. Wendt, Klaus Klumpp, Patrick S. Hume, William J. Janssen, Rachel Brody, Kenneth E. Palmer, Silvia M. Uriarte, Patrick Ten Eyck, David K. Meyerholz, Michael L. Merchant, Kenneth McLeish, Tom Gallagher, Jiapeng Huang, Jun Yan, Stanley Perlman

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Usage data is cumulative from January 2025 through September 2025.

Usage JCI PMC
Text version 3,496 192
PDF 1,214 43
Figure 493 2
Table 170 0
Supplemental data 293 10
Citation downloads 107 0
Totals 5,773 247
Total Views 6,020

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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