TY - JOUR
T1 - Neutrophil Extracellular Trap Formation Potential Correlates with Lung Disease Severity in COVID-19 Patients
AU - Kinnare, Nedha
AU - Hook, Jessica S.
AU - Patel, Parth A.
AU - Monson, Nancy L.
AU - Moreland, Jessica G.
N1 - Publisher Copyright:
© 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
PY - 2022/4
Y1 - 2022/4
N2 - Severe lung inflammation is common in life-threatening coronavirus disease 2019 (COVID-19). This study tested the hypothesis that polymorphonuclear (PMN, neutrophil) phenotype early in the course of disease progression would predict peak lung disease severity in patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It is increasingly evident that PMN activation contributes to tissue injury resulting from extracellular reactive oxygen species generation, granule exocytosis with release of proteases, neutrophil extracellular trap (NET) formation, and release of cytokines. The current study focuses on PMN activation in response to SARS-CoV-2 infection, specifically, the association between NETs and lung disease. This is a prospective cohort study at an academic medical center with patients enrolled within 4 days of admission at 3 tertiary hospitals: Clements University Hospital, Parkland Memorial Hospital, and Children’s Health in Dallas, TX. Patients were categorized as having minimal or moderate to severe lung disease based on peak respiratory support. Healthy donor controls matched for age, sex, race, and ethnicity were also enrolled. Neutrophils from COVID-19 patients displayed greater IL-8 expression, elastase release, and NET formation as compared with neutrophils from healthy donors. Importantly, neutrophils from COVID-19 patients had enhanced NET formation in the absence of any additional stimulus, not seen in PMN from healthy donors. Moreover, PMA-elicited NET formation by circulating PMN correlated with severity of lung disease. We speculate that neutrophil immuno-phenotyping can be used to predict lung disease severity in COVID-19 patients.
AB - Severe lung inflammation is common in life-threatening coronavirus disease 2019 (COVID-19). This study tested the hypothesis that polymorphonuclear (PMN, neutrophil) phenotype early in the course of disease progression would predict peak lung disease severity in patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It is increasingly evident that PMN activation contributes to tissue injury resulting from extracellular reactive oxygen species generation, granule exocytosis with release of proteases, neutrophil extracellular trap (NET) formation, and release of cytokines. The current study focuses on PMN activation in response to SARS-CoV-2 infection, specifically, the association between NETs and lung disease. This is a prospective cohort study at an academic medical center with patients enrolled within 4 days of admission at 3 tertiary hospitals: Clements University Hospital, Parkland Memorial Hospital, and Children’s Health in Dallas, TX. Patients were categorized as having minimal or moderate to severe lung disease based on peak respiratory support. Healthy donor controls matched for age, sex, race, and ethnicity were also enrolled. Neutrophils from COVID-19 patients displayed greater IL-8 expression, elastase release, and NET formation as compared with neutrophils from healthy donors. Importantly, neutrophils from COVID-19 patients had enhanced NET formation in the absence of any additional stimulus, not seen in PMN from healthy donors. Moreover, PMA-elicited NET formation by circulating PMN correlated with severity of lung disease. We speculate that neutrophil immuno-phenotyping can be used to predict lung disease severity in COVID-19 patients.
KW - IL-8
KW - SARS-CoV-2
KW - SIRS
KW - elastase
KW - immunophenotyping
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U2 - 10.1007/s10753-021-01585-x
DO - 10.1007/s10753-021-01585-x
M3 - Article
C2 - 34718927
AN - SCOPUS:85118297414
SN - 0360-3997
VL - 45
SP - 800
EP - 811
JO - Inflammation
JF - Inflammation
IS - 2
ER -