Nannan Zhang1,2,3,4, Liuluan Zhu5,6, Yue Zhang5,6, Chun Zhou7, Rui Song8, Xiaoyu Yang5,6, Linna Huang1,2,3, Shuyu Xiong1,2,3, Xu Huang1,2, Fei Xu7, Yajie Wang7, Gang Wan9, Zhihai Chen8, Ang Li10, Qingyuan Zhan1,2, Hui Zeng5,6. 1. Center for Respiratory Diseases, China-Japan Friendship Hospital, Beijing, China. 2. Department of Pulmonary and Critical Care Medicine, China-Japan Friendship Hospital, Beijing, China. 3. National Clinical Research Center for Respiratory Diseases, Beijing, China. 4. Department of Pulmonary and Critical Care Medicine, Affiliated Hospital of Jining Medical University, Jining, Shandong, China. 5. Institute of Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing, China. 6. Beijing Key Laboratory of Emerging Infectious Diseases, Beijing, China. 7. Department of Clinical Laboratory, Beijing Ditan Hospital, Capital Medical University, Beijing, China. 8. The National Clinical Key Department of Infectious Disease, Beijing Ditan Hospital, Capital Medical University, Beijing, China. 9. Statistics Room, Beijing Ditan Hospital, Capital Medical University, Beijing, China. 10. Intensive Care Unit, Beijing Ditan Hospital, Capital Medical University, Beijing, China.
Abstract
BACKGROUND: High levels of circulating neutrophil extracellular traps (NETs) are associated with a poor prognosis in influenza A infection. It remains unclear whether NETs in the plasma or bronchoalveolar lavage fluid (BALF) can predict clinical outcomes in influenza. METHODS: One hundred eighteen patients who were diagnosed with H1N1 influenza in 2017-2018 were recruited. The NETs were assessed in plasma and BALF samples by quantifying cell-free deoxyribonucleic acid (cfDNA) and protein-DNA complexes. Predictions of severe illness and 60-day mortality were analyzed with receiver operating characteristic curves. RESULTS: The NET levels were significantly elevated in the BALF and contributed to the pathology of lungs, yet it was not associated with disease severity or mortality in patients severely infected with H1N1. Plasma NET levels were significantly increased in the patients with severe influenza and positively correlated with the oxygen index and sequential organ failure assessment scores. High levels of plasma cfDNA (>286.6 ng/mL) or histone-bound DNA (>9.4 ng/mL) discriminated severe influenza from mild, and even higher levels of cfDNA (>306.3 ng/mL) or histone-bound DNA (>23.1 ng/mL) predicted fatal outcomes in severely ill patients. CONCLUSIONS: The cfDNA and histone-bound DNA in plasma represent early predictive biomarkers for the prognosis of influenza.
BACKGROUND: High levels of circulating neutrophil extracellular traps (NETs) are associated with a poor prognosis in influenza A infection. It remains unclear whether NETs in the plasma or bronchoalveolar lavage fluid (BALF) can predict clinical outcomes in influenza. METHODS: One hundred eighteen patients who were diagnosed with H1N1 influenza in 2017-2018 were recruited. The NETs were assessed in plasma and BALF samples by quantifying cell-free deoxyribonucleic acid (cfDNA) and protein-DNA complexes. Predictions of severe illness and 60-day mortality were analyzed with receiver operating characteristic curves. RESULTS: The NET levels were significantly elevated in the BALF and contributed to the pathology of lungs, yet it was not associated with disease severity or mortality in patients severely infected with H1N1. Plasma NET levels were significantly increased in the patients with severe influenza and positively correlated with the oxygen index and sequential organ failure assessment scores. High levels of plasma cfDNA (>286.6 ng/mL) or histone-bound DNA (>9.4 ng/mL) discriminated severe influenza from mild, and even higher levels of cfDNA (>306.3 ng/mL) or histone-bound DNA (>23.1 ng/mL) predicted fatal outcomes in severely ill patients. CONCLUSIONS: The cfDNA and histone-bound DNA in plasma represent early predictive biomarkers for the prognosis of influenza.
Authors: Jose Otto Reusing; Jongwon Yoo; Amishi Desai; Katya Brossart; Sarah McCormick; Allyson Koyen Malashevich; Michelle S Bloom; Gordon Fehringer; Roseann White; Paul R Billings; Hossein Tabriziani; Zachary P Demko; Philippe Gauthier; Sanjeev K Akkina; Elias David-Neto Journal: Transplant Proc Date: 2022-03-15 Impact factor: 1.014