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1.
Journal of Clinical Investigation ; 130(12):6588-6599, 2020.
Article in English | ProQuest Central | ID: covidwho-1021206

ABSTRACT

BACKGROUND. Marked progress is achieved in understanding the physiopathology of coronavirus disease 2019 (COVID-19), which caused a global pandemic. However, the CD4· T cell population critical for antibody response in COVID-19 is poorly understood. METHODS. In this study, we provided a comprehensive analysis of peripheral CD4· T cells from 13 COVID-19 convalescent patients, defined as confirmed free of SARS-CoV-2 for 2 to 4 weeks, using flow cytometry and magnetic chemiluminescence enzyme antibody immunoassay. The data were correlated with clinical characteristics. RESULTS. We observed that, relative to healthy individuals, convalescent patients displayed an altered peripheral CD4· T cell spectrum. Specifically, consistent with other viral infections, cTfh1 cells associated with SARS-CoV-2-targeting antibodies were found in COVID-19 covalescent patients. Individuals with severe disease showed higher frequencies of Tem and Tfh-em cells but lower frequencies of Tcm, Tfh-cm, Tfr, and Tnaive cells, compared with healthy individuals and patients with mild and moderate disease. Interestingly, a higher frequency of cTfh-em cells correlated with a lower blood oxygen level, recorded at the time of admission, in convalescent patients. These observations might constitute residual effects by which COVID-19 can impact the homeostasis of CD4· T cells in the long-term and explain the highest ratio of class-switched virus-specific antibody producing individuals found in our severe COVID-19 cohort. CONCLUSION. Our study demonstrated a close connection between CD4· T cells and antibody production in COVID-19 convalescent patients. FUNDING. Six Talent Peaks Project in Jiangsu Province and the National Natural Science Foundation of China (NSFC).

2.
J Clin Invest ; 130(12): 6588-6599, 2020 12 01.
Article in English | MEDLINE | ID: covidwho-1013100

ABSTRACT

BACKGROUNDMarked progress is achieved in understanding the physiopathology of coronavirus disease 2019 (COVID-19), which caused a global pandemic. However, the CD4+ T cell population critical for antibody response in COVID-19 is poorly understood.METHODSIn this study, we provided a comprehensive analysis of peripheral CD4+ T cells from 13 COVID-19 convalescent patients, defined as confirmed free of SARS-CoV-2 for 2 to 4 weeks, using flow cytometry and magnetic chemiluminescence enzyme antibody immunoassay. The data were correlated with clinical characteristics.RESULTSWe observed that, relative to healthy individuals, convalescent patients displayed an altered peripheral CD4+ T cell spectrum. Specifically, consistent with other viral infections, cTfh1 cells associated with SARS-CoV-2-targeting antibodies were found in COVID-19 covalescent patients. Individuals with severe disease showed higher frequencies of Tem and Tfh-em cells but lower frequencies of Tcm, Tfh-cm, Tfr, and Tnaive cells, compared with healthy individuals and patients with mild and moderate disease. Interestingly, a higher frequency of cTfh-em cells correlated with a lower blood oxygen level, recorded at the time of admission, in convalescent patients. These observations might constitute residual effects by which COVID-19 can impact the homeostasis of CD4+ T cells in the long-term and explain the highest ratio of class-switched virus-specific antibody producing individuals found in our severe COVID-19 cohort.CONCLUSIONOur study demonstrated a close connection between CD4+ T cells and antibody production in COVID-19 convalescent patients.FUNDINGSix Talent Peaks Project in Jiangsu Province and the National Natural Science Foundation of China (NSFC).


Subject(s)
Antibodies, Viral/immunology , Antibody Formation , CD4-Positive T-Lymphocytes/immunology , COVID-19/immunology , Convalescence , SARS-CoV-2/immunology , T-Lymphocyte Subsets/immunology , Adult , Aged , Antibodies, Viral/blood , CD4-Positive T-Lymphocytes/metabolism , COVID-19/blood , Female , Humans , Male , Middle Aged , SARS-CoV-2/metabolism , T-Lymphocyte Subsets/metabolism
3.
SSRN; 2020.
Preprint | SSRN | ID: ppcovidwho-1158

ABSTRACT

Background: A critical issue is to identify COVID-19 patients early who develosevere pneumonia. Understanding the relationshiof the laboratory parameters an

4.
J Clin Lab Anal ; 34(10): e23527, 2020 Oct.
Article in English | MEDLINE | ID: covidwho-734171

ABSTRACT

BACKGROUND: Serum amyloid A (SAA), interleukin-6 (IL-6) and neutrophil-to-lymphocyte ratio (NLR) play critical roles in inflammation and are used in clinical laboratories as indicators of inflammation-related diseases. We aimed to provide potential laboratory basis for auxiliary distinguishing coronavirus disease (COVID-19) by monitoring above indicators. METHODS: A total of 84 patients with confirmed COVID-19 were enrolled in the study. Baseline characteristics and laboratory results were collected and analyzed. Receiver operating characteristic (ROC) curve analysis was used to combined detection of SAA and IL-6 in patients with COVID-19, and independent risk factors for severity of COVID-19 were assessed by using binary logistic regression. RESULTS: The main clinical symptoms of patients with COVID-19 were fever (98.8%), fatigue (61.9%), and dry cough (58.3%). SAA, IL-6, and NLR were significantly higher in patients with COVID-19 (all P < .001), and compared with nonsevere patients, three indicators of severe patients were significantly elevated. Besides, combined detection of SAA and IL-6 better separates healthy people from patients with COVID-19 than detection of SAA or IL-6 alone. In addition, elevated SAA, IL-6, and NLR can be used as independent variables for predicting the severity of patients with COVID-19. CONCLUSION: Serum amyloid A and IL-6 could be used as addition parameters to helping the distinguish of patients with COVID-19 from healthy people, and can provide potential basis for separating patients with nonsevere and severe clinical signs.


Subject(s)
Coronavirus Infections , Interleukin-6/blood , Pandemics , Pneumonia, Viral , Serum Amyloid A Protein/analysis , Adult , Betacoronavirus , COVID-19 , Coronavirus Infections/blood , Coronavirus Infections/diagnosis , Coronavirus Infections/epidemiology , Cross-Sectional Studies , Female , Humans , Male , Middle Aged , Pneumonia, Viral/blood , Pneumonia, Viral/diagnosis , Pneumonia, Viral/epidemiology , ROC Curve , Risk Factors , SARS-CoV-2
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