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1.
J Allergy Clin Immunol ; 148(6): 1481-1492.e2, 2021 12.
Article in English | MEDLINE | ID: covidwho-1555521

ABSTRACT

BACKGROUND: Understanding the complexities of immune memory to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is key to gain insights into the durability of protective immunity against reinfection. OBJECTIVE: We sought to evaluate the immune memory to SARS-CoV-2 in convalescent patients with longer follow-up time. METHODS: SARS-CoV-2-specific humoral and cellular responses were assessed in convalescent patients with coronavirus disease 2019 (COVID-19) at 1 year postinfection. RESULTS: A total of 78 convalescent patients with COVID-19 (26 moderate, 43 severe, and 9 critical) were recruited after 1 year of recovery. The positive rates of both anti-receptor-binding domain and antinucleocapsid antibodies were 100%, whereas we did not observe a statistical difference in antibody levels among different severity groups. Accordingly, the prevalence of neutralizing antibodies (nAbs) reached 93.59% in convalescent patients. Although nAb titers displayed an increasing trend in convalescent patients with increased severity, the difference failed to achieve statistical significance. Notably, there was a significant correlation between nAb titers and anti-receptor-binding domain levels. Interestingly, SARS-CoV-2-specific T cells could be robustly maintained in convalescent patients, and their number was positively correlated with both nAb titers and anti-receptor-binding domain levels. Amplified SARS-CoV-2-specific CD4+ T cells mainly produced a single cytokine, accompanying with increased expression of exhaustion markers including PD-1, Tim-3, TIGIT, CTLA-4, and CD39, while the proportion of multifunctional cells was low. CONCLUSIONS: Robust SARS-CoV-2-specific humoral and cellular responses are maintained in convalescent patients with COVID-19 at 1 year postinfection. However, the dysfunction of SARS-CoV-2-specific CD4+ T cells supports the notion that vaccination is needed in convalescent patients for preventing reinfection.

2.
Front Immunol ; 12: 697622, 2021.
Article in English | MEDLINE | ID: covidwho-1518482

ABSTRACT

Objectives: The longitudinal and systematic evaluation of immunity in coronavirus disease 2019 (COVID-19) patients is rarely reported. Methods: Parameters involved in innate, adaptive, and humoral immunity were continuously monitored in COVID-19 patients from onset of illness until 45 days after symptom onset. Results: This study enrolled 27 mild, 47 severe, and 46 deceased COVID-19 patients. Generally, deceased patients demonstrated a gradual increase of neutrophils and IL-6 but a decrease of lymphocytes and platelets after the onset of illness. Specifically, sustained low numbers of CD8+ T cells, NK cells, and dendritic cells were noted in deceased patients, while these cells gradually restored in mild and severe patients. Furthermore, deceased patients displayed a rapid increase of HLA-DR expression on CD4+ T cells in the early phase, but with a low level of overall CD45RO and HLA-DR expressions on CD4+ and CD8+ T cells, respectively. Notably, in the early phase, deceased patients showed a lower level of plasma cells and antigen-specific IgG, but higher expansion of CD16+CD14+ proinflammatory monocytes and HLA-DR-CD14+ monocytic-myeloid-derived suppressor cells (M-MDSCs) than mild or severe patients. Among these immunological parameters, M-MDSCs showed the best performance in predicting COVID-19 mortality, when using a cutoff value of ≥10%. Cluster analysis found a typical immunological pattern in deceased patients on day 9 after onset, which was characterized as the increase of inflammatory markers (M-MDSCs, neutrophils, CD16+CD14+ monocytes, and IL-6) but a decrease of host immunity markers. Conclusions: This study systemically characterizes the kinetics of immunity of COVID-19, highlighting the importance of immunity in patient prognosis.


Subject(s)
COVID-19/immunology , SARS-CoV-2 , Adaptive Immunity , Aged , Aged, 80 and over , Antibodies, Viral/blood , B-Lymphocytes/immunology , COVID-19/blood , COVID-19/classification , COVID-19/physiopathology , Cytokines/blood , Dendritic Cells/immunology , Female , Humans , Immunity, Innate , Immunoglobulin G/blood , Killer Cells, Natural/immunology , Lymphocyte Count , Male , Middle Aged , SARS-CoV-2/immunology , Severity of Illness Index , T-Lymphocytes/immunology
3.
J Allergy Clin Immunol ; 148(6): 1481-1492.e2, 2021 12.
Article in English | MEDLINE | ID: covidwho-1428085

ABSTRACT

BACKGROUND: Understanding the complexities of immune memory to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is key to gain insights into the durability of protective immunity against reinfection. OBJECTIVE: We sought to evaluate the immune memory to SARS-CoV-2 in convalescent patients with longer follow-up time. METHODS: SARS-CoV-2-specific humoral and cellular responses were assessed in convalescent patients with coronavirus disease 2019 (COVID-19) at 1 year postinfection. RESULTS: A total of 78 convalescent patients with COVID-19 (26 moderate, 43 severe, and 9 critical) were recruited after 1 year of recovery. The positive rates of both anti-receptor-binding domain and antinucleocapsid antibodies were 100%, whereas we did not observe a statistical difference in antibody levels among different severity groups. Accordingly, the prevalence of neutralizing antibodies (nAbs) reached 93.59% in convalescent patients. Although nAb titers displayed an increasing trend in convalescent patients with increased severity, the difference failed to achieve statistical significance. Notably, there was a significant correlation between nAb titers and anti-receptor-binding domain levels. Interestingly, SARS-CoV-2-specific T cells could be robustly maintained in convalescent patients, and their number was positively correlated with both nAb titers and anti-receptor-binding domain levels. Amplified SARS-CoV-2-specific CD4+ T cells mainly produced a single cytokine, accompanying with increased expression of exhaustion markers including PD-1, Tim-3, TIGIT, CTLA-4, and CD39, while the proportion of multifunctional cells was low. CONCLUSIONS: Robust SARS-CoV-2-specific humoral and cellular responses are maintained in convalescent patients with COVID-19 at 1 year postinfection. However, the dysfunction of SARS-CoV-2-specific CD4+ T cells supports the notion that vaccination is needed in convalescent patients for preventing reinfection.

4.
International Journal of Infectious Diseases ; 95:436-440, 2020.
Article in English | CAB Abstracts | ID: covidwho-1409652

ABSTRACT

Background: The differential diagnosis between novel coronavirus pneumonia patients (NCPP) and influenza patients (IP) remains a challenge in clinical practice.

5.
Front Cell Infect Microbiol ; 10: 586054, 2020.
Article in English | MEDLINE | ID: covidwho-1145559

ABSTRACT

Background: The outbreak of coronavirus disease 2019 (COVID-19) has become a global public health concern. Many inpatients with COVID-19 have shown clinical symptoms related to sepsis, which will aggravate the deterioration of patients' condition. We aim to diagnose Viral Sepsis Caused by SARS-CoV-2 by analyzing laboratory test data of patients with COVID-19 and establish an early predictive model for sepsis risk among patients with COVID-19. Methods: This study retrospectively investigated laboratory test data of 2,453 patients with COVID-19 from electronic health records. Extreme gradient boosting (XGBoost) was employed to build four models with different feature subsets of a total of 69 collected indicators. Meanwhile, the explainable Shapley Additive ePlanation (SHAP) method was adopted to interpret predictive results and to analyze the feature importance of risk factors. Findings: The model for classifying COVID-19 viral sepsis with seven coagulation function indicators achieved the area under the receiver operating characteristic curve (AUC) 0.9213 (95% CI, 89.94-94.31%), sensitivity 97.17% (95% CI, 94.97-98.46%), and specificity 82.05% (95% CI, 77.24-86.06%). The model for identifying COVID-19 coagulation disorders with eight features provided an average of 3.68 (±) 4.60 days in advance for early warning prediction with 0.9298 AUC (95% CI, 86.91-99.04%), 82.22% sensitivity (95% CI, 67.41-91.49%), and 84.00% specificity (95% CI, 63.08-94.75%). Interpretation: We found that an abnormality of the coagulation function was related to the occurrence of sepsis and the other routine laboratory test represented by inflammatory factors had a moderate predictive value on coagulopathy, which indicated that early warning of sepsis in COVID-19 patients could be achieved by our established model to improve the patient's prognosis and to reduce mortality.


Subject(s)
COVID-19/blood , Sepsis/virology , Adult , Aged , COVID-19/diagnosis , COVID-19/epidemiology , COVID-19 Testing , China/epidemiology , Female , Humans , Logistic Models , Machine Learning , Male , Middle Aged , Prognosis , ROC Curve , Retrospective Studies , Risk Factors , SARS-CoV-2/isolation & purification , Sepsis/blood , Sepsis/diagnosis
6.
Front Med (Lausanne) ; 7: 374, 2020.
Article in English | MEDLINE | ID: covidwho-646639

ABSTRACT

Background: The predictive value of prealbumin for the prognosis of coronavirus disease 2019 (COVID-19) has not been extensively investigated. Methods: A total of 1,115 patients with laboratory-confirmed COVID-19 were enrolled at Tongji hospital from February to April 2020 and classified into fatal (n = 129) and recovered (n = 986) groups according to the patient's outcome. Prealbumin and other routine laboratory indicators were measured simultaneously. Results: The level of prealbumin on admission was significantly lower in fatal patients than in recovered patients. For predicting the prognosis of COVID-19, the performance of prealbumin was better than most routine laboratory indicators, such as albumin, lymphocyte count, neutrophil count, hypersensitive C-reactive protein, d-dimer, lactate dehydrogenase, creatinine, and hypersensitive cardiac troponin I. When a threshold of 126 mg/L was used to discriminate between fatal and recovered patients, the sensitivity and specificity of prealbumin were, respectively, 78.29 and 90.06%. Furthermore, a model based on the combination of nine indexes showed an improved performance in predicting the death of patients with COVID-19. Using a cut-off value of 0.19, the prediction model was able to distinguish between fatal and recovered individuals with a sensitivity of 86.82% and a specificity of 90.37%. Conclusions: A lower level of prealbumin on admission may indicate a worse outcome of COVID-19. Immune and nutritional status may be vital factors for predicting disease progression in the early stage of COVID-19.

7.
J Clin Immunol ; 40(7): 960-969, 2020 10.
Article in English | MEDLINE | ID: covidwho-641161

ABSTRACT

BACKGROUND: There are currently rare satisfactory markers for predicting the death of patients with coronavirus disease 2019 (COVID-19). The aim of this study is to establish a model based on the combination of serum cytokines and lymphocyte subsets for predicting the prognosis of the disease. METHODS: A total of 739 participants with COVID-19 were enrolled at Tongji Hospital from February to April 2020 and classified into fatal (n = 51) and survived (n = 688) groups according to the patient's outcome. Cytokine profile and lymphocyte subset analysis was performed simultaneously. RESULTS: The fatal patients exhibited a significant lower number of lymphocytes including B cells, CD4+ T cells, CD8+ T cells, and NK cells and remarkably higher concentrations of cytokines including interleukin-2 receptor, interleukin-6, interleukin-8, and tumor necrosis factor-α on admission compared with the survived subjects. A model based on the combination of interleukin-8 and the numbers of CD4+ T cells and NK cells showed a good performance in predicting the death of patients with COVID-19. When the threshold of 0.075 was used, the sensitivity and specificity of the prediction model were 90.20% and 90.26%, respectively. Meanwhile, interleukin-8 was found to have a potential value in predicting the length of hospital stay until death. CONCLUSIONS: Significant increase of cytokines and decrease of lymphocyte subsets are found positively correlated with in-hospital death. A model based on the combination of three markers provides an attractive approach to predict the prognosis of COVID-19.


Subject(s)
Betacoronavirus/immunology , Coronavirus Infections/mortality , Cytokines/blood , Lymphocyte Subsets/immunology , Models, Biological , Pneumonia, Viral/mortality , Aged , Aged, 80 and over , Betacoronavirus/genetics , Betacoronavirus/isolation & purification , Biomarkers/blood , COVID-19 , COVID-19 Testing , China/epidemiology , Clinical Laboratory Techniques/methods , Coronavirus Infections/blood , Coronavirus Infections/diagnosis , Coronavirus Infections/epidemiology , Coronavirus Infections/immunology , Cytokines/immunology , Female , Humans , Length of Stay , Lymphocyte Count , Male , Middle Aged , Pandemics , Pneumonia, Viral/blood , Pneumonia, Viral/epidemiology , Pneumonia, Viral/immunology , Prognosis , RNA, Viral/isolation & purification , Reverse Transcriptase Polymerase Chain Reaction , Risk Assessment/methods , SARS-CoV-2
8.
Travel Med Infect Dis ; 36: 101782, 2020.
Article in English | MEDLINE | ID: covidwho-595825

ABSTRACT

INTRODUCTION: There are currently no satisfactory methods for predicting the outcome of Coronavirus Disease-2019 (COVID-19). The aim of this study is to establish a model for predicting the prognosis of the disease. METHODS: The laboratory results were collected from 54 deceased COVID-19 patients on admission and before death. Another 54 recovered COVID-19 patients were enrolled as control cases. RESULTS: Many laboratory indicators, such as neutrophils, AST, γ-GT, ALP, LDH, NT-proBNP, Hs-cTnT, PT, APTT, D-dimer, IL-2R, IL-6, IL-8, IL-10, TNF-α, CRP, ferritin and procalcitonin, were all significantly increased in deceased patients compared with recovered patients on admission. In contrast, other indicators such as lymphocytes, platelets, total protein and albumin were significantly decreased in deceased patients on admission. Some indicators such as neutrophils and procalcitonin, others such as lymphocytes and platelets, continuously increased or decreased from admission to death in deceased patients respectively. Using these indicators alone had moderate performance in differentiating between recovered and deceased COVID-19 patients. A model based on combination of four indicators (P = 1/[1 + e-(-2.658+0.587×neutrophils - 2.087×lymphocytes - 0.01×platelets+0.004×IL-2R)]) showed good performance in predicting the death of COVID-19 patients. When cutoff value of 0.572 was used, the sensitivity and specificity of the prediction model were 90.74% and 94.44%, respectively. CONCLUSIONS: Using the current indicators alone is of modest value in differentiating between recovered and deceased COVID-19 patients. A prediction model based on combination of neutrophils, lymphocytes, platelets and IL-2R shows good performance in predicting the outcome of COVID-19.


Subject(s)
Coronavirus Infections/mortality , Pneumonia, Viral/mortality , Aged , Aged, 80 and over , Alkaline Phosphatase/metabolism , Aspartate Aminotransferases/metabolism , Betacoronavirus , C-Reactive Protein/metabolism , COVID-19 , Case-Control Studies , Coronavirus Infections/blood , Coronavirus Infections/metabolism , Female , Ferritins/metabolism , Fibrin Fibrinogen Degradation Products/metabolism , Humans , Interleukin-10/metabolism , Interleukin-6/metabolism , Interleukin-8/metabolism , L-Lactate Dehydrogenase/metabolism , Leukocyte Count , Lymphocyte Count , Male , Middle Aged , Models, Theoretical , Natriuretic Peptide, Brain/metabolism , Neutrophils , Pandemics , Partial Thromboplastin Time , Peptide Fragments/metabolism , Pneumonia, Viral/blood , Pneumonia, Viral/metabolism , Procalcitonin/metabolism , Prognosis , Prothrombin Time , ROC Curve , Receptors, Interleukin-2/metabolism , SARS-CoV-2 , Troponin T/metabolism , Tumor Necrosis Factor-alpha/metabolism , gamma-Glutamyltransferase/metabolism
9.
Int J Infect Dis ; 95: 436-440, 2020 Jun.
Article in English | MEDLINE | ID: covidwho-155290

ABSTRACT

BACKGROUND: The differential diagnosis between novel coronavirus pneumonia patients (NCPP) and influenza patients (IP) remains a challenge in clinical practice. METHODS: Between January 2018 and March 2020, 1,027 NCPP and 1,140 IP were recruited from Tongji hospital. Routine blood examination, biochemical indicators and coagulation function analysis were simultaneously performed in all participants. RESULTS: There was no sex predominance in NCPP. The NCPP were frequently encountered in the sixth and seventh decades of life. The mean age of NCPP (56±16 years) was higher than IP (47±17 years), but without statistical difference. Although most results of routine laboratory tests between NCPP and IP had no significant differences, some laboratory tests showed an obvious change in NCPP. It was observed that NCPP had significantly decreased white blood cells, alkaline phosphatase and d-dimer compared with IP. However, the results of lactate dehydrogenase, erythrocyte sedimentation rate and fibrinogen were significantly increased in NCPP compared with IP. The diagnostic model based on a combination of 18 routine laboratory indicators showed an area under the curve of 0.796 (95% CI, 0.777-0.814), with a sensitivity of 46.93% and specificity of 90.09% when using a cut-off value of 0.598. CONCLUSIONS: Some routine laboratory results had statistical difference between NCPP and IP. A diagnostic model based on a combination of routine laboratory results provided an adjunct approach in the differential diagnosis between NCPP and IP.


Subject(s)
Betacoronavirus , Coronavirus Infections/diagnosis , Influenza, Human/diagnosis , Pneumonia, Viral/diagnosis , Adult , Aged , COVID-19 , COVID-19 Testing , Clinical Laboratory Techniques , Diagnosis, Differential , Female , Humans , Leukocyte Count , Male , Middle Aged , Pandemics , SARS-CoV-2
10.
JCI Insight ; 5(10)2020 05 21.
Article in English | MEDLINE | ID: covidwho-118074

ABSTRACT

BACKGROUNDThe coronavirus disease 2019 (COVID-19), infected by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has caused a severe outbreak throughout the world. The host immunity of COVID-19 patients is unknown.METHODSThe routine laboratory tests and host immunity in COVID-19 patients with different severity of illness were compared after patient admission.RESULTSA total of 65 SARS-CoV-2-positive patients were classified as having mild (n = 30), severe (n = 20), and extremely severe (n = 15) illness. Many routine laboratory tests, such as ferritin, lactate dehydrogenase, and D-dimer, were increased in severe and extremely severe patients. The absolute numbers of CD4+ T cells, CD8+ T cells, and B cells were gradually decreased with increased severity of illness. The activation markers such as HLA-DR and CD45RO expressed on CD4+ and CD8+ T cells were increased in severe and extremely severe patients compared with mild patients. The costimulatory molecule CD28 had opposite results. The percentage of natural Tregs was decreased in extremely severe patients. The percentage of IFN-γ-producing CD8+ T cells was increased in both severe and extremely severe patients compared with mild patients. The percentage of IFN-γ-producing CD4+ T cells was increased in extremely severe patients. IL-2R, IL-6, and IL-10 were all increased in extremely severe patients. The activation of DC and B cells was decreased in extremely severe patients.CONCLUSIONThe number and function of T cells are inconsistent in COVID-19 patients. The hyperfunction of CD4+ and CD8+ T cells is associated with the pathogenesis of extremely severe SARS-CoV-2 infection.FUNDINGThis work was funded by the National Mega Project on Major Infectious Disease Prevention (2017ZX10103005-007) and the Fundamental Research Funds for the Central Universities (2019kfyRCPY098).


Subject(s)
Coronavirus Infections/immunology , Coronavirus Infections/physiopathology , Pneumonia, Viral/immunology , Pneumonia, Viral/physiopathology , Betacoronavirus , CD4-Positive T-Lymphocytes/immunology , CD8-Positive T-Lymphocytes/immunology , COVID-19 , Cytokines/metabolism , Diagnostic Tests, Routine , Female , Humans , Immunity , Lymphocyte Count , Male , Middle Aged , Pandemics , SARS-CoV-2 , Severity of Illness Index , T-Lymphocytes/immunology
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