SARS-CoV-2 evolves to reduce but not abolish neutralizing action.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern (VOCs) have prolonged coronavirus disease 2019 (COVID-19) pandemic by escaping pre-existing immunity acquired by natural infection or vaccination. Elucidation of VOCs' mutation trends and evasion of neutralization is required to update current control measures. Mutations and the prevalence of VOCs were analyzed in the global immunization coverage rate context. Lentivirus-based pseudovirus neutralization analysis platforms for SARS-CoV-2 prototype strain (PS) and VOCs, containing Alpha, Beta, Gamma, Delta, and Omicron, were constructed based on the spike protein of each variant and HEK 293T cell line expressing the human angiotensin-converting enzyme 2 (hACE2) receptor on the surface, and an enhanced green fluorescent protein reporter. Serum samples from 65 convalescent individuals and 20 WIBP-CorV vaccine recipients and four therapeutic monoclonal antibodies (mAbs) namely imdevimab, casirivimab, bamlanivimab, and etesevimab were used to evaluate the neutralization potency against the variants. Pseudovirus-based neutralization assay platforms for PS and VOCs were established, and multiplicity of infection (MOI) was the key factor influencing the assay result. Compared to PS, VOCs may enhance the infectivity of hACE2-293T cells. Except for Alpha, other VOCs escaped neutralization to varying degrees. Attributed to favorable and emerging mutations, the current pandemic Omicron variant of all VOCs demonstrated the most significant neutralization-escaping ability to the sera and mAbs. Compared with the PS pseudovirus, Omicron had 15.7- and 3.71-fold decreases in the NT50 value (the highest serum dilution corresponding to a neutralization rate of 50%); and correspondingly, 90% and 43% of immunization or convalescent serum samples lost their neutralizing activity against the Omicron variant, respectively. Therefore, SARS-CoV-2 has evolved persistently with a strong ability to escape neutralization and prevailing against the established immune barrier. Our findings provide important clues to controlling the COVID-19 pandemic caused by new variants.

Correlation of Chest CT and RT-PCR Testing for Coronavirus Disease 2019 (COVID-19) in China: A Report of 1014 Cases.

Background Chest CT is used in the diagnosis of coronavirus disease 2019 (COVID-19) and is an important complement to reverse-transcription polymerase chain reaction (RT-PCR) tests. Purpose To investigate the diagnostic value and consistency of chest CT as compared with RT-PCR assay in COVID-19. Materials and Methods This study included 1014 patients in Wuhan, China, who underwent both chest CT and RT-PCR tests between January 6 and February 6, 2020. With use of RT-PCR as the reference standard, the performance of chest CT in the diagnosis of COVID-19 was assessed. In addition, for patients with multiple RT-PCR assays, the dynamic conversion of RT-PCR results (negative to positive, positive to negative) was analyzed as compared with serial chest CT scans for those with a time interval between RT-PCR tests of 4 days or more. Results Of the 1014 patients, 601 of 1014 (59%) had positive RT-PCR results and 888 of 1014 (88%) had positive chest CT scans. The sensitivity of chest CT in suggesting COVID-19 was 97% (95% confidence interval: 95%, 98%; 580 of 601 patients) based on positive RT-PCR results. In the 413 patients with negative RT-PCR results, 308 of 413 (75%) had positive chest CT findings. Of those 308 patients, 48% (103 of 308) were considered as highly likely cases and 33% (103 of 308) as probable cases. At analysis of serial RT-PCR assays and CT scans, the mean interval between the initial negative to positive RT-PCR results was 5.1 days ± 1.5; the mean interval between initial positive to subsequent negative RT-PCR results was 6.9 days ± 2.3. Of the 1014 patients, 60% (34 of 57) to 93% (14 of 15) had initial positive CT scans consistent with COVID-19 before (or parallel to) the initial positive RT-PCR results. Twenty-four of 57 patients (42%) showed improvement on follow-up chest CT scans before the RT-PCR results turned negative. Conclusion Chest CT has a high sensitivity for diagnosis of coronavirus disease 2019 (COVID-19). Chest CT may be considered as a primary tool for the current COVID-19 detection in epidemic areas. © RSNA, 2020 Online supplemental material is available for this article. A translation of this abstract in Farsi is available in the supplement. ترجمه چکیده این مقاله به فارسی، در ضمیمه موجود است.

Comparison of the Performance of 24 Severe Acute Respiratory Syndrome Coronavirus 2 Antibody Assays in the Diagnosis of Coronavirus Disease 2019 Patients.

Background: The accurate detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the key to control Coronavirus Disease-2019 (COVID-19). The performance of different antibody detection methods for diagnosis of COVID-19 is inconclusive. Methods: Between 16 February and 28 February 2020, 384 confirmed COVID-19 patients and 142 healthy controls were recruited. 24 different serological tests, including 4 enzyme-linked immunosorbent assays (EIAs), 10 chemiluminescent immunoassays (CLIAs), and 10 lateral flow immunoassays (LFIAs), were simultaneously performed. Results: The sensitivities of anti-SARS-CoV-2 IgG and IgM antibodies with different reagents ranged from 75 to 95.83% and 46.09 to 92.45%, respectively. The specificities of both anti-SARS-CoV-2 IgG and IgM were relatively high and comparable among different reagents, ranged from 88.03 to 100%. The area under the curves (AUCs) of different tests ranged from 0.733 to 0.984, and the AUCs of EIAs or CLIAs were significantly higher than those of LFIAs. The sensitivities of both IgG and IgM gradually increased with increase of onset time. After 3-4 weeks, the sensitivities of anti-SARS-CoV-2 IgG were maintained at a certain level but the sensitivities of IgM were gradually decreased. Six COVID-19 patients who displayed negative anti-SARS-CoV-2 results were associated with the factors such as older age, having underlying diseases, and using immunosuppressant. Conclusion: Besides the purpose of assessing the impact of the SARS-CoV-2 pandemic in the population, SARS-CoV-2 antibody assays may have an adjunct role in the diagnosis and exclusion of COVID-19, especially by using high-throughput technologies (EIAs or CLIAs).

Age- and Severity-Associated Humoral Immunity Response in COVID-19 Patients: A Cohort Study from Wuhan, China.

Age has been found to be the single most significant factor in COVID-19 severity and outcome. However, the age-related severity factors of COVID-19 have not been definitively established. In this study, we detected SARS-CoV-2-specific antibody responses and infectious disease-related blood indicators in 2360 sera from 783 COVID-19 patients, with an age range of 1-92 years. In addition, we recorded the individual information and clinical symptoms of the patients. We found that the IgG responses for S1, N, and ORF3a and the IgM for NSP7 were associated with severe COVID-19 at different ages. The IgM responses for the S-protein peptides S1-113 (aa 673-684) and S2-97 (aa 1262-1273) were associated with severe COVID-19 in patients aged <60. Furthermore, we found that the IgM for S1-113 and NSP7 may play a protective role in patients aged <60 and >80, respectively. Regarding clinical parameters, we analyzed the diagnostic ability of five clinical parameters for severe COVID-19 in six age groups and identified three-target panel, glucose, IL-6, myoglobin, IL-6, and NT proBNP as the appropriate diagnostic markers for severe COVID-19 in patients aged <41, 41-50, 51-60, 61-70, 71-80, and >80, respectively. The age-associated severity factors revealed here will facilitate our understanding of COVID-19 immunity and diagnosis, and eventually provide meaningful information for combating the pandemic.

Comparison of the Performance of 24 Severe Acute Respiratory Syndrome Coronavirus 2 Antibody Assays in the Diagnosis of Coronavirus Disease 2019 Patients

Background The accurate detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the key to control Coronavirus Disease-2019 (COVID-19). The performance of different antibody detection methods for diagnosis of COVID-19 is inconclusive. Methods Between 16 February and 28 February 2020, 384 confirmed COVID-19 patients and 142 healthy controls were recruited. 24 different serological tests, including 4 enzyme-linked immunosorbent assays (EIAs), 10 chemiluminescent immunoassays (CLIAs), and 10 lateral flow immunoassays (LFIAs), were simultaneously performed. Results The sensitivities of anti-SARS-CoV-2 IgG and IgM antibodies with different reagents ranged from 75 to 95.83% and 46.09 to 92.45%, respectively. The specificities of both anti-SARS-CoV-2 IgG and IgM were relatively high and comparable among different reagents, ranged from 88.03 to 100%. The area under the curves (AUCs) of different tests ranged from 0.733 to 0.984, and the AUCs of EIAs or CLIAs were significantly higher than those of LFIAs. The sensitivities of both IgG and IgM gradually increased with increase of onset time. After 3–4 weeks, the sensitivities of anti-SARS-CoV-2 IgG were maintained at a certain level but the sensitivities of IgM were gradually decreased. Six COVID-19 patients who displayed negative anti-SARS-CoV-2 results were associated with the factors such as older age, having underlying diseases, and using immunosuppressant. Conclusion Besides the purpose of assessing the impact of the SARS-CoV-2 pandemic in the population, SARS-CoV-2 antibody assays may have an adjunct role in the diagnosis and exclusion of COVID-19, especially by using high-throughput technologies (EIAs or CLIAs).

5-Hydroxymethylcytosine Signatures in Circulating Cell-Free DNA as Early Warning Biomarkers for COVID-19 Progression and Myocardial Injury.

Background: The symptoms of coronavirus disease 2019 (COVID-19) range from moderate to critical conditions, leading to death in some patients, and the early warning indicators of the COVID-19 progression and the occurrence of its serious complications such as myocardial injury are limited. Methods: We carried out a multi-center, prospective cohort study in three hospitals in Wuhan. Genome-wide 5-hydroxymethylcytosine (5hmC) profiles in plasma cell-free DNA (cfDNA) was used to identify risk factors for COVID-19 pneumonia and develop a machine learning model using samples from 53 healthy volunteers, 66 patients with moderate COVID-19, 99 patients with severe COVID-19, and 38 patients with critical COVID-19. Results: Our warning model demonstrated that an area under the curve (AUC) for 5hmC warning moderate patients developed into severe status was 0.81 (95% CI 0.77-0.85) and for severe patients developed into critical status was 0.92 (95% CI 0.89-0.96). We further built a warning model on patients with and without myocardial injury with the AUC of 0.89 (95% CI 0.84-0.95). Conclusion: This is the first study showing the utility of 5hmC as an accurate early warning marker for disease progression and myocardial injury in patients with COVID-19. Our results show that phosphodiesterase 4D and ten-eleven translocation 2 may be important markers in the progression of COVID-19 disease.

SARS-CoV-2-specific antibody response characteristics in COVID-19 patients of different ages.

Age has been found to be one of the main risk factors for the severity and outcome of COVID-19. However, differences in SARS-CoV-2 specific antibody responses among COVID-19 patients of different age groups remain largely unknown. In this study, we analyzed the IgG/IgM responses to 21 SARS-CoV-2 proteins and 197 peptides that fully cover the spike protein against 731 sera collected from 731 COVID-19 patients aged from 1 to We show that there is no overall difference in SARS-CoV-2 antibody responses in COVID-19 patients in the 4 age groups. By antibody response landscape maps, we find that the IgG response profiles of SARS-CoV-2 proteins are positively correlated with age. The S protein linear epitope map shows that the immunogenicity of the S-protein peptides is related to peptide sequence, disease severity and age of the COVID-19 patients. Furthermore, the enrichment analysis indicates that low S1 IgG responses are enriched in patients aged <50 and high S1 IgG responses are enriched in mild COVID-19 patients aged >60. In addition, high responses of non-structural/accessory proteins are enriched in severe COVID-19 patients aged >70. These results suggest the distinct immune response of IgG/IgM to each SARS-CoV-2 protein in patients of different age, which may facilitate a deeper understanding of the immune responses in COVID-19 patients.

Immunologic memory to SARS-CoV-2 in convalescent COVID-19 patients at 1 year postinfection.

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.

Anti-SARS-CoV-2 IgG responses are powerful predicting signatures for the outcome of COVID-19 patients.

Introduction: The COVID-19 global pandemic is far from ending. There is an urgent need to identify applicable biomarkers for early predicting the outcome of COVID-19. Growing evidences have revealed that SARS-CoV-2 specific antibodies evolved with disease progression and severity in COIVD-19 patients. Objectives: We assumed that antibodies may serve as biomarkers for predicting the clinical outcome of hospitalized COVID-19 patients on admission. Methods: By taking advantage of a newly developed SARS-CoV-2 proteome microarray, we surveyed IgG responses against 20 proteins of SARS-CoV-2 in 1034 hospitalized COVID-19 patients on admission and followed till 66 days. The microarray results were further correlated with clinical information, laboratory test results and patient outcomes. Cox proportional hazards model was used to explore the association between SARS-CoV-2 specific antibodies and COVID-19 mortality. Results: Nonsurvivors (n = 955) induced higher levels of IgG responses against most of non-structural proteins than survivors (n = 79) on admission. In particular, the magnitude of IgG antibodies against 8 non-structural proteins (NSP1, NSP4, NSP7, NSP8, NSP9, NSP10, RdRp, and NSP14) and 2 accessory proteins (ORF3b and ORF9b) possessed significant predictive power for patient death, even after further adjustments for demographics, comorbidities, and common laboratory biomarkers for disease severity (all with p trend < 0.05). Additionally, IgG responses to all of these 10 non-structural/accessory proteins were also associated with the severity of disease, and differential kinetics and serum positive rate of these IgG responses were confirmed in COVID-19 patients of varying severities within 20 days after symptoms onset. The area under curves (AUCs) for these IgG responses, determined by computational cross-validations, were between 0.62 and 0.71. Conclusions: Our findings might have important implications for improving clinical management of COVID-19 patients.

The Dynamic Immunological Parameter Landscape in Coronavirus Disease 2019 Patients With Different Outcomes.

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.

COVID-ONE-hi: The One-stop Database for COVID-19-specific Humoral Immunity and Clinical Parameters.

Coronavirus disease 2019 (COVID-19), which is caused by SARS-CoV-2, varies with regard to symptoms and mortality rates among populations. Humoral immunity plays critical roles in SARS-CoV-2 infection and recovery from COVID-19. However, differences in immune responses and clinical features among COVID-19 patients remain largely unknown. Here, we report a database for COVID-19-specific IgG/IgM immune responses and clinical parameters (named COVID-ONE-hi). COVID-ONE-hi is based on the data that contain the IgG/IgM responses to 24 full-length/truncated proteins corresponding to 20 of 28 known SARS-CoV-2 proteins and 199 spike protein peptides against 2360 serum samples collected from 783 COVID-19 patients. In addition, 96 clinical parameters for the 2360 serum samples and basic information for the 783 patients are integrated into the database. Furthermore, COVID-ONE-hi provides a dashboard for defining samples and a one-click analysis pipeline for a single group or paired groups. A set of samples of interest is easily defined by adjusting the scale bars of a variety of parameters. After the "START" button is clicked, one can readily obtain a comprehensive analysis report for further interpretation. COVID-ONE-hi is freely available at www.COVID-ONE.cn.

Kinetics of Neutralizing Antibody Response Underscores Clinical COVID-19 Progression.

BACKGROUND: Neutralizing antibody (nAb) response is generated following infection or immunization and plays an important role in the protection against a broad of viral infections. The role of nAb during clinical progression of coronavirus disease 2019 (COVID-19) remains little known. METHODS: 123 COVID-19 patients during hospitalization in Tongji Hospital were involved in this retrospective study. The patients were grouped based on the severity and outcome. The nAb responses of 194 serum samples were collected from these patients within an investigation period of 60 days after the onset of symptoms and detected by a pseudotyped virus neutralization assay. The detail data about onset time, disease severity and laboratory biomarkers, treatment, and clinical outcome of these participants were obtained from electronic medical records. The relationship of longitudinal nAb changes with each clinical data was further assessed. RESULTS: The nAb response in COVID-19 patients evidently experienced three consecutive stages, namely, rising, stationary, and declining periods. Patients with different severity and outcome showed differential dynamics of the nAb response over the course of disease. During the stationary phase (from 20 to 40 days after symptoms onset), all patients evolved nAb responses. In particular, high levels of nAb were elicited in severe and critical patients and older patients (≥60 years old). More importantly, critical but deceased COVID-19 patients showed high levels of several proinflammation cytokines, such as IL-2R, IL-8, and IL-6, and anti-inflammatory cytokine IL-10 in vivo, which resulted in lymphopenia, multiple organ failure, and the rapidly decreased nAb response. CONCLUSION: Our results indicate that nAb plays a crucial role in preventing the progression and deterioration of COVID-19, which has important implications for improving clinical management and developing effective interventions.

Antibody-dependent cellular cytotoxicity response to SARS-CoV-2 in COVID-19 patients.

Antibody-dependent cellular cytotoxicity (ADCC) responses to viral infection are a form of antibody regulated immune responses mediated through the Fc fragment. Whether severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) triggered ADCC responses contributes to COVID-19 disease development is currently not well understood. To understand the potential correlation between ADCC responses and COVID-19 disease development, we analyzed the ADCC activity and neutralizing antibody response in 255 individuals ranging from asymptomatic to fatal infections over 1 year post disease. ADCC was elicited by 10 days post-infection, peaked by 11-20 days, and remained detectable until 400 days post-infection. In general, patients with severe disease had higher ADCC activities. Notably, patients who had severe disease and recovered had higher ADCC activities than patients who had severe disease and deceased. Importantly, ADCC activities were mediated by a diversity of epitopes in SARS-COV-2-infected mice and induced to comparable levels against SARS-CoV-2 variants of concern (VOCs) (B.1.1.7, B.1.351, and P.1) as that against the D614G mutant in human patients and vaccinated mice. Our study indicates anti-SARS-CoV-2 ADCC as a major trait of COVID-19 patients with various conditions, which can be applied to estimate the extra-neutralization level against COVID-19, especially lethal COVID-19.

Trans-ethnic genome-wide association study of severe COVID-19.

COVID-19 has caused numerous infections with diverse clinical symptoms. To identify human genetic variants contributing to the clinical development of COVID-19, we genotyped 1457 (598/859 with severe/mild symptoms) and sequenced 1141 (severe/mild: 474/667) patients of Chinese ancestry. We further incorporated 1401 genotyped and 948 sequenced ancestry-matched population controls, and tested genome-wide association on 1072 severe cases versus 3875 mild or population controls, followed by trans-ethnic meta-analysis with summary statistics of 3199 hospitalized cases and 897,488 population controls from the COVID-19 Host Genetics Initiative. We identified three significant signals outside the well-established 3p21.31 locus: an intronic variant in FOXP4-AS1 (rs1853837, odds ratio OR = 1.28, P = 2.51 × 10-10, allele frequencies in Chinese/European AF = 0.345/0.105), a frameshift insertion in ABO (rs8176719, OR = 1.19, P = 8.98 × 10-9, AF = 0.422/0.395) and a Chinese-specific intronic variant in MEF2B (rs74490654, OR = 8.73, P = 1.22 × 10-8, AF = 0.004/0). These findings highlight an important role of the adaptive immunity and the ABO blood-group system in protection from developing severe COVID-19.

The trans-omics landscape of COVID-19.

The outbreak of coronavirus disease 2019 (COVID-19) is a global health emergency. Various omics results have been reported for COVID-19, but the molecular hallmarks of COVID-19, especially in those patients without comorbidities, have not been fully investigated. Here we collect blood samples from 231 COVID-19 patients, prefiltered to exclude those with selected comorbidities, yet with symptoms ranging from asymptomatic to critically ill. Using integrative analysis of genomic, transcriptomic, proteomic, metabolomic and lipidomic profiles, we report a trans-omics landscape for COVID-19. Our analyses find neutrophils heterogeneity between asymptomatic and critically ill patients. Meanwhile, neutrophils over-activation, arginine depletion and tryptophan metabolites accumulation correlate with T cell dysfunction in critical patients. Our multi-omics data and characterization of peripheral blood from COVID-19 patients may thus help provide clues regarding pathophysiology of and potential therapeutic strategies for COVID-19.

Antibody landscape against SARS-CoV-2 reveals significant differences between non-structural/accessory and structural proteins.

The immunogenicity of the SARS-CoV-2 proteome is largely unknown, especially for non-structural proteins and accessory proteins. In this study, we collect 2,360 COVID-19 sera and 601 control sera. We analyze these sera on a protein microarray with 20 proteins of SARS-CoV-2, building an antibody response landscape for immunoglobulin (Ig)G and IgM. Non-structural proteins and accessory proteins NSP1, NSP7, NSP8, RdRp, ORF3b, and ORF9b elicit prevalent IgG responses. The IgG patterns and dynamics of non-structural/accessory proteins are different from those of the S and N proteins. The IgG responses against these six proteins are associated with disease severity and clinical outcome, and they decline sharply about 20 days after symptom onset. In non-survivors, a sharp decrease of IgG antibodies against S1 and N proteins before death is observed. The global antibody responses to non-structural/accessory proteins revealed here may facilitate a deeper understanding of SARS-CoV-2 immunology.

The dynamics of immune response in COVID-19 patients with different illness severity.

This study aimed to analyze the dynamic changes of lymphocyte subsets and specific antibodies in coronavirus disease 2019 (COVID-19) patients with different illness severity. The amounts of lymphocyte subsets and the levels of immunoglobulin M (IgM) and IgG antibody were retrospectively analyzed in 707 COVID-19 cases. The amounts of lymphocyte subsets were significantly decreased with the increased severity of illness and the levels of IgM and IgG were lower in critical cases than severe and moderate cases. In deceased patients, the lymphocytes subsets were significantly lower than recovered patients. However, the relationship between the levels of IgM and IgG and the amounts of lymphocyte subsets were not significantly correlated. During different stages of COVID-19, the total T cell, CD4+ T cell, and CD8+ T cell counts were gradually recovered to the normal levels in severe and critical groups but the changing trend was relatively stable in the moderate group. The production of IgM and IgG antibodies were delayed in critical groups but also could reach the peak levels at one month after illness onset and decreased to background levels. To detect the kinetics of lymphocytes and antibodies has important clinical value in predicting the illness severity and understanding the pathogenesis of COVID-19.

Antibody dynamics to SARS-CoV-2 in asymptomatic COVID-19 infections.

BACKGROUND: The missing asymptomatic COVID-19 infections have been overlooked because of the imperfect sensitivity of the nucleic acid testing (NAT). Globally understanding the humoral immunity in asymptomatic carriers will provide scientific knowledge for developing serological tests, improving early identification, and implementing more rational control strategies against the pandemic. MEASURE: Utilizing both NAT and commercial kits for serum IgM and IgG antibodies, we extensively screened 11 766 epidemiologically suspected individuals on enrollment and 63 asymptomatic individuals were detected and recruited. Sixty-three healthy individuals and 51 mild patients without any preexisting conditions were set as controls. Serum IgM and IgG profiles were further probed using a SARS-CoV-2 proteome microarray, and neutralizing antibody was detected by a pseudotyped virus neutralization assay system. The dynamics of antibodies were analyzed with exposure time or symptoms onset. RESULTS: A combination test of NAT and serological testing for IgM antibody discovered 55.5% of the total of 63 asymptomatic infections, which significantly raises the detection sensitivity when compared with the NAT alone (19%). Serum proteome microarray analysis demonstrated that asymptomatics mainly produced IgM and IgG antibodies against S1 and N proteins out of 20 proteins of SARS-CoV-2. Different from strong and persistent N-specific antibodies, S1-specific IgM responses, which evolved in asymptomatic individuals as early as the seventh day after exposure, peaked on days from 17 days to 25 days, and then disappeared in two months, might be used as an early diagnostic biomarker. 11.8% (6/51) mild patients and 38.1% (24/63) asymptomatic individuals did not produce neutralizing antibody. In particular, neutralizing antibody in asymptomatics gradually vanished in two months. CONCLUSION: Our findings might have important implications for the definition of asymptomatic COVID-19 infections, diagnosis, serological survey, public health, and immunization strategies.

Distinct effects of asthma and COPD comorbidity on disease expression and outcome in patients with COVID-19.

BACKGROUND: The impacts of chronic airway diseases on coronavirus disease 2019 (COVID-19) are far from understood. OBJECTIVE: To explore the influence of asthma and chronic obstructive pulmonary disease (COPD) comorbidity on disease expression and outcomes, and the potential underlying mechanisms in COVID-19 patients. METHODS: A total of 961 hospitalized COVID-19 patients with a definite clinical outcome (death or discharge) were retrospectively enrolled. Demographic and clinical information were extracted from the medical records. Lung tissue sections from patients suffering from lung cancer were used for immunohistochemistry study of angiotensin-converting enzyme II (ACE2) expression. BEAS-2B cell line was stimulated with various cytokines. RESULTS: In this cohort, 21 subjects (2.2%) had COPD and 22 (2.3%) had asthma. After adjusting for confounding factors, COPD patients had higher risk of developing severe illness (OR: 23.433; 95% CI 1.525-360.135; P < .01) and acute respiratory distress syndrome (OR: 19.762; 95% CI 1.461-267.369; P = .025) than asthmatics. COPD patients, particularly those with severe COVID-19, had lower counts of CD4+ T and CD8+ T cells and B cells and higher levels of TNF-α, IL-2 receptor, IL-10, IL-8, and IL-6 than asthmatics. COPD patients had increased, whereas asthmatics had decreased ACE2 protein expression in lower airways, compared with that in control subjects without asthma and COPD. IL-4 and IL-13 downregulated, but TNF-α, IL-12, and IL-17A upregulated ACE2 expression in BEAS-2B cells. CONCLUSION: Patients with asthma and COPD likely have different risk of severe COVID-19, which may be associated with different ACE2 expression.