ABSTRACT
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 (COVID-ONE humoral immune). COVID-ONE humoral immunity is based on a dataset that contains the IgG/IgM responses to 21 of 28 known SARS-CoV-2 proteins and 197 spike protein peptides against 2,360 COVID-19 samples collected from 783 patients. In addition, 96 clinical parameters for the 2,360 samples and information for the 783 patients are integrated into the database. Furthermore, COVID-ONE humoral immune 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-humoral immune is freely available at www.COVID-ONE.cn.
Subject(s)
COVID-19ABSTRACT
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 (COVID-ONE humoral immune). COVID-ONE humoral immunity is based on a dataset that contains the IgG/IgM responses to 21 of 28 known SARS-CoV-2 proteins and 197 spike protein peptides against 2,360 COVID-19 samples collected from 783 patients. In addition, 96 clinical parameters for the 2,360 samples and information for the 783 patients are integrated into the database. Furthermore, COVID-ONE humoral immune 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-humoral immune is freely available at www.COVID-ONE.cn.
Subject(s)
COVID-19ABSTRACT
Background: The COIVD-19 global pandemic is far from ending. There is an urgent need to identify applicable biomarkers for predicting the outcome of COVID-19. Growing evidences have revealed that SARS-CoV-2 specific antibodies remain elevated with disease progression and severity in COIVD-19 patients. We assumed that antibodies may serve as biomarkers for predicting disease outcome.Method: By taking advantage of a newly developed SARS-CoV-2 proteome microarray, we surveyed IgM/IgG responses against 20 SARS-CoV-2 proteins in 1,034 hospitalized COVID-19 patients on admission, who were 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: We found that high level of IgM against ORF7b at the time of hospitalization is an independent predictor of patient survival ( p trend = 0.002), while levels of IgG responses to 6 non-structural proteins and 1 accessory protein, i. e., NSP4, NSP7, NSP9, NSP10, RdRp (NSP12), NSP14, and ORF3b, possess significant predictive power for patient death, even after further adjustments for demographics, comorbidities, and common laboratory markers for disease severity (all with p trend < 0.05). Spline regression analysis indicated that the correlation between ORF7b IgM, NSP9 IgG, and NSP10 IgG and the risk of COVID-19 mortality shows linear ( p = 0.0013, 0.0073 and 0.0003, respectively). Their AUCs for predictions, determined by computational cross-validations (validation1), were 0.74 (cut-off = 7.59), 0.66 (cut-off = 9.13), and 0.68 (cut-off = 6.29), respectively. Further validations were conducted in the second and third serial samples of these cases (validation2A, n = 633, validation2B, n = 382), with high accuracy of prediction for outcome.Conclusion: These findings have important implications for improving clinical management, and especially for developing medical interventions and vaccines.Funding Statement: This work was supported by grants from the Fundamental Research Funds for the Central Universities (HUST COVID-19 Rapid Response Call No. 2020kfyXGYJ040) and Wuhan Bureau of Science and Technology (No. 2020020601012218).Declaration of Interests: The authors declare no conflicts of interest.Ethics Approval Statement: The study was approved by the Ethical Committee of Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China (IRB ID:TJ-C20200128).
Subject(s)
COVID-19ABSTRACT
The immunogenicity of SARS-CoV-2 proteome is largely unknown, especially for non-structural proteins and accessory proteins. Here we collected 2,360 COVID-19 sera and 601 control sera. We analyzed these sera on a protein microarray with 20 proteins of SARS-CoV-2, built an antibody response landscape for IgG and IgM. We found that non-structural proteins and accessory proteins NSP1, NSP7, NSP8, RdRp, ORF3b and ORF9b elicit prevalent IgG responses. The IgG patterns and dynamic of non-structural/ accessory proteins are different from that of S and N protein. The IgG responses against these 6 proteins are associated with disease severity and clinical outcome and declined sharply about 20 days after symptom onset. In non-survivors, sharp decrease of IgG antibodies against S1 and N protein before death was observed. The global antibody responses to non-structural/ accessory proteins revealed here may facilitate deeper understanding of SARS-CoV-2 immunology.Funding: This work was partially supported by the National Key Research and Development Program of China Grant (No.2016YFA0500600), National Natural Science Foundation of China (No. 31970130, 31600672, 31670831, 31370813, 31900112 and 21907065).Conflict of Interest: The authors declare no competing interests.Ethical Approval: The study was approved by the Ethical Committee of Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China (ITJ-C20200128). Written informed consent was obtained from all participants enrolled in this study.
Subject(s)
COVID-19ABSTRACT
The immunogenicity of SARS-CoV-2 proteome is largely unknown, especially for non-structural proteins and accessory proteins. Here we collected 2,360 COVID-19 sera and 601 control sera. We analyzed these sera on a protein microarray with 20 proteins of SARS-CoV-2, built an antibody response landscape for IgG and IgM. We found that non-structural proteins and accessory proteins NSP1, NSP7, NSP8, RdRp, ORF3b and ORF9b elicit prevalent IgG responses. The IgG patterns and dynamic of non-structural/ accessory proteins are different from that of S and N protein. The IgG responses against these 6 proteins are associated with disease severity and clinical outcome and declined sharply about 20 days after symptom onset. In non-survivors, sharp decrease of IgG antibodies against S1 and N protein before death was observed. The global antibody responses to non-structural/ accessory proteins revealed here may facilitate deeper understanding of SARS-CoV-2 immunology. HighlightsO_LIAn antibody response landscape against SARS-CoV-2 proteome was constructed C_LIO_LINon-structural/accessory proteins elicit prevalent antibody responses but likely through a different mechanism to that of structural proteins C_LIO_LIIgG antibodies against non-structural/accessory proteins are more associated with disease severity and clinical outcome C_LIO_LIFor non-survivors, the levels of IgG antibodies against S1 and N decline significantly before death C_LI
Subject(s)
COVID-19ABSTRACT
The COIVD-19 global pandemic is far from ending. There is an urgent need to identify applicable biomarkers for predicting the outcome of COVID-19. Growing evidences have revealed that SARS-CoV-2 specific antibodies remain elevated with disease progression and severity in COIVD-19 patients. We assumed that antibodies may serve as biomarkers for predicting disease outcome. By taking advantage of a newly developed SARS-CoV-2 proteome microarray, we surveyed IgM/ IgG responses against 20 SARS-CoV-2 proteins in 1,034 hospitalized COVID-19 patients on admission, who were followed till 66 days. The microarray results were 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. We found that high level of IgM against ORF7b at the time of hospitalization is an independent predictor of patient survival (p trend = 0.002), while levels of IgG responses to 6 non-structural proteins and 1 accessory protein, i. e., NSP4, NSP7, NSP9, NSP10, RdRp (NSP12), NSP14, and ORF3b, possess significant predictive power for patient death, even after further adjustments for demographics, comorbidities, and common laboratory markers for disease severity (all with p trend < 0.05). Spline regression analysis indicated that the correlation between ORF7b IgM, NSP9 IgG, and NSP10 IgG and risk of COVID-19 mortality is linear (p = 0.0013, 0.0073 and 0.0003, respectively). Their AUCs for predictions, determined by computational cross-validations (validation1), were 0.74 (cut-off = 7.59), 0.66 (cut-off = 9.13), and 0.68 (cut-off = 6.29), respectively. Further validations were conducted in the second and third serial samples of these cases (validation2A, n = 633, validation2B, n = 382), with high accuracy of prediction for outcome. These findings have important implications for improving clinical management, and especially for developing medical interventions and vaccines.
Subject(s)
Death , COVID-19ABSTRACT
Serological test plays an essential role in monitoring and combating COVID-19 pandemic. Recombinant spike protein (S protein), especially S1 protein is one of the major reagents for serological tests. However, the high cost in production of S protein, and the possible cross-reactivity with other human coronaviruses poses unneglectable challenges. Taking advantage of a peptide microarray of full spike protein coverage, we analyzed 2,434 sera from 858 COVID-19 patients, sera from 63 asymptomatic patients and 610 controls collected from multiple clinical centers. Based on the results of the peptide microarray, we identified several S protein derived 12-mer peptides that have high diagnosis performance. Particularly, for monitoring IgG response, one peptide (aa 1148-1159 or S2-78) has a comparable sensitivity (95.5%, 95% CI 93.7-96.9%) and specificity (96.7%, 95% CI 94.8-98.0%) to that of S1 protein for detection of both COVID-19 patients and asymptomatic infections. Furthermore, the performance of S2-78 IgG for diagnosis was successfully validated by ELISA with an independent sample cohort. By combining S2-78/ S1 with other peptides, a two-step strategy was proposed to ensure both the sensitivity and specificity of S protein based serological assay. The peptide/s identified in this study could be applied independently or in combination with S1 protein for accurate, affordable, and accessible COVID-19 diagnosis.
Subject(s)
COVID-19ABSTRACT
Neutralization antibodies and vaccines for treating COVID-19 are desperately needed. For precise development of antibodies and vaccines, the key is to understand which part of SARS-CoV-2 Spike protein is highly immunogenic on a systematic way. We generate a linear epitope landscape of Spike protein by analyzing serum IgG response of 1,051 COVID-19 patients with a peptide microarray. We reveal two regions that rich of linear epitopes, i.e., CTD and a region close to the S2’ cleavage site and fusion peptide. Unexpectedly, we find RBD is lack of linear epitope. Besides 3 moderate immunogenic peptides from RBD, 16 highly immunogenic peptides from other regions of Spike protein are determined. These peptides could serve as the base for precise development of antibodies and vaccines for COVID-19 on a systematic level.Funding: This work was partially supported by National Key Research and Development Program of China Grant (No. 2016YFA0500600), Science and Technology Commission of Shanghai Municipality (No. 19441911900), Interdisciplinary Program of Shanghai Jiao Tong University (No. YG2020YQ10), National Natural Science Foundation of China (No. 31970130, 31600672, 31670831, and 31370813).Conflict of Interest: The authors declare no competing interest.
Subject(s)
COVID-19ABSTRACT
Neutralization antibodies and vaccines for treating COVID-19 are desperately needed. For precise development of antibodies and vaccines, the key is to understand which part of SARS-CoV-2 Spike protein is highly immunogenic on a systematic way. We generate a linear epitope landscape of Spike protein by analyzing serum IgG response of 1,051 COVID-19 patients with a peptide microarray. We reveal two regions that rich of linear epitopes, i.e., CTD and a region close to the S2' cleavage site and fusion peptide. Unexpectedly, we find RBD is lack of linear epitope. Besides 3 moderate immunogenic peptides from RBD, 16 highly immunogenic peptides from other regions of Spike protein are determined. These peptides could serve as the base for precise development of antibodies and vaccines for COVID-19 on a systematic level.
Subject(s)
Severe Acute Respiratory Syndrome , COVID-19ABSTRACT
ImportanceAsymptomatic COVID-19 infections have a long duration of viral shedding and contribute substantially to disease transmission. However, the missing asymptomatic cases have been significantly overlooked because of imperfect sensitivity of nucleic acid testing. We aimed to investigate the humoral immunity in asymptomatics, which will help us develop serological tests and improve early identification, understand the humoral immunity to COVID-19, and provide more rational control strategies for the pandemic. ObjectiveTo better control the pandemic of COVID-19, dynamics of IgM and IgG responses to 23 proteins of SARS-CoV-2 and neutralizing antibody in asymptomatic COVID-19 infections after exposure time were investigated. Design, setting, and participants63 asymptomatic individuals were screened by RT-qPCR and ELISA for IgM and IgG from 11,776 personnel returning to work, and close contacts with the confirmed cases in different communities of Wuhan by investigation of clusters and tracing infectious sources. 63 healthy contacts with both negative results for NAT and antibodies were selected as negative controls. 51 mild patients without any preexisting conditions were also screened as controls from 1056 patients during hospitalization in Tongji Hospital. A total of 177 participants were enrolled in this study and serial serum samples (n=213) were collected. The research was conducted between 17 February 2020 and 28 April 2020. Serum IgM and IgG profiles of 177 participants were further probed using a SARS-CoV-2 proteome microarray. Neutralizing antibody responses in different population were detected by a pseudotyped virus neutralization assay system. The dynamics of IgM and IgG antibodies and neutralizing antibodies were analyzed with exposure time or symptoms onset. ResultsAsymptomatics were classified into four subgroups based on NAT and serological tests. In particular, only 19% had positive NAT results while approximately 81% detected positive IgM/IgG responses. Comparative SARS-CoV-2 proteome microarray further demonstrated that there was a significantly difference of antibody dynamics responding to S1 or N proteins among three populations, although IgM and IgG profiles could not be used to differentiate them. S1 specific IgM responses were elicited in asymptomatic individuals as early to the seventh day after exposure and peaked on days from 17d to 25d, which might be used as an early diagnostic biomarker and give an additional 36.5% seropositivity. Mild patients produced stronger both S1 specific IgM and neutralizing antibody responses than asymptomatic individuals. Most importantly, S1 specific IgM/IgG responses and the titers of neutralizing antibody in asymptomatic individuals gradually vanished in two months. Conclusions and relevanceOur findings might have important implications for the definition of asymptomatic COVID-19 infections, diagnosis, serological survey, public health and immunization strategies.