Clinical evaluation of the antibody response in patients with COVID-19 using automated high-throughput immunoassays.
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ABSTRACT:
SUBMITTER: Kubota K
PROVIDER: S-EPMC7954771 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Virus neutralization remains the gold standard for determining antibody efficacy. Therefore, a high-throughput assay to measure SARS-CoV-2 neutralizing antibodies is urgently needed for COVID-19 serodiagnosis, convalescent plasma therapy, and vaccine development. Here, we report on a fluorescence-based SARS-CoV-2 neutralization assay that detects SARS-CoV-2 neutralizing antibodies in COVID-19 patient specimens and yields comparable results to plaque reduction neutralizing assay, the gold standard of serological testing. The fluorescence-based neutralization assay is specific to measure COVID-19 neutralizing antibodies without cross reacting with patient specimens with other viral, bacterial, or parasitic infections. Collectively, our approach offers a rapid platform that can be scaled to screen people for antibody protection from COVID-19, a key parameter necessary to safely reopen local communities.
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Project description:ObjectiveNumerous immunoassays for detecting antibodies directed against SARS-CoV-2 have been rapidly developed and released. Validations of these have been performed with a limited number of samples. The lack of standardisation might lead to significantly different results. This study compared ten automated assays from six vendors in terms of sensitivity, specificity and reproducibility.MethodsThis study compared ten fully automated immunoassays from the following vendors: Diasorin, Epitope Diagnostics, Euroimmun, Roche, YHLO, and Snibe. The retrospective part of the study included patients with a laboratory-confirmed COVID-19 infection, and controls comprised patients with a suspected infection, in whom the disease was excluded. Furthermore, biobanked sera were taken as negative controls (n = 97). The retrospective part involved four groups: (1) laboratory-confirmed COVID-19 infection (n = 183); (1B) suspected COVID-19 infection (n = 167) without a qRT-PCR result but positive serological results from at least two different assays, and suspected COVID-19 infection due to a positive serological result from the Roche assay (n = 295); (2) biobanked sera obtained from patients before the emergence of SARS-CoV-2 (n = 97) as negative controls; and (2A) probably COVID-19-negative sera with negative serological results from at least two different assays (n = 152).ResultsOverall diagnostic sensitivities were: Euroimmun (IgA) 87%; Epitope Diagnostics (IgG) 83%; YHLO (IgG) 77%; Roche (IgM/IgG) 77%; Euroimmun (IgG) 75%; Diasorin (IgG) 53%; Epitope Diagnostics (IgM) 52%; Snibe (IgG) 47%; YHLO (IgM) 35%; and Snibe (IgM) 26%. Diagnostic specificities were: YHLO (IgG) 100%; Roche, 100%; Snibe (IgM/IgG) 100%; Diasorin (IgG) 97%; Euroimmun (IgG) 94%; YHLO (IgM) 94%; Euroimmun (IgA) 83%.ConclusionAssays from different vendors substantially varied in terms of their performance. These findings might facilitate selection of appropriate serological assays.
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Project description:Quantitative SARS-CoV-2 antibody assays against the spike (S) protein are useful for monitoring immune response after infection or vaccination. We compared the results of three chemiluminescent immunoassays (CLIAs) (Abbott, Roche, Siemens) and a surrogate virus neutralization test (sVNT, GenScript) using 191 sequential samples from 32 COVID-19 patients. All assays detected >90% of samples collected 14 days after symptom onset (Abbott 97.4%, Roche 96.2%, Siemens 92.3%, and GenScript 96.2%), and overall agreement among the four assays was 91.1% to 96.3%. When we assessed time-course antibody levels, the Abbott and Siemens assays showed higher levels in patients with severe disease (p < 0.05). Antibody levels from the three CLIAs were correlated (r = 0.763-0.885). However, Passing-Bablok regression analysis showed significant proportional differences between assays and converting results to binding antibody units (BAU)/mL still showed substantial bias. CLIAs had good performance in predicting sVNT positivity (Area Under the Curve (AUC), 0.959-0.987), with Abbott having the highest AUC value (p < 0.05). SARS-CoV-2 S protein antibody levels as assessed by the CLIAs were not interchangeable, but showed reliable performance for predicting sVNT results. Further standardization and harmonization of immunoassays might be helpful in monitoring immune status after COVID-19 infection or vaccination.
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Project description:IntroductionSARS-CoV-2 seroconversion is important for epidemiological studies as well as contact tracing.Material and methodsThe antibody response against SARS-CoV-2 was examined in 111 patients with a positive qRT-PCR. Seroconversion was assessed using the Elecsys from Roche, the Liaison S1/S2 IgG from Diasorin, the IgG and IgA from Euroimmun, as well as the VIDAS IgG and IgM. Specificity was estimated based on the measurement of SARS-CoV-2 antibodies in 96 residual samples collected during a non-pandemic period.ResultsThe highest overall sensitivity for detecting seroconversion was obtained using the Elecsys (81.1%), the Euroimmun with a combined detection of IgG/IgA (86.5%), and the VIDAS with a simultaneous measurement of IgG/IgM (78.4%).The Elecsys and the VIDAS IgG/IgM demonstrated a specificity as well as a positive predictive value of 100%.ConclusionsThe Elecsys and the VIDAS methods with a combination of IgG/IgM measurement demonstrated a high sensitivity with no false positive results.
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Project description:COVID-19 outbreak brings intense pressure on healthcare systems, with an urgent demand for effective diagnostic, prognostic and therapeutic procedures. Here, we employed Automated Machine Learning (AutoML) to analyze three publicly available high throughput COVID-19 datasets, including proteomic, metabolomic and transcriptomic measurements. Pathway analysis of the selected features was also performed. Analysis of a combined proteomic and metabolomic dataset led to 10 equivalent signatures of two features each, with AUC 0.840 (CI 0.723-0.941) in discriminating severe from non-severe COVID-19 patients. A transcriptomic dataset led to two equivalent signatures of eight features each, with AUC 0.914 (CI 0.865-0.955) in identifying COVID-19 patients from those with a different acute respiratory illness. Another transcriptomic dataset led to two equivalent signatures of nine features each, with AUC 0.967 (CI 0.899-0.996) in identifying COVID-19 patients from virus-free individuals. Signature predictive performance remained high upon validation. Multiple new features emerged and pathway analysis revealed biological relevance by implication in Viral mRNA Translation, Interferon gamma signaling and Innate Immune System pathways. In conclusion, AutoML analysis led to multiple biosignatures of high predictive performance, with reduced features and large choice of alternative predictors. These favorable characteristics are eminent for development of cost-effective assays to contribute to better disease management.
| S-EPMC8302755 | biostudies-literature
Project description:Serological SARS-CoV-2 assays are urgently needed for diagnosis, contact tracing and for epidemiological studies. So far, there is limited data on how recently commercially available, high-throughput immunoassays, using different recombinant SARS-CoV-2 antigens, perform with clinical samples. Focusing on IgG and total antibodies, we demonstrate the performance of four automated immunoassays (Abbott Architect™ i2000 (N protein-based)), Roche cobas™ e 411 analyzer (N protein-based, not differentiating between IgA, IgM or IgG antibodies), LIAISON®XL platform (S1 and S2 protein-based), VIRCLIA® automation system (S1 and N protein-based) in comparison to two ELISA assays (Euroimmun SARS-CoV-2 IgG (S1 protein-based) and Virotech SARS-CoV-2 IgG ELISA (N protein-based)) and an in-house developed plaque reduction neutralization test (PRNT). We tested follow up serum/plasma samples of individuals PCR-diagnosed with COVID-19. When calculating the overall sensitivity, in a time frame of 49 days after first PCR-positivity, the PRNT as gold standard, showed the highest sensitivity with 93.3% followed by the dual-target assay for the VIRCLIA® automation system with 89%. The overall sensitivity in the group of N protein-based assays ranged from 66.7 to 77.8% and in the S protein-based-assays from 71.1 to 75.6%. Five follow-up samples of three individuals were only detected in either an S and/or N protein-based assay, indicating an individual different immune response to SARS-CoV-2 and the influence of the used assay in the detection of IgG antibodies. This should be further analysed. The specificity of the examined assays was ≥ 97%. However, because of the low or unknown prevalence of SARS-CoV-2, the examined assays in this study are currently primarily eligible for epidemiological investigations, as they have limited information in individual testing.
| S-EPMC7263247 | biostudies-literature
Project description:The submitted files contain ChIP-seq data for the p300 transcriptional coactivator in GM12878 cells and for the NRSF transcription factor in GM12878 and Jurkat cells generated using a fully automated robotic chromatin immunoprecipitation protocol. Cells were fixed using 1% formaldehyde (NRSF samples) or 1% formaldehyde at 37C (p300 samples).
2014-06-01 | GSE53366 | GEO
Project description:The COVID-19 pandemic is an unprecedented global challenge, and point-of-care diagnostic classifiers are urgently required. Here, we present a platform for ultra-high-throughput serum and plasma proteomics that builds on ISO13485 standardization to facilitate simple implementation in regulated clinical laboratories. Our low-cost workflow handles up to 180 samples per day, enables high precision quantification, and reduces batch effects for large-scale and longitudinal studies. We use our platform on samples collected from a cohort of early hospitalized cases of the SARS-CoV-2 pandemic and identify 27 potential biomarkers that are differentially expressed depending on the WHO severity grade of COVID-19. They include complement factors, the coagulation system, inflammation modulators, and pro-inflammatory factors upstream and downstream of interleukin 6. All protocols and software for implementing our approach are freely available. In total, this work supports the development of routine proteomic assays to aid clinical decision making and generate hypotheses about potential COVID-19 therapeutic targets.
| S-EPMC7264033 | biostudies-literature
Project description:Since December 2019, we have been in the battlefield with a new threat to the humanity, known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes coronavirus disease 2019 (COVID-19), characterized by viral pneumonia. It may be asymptomatic or cause various symptoms, ranging from flu-like symptoms to acute respiratory distress syndrome and eventually death. At present, the only reliable test for COVID-19 diagnosis is quantitative reverse transcriptase-polymerase chain reaction. Assessing the immune response against SARS-CoV-2 could increase the detection sensitivity of infected population. Hereby, we report the performances of a fully automated chemiluminescent immunoassay (CLIA) on 276 serum samples. One hundred samples obtained from COVID-19 negative subjects (COVID-19 free) were analyzed to evaluate the diagnostic specificity of antibody (Ab) detection. Thereafter, 176 samples obtained from 125 patients with confirmed COVID-19 (COVID-19 patients) were selected to assess the diagnostic sensitivity of the CLIA. All samples were analyzed on MAGLUMI 800 platform. All COVID-19 free samples had Ab levels below the cutoff values. Hence, the diagnostic specificity was estimated at 100% (95% confidence interval [CI] = 96.3-100.0; positive predictive value = 100%). By the 18th day from the onset of symptoms, we reached an optimal diagnostic sensitivity (more than 95.0%) In fact, the diagnostic sensitivity increased over time and between 15 and 25 days after symptoms onset, reached 95.5% (95% CI = 84.9-99.2). The new automated CLIA analyzer appeared to be a robust and reliable method to measure specific Ab against COVID-19 at high throughput. Our data suggest that combining Ab and nucleic acid detection could increase diagnostic sensitivity.
| S-EPMC7436871 | biostudies-literature
Project description:ObjectivesThe aim was to determine the antibody response against SARS-CoV-2 spike protein and nucleoprotein using four automated immunoassays and three ELISAs for the detection of total Ig antibodies (Roche) or IgG (Abbott, Diasorin, Snibe, Euroimmun, Mikrogen) in COVID-19 patients.MethodsSensitivity and dynamic trend to seropositivity were evaluated in 233 samples from 114 patients with moderate, severe or critical COVID-19 confirmed with PCR on nasopharyngeal swab. Specificity was evaluated in 113 samples collected before January 2020, including 24 samples from patients with non-SARS coronavirus infection.ResultsSensitivity for all assays was 100% (95% confidence interval 83.7-100) 3 weeks after onset of symptoms. Specificity varied between 94.7% (88.7-97.8) and 100% (96.1-100). Calculated at the cut-offs that corresponded to a specificity of 95% and 97.5%, Roche had the highest sensitivity (85.0% (79.8-89.0) and 81.1% (76.6-85.7), p < 0.05 except vs. Abbott). Seroconversion occurred on average 2 days earlier for Roche total Ig anti-N and the three IgG anti-N assays (Abbott, Mikrogen, Euroimmun) than for the two IgG anti-S assays (Diasorin, Euroimmun) (≥50% seroconversion day 9-10 vs. day 11-12 and p < 0.05 for percent seropositive patients day 9-10 to 17-18). There was no significant difference in the IgG antibody time to seroconversion between critical and non-critical patients.DiscussionSeroconversion occurred within 3 weeks after onset of symptoms with all assays and on average 2 days earlier for assays detecting IgG or total Ig anti-N than for IgG anti-S. The specificity of assays detecting anti-N was comparable to anti-S and excellent in a challenging control population.
| S-EPMC7834107 | biostudies-literature