Validation and performance of a quantitative IgG assay for the screening of SARS-CoV-2 antibodies
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Abstract
The current COVID-19 epidemic imposed an unpreceded challenge to the scientific community in terms of treatment, epidemiology, diagnosis, social interaction, fiscal policies and many other areas. The development of accurate and reliable diagnostic tools (high specificity and sensitivity) is crucial in the current period, the near future and in the long term. These assays should provide guidance to identify immune presumptive protected persons, potential plasma, and/or B cell donors and vaccine development among others. Also, such assays will be contributory in supporting prospective and retrospective studies to identify the prevalence and incidence of COVID-19 and to characterize the dynamics of the immune response. As of today, only thirteen serological assays have received the Emergency Use Authorization (EUA) by the U.S. Federal Drug Administration (FDA). In this work we describe the development and validation of a quantitative IgG enzyme-linked immunoassay (ELISA) using the recombinant SARS-CoV-2 Spike Protein S1 domain, containing the receptor-binding domain (RBD), showing 98% sensitivity, 98.9% specificity and positive and negative predictive values of 100% and 99.2%, respectively. The assay showed to be useful to test for SARS-CoV-2 IgG antibodies in plasma samples from COVID-19-recovered subjects as potential donors for plasmapheresis. This assay is currently under review by the Federal Drug Administration for an Emergency Use Authorization request (Submission Number EUA201115).
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SciScore for 10.1101/2020.06.11.146332: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Antibodies Sentences Resources For comparison with two others serological tests (CoronaCheck and Abbott Architect) holding an EUA, we used a set of nine (9) samples assumed to be positive for IgG and IgM and eighteen (18) assumed to be IgG positive for SARS-CoV-2 antibodies. SARS-CoV-2suggested: NoneCovIgG-Assay: CovIgG-Assay is an indirect ELISA for quantitative determination of human IgG antibody class, which was optimized by checkerboard titration. human IgGsuggested: NoneEstimation of Antibody Titer: To estimate the IgG antibody titer, 40 COVID-19 samples were subjected to serial dilutions from 1:100 to 1:12,800. IgGsuggested: NoneSciScore for 10.1101/2020.06.11.146332: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Antibodies Sentences Resources For comparison with two others serological tests (CoronaCheck and Abbott Architect) holding an EUA, we used a set of nine (9) samples assumed to be positive for IgG and IgM and eighteen (18) assumed to be IgG positive for SARS-CoV-2 antibodies. SARS-CoV-2suggested: NoneCovIgG-Assay: CovIgG-Assay is an indirect ELISA for quantitative determination of human IgG antibody class, which was optimized by checkerboard titration. human IgGsuggested: NoneEstimation of Antibody Titer: To estimate the IgG antibody titer, 40 COVID-19 samples were subjected to serial dilutions from 1:100 to 1:12,800. IgGsuggested: NoneSoftware and Algorithms Sentences Resources Same set of 18 samples reported as SARS-CoV-2 IgG positive were also tested by Abbott Architect SARS-CoV-2 IgG (Abbott Laboratories Diagnostics Division Abbott Park, IL 60064 USA). Abbott Architectsuggested: (Abbott ARCHITECT i1000sr System, RRID:SCR_019328)Abbottsuggested: (Abbott, RRID:SCR_010477)Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- No funding statement was detected.
- No protocol registration statement was detected.
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