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Comparison of Two Commercial Surrogate Elisas to Detect a Neutralizing Antibody Response to SARS-CoV-2 (preprint)
ssrn; 2020.
Preprint
in English
| PREPRINT-SSRN | ID: ppzbmed-10.2139.ssrn.3716021
ABSTRACT
Introduction:
Reliable methods for the detection of SARS-CoV-2 neutralizing antibodies (NAbs) are essential for the evaluation of vaccine candidates and for the selection of convalescent plasma donors. Virus neutralization tests (NTs) are the gold standard for the detection and quantification of NAbs, but they are complex and require BSL3 facilities. In contrast, surrogate enzyme-linked immunosorbent assays (sELISA) offer the possibility of high-throughput testing under standard laboratory safety conditions. In this study, we investigated two commercial sELISA kits (GenScript, AdipoGen) designed for the detection of SARS-CoV-2 NAbs.Methods:
276 plasma samples were screened using commercial IgG-ELISA and NAbs titers were determined by micro-neutralization test (micro-NT). In addition, all samples were tested in both sELISA. Sensitivity and specificity for both sELISA were determined in comparison to the micro-NT results.Results:
57% of the samples were positive for SARS-CoV-2 NAbs in micro-NT, while 43% tested negative. Comparison with micro-NT results showed a sensitivity of 98.2% and a specificity of 69.5% for the GenScript ELISA. The AdipoGen ELISA had a sensitivity of 83.5% and a specificity of 97.8%. False negative results were obtained mainly on samples with low NAbs titers.Conclusion:
Both sELISA were able to qualitatively detect NAbs in plasma samples. Sensitivity and specificity differed between sELISA with GenScript superior in sensitivity and AdipoGen superior in specificity. Both sELISA were unable to quantify NAbs, thus neither of them can completely replace conventional NTs. However, in a two-step diagnostic algorithm, AdipoGen could potentially replace NT as a subsequent confirmatory test due to its high specificity.
Full text:
Available
Collection:
Preprints
Database:
PREPRINT-SSRN
Language:
English
Year:
2020
Document Type:
Preprint
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