Anti-N SARS-CoV-2 assays for evaluation of natural viral infection.

The 2019 coronavirus (COVID-19) epidemic, required the development of different diagnostic tests. While reverse transcriptase real-time PCR (RT-PCR) remains the first-line test of choice in acute infection diagnosis, anti-N antibodies serological assays provide a valuable tool to differentiate natural SARS-CoV-2 immunological response from that induced by vaccination, thus the goal of our study was to evaluate three serological tests agreement for these antibodies detection. Three anti-N different tests were examined in 74 sera from patients referred or not COVID infection: immunochromatographic rapid test (Panbio™ COVID-19 IgG/IgM Rapid Test Device Abbott, Germany), ELISA kit (NovaLisa® SARS-CoV-2 IgG and IgM NovaTech Immunodiagnostic GmbH, Germany) and ECLIA immunoassay (Elecsys® Anti-SARS-CoV-2 Roche Diagnostics, Manheim, Germany). Qualitative comparison of the three analytical methods revealed a moderate agreement between ECLIA immunoassay and immunochromatographic rapid test (Cohen kappa coefficient κ = 0.564). Correlation analysis indicated weak positive correlation between total Ig (IgT) detected by ECLIA immunoassay and IgG by ELISA test (p < 0.0001), the analysis of ECLIA IgT and IgM ELISA detected, showed no statistical correlation. Comparison between of three analytical systems available for anti-N SARS-CoV-2 IgG and IgM antibodies showed a general agreement when compared to detect total and G class immunoglobulins, while doubtful or discordant results have been highlighted for IgT and IgM class. Anyway, all the tests examined provide reliable results to assess the serological status of SARS-CoV-2 infected patients. Copyright © 2023. Published by Elsevier B.V.

Citation

Aurelia Gaeta, Antonio Angeloni, Anna Napoli, Beatrice Pucci, Lilia Cinti, Piergiorgio Roberto, Flavia Colaiacovo, Elena Berardelli, Antonella Farina, Guido Antonelli, Emanuela Anastasi. Anti-N SARS-CoV-2 assays for evaluation of natural viral infection. Journal of immunological methods. 2023 Jul;518:113486

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PMID: 37156408

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