Comparison of 2 fully automated tests detecting antibodies against nucleocapsid N and spike S1/S2 proteins in COVID-19

  • Heini Flinck*
  • , Anne Rauhio
  • , Bruno Luukinen
  • , Terho Lehtimäki
  • , Anna-Maija Haapala
  • , Tapio Seiskari
  • , Janne Aittoniemi
  • *Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

12 Citations (Scopus)

Abstract

Automated assays for detecting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibodies in coronavirus disease 2019 (COVID-19) diagnostics have recently come available. We compared the performance of the Elecsys® Anti–SARS-CoV-2 and LIAISON® SARS-CoV-2 S1/S2 IgG tests. The seroconversion panel comprised of 120 samples from 13 hospitalized COVID-19 patients. For the sensitivity and specificity testing, samples from COVID-19 outpatients >15 days after positive nucleic acid amplification test (NAAT) result (n = 35) and serum control samples collected before the COVID-19 era (n = 161) were included in the material. Samples for the detection of possible cross-reactions were also tested. Based on our results, the SARS-CoV-2 antibodies can be quite reliably detected 2 weeks after NAAT positivity and 3 weeks after the symptom onset with both tests. However, since some COVID-19 patients were positive only with Elecsys®, the antibodies should be screened against N-antigen (Elecsys®) and reactive samples confirmed with S antigen (LIAISON®), but both results should be reported. In some COVID-19 patients, the serology can remain negative.

Original languageEnglish
Article number115197
JournalDiagnostic Microbiology and Infectious Disease
Volume99
Issue number1
Early online date29 Aug 2020
DOIs
Publication statusPublished - Jan 2021
Publication typeA1 Journal article-refereed

Funding

The study was supported by Tampere Tuberculosis Foundation and Competitive State Research Financing of Expert Responsibility area of Tampere .

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Antibody
  • COVID-19
  • Elecsys
  • LIAISON
  • SARS-CoV-2
  • Serology

Publication forum classification

  • Publication forum level 1

ASJC Scopus subject areas

  • Microbiology (medical)
  • Infectious Diseases

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