Comparison of SARS-CoV-2 serological assays for use in epidemiological surveillance in Scotland

  1. Lindsay McDonald
  2. Helen Wise
  3. Frauke Muecksch
  4. Daniel Poston
  5. Sally Mavin
  6. Kate Templeton
  7. Elizabeth Furrie
  8. Claire Richardson
  9. Jaqueline McGuire
  10. Lisa Jarvis
  11. Kristen Malloy
  12. Andrew McAuley
  13. Norah Palmateer
  14. Elizabeth Dickson
  15. Theodora Hatziioannou
  16. Paul Bieniasz
  17. Sara Jenks

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Abstract

No abstract available

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  1. Version published to 10.1016/j.jcvp.2021.100028
  2. ScreenIT

    SciScore for 10.1101/2021.04.20.21255596: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variableSample numbers are stratified with equal numbers of male and female specimens from each of the following age groups - ≤ 20, 21-40, 41-64, ≥65.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Automated serological assays: Five commercial immunoassays designed for use in automated high-throughput analysers were used for the detection of antibodies to SARS-CoV-2: Abbott Architect SARS-CoV-2 IgG (anti-N), Roche Anti-SARS-CoV-2 total antibody (anti-N), DiaSorin LIAISON® S1/S2 SARS-CoV-2 IgG assay, Siemens SARS-CoV-2 total antibody (anti-S), and EUROIMMUN Anti-SARS-CoV-2 ELISA (anti-S IgG).
    anti-N
    suggested: None
    Anti-SARS-CoV-2
    suggested: None
    anti-S
    suggested: None
    anti-S IgG
    suggested: None
    Experimental Models: Cell Lines
    SentencesResources
    22 target cells (for HIV-1NLΔEnv-NanoLuc/SARS-CoV-2 and HCoV-OC43) or HT1080/ACE2cl.14 (for HCoV-NL63 and HCoV-229E) plated the previous day at 1×104 cells/well in 100 µl medium, giving a final starting serum dilution of 1:50.
    HCoV-NL63
    suggested: RRID:CVCL_RW88)
    Software and Algorithms
    SentencesResources
    Assays were performed on the Abbott Architect (NHS Lothian)
    Abbott Architect
    suggested: (Abbott ARCHITECT i1000sr System, RRID:SCR_019328)
    Spearman’s r correlations were generated using GraphPad Prism 9 to compare immunoassay and neutralisation titres for 28 primary care samples producing a positive result by any assay.
    GraphPad Prism
    suggested: (GraphPad Prism, RRID:SCR_002798)

    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: We detected the following sentences addressing limitations in the study:
    One limitation of our study is that calculations are based on relatively small numbers of positive samples. Given the low population prevalence, larger cohorts would be required to conclusively determine optimal immunoassays for correlation with neutralising antibody activity. It is also worth noting that all samples included predate the emergence of epidemiologically significant new variants. Their impact on assay performance for seroprevalence therefore remains unknown. This study demonstrates the dependence of SARS-CoV-2 assay suitability on population and study-specific factors. Ongoing investigation of these will be critical to reliable assessment of levels of exposure and protection in the face of evolving factors including waves of infection, new variants and population vaccination.

    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.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  3. Version published to 10.1101/2021.04.20.21255596v1 on medRxiv