Multianalyte serology in home-sampled blood enables an unbiased assessment of the immune response against SARS-CoV-2

  1. Niclas Roxhed
  2. Annika Bendes
  3. Matilda Dale
  4. Cecilia Mattsson
  5. Leo Hanke
  6. Tea Dodig-Crnković
  7. Murray Christian
  8. Birthe Meineke
  9. Simon Elsässer
  10. Juni Andréll
  11. Sebastian Havervall
  12. Charlotte Thålin
  13. Carina Eklund
  14. Joakim Dillner
  15. Olof Beck
  16. Cecilia E. Thomas
  17. Gerald McInerney
  18. Mun-Gwan Hong
  19. Ben Murrell
  20. Claudia Fredolini
  21. Jochen M. Schwenk

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Abstract

Serological testing is essential to curb the consequences of the COVID-19 pandemic. However, most assays are still limited to single analytes and samples collected within healthcare. Thus, we establish a multianalyte and multiplexed approach to reliably profile IgG and IgM levels against several versions of SARS-CoV-2 proteins (S, RBD, N) in home-sampled dried blood spots (DBS). We analyse DBS collected during spring of 2020 from 878 random and undiagnosed individuals from the population in Stockholm, Sweden, and use classification approaches to estimate an accumulated seroprevalence of 12.5% (95% CI: 10.3%–14.7%). This includes 5.4% of the samples being IgG + IgM + against several SARS-CoV-2 proteins, as well as 2.1% being IgG − IgM + and 5.0% being IgG + IgM − for the virus’ S protein. Subjects classified as IgG + for several SARS-CoV-2 proteins report influenza-like symptoms more frequently than those being IgG + for only the S protein (OR = 6.1; p  < 0.001). Among all seropositive cases, 30% are asymptomatic. Our strategy enables an accurate individual-level and multiplexed assessment of antibodies in home-sampled blood, assisting our understanding about the undiagnosed seroprevalence and diversity of the immune response against the coronavirus.

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  1. Version published to 10.1038/s41467-021-23893-4
  2. ScreenIT

    SciScore for 10.1101/2020.07.01.20143966: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    No key resources detected.

    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:
    However, there are some limitations to the chosen design and approach. First, anonymized and population-based studies are more attractive but such a design limits the possibilities to conduct follow-up analyses. Other studies using multiplexed assays may therefore investigate the dynamics of antibody titers, such as IgM, and determine if particular antigens become dominant over time. Secondly, minimal and self-reported information limits the possibilities to draw further and more general conclusions about COVID-19, as both types of information can be biased by completeness and subjectivity of the reported scales. Our study can be expanded beyond Stockholm to more remote areas with greater distances to health care centers and include more than the analyzed 1000 DBS samples to increase the power and study the seroprevalence in different regions of Sweden and other countries. The investigation studied the antibodies as well as proteins in DBS eluates from discs having dried blood from a volume of 10 µl. These 3D matrices fitted into regular 96-well microtiter plates, hence opened up the possibility to process samples in a high-throughput format. Pre-analytical sample handling was minimal. The protocol included the addition of elution buffer to the blood discs, incubation, and centrifugation to prepare the eluates from the cell-free supernatants for the analyses. All steps were compatible with well-established protocols for antibody profiling with serum or plasma samples. Since w...

    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

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  3. Version published to 10.1101/2020.07.01.20143966v1 on medRxiv