SARS-CoV-2 RNA detected in blood products from patients with COVID-19 is not associated with infectious virus

  1. Monique I. Andersson
  2. Carolina V. Arancibia-Carcamo
  3. Kathryn Auckland
  4. J. Kenneth Baillie
  5. Eleanor Barnes
  6. Tom Beneke
  7. Sagida Bibi
  8. Tim Brooks
  9. Miles Carroll
  10. Derrick Crook
  11. Kate Dingle
  12. Christina Dold
  13. Louise O. Downs
  14. Laura Dunn
  15. David W. Eyre
  16. Javier Gilbert Jaramillo
  17. Heli Harvala
  18. Sarah Hoosdally
  19. Samreen Ijaz
  20. Tim James
  21. William James
  22. Katie Jeffery
  23. Anita Justice
  24. Paul Klenerman
  25. Julian C. Knight
  26. Michael Knight
  27. Xu Liu
  28. Sheila F. Lumley
  29. Philippa C. Matthews
  30. Anna L. McNaughton
  31. Alexander J. Mentzer
  32. Juthathip Mongkolsapaya
  33. Sarah Oakley
  34. Marta S. Oliveira
  35. Timothy Peto
  36. Rutger J. Ploeg
  37. Jeremy Ratcliff
  38. Melanie J. Robbins
  39. David J. Roberts
  40. Justine Rudkin
  41. Rebecca A. Russell
  42. Gavin Screaton
  43. Malcolm G. Semple
  44. Donal Skelly
  45. Peter Simmonds
  46. Nicole Stoesser
  47. Lance Turtle
  48. Susan Wareing
  49. Maria Zambon

Reviewed by

Read the full article

Listed in

Log in to save this article

Abstract

Background: Laboratory diagnosis of SARS-CoV-2 infection (the cause of COVID-19) uses PCR to detect viral RNA (vRNA) in respiratory samples. SARS-CoV-2 RNA has also been detected in other sample types, but there is limited understanding of the clinical or laboratory significance of its detection in blood.

Methods: We undertook a systematic literature review to assimilate the evidence for the frequency of vRNA in blood, and to identify associated clinical characteristics. We performed RT-PCR in serum samples from a UK clinical cohort of acute and convalescent COVID-19 cases (n=212), together with convalescent plasma samples collected by NHS Blood and Transplant (NHSBT) (n=462 additional samples). To determine whether PCR-positive blood samples could pose an infection risk, we attempted virus isolation from a subset of RNA-positive samples.

Results: We identified 28 relevant studies, reporting SARS-CoV-2 RNA in 0-76% of blood samples; pooled estimate 10% (95%CI 5-18%). Among serum samples from our clinical cohort, 27/212 (12.7%) had SARS-CoV-2 RNA detected by RT-PCR. RNA detection occurred in samples up to day 20 post symptom onset, and was associated with more severe disease (multivariable odds ratio 7.5). Across all samples collected ≥28 days post symptom onset, 0/494 (0%, 95%CI 0-0.7%) had vRNA detected. Among our PCR-positive samples, cycle threshold (ct) values were high (range 33.5-44.8), suggesting low vRNA copy numbers. PCR-positive sera inoculated into cell culture did not produce any cytopathic effect or yield an increase in detectable SARS-CoV-2 RNA.

Conclusions: vRNA was detectable at low viral loads in a minority of serum samples collected in acute infection, but was not associated with infectious SARS-CoV-2 (within the limitations of the assays used). This work helps to inform biosafety precautions for handling blood products from patients with current or previous COVID-19.

Article activity feed

  1. Version published to 10.12688/wellcomeopenres.16002.1
  2. ScreenIT

    SciScore for 10.1101/2020.05.21.20105486: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementConsent: Convalescent healthcare workers with hospital encounters (n=38) and convalescent patients (n=32) provided informed consent for recruitment into the ISARIC WHO Clinical Characterisation Protocol UK (ISARIC
    IRB: WHO CCP-UK), with ethics approval by the South Central (Oxford C) Research Ethics Committee in England (Ref: 13/SC/0149), and Scotland A Research Ethics Committee in Scotland (Ref: 20/SS/0028).
    Randomizationnot detected.
    BlindingSamples VC01-20 were provided blinded for viral culture experiments.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Experimental Models: Cell Lines
    SentencesResources
    50 μL aliquots of samples VC1-VC20 were separately added to 2.4 × 105 Vero E6 cells (Cell Bank, Sir William Dunn School of Pathology, University of Oxford) in 24 well plates.
    Vero E6
    suggested: None
    Software and Algorithms
    SentencesResources
    Terminology and definitions: Systematic literature review: We searched PubMed, Web of Science, MedRxiv and Google between 7th-11th May 2020, using the search terms (“SARS-CoV-2” OR “COVID” OR “2019-nCoV” OR “COVID-19” OR “2019 NCOV” or “SARS COV 2” or “2019NCOV” or “2019-nCoV” or “2019 novel coronavirus”) AND (“qPCR” OR “RT-PCR” OR “PCR” OR “VIRAL LOAD” OR “RNAaemia” OR “RNAemia” OR “viraemia” OR “viremia” OR “RNA-aemia” OR “RNA-emia”
    PubMed
    suggested: (PubMed, RRID:SCR_004846)
    Data were collated in Microsoft Excel.
    Microsoft Excel
    suggested: (Microsoft Excel, RRID:SCR_016137)
    We analysed and presented data using GraphPad Prism v.8.3.1.
    GraphPad Prism
    suggested: (GraphPad Prism, RRID:SCR_002798)

    Results from OddPub: Thank you for sharing your data.

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Caveats and limitations: Datasets reported in the literature represent mostly a small number of carefully selected patients, typically in the acute hospital setting and therefore biased towards inclusion of more unwell patients meeting WHO criteria for severe or critical disease. Recognising that the field that is currently moving at pace, we elected to include papers from the pre-print server MedRxiv, for which peer review has not been undertaken. As a result, not all material included has undergone this quality assurance step. Published reports frequently do not include timing of sample collection relative to diagnostic respiratory samples and/or symptom onset, samples from individuals with trivial or absent symptoms are not well represented in existing studies and there are insufficient data to distinguish between frequency or quantification of vRNA present in whole blood, versus serum or plasma. Due to the logistics of rapid recuitment of different patient groups through different pathways, RT-PCR methods varied by cohort, potentially introducing some variation in the sensitivity of detection. In our clinical samples, we adopted an inclusive approach to reporting detection of vRNA, by including samples with Ct values above those which would normally be called positive by a clinical diagnostic facility. This may lead to an over-estimation of the true prevalence of RNA-aemia in this sample group. Many previous publications do not report ct values and direct comparisons betw...

    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.
    • Thank you for including a protocol registration statement.

    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 10.1101/2020.05.21.20105486 on medRxiv