Markers of Immune Activation and Inflammation in Individuals With Postacute Sequelae of Severe Acute Respiratory Syndrome Coronavirus 2 Infection

  1. Michael J Peluso
  2. Scott Lu
  3. Alex F Tang
  4. Matthew S Durstenfeld
  5. Hsi-en Ho
  6. Sarah A Goldberg
  7. Carrie A Forman
  8. Sadie E Munter
  9. Rebecca Hoh
  10. Viva Tai
  11. Ahmed Chenna
  12. Brandon C Yee
  13. John W Winslow
  14. Christos J Petropoulos
  15. Bryan Greenhouse
  16. Peter W Hunt
  17. Priscilla Y Hsue
  18. Jeffrey N Martin
  19. J Daniel Kelly
  20. David V Glidden
  21. Steven G Deeks
  22. Timothy J Henrich

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Abstract

Background

The biological processes associated with postacute sequelae of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (PASC) are unknown.

Methods

We measured soluble markers of inflammation in a SARS-CoV-2 recovery cohort at early (<90 days) and late (>90 days) timepoints. We defined PASC as the presence of 1 or more coronavirus disease 2019 (COVID-19)–attributed symptoms beyond 90 days. We compared fold-changes in marker values between those with and without PASC using mixed-effects models with terms for PASC and early and late recovery time periods.

Results

During early recovery, those who went on to develop PASC generally had higher levels of cytokine biomarkers including tumor necrosis factor–α (1.14-fold higher mean ratio [95% confidence interval {CI}, 1.01–1.28]; P = .028) and interferon-γ–induced protein 10 (1.28-fold higher mean ratio [95% CI, 1.01–1.62]; P = .038). Among those with PASC, there was a trend toward higher interleukin 6 levels during early recovery (1.29-fold higher mean ratio [95% CI, .98–1.70]; P = .07), which became more pronounced in late recovery (1.44-fold higher mean ratio [95% CI, 1.11–1.86]; P < .001). These differences were more pronounced among those with a greater number of PASC symptoms.

Conclusions

Persistent immune activation may be associated with ongoing symptoms following COVID-19. Further characterization of these processes might identify therapeutic targets for those experiencing PASC.

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  1. Version published to 10.1093/infdis/jiab490
  2. ScreenIT

    SciScore for 10.1101/2021.07.09.21260287: (What is this?)

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

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Biomarker and antibody assays: The fully automated HD-X Simoa platform was used to measure biomarkers in blood plasma including monocyte chemoattractant protein 1 (MCP-1), Cytokine 3-PlexA (IL-6, IL-10, TNFa)
    IL-6
    suggested: None
    IL-10
    suggested: None

    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:
    Limitations of this study include the use of a convenience sample that may not be representative of the SARS-CoV- 2 epidemic and lack of specimens from the acute infection period. There is currently no widely agreed upon case definition for PASC, and we adopted a broad case definition which might be overly sensitive. We also used a rough temporal cutoff to classify PASC, which may have led to misclassification bias in our results. Still, our sensitivity analyses showed similar findings, suggesting the presence of a true effect. We measured a relatively small number of biomarkers based on hypotheses derived from published signatures during acute infection, but more in depth biomarker characterization may be more revealing. While we performed multiple statistical analyses, our findings were consistent with our prespecified hypotheses. Nonetheless, our observation will help inform on mechanistic pathways that could contribute to PASC and direct future research leading to the identification of potential therapeutic targets.

    Results from TrialIdentifier: We found the following clinical trial numbers in your paper:

    IdentifierStatusTitle
    NCT04362150Active, not recruitingLong-term Impact of Infection With Novel Coronavirus (COVID-…

    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.

    Results from scite Reference Check: We found no unreliable references.

    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 10.1101/2021.07.09.21260287v1 on medRxiv