Immunofibrotic drivers of impaired lung function in postacute sequelae of SARS-CoV-2 infection

  1. Hyung J. Chun
  2. Elias Coutavas
  3. Alexander B. Pine
  4. Alfred I. Lee
  5. Vanessa L. Yu
  6. Marcus K. Shallow
  7. Coral X. Giovacchini
  8. Anne M. Mathews
  9. Brian Stephenson
  10. Loretta G. Que
  11. Patty J. Lee
  12. Bryan D. Kraft

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Abstract

Individuals recovering from COVID-19 frequently experience persistent respiratory ailments, which are key elements of postacute sequelae of SARS-CoV-2 infection (PASC); however, little is known about the underlying biological factors that may direct lung recovery and the extent to which these are affected by COVID-19 severity.

METHODS

We performed a prospective cohort study of individuals with persistent symptoms after acute COVID-19, collecting clinical data, pulmonary function tests, and plasma samples used for multiplex profiling of inflammatory, metabolic, angiogenic, and fibrotic factors.

RESULTS

Sixty-one participants were enrolled across 2 academic medical centers at a median of 9 weeks (interquartile range, 6–10 weeks) after COVID-19 illness: n = 13 participants (21%) had mild COVID-19 and were not hospitalized, n = 30 participants (49%) were hospitalized but were considered noncritical, and n = 18 participants (30%) were hospitalized and in the intensive care unit (ICU). Fifty-three participants (85%) had lingering symptoms, most commonly dyspnea (69%) and cough (58%). Forced vital capacity (FVC), forced expiratory volume in 1 second (FEV1), and diffusing capacity for carbon monoxide (DLCO) declined as COVID-19 severity increased ( P < 0.05) but these values did not correlate with respiratory symptoms. Partial least-squares discriminant analysis of plasma biomarker profiles clustered participants by past COVID-19 severity. Lipocalin-2 (LCN2), MMP-7, and HGF identified by our analysis were significantly higher in the ICU group ( P < 0.05), inversely correlated with FVC and DLCO ( P < 0.05), and were confirmed in a separate validation cohort ( n = 53).

CONCLUSION

Subjective respiratory symptoms are common after acute COVID-19 illness but do not correlate with COVID-19 severity or pulmonary function. Host response profiles reflecting neutrophil activation (LCN2), fibrosis signaling (MMP-7), and alveolar repair (HGF) track with lung impairment and may be novel therapeutic or prognostic targets.

Funding

National Heart, Lung, and Blood Institute (K08HL130557 and R01HL142818), American Heart Association (Transformational Project Award), the DeLuca Foundation Award, a donation from Jack Levin to the Benign Hematology Program at Yale University, and Duke University.

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  1. Version published to 10.1172/jci.insight.148476
  2. ScreenIT

    SciScore for 10.1101/2021.01.31.21250870: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: Subject Enrollment: The studies were approved by the institutional review boards of Yale University (#2000027792 and #1401013259) and Duke University (Pro00105518 and Pro00106151).
    Consent: Written informed consent was provided by all subjects prior to study activities.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Differences between groups were analyzed by Kruskal-Wallis test with Benjamini-Hochberg post-hoc test to control for false discovery rate or one-way ANOVA with Fisher’s LSD post-hoc test (Graphpad Prism, San Diego, CA).
    Graphpad
    suggested: (GraphPad, RRID:SCR_000306)
    Simple linear regression were performed by Prism.
    Prism
    suggested: (PRISM, RRID:SCR_005375)
    Partial least-squares discriminant analysis (PLS-DA) was performed using SIMCA v15 (Umetrics, Umeå, Sweden).
    SIMCA
    suggested: (SIMCA, RRID:SCR_014688)
    The random-forest feature selection (Boruta algorithm) was performed using the Boruta package in R software.
    Boruta
    suggested: (Boruta, RRID:SCR_016234)

    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:
    Our study has several limitations. First, we only recruited subjects that had ongoing symptoms after COVID-19 infection, therefore we cannot report the true prevalence of symptoms or pulmonary function derangements in subjects with asymptomatic infection or in subjects with symptom resolution after COVID-19 infection. Second, our plasma biomarker profiles represent a single time point for each subject, and therefore we cannot draw conclusions about trajectory or changes over time. Third, we cannot establish mechanism in this human cohort study; however, our findings are highly associational and lay the foundations to drive further work in this area. In conclusion, persistent respiratory symptoms and impaired lung function are common after acute COVID-19 illness, but subjective symptoms alone do not predict lung injury. Partial least-squares discriminant analysis reliably identifies and separates subjects by COVID-19 illness severity based on their plasma biomarker profiles, even 9 weeks after recovery. Circulating factors associated with acute neutrophil activation, fibrosis signaling, and alveolar epithelial repair remain elevated in survivors of acute COVID-19 infection and strongly associate with impaired pulmonary function. Our study provides novel insights into divergent host responses of lung repair after COVID-19 pneumonia and suggest that immunologic and fibrotic drivers of disease severity in the acute COVID-19 illness may regulate the trajectory of recovery in the p...

    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 10.1101/2021.01.31.21250870 on medRxiv