Caspases and therapeutic potential of caspase inhibitors in moderate–severe SARS‐CoV‐2 infection and long COVID

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Abstract

Background

COVID‐19 can present with lymphopenia and extraordinary complex multiorgan pathologies that can trigger long‐term sequela.

Aims

Given that inflammasome products, like caspase‐1, play a role in the pathophysiology of a number of co‐morbid conditions, we investigated caspases across the spectrum of COVID‐19 disease.

Materials & Methods

We assessed transcriptional states of multiple caspases and using flow cytometry, the expression of active caspase‐1 in blood cells from COVID‐19 patients in acute and convalescent stages of disease. Non‐COVID‐19 subject presenting with various comorbid conditions served as controls.

Results

Single‐cell RNA‐seq data of immune cells from COVID‐19 patients showed a distinct caspase expression pattern in T cells, neutrophils, dendritic cells, and eosinophils compared with controls. Caspase‐1 was upregulated in CD4+ T‐cells from hospitalized COVID‐19 patients compared with unexposed controls. Post‐COVID‐19 patients with lingering symptoms (long‐haulers) also showed upregulated caspase‐1activity in CD4+ T‐cells that ex vivo was attenuated with a select pan‐caspase inhibitor. We observed elevated caspase‐3/7levels in red blood cells from COVID‐19 patients compared with controls that was reduced following caspase inhibition.

Discussion

Our preliminary results suggest an exuberant caspase response in COVID‐19 that may facilitate immune‐related pathological processes leading to severe outcomes. Further clinical correlations of caspase expression in different stages of COVID‐19 will be needed.

Conclusion

Pan‐caspase inhibition could emerge as a therapeutic strategy to ameliorate or prevent severe COVID‐19.

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  1. SciScore for 10.1101/2020.11.02.20223636: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementConsent: Control blood samples from healthy volunteers without SARS CoV-2 infection or co-morbid conditions were collected after obtaining written informed consent.
    IRB: All human studies were approved by institutional review boards (IRB 269846-10 and 1285028 protocols from State University of New York Downstate Medical Center and Amerimmune respectively).
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    RNA-Seq data from cell lines infected in vitro with SARS-CoV-2 was accessed from GEO: GSE147507 (28).
    SARS-CoV-2
    suggested: (Active Motif Cat# 91351, RRID:AB_2847848)
    Expression values for Caspase genes were normalized by DESeq2.
    DESeq2
    suggested: (DESeq, RRID:SCR_000154)
    All statistical tests were performed with GraphPad Prism version 8.0 (Graphpad Software Inc., CA, USA).
    GraphPad Prism
    suggested: (GraphPad Prism, RRID:SCR_002798)
    Graphpad
    suggested: (GraphPad, RRID:SCR_000306)

    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: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    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.