Decreased plasma levels of the survival factor renalase are associated with worse outcomes in COVID-19

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Abstract

Introduction

Renalase (RNLS), a novel secreted plasma flavoprotein, has anti-inflammatory effects in a variety of disease processes. Severe COVID-19 disease is associated with disordered inflammatory responses. We hypothesized that reduced plasma RNLS levels could be a marker of COVID-19 disease severity.

Methods

Plasma was collected from 51 hospitalized COVID-19 patients and 15 uninfected non-hospitalized controls. Plasma RNLS and cytokine levels were measured and sociodemographic and clinical data were collected from chart review. Data were analyzed using nonparametric analyses and Kaplan Meir curve log rank analysis.

Results

Plasma RNLs levels were negatively correlated with inflammatory markers, including IL-1β, IL-6, and TNFα (p = 0.04, p = 0.03, p = 0.01, respectively). Patients with COVID-19 disease had lower levels of RNLS than controls. Lower levels of RNLS were associated with more severe disease among COVID-19 patients. Low RNLS was also associated with worse survival among COVID-19 patients (HR = 4.54; 95% CI: 1.06-19.43; p = 0.005).

Conclusion

Low plasma RNLS levels are associated with severe COVID-19 disease and may be a useful additional biomarker when identifying patients with severe COVID-19 disease. Given RNLS’ antiinflammatory properties and negative correlation with inflammatory markers, these findings also suggest evidence of a potential pathophysiological mechanism for severe COVID-19 disease.

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  1. SciScore for 10.1101/2020.06.02.20120865: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: The protocol was approved by the local institutional review board (HIC 2000027792)
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Analysis was conducted using nonparametric statistical methodologies (SPSS Version 24, IBM Statistics; Armonk, NY)
    SPSS
    suggested: (SPSS, RRID:SCR_002865)

    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

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