Impaired function and delayed regeneration of dendritic cells in COVID-19

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Abstract

Disease manifestations in COVID-19 range from mild to severe illness associated with a dysregulated innate immune response. Alterations in function and regeneration of dendritic cells (DC) and monocytes may contribute to immunopathology and influence adaptive immune responses in COVID-19 patients. We analyzed circulating DC and monocyte subsets in 65 hospitalized COVID-19 patients with mild/moderate or severe disease from acute disease to recovery and in healthy controls. Persisting reduction of all DC subpopulations was accompanied by an expansion of proliferating Lineage - HLADR + cells lacking DC markers. Increased frequency of the recently discovered CD163 + CD14 + DC3 subpopulation in patients with more severe disease was associated with systemic inflammation, activated T follicular helper cells, and antibody-secreting cells. Persistent downregulation of CD86 and upregulation of PD-L1 in conventional DC (cDC2 and DC3) and classical monocytes associated with a reduced capacity to stimulate naïve CD4 + T cells correlated with disease severity. Long-lasting depletion and functional impairment of DCs and monocytes may have consequences for susceptibility to secondary infections and therapy of COVID-19 patients.

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  1. SciScore for 10.1101/2021.05.26.445809: (What is this?)

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

    Table 1: Rigor

    EthicsConsent: Written informed consent was received from participants prior to inclusion in the study and patient data were anonymized for analysis.
    IRB: The study was approved by the local ethics committee (No. 20-245).
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    T cells were stained with Cell Trace Violet dye (ThermoFisher, cat. #C34557) washed twice with RPMI 1640 (10% FCS) and cocultured with DC3 or monocytes (APC:T 1:2 ratio) in 150 µl of RPMI 1640 (Biochrom, 10% FCS, 100 U/ml penicillin, 100 μg/ml streptomycin, 1% non-essential amino acids, 1 mM sodium pyruvate, 2 mM GlutaMAX™, 0.05 mM β-mercaptoethanol) on a 96-well flat bottom plate coated with anti-CD3 antibody (10µg/ml, cat. # 317325, BioLegend).
    DC3
    suggested: (Novus Cat# NB 100-2694, RRID:AB_608325)
    anti-CD3
    suggested: None
    Anti-SARS-CoV-2 antibody detection assays: The following commercial CE in vitro diagnostics (IVD) marked assays were used to determine the presence of SARS-CoV-2-specific antibodies in serum specimens: Architect SARS-CoV-2 IgG (6R86, Abbott, Illinois, USA) detecting anti-nucleocapsid antibodies and Anti-SARS-CoV-2-ELISA IgG (EI 2606-9601 G, EuroImmun, Lübeck, Germany
    Anti-SARS-CoV-2
    suggested: (PhosphoSolutions Cat# CoV2-2G1, RRID:AB_2868397)
    anti-nucleocapsid
    suggested: None
    Anti-SARS-CoV-2-ELISA IgG
    suggested: None
    Software and Algorithms
    SentencesResources
    FCS files were exported and analyzed with FlowJo software v10.7.1.
    FlowJo
    suggested: (FlowJo, RRID:SCR_008520)
    FlowJo workspace was imported with flowWorkspace::open_flowjo_xml (flowWorkspace version 4.2.0).
    flowWorkspace
    suggested: (flowWorkspace, RRID:SCR_001155)
    Anti-SARS-CoV-2 antibody detection assays: The following commercial CE in vitro diagnostics (IVD) marked assays were used to determine the presence of SARS-CoV-2-specific antibodies in serum specimens: Architect SARS-CoV-2 IgG (6R86, Abbott, Illinois, USA) detecting anti-nucleocapsid antibodies and Anti-SARS-CoV-2-ELISA IgG (EI 2606-9601 G, EuroImmun, Lübeck, Germany
    Abbott
    suggested: (Abbott, RRID:SCR_010477)
    Statistical analysis: Statistical analysis was performed using GraphPad Prism 9.1.0 and R 4.0.3 (packages used: ggplot2_3.3.3, ComplexHeatmap_2.4.3, ggstatsplot_0.6.8, bestNormalize_1.7.0, robustbase_0.93.7)
    GraphPad Prism
    suggested: (GraphPad Prism, RRID:SCR_002798)

    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.

    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.