Identification of a Novel Susceptibility Marker for SARS-CoV-2 Infection in Human Subjects and Risk Mitigation with a Clinically Approved JAK Inhibitor in Human/Mouse Cells

  1. Marianne R. Spalinger
  2. Rong Hai
  3. Jiang Li
  4. Alina N. Santos
  5. Tara M. Nordgren
  6. Michel L. Tremblay
  7. Lars Eckmann
  8. Elaine Hanson
  9. Michael Scharl
  10. Xiwei Wu
  11. Brigid S. Boland
  12. Declan F. McCole

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Abstract

Coronavirus disease (COVID-19), caused by SARS-CoV-2, has affected over 65 million individuals and killed over 1.5 million persons (December 8, 2020; www.who.int ) 1 . While fatality rates are higher among the elderly and those with underlying comorbidities 2 , host factors that promote susceptibility to SARS-CoV-2 infection and severe disease are poorly understood. Although individuals with certain autoimmune/inflammatory disorders show increased susceptibility to viral infections, there is incomplete knowledge of SARS-CoV-2 susceptibility in these diseases. 3–7 We report that the autoimmune PTPN2 risk variant rs1893217 promotes expression of the SARS-CoV-2 receptor, ACE2, and increases cellular entry mediated by SARS-CoV-2 spike protein. Elevated ACE2 expression and viral entry were mediated by increased JAK-STAT signalling, and were reversed by the JAK inhibitor, tofacitinib. Collectively, our findings uncover a novel risk biomarker for increased expression of the SARS-CoV-2 receptor and viral entry, and identify a clinically approved therapeutic agent to mitigate this risk.

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  1. ScreenIT

    SciScore for 10.1101/2020.12.09.416586: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementConsent: All patients provided informed consent.
    IACUC: All mouse experiments were conducted according to protocols approved by the IACUC commission of the University of California Riverside (
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    PTPN2 phosphatase assay: For PTPN2 activity measurements, 100 μg protein lysates were pre-cleared for 1 h using Sepharose A beads, incubated with 2 μl anti-PTPN2 antibody (Clone D7T7D, Cell Signaling Technologies) over night, incubated with Sepharose A beads for 1 h and centrifuged (3 min. at 12’000 g at 4°C).
    anti-PTPN2
    suggested: (Cell Signaling Technology Cat# 58935, RRID:AB_2799550)
    Experimental Models: Cell Lines
    SentencesResources
    VLPs and measurement of VLP uptake: To produce pseudoparticles, 293T cells were transfected with plasmids encoding a minimal HIV (pTRIP, CSGW, CSPW) provirus expressing the Gaussia Luciferase (Gluc)
    293T
    suggested: NCBI_Iran Cat# C498, RRID:CVCL_0063)
    , Caco-2BBe, A549 and THP-1 cells were originally obtained from ATCC and cultured according to the manufacturer’s recommendation in medium with 10% FCS.
    Caco-2BBe
    suggested: None
    A549
    suggested: None
    THP-1
    suggested: None
    Experimental Models: Organisms/Strains
    SentencesResources
    Mice: PTPN2-knock-out (KO) mice in the BALB/c background were a gift from Prof. M.
    BALB/c
    suggested: RRID:IMSR_ORNL:BALB/cRl)
    To generate mice lacking PTPN2 specifically in intestinal epithelial cells (ΔIEC mice), mice with a loxP-flanked exon 3 of the PTPN2 gene (PTPN2-fl/fl mice, originally obtained from EUCOMM, abbreviated as fl/fl) were crossed with VillinCre-ERT2 mice (Jackson Laboratories).
    PTPN2-fl/fl
    suggested: None
    VillinCre-ERT2
    suggested: None
    Software and Algorithms
    SentencesResources
    The sequences were aligned to human genome assembly hg38 using Tophat2 v2.0.14.
    Tophat2
    suggested: None
    RNA-seq data quality was evaluated using RSeQC v2.5.
    RSeQC
    suggested: (RSeQC, RRID:SCR_005275)
    For each sample, expression counts for Ensembl genes (v92) were summarized by HTseq v0.6.1, and reads per kilobase of transcript per million mapped reads (RPKM) were calculated.
    HTseq
    suggested: (HTSeq, RRID:SCR_005514)
    Count normalization and differential expression analyses between groups were conducted using Bioconductor package “DESeq2” v1.14.1.
    Bioconductor
    suggested: (Bioconductor, RRID:SCR_006442)
    The Gene Ontology and pathway analysis was performed using DAVID online tools and Ingenuity Pathway Analysis (IPA).
    DAVID
    suggested: (DAVID, RRID:SCR_001881)
    Ingenuity Pathway Analysis
    suggested: (Ingenuity Pathway Analysis, RRID:SCR_008653)
    Significant differences were determined using GraphPad Prism v9 software using analysis of variance (ANOVA). p-values below 0.05 were considered significant.
    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.
    • No funding statement was detected.
    • 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.

  2. Version published to 10.1101/2020.12.09.416586v1 on bioRxiv