Monocytopenia, monocyte morphological anomalies and hyperinflammation characterise severe COVID‐19 in type 2 diabetes

  1. Fawaz Alzaid
  2. Jean‐Baptiste Julla
  3. Marc Diedisheim
  4. Charline Potier
  5. Louis Potier
  6. Gilberto Velho
  7. Bénédicte Gaborit
  8. Philippe Manivet
  9. Stéphane Germain
  10. Tiphaine Vidal‐Trecan
  11. Ronan Roussel
  12. Jean‐Pierre Riveline
  13. Elise Dalmas
  14. Nicolas Venteclef
  15. Jean‐François Gautier

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Abstract

Early in the COVID‐19 pandemic, type 2 diabetes (T2D) was marked as a risk factor for severe disease and mortality. Inflammation is central to the aetiology of both conditions where variations in immune responses can mitigate or aggravate disease course. Identifying at‐risk groups based on immunoinflammatory signatures is valuable in directing personalised care and developing potential targets for precision therapy. This observational study characterised immunophenotypic variation associated with COVID‐19 severity in T2D. Broad‐spectrum immunophenotyping quantified 15 leucocyte populations in peripheral circulation from a cohort of 45 hospitalised COVID‐19 patients with and without T2D. Lymphocytopenia and specific loss of cytotoxic CD8 + lymphocytes were associated with severe COVID‐19 and requirement for intensive care in both non‐diabetic and T2D patients. A morphological anomaly of increased monocyte size and monocytopenia restricted to classical CD14 Hi CD16 − monocytes was specifically associated with severe COVID‐19 in patients with T2D requiring intensive care. Increased expression of inflammatory markers reminiscent of the type 1 interferon pathway (IL6, IL8, CCL2, INFB1) underlaid the immunophenotype associated with T2D. These immunophenotypic and hyperinflammatory changes may contribute to increased voracity of COVID‐19 in T2D. These findings allow precise identification of T2D patients with severe COVID‐19 as well as provide evidence that the type 1 interferon pathway may be an actionable therapeutic target for future studies.

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  1. Version published to 10.15252/emmm.202013038
  2. ScreenIT

    SciScore for 10.1101/2020.06.02.20119909: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: This study was approved by local institutions and ethical committees, the Ethics Committee of CPP Ile-de-France granted approval for all individuals (Ile de France V number 15070).
    Consent: All patients provided informed consent indicating that they understood the nature of their participation in the study (NCT02671864).
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    The following antibodies were used: anti-HLA-DR (AC122) and anti-CD8 (BW135/80) from Miltenyi; anti-CD14 (MΦP9), anti-CD3 (UCHT1) and anti-CD123 (7G3) from BD Biosciences; anti-CD16 (
    anti-HLA-DR (AC122
    suggested: None
    anti-CD8
    suggested: None
    anti-CD14
    suggested: None
    anti-CD3
    suggested: None
    anti-CD123
    suggested: None
    anti-CD16
    suggested: None
    After washing, cells were fixed and stained using the Foxp3-staining kit (00–5523–00; Thermo Fisher Scientific) according to the manufacturer’s protocol and using the anti-IRF5 (ab21689; Abcam) antibody for 1h at 4°C in the dark, followed by the donkey-anti-Rabbit-PE (12–4739–81; Thermo Fisher Scientific) secondary antibody for 20 minutes at 4°C in the dark.
    anti-IRF5
    suggested: (Abcam Cat# ab21689, RRID:AB_446483)
    Software and Algorithms
    SentencesResources
    The following antibodies were used: anti-HLA-DR (AC122) and anti-CD8 (BW135/80) from Miltenyi; anti-CD14 (MΦP9), anti-CD3 (UCHT1) and anti-CD123 (7G3) from BD Biosciences; anti-CD16 (
    BD Biosciences
    suggested: (BD Biosciences, RRID:SCR_013311)
    Acquisition was performed on a LSR-Fortessa flow cytometer (BD Biosciences) and analysed with FlowJo software (Tree Star).
    FlowJo
    suggested: (FlowJo, RRID:SCR_008520)
    Primer sequences were designed using Primer3 (32)(33) (http://bioinfo.ut.ee/primer3-0.4.0/) used: IL8 (F: AGACAGCAGAGCACACAAGC; and R: ATGGTTCCTTCCGGTGGT); CCL2 (F: TTCTGTGCCTGCTGCTCAT; and R: GGGGCATTGATTGCATCT); IRF5 (F: GATGGGGACAACACCATCTT; and R: GGCTTTTGTTAAGGGCACAG); IL6 (F: GCCCAGCTATGAACTCCTTCT; and R: GAAGGCAGCAGGCAACAC); IFNB1 (F: GGAAAGAGGAGAGTGACAGAAAA; and R: TTGGATGCTCTGGTCATCTTTA) and 18S (F: TTCGAACGTCTGCCCTATCAA; and R: ATGGTAGGCACGGCGACTA).
    Primer3
    suggested: (Primer3, RRID:SCR_003139)
    Statistical analyses were carried out using JMP (SAS Institute Inc, Cary, NC), XLSTAT 2014 (Addinsoft, Brooklyn, NY),
    SAS Institute
    suggested: (Statistical Analysis System, RRID:SCR_008567)
    , Graphpad Prism (Graphpad), SPSS Statistics (SPSS corporation) and R Software 3.6.0 (http://www.r-project.org).
    Graphpad
    suggested: (GraphPad, RRID:SCR_000306)
    SPSS
    suggested: (SPSS, RRID:SCR_002865)
    http://www.r-project.org
    suggested: (R Project for Statistical Computing, RRID:SCR_001905)
    Principal component analysis (PCA) was performed from total lymphocyte and monocytes sub-populations FACS quantification with FactoMineR R package (doi 10.18637/jss.v025.i01), and factoextra package (factoextra.bib) was used to construct graphics.
    FactoMineR
    suggested: (FactoMineR, RRID:SCR_014602)

    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: We found the following clinical trial numbers in your paper:

    IdentifierStatusTitle
    NCT02671864RecruitingIncretin-mimetic Hypoglycemic Drugs and Severe Retinopathy

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: Please consider improving the rainbow (“jet”) colormap(s) used on pages 18, 19 and 29. At least one figure is not accessible to readers with colorblindness and/or is not true to the data, i.e. not perceptually uniform.

    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 10.1101/2020.06.02.20119909 on medRxiv