Sex differences in immune responses that underlie COVID-19 disease outcomes

  1. Takehiro Takahashi
  2. Mallory K. Ellingson
  3. Patrick Wong
  4. Benjamin Israelow
  5. Carolina Lucas
  6. Jon Klein
  7. Julio Silva
  8. Tianyang Mao
  9. Ji Eun Oh
  10. Maria Tokuyama
  11. Peiwen Lu
  12. Arvind Venkataraman
  13. Annsea Park
  14. Feimei Liu
  15. Amit Meir
  16. Jonathan Sun
  17. Eric Y. Wang
  18. Arnau Casanovas-Massana
  19. Anne L. Wyllie
  20. Chantal B. F. Vogels
  21. Rebecca Earnest
  22. Sarah Lapidus
  23. Isabel M. Ott
  24. Adam J. Moore
  25. Yale IMPACT Research Team
  26. Kelly Anastasio
  27. Michael H. Askenase
  28. Maria Batsu
  29. Hannah Beatty
  30. Santos Bermejo
  31. Sean Bickerton
  32. Kristina Brower
  33. Molly L. Bucklin
  34. Staci Cahill
  35. Melissa Campbell
  36. Yiyun Cao
  37. Edward Courchaine
  38. Rupak Datta
  39. Giuseppe DeIuliis
  40. Bertie Geng
  41. Laura Glick
  42. Ryan Handoko
  43. Chaney Kalinich
  44. William Khoury-Hanold
  45. Daniel Kim
  46. Lynda Knaggs
  47. Maxine Kuang
  48. Eriko Kudo
  49. Joseph Lim
  50. Melissa Linehan
  51. Alice Lu-Culligan
  52. Amyn A. Malik
  53. Anjelica Martin
  54. Irene Matos
  55. David McDonald
  56. Maksym Minasyan
  57. Subhasis Mohanty
  58. M. Catherine Muenker
  59. Nida Naushad
  60. Allison Nelson
  61. Jessica Nouws
  62. Marcella Nunez-Smith
  63. Abeer Obaid
  64. Isabel Ott
  65. Hong-Jai Park
  66. Xiaohua Peng
  67. Mary Petrone
  68. Sarah Prophet
  69. Harold Rahming
  70. Tyler Rice
  71. Kadi-Ann Rose
  72. Lorenzo Sewanan
  73. Lokesh Sharma
  74. Denise Shepard
  75. Erin Silva
  76. Michael Simonov
  77. Mikhail Smolgovsky
  78. Eric Song
  79. Nicole Sonnert
  80. Yvette Strong
  81. Codruta Todeasa
  82. Jordan Valdez
  83. Sofia Velazquez
  84. Pavithra Vijayakumar
  85. Haowei Wang
  86. Annie Watkins
  87. Elizabeth B. White
  88. Yexin Yang
  89. Albert Shaw
  90. John B. Fournier
  91. Camila D. Odio
  92. Shelli Farhadian
  93. Charles Dela Cruz
  94. Nathan D. Grubaugh
  95. Wade L. Schulz
  96. Aaron M. Ring
  97. Albert I. Ko
  98. Saad B. Omer
  99. Akiko Iwasaki

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Abstract

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  1. ScreenIT

    SciScore for 10.1101/2020.06.06.20123414: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: Ethics statement: This study was approved by Yale Human Research Protection Program Institutional Review Boards (FWA00002571, Protocol ID. 2000027690)
    Consent: Informed consents was obtained from all enrolled patients and healthcare workers.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variableThis patient group, Cohort A, consisted of 39 patients (17 men and 22 women).

    Table 2: Resources

    Antibodies
    SentencesResources
    Plasma and PBMCs were isolated from whole blood and plasma was used for titer measurements of SARS-CoV-2 spike S1 protein specific IgG and IgM antibodies (anti-S1 IgG and IgM) and cytokine/chemokine measurements.
    IgM
    suggested: None
    anti-S1 IgG
    suggested: None
    Among these patients, we could obtain whole blood for flow cytometry analysis using fresh PBMCs, plasma for cytokine/chemokine measurements, anti-S1 antibody measurements and nasopharyngeal swab and saliva from total of 93 individuals for the present study.
    anti-S1
    suggested: None
    Plates were washed three times with PBS-T (PBS with 0.1% Tween-20) and 50 µl of HRP anti-Human IgG Antibody (GenScript #A00166, 1:5000) or anti-Human IgM-Peroxidase
    anti-Human IgG
    suggested: None
    anti-Human IgM-Peroxidase
    suggested: None
    Flow cytometry: Exact antibody clones and vendors that were used for flow cytometric analysis are as follows: BB515 anti-HLA-DR (G46-6), BV785 anti-CD16 (3G8)
    anti-HLA-DR ( G46-6
    suggested: None
    anti-CD16
    suggested: None
    Software and Algorithms
    SentencesResources
    Ethics statement: This study was approved by Yale Human Research Protection Program Institutional Review Boards (FWA00002571, Protocol ID. 2000027690)
    Yale Human Research Protection Program
    suggested: None
    Data were analysed using FlowJo software version 10.6 software (Tree Star).
    FlowJo
    suggested: (FlowJo, RRID:SCR_008520)
    Bioconductor R software was used to generate heatmaps (Fig. 1c, 2a, 3a, 3g), XY graphs for correlation analyses (Fig. 2e and 4e), and Pearson correlation plots (Fig. 4d).
    Bioconductor
    suggested: (Bioconductor, RRID:SCR_006442)

    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.

  2. Version published to 10.1038/s41586-020-2700-3
  3. ScreenIT

    SciScore for 10.1101/2020.06.06.20123414: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statement12 Methods Ethics statement This study was approved by Yale Human Research Protection Program Institutional Review Boards ( FWA00002571 , Protocol ID . 2000027690)Randomizationnot detected.Blindingnot detected.Power Analysisnot detected.Sex as a biological variableHowever, whether immune responses against SARS-CoV-2 differ between sexes, and whether such differences explain male susceptibility to COVID-19, is currently unknown.

    Table 2: Resources

    Antibodies
    SentencesResources
    To elucidate the differential immune response against SARS-CoV-2 infection in men and women, we performed detailed analysis on the sex differences in immune phenotype via the assessment of viral loads, SARS-CoV-2 specific antibody levels, plasma cytokines/chemokines, and blood cell phenotypes.
    SARS-CoV-2
    suggested: None
    Plasma and PBMCs were isolated from whole 3 blood and plasma was used for titer measurements of SARS-CoV-2 spike S1 protein specific IgG and IgM antibodies (anti-S1 IgG and IgM) and cytokine/chemokine measurements.
    anti-S1 IgG
    suggested: None
    We found induction of anti-SARS-CoV-2 S1 protein specific IgG and IgM ( anti-S1-IgG and –IgM ) antibodies in the plasma of many patients , and IgG levels tended to be higher in female patients , though not significantly different from their male counterpart ( Fig . 1b) .
    anti-SARS-CoV-2 S1 protein specific IgG
    suggested: None
          <div style="margin-bottom:8px">
        <div><b>IgM ( anti-S1-IgG and –IgM )</b></div>
        <div>suggested: None</div>
      </div>
    </td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Among these patients , we could obtain whole blood for flow cytometry analysis using fresh PBMCs , plasma for cytokine/chemokine measurements , anti-S1 antibody measurements and nasopharyngeal swab and saliva from total of 93 individuals for the present study .</td><td style="min-width:100px;border-bottom:1px solid lightgray">
      <div style="margin-bottom:8px">
        <div><b>anti-S1</b></div>
        <div>suggested: (LifeSpan Cat# LS-C51545-40, <a href="https://scicrunch.org/resources/Any/search?q=AB_10556781">AB_10556781</a>)</div>
      </div>
    </td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Plates were washed three times with PBS-T ( PBS with 0.1 % Tween-20 ) and 50 µl of HRP anti-Human IgG Antibody ( GenScript #A00166 , 1:5000 ) or anti-Human IgM-Peroxidase Antibody ( SigmaAldrich #A6907 , 1:5000 ) diluted in dilution solution were added to each well .</td><td style="min-width:100px;border-bottom:1px solid lightgray">
      <div style="margin-bottom:8px">
        <div><b>anti-Human IgG</b></div>
        <div>suggested: None</div>
      </div>
    
      <div style="margin-bottom:8px">
        <div><b>anti-Human IgM-Peroxidase</b></div>
        <div>suggested: None</div>
      </div>
    </td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Flow cytometry Exact antibody clones and vendors that were used for flow cytometric analysis are as follows: BB515 anti-HLA-DR ( G46-6) , BV785 anti-CD16 ( 3G8)</td><td style="min-width:100px;border-bottom:1px solid lightgray">
      <div style="margin-bottom:8px">
        <div><b>anti-HLA-DR ( G46-6</b></div>
        <div>suggested: None</div>
      </div>
    
      <div style="margin-bottom:8px">
        <div><b>anti-CD16</b></div>
        <div>suggested: None</div>
      </div>
    </td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Bar = median . b , Titers of specific IgG and IgM antibody titers against SARS-CoV-2 S1 protein were measured.</td><td style="min-width:100px;border-bottom:1px solid lightgray">
      <div style="margin-bottom:8px">
        <div><b>median . b , Titers of specific IgG</b></div>
        <div>suggested: None</div>
      </div>
    
      <div style="margin-bottom:8px">
        <div><b>IgM</b></div>
        <div>suggested: None</div>
      </div>
    
      <div style="margin-bottom:8px">
        <div><b>SARS-CoV-2 S1 protein were measured.</b></div>
        <div>suggested: None</div>
      </div>
    </td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">a virus RNA copies, and anti-S1-IgG antibody are compared.</td><td style="min-width:100px;border-bottom:1px solid lightgray">
      <div style="margin-bottom:8px">
        <div><b>anti-S1-IgG</b></div>
        <div>suggested: None</div>
      </div>
    </td></tr><tr><td style="min-width:100px;text-align:center; padding-top:4px;" colspan="2"><b>Software and Algorithms</b></td></tr><tr><td style="min-width:100px;text=align:center"><i>Sentences</i></td><td style="min-width:100px;text-align:center"><i>Resources</i></td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">12 Methods Ethics statement This study was approved by Yale Human Research Protection Program Institutional Review Boards ( FWA00002571 , Protocol ID . 2000027690)</td><td style="min-width:100px;border-bottom:1px solid lightgray">
      <div style="margin-bottom:8px">
        <div><b>Yale Human Research Protection Program</b></div>
        <div>suggested: None</div>
      </div>
    </td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Data were analysed using FlowJo software version 10.6 software ( Tree Star) .</td><td style="min-width:100px;border-bottom:1px solid lightgray">
      <div style="margin-bottom:8px">
        <div><b>FlowJo</b></div>
        <div>suggested: (FlowJo, <a href="https://scicrunch.org/resources/Any/search?q=SCR_008520">SCR_008520</a>)</div>
      </div>
    </td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">Bioconductor R software was used to generate heatmaps ( Fig . 1c , 2a , 3a , 3g) , XY graphs for correlation analyses ( Fig . 2e and 4e) , and Pearson correlation plots ( Fig . 4d) .</td><td style="min-width:100px;border-bottom:1px solid lightgray">
      <div style="margin-bottom:8px">
        <div><b>Bioconductor</b></div>
        <div>suggested: (Bioconductor, <a href="https://scicrunch.org/resources/Any/search?q=SCR_006442">SCR_006442</a>)</div>
      </div>
    </td></tr><tr><td style="min-width:100px;vertical-align:top;border-bottom:1px solid lightgray">This work was supported by the Women’s Health Research at Yale Pilot Project Program ( AI , AR) , Fast Grant from Emergent Ventures at the Mercatus Center , Mathers Foundation , and the Ludwig Family Foundation . A . I . is an Investigator of the Howard Hughes Medical Institute.</td><td style="min-width:100px;border-bottom:1px solid lightgray">
      <div style="margin-bottom:8px">
        <div><b>Yale Pilot Project Program</b></div>
        <div>suggested: None</div>
      </div>
    </td></tr></table>

    Results from OddPub: We did not find a statement about open data. We also did not find a statement about open code. Researchers are encouraged to share open data when possible (see Nature blog).

    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 is not a substitute for expert review. SciScore checks for the presence and correctness of RRIDs (research resource identifiers) in the manuscript, and detects sentences that appear to be missing RRIDs. SciScore also checks to make sure that rigor criteria are addressed by authors. It does this by detecting sentences that discuss criteria such as blinding or power analysis. SciScore does not guarantee that the rigor criteria that it detects are appropriate for the particular study. Instead it assists authors, editors, and reviewers by drawing attention to sections of the manuscript that contain or should contain various rigor criteria and key resources. For details on the results shown here, including references cited, please follow this link.

  4. Version published to 10.1101/2020.06.06.20123414 on medRxiv