Anti-SARS-CoV-2 IgG responses are powerful predicting signatures for the outcome of COVID-19 patients

  1. Qing Lei
  2. Cai-zheng Yu
  3. Yang Li
  4. Hong-yan Hou
  5. Zhao-wei Xu
  6. Zong-jie Yao
  7. Yan-di Zhang
  8. Dan-yun Lai
  9. Jo-Lewis Banga Ndzouboukou
  10. Bo Zhang
  11. Hong Chen
  12. Zhu-qing Ouyang
  13. Jun-biao Xue
  14. Xiao-song Lin
  15. Yun-xiao Zheng
  16. Xue-ning Wang
  17. He-wei Jiang
  18. Hai-nan Zhang
  19. Huan Qi
  20. Shu-juan Guo
  21. Mei-an He
  22. Zi-yong Sun
  23. Feng Wang
  24. Sheng-ce Tao
  25. Xiong-lin Fan

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Abstract

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  3. Version published to 10.1016/j.jare.2021.11.014
  4. Version published to 10.1101/2020.11.10.20228890v3 on medRxiv
  5. Version published to 10.1101/2020.11.10.20228890v2 on medRxiv
  6. ScreenIT

    SciScore for 10.1101/2020.11.10.20228890: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: Ethical approval: The study was approved by the Ethical Committee of Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China (IRB ID:TJ-C20200128).
    RandomizationFor each cross-validation procedure, 477 survivors and 39 nonsurvivors were randomly selected as the training set.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.
    Cell Line AuthenticationAuthentication: markers (C-reactive protein, procalcitonin) were performed by automated analyzers according to the manufacturers’ instructions.

    Table 2: Resources

    Antibodies
    SentencesResources
    After excluding individuals whose 23 anti-SARS-CoV-2 antibody indicators were missing more than three, a total of 1,034 eligible participants (524 females and 510 males) with available data from serum proteome microarray and clinical outcomes were enrolled for the final analysis.
    anti-SARS-CoV-2
    suggested: (Hytest Cat# 3CV4-C524, RRID:AB_2889086)
    The arrays were washed with 1×PBST and bound antibodies were detected by incubating with Cy3-conjugated goat anti-human IgG and Alexa Fluor 647-conjugated donkey anti-human IgM (Jackson ImmunoResearch, PA, USA), which were diluted 1: 1,000 in 1×PBST, and incubated at room temperature for 1 h.
    anti-human IgG
    suggested: (Bio-Rad Cat# MCA647F, RRID:AB_808612)
    anti-human IgM
    suggested: None
    Software and Algorithms
    SentencesResources
    Cluster analysis was performed with pheatmap package of R.
    pheatmap
    suggested: (pheatmap, RRID:SCR_016418)
    SAS (version 9.4), R (version 4.0.0), and SPSS (version 23.0) were used to conduct statistical analyses when applicably used.
    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

    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.

  7. Version published to 10.1101/2020.11.10.20228890v1 on medRxiv