Identification of risk and protective human leukocyte antigens in COVID-19 using genotyping and structural modeling

  1. Yiran Shen
  2. David A. Ostrov
  3. Santosh Rananaware
  4. Piyush K Jain
  5. Cuong Q. Nguyen

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Abstract

COVID-19 is caused by severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2). The severity of COVID-19 is highly variable and related to known (e.g., age, obesity, immune deficiency) and unknown risk factors. Since innate and adaptive immune responses are elicited in COVID-19 patients, we genotyped 94 Florida patients with confirmed COVID-19 and 89 healthy controls. We identified an HLA gene, HLA-DPA1, in which specific alleles were associated with the risk of SARS-CoV-2 positivity and COVID-19 disease. HLA-DPA1*01:03 was associated with reduced incidence of SARS-CoV-2 positivity, whereas HLA-DPA1*03:01 was associated with increased risk of SARS-CoV-2 positivity. These data suggest a model in which COVID-19 severity is influenced by immunodominant peptides derived from SARS-CoV-2 preferentially presented by specific HLA-DP molecules to either protective (for asymptomatic COVID-19) or pathogenic T cells (in severe COVID-19). Although this study is limited to comparing SARS-CoV-2 positive and negative subjects, these data suggest that HLA typing of COVID-19 patients stratified for disease severity may be informative for identifying biomarkers and disease mechanisms in high-risk individuals.

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  1. ScreenIT

    SciScore for 10.1101/2021.05.04.21256636: (What is this?)

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

    Table 1: Rigor

    EthicsIRB: The study was approved by the Institutional Review Board of the University of Florida.
    Sex as a biological variableIn the SARS-CoV-2 positive cohort, there were 50 females, 43 males, and 1 undisclosed, in which there were 17 white, 21 black, 1 Asian, 1 Non-Hispanic, and 55 undisclosed.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Isolated genomic DNA was quantified by NanoDrop™ One/OneC
    NanoDrop™
    suggested: None
    PyMOL (https://pymol.org/2/) was used to generate molecular graphic images.
    PyMOL
    suggested: (PyMOL, RRID:SCR_000305)
    Odds ratios (ORs, 95% confidence interval [CI]) and p-values were calculated using R 4.0.3 (R Core Team, 2018), the exact2×2 (v1.6.5; Fay MP, 2010) package or Prism 9.0 software (GraphPad Software, La Jolla California USA).
    Prism
    suggested: (PRISM, RRID:SCR_005375)
    GraphPad
    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: We detected the following sentences addressing limitations in the study:
    The data suggest that HLA-DPA1*01:03 may be protective because of effects on immunodomiant peptide binding, whereas HLA-DPA1*03:01 was associated with risk to SARS-CoV-2 infection because of limitations on binding immunodominant SARS-CoV-2 epitopes. The limitations of this study were the small population cohort and the lack of patient clinical information that could be extrapolated to examine the associations of other clinical symptoms and HLAs. Overall, this study demonstrates HLA typing and in-silico structural modeling to identify susceptible and protective HLA alleles. This approach can potentially provide a genetic biomarker to determine if an individual is protected from the severity of the infection or if an individual is susceptible to the disease. These biomarkers may be essential in the decision-making process for developing and implementing a strategy to keep the individual safe if there is no vaccine or treatment available.

    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.

  2. Version published to 10.1101/2021.05.04.21256636v1 on medRxiv