Investigation of COVID-19 comorbidities reveals genes and pathways coincident with the SARS-CoV-2 viral disease

  1. Mary E. Dolan
  2. David P. Hill
  3. Gaurab Mukherjee
  4. Monica S. McAndrews
  5. Elissa J. Chesler
  6. Judith A. Blake

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Abstract

The emergence of the SARS-CoV-2 virus and subsequent COVID-19 pandemic initiated intense research into the mechanisms of action for this virus. It was quickly noted that COVID-19 presents more seriously in conjunction with other human disease conditions such as hypertension, diabetes, and lung diseases. We conducted a bioinformatics analysis of COVID-19 comorbidity-associated gene sets, identifying genes and pathways shared among the comorbidities, and evaluated current knowledge about these genes and pathways as related to current information about SARS-CoV-2 infection. We performed our analysis using GeneWeaver (GW), Reactome, and several biomedical ontologies to represent and compare common COVID-19 comorbidities. Phenotypic analysis of shared genes revealed significant enrichment for immune system phenotypes and for cardiovascular-related phenotypes, which might point to alleles and phenotypes in mouse models that could be evaluated for clues to COVID-19 severity. Through pathway analysis, we identified enriched pathways shared by comorbidity datasets and datasets associated with SARS-CoV-2 infection.

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  1. Version published to 10.1038/s41598-020-77632-8
  2. ScreenIT

    SciScore for 10.1101/2020.09.21.306720: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    The genes in the MeSH and HPO gene sets and associated metadata (indicating their association with COVID-19 and citations supporting the association) were incorporated into GW and used for analysis.
    MeSH
    suggested: (MeSH, RRID:SCR_004750)
    Gene Set Comparison: To identify genes that were shared by all five comorbidities or four out of five comorbidities, we used the GeneWeaver ‘Combine GeneSets’ tool.
    GeneSets’
    suggested: None
    To visualize the intersection of comorbidity gene sets graphically, we used the GeneWeaver ‘HiSim graph’ tool.
    GeneWeaver
    suggested: (Gene Weaver, RRID:SCR_003009)

    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

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  3. Version published to 10.1101/2020.09.21.306720v1 on bioRxiv