Transcriptomic profiling of disease severity in patients with COVID-19 reveals role of blood clotting and vasculature related genes

  1. Kiran Iqbal Masood
  2. Syed Faisal Mahmood
  3. Saba Shahid
  4. Nosheen Nasir
  5. Najia Ghanchi
  6. Asghar Nasir
  7. Bushra Jamil
  8. Iffat Khanum
  9. Safina Razzak
  10. Akbar Kanji
  11. Zahra Hasan

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Abstract

COVID-19 caused by SARS-CoV-2 manifests as a range of symptoms. Understanding the molecular mechanisms responsible for immuno-pathogenesis of disease is important for treatment and management of COVID-19. We examined host transcriptomes in moderate and severe COVID-19 cases with a view to identifying pathways that affect its progression. RNA extracted from whole blood of COVID-19 cases was analysed by microarray analysis. Moderate and severe cases were compared with healthy controls and differentially regulated genes (DEGs) categorized into cellular pathways.

DEGs in COVID-19 cases were mostly related to host immune activation and cytokine signaling, pathogen uptake, host defenses, blood and vasculature genes, and SARS-CoV-2- and other virus-affected pathways. The DEGs in these pathways were increased in severe compared with moderate cases. In a severe COVID-19 patient with an unfavourable outcome we observed dysregulation of genes in platelet homeostasis and cardiac conduction and fibrin clotting with disease progression.

COVID-19 morbidity is associated with cytokine activation, cardiovascular risk and thrombosis. We identified DEGs related to dysregulation of blood clotting and homeostasis, platelet activation pathways and to be associated with disease progression. These can be biomarkers of disease progression and also potential targets for treatment interventions in COVID-19.

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    SciScore for 10.1101/2020.06.18.20132571: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: This study received approval from the Ethics Review Committee of the Aga Khan University.
    Consent: Written and /or verbal consent was taken from all study subjects.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variableAll study subjects were males and females aged over 18 years.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Cellular Pathway analysis: DEGs significantly up- or down-regulated (p<0.05) with Gene fold change < −2 or > 2 were identified by TCAS software and categorised using the WikiPathways.
    WikiPathways
    suggested: (WikiPathways, RRID:SCR_002134)

    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.
    • Thank you for including a protocol registration statement.

    About SciScore

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  2. Version published to 10.1101/2020.06.18.20132571v1 on medRxiv