In-depth blood proteome profiling analysis revealed distinct functional characteristics of plasma proteins between severe and non-severe COVID-19 patients

  1. Joonho Park
  2. Hyeyoon Kim
  3. So Yeon Kim
  4. Yeonjae Kim
  5. Jee-Soo Lee
  6. Kisoon Dan
  7. Moon-Woo Seong
  8. Dohyun Han

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Abstract

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has infected over forty million patients worldwide. Although most coronavirus disease 2019 (COVID-19) patients have a good prognosis, some develop severe illness. Markers that define disease severity or predict clinical outcome need to be urgently developed as the mortality rate in critical cases is approximately 61.5%. In the present study, we performed in-depth proteome profiling of undepleted plasma from eight COVID-19 patients. Quantitative proteomic analysis using the BoxCar method revealed that 91 out of 1222 quantified proteins were differentially expressed depending on the severity of COVID-19. Importantly, we found 76 proteins, previously not reported, which could be novel prognostic biomarker candidates. Our plasma proteome signatures captured the host response to SARS-CoV-2 infection, thereby highlighting the role of neutrophil activation, complement activation, platelet function, and T cell suppression as well as proinflammatory factors upstream and downstream of interleukin-6, interleukin-1B, and tumor necrosis factor. Consequently, this study supports the development of blood biomarkers and potential therapeutic targets to aid clinical decision-making and subsequently improve prognosis of COVID-19.

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  1. Version published to 10.1038/s41598-020-80120-8
  2. ScreenIT

    SciScore for 10.1101/2020.08.18.255315: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementConsent: All patients with positive results for SARS-CoV-2 infection, detected by analyzing the respiratory specimens via PCR, and willing to provide written informed consent were eligible for participation.
    IRB: The Ethics Committee and Institutional Review Board of the National Medical Center (IRB
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Data processing for label-free quantification: Mass spectra were processed using MaxQuant version 1.6.1.0 [33]
    MaxQuant
    suggested: (MaxQuant, RRID:SCR_014485)
    The MS proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE [35] partner repository with the data set identifier PXD020354.
    PRIDE
    suggested: (Pride-asap, RRID:SCR_012052)
    Statistical analysis: For pair-wise analysis in plasma experiments, data were statistically analyzed using Perseus software [36].
    Perseus
    suggested: (Perseus, RRID:SCR_015753)
    Bioinformatics analysis: Funtional gene ontology (GO) and pathway enrichment analysis were performed using the EnrichR online tool (http://amp.pharm.mssm.edu/Enrichr/) [8].
    EnrichR
    suggested: (Enrichr, RRID:SCR_001575)
    Upstream regulation and protein networks were evaluated via Ingenuity Pathway Analysis (IPA, QIAGEN, Hilden, Germany) based on the DEPs in the plasma experiment.
    Ingenuity Pathway Analysis
    suggested: (Ingenuity Pathway Analysis, RRID:SCR_008653)

    Results from OddPub: Thank you for sharing your data.

    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 10.1101/2020.08.18.255315v1 on bioRxiv