Genetic and Clinical Characteristics of Patients in the Middle East With Multisystem Inflammatory Syndrome in Children

This article has been Reviewed by the following groups

Read the full article See related articles

Abstract

No abstract available

Article activity feed

  1. SciScore for 10.1101/2021.11.30.21267109: (What is this?)

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

    Table 1: Rigor

    EthicsIRB: Patients: This study was approved by the Dubai Scientific Research Ethics Committee—Dubai Health Authority (Approval number DSREC-07/2020_04) and the Institutional Review Board of the Specialty Hospital,
    Consent: Patients (and their guardians) recruited in Dubai or Jordan provided written consent for their de-identified data to be used for research, and this study was performed in accordance with the relevant laws and regulations that govern research in both countries.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    All patients had evidence of SARS-CoV-2 infection either by RT-PCR, SARS-CoV-2 antibodies, or recent exposure to a confirmed case of COVID-19.
    SARS-CoV-2
    suggested: None
    Software and Algorithms
    SentencesResources
    We used three filters to retain: a) truncating or loss of function (LoF) variants in the 182 inflammatory/immune related genes with deleterious effect on RefSeq canonical transcripts, and allele frequency <1% in the Genome Aggregation Database (gnomAD); b) homozygous missense or loss of function variants across the 186 genes, and allele frequency <1% in gnomAD; and c) missense variants in a subset of genes (N =14) recently associated with severe COVID-19 (18, 19) and gnomAD allele frequency <0.5%.
    RefSeq
    suggested: (RefSeq, RRID:SCR_003496)
    Enrichment Analysis: Enrichment of rare, likely deleterious genetic variants in patients with MIS-C was determined by comparing the proportion of functional alleles (nonsense, frameshift, missense, and canonical ±1,2 splicing) in the MIS-C group to that in controls, and p-values were calculated using the Fisher’s exact test (GraphPad Prism v9.2.0).
    GraphPad
    suggested: (GraphPad Prism, RRID:SCR_002798)
    For each gene, total allele count was divided by maximum allele number in the database and Fisher’s exact test was performed using Graph Pad Prism v9.2.0.
    Graph Pad Prism
    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:
    One limitation of this study is the lack of functional analyses to characterize the mechanism(s) through which the mutated genes contribute to MIS-C disease onset and/or progression. However, as shown in Table 3, most variants are highly concentrated to genes in the interferon (IFN), and toll-like receptor (TLR) pathways suggesting that disturbance of such pathways might underlie the cytokine storms and dysregulated inflammatory markers (Table 2) in those patients. Protein-protein network analysis (Supplementary Figure 1) further confirms the significant interaction and convergence of most mutated genes in this study. Although our genetic analysis revealed some overlap with the type I IFN pathway shown to be altered in patients with severe COVID-19 (18), the majority of identified variants, especially truncating ones, in MIS-C patients affect genes which do not overlap with those in patients with severe COVID-19. These results suggest that MIS-C and severe COVID-19 have distinct genetic determinants and molecular etiologies. In summary, our study on patients from the Middle East shows that MIS-C has a genetic component and paves the way for additional studies designed to include larger numbers of patients from diverse backgrounds along with functional analyses to fully characterize the genetic contribution to this new disease entity.

    Results from TrialIdentifier: No clinical trial numbers were referenced.


    Results from Barzooka: We found bar graphs of continuous data. We recommend replacing bar graphs with more informative graphics, as many different datasets can lead to the same bar graph. The actual data may suggest different conclusions from the summary statistics. For more information, please see Weissgerber et al (2015).


    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.