Genes associated with liver damage signalling pathways may impact the severity of COVID-19 symptoms in Spanish and Italian populations

  1. Leire Moya
  2. Samaneh Farashi
  3. Prashanth N Suravajhala
  4. Panchadsaram Janaththani
  5. Jyotsna Batra

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Abstract

Aim

The novel SARS-CoV-2 virus, which causes the COVID-19 disease, has infected more than 10 million people and caused 500K deaths worldwide. In Europe, over 2 million confirmed cases have been reported, while nearly 200K people have died from the disease. Despite strict containment measures in Spain and Italy after the first reported COVID-19 patient, these two countries have remained in the top five European nations with the highest mortality rate for over two months. We hypothesised that a genetic mechanism could partially explain the poor survival outcome observed in these two countries.

Methods

An extensive literature search to identify human candidate genes linked to SARS-CoV infection, host immune evasion and disease aggressiveness was carried out. Pathway analysis (IPA) was performed to select the most significantly associated canonical signalling pathways with the genes of interest. The genetic variants’ at these genes with ±1Mb flanking region was extracted (GRCh37/hg19 built). Over 80 million single nucleotide polymorphisms (SNPs) were analysed in genome-wide data of 2,504 individuals (1000 genomes, phase III, https://www.internationalgenome.org/ ). Principal component (PC) analysis was performed, ancestry by the whole genome was inferred and subsets of the regions of interest were extracted (PLINK v1.9b, http://pngu.mgh.harvard.edu/purcell/plink/ ). PC1 to PC20 values from five European ancestries, including the Spanish and Italian populations, were used for PC analysis. Gene function predictions were run with our genes of interest as a query to the GeneMANIA Cytoscape plugin ( https://genemania.org/ ).

Results

A total of 437 candidate genes associated with SARS were identified, including 21 correlated with COVID-19 aggressiveness. The two most significant pathways associated with all 437 genes ( Caveolar-mediated Endocytosis and MSP-RON Signalling ) did not show any segregation at the population level. However, the most significant canonical pathway associated with genes linked to COVID-19 aggressiveness, the Hepatic Fibrosis and Hepatic Stellate Cell Activation, showed population-specific segregation. Both the Spanish and Italian populations clustered together from the rest of Europe. This was also observed for the Finnish population but in the opposite direction. These results suggest some of the severe COVID-19 cases reported in Spain and Italy could be partially explained by a pre-existing liver condition (especially liver cancer) and/or may lead to further COVID-19 related liver complications.

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  1. ScreenIT

    SciScore for 10.1101/2020.07.03.179028: (What is this?)

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

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Identification of candidate genes for analysis: PubMed was accessed between the 31st of March and 25th of May 2020.
    PubMed
    suggested: (PubMed, RRID:SCR_004846)
    Also, selected genes associated with COVID-19 severe symptoms were entered in the GeneMANIA Cytoscape plugin to predict physical protein-protein interactions [23].
    GeneMANIA
    suggested: (GeneMANIA, RRID:SCR_005709)
    The data utilised come from reported studies and public large databases such as BIOGRID (Breitkreutz et al., 2008), GEO (Barrett et al., 2009)
    BIOGRID
    suggested: (BioGrid Australia, RRID:SCR_006334)
    , I2D (Brown and Jurisica, 2005) and Pathway Commons (http://www.pathwaycommons.org).
    http://www.pathwaycommons.org
    suggested: (cPath, RRID:SCR_001749)
    PCs were computed using PLINK software v1.9b for all samples of 1000G (1KG) project, phase 3 version 5b, to infer the ancestry of the samples based on the whole genome data.
    PLINK
    suggested: (PLINK, RRID:SCR_001757)

    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.

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  2. Version published to 10.1101/2020.07.03.179028v1 on bioRxiv