The aging whole blood transcriptome reveals a potential role of FASLG in COVID-19

  1. Luiz Gustavo de Almeida Chuffa
  2. Jeferson dos Santos Souza
  3. Mariana Costa de Mello
  4. Mario de Oliveira Neto
  5. Robson Francisco Carvalho

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Abstract

The risk for severe illness from COVID-19 increases with age as older patients are at the highest risk. Although it is still unclear whether the virus is blood-transmitted, the viral RNA is detected in serum. Identifying how Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) interacts with specific blood components during aging is expected to guide proper therapies. Considering that all human coronavirus require host cellular molecules to promote infection, we investigated the aging whole blood transcriptome from the Genotype-Tissue Expression (GTEx) database to explore differentially expressed genes (DEGs) translated into proteins potentially interacting with viral proteins. From a total of 22 DEGs in aged blood, five genes ( FASLG, CTSW, CTSE, VCAM1 , and BAG3 ) changed expression during aging. These age-related genes are involved in immune response, inflammation, cell component and cell adhesion, and platelet activation/aggregation. Both males and females older than 50 overexpress FASLG compared with younger adults (20-30 years old), possibly inducing a hyper-inflammatory cascade that activates specific immune cells. Furthermore, the expression of cathepsins ( CTSW and CTSE ) and the anti-apoptotic co-chaperone molecule BAG3 was significantly increased throughout aging in both gender. By exploring publicly available Single-Cell RNA-Sequencing (scRNA-Seq) data on peripheral blood of SARS-CoV-2-infected patients, we found FASLG and CTSW expressed mainly in natural killer (NK) cells and CD8+ (cytotoxic) T lymphocytes whereas BAG3 was expressed in CD4+ T cells, naive T cells, and CD14+ monocytes. The increased expression of FASLG in blood during aging may explain why older patients are more prone to severe acute viral infection complications. These results indicate FASLG as a prognostic candidate and potential therapeutic target for more aggressive clinical manifestation of COVID-19.

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    SciScore for 10.1101/2020.12.04.412494: (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
    The BioJupies platform (https://amp.pharm.mssm.edu/biojupies/) [17] was used to find the differentially expressed genes (DEGs) in whole blood samples over aging (20-79 years-old).
    BioJupies
    suggested: (BioJupies, RRID:SCR_016346)
    The results were analyzed with GraphPad Prism v. 6.00 for Windows (GraphPad Software, La Jolla, California, USA).
    GraphPad Prism
    suggested: (GraphPad Prism, RRID:SCR_002798)
    GraphPad
    suggested: (GraphPad Prism, RRID:SCR_002798)
    Tissue-specific interaction networks of potential SARS-CoV-host blood interactome: The HumanBase tool (https://hb.flatironinstitute.org) [21] was used to provide whole blood-specific networks based on upregulated genes during aging that code for proteins potentially interacting with SARS-CoV according to P-HIPSTer.
    HumanBase
    suggested: (HumanBase, RRID:SCR_016145)
    KEGG) pathway enrichment analysis and Gene Ontology enrichment analysis (Biological Processes) to identify the functions of DEGs by using the EnrichR database (http://amp.pharm.mssm.edu/Enrichr/) [22].
    KEGG
    suggested: (KEGG, RRID:SCR_012773)
    EnrichR
    suggested: (Enrichr, RRID:SCR_001575)
    The molecular function and protein class related to the blood components during aging were performed in the PANTHER classification system v.
    PANTHER
    suggested: (PANTHER, RRID:SCR_004869)
    We used the UniProtKB database (http://www.uniprot.org/) to obtain functional information of the identified proteins.
    UniProtKB
    suggested: (UniProtKB, RRID:SCR_004426)
    http://www.uniprot.org/
    suggested: (Universal Protein Resource, RRID:SCR_002380)
    Protein-protein interaction (PPI) networks based on blood gene expression profile during aging: The genes that appeared overexpressed in aged blood samples were analyzed by STRING online tool (https://string-db.org/) [24].
    STRING
    suggested: (STRING, RRID:SCR_005223)
    Structural analysis of the Fas and FasL: The genes Fas (genbank code: XP_006717882.1) and FasL ( genbank code: NP_000630.1) were obtained on NCBI GenBank, and protein structure blast of these sequences were performed using NCBI blastp suite [26].
    blastp
    suggested: (BLASTP, RRID:SCR_001010)
    Metascape was used to provide GO terms enrichment [32] obtained from aged blood genes that potentially interact with SARS-CoV-2.
    Metascape
    suggested: (Metascape, RRID:SCR_016620)

    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.
    • No funding statement was detected.
    • No protocol registration statement was detected.

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  2. Version published to 10.1101/2020.12.04.412494v1 on bioRxiv