Exploiting Molecular Basis of Age and Gender Differences in Outcomes of SARS-CoV-2 Infections

  1. Daniele Mercatelli
  2. Elisabetta Pedace
  3. Federico M. Giorgi
  4. Pietro Hiram Guzzi

Reviewed by

Read the full article

Listed in

Log in to save this article

Abstract

Motivation

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (coronavirus disease, 2019; COVID-19) is associated with adverse outcomes in patients. It has been observed that lethality seems to be related to the age of patients. Moreover, it has been demonstrated that ageing causes some modifications at a molecular level.

Objective

The study aims to shed out light on a possible link between the increased COVID-19 lethality and the molecular changes that occur in elderly people.

Methods

We considered public datasets on ageing-related genes and their expression at tissue level. We selected interactors that are known to be related to ageing process. Then, we performed a network-based analysis to identify interactors significantly related to both SARS-CoV-2 and ageing. Finally, we investigated changes on the expression level of coding genes at tissue, gender and age level.

Results

We observed a significant intersection between some SARS-CoV-2 interactors and ageing-related genes suggesting that those genes are particularly affected by COVID-19 infection. Our analysis evidenced that virus infection particularly affects ageing molecular mechanisms centred around proteins EEF2, NPM1, HMGA1, HMGA2, APEX1, CHEK1, PRKDC, and GPX4. We found that HMGA1, and NPM1 have a different expression in lung of males, while HMGA1, APEX1, CHEK1, EEF2, and NPM1 present changes in expression in males due to aging effects.

Conclusion

Our study generated a mechanistic framework to explaining the correlation between COVID-19 incidence in elderly patients and molecular mechanisms of ageing. This will provide testable hypotheses for future investigation and pharmacological solutions tailored on specific age ranges.

Article activity feed

  1. ScreenIT

    SciScore for 10.1101/2021.05.23.21257669: (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
    We gathered data from the GenAge dataset that derived human genes by projecting sequence orthologs in model organisms.
    GenAge
    suggested: (GenAge, RRID:SCR_010223)
    We used the Search Tool for the Retrieval of Interacting Genes/Proteins database (STRING) [54] that is a freely available repository storing both physical and functional association among proteins.
    STRING
    suggested: (STRING, RRID:SCR_005223)
    Bioinformatic Analysis: We selected all known SARS-CoV-2 interacting partners.
    Bioinformatic
    suggested: (QFAB Bioinformatics, RRID:SCR_012513)

    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.

    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.

  2. Version published to 10.1101/2021.05.23.21257669v1 on medRxiv
  3. Version published to 10.1016/j.csbj.2021.07.002