Genetic polymorphisms mediating behavioural and immune response to pathogens may moderate the impact of the COVID-19 pandemic: a pilot study

This article has been Reviewed by the following groups

Read the full article See related articles

Abstract

Background

The COVID-19 pandemic has affected the entire world, but there are wide variations in prevalence and mortality across nations. Genetic variants which influence behavioural or immune responses to pathogens, selected for by pathogen pressure, may influence this variability. Two relevant polymorphisms in this context are the s allele of the serotonin transporter promoter (5-HTTLPR) and the G allele of the interleukin-6 gene (IL-6 rs1800795).

Methods

The frequencies of the 5-HTTLPR s allele and IL-6 rs1800795 G allele were obtained from published data. The correlations between these allele frequencies and the prevalence and mortality rates of COVID-19 were examined across 44 nations.

Results

The IL-6 rs1800795 G allele was negatively correlated with COVID-19 prevalence (ρ = −0.466, p < 0.01) and mortality (ρ = −0.591, p<0.001) across nations. The 5-HTTLPR s allele was negatively correlated with COVID-19 mortality rates (ρ = −0.437, p = 0.023).

Conclusions

These results suggest that a significant relationship exists between genetic variants that influence behavioural and immune responses to pathogens and indices of the impact of COVID-19 across nations. Further investigation of these variants and their correlates may permit the development of better preventive or therapeutic strategies in the management of the COVID-19 pandemic.

Article activity feed

  1. SciScore for 10.1101/2020.06.03.20120998: (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
    Data was entered and analyzed using the Statistical Package for Social Sciences, version 20.0 (IBM SPSS Statistics for Windows, Version 20.0, Armonk, NY: IBM Corporation).
    SPSS
    suggested: (SPSS, RRID:SCR_002865)

    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:
    The results presented above are subject to certain limitations. First, they are based on a hypothesis which, though supported by historical evidence, still remains provisional. Second, they are based on available data from a limited number of countries. Third, as the COVID-19 outbreak is still evolving in many countries, the prevalence and mortality rates used for analysis in this study may not accurately reflect further trends in certain countries, particularly if healthcare systems are overwhelmed by a high case load [1]. Fourth, given the preliminary nature of this study, confounding factors such as mean age and total population, which could influence the prevalence and mortality rates of COVID-19, were not taken into account. Despite these considerations, this study suggests that further research into the relationship between population-level genetic variants, particularly those related to protection against pathogens, and the impact of disease outbreaks such as the COVID-19 pandemic is warranted. The identification of other genetic polymorphisms influencing either immune or behavioural defences against infection, and the elucidation of their molecular and psychological mechanisms and the interplay between them, could potentially lead to promising new approaches to the control and management of large-scale disease outbreaks, both now and in the future.

    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

    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.