Genetic and Phenotypic Evidence for the Causal Relationship Between Aging and COVID-19

  1. Kejun Ying
  2. Ranran Zhai
  3. Timothy V. Pyrkov
  4. Marco Mariotti
  5. Peter O. Fedichev
  6. Xia Shen
  7. Vadim N. Gladyshev

Reviewed by

Read the full article

Listed in

Log in to save this article

Abstract

Epidemiological studies have revealed that the elderly and those with co-morbidities are most susceptible to COVID-19. To understand the genetic link between aging and the risk of COVID-19, we conducted a multi-instrument Mendelian randomization analysis and found that the genetic variation that leads to a longer lifespan is significantly associated with a lower risk of COVID-19 infection. The odds ratio is 0.32 (95% CI: 0.18 to 0.57; P = 1.3 × 10 -4 ) per additional 10 years of life, and 0.62 (95% CI: 0.51 to 0.77; P = 7.2 × 10 -6 ) per unit higher log odds of surviving to the 90th percentile age. On the other hand, there was no association between COVID-19 susceptibility and healthspan (the lifespan free of the top seven age-related morbidities). To examine the relationship at the phenotypic level, we applied various biological aging clock models and detected an association between the biological age acceleration and future incidence and severity of COVID-19 infection for all subjects as well as for the individuals free of chronic disease. Biological age acceleration was also significantly associated with the risk of death in COVID-19 patients. Our findings suggest a causal relationship between aging and COVID-19, defined by genetic variance, the rate of aging, and the burden of chronic diseases.

Article activity feed

  1. ScreenIT

    SciScore for 10.1101/2020.08.06.20169854: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Only the autosomal SNPs available in the 1000 Genomes reference panel were used, and the 1000 Genomes European ancestry reference was used to estimate the linkage disequilibrium (LD) among these SNPs.
    1000 Genomes
    suggested: (1000 Genomes Project and AWS, RRID:SCR_008801)

    Results from OddPub: Thank you for sharing your code and data.

    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.

    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 10.1101/2020.08.06.20169854v2 on medRxiv
  3. Version published to 10.1101/2020.08.06.20169854v1 on medRxiv