Clinical population genetic analysis of variants in the SARS-CoV-2 receptor ACE2

  1. Amin Ardeshirdavani
  2. Pooya Zakeri
  3. Amirhosein Mehrtash
  4. Sayed Mostafa Hosseini
  5. Guangdi Li
  6. Hanifeh Mirtavoos-Mahyari
  7. Mohamad javad Soltanpour
  8. Mahmoud Tavallaie
  9. Yves Moreau

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Abstract

Purpose

SARS-CoV-2 infects cells via the human Angiotensin-converting enzyme 2 (ACE2) protein. The genetic variation of ACE2 function and expression across populations is still poorly understood. This study aims at better understanding the genetic basis of COVID-19 outcomes by studying association between genetic variation in ACE2 and disease severity in the Iranian population.

Methods

We analyzed two large Iranian cohorts and several publicly available human population variant databases to identify novel and previously known ACE2 exonic variants present in the Iranian population and considered those as candidate variants for association between genetic variation and disease severity. We genotyped these variants across three groups of COVID-19 patients with different clinical outcomes (mild disease, severe disease, and death) and evaluated this genetic variation with regard to clinical outcomes.

Results

We identified 32 exonic variants present in Iranian cohorts or other public variant databases. Among those, 11 variants are novel and have thus not been described in other populations previously. Following genotyping of these 32 candidate variants, only the synonymous polymorphism (c.2247G>A) was detected across the three groups of COVID-19 patients.

Conclusion

Genetic variability of known and novel exonic variants was low among our COVID-19 patients. Our results do not provide support for the hypothesis that exonic variation in ACE2 has a sizeable impact on COVID-19 severity across the Iranian population.

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  1. ScreenIT

    SciScore for 10.1101/2020.05.27.20115071: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: Ethics Statement: This study was approved by the Baqiyatallah University of Medical Sciences ethics committee, approval ID: IR.BMSU.REC.1399.041.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Structural visualization is prepared using PyMOL V2.122.
    PyMOL
    suggested: (PyMOL, RRID:SCR_000305)

    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:
    However, these results should be interpreted cautiously because of the small number of patients included in this study, which is a major limitation of this investigation. This limitation, in turn, may lead to potential biases in our analysis. In particular, our results do not preclude that statistically significant effects could be detected for some variants in larger patient cohorts from Iran, although one can speculate that the effect size is likely to be small and thus of limited clinical relevance. Furthermore, our results do not preclude that some of the rare variants identified could have a sizeable effect for individual carriers, although it appears unlikely that rare variants could have a sizeable contribution to the disease burden of the whole Iranian population. Also, we did not assess non-exonic or regulatory ACE2 variation, so we cannot speculate on its potential clinical relevance in the Iranian population. Thus, there is still a need to perform larger clinical studies assessing the role of ACE2 variants in COVID-19 clinical outcomes, in particular for rare variants. Finally, we cannot exclude that exonic ACE2 variation could be relevant in other populations. While ACE2 is the main host cell receptor of SARS-CoV-2 and plays a central role in the entry of the virus into the cell, it is only one of the many candidate genes that could be associated with the variability of disease severity among COVID-19 patients. Another important candidate is a cellular protease, c...

    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 10.1101/2020.05.27.20115071v1 on medRxiv