COVID-19 genomic susceptibility: Definition of ACE2 variants relevant to human infection with SARS-CoV-2 in the context of ACMG/AMP Guidance

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Abstract

Background

Mortality remains very high and unpredictable in CoViD-19, with intense public protection strategies tailored to preceived risk. Males are at greater risk of severe CoViD-19 complications. Genomic studies are in process to identify differences in host susceptibility to SARS-CoV-2 infection.

Methods

Genomic structures were examined for the ACE2 gene that encodes angiotensin-converting enzyme 2, the obligate receptor for SARS-CoV-2. Variants in 213,158 exomes/genomes were integrated with ACE2 protein functional domains, and pathogenicity criteria from the American Society of Human Genetics and Genomics/Association for Molecular Pathology.

Results

483 variants were identified in the 19 exons of ACE2 on the X chromosome. All variants were rare, including nine loss-of-function (potentially SARS-CoV-2 protective) alleles present only in female heterozygotes. Unopposed variant alleles were more common in males (262/3596 [7.3%] nucleotides) than females (9/3596 [0.25%] nucleotides, p <0.0001). 37 missense variants substituted amino acids in SARS-CoV-2 interacting regions or critical domains for transmembrane ACE2 expression. Four upstream open reading frames with 31 associated variants were identified. Excepting loss-of-function alleles, variants would not meet minimum criteria for classification as ‘Likely Pathogenic/beneficial’ if differential frequencies emerged in patients with CoViD-19.

Conclusions

Males are more exposed to consequences from a single variant ACE2 allele. Common risk/beneficial alleles are unlikely in regions subject to evolutionary constraint. ACE2 upstream open reading frames may have implications for aminoglycoside use in SARS-CoV-2-infected patients. For this SARS-CoV-2-interacting protein with pre-identified functional domains, pre-emptive functional and computational studies are encouraged to accelerate interpretations of genomic variation for personalised and public health use.

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  1. SciScore for 10.1101/2020.05.12.20098160: (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 variableThese 213,158 exomes and genomes from largely non-overlapping 111,454 male and 101,704 female datasets [21], mapped to GRCh37/hg19 [16] (version 2, 141,456 samples), and GRCh37/hg19 [17] (version 3, 71,702 genomes) [21].

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    ACE2 Reference Sequence: The reference sequence for the human 3596 nucleotide transcript encoding ACE2 (NM_021804, 19-Apr-2020 update), was downloaded from RefSeq [15] and cross mapped to the National Center for Biotechnology Information Genome Reference Consortium Human Builds GRCh37/hg19 [16] and GRCh38/hg38 [17], utilising University of Santa Cruz (UCSC) Genome Browser resources [18,19].
    RefSeq
    suggested: (RefSeq, RRID:SCR_003496)
    Definition of ACE2 nucleotides relevant to SARS-CoV-2 infection: Amino acids participating in hydrogen bonding with SARS-CoV-2 [13], and immediately adjacent residues, were mapped to the primary amino acid and nucleotide sequences of NM_021804.
    SARS-CoV-2
    suggested: (Active Motif Cat# 91351, RRID:AB_2847848)
    Data Analysis: Aligned data were uploaded to STATA IC 15.1 (Statacorp, Texas, US) in order to generate descriptive statistics, perform two way comparisons using χ2 and Mann Whitney tests, and generate graphs.
    Statacorp
    suggested: None

    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:
    Thus, although a limitation of the current study is that not every human genomic database was examined, a wider number of coding ACE2 variants were retrieved compared to other publications [24], most likely due to combined use of both the GRCh37/hg19-mapping and more recent GRCh37/hg19-mapping gnomAD databases. The study by design was limited to ACE2, in order to illustrate principles, but could be expanded to additional potential regions of genomic risk. Study strengths include highlighting the landscape of genetic variation relevant to SARS-CoV-2, and questioning how strictly putative COVID-19 risk and protective alleles should be defined, particularly if they may become part of public health policies, as for underlying health conditions [25,26]. The pattern from Mendelian disorders was of over-exuberant pathogenicity calls in early research reports, with pathogenicity classifications of many variants later downgraded as assignments became increasingly stringent [14,28]. As a result, high proportion of coding variants in known disease-causing genes are currently clinically non-actionable due to classification as a VUS. This is important because many individuals are “pre-genotyped,” having undergone whole genome sequencing as part of other initiatives [29–31], and will have direct access to open-source research publication of COVID-19 associated variants, before they are subjected to the rigorous oversights applied by Clinical Geneticists. To facilitate classification if var...

    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.