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Figure.  Nasal Gene Expression of ACE2 in Different Age Groups
Nasal Gene Expression of ACE2 in Different Age Groups

Data are means (data points) and 95% confidence intervals (error bars) for angiotensin-converting enzyme 2 (ACE2) gene expression in younger children (aged <10 years), older children (aged 10-17 years), young adults (aged 18-24 years), and adults (aged ≥25 years). Gene counts are shown as logarithmic (log2) counts per million. P values are from linear regression modeling in which ACE2 gene expression in log2 counts per million was the dependent variable and age group was the independent variable.

Table.  β Coefficients for Age Group From Unadjusted and Adjusted Linear Regression Modelsa
β Coefficients for Age Group From Unadjusted and Adjusted Linear Regression Modelsa
1.
Wu  Z, McGoogan  JM.  Characteristics of and important lessons from the coronavirus disease 2019 (COVID-19) outbreak in China: summary of a report of 72 314 cases from the Chinese Center for Disease Control and Prevention.   JAMA. 2020;323(13):1239-1242. doi:10.1001/jama.2020.2648PubMedGoogle ScholarCrossref
2.
CDC COVID-19 Response Team.  Coronavirus disease 2019 in children—United States, February 12–April 2, 2020.   MMWR Morb Mortal Wkly Rep. 2020;69(14):422-426. doi:10.15585/mmwr.mm6914e4PubMedGoogle ScholarCrossref
3.
Dong  Y, Mo  X, Hu  Y,  et al.  Epidemiology of COVID-19 among children in China.   Pediatrics. 2020;145(4):e20200702. doi:10.1542/peds.2020-0702PubMedGoogle Scholar
4.
Hoffmann  M, Kleine-Weber  H, Schroeder  S,  et al.  SARS-CoV-2 cell entry depends on ACE2 and TMPRSS2 and is blocked by a clinically proven protease inhibitor.   Cell. 2020;181(2):271-280.e8. doi:10.1016/j.cell.2020.02.052PubMedGoogle ScholarCrossref
5.
Schouten  LR, van Kaam  AH, Kohse  F,  et al; MARS Consortium.  Age-dependent differences in pulmonary host responses in ARDS: a prospective observational cohort study.   Ann Intensive Care. 2019;9(1):55. doi:10.1186/s13613-019-0529-4PubMedGoogle ScholarCrossref
6.
Chun  Y, Do  A, Grishina  G,  et al.  Integrative study of the upper and lower airway microbiome and transcriptome in asthma.   JCI Insight. 2020;5(5):e133707. doi:10.1172/jci.insight.133707PubMedGoogle Scholar
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    1 Comment for this article
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    Confounding Effects of Atopy and Intranasal Corticosteroids on ACE2
    Prof Brian Lipworth, MD | University of Dundee, Tayside Rhinology Mega-Clinic
    The nose is often the first portal of entry for SARS-CoV-2, which enters respiratory epithelial cells via ACE2 . The data from Bunyavanich et al (1) suggests that ACE2 activity in the nose is attenuated in younger children which might explain the lower prevalence of COVID-19 in younger children. There are however some issues in regard to their interpretation of the results. First, the 95% CI for log2-transformed ACE2 values are overlapping when comparing age groups <10 yo versus 10-17 yo, in turn suggesting there is no significant difference between the two groups especially after correcting the alpha error for multiple pairwise comparisons. Second they report that 50% of individuals in the overall cohort had concomitant asthma and that differences between age groups were observed after adjusting for gender and asthma. In such individuals <10 yo there would be a higher prevalence of atopy in regard to the presence of allergic eczema and allergic rhinitis. Since both atopy and topical corticosteroids both reduce airway epithelial ACE2 expression including the nose (2-4), these are likely to be relevant confounding factors which could contribute to lower ACE2 expression seen in the present study . It would therefore be pertinent to know if ACE2 expression remains lower in younger people after removing data for those subjects who were allergic or taking intranasal corticosteroids.

    References

    1. Bunyavanich S, Do A, Vicencio A. Nasal Gene Expression of Angiotensin-Converting Enzyme 2 in Children and Adults. JAMA. 2020.
    2. Kimura H, Francisco D, Conway M, et al. Type 2 Inflammation Modulates ACE2 and TMPRSS2 in Airway Epithelial Cells. Journal of Allergy and Clinical Immunology.
    3. Jackson DJ, Busse WW, Bacharier LB, et al. Association of respiratory allergy, asthma, and expression of the SARS-CoV-2 receptor ACE2. Journal of Allergy and Clinical Immunology.
    4. Peters MC, Sajuthi S, Deford P, et al. COVID-19 Related Genes in Sputum Cells in Asthma: Relationship to Demographic Features and Corticosteroids. Am J Respir Crit Care Med. 2020.
    CONFLICT OF INTEREST: None Reported
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    Research Letter
    May 20, 2020

    Nasal Gene Expression of Angiotensin-Converting Enzyme 2 in Children and Adults

    Author Affiliations
    • 1Department of Pediatrics, Icahn School of Medicine at Mount Sinai, New York, New York
    • 2Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York
    JAMA. Published online May 20, 2020. doi:10.1001/jama.2020.8707

    Children account for less than 2% of identified cases of coronavirus disease 2019 (COVID-19).1,2 It is hypothesized that the lower risk among children is due to differential expression of angiotensin-converting enzyme 2 (ACE2),3 the receptor that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) uses for host entry.4 We investigated ACE2 gene expression in the nasal epithelium of children and adults.

    Methods

    We conducted a retrospective examination of nasal epithelium from individuals aged 4 to 60 years encountered within the Mount Sinai Health System, New York, New York, during 2015-2018. Samples were collected from individuals with and without asthma for research on nasal biomarkers of asthma. The study was approved by the Mount Sinai institutional review board. Written informed consent was obtained from participants (or their parents for minors). Nasal epithelium was collected using a cytology brush that was immediately placed in RNA stabilization fluid and stored at −80 °C. RNA was isolated within 6 months. RNA samples were checked for quality and sequenced as a single batch in 2018. Sequence data processing included sequence alignment and normalization of gene expression counts across genes and samples.

    Given the role of ACE2 in SARS-CoV-2 host entry,4 ACE2 gene expression was the focus of this study. Linear regression models with and without adjustment for covariates (sex and asthma) were built with ACE2 gene expression in log2 counts per million as the dependent variable and age group as the independent variable using R software, version 3.6.0 (R Foundation). Age was categorized into the following groups reflecting developmental life stages: younger children (aged <10 years), older children (aged 10-17 years), young adults (aged 18-24 years), and adults (aged ≥25 years). Two-sided tests and a significance threshold of P ≤ .05 were used. Trend pattern was evaluated using polynomial orthogonal contrasts.

    Results

    The cohort of 305 individuals aged 4 to 60 years was balanced with regard to sex (48.9% male). Because the cohort had been recruited to study biomarkers of asthma, 49.8% had asthma.

    We found age-dependent ACE2 gene expression in nasal epithelium (Figure). ACE2 gene expression was lowest (mean log2 counts per million, 2.40; 95% CI, 2.07-2.72) in younger children (n = 45) and increased with age, with mean log2 counts per million of 2.77 (95% CI, 2.64-2.90) for older children (n = 185), 3.02 (95% CI, 2.78-3.26) for young adults (n = 46), and 3.09 (95% CI, 2.83-3.35) for adults (n = 29).

    Linear regression with ACE2 gene expression as the dependent variable and age group as the independent variable showed that compared with younger children, ACE2 gene expression was significantly higher in older children (P = .01), young adults (P < .001), and adults (P = .001) (Figure). As the distributions of sex and asthma varied among the age groups, a linear regression model adjusted for sex and asthma was built that also showed significant adjusted associations (P ≤ .05) between ACE2 expression and age group. Regression (β) coefficients for age groups from the unadjusted and adjusted models are shown in the Table. These regression coefficients indicate the difference in ACE2 expression (in log2 counts per million) between a given age group and the group of children younger than 10 years. Tests for trend using polynomial orthogonal contrasts indicated a significant linear trend for change in ACE2 expression with advancing age group (P ≤ .05).

    Discussion

    The results from this study show age-dependent expression of ACE2 in nasal epithelium, the first point of contact for SARS-CoV-2 and the human body. Covariate-adjusted models showed that the positive association between ACE2 gene expression and age was independent of sex and asthma. Lower ACE2 expression in children relative to adults may help explain why COVID-19 is less prevalent in children.3 A limitation of this study is that the sample did not include individuals older than 60 years.

    Few studies have examined the relationship between ACE2 in the airway and age. A study of bronchoalveolar lavage fluid from 92 patients with acute respiratory distress syndrome reported no association between ACE2 protein activity and age,5 but epithelial gene expression was not examined, and ACE2 protein may be variably shed into bronchoalveolar lavage fluid. Furthermore, the lung and nasal environments are distinct, with known differences in gene expression.6 This study provides novel results on ACE2 gene expression in nasal epithelium and its relationship with age.

    Section Editor: Jody W. Zylke, MD, Deputy Editor.
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    Article Information

    Corresponding Author: Supinda Bunyavanich, MD, MPH, Icahn School of Medicine at Mount Sinai, 1425 Madison Ave #1498, New York, NY 10029 (supinda@post.harvard.edu).

    Accepted for Publication: May 7, 2020.

    Published Online: May 20, 2020. doi:10.1001/jama.2020.8707

    Author Contributions: Dr Bunyavanich had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

    Concept and design: All authors.

    Acquisition, analysis, or interpretation of data: Bunyavanich, Do.

    Drafting of the manuscript: Bunyavanich.

    Critical revision of the manuscript for important intellectual content: All authors.

    Statistical analysis: Bunyavanich, Do.

    Obtained funding: Bunyavanich.

    Administrative, technical, or material support: Bunyavanich.

    Supervision: Bunyavanich, Vicencio.

    Conflict of Interest Disclosures: Dr Vicencio reported being an investor in Filament Biosolutions. No other disclosures were reported.

    Funding/Support: This study was funded by National Institutes of Health grant R01 AI118833.

    Role of the Funder/Sponsor: The funding organization had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; or decision to submit the manuscript for publication.

    Additional Contributions: We thank Robert Griffin, MD, PhD, Hospital for Special Surgery, and Yoojin Chun, MS, Icahn School of Medicine at Mount Sinai, for their assistance with manuscript preparation. Dr Griffin and Ms Chun did not receive compensation for their contributions.

    References
    1.
    Wu  Z, McGoogan  JM.  Characteristics of and important lessons from the coronavirus disease 2019 (COVID-19) outbreak in China: summary of a report of 72 314 cases from the Chinese Center for Disease Control and Prevention.   JAMA. 2020;323(13):1239-1242. doi:10.1001/jama.2020.2648PubMedGoogle ScholarCrossref
    2.
    CDC COVID-19 Response Team.  Coronavirus disease 2019 in children—United States, February 12–April 2, 2020.   MMWR Morb Mortal Wkly Rep. 2020;69(14):422-426. doi:10.15585/mmwr.mm6914e4PubMedGoogle ScholarCrossref
    3.
    Dong  Y, Mo  X, Hu  Y,  et al.  Epidemiology of COVID-19 among children in China.   Pediatrics. 2020;145(4):e20200702. doi:10.1542/peds.2020-0702PubMedGoogle Scholar
    4.
    Hoffmann  M, Kleine-Weber  H, Schroeder  S,  et al.  SARS-CoV-2 cell entry depends on ACE2 and TMPRSS2 and is blocked by a clinically proven protease inhibitor.   Cell. 2020;181(2):271-280.e8. doi:10.1016/j.cell.2020.02.052PubMedGoogle ScholarCrossref
    5.
    Schouten  LR, van Kaam  AH, Kohse  F,  et al; MARS Consortium.  Age-dependent differences in pulmonary host responses in ARDS: a prospective observational cohort study.   Ann Intensive Care. 2019;9(1):55. doi:10.1186/s13613-019-0529-4PubMedGoogle ScholarCrossref
    6.
    Chun  Y, Do  A, Grishina  G,  et al.  Integrative study of the upper and lower airway microbiome and transcriptome in asthma.   JCI Insight. 2020;5(5):e133707. doi:10.1172/jci.insight.133707PubMedGoogle Scholar
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