Letters
RESEARCH LETTER

Figure. Nasal Gene Expression of ACE2 in Different Age Groups

Nasal Gene Expression of Angiotensin-Converting
Enzyme 2 in 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 biomarkersof asthma. The study was approved by the Mount Sinai
institutional review board. Written informed consent wasobtained from participants (or their parents for minors).
Nasal epithelium was collected using a cytology brush thatwas immediately placed in RNA stabilization fluid andstored at −80 °C. RNA was isolated within 6 months. RNAsamples were checked for quality and sequenced as a single
batch in 2018. Sequence data processing included sequencealignment 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 groupas 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 (aged18-24 years), and adults (aged ≥25 years). Two-sided tests anda 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 thecohort 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 (meanlog2 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).
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3.50

ACE2 expression, log2 counts per million

Children account for less than 2% of identified cases of coronavirus disease 2019 (COVID-19).1,2 It is hypothesized that thelower risk among children is due to differential expression ofangiotensin-converting enzyme 2 (ACE2),3 the receptor
Editorialthat 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.

P =.001
P <.001

3.25

P =.01

3.00

2.75

2.50

2.25

2.00
<10(n = 45)

10-17(n = 185)

18-24(n = 46)≥25(n = 29)Age, yData are means (data points) and 95% confidence intervals (error bars) forangiotensin-converting enzyme 2 (ACE2) gene expression in younger children(aged <10 years), older children (aged 10-17 years), young adults (aged 18-24years), and adults (aged ⱖ25 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 andage group was the independent variable.

Table. β Coefficients for Age Group From Unadjusted and Adjusted
Linear Regression Modelsa
β Coefficient (95% CI)cb

Age group, yUnadjusted model

Adjusted modeld

10-17

0.37 (0.08-0.67)

0.30 (0.01-0.59)

18-24

0.63 (0.26-1.00)

0.49 (0.13-0.86)≥25

0.69 (0.27-1.11)

0.52 (0.09-0.94)

aAngiotensin-converting enzyme 2 gene expression in log2 counts per million
was the dependent variable and age group was the independent variable.

bChildren younger than 10 years were the reference age group.

c

β Coefficients indicate the difference in ACE2 gene expression (in log2 countsper million) between a given age group and the group of children younger than
10 years.

dAdjusted for sex and asthma.

Linear regression with ACE2 gene expression as the dependent variable and age group as the independent variableshowed 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 thedistributions of sex and asthma varied among the age groups,
a linear regression model adjusted for sex and asthma was builtthat 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 permillion) between a given age group and the group of children(Reprinted) JAMA Published online May 20, 2020

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Letters

younger than 10 years. Tests for trend using polynomial orthogonal contrasts indicated a significant linear trend forchange 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 ACE2gene 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,5but 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.

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 thedesign and conduct of the study; collection, management, analysis, andinterpretation 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 forSpecial Surgery, and Yoojin Chun, MS, Icahn School of Medicine at Mount Sinai,
for their assistance with manuscript preparation. Dr Griffin and Ms Chun did notreceive compensation for their contributions.
1. Wu Z, McGoogan JM. Characteristics of and important lessons from thecoronavirus disease 2019 (COVID-19) outbreak in China: summary of a report of72 314 cases from the Chinese Center for Disease Control and Prevention. JAMA.
2020;323(13):1239-1242. doi:10.1001/jama.2020.2648
2. CDC COVID-19 Response Team. Coronavirus disease 2019 in children—UnitedStates, February 12–April 2, 2020. MMWR Morb Mortal Wkly Rep. 2020;69(14):422-426. doi:10.15585/mmwr.mm6914e4

Supinda Bunyavanich, MD, MPH
Anh Do, PhD
Alfin Vicencio, MD

3. Dong Y, Mo X, Hu Y, et al. Epidemiology of COVID-19 among children inChina. Pediatrics. 2020;145(4):e20200702. doi:10.1542/peds.2020-0702

Author Affiliations: Department of Pediatrics, Icahn School of Medicine atMount Sinai, New York, New York (Bunyavanich, Vicencio); Department ofGenetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai,New York, New York (Do).
Corresponding Author: Supinda Bunyavanich, MD, MPH, Icahn School ofMedicine 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

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

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 proteaseinhibitor. Cell. 2020;181(2):271-280.e8. doi:10.1016/j.cell.2020.02.052
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/s13613-019-0529-4
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.133707

JAMA Published online May 20, 2020 (Reprinted)© 2020 American Medical Association. All rights reserved.

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