1 Zhou P.

Yang X.L.

Wang X.G.

Hu B.

Zhang L.

Zhang W.

et al. A pneumonia outbreak associated with a new coronavirus of probable bat origin. 2 Wu Z, McGoogan JM. Characteristics of and important lessons from the coronavirus disease 2019 (COVID-19) outbreak in China: summary of a report of 72314 cases from the Chinese Center for Disease Control and Prevention [e-pub ahead of print]. JAMA https://doi.org/10.1001/jama.2020.2648. Accessed March 25, 2020. 2 Wu Z, McGoogan JM. Characteristics of and important lessons from the coronavirus disease 2019 (COVID-19) outbreak in China: summary of a report of 72314 cases from the Chinese Center for Disease Control and Prevention [e-pub ahead of print]. JAMA https://doi.org/10.1001/jama.2020.2648. Accessed March 25, 2020. The novel coronavirus SARS-CoV-2 (COVID-19) was recognized in December 2019 as a cause of severe pneumonia and has now led to a global pandemic.Respiratory illnesses caused by COVID-19 cover a range of severity. The identification of risk and protective factors for disease severity from COVID-19 is critical to direct development of new treatments and infection prevention strategies. Early large case series have identified a number of risk factors for severe disease, including older age, hypertension, diabetes, cardiovascular disease, tobacco exposure, and chronic obstructive pulmonary disease.The US Centers for Disease Control and Prevention lists asthma as a risk factor for severe COVID-19 illness, which is logical given that many respiratory viruses have been well established to cause more serious illnesses in those with chronic airway diseases such as asthma. However, asthma and respiratory allergy have not been identified as significant risk factors for severe COVID-19 illness in case series from China.These preliminary reports led us to question whether we could identify features of allergy and/or asthma that could be associated with potential for reduced severity of COVID-19 illness.

1 Zhou P.

Yang X.L.

Wang X.G.

Hu B.

Zhang L.

Zhang W.

et al. A pneumonia outbreak associated with a new coronavirus of probable bat origin. 3 Jia H.P.

Look D.C.

Shi L.

Hickey M.

Pewe L.

Netland J.

et al. ACE2 receptor expression and severe acute respiratory syndrome coronavirus infection depend on differentiation of human airway epithelia. 4 Brake S.J.

Barnsley K.

Lu W.

McAlinden K.D.

Eapen M.S.

Sohal S.S. Smoking upregulates angiotensin-converting enzyme-2 receptor: a potential adhesion site for novel coronavirus SARS-CoV-2 (Covid-19). SARS-CoV-2 uses angiotensin-converting enzyme 2 (ACE2) as its cellular receptor, as do SARS-CoV and the coronavirus NL63.Higher ACE2 expression increases in vitro susceptibility to SARS-CoV,and studies examining factors that affect ACE2 gene expression have revealed that its upregulation is associated with smoking, diabetes, and hypertension, all of which are associated with increased severity of COVID-19 illness.

5 Larson D, Patel P, Salapatek AM, Couroux P, Whitehouse D, Pina A, et al. Nasal allergen challenge and environmental exposure chamber challenge: a randomized trial comparing clinical and biological responses to cat allergen. J Allergy Clin Immunol https://doi.org/10.1016/j.jaci.2020.02.024. Accessed March 25, 2020. We hypothesized that 1 potential explanation for the unexpected observation that asthma and other allergic diseases may not be a risk factor for severe COVID-19 disease is a reduced ACE2 gene expression in airway cells and thus decreased susceptibility to infection. To test this hypothesis, we examined whether asthma and respiratory allergy are associated with reduced ACE2 expression in airway cells from 3 different cohorts of children and adults. In all 3 studies, total RNA was extracted from nasal or lower airway epithelial brush samples, with RNA sequencing performed independently for each study as previously described and provided in detail in the Supplementary Information (available in this article’s Online Repository at www.jacionline.org ).Differential expression of ACE2 was assessed by using a weighted linear mixed effects model (limma) appropriate for RNA sequencing data and an empiric Bayes method.

6 Bacharier L.B.

Beigelman A.

Calatroni A.

Jackson D.J.

Gergen P.J.

O'Connor G.T.

et al. Longitudinal phenotypes of respiratory health in a high-risk urban birth cohort. 2 Wu Z, McGoogan JM. Characteristics of and important lessons from the coronavirus disease 2019 (COVID-19) outbreak in China: summary of a report of 72314 cases from the Chinese Center for Disease Control and Prevention [e-pub ahead of print]. JAMA https://doi.org/10.1001/jama.2020.2648. Accessed March 25, 2020. Fig 1 ACE2 expression is decreased in the nasal epithelium of children with allergic sensitization (Sens) and allergic asthma. A, ACE2 expression levels in nasal brush samples from 11-year-old children in the URECA cohort according to asthma diagnosis by the age of 10 years, dichotomized as no (–) or yes (+), and IgE sensitization trajectory at the age of 10 years, dichotomized as not/minimally (no/Min) IgE-sensitized (–) or IgE-sensitized (+), showing lower levels of ACE2 in children with atopy and atopic asthma. B, ACE2 expression in URECA children with asthma, subdivided according to the degree of IgE sensitization and demonstrating progressively lower levels of ACE2 according to the degree of IgE sensitization among children with asthma. Those children with both asthma and the highest IgE sensitization had the lowest levels of ACE2 expression. Expression levels are log2-transformed. Shown are median values (horizontal), interquartile ranges (boxes), and 1.5× interquartile range (whiskers). The printed FCs are for the non–log2-transformed expression values to aid in interpretation of the effect sizes. Children at high risk for asthma based on parental histories and living in urban neighborhoods were enrolled prenatally and followed prospectively in the Urban Environment and Childhood Asthma (URECA) cohort; 318 of them had nasal epithelial brushes obtained at 11 years of age. Prevalence of asthma was assessed at 10 years of age, and atopic status was defined by allergic sensitization trajectories (no or minimal, low, medium, and high) as previously described.Additional type 2 biomarkers, including fractional exhaled nitric oxide, peripheral blood eosinophil level, and total IgE level, were evaluated by using standard methods. In URECA, allergic sensitization was inversely related to ACE2 expression in the nasal epithelium regardless of asthma status ( Fig 1 , A). In children with asthma, moderate allergic sensitization (fold change [FC] = 0.70; P = 4.2E–3) and high allergic sensitization (FC = 0.54; P = 6.4E–5) were associated with progressively greater reductions in ACE2 expression compared with in children with asthma but no/minimal allergic sensitization ( Fig 1 , B). ACE2 expression was also significantly inversely associated with type 2 biomarkers (see Table E1 in this article’s Online Repository at www.jacionline.org ), including the number of positive allergen-specific IgE test results (β coefficient –0.089; P = 3.1E–5), total IgE level (β coefficient –0.31; P = 5.1E–6), fractional exhaled nitric oxide (β coefficient –0.45; P = 3.4E–3), and nasal epithelial expression of IL13 (β coefficient –0.123; P = 8.6E–5). ACE2 expression was not significantly correlated with peripheral blood eosinophil level (β coefficient –0.13; P = .07). Although male sex has been associated with increased severity of COVID-19 illness,no sex-based differences in ACE2 expression were found in URECA. Of note, 10 participants reported nasal corticosteroid use at the time of nasal sampling, and it was not associated with alterations in ACE2 expression.

5 Larson D, Patel P, Salapatek AM, Couroux P, Whitehouse D, Pina A, et al. Nasal allergen challenge and environmental exposure chamber challenge: a randomized trial comparing clinical and biological responses to cat allergen. J Allergy Clin Immunol https://doi.org/10.1016/j.jaci.2020.02.024. Accessed March 25, 2020. Fig 2 A, ACE2 expression was significantly decreased in nasal brush samples from adults in the cohort with allergic rhinitis and cat allergen sensitization both 8 hours after a cat allergen NAC and 8 hours after the second day of a cat allergen EEC (n = 24) (B, ACE2 expression was significantly decreased in bronchial epithelial brush samples from adults with allergic asthma 48 hours after a segmental bronchial allergen challenge (n = 23). Expression levels are log2-transformed. Shown are median values (horizontal), interquartile ranges (boxes), and 1.5× interquartile range (whiskers). The printed FCs are for the non–log2-transformed expression values to aid in interpretation of the effect sizes. ACE2 expression is decreased in nasal and bronchial epithelium of individuals with allergy after allergen challenge.ACE2 expression was significantly decreased in nasal brush samples from adults in the cohort with allergic rhinitis and cat allergen sensitization both 8 hours after a cat allergen NAC and 8 hours after the second day of a cat allergen EEC (n = 24) ( https://www.itntrialshare.org/CATEEC_primary.url ).ACE2 expression was significantly decreased in bronchial epithelial brush samples from adults with allergic asthma 48 hours after a segmental bronchial allergen challenge (n = 23). Expression levels are log2-transformed. Shown are median values (horizontal), interquartile ranges (boxes), and 1.5× interquartile range (whiskers). The printed FCs are for the non–log2-transformed expression values to aid in interpretation of the effect sizes. We also evaluated 24 adult participants with allergic rhinitis to cat who had no asthma symptoms in the prior year, were enrolled in a study in which they underwent nasal cat allergen challenge (NAC), and had been exposed to cat allergen through an environmental exposure chamber (EEC), as previously described.Pre–allergen challenge and post–allergen challenge nasal brush samples were obtained. Allergen exposure by both NAC and EEC led to significant reductions in ACE2 expression ( Fig 2 , A) (with NAC, FC = 0.81 and P = 2.4E–3; with exposure through an EEC, FC = 0.79 and P = 1.6E–3).

7 Kelly E.A.

Esnault S.

Liu L.Y.

Evans M.D.

Johansson M.W.

Mathur S.

et al. Mepolizumab attenuates airway eosinophil numbers, but not their functional phenotype, in asthma. An additional cohort of 23 adult participants with mild asthma that was not treated with asthma controller therapy underwent segmental allergen bronchoprovocation to dust mite, ragweed, or cat, as previously described.Pre–allergen challenge and post–allergen challenge bronchial brushings were obtained and demonstrated significantly reduced ACE2 expression in lower airway epithelium in the post–allergen challenge samples ( Fig 2 , B) (FC 0.64; P = .01).

From in vitro models obtained from the Gene Expression Omnibus, we assessed the effects of IL-13, a type 2 cytokine strongly related to allergic asthma, on ACE2 expression in differentiated airway epithelial cells. IL-13 significantly reduced ACE2 expression (see Fig E1 in this article’s Online Repository at www.jacionline.org ) in both nasal (FC = 0.44; P = 5.8E–4) and bronchial (FC = 0.80; P = 5.1E–3) epithelium.

2 Wu Z, McGoogan JM. Characteristics of and important lessons from the coronavirus disease 2019 (COVID-19) outbreak in China: summary of a report of 72314 cases from the Chinese Center for Disease Control and Prevention [e-pub ahead of print]. JAMA https://doi.org/10.1001/jama.2020.2648. Accessed March 25, 2020. Viral respiratory infections are the most common trigger of severe asthma exacerbations in children and adults. Unexpectedly, large epidemiologic studies of the COVID-19 pandemic in China did not identify asthma as a risk factor of severe COVID-19–related illnesses.Here, we report that respiratory allergy and controlled allergen exposures are each associated with significant reductions in ACE2 expression. ACE2 expression was lowest in those with both high levels of allergic sensitization and asthma. Importantly, nonatopic asthma was not associated with reduced ACE2 expression. Given that ACE2 serves as the receptor for SARS-CoV-2, our findings suggest a potential mechanism of reduced COVID-19 severity in patients with respiratory allergies. However, it is likely that additional factors beyond ACE2 expression modulate the response to COVID-19 in individuals with allergy, and elucidation of these factors may also provide important insights into COVID-19 disease pathogenesis.

8 Li Y.

Zeng Z.

Cao Y.

Liu Y.

Ping F.

Liang M.

et al. Angiotensin-converting enzyme 2 prevents lipopolysaccharide-induced rat acute lung injury via suppressing the ERK1/2 and NF-kappaB signaling pathways. The strengths of our study include carefully phenotyped cohorts of children and adults. Further, the allergen challenge studies included both upper and lower airway samples, with each demonstrating a consistent impact on ACE2 expression. The limitations include lack of clinical information to directly link ACE2 expression to SARS-CoV-2 infection and illness severity in our study populations. In addition, we do not have data on the ACE2 protein levels to confirm the gene expression data, although previous work suggests a direct association between ACE2 mRNA levels and ACE2 protein levels in the lung.

9 Centers for Disease Control and Prevention

Hospitalization rates and characteristics of patients hospitalized with laboratory-confirmed coronavirus disease 2019 - COVID-NET, 14 States, March 1-30, 2020. It is important to note that early data in the United States suggest a higher rate of asthma in patients hospitalized for severe COVID-19 illness, but the data do not specify whether the asthma was allergic, which is an important differentiation that relates to our findings. Nor do the data mention the potential presence of other comorbidities, such as obesity, that have been identified as risk factors for COVID-19 illness.Future studies focused on respiratory allergy, asthma, and perhaps other allergic disorders are needed to provide greater understanding of the impact of underlying allergy on COVID-19 susceptibility and disease severity. The modulation of ACE2 expression by type 2 inflammatory processes suggests the need to comprehensively evaluate the role of type 2 immune regulation in COVID-19 pathogenesis. Further elucidation of these relationships could identify novel therapeutic strategies to more effectively control this pandemic.

Methods In all 3 studies, total RNA was extracted from epithelial brush samples preserved in RLT buffer (Qiagen, Germantown, Md). Samples were thawed, vortexed, and quick-spun, after which the supernatant was transferred to fresh tubes. The samples were then spun through a Qiashredder column (Qiagen) and extracted by using RNeasy mini kits (Qiagen) with 25-μL elution volumes following the manufacturer’s protocol. In the cat allergy upper airway challenge study, sequencing libraries were constructed from total RNA by using TruSeq RNA Sample Preparation Kits v2 (Illumina). In the URECA and adult asthma studies, sequencing libraries were constructed from total RNA by using SMART-Seq v4 Ultra Low Input RNA Kit (Takara). For each study, libraries were clustered onto a flow cell by using a cBOT amplification system with a HiSeq SR v4 Cluster Kit (Illumina). Single-read sequencing was carried out on a HiSeq2500 sequencer (Illumina), using a HiSeq SBS v4 Kit to generate 58-bp reads, with a target of approximately 10 million reads per sample. Samples for each study were processed and sequenced independently. E1 Smedley D.

Haider S.

Durinck S.

Pandini L.

Provero P.

Allen J.

et al. The BioMart community portal: an innovative alternative to large, centralized data repositories. E2 Liu R.

Holik A.Z.

Su S.

Jansz N.

Chen K.

Leong H.S.

et al. Why weight? Modelling sample and observational level variability improves power in RNA-seq analyses. Reads were processed by using workflows managed on the Galaxy platform. Reads were trimmed by 1 base at the 3' end and then trimmed from both ends until base calls had a minimum quality score of at least 30 (Galaxy FASTQ Trimmer tool [version 1.0.0]). FastqMcf (version 1.1.2) was used to remove any remaining adapter sequence. To align the trimmed reads, we used the STAR aligner with the GRCh38 reference genome and gene annotations from ensembl, release 91. Gene counts were generated by using HTSeq-count (version 0.4.1). For quality control, the samples kept were those that had counts greater than 1 million, more than 80% of reads aligned, and a median coefficient of variation (CV) coverage less than 1. Genes were filtered to include those that had a trimmed mean of M-value (TMM) normalization count of at least 1 in at least 10% of libraries and were classified as protein coding by using BioMart.Counts were transformed to log2 counts per million along with observation-level weights by using voomWithQualityWeights from the limma R packageto create a weighted gene expression matrix suitable for downstream analyses. E2 Liu R.

Holik A.Z.

Su S.

Jansz N.

Chen K.

Leong H.S.

et al. Why weight? Modelling sample and observational level variability improves power in RNA-seq analyses. , E3 Ritchie M.E.

Phipson B.

Wu D.

Hu Y.

Law C.W.

Shi W.

et al. Limma powers differential expression analyses for RNA-sequencing and microarray studies. Differential expression of ACE2 was assessed independently in each data set by using a weighted linear mixed effects model (limma) appropriate for RNA sequencing data and an empiric Bayes method.Mixed effects linear regression models were used; they included relevant clinical or technical variables (for URECA, cytologically determined cell percentages in the brush and the clinical site were used; for the upper airway challenge study, processing batch was used; and for the adult asthma study, no fixed effects were included) and a random effect of participant in both of the airway challenge studies. P values less than .05 were considered statistically significant. E4 Barrett T.

Wilhite S.E.

Ledoux P.

Evangelista C.

Kim I.F.

Tomashevsky M.

et al. NCBI GEO: archive for functional genomics data sets--update. E5 Alevy Y.G.

Patel A.C.

Romero A.G.

Patel D.A.

Tucker J.

Roswit W.T.

et al. IL-13-induced airway mucus production is attenuated by MAPK13 inhibition. E2 Liu R.

Holik A.Z.

Su S.

Jansz N.

Chen K.

Leong H.S.

et al. Why weight? Modelling sample and observational level variability improves power in RNA-seq analyses. , E3 Ritchie M.E.

Phipson B.

Wu D.

Hu Y.

Law C.W.

Shi W.

et al. Limma powers differential expression analyses for RNA-sequencing and microarray studies. We searched the National Center for Biotechnology Information Gene Expression Omnibus for the terms IL13 and epithelial subset to the organism Homo sapiens.From this we identified 2 studies investigating the effects of IL-13 stimulation on human airway epithelial cells grown at an air-liquid interface that had repeated measures in the IL-13 stimulation and unstimulated groups. In the GSE110799 study, human nasal epithelial cells isolated from nasal turbinates were cultured in an air-liquid interface until the full differentiation was complete, after which the differentiated cells at ALI-D47 were incubated with 100 ng/mL of IL-13 for 3 days. In GSE37693, RNA was isolated from primary culture airway epithelial cells grown at an air-liquid interface treated with or without IL-13 for 21 days.Differential expression analysis was performed by using GEO2R, which performs voom and limmain the National Center for Biotechnology Information's Gene Expression Omnibus browser. Fig E1 IL-13 stimulation decreases ACE2 expression in nasal and bronchial epithelium. IL-13 stimulation of airway epithelial cells grown in an air-liquid interface decreased ACE2 expression in nasal epithelium (FC = 0.44; P = 5.8E–4; n = 2 per condition) (A) and bronchial epithelium (FC = 0.80; P = 5.1E–3; n = 4 per condition) (B). Shown are mean expression levels (red) and individual points representing biologic replicates. Table E1 Association of T2 biomarkers and nasal brush ACE2 expression in the URECA cohort Biomarker Association with ACE2 expression (β coefficient) P value Positive allergen-specific IgE –0.089 3.1E–5 Total IgE level –0.31 5.1E–6 Fractional exhaled nitric oxide –0.45 3.4E–3 Blood eosinophils –0.13 .07 Nasal epithelial IL-13 expression –0.123 8.6E–5

Article Info Publication History Footnotes This project has been funded in whole or in part with Federal funds from the National Institute of Allergy and Infectious Diseases, National Institutes of Health (NIH) , Department of Health and Human Services , under grant numbers 1UM1AI114271-01, UM2AI117870 , 5UM1AI114271-03 , and UM1AI109565 . Additional support was provided by the National Heart, Lung, and Blood Institute , NIH, through grant number RO1HL12384 , and National Center for Advancing Translational Sciences , NIH, through grant numbers UL1TR001079 , 1UL1TR001430 , UL1TR001873 , and UL1TR002345 . Its contents are solely the responsibility of the authors and do not necessarily represent the official views of the NIH. The co-authorship by Drs Gergen, Becker, and Togias on this publication does not necessarily constitute endorsement by the National Institute of Allergy and Infectious Diseases, the NIH or any other agency of the United States government. Disclosure of potential conflict of interest: D. J. Jackson reports grants from the National Institutes of Health (NIH)/National Institute of Allergy and Infectious Diseases (NIAID)/National Heart, Lung and Blood Institute (NHLBI) and GlaxoSmithKline, as well as personal fees from Pfizer for data and safety and monitoring board participation and personal consulting fees from Novartis, Sanofi-Regeneron, GlaxoSmithKline, Vifor Pharma, and AstraZeneca. W. W. Busse reports grants from the NIH/NIAID/NHLBI during the conduct of the study, as well as personal fees from Novartis, Sandoz, Regeneron, AstraZeneca, GlaxoSmithKline, Genentech, Teva, Elsevier, Arrowhead, resTORbio, Med Learning Group, Practicing Clinicians Exchange, Boston Scientific, and Medscape. L. B. Bacharier reports grant support from the NIH/NIAID/NHLBI, Sanofi, and Vectura, as well as personal fees from GlaxoSmithKline, Genentech, Novartis, Merck, DBV Technologies, Teva, Boehringer Ingelheim, AstraZeneca, WebMD/Medscape, Sanofi, Regeneron, Vectura, and Circassia. R. A. Wood receives grant support from the NIH, Astellas, Aimmune, DBV, Sanofi, and Regeneron, as well as royalties from Up To Date. J. E. Gern reports grants from the NIH; personal fees and stock options from Meissa Vaccines, Inc; personal fees from AstraZeneca and Ena Therapeutics; and a patent on methods for production of rhinoviruses. Dr. Altman reports personal fees from Regeneron for consulting. The rest of the authors declare that they have no relevant conflicts of interest. Identification DOI: https://doi.org/10.1016/j.jaci.2020.04.009 Copyright © 2020 American Academy of Allergy, Asthma & Immunology ScienceDirect Access this article on ScienceDirect

Linked Article COVID-19: Start with the nose Journal of Allergy and Clinical Immunology

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