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Record W4382011852 · doi:10.1111/all.15793

Protein expression of <scp>SARS‐CoV</scp>‐2 receptors <scp>ACE2</scp> and <scp>TMPRSS2</scp> in allergic airways after allergen challenge

2023· letter· en· W4382011852 on OpenAlexafffundabout
Christiane E. Whetstone, Maral Ranjbar, Ruth P. Cusack, Dhuha Al‐Sajee, Hafsa Omer, Nadia Alsaji, Terence Ho, MyLinh Duong, Patrick Mitchell, Imran Satia, Paul K. Keith, Yanqing Xie, Jonathan MacLean, Doron D. Sommer, Paul M. O’Byrne, Roma Sehmi, Gail M. Gauvreau

Bibliographic record

VenueAllergy · 2023
Typeletter
Languageen
FieldMedicine
TopicSARS-CoV-2 and COVID-19 Research
Canadian institutionsMcMaster University Medical CentrePopulation Health Research InstituteMcMaster University
FundersMitacsAstraZeneca Canada
KeywordsImmunologyMedicineEosinophil cationic proteinSputumAllergenEosinophilTMPRSS2CytokineAllergyRhinovirusAsthmaInternal medicinePathologyVirus

Abstract

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Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) utilizes the angiotensin-converting enzyme 2 (ACE2) receptor in conjunction with the cell surface transmembrane protease serine 2 (TMPRSS2) to enter host cells.1 The type 2 (T2) cytokine IL-13 has been shown to downregulate ACE2 mRNA levels in cultured epithelial cells of asthmatic donors,2, 3 however, whether environmental triggers causing elevated airway IL-13 levels in vivo translates to changes in protein levels in asthmatic airways is unknown. By immunofluorescence microscopy, we assessed protein expression of ACE2 and TMPRSS2 under T2 high conditions after allergen challenge of the upper and lower airways of subjects with allergic asthmatics and allergic rhinitis, respectively (Table S1 Supporting Information). The study was approved by the Hamilton Integrated Research Ethics Board, and participants provided informed written consent. Eleven participants with mild allergic asthma (FEV1 ≥ 70% predicted, methacholine PC20 ≤ 16 mg/mL, skin prick test positive) underwent whole lung allergen inhalation challenges (AIC), resulting in early and late bronchoconstriction responses, sputum eosinophilia (Figure 1A,B), and increased sputum eotaxin-1, eosinophil-derived neurotoxin (EDN) and the T2 cytokines IL-5, and IL-13 post-challenge (p < .05) (Table S2 supplementary material). Ten participants underwent a second AIC using the same dose of allergen, and endobronchial biopsies were obtained before and again at 24 h post-AIC. There was a significant reduction in the number of bronchial tissue cells immuno-positive for ACE2, TMPRSS2, and double positive for ACE2/TMPRSS2 (p = .002, p = .014, p = .002, respectively) measured 24 h post-AIC (Figure 1C,D). There was no correlation between SARS-CoV-2 receptor immuno-positive cells and levels of biomarkers in sputum. Ten allergic asthmatics with co-morbid allergic rhinitis completed a crossover study with nasal allergen challenge (NAC) conducted after 21 days of intranasal placebo or triamcinolone (220 mcg BID) treatment. The NAC-induced changes in peak nasal inspiratory flow rate, nasal lavage eosinophils (Figure 2A,B) IL-5, IL-13, and eotaxin-1 (Table S2 Supporting Information) observed during placebo treatment were all significantly attenuated by triamcinolone (p < .05). In biopsies of inferior nasal turbinate, NAC did not change the number of cells immuno-positive for ACE2 or TMPRSS2 (Figure 2C,D), and we did not observe a relationship between immunopositivity for ACE2, TMPRSS2, and biomarkers in nasal lavage. Previous studies have reported that nasal and bronchial allergen challenges lower ACE2 mRNA transcript in epithelium of nasal and bronchial brushing, respectively.3 Using in vitro model data sourced from Gene Expression Omnibus, Jackson et al found that IL-13 reduced ACE2 mRNA expression in differentiated nasal and bronchial epithelium. Using cultured primary human bronchial epithelial cells Stocker et al reported that IL-13 decreases long ACE2 mRNA isoforms and reduces glycosylation of full length ACE2 protein, thereby limiting expression on the apical side of ciliated cells exposed to viral infection.2 We therefore hypothesized that elevation of IL-13 levels after allergen challenge and lowering of IL-13 with corticosteroid treatment would correspondingly regulate ACE2 protein expression in airways. Indeed, ACE2 and TMPRSS2 immunopositivity was significantly reduced in bronchial tissue after AIC. In nasal tissue, however, interpretation of the data is inconclusive due to low ACE2 and TMPRSS2 protein levels measured at baseline in inferior nasal turbinate tissue, and by the small study sample size. The proposed protective mechanisms of IL-13 raise the possibility that T2 high airways may be protective against SARS-CoV-2, but to date, this has not been supported by clinical observations. In general populations, there is no clear association between asthma and SARS-CoV-2 infectivity or hospitalization.4, 5 Counterintuitive to a proposed protective role of IL-13, treatment with dupilumab, a monoclonal antibody that blocks IL-13 signaling, was reported to improve survival in asthmatic patients compared with matched controls after SARS-CoV-2 infection.6 Collectively, these data suggest that despite dampening of ACE2 and TMPRSS2 receptor expression in airways by IL-13, there are other factors contributing meaningfully to the rate of SARS-CoV-2 infectivity and hospitalization in asthmatic patients. All authors contributed to the study design, acquisition or analysis of data, were involved with drafting of this manuscript, and approved the final version and are accountable for all aspects of the work. We would like to acknowledge funding from AstraZeneca Canada (ESR 20-20723) and Mitacs (IT22844). The authors have no conflict of interest related to this manuscript. Outside of this work, MD reports research funding from Gilead and Janssen; DDS reports Advisory Board, research funding, speaking fees from GSK, Sanofi, Stryker; PMB reports personal fees for consulting or speaker fees from AstraZeneca, GSK, MedImmune, Chiesi, Menarini and Covis and research grants from AstraZeneca, MedImmune, Biohaven, Merck and Bayer; GMG reports personal fees for consulting or speaker fees from AstraZeneca, Sanofi–Regeneron and research grants from Biohaven, Genentech, BioGaia, Novartis. The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions. Data S1. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.038
GPT teacher head0.297
Teacher spread0.259 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations2
Published2023
Admission routes3
Has abstractyes

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