Comparison of upper and lower airway expression of SARS‐CoV‐2 receptors in allergic asthma
Notice bibliographique
Résumé
Severe Acute Respiratory Syndrome-Coronavirus-2 (SARS-CoV-2) which is responsible for Coronavirus disease-19 (COVID-19), infects host cells through the cell surface receptor angiotensin-converting enzyme 2 (ACE2) in conjunction with the cell surface transmembrane protease serine 2 (TMPRSS2). In asthmatic patients, mRNA expression of these receptors are shown to be down regulated in upper airways compared to the lower airways.1 Additionally, it is evident that type 2 asthma (T2) inflammation influences the expression of ACE2 and TMPRSS2.2, 3 In the present study, we examined the levels of ACE2 and TMPRSS2 in upper and lower airways and investigated the relationship to T2 inflammation through measures of alarmin cytokines IL-33 and thymic stromal lymphopoietin (TSLP). Bronchial tissue from allergic asthmatics (AA) and healthy controls (HC), and nasal tissue from AA with additional co-morbid allergic rhinitis (AR), and HC (Table S1) was immuno-stained and analyzed by immunofluorescent microscopy for protein expression of ACE2, TMPRSS2, IL-33 and TSLP. Written consent was obtained from all the participants of this study. We found significantly more cells immuno-positive for ACE2 in the bronchial tissue of AA versus bronchial tissue of HC (p <.0001), and versus nasal tissue of AR (p =.007) (Figure 1A). There were significantly more TMPRSS2 immuno-positive cells in nasal tissue of AR compared to HC (p =.002), while co-expression of ACE2 and TMPRSS2 was more frequent in AA versus HC in bronchial tissue (p =.02), but not significantly so in nasal tissue (p =.09) (Figure 1A). IL-33 displayed the same pattern as ACE2, with highest levels measured in the bronchial tissue of AA (Figure 1B). There was a significantly higher number of TSLP immuno-positive cells in bronchial versus nasal tissue, and this was a consistent finding in both the allergic (p =.02) and the HC (p =.002) (Figure 1B). This higher expression of the SARS-CoV-2 receptors as well as alarmin cytokines in allergic tissue, particularly in the bronchial tissue compared to the nasal tissue, is consistent with previous literature demonstrating primary expression of these receptors in bronchial cells, and that ongoing exposure inhaled allergens upregulates alarmin cytokines in asthmatic individuals.3 A similar pattern in the expression of alarmins and SARS-CoV-2 receptors in allergic tissue led us to investigate whether there were any relationships. When including all tissue and donors we observed a weak positive correlation between ACE2 levels and IL-33 and (r = 0.35, p =.01) but not with TSLP. However, in the smaller datasets examining upper and lower airway tissue separately we did not find any significant correlations between the expression of alarmins and ACE2/TMPRSS2 (data not shown); additional experiments are required to explore this observation. Our study is the first to report higher protein levels of ACE2 and TMPRSS2 receptors in in allergic tissue, and these findings are consistent with measurements of RNA in previous studies,1, 4 together suggesting that individuals with allergic airways disease may have a higher number of viral entry receptors in airways compared to HC. Despite these findings, recent data have shown that asthmatic patients have a lower risk of COVID-19 infection.5 These findings could be affected by a variety of factors in asthmatic patients including increased mucus production and susceptibility and exposure of S1/S2 cleavage site to proteases, but other factors such as age, sex, genetic predisposition, expression of non-functional isoform of the ACE2 receptor, and different SARS-CoV-2 variants could also play a role.6 Our staining antibodies are unable to distinguish between the long and short isoforms of the ACE2 receptor, and additional research is required to explore whether asthmatic patients possess a higher prevalence of the short isoform. Overall, further research is needed to fully understand the mechanisms underlying the lower risk of COVID-19 in asthmatic patients, which may have important implications for the management of COVID-19 in individuals with allergic airway disease. 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. 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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».