Home » Abstracts » Human Health Proteomics » Divergent responses to SARS-CoV-2 infection in bronchial epithelium with pre-existing respiratory diseases

Divergent responses to SARS-CoV-2 infection in bronchial epithelium with pre-existing respiratory diseases

Human Health Proteomics

Abstract #160 Posted on26 March 202512 May 2025 12 May 2025 13h07

Author(s)

Justine Oliva | CIRI, Centre International de Recherche en Infectiologie, Team VirPath - Université Claude Bernard Lyon 1 | 46 Allée d’Italie, 69364, Lyon, France
Manon Ruffin | Centre de Recherche Saint-Antoine (CRSA) - Sorbonne Université | 34 rue Crozatier, 75012, Paris, France
Claire Calmel | Centre de Recherche Saint-Antoine (CRSA) - Sorbonne Université | 34 rue Crozatier, 75012, Paris, France
Aurélien Gibeaud | CIRI, Centre International de Recherche en Infectiologie, Team VirPath - Université Claude Bernard Lyon 1 | 46 Allée d’Italie, 69364, Lyon, France
Andrés Pizzorno | CIRI, Centre International de Recherche en Infectiologie, Team VirPath - Université Claude Bernard Lyon 1 | 46 Allée d’Italie, 69364, Lyon, France
Clémence Gaudin | Centre de Recherche Saint-Antoine (CRSA) - Sorbonne Université | 34 rue Crozatier, 75012, Paris, France
Solenne Chardonnet | UMS PASS, Plateforme Post-génomique de la Pitié-Salpêtrière (P3S) - Sorbonne Université | 91 boulevard de l'hôpital, 75013, Paris, France
Viviane de Almeida Bastos (Presenting Author) | UMS PASS, Plateforme Post-génomique de la Pitié-Salpêtrière (P3S) - Sorbonne Université | 91 boulevard de l'hôpital, 75013, Paris, France
Manuel Rosa-Calatrava | CIRI, Centre International de Recherche en Infectiologie, Team VirPath - Université Claude Bernard Lyon 1 | 46 Allée d’Italie, 69364, Lyon, France
Antoine Soulé | Department of Electrical and Computer Engineering - McGill University | 3480 University Street, H3A 0E9, Montréal, Canada
Amin Emad | Department of Electrical and Computer Engineering - McGill University | 3480 University Street, H3A 0E9, Montréal, Canada
Simon Rousseau | The Meakins-Christie Laboratories at the Research Institute of the McGill University Health Centre Research Institute - McGill University | 1001 boul Décarie, H4A 3J1, Montréal, Canada
Harriet Corvol | Pneumologie Pédiatrique, APHP, Hopital Trousseau | 26 Av. du Dr Arnold Netter, 75012, Paris, France
Olivier Terrier | CIRI, Centre International de Recherche en Infectiologie, Team VirPath - Université Claude Bernard Lyon 1 | 46 Allée d’Italie, 69364, Lyon, France
Loic Guillot | Centre de Recherche Saint-Antoine (CRSA) - Sorbonne Université | 34 rue Crozatier, 75012, Paris, France

Abstract

COVID-19 has impacted over 700 million people worldwide, causing significant mortality and morbidity. While patients with pre-existing respiratory pathologies were anticipated to be at a higher risk of developing severe COVID-19, limited research has explored how these underlying conditions influence the severity of infection. We investigated and compared the response of bronchial epithelial cells from healthy donors and patients with pre-existing respiratory conditions: cystic fibrosis (CF) and chronic obstructive respiratory disease (COPD) to SARS-CoV-2. For healthy donors, SARS-CoV-2 infection promotes loss of epithelium integrity. Omics results highlighted an inflammatory profile characterized by IFN pathway activation and a strong expression of CXCL-10 at 72 h post-infection, a cytokine correlated positively with severity in our cohort. CF and COPD samples displayed a delayed decrease or no disruption of epithelial integrity. Omics analyses showed that the epithelium was already pro-inflammatory before infection, with a weaker response to SARS-CoV-2. Notably, the proteomic profile of CF cells before infection highlighted a distinct peptidase activity, with an up-regulation of A1AT, which may inhibit TMPRSS2 – an enzyme crucial for invasion. In conclusion, the pre-existing inflammatory environment in CF and COPD patients may paradoxically provide a protective effect against severe COVID-19. This study identifies potential biomarkers that could aid in clinical monitoring.

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