Dataset Information

Single-cell analysis of bronchoalveolar cells in inflammatory and fibrotic post-COVID lung disease

ABSTRACT: Rationale: Persistent pulmonary sequelae are evident in many survivors of acute coronavirus disease 2019 (COVID-19) but the molecular mechanisms responsible are incompletely understood. Post-COVID radiological lung abnormalities comprise two broad categories, organising pneumonia and reticulation, interpreted as indicative of subacute inflammation and fibrosis, respectively. Whether these two patterns represent distinct pathologies, likely to require different treatment strategies is not known. Objectives: We sought to identify differences at molecular and cellular level, in the local immunopathology of post-COVID inflammation and fibrosis. Methods: We compared single-cell transcriptomic profiles and T cell receptor (TCR) repertoires of bronchoalveolar cells obtained from convalescent individuals with each radiological pattern of post-COVID lung disease (PCLD). Measurements and Main Results: Inflammatory and fibrotic PCLD single-cell transcriptomes closely resembled each other across all cell types. However, CD4 central memory T cells (TCM) and CD8 effector memory T cells (TEM) were significantly more abundant in inflammatory PCLD. A greater proportion of CD4 TCM also exhibited clonal expansion in inflammatory PCLD. High levels of clustering of similar TCRs from multiple donors was a striking feature of both PCLD phenotypes, consistent with tissue localised antigen-specific immune responses, but there was no enrichment for known SARS-CoV-2 reactive TCRs. Conclusions: There is no evidence that radiographic organising pneumonia and reticulation in post-COVID lung disease are associated with differential immmunopathological pathways. Inflammatory radiology is characterised by greater bronchoalveolar T cell accumulation. Both groups show evidence of shared antigen-specific T cell responses, but the antigenic target for these T cells remains to be identified.

ORGANISM(S): Homo sapiens

PROVIDER: GSE228236 | GEO | 2024/06/05

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Project description:Segmental instillation of lipopolysaccharide (LPS) by bronchoscopy can be used as a model to safely induce transient airway inflammation in the human lung. The LPS challenge model enables investigation of cellular mechanisms involved in pulmonary inflammatory processes as well as pharmacodynamic analysis of investigational drugs for the treatment of respiratory diseases. Aim of this work was to describe the transcriptomic profile of the human segmental LPS challenge model with contextualization to major respiratory diseases. Pre-challenge bronchoalveolar lavage fluid (BAL) and biopsies were sampled from twenty-eight smoking, healthy subjects, followed by segmental LPS challenge and saline control challenge. Twenty-four hours post instillation, BAL and biopsies were collected from the challenged lung segments. Total RNA of cells from BAL and biopsy samples were sequenced for subsequent data analysis. Differential gene expression analysis resulted in 6316 upregulated differentially expressed genes (DEGs) and 241 downregulated DEG in BAL, but only one downregulated DEG in biopsy samples after LPS challenge compared to saline challenge. Upregulated DEG in BAL were related to molecular functions such as “Inflammatory response” or “antimicrobial humoral immune response mediated by antimicrobial peptide”, enriched biological processes such as “chemokine receptor activity”, and upregulated pro-inflammatory pathways such as “Wnt signaling pathway”, “Ras signaling pathway” or “JAK-STAT signaling pathway”. Furthermore, the segmental LPS challenge model resembled aspects of the five most prevalent respiratory diseases chronic obstructive pulmonary disease (COPD), asthma, pneumonia, tuberculosis and lung cancer and featured similarities with acute exacerbations in COPD (AECOPD) and community-acquired pneumonia (CAP). Overall, our study provides extensive information about the transcriptomic profile from BAL cells and mucosal biopsies following LPS challenge in healthy smokers. It expands the knowledge about the LPS challenge model providing potential overlap with respiratory diseases in general and infection-triggered respiratory insults such as AECOPD in particular.

Dataset Information

Single-cell analysis of bronchoalveolar cells in inflammatory and fibrotic post-COVID lung disease

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets