The contribution of miRNAs to airway inflammation
File(s)
Author(s)
Headley-Morris, Lauren
Type
Thesis
Abstract
This thesis explores the role of microRNAs (miRNAs) in asthma and eosinophilic lung disease (ELD) through a series of next generation sequencing (NGS) studies. The research aimed to identify differentially expressed (DE) miRNAs and their potential biological implications in these respiratory conditions.
Initially, a nasosorption sampling method was optimized for miRNA sequencing from nasal mucosal samples, demonstrating its feasibility as a non-invasive approach for planned subsequent respiratory studies. In addition to optimization of the sampling, extraction and sequencing library generation an analytical pipeline for downstream processing of generated sequencing data was also developed. Due to the impacts of the COVID pandemic the focus of the thesis had to alter. Consequently, research became focused on the analysis of circulating miRNA expression in whole blood samples from severe asthmatics, non-severe asthmatics, and healthy controls using NGS. These investigations identified distinct miRNA signatures associated with asthma severity, including miR-1304-3p, miR-32-5p, and members of the let-7 family.
Gene ontology analyses of the DE-miRNAs implicated their involvement in processes such as apoptosis regulation, cellular metabolism, and enzyme binding, providing insights into potential underlying molecular mechanisms of disease. The research also explored miRNA expression in both whole blood and lung biopsy samples from individuals with ELD and healthy controls, revealing potential associations between miRNAs and clinical features, as seen with miR-202-5p and Eosinophil counts.
While sample size limitations and technical challenges were encountered, particularly in relation to the ELD study, the research highlighted the complexity of miRNA regulatory networks in respiratory diseases. The findings lay the groundwork for future research aimed at developing novel diagnostic tools and personalized treatment approaches for respiratory diseases.
Initially, a nasosorption sampling method was optimized for miRNA sequencing from nasal mucosal samples, demonstrating its feasibility as a non-invasive approach for planned subsequent respiratory studies. In addition to optimization of the sampling, extraction and sequencing library generation an analytical pipeline for downstream processing of generated sequencing data was also developed. Due to the impacts of the COVID pandemic the focus of the thesis had to alter. Consequently, research became focused on the analysis of circulating miRNA expression in whole blood samples from severe asthmatics, non-severe asthmatics, and healthy controls using NGS. These investigations identified distinct miRNA signatures associated with asthma severity, including miR-1304-3p, miR-32-5p, and members of the let-7 family.
Gene ontology analyses of the DE-miRNAs implicated their involvement in processes such as apoptosis regulation, cellular metabolism, and enzyme binding, providing insights into potential underlying molecular mechanisms of disease. The research also explored miRNA expression in both whole blood and lung biopsy samples from individuals with ELD and healthy controls, revealing potential associations between miRNAs and clinical features, as seen with miR-202-5p and Eosinophil counts.
While sample size limitations and technical challenges were encountered, particularly in relation to the ELD study, the research highlighted the complexity of miRNA regulatory networks in respiratory diseases. The findings lay the groundwork for future research aimed at developing novel diagnostic tools and personalized treatment approaches for respiratory diseases.
Version
Open Access
Date Issued
2024-10-23
Date Awarded
01/01/2025
License URL
Advisor
Moffatt, Miriam
Lovett, Michael
Hansel, Trevor
Sponsor
Asthma UK (Organisation)
Publisher Department
National Heart & Lung Institute
Publisher Institution
Imperial College London
Qualification Level
Doctoral
Qualification Name
Doctor of Philosophy (PhD)