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Title: The involvement of microRNAs in macrophages' response to viruses in asthma exacerbations
Author: Francisco Garcia, Ana Soraia
ISNI:       0000 0004 8501 6932
Awarding Body: University of Southampton
Current Institution: University of Southampton
Date of Award: 2014
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Background: More than half of asthma exacerbations are caused by infection with human rhinovirus. When infected with rhinovirus (RV), macrophages produce tumour necrosis factor α (TNF-α), a pro-inflammatory cytokine that has been reported to be increased in the bronchoalveolar lavage of severe asthmatics. MicroRNAs thought to be involved in inflammatory responses were seen to be upregulated in alveolar macrophages of asthmatic patients. Hypothesis: MicroRNA profile is altered in asthmatic macrophages and airway and this leads to an exaggerated pro-inflammatory response to rhinoviral infections. Results: MiR-27a, miR-155 and miR-152 contributed to RV-induced TNF-α overexpression in alveolar macrophages. Upregulation of these microRNAs had an effect not only the cells' total RNA content but also polysome-bound genes, which only marginally overlapped with Targetscan 6.2 predictions. Only 24 of these genes were common to total and polysome-bound RNA. The microRNA and inflammatory profiles of these cells could be affected by the contents of bronchoalveolar lavage, in particular exosomes. Only 6% of exosomal RNA from severe asthmatic BAL is composed of microRNAs, compared to 27% in healthy controls. Dysregulated microRNAs could affect relevant pathways such as epithelial barrier, transforming growth factor β (TGF-β) and mitogen-activated protein kinases (MAPK) pathways, among others. Conclusions: MiR-27a, miR-155 and miR-152 are upregulated in macrophages from asthmatic patients. These microRNAs are able to increase TNF-α production following RV infection which could lead to worsening of symptoms in an asthmatic exacerbation. Such dysregulation could arise from differential loading of exosomes by airway cells. In order to improve their efficacy, microRNA function studies should ally in silico prediction tools with sequencing of both total and polysome-bound RNA.
Supervisor: Howarth, Peter ; Lau, Laurie Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available