Identification of clinical, immunological and genetic markers of asthma subgroups
Publication Date
December 15, 2022
Creator
Abstract
Asthma is a heterogeneous disease thought to be driven by multiple overlapping clinical and immunological features present to different extents in different patients. Genome wide association studies (GWAS) have identified genetic signals associated with the risk of developing asthma, with many of these signals being in loci/genes involved in the type 2 inflammatory pathway. New asthma biological drugs that target specific components of the type 2 inflammation pathway have been brought into clinic over the last decade e.g. anti-IL5 (Mepolizumab). However, identifying patients who may or may not respond is still difficult. This thesis used three approaches; clinical, blood inflammatory and genetic profiling to explore asthma heterogeneity, with implications on treatment and wider asthma management. 4,205 asthma patients aged 16-60 were selected from the Genetics of Asthma Severity and Phenotypes (GASP) database; a Luminex assay was used for quantification of the serum biomarkers in 708 asthma patients, and 3,037 patients were genotyped for 25 genetic variants associated with moderate-severe asthma. The clinical data showed patients with childhood onset of asthma are more atopic compared to the adult-onset groups (IgE: <16 150 KU/L, 16-34 85.5 KU/L & 35-60 89.5 KU/L; p= 7.8x10-8). Serum data demonstrated multiple Th2 cytokines are present in the blood with highly correlated expression including IL-4 and IL-5 (r2= 0.51; p= <0.001). Some patients had multiple drivers of inflammation as 24.4% of patients overlapped for Th1, Th2 and Th17 cytokines using the top quartiles of biomarker levels. The genetic risk factors for moderate-severe asthma are implicated in the clinical features of asthma. rs61816764 (FLG) and rs9303277 (IKFZ3), showed the strongest effect size with childhood onset (p= 2.67x10-4 and 2.20x10-7; respectively). These data provide greater insight on the ability of stratified medicine, using genetics and inflammatory profile, to help identify the type of inflammation in asthma, guide treatment for biological therapy and even identify patients that may be suitable for combination biologic therapy.
Item Type
ethesis
Thesis Type
PhD
Supervisors
Subjects (LC)
Associated Schools / Departments
School of Medicine
eprints ID
69607
UoN Repository URI
Except where otherwise noted, this item's license is described as
File(s)![Thumbnail Image]()
Name
Karina Bingham PhD Thesis corrected version 20.07.22.pdf
Type
Full-text
Description
Examined. Final Corrected version of Thesis Karina Bingham
Size
5.48 MB
Format
Adobe PDF
Checksum (MD5)
a9495b5030a7ec5f1769a0e9242bcdb0