Identifying new therapeutic targets for asthma

Saturday, 31 March 2018

Severe asthma is defined as asthma that remains partly or totally unresponsive to asthma treatments.

Severe asthma is defined as asthma that remains partly or totally unresponsive to asthma treatments (1). The inflammatory mechanisms underlying severe asthma involve multiple cellular compartments with a diversity of disease-driving mechanisms. The CD4 T-helper Type 2 cell (Th2)-mediated pathway orchestrated by the airway epithelium has been recognized as a driving force in allergic asthma (2, 3). Eosinophil counts in induced sputum has been used as a surrogate biomarker for this pathway (4). However, eosinophilic asthma can also be underlined by a non-Th2 mechanism involving innate lymphoid cells of the type 2 (ILC2) (5, 6). The driving mechanism for non-eosinophilic asthma such as neutrophilic asthma has been associated with altered innate immune response and the activation of Th17 cells (7, 8). Gene expression analysis of sputum or blood cells from patients with neutrophilic asthma have reported high expression of genes related to pathogen recognition, neutrophil chemotaxis, protease activity and inflammasome assembly (9-11). The disease driver(s) associated with paucigranulocytic asthma remain largely unclear (12, 13), whilst clustering using clinical features alone have not yielded information on the underlying biology as similar inflammatory cell profiles have been seen between these clinical clusters (14). There is a need for new drugs to treat these patients but drug development is hindered by the inability of current models to accurately reflect the heterogeneity of severe asthma and to predict pathways that may be implicated in non-T2 asthma (15). One potential approach to overcome this lack of predictive models is to determine whether the current models reflect subtypes of asthma by examining the transcriptomic profile of various asthma models onto human asthma transcriptomic data. We hypothesise that different mouse models of asthma will map to distinct subsets of human asthma and that this mapping will elucidate key pathways that will define each model. The specific aims are: (1) To produce gene signatures that define 6 mouse models of asthma, (2) Map these signatures to human asthma, and (3) Examine how human asthma subset signatures map to mouse models. In this project we will produce gene signatures from 6 murine models of asthma using gene set expression analysis (GSEA). These signatures will then be mapped onto transcriptomic profiles from human severe and non-severe asthma obtained in U-BIOPRED using gene set variation analysis (GSVA). We will also use topological data analysis (TDA) as developed by Ayasdi to produce a 3D topological map of human asthma transcriptomics over which the various mouse signatures can be overlaid. Clusters of overlapping signatures may help define the characteristics of patients that are best defined by each mouse model. As a control we will use non-asthma mouse models of disease and perform reverse analysis by mapping gene transcriptomic signatures of published human asthma subsets onto mouse models using GSVA. A joint project 50:50 between Newcastle and Imperial College London with equal time spent at each


This PhD opportunity does not guarantee a scholarship. To also be considered for a scholarship please apply to the relevant scholarship round.


We seek highly organised, enthusiastic, motivated & organised people interested in immunology, epi/genetics, cellular/molecular biology, physiology, histology to work on lung projects. They will ideally have strong English & have experience in relevant techniques & working with mice & cell culture.

This opportunity is available for Domestic and International students.


For more information please contact:

Contact Name: Prof Phil Hansbro
Phone: +61 0427 263 084


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