We will accomplish this by taking the following stepwise approach:
We will first validate the risk SNPs associated to the 61 druggable genes for asthma, lung function and blood eosinophils (LifeLines cohort) and then determine which specific asthma subtype is regulated by these SNPs, by relating risk SNPs to asthma and its related subtypes (total IgE, IgE sensitisation, blood eosinophils, airway hyperresponsiveness (AHR), lung function, asthma onset) in three cohorts with rich asthma phenotypes. (Dutch Asthma GWAS study, PIAMA). We will use this information to understand which asthma related trait is specifically regulated by this SNP. This may help to define readouts in any further drug study. For example, a SNP may regulate a transcript involved in AHR. A drug developed to counteract this transcript may then first be studied for any effect on AHR.
In order to select the targets to be considered for drug repositioning, we will employ a staged approach: We will first validate if the gene transcripts display the expected differential expression in RNA Seq datasets from lung tissue or bronchial epithelial cells obtained from asthma patients and controls (biopsy and single-cell RNA sequencing datasets that are already available). Next, we will interrogate the expression of these genes in human primary cell culture models such as lung epithelial organoid cultures, air-liquid interface cultured human airway epithelial cells and human airway smooth muscle cells to evaluate the suitability of these models for step (3). We will compare expression levels between cells obtained from asthma patients and controls, as well as generate an asthma-like phenotype in these primary cells by exposing them to IL-13 and/or TGF-β. These experiments will not only provide additional support for the gene transcripts to be associated with asthma, but also will help prioritise the validation studies under (4). We will prioritise druggable genes, that (1) show consistent association with asthma (related traits); (2) and show differential expression in human asthma versus controls datasets.
Drugs that have been developed to target validated genes will then be prioritised based on type (where we will select small molecules over biologicals), availability and ability to manufacture. These drugs will then be tested in proof of concept studies in vitro, for which the selection of the models will be based on the validation studies under 2. The most promising drugs will then be evaluated in vivo. To direct the choice of in vivo model, we will first test which genes display similar expression changes in lung tissue in our in vivo models of asthma, including house dust mite induced asthma as well as ovalbumin induced asthma in the mouse and guinea pig by analysing existing gene expression datasets (whole lung RNA seq, airway epithelial RNA seq). We anticipate to test at least 3 drugs in the in vivo models that have been shown relevant for the specific target in the validation studies.