Biomarker discovery for asthma phenotyping: From gene expression to the clinic

Asthma is considered a complex respiratory disease of which various asthma phenotypes are being discovered. Clinical biomarkers have shown to be successful in the management of asthma phenotypes. High-throughput omics technologies are now available to allow further biomarker discovery for this complex disease, such as transcriptomics, proteomics, lipidomics, and breathomics. In this thesis, I discussed the strengths and limitations of transcriptomics by microarrays and next-generation RNA sequencing. Next, metabolomics in exhaled air is reviewed as a non-invasive tool for the clinic. To conclude, composite molecular fingerprints have the best prospect as biomarkers in the phenotyping of patients with complex respiratory diseases such as asthma.
Furthermore, I studied the link between the upper and lower airways by analysing gene expression profiles of upper and lower airway epithelial cells in healthy individuals and examining the impact of allergic rhinitis and asthma on these expression profiles. Several new genes and pathways were identified that might be potential targets for future drug development. Next, I examined the responses of airway epithelium to double-stranded RNA (dsRNA) as a model of viral induced exacerbations. Potential targets for drug-discovery studies were identified, related to mitochondrial dysfunction and interferon signalling.
In the next study, blood eosinophils represented an accurate biomarker for eosinophilic airway inflammation which can facilitate guidance of current and novel individualised asthma treatment.
In the last chapter a composite electronic nose (eNose) platform was used to assess eosinophilic airway inflammation in patients with asthma in a quick and non-invasive way, thereby potentially facilitating personalized asthma management.