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Chronic airway diseases cause a large burden for patients and caregivers and have large economic impact. Moreover, the burden is expected to increase with an increasing life expectancy of the world population. Therefore, there is a need for new biomarkers that can guide diagnosis, monitoring and the treatment of chronic airway diseases. Exhaled breath contains a complex mixture of volatile organic compounds (VOC) that can reflect local, systemic and exogenous (patho)physiological processes in the airways and alveoli and may thus be a promising target for biomarker discovery. Furthermore, breathomics holds the potential for non-invasive, easy, safe and point-of-care analysis. Several techniques for exhaled breath analysis exist that can be distinguished by three main aspects; the ability to detect individual VOCs or VOC patterns, real-time or offline measurements, and targeted or untargeted approaches. Available techniques have different advantages and limitations regarding sensitivity, specificity, costs and complexity. Multiple clinical studies already show the many opportunities of exhaled breath analysis regarding disease diagnosis, monitoring and prediction in diseases like asthma, chronic obstructive pulmonary disease (COPD) and cystic fibrosis (CF). To allow for implementation of exhaled breath in clinical practice, limitations of current detection techniques (e.g., the need for highly specialized personnel and machinery or sensitivity to detect very low concentrations of molecules in exhaled breath) should be overcome and results should be validated. Breathomics has large potential to make more personalized treatment possible in chronic airway diseases.

Contains fulltext : 165623.pdf (Publisher’s version ) (Open Access) Radboud University, 03 februari 2017 Promotor : Wevers, R.A. Co-promotores : Cristescu, S.M., Harren, F.J.M., Merkus, P.J.F.M.

Mucociliary clearance protects the host from pathogens by propelling them out of the airways via a layer of mucus. There are two key components to this process: proper mucus production and coordinated ciliary beating. If any or both of these components are not functioning properly, this can cause a mucociliary clearance disorder, such as cystic fibrosis (CF) or primary ciliary dyskinesia (PCD). This thesis discusses the development of outcome measures and biomarkers for the use of monitoring the effect of therapy and disease progression for people with a mucociliary clearance disorder. The thesis starts out on PCD and the challenges caused by the high heterogeneity of the disease. It discusses the challenges of designing proper clinical trials for people with PCD and CF and the phenotypes that are not included in those trials. A core outcome set is developed for PCD and one of the chapters shows the results of a real-life study including a severe CF phenotype, which was excluded from clinical trials. Next to outcomes in clinical trials, this thesis also focusses on biomarkers. Specifically, biomarkers in exhaled breath for the detection of pathogen infection. This thesis explores a novel route in validating these biomarkers. Finally, this thesis concludes that a hypothesis driven approach is key in monitoring disease progression and effectiveness of therapy, within people with a mucociliary clearance disease. Collaboration is extremely important for future development of new therapies and improving clinical care and quality of life for people with CF and PCD.

Asthma is a heterogeneous disease that presents with multiple clinical manifestations (phenotypes) with variable severities and treatment responses. It remains unclear whether high throughput omics could play a role in asthma phenotypic assessment. The objective of this thesis is to explore the value of omics, particularly the sputum microbiome and the exhaled breath metabolome, in asthma phenotyping using advanced statistical approaches. Part 1 is an introduction to the thesis exploring the importance of asthma precision medicine and the associations of different omics with asthma characteristics. Part 2 highlights the microbiota role in understanding and phenotyping asthma. The studies have shown that the sputum microbiome may play a role in refining the therapeutically challenging neutrophilic asthma phenotype. In this part, we have also shown that combining multiple omics provide more insight into the pathophysiology of asthma disease. Part 3 highlights the role of exhaled breath profiling by eNose in phenotyping and monitoring patients with asthma. The studies have shown that the eNose could serve as a non-invasive tool in screening the atopic asthma phenotype and may allow longitudinal monitoring of patients with asthma. Part 2 and Part 3 have shown the promising value of using omics in phenotyping patients with asthma, which may allow targeting diagnostic and therapeutic decisions to the individual patients' needs. Part 4 is a general discussion of the thesis, in which we have addressed the limitations and the general challenges in applying omics, particularly the microbial and the exhaled breath profiles, in the clinical decision-making process.

Asthma is in many respects a markedly heterogeneous condition, demonstrating strong variability between patients in terms of clinical presentation as well as pathology. This thesis aimed to expand our knowledge on asthma heterogeneity and to optimise treatment based on more targeted management strategies via an interdisciplinary approach by involving both laboratory and clinical studies. An in vitro study was conducted investigating the effects of short-chain fatty acids on barrier function modulation of human bronchial airway epithelial cells and their restoration after exposure to stimuli. We demonstrated that short-chain fatty acids can enhance barrier function of bronchial airway epithelial cells in a type- and concentration-dependent manner. In a meta-analysis of genome-wide association studies on the influence of genetic variation on exacerbation occurrence in children with asthma despite LABA therapy, we could identify eight suggestively associated genetic variants. In a real-life clinical trial we investigated the extent of exclusion of severe asthma patients from participation in randomised clinical trials investigating targeted biological therapies. The results show an exclusion of 82.4% of severe asthma patients treated in clinical care with biological therapies. Nevertheless, excluded patients demonstrated a similar clinical response to biological therapy after six months of continued use as reported in aforementioned clinical studies. Lastly, an unsupervised, data-driven longitudinal characterisation of different clusters of disease progression in severe asthma was conducted. In this study we could demonstrate that higher FeNO levels at baseline were associated with assignment to a cluster exhibiting respiratory worsening over time.

This thesis describes the short-term effects of environmental exposures on the cardiorespiratory system, and consists of two parts. In the first part, we investigated the short-term health effects of air pollution, in which 21 healthy young adults were repeatedly (2-5 visits) exposed for 5 hours to the ambient air near a major airport and two highways. We found that exposures to high levels of ultrafine particles, decreased lung function, prolonged the QTc interval, altered the exhaled breath profile, and heightened concentrations of oxidative stress markers in urine. This study shows the importance of air pollution reduction and the need for future research to determine how detrimental the (long-term) effects of exposure to ultrafine particles (from aviation) are. In the second part, we investigated the effects of a rhinovirus challenge on the fluctuations in exhaled metabolites. Exhaled breath measurements were performed 2-3 times per week using an electronic nose, 60 days before and 30 days after a rhinovirus-16 (RV16) challenge, in non-atopic healthy adults (n=12) and atopic mild asthmatics (n=12). We found that day-to-day fluctuations in the exhaled breath profiles rapidly increased after the RV16 challenge, with distinct differences between atopic mild asthmatics and non-atopic healthy volunteers. This proof-of-concept study shows the potential of exhaled breath analysis for monitoring of virus-induced exacerbations in asthma.