The influence of smoking status on exhaled breath profiles in asthma and COPD patients

Breath analysis using eNose technology can be used to discriminate between asthma and COPD patients, but it remains unclear whether results are influenced by smoking status. We aim to study whether eNose can discriminate between ever- vs. never-smokers and smoking <24 vs. >24 h before the exhaled breath, and if smoking can be considered a confounder that influences eNose results. We performed a cross-sectional analysis in adults with asthma or chronic obstructive pulmonary disease (COPD), and healthy controls. Ever-smokers were defined as patients with current or past smoking habits. eNose measurements were performed by using the SpiroNose. The principal component (PC) described the eNose signals, and linear discriminant analysis determined if PCs classified ever-smokers vs. never-smokers and smoking <24 vs. >24 h. The area under the receiver-operator characteristic curve (AUC) assessed the accuracy of the models. We selected 593 ever-smokers (167 smoked <24 h before measurement) and 303 never-smokers and measured the exhaled breath profiles of discriminated ever- and never-smokers (AUC: 0.74; 95% CI: 0.66-0.81), and no cigarette consumption <24h (AUC 0.54, 95% CI: 0.43-0.65). In healthy controls, the eNose did not discriminate between ever or never-smokers (AUC 0.54; 95% CI: 0.49-0.60) and recent cigarette consumption (AUC 0.60; 95% CI: 0.50-0.69). The eNose could distinguish between ever and neversmokers in asthma and COPD patients, but not recent smokers. Recent smoking is not a confounding factor of eNose breath profiles

Pharmacogenomic associations of adverse drug reactions in asthma: systematic review and research prioritisation

A systematic review of pharmacogenomic studies capturing adverse drug reactions (ADRs) related to asthma medications was undertaken, and a survey of Pharmacogenomics in Childhood Asthma (PiCA) consortia members was conducted. Studies were eligible if genetic polymorphisms were compared with suspected ADR(s) in a patient with asthma, as either a primary or secondary outcome. Five studies met the inclusion criteria. The ADRs and polymorphisms identified were change in lung function tests (rs1042713), adrenal suppression (rs591118), and decreased bone mineral density (rs6461639) and accretion (rs9896933, rs2074439). Two of these polymorphisms were replicated within the paper, but none had external replication. Priorities from PiCA consortia members (representing 15 institution in eight countries) for future studies were tachycardia (SABA/LABA), adrenal suppression/crisis and growth suppression (corticosteroids), sleep/behaviour disturbances (leukotriene receptor antagonists), and nausea and vomiting (theophylline). Future pharmacogenomic studies in asthma should collect relevant ADR data as well as markers of efficacy

Treatment response in childhood asthma. An interplay of genes and inflammatory signals

Treatment response in asthmatic children Asthma is a chronic disease of the airways and the most common chronic disease among children. Inhaled corticosteroids (ICS) are the cornerstone of persistent asthma treatment and are thought to function due to their anti-inflammatory properties. Additionally, β2-adrenergic receptor agonists (short- or long-acting) are used to relieve asthma symptoms. Although asthma treatment is effective in many patients, there is large variability in the level of symptom control and lung function improvement. Furthermore, a small group of patients continues to suffer from severe exacerbations, or long-term uncontrolled asthma symptoms, despite asthma maintenance treatment. The thesis of Susanne Vijverberg describes research on the biological profile underlying asthma treatment outcomes in children. Research methodologies from the fields of pharmacoepidemiology, pharmacogenetics, immunology and breath metabolomics were applied to study asthma treatment response. Most studies have been performed in the context of the PACMAN cohort study, a Dutch pharmacy-based cohort study of children with a reported use of asthma medication. Main findings of this thesis The research in this thesis shows that various genetic loci influence the risk of severe exacerbations or poor symptom control in children with a reported use of asthma medication. Variation in the gene ST13 and in a DNA region called the 17q21 locus, were found to be associated with an increased risk of severe exacerbations despite ICS use. Variation in another gene, ADRB2, was found to be associated with a poorer response to long-acting β2-adrenergic receptor agonists. Especially this genetic marker seems to have a large effect on treatment response. Furthermore, the research shows that the pre-activation of granulocytes in the peripheral blood did not relate to asthma symptoms or lung function. Airway inflammation is one of the main pathological characteristics of asthma. Inflamed tissue releases chemo-attractants and cytokines which recruit activated immune cells, such as granulocytes, from the peripheral blood. It was hypothesized that the level of pre-activated granulocytes in peripheral blood would be different in children with uncontrolled asthma symptoms compared to children with controlled symptoms. However, no differences were found. Additionally, preliminary data in this thesis shows that breath analysis might be promising tool to identify distinct asthma phenotypes in a non-invasive manner. The measurement of a combination of exhaled inflammatory markers is more accurate in capturing the different aspects of asthma control than the measurement of one single exhaled inflammatory marker. Recommendations In the near future, clinically applicable algorithms incorporating genetic and inflammatory markers may help to diagnose and stratify treatment. The first steps towards this personalised treatment involve the identification and validation of potential biomarkers. A multi-dimensional biomarker approach (the assessment of a multitude of biomarkers), rather than a single biomarker-approach should be applied to characterize the different asthma phenotypes. In addition, there is a need for international collaboration to exchange knowledge, obtain larger study populations and validate biomarkers. Lastly, large randomised controlled trials are necessary to evaluate the clinical value of ADRB2-guided treatment in asthmatic children in comparison to current clinical practises

Pharmacogenomics of inhaled corticosteroids and leukotriene modifiers : a systematic review

BACKGROUND Pharmacogenetics studies of anti-inflammatory medication of asthma have expanded rapidly in recent decades, but the clinical value of their findings remains limited. OBJECTIVE To perform a systematic review of pharmacogenomics and pharmacogenetics of inhaled corticosteroids (ICS) and leukotriene modifiers (LTMs) in patients with asthma. METHODS Articles published between 1999 and June 2015 were searched using PubMed and EMBASE. Pharmacogenomics/genetics studies of patients with asthma using ICS or LTMs were included if ≥1 of the following outcomes were studied: lung function, exacerbation rates or asthma symptoms. The studies of Single Nucleotide Polymorphisms (SNPs) that had been replicated at least once were assessed in more detail. RESULTS In total, 59 publications were included in the systematic review: 26 addressed LTMs (including two genomewide Genome-Wide association studies [GWAS]) and 33 addressed ICS (including four GWAS). None of the GWAS reported similar results. Furthermore, none of the SNPs assessed in candidate gene studies were identified in a GWAS. No consistent reports were found for candidate gene studies of LTMs. In candidate gene studies of ICS, the most consistent results were found for rs28364072 in FCER2. This SNP was associated with all three outcomes of poor response, and the largest effect was reported with the risk of exacerbations (hazard ratio, 3.95; 95% CI, 1.64–9.51). CONCLUSION AND CLINICAL RELEVANCE There is a lack of replication of genetic variants associated with poor ICS or LTM response. The most consistent results were found for the FCER2 gene [encoding for a low-affinity IgE receptor (CD23)] and poor ICS response. Larger studies with well-phenotyped patients are needed to assess the clinical applicability of ICS and LTM pharmacogenomics/genetics

Diagnosing eosinophilic asthma using a multivariate prediction model based on blood granulocyte responsiveness

Background: The identification of inflammatory asthma phenotypes, using sputum analysis, has proven its value in diagnosis and disease monitoring. However due to technical limitations of sputum analysis there is a strong need for fast and non-invasive diagnostics. This study included the activation state of eosinophils and neutrophils in peripheral blood to phenotype and monitor asthma. Objectives: To (1) construct a multivariable model using the activation state of blood granulocytes, (2) compare its diagnostic value with sputum eosinophilia as gold standard and (3) validate the model in an independent patient cohort. Methods: Clinical parameters, activation of blood granulocytes and sputum characteristics were assessed in 115 adult asthma patients (training cohort/Utrecht) and 34 patients (validation cohort/Oxford). Results: The combination of blood eosinophil count, FeNO, ACQ, medication use, nasal polyposis, aspirin sensitivity and neutrophil/eosinophil responsiveness upon stimulation with fMLF, was found to identify sputum eosinophilia with 90.5% sensitivity and 91.5% specificity in the training cohort and with 77% sensitivity and 71% specificity in the validation cohort (relatively high percentage on OCS). Conclusions: The proposed prediction model identifies eosinophilic asthma without the need for sputum induction. The model forms a non-invasive and externally validated test to assess eosinophilic asthma in patients not on OCS

Breathomics in Chronic Airway Diseases

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

Genetic variation in uncontrolled childhood asthma despite ICS treatment

Genetic variation may partly explain asthma treatment response heterogeneity. We aimed to identify common and rare genetic variants associated with asthma that was not well controlled despite inhaled corticosteroid (ICS) treatment. Data of 110 children was collected in the Children Asthma Therapy Optimal trial. Associations of genetic variation with measures of lung function (FEV1%pred), airway hyperresponsiveness (AHR) to methacholine (Mch PD20) and treatment response outcomes were analyzed using the exome chip. The 17q12-21 locus (containing ORMDL3 and GSMDB) previously associated with childhood asthma was investigated separately. Single-nucleotide polymorphisms (SNPs) in the 17q12-21 locus were found nominally associated with the outcomes. The strongest association in this region was found for rs72821893 in KRT25 with FEV1%pred (P=3.75*10-5), Mch PD20 (P=0.00095) and Mch PD20-based treatment outcome (P=0.006). No novel single SNPs or burden tests were significantly associated with the outcomes. The 17q12-21 region was associated with FEV1%pred and AHR, and additionally with ICS treatment response.The Pharmacogenomics Journal advance online publication, 12 May 2015; doi:10.1038/tpj.2015.36

Association of bronchial steroid inducible methylation quantitative trait loci with asthma and chronic obstructive pulmonary disease treatment response.

Pathogenesis and treatment of chronic pulmonary disease