Mariana Valente
Farraia
Uso de um nariz electrónico para identificar asma
em indivíduos com sintomas respiratórios: do
laboratório ao doente
Use of an electronic nose to identify asthma in
subjects with respiratory symptoms: from bench to
bedside
Mariana Valente
Farraia
Uso de um nariz electrónico para identificar asma
em indivíduos com sintomas respiratórios: do
laboratório ao doente
Use of an electronic nose to identify asthma in
subjects with respiratory symptoms: from bench to
bedside
Tese apresentada à Universidade de Aveiro para cumprimento dos
requisitos necessários à obtenção do grau de Mestre em Bioquímica, ramo de Métodos Biomoleculares, realizada sob a orientação científica de André Moreira, Professor Imunologia Básica e Clínica, Departamento de Patologia, Faculdade de Medicina, Universidade do Porto e Sílvia M. Rocha,
Professora do Departamento de Química da Universidade de Aveiro.
Apoio financeiro do Projeto NORTE-01-0145-FEDER-000010 – Health, Comfort and Energy in the Built Environment (HEBE), cofinanciado pelo Programa Operacional Regional do Norte (NORTE2020), pelo Fundo Europeu de Desenvolvimento Regional (FEDER).
Apoio financeiro do Projeto “Establishing protocols to assess occupational exposure to
microbiota in clinical settings” (EXPOSE 02/SAICT/2016 - Candidatura nº 023222), financiado pelo Programa Operacional Competitividade e Internacionalização (COMPETE 2020).
o júri
presidente Prof. Doutora Maria do Rosário Gonçalves dos Reis Marques Domingues professora associada com agregação, Universidade de Aveiro
Prof. Doutor Frederico Eugénio de Castro Soares Regateiro professor auxiliar, Faculdade de Medicina da Universidade de Coimbra
Prof. Doutor André Miguel Afonso de Sousa Moreira
agradecimentos A elaboração deste trabalho não foi possível sem a ajuda e apoio de diversas pessoas que, contribuíram de diversas formas até à chegada deste marco no meu percurso académico.
O meu sincero agradecimento ao meu orientador, Professor André Moreira, por me ter concedido a oportunidade de trabalhar com a sua equipa e por ter sido uma ajuda e apoio constante ao longo deste ano de trabalho. Obrigada pela disponibilidade e palavras de motivação ao longo das várias fases deste projeto. Quero ainda deixar as minhas palavras de agradecimento à
Professora Sílvia Rocha pelo acompanhamento e disponibilidade despendidos ao longo deste projeto.
Agradeço também ao João Rufo, Inês Paciência e Francisca Mendes por me terem acolhido, acompanhado, apoiado e auxiliado em vários momentos. Foi um prazer ter-vos conhecido e ter tido a oportunidade de aprender com vocês! A todas as pessoas que, de certa forma contribuíram para todo o meu
percurso académico (professores, colegas, amigos), agradeço por me terem ensinado e partilhado conhecimentos e ensinamentos. Ainda, aos meus colegas do Mestrado em Bioquímica e Licenciatura em Ciências Biomédicas, agradeço por me terem acompanhado, tanto nos melhores como nos
momentos mais difíceis, e por terem contribuído para que Aveiro se tornasse ainda mais especial. Obrigada também aos meus amigos mais chegados pela paciência e motivação.
As minhas últimas palavras são dedicadas aos meus pais e irmã. Obrigado por estarem sempre presentes, pelos sacrifícios, pela confiança, pelo apoio e pelos muitos bons momentos e experiências que sempre me conseguiram proporcionar ao longo destes anos. Um obrigado também aos meus tios, primos e avós. Termino com um último obrigado ao meu namorado por me ter sempre acompanhado, incentivado e motivado ao longo deste ano.
palavras-chave
resumo
Nariz electrónico; ar exalado; asma; diagnóstico; Cyranose 320; compostos orgânicos voláteis.
Os compostos orgânicos voláteis (VOC) no ar exalado têm demonstrado resultados promissores na discriminação de indivíduos com asma e controlos saudáveis. Esta tese pretende providenciar uma revisão sistemática acerca do uso da tecnologia do nariz eletrónico (eNose) no diagnóstico de doenças e perceber se a análise do perfil de VOC com o eNose pode ser aplicada para identificar asma numa população com sintomas respiratórios.
Inicialmente, foi elaborada uma pesquisa sistemática para identificar os estudos publicados relativos ao uso do eNose como potencial ferramenta de diagnóstico na medicina. Depois, foi conduzido um estudo de corte transversal, no qual foram recolhidas e analisadas, por um eNose composto por 32
sensores (Cyranose 320®), amostras de ar exalado de 199 indivíduos
recrutados de uma clínica. Os parâmetros da função pulmonar foram
recolhidos, tal como, o preenchimento do questionário CARAT para aceder ao nível de controlo das doenças das vias aéreas. O modelo multivariado de análise de clusters foi contruindo usando os valores de resistência dos 32 sensores sendo que, foi possível dividir a população em 2 clusters de acordo com o perfil de VOC. Os modelos generalizados lineares ajustados para os agentes confundidores foram calculados para testar o modelo desenvolvido. Foram selecionados para análise qualitativa quarenta e oito estudos, sendo que o Cyranose 320® é o aparelho mais usado. Já foram conduzidos diversos
estudos de prova de conceito em diversas doenças sendo que, a asma e a doença obstrutiva crónica (DPOC) alcançaram bons resultados de precisão (CVV>80%). O estudo de corte transversal incluiu 67.8% de indivíduos com diagnóstico médico de asma. O perfil dos VOC foi capaz de distinguir
participantes com pior controlo de sintomas característicos de asma daqueles com maior controlo (p=0.01). Os indivíduos com pior controlo dos sintomas foram distinguidos usando o modelo hierárquico de clusters desenvolvido. Os resultados dos vários estudos na área sugerem que o eNose é uma ferramenta complementar de diagnóstico promissora. Contudo, é urgente o desenho de ensaios confirmatórios em populações em que o dispositivo será usado. Numa população caracterizada por doenças respiratórias, a análise do perfil de VOC usando um eNose pode ser usada como meio complementar rápido e não-invasivo de diagnóstico para identificar indivíduos com sintomas de asma não controlados. Esta descoberta poderá levar a uma melhora no tratamento e gestão da doença, encorajando o desenho de ensaios confirmatórios.
xi keywords
abstract
Electronic nose, exhaled breath, asthma, diagnosis, Cyranose 320; volatile organic compounds.
Exhaled breath volatile organic compounds (VOC) have shown promising results when discriminating individuals with asthma from healthy controls. This study aims to provide a systematic review of the use of electronic nose (eNose) technology to diagnosis diseases and to assess if the exhaled VOC analysis using an eNose may be applied to identify individuals with asthma in a population with respiratory symptoms.
A systematic search for published studies using the eNose as a diagnostic tool in medicine was performed. Then, a cross-sectional study was conducted and breath samples from 199 participants recruited from an outpatient clinic were collected and analysed using an electronic nose composed by 32 sensors (Cyranose 320®). Lung function parameters and CARAT questionnaire to
assess level of control of airways disease were performed. A multivariate cluster analysis model, using resistance data from the 32 sensors, was built to discriminate the VOC patterns between individuals separating the population in 2 clusters. Adjusted generalized linear models (GLM) for confounders were used to test the developed model.
Forty-eight studies were selected for qualitative analysis and Cyranose 320®
was the most used device. Proof-of-concept studies were already performed in several diseases and good accuracy values (CVV>80%) for some respiratory diseases, like asthma and COPD, were found. Regarding the cross-sectional study, study population was composed by 67.8% of individuals with a medical diagnosis of asthma. Smell-prints were able to distinguish participants with uncontrolled asthma-like symptoms from those with controlled symptoms (p= 0.01). Individuals with symptoms of uncontrolled airways disease were discernible using the developed hierarchical cluster model.
The results from the revised studies suggests that eNoses can be promising diagnostic devices. However, confirmatory clinical trials in intend-to-treat populations are urgent. In a population with respiratory diseases, the analysis of the VOC profile by eNose may be used as a fast and non-invasive
complementary diagnostic agent for screening individuals in search of uncontrolled asthma-like symptoms. This may lead to an enhanced management and treatment of disease and encourages the design of confirmatory trials.
xiii
Abbreviations
5-LO - 5-lipoxygenase AAT - Alpha 1-anti-trypsin
ACQ - Asthma control questionnaire ACT - Asthma control test
ALS - Amyotrophic lateral sclerosis ARDS - Acute respiratory distress syndrome
ARIA - Allergic Rhinitis and its impact on Asthma group ATP - Adenosine triphosphate
ATS - American Thoracic Society
ATS-ERS - American Thoracic Society – European Respiratory Society AUC - Area under the curve
BALF - Bronchoalveolar lavage fluid BD - Bronchodilatation
BMI - Body mass index CA - Cluster analysis
CARAT - Control of Allergic Rhinitis and Asthma Test COPD - Chronic obstructive pulmonary disease
COSMIN - Consensus-based Standards for the selection of Health Measurement Instruments
CT - Computed tomography CYP450 - Cytochrome P450 CVV - Cross validation value
xiv
DFA - Discriminant function analysis EBC - Exhaled breath condensate eNose - Electronic nose
ENT - Ear, nose and throat
FEF 25-75 - Forced expiratory flow 25 – 75% FeNO - Fractional exhaled nitric oxide
FEV1 - Forced expiratory volume in the first second FN - False negative
FP - False positive FVC - Forced vital capacity
GCxGC-TOF-MS - Two-dimensional gas chromatography time of flight mass spectrometry
GINA - Global initiative for asthma
GC-MS - Gas-chromatography mass-spectrometry GLM - Generalized linear model
IA - Invasive aspergillosis ICS - Inhaled corticosteroid IFN-α - Interferon alpha IgE - Immunoglobulin E IL - Interleukin
ILC2 - Innate lymphoid type 2 cells LABA - Long-acting β2-agonist
LDL - Low-density lipoprotein LOS - Late-onset sepsis
xv
LR - Likelihood ratio LT - Leukotriene LTB4 - Leukotriene B4
LTRA - Leukotriene receptor antagonist M-distance - Mahalanobis distance
MHCII - Major histocompatibility complex II MPM - Malignant pleural mesothelioma
NMR - Nuclear magnetic resonance spectroscopy NO - Nitric oxide
NOSII - Nitric oxide synthase II NPV - Negative predictive value OSAS - Obstructive sleep apnoea PARC - Pattern recognition PC - Principal component
PCA - Principal component analysis PCR - Principal component regression PEF - Peak expiratory flow
PGD2 - Prostaglandin 2 PLA - Phospholipase A2 PPV - Positive predictive value PsA - Psoriatic arthritis
PUFA - Polyunsaturated fatty acids QCM - Quartz crystal microbalance
xvi
R0 - Response to the baseline reading
RA - Rheumatoid arthritis ROC - Receiving operator curve ROS - Reactive oxygen species Rt - Response of sample gas SAW - Surface acoustic waves SPT - Skin-prick test
SR - Relative sensor response
STARD - Standards for Reporting of Diagnostic Accuracy Studies TCA cycle - Tricarboxylic acid cycle
TGF-β - Transforming growth factor beta Th - T helper
TN - True negative TP - True positive
TSLP - Thymic stromal lymphopoietin VAP - Ventilator associated pneumonia VLDL - Very-low-density lipoprotein VOC - Volatile organic compounds WHO - World health organization WSS - Within-cluster sum of square
xvii
Table of contents
Abbreviations ... xiii
Table of contents ... xvii
List of Figures ... xix
List of Tables ... xxi
I. Introduction ... 1
1. Asthma ... 1
1.1. Pathophysiology and Phenotypes... 1
1.2. Diagnosis ... 5
1.3. Altered metabolic pathways ... 9
1.4. Exhaled breath analysis and its potential as a diagnostic tool ... 13
1.5. Exhaled breath and potential biomarkers ... 15
2. Electronic Noses for Clinical Applications ... 19
2.1. Clinical evaluation of diagnostic devices ... 19
2.2. Electronic olfactory system ... 21
2.3. Cyranose 320® ... 23
3. Data Processing ... 25
3.1. eNose data analysis ... 25
3.2. Statistical analysis to eliminate confounding effects ... 27
4. Future perspectives and challenges ... 28
II. Objectives ... 30
III. Materials and Methods ... 31
1. Systematic Review: eNose as a diagnostic tool in medicine ... 31
1.1. Search criteria ... 31
2. Cross Sectional Study ... 31
2.1. Exhaled breath collection ... 31
2.2. Study Design ... 34
2.3. Participants ... 34
2.4. Clinical and Physical Assessment ... 35
2.5. Data Analysis ... 37
2.6. Quality Control Sample ... 38
3. Sensors’ response to standard solutions ... 39
xviii
IV. Results ... 41
1. Systematic Review ... 41
2. Cross Sectional Study ... 42
2.1. Exhaled breath collection ... 42
2.2. Clinical Characteristics of participants ... 44
2.3. Hierarchical cluster analysis ... 45
2.4. Quality control sample ... 51
2.5. Sensors’ response to standard solutions ... 53
V. Discussion ... 55
VI. Conclusions ... 60
VII. References ... 61
xix
List of Figures
Figure 1 - T-cell immune response in asthma. ... 2
Figure 2 – Heterogeneity of asthma and representation of main phenotypes according to GINA report (allergic, non-allergic, with obesity and late onset). ... 4
Figure 3 – Representation of some altered metabolic pathways in asthma linked to cellular energy, lipid and amino acid metabolism. ... 10
Figure 4 – Oxidative stress induces lipid peroxidation of PUFA from cellular membranes leading to formation of hydrocarbons that can be excreted in exhaled breath or be further metabolized by CYP450 enzymes to alcohols. ... 16
Figure 5- Cyranose 320 ® device (left) and Custom noseChip® sensor (right). ... 24
Figure 6 - Exhaled breath collection system.. ... 32
Figure 7 - Exhaled breath collection.. ... 32
Figure 8 - Flow of participants through the study. ... 35
Figure 9- Exhaled breath analysis with Cyranose 320®. ... 37
Figure 10- Analysis of ten samples of decane with Cyranose 320® after incubation in dry bath for 2 min at 37ºC. ... 39
Figure 11 - Summary of the literature search. ... 41
Figure 12- Principal component analysis to assess how smell prints from the 32 sensors were separated in two clusters. ... 45
Figure 13- Total within sum of squares method to assess optimal number of clusters, K=2. ... 45
Figure 14- Average silhouette width method to assess optimal number of clusters, K=2. ... 46
Figure 15- Ward’s minimum variance hierarchical clustering model. ... 46
Figure 16 - Classification rates estimates between the two clusters of the hierarchical model. ... 49
Figure 17 - Dispersion, in time, of samples classification in clusters 1 or 2. ... 52
Figure 18 - Response of the most discriminative sensors to different solutions at the same concentration (50ppm). ... 54
xxi
List of Tables
Table 1- Severity of any spirometric abnormality based on the forced expiratory volume in one
second (FEV1). ... 6
Table 2- Schematization of current diagnosis of asthma. ... 7
Table 3- Summary of metabolomics analysis and identification of altered pathways found in asthma studies conducted in humans. ... 12
Table 4- Summary of exhaled VOC significantly different in asthma patients. ... 17
Table 5- Diagnostic decision matrix. ... 21
Table 6- Brief description of 4 types of sensors used in eNoses. ... 23
Table 7 - Cyranose 320® settings for exhaled breath analysis. ... 33
Table 8- Main characteristics of hexanal, hexane, decane, hexanoic acid, 1-octen-3ol and 2-dodecanol. ... 40
Table 9 - Interclass Mahalanobis distance between samples collecting with different filtering time (1, 2 and 5 minutes). ... 43
Table 10 - Cross validation results. ... 43
Table 11- Wilcoxon’s test results performed for each sensor (32 sensors) to compare 1 and 2 minutes of filtering time (1min vs 2min) and 2 and 5 minutes of filtering time (2min vs 5min)... 43
Table 12 - Participants’ characteristics. ... 44
Table 13 - Differences between the hierarchical model clusters according to participants’ clinical characteristics. ... 47
Table 14- Differences between the hierarchical model clusters according to CARAT questionnaire. ... 48
Table 15 - Differences between the hierarchical model clusters according to lung functions parameters. ... 48
Table 16 - Generalized linear models between hierarchical model clusters and control of respiratory symptoms using CARAT questionnaire (CARAT10 global score, CARAT asthma and CARAT rhinitis subscores; CARAT to assess rhinitis and asthma control – controlled/uncontrolled)... 50
Table 17 - Wilcoxon’s test results to evaluate differences in the response of all sensors in time. ... 52
Table 18 - Wilcoxon’s test results performed for each sensor (32 sensors) to compare sensors’ response in time (1 – first measurement; 2 - second measurement; 3- third measurement). ... 52
xxii Table 19 - Cross validation results. ... 53 Table 20 - Interclass Mahalanobis distance. ... 53
1
I.
Introduction
1. Asthma
1.1. Pathophysiology and Phenotypes
Asthma is a chronic inflammatory disorder of the airways leading to hyperresponsiveness, reversible airway obstruction, mucus hyper-production and airway wall remodelling being symptomatically characterized by wheeze, cough, chest tightness and shortness of breath.1,2 Despite similarities in clinical expression, asthma patients present a large range of underlying disease mechanisms and processes. Asthma affects 300 million people worldwide.3
Airway inflammation in allergic asthma can be caused by an imbalance between two opposite populations of T helper (Th) lymphocytes.4 Th1 cells produce interleukin-2 (IL-2) and interferon α (IFN-α) which are important in cellular defence mechanisms in response to infections. Th2 cells produce a group of cytokines including IL-4, IL-5, IL-9 and IL-13, which are responsible for mediate allergic inflammation. Generally, inhaled allergens stimulate Th2 cells proliferation and Th2 cytokines are released.5 Initially, allergen exposure leads to an increase of epithelial-derived thymic stromal lymphopoietin (TSLP), originated from the epithelium, stimulating mast cell activity and triggering maturation of dendritic cells and production of OX40 ligand.6 Allergens are taking up by dendritic cells, which are responsible for processing antigenic molecules and presenting them through the major histocompatibility complex II (MHCII) to naïve CD4+ T-cell receptors in lymph nodes.4
Subsequently, allergen-specific naïve CD4+ T-cells binds to OX40 ligand and differentiate into inflammatory Th2 cells leading to production of cytokines.6
IL-4 and IL-13 promote upregulation of adhesion molecules and eotaxin, which is a chemoattractant of eosinophils, and development of globet cell metaplasia which increases the secretion of gel-forming mucins.4,7,8 IL-4 and IL-13 also activate B-cells leading to
production of IgE. IL-5 is responsible for eosinophil growth, maturation, activation and survival.9 Eosinophils develop in the bone marrow from stem cells (CD34+) under the influence of IL-3 and IL-5, moving into the tissues due to IL-4 and IL-5.10 IL-9 is produced by Th-9 cells, which differentiate in response to IL-4 and TGF-β (transforming growth factor β), and promotes T cell proliferation, production of IgE by B-cells, survival and maturation of eosinophils and increase the number of mast cells.11 Eosinophils contain inflammatory
2
enzymes and generate leukotrienes, reactive oxygen species (ROS) and pro-inflammatory cytokines, worsening inflammation process and leading to airway remodelling and bronchoconstriction.1 Airway inflammation cause damage to epithelium. Then, damaged cells will be repaired in the injury-repair cycle and will produce profibrotic mediators like TGF-β, fibroblast growth factor and endothelin, inducing the release by fibroblasts and myofibroblasts of collagen, elastic fiber, proteoglycan and glycoprotein contributing to airway wall thickening.4 Mast cells release bronchoconstriction mediators like histamine and
prostaglandin D2 (PGD2) after IgE signalling.12 Airway hyperresponsiveness and
obstruction result of increased number of mast cells in airway smooth muscle. Further, endogenous production of ROS during inflammatory process plus exogenous ROS can lead to oxidative stress, propagating tissue injury and contributing to inflammatory and hypersensitive conditions.13 Celik et al showed asthma is related with increased levels of ROS, overwhelming defensive capacity of antioxidant system and leading to oxidative stress in the respiratory tract.14 Some of these events are schematized in Figure 1. In the absence of allergy, eosinophilic inflammation can occur in response to epithelial damage by inhaled
Figure 1 - T-cell immune response in asthma. DCs present allergen to naЇve T-cells, leading to the development of Th2 cells. Th2 cells produce and release cytokines which are responsible to stimulate allergic and eosinophilic inflammation. Response to pollutants and microbes can lead to non-allergic eosinophilic inflammation through action of ILC2 cells. NaЇve T-cells can also differentiate into Th17 cells which release IL-17 and IL-22 leading to neutrophilic inflammation. DCs, dendritic cells; IL, interleukin; ILC2, innate lymphoid type 2 cells; MHCII, major histocompatibility complex II; ROS, reactive oxygen species; TLSP, epithelial-derived thymic stromal lymphopoietin. Adapted from 1,4,5. Image built with Servier Medical Art (SMART).
3
pollutants and microbes.5 In this case, cytokines involved in early stages of the inflammatory process are IL-25, IL-33 and TSLP.15 IL-33 stimulates innate lymphoid type 2 cells (ILC2) leading to production of type 2 cytokines (IL-5 and IL-13).16 These cytokines will contribute to the maturation and survival of eosinophils and hyperproduction of mucus. ILC2 response can also be present in allergic eosinophilic inflammation.
Nowadays, another subset of CD4+ effector Th cells are known: Th17 cells.17 Th17 cells produce IL-17 and IL-22 that are responsible for neutrophils recruitment and development of airway hyperresponsiveness. Th17 cells are related with moderate and severe cases of asthma with neutrophilic inflammation.18 Th2 inflammation is related with steroid sensitive asthma (allergic asthma) and Th17 cells are mainly associated with non-eosinophilic inflammation and neutrophilic inflammation (steroid resistant asthma). Although Th17 cells can also be present in severe allergic asthma.4 IL-17A seems to induce steroid insensitivity in bronchial epithelial cells, but further investigation is required to achieve better understandings about non-steroid responsive asthma.18
The complexity and heterogeneity of the disease led Global Initiative of Asthma (GINA) to identify several phenotypes (Figure 2), being the most commons: allergic asthma, non-allergic asthma, late-onset asthma, asthma with fixed airflow limitation and asthma with obesity.19 Allergic asthma is the most common phenotype also known as atopic asthma described above as the result of Th2 response and, consequently, characterized by eosinophilic airway inflammation and well treatment response to inhaled corticosteroid (ICS) treatment. This phenotype often initiates in childhood and is associated with family history of allergic disease such as eczema, allergic rhinitis or food or drug allergy. Non-allergic asthma is not associated with allergy and sputum of patients may be neutrophilic, eosinophilic or contain only a few inflammatory cells (paucigranulocytic). These patients often respond less well to ICS treatment. Late-onset asthma phenotype typically appears later in life with higher degree of severity and it is more predominant in women, being treated with higher doses of ICS. Airway wall remodelling in patients with long-standing asthma can lead to development of fixed airflow limitation which is characteristic of asthma airflow limitation phenotype.20 Asthma with obesity can be present in some obese patients with
4
pharmacological treatment follows a stepwise approach and some asthmatics continue to suffer persistent symptoms and exacerbations which reinforces the importance of understanding the underlying mechanisms associated to each patient.5
There is not a definitive answer about what initiates inflammatory process and what makes some people more susceptible to its effect, but it is suggested that origin of asthma primarily occur early in life. Expression of asthma depends on the interplay between two major factors: host factors and environmental exposures that occur during development of
• Less well response to ICS • Weight loss improves
symptoms • Eosinophils
• Response to pollutants and microbes ( IL-25, IL-23, TSLP) stimulates ILC2 cells
• IL-5, PGD2 • Response to allergens ( TSLP)
• Th2 response • IL-4, IL-5, IL-13 • Eosinophilic
• Associated with atopy • Early onset (childhood) • Serum IgE
• PGD2
• Well treatment response to ICS
• Women
• Less well response to ICS
• Response to epithelial damage caused by pollutants and microbes
• Less well response to ICS
• Response to bacterial colonization, pollutants, oxidative stress
• Th17 response
• IL-17A, IL-17F, IL-22
• Few inflammatory cells • Neutrophilic
Asthma
Allergic Non-Allergic Eosinophilic Neutrophilic Paucigranulocytic With ObesityLate onset Others
Figure 2 – Heterogeneity of asthma and representation of main phenotypes according to GINA report (allergic, non-allergic, with obesity and late onset). Allergic asthma is typically characterized by atopy and eosinophilic inflammation. Non-allergic asthma can be segmented into eosinophilic, neutrophilic or paucigranulocytic inflammation. Late onset is more common to appear in women with high degree of severity and is typically neutrophilic. Obesity may influence asthma through numerous factors presenting a less degree of eosinophilic inflammation.19 ICS: inhaled corticosteroids; PGD2: prostaglandin 2; TSLP: thymic stromal lymphopoietin; IL: interleukin.
5
immune system.1 Evidence suggests asthmatics have an imbalance between Th1/Th2 responses, characterized by a shift towards Th2 cytokine-like disease. The “hygiene hypothesis” explains how this imbalance may justify the decrease number of asthmatics in non-industrialized countries.21 Following birth, environmental stimuli will activate Th1 responses and bring Th1/Th2 to an appropriate balance. However, absence of those stimuli is associated with persistence of Th2 cytokine pattern. Therefore, a person with a cytokine imbalance toward Th2 will set the stage to promote production of IgE antibodies to key environmental antigens and sensitization occurs. Exposure of children, who live on a farm, to different bacteria and fungi types showed a reduce prevalence of asthma when compared to children not living in a farm.22 Thus, the probability of develop asthma decreases with early exposure to diverse microbes which contributes to a rich microbiome. Still, the reason why some individuals are more susceptible to these allergic events has not been well-known and more studies are required.
Asthma is a heterogeneous inflammatory disease mainly triggered by Th2 cytokines. Cytokines are responsible for mediate allergic and non-allergic inflammation and for epithelial and smooth muscle changes causing bronchoconstriction and hyperresponsiveness, leading to asthma symptoms. Naïve T-cells can also differentiate into Th17 cells and stimulate neutrophilic inflammation which is not responsive to steroid treatment. Asthma pathogenesis is under discussion and is still unknown why some persons are more predisposing to develop the disease than others.
1.2. Diagnosis
To establish a diagnosis of asthma it is necessary to assess medical history, to perform a physical exam focus on the upper respiratory tract, to evaluate airflow obstruction reversibility by spirometry with reversibility challenge using a bronchodilator and, if necessary, to perform additional studies to exclude alternative diagnostics.23 However, due to heterogeneity of the disease, a gold standard diagnosis did not exist being probability-based according to the parameters described above.24
Clinical history includes symptoms identification likely to be due to asthma and family history of asthma and allergies assessment.2 Symptoms reported by asthmatics are: wheezing, history of cough especially at night, chest tightness, nocturnal awakenings and dyspnoea. Additionally, it should be obtained information about exacerbating triggers and environmental or occupational factors that can contribute for symptoms worsening (exercise,
6
smoke, house-dust mite, mould, pollen, animals with fur or hair, changes in weather, strong emotional expression and airborne chemicals or dust). The physical exam has focus on upper respiratory tract and evaluates: hyper expansion of the thorax; sounds of wheezing during normal breathing or during a prolonged phase of forced exhalation; increase of nasal secretion, mucosal swelling and/or nasal polyps; atopic dermatitis or other manifestation of an allergic skin condition. Physical findings and symptoms increase the probability of having asthma, but are not sufficient to diagnosis the disease. Absence of symptoms or physical findings doesn’t exclude diagnosis of asthma because this disease is variable and signs of airflow obstruction are often absenting between attacks.2
As symptoms are not sufficient to diagnosis asthma, it is necessary to perform a pulmonary function test (spirometry) to establish a more complete and objective diagnostic.23 Spirometry measures, among others parameters, the maximal volume of air forcibly exhaled as fast as possible (forced vital capacity, FVC); the volume of exhaled air in the first minute of this manoeuvre (forced expiratory volume in the first second, FEV1);
the maximal flow that can be exhaled during the manoeuvre (peak expiratory flow, PEF) and the forced expiratory flow at 25-75% of the pulmonary volume (FEF 25-75%).2 These measurements help to determine airflow obstruction, its severity and its reversibility, after salbutamol inhalation, in an objective way. Classification of the airway obstruction according to FEV1 is represented in Table 1.25 Reversibility criteria is an increase in FEV1 of at least 200 mL and 12% when compared to the baseline measurement, after inhalation of a short-acting bronchodilator (salbutamol 4x 100 µg is the most used). Degree of reversibility can be correlated with airway inflammation which can be measured by sputum eosinophilia and FeNO (fractional exhaled nitric oxide).2 Additional studies are not routinely necessary but may be useful to despite alternative diagnosis. This information is schematized in Table 2.
Table 1- Severity of any spirometric abnormality based on the forced expiratory volume in one second (FEV1) 25.
Degree of severity FEV1% predicted
Mild >70
Moderate 60-69 Moderately severe 50-59
Severe 35-49
7
Fractional exhaled nitric oxide (FeNO) is an indirect marker of eosinophilic airway inflammation. Nitric oxide (NO) is present in high levels in exhaled breath of asthmatics and its levels return to normal state after CS treatment.26 In exhaled air, NO seems to be originated from airway epithelium as a result of increased activity of nitric oxide synthase II (NOSII) during inflammation.27 NO synthase, in presence of oxygen and NADPH converts Table 2-Schematization of current diagnosis of asthma. Adapted from 2,23.
L-arginine into NO and L-citrulline.28 NOS protein is increased in airway epithelium cells of asthmatics and is activated and produced in response to cytokines, allowing large production of NO.27 Exhaled NO measurements are strong recommended in patients with asthma by American Thoracic Society (ATS).29 It is recommended to diagnosis eosinophilic airway inflammation, to determine the likelihood of steroid responsiveness in patients with chronic respiratory symptoms due to airway inflammation and to monitoring airway inflammation in asthmatics. Other inflammatory markers are IgE and sputum eosinophilia
Asthma Diagnosis 1. Clinical History 1. Symptoms:
▪ Wheezing;
▪ History of cough especially at night; ▪ Chest tightness;
▪ Nocturnal awakenings; ▪ Dyspnoea.
2. Family History
3. Possible exacerbating triggers: ▪ Exercise;
▪ Smoke;
▪ House-dust mite; ▪ Mould;
▪ Pollen;
▪ Animals with fur or hair; ▪ Changes in weather;
▪ Strong emotional expression;
▪ Airborne chemicals or dust. 2. Physical Exam
To evaluate: ▪ Hyper expansion of the thorax;
▪ Sounds of wheezing;
▪ Increased nasal secretion, mucosal swelling and/or nasal polyps; ▪ Atopic dermatitis or other manifestation of an allergic skin condition.
3. Pulmonary Function Test
Spirometry with reversibility test Reversibility criteria:
Increase of FEV1 >200 mL and ≥12%, after inhalation of a short-acting bronchodilator. 4. Additional tests if necessary
8
and can also be used to assess inflammation.19 Association between asthma and allergy is also recognize and it is usual to use skin testing to determine sensibility to some commons allergens.19 This test is important to identify triggers and sensitized patients should avoid exposure to those specific allergens, preventing acute exacerbations.
After diagnosis, patients should be followed to evaluate the level of asthma control and treatment efficacy. Asthma control is achieved when asthma manifestations have been reduced or removed by treatment.19 Thus, symptom control and future risk of adverse
outcomes should be assessed. Lung function, especially FEV1, is an important part of the assessment of future risk.30 A low FEV1 identify patients at risk of asthma exacerbations especially if FEV1 is under 60%. Significant bronchodilator reversibility in a patient taking controller treatment also suggests poor asthma control. In children, spirometry is not reliable until 5 years old or more and children with uncontrolled asthma have normal lung function between acute exacerbations.19 The physician can also use validated questionnaires to evaluate level of control of the disease. CARAT, CARAT Kid, ACT and ACQ are examples of those questionnaires. It is also important to assess asthma severity when the patient has been on regular controller treatment for several months. Mild asthma is well controlled with reliever medication alone or with low intensity controller treatment such as low doses of ICS or leukotriene receptor antagonists (LTRA). Moderate asthma is well controlled with low doses of ICS/LABA (long-acting β2-agonist). Severe asthma requires higher doses of
ICS/LABA or it remains uncontrolled despite this treatment (steroid resistant).19
Diagnosis of asthma is a challenge for clinicians because of its heterogeneity and symptoms plus examination can lead to other lung diseases. Still, spirometry with reversibility test can provide an objective measurement of airway obstruction (reversible in patients with asthma) but requires a good collaboration of the patient and normal values don’t exclude the diagnosis of asthma.24 Spirometry only allows to measure volumes and to
evaluate the severity of the obstruction and bronchodilator reversibility sometimes overlaps in health and disease.31 The absence of an ideal diagnostic test, difficulty in the evaluation
of pulmonary function tests and heterogeneity of the disease leads clinicians to conduct a trial-of-treatment approach with inhaled CS.32 Thus, it is necessary to explore other methods,
9 1.3. Altered metabolic pathways
Metabolomics provides biochemical profiles of endogenous metabolites in biological systems and allows the development of novel biomarkers and improvement of pathophysiology understandings. Urine, exhaled breath condensate (EBC), plasma, serum and bronchoalveolar lavage fluid (BALF) can be used to identify the metabolomic profile of asthma patients.33,34 Abnormal metabolic activity is primarily localized in the lung and respiratory tract, however impaired lung function can lead to systemic metabolic alterations.35 Several circulating metabolites in asthmatics are different from those in healthy individuals. Mass spectrometry (MS) and nuclear magnetic resonance spectroscopy (NMR) are the main techniques used to achieve these discoveries.33
Metabolomic studies reveal some altered pathways associated with asthma including changes in the amino acid metabolism, oxidative stress and hypoxia, lipid metabolism, cellular energy homeostasis and immune and inflammatory pathways.36–38 Some of these altered pathways are schematized in Figure 3. Metabolites involved in tricarboxylic acid (TCA) cycle are increased in asthmatics which reflects the increase of energetic burden in this population due inflammation, bronchoconstriction and hyperresponsiveness of the airways. These metabolites were found in urine and serum of asthmatics and succinate was the most consistent between studies.35,36,39 Fumarate, oxaloacetate, cis-aconitate and
2-oxoglutarate were also found higher in asthmatics who had recently suffered an exacerbation.39 TCA cycle changes can also be resultant of hypoxic stress due to poor
oxygenation, especially during an exacerbation.36 This alteration is supported by presence
of high levels of lactate and low levels of glucose. Additionally, inosine, a breakdown product of adenosine, was increased in asthmatics and is capable of penetrate in cells and enhance activity of pyruvate oxidase and other enzymes, facilitating cell metabolism under hypoxic stress during poor oxygenation.35
Lipid metabolism is enriched in asthmatics since they drive inflammatory responses, promote release of histamine and are essential to cellular energy metabolism.36 The presence of LDL, VLDL and its hydrolysis products have been found to activate the release of histamine which promotes bronchoconstriction of airway muscles.40 Since energetic burden is increased, which leads to low levels of glucose, lipids can be used to provide acetyl-CoA. Breakdown of lipids under insufficient glucose leads to production of acetone which was found in high levels in serum of patients.36 However, low levels of acetone were found in a
10
different study conducted in children with asthma and until now is a compound with no concordance between studies.41 Active inflammatory cells in the airways release ROS, leading to oxidative stress and creation of favourable conditions to occur lipid peroxidation of polyunsaturated fatty acids (PUFAs) from cells, reducing the ability of epithelium to repair damage.36,37 The metabolites resultant of lipid peroxidation are mainly hydrocarbons
including hexane, heptane, pentanal, heptanal, decanal, octane, nonadecane, 4-methylheptane, 2,4-dimethylheptane 2,4-dimethylpentane, 2-methylpentane and other alkanes and aldehydes.37,41 These metabolites and pathway are specified in subchapter 1.5
of the introduction chapter. Levels of phosphocholine were decreased in the serum of patients which can indicate a lack of protection of airways since it is an important component of endothelial cell barrier.36 Still related with lipid metabolism, increased levels of carnitine and acetyl-carnitine were found in urine headspace of asthmatics during exacerbation, which reveals an increase of oxidative burden since these metabolites are essential to transport fatty acids into mitochondria for oxidation.42
TCA cycle Oxaloacetate Cis-aconitate α-ketoglutarate Succinate Fumarate Acetyl-CoA Pyruvate Lactate Pyruvate oxidase Glucose Glycogen ATP Adenosine Inosine +
Altered Energy Metabolism
Histidine Histamine
Glutamine, Asparagine, Leucine, Valine, Alanine, Arginine
Taurine Arachidonate Bile acids (cholate, glycocholated, glycodeoxycholate, taurocholate) release
Altered Aminoacids Metabolism
LTB4 Fatty Acids Triacylglycerides LDL, VLDL PUFAs Hydrocarbons
Altered Lipid Metabolism
Figure 3 – Representation of some altered metabolic pathways in asthma linked to cellular energy, lipid and amino acid metabolism.36, 38-39, 41, 46 ATP, adenosine triphosphate; LDL, low-density lipoprotein; LTB4, leukotriene B4; PUFA’s, polyunsaturated fatty acids; ROS, reactive oxygen species; TCA cycle, tricarboxylic acid cycle; VLDL, very-low-density lipoprotein.
11
Amino acid metabolism is also altered in asthmatics.38 Some amino acids appear to be in higher levels compared with healthy controls and others in lower levels. Glutamine, asparagine, leucine, valine, alanine and arginine were found in low levels in serum and phenylalanine, methionine, histidine and taurine were upregulated.35,36,38 Histidine is a precursor of histamine, which is an important protein involved in inflammatory process and bronchoconstriction of muscles.36 Histamine and 1-methylhistamine, a downstream metabolite were found in high levels in urine of asthmatics.39 Methionine is an important
donor of methyl groups and is converted into its active form (S-adenosylmethionine) by methionine adenosyltransferase. In asthma, methylation was associated with arginine residues being arginine methylation a positive inducer of cytokine gene activation and signalling.43 High taurine levels were also found in asthmatics’ plasma and it is released by cells when taurine-releasing pathways are activated by arachidonic acid oxidation via 5-lipoxygenase to leukotrienes, independently of disease severity.38 Arachidonate, an inflammatory biomarker and precursor of leukotrienes, was found high in plasma of asthma subjects and had a positive correlation with taurine levels, highlighting the relation between oxidation of arachidonic acid and release of taurine. Taurine levels were also positively associated with an increase of bile acids production (cholate, glycocholate, glycodeoxycholate, taurocholate and lathosterol, an intermediate) being the major metabolic pathway of its elimination.38 Nitrogen metabolism was also found altered in serum of asthmatics that showed low levels of ornithine, citrulline, arginine and formate suggesting alterations in urea cycle (important pathway in the excretion of ammonia resultant of amino acids catabolism).35,36 Sinha et al detected low levels of ammonia in the EBC of asthmatics and connected the finding to low levels of glutaminase activity possibly indicating alterations in glutamate-glutamine cycle.44 Glutaminase is responsible for generate glutamate and ammonia from glutamine. This hypothesis is reinforced by Jung et al that found increase levels of glutamine and glutamate in serum of patients.36
Differences in other compounds related with immune and inflammatory processes were found in the urine of patients.45 Urocanic acid is an intermediate of histidine catabolism
and a potent immune-suppressor. This compound was found in low levels in the urine of patients contributing to poor resolution of the inflammatory process. Nicotinamide, adenosine monophosphate and arachidonate are inflammatory markers and were found in high levels in plasma of asthmatics as expected since this is an inflammatory disease.38 These
12
compounds were found in mild and severe cases of asthma. Taurocholate was additionally found in severe cases of asthma and is associated with synthesis of taurine.38 In addition, a study conducted in children showed high levels of leukotriene B4 (LTB4) in exhaled breath condensate (EBC) of atopic asthmatics not taking corticosteroid therapy compared with healthy children, atopic non-asthmatic children and children with asthma taking ICS.46 LTB4
is a potent inflammatory lipid mediator and a chemoattractant of neutrophils, contributing to the pathophysiology of asthma and is synthetized from arachidonic acid via 5-lipoxygenase.47 Finally, steroid metabolism was found altered in severe asthmatics with the
identification of low levels of steroids (1-stearoylglycerol, dehydroisoandrosterone sulphate, androsterone sulphate, epi-androsterone sulphate).38 Severe asthma patients may experience suppression of adrenal steroids due to its therapy which includes taking high doses of inhaled corticosteroid. Many of the others metabolomic pathways described above are shared between severe and non-severe asthmatics.
In summary, asthma is associated with abnormalities in TCA cycle, hypoxia metabolism, lipid and amino acid metabolism due to the effort to breathe and presence of hypoxic stress due to poor oxygenation. The pathways and metabolites altered in asthma and explained in this chapter are summarised in the Table 3.
Table 3-Summary of metabolomics analysis and identification of altered pathways found in asthma studies conducted in humans.
Cellular pathway
Altered metabolites
Biofluid Methods
High levels Low levels
Cellular energy homeostasis and hypoxia
Succinate 35,36, inosine 35,
lactate 36 Glucose 36 Serum
GC-MS 35, NMR 36 Fumarate, oxaloacetate, cis-aconitate and 2-oxoglutarate 39 - Urine NMR 39 Lipid metabolism VLDL and hydrolysis products, acetone 36 Phosphocholine 36, choline 36 Serum NMR 36 Carnitine, acetyl-carnitine 39,42 - Urine NMR 39,42 Lipid peroxidation and Oxidative stress 2,4-dimethylpentane, 2,4-dimethylheptane, 2-undecenal, octane, 2-methylpentane, 2-methylhexane 41 Acetone, 2,2,4-trimethylheptane, 2,3,6-trimethyloctane 41 Exhaled breath GC-MS 41 Hexane, heptane,
pentanal, heptanal, - Urine
GCxGC-ToFMS 37
13 decanal, octane,
nonadecane, 4-methylheptane, 2,4-dimethylheptane and other alkanes and aldehydes 37 Amino acid metabolism Phenylalanine 35, histidine 36, glutamine 36, methionine 36, glutamate 36, glycine 36 Glutamine 35, asparagine 35, arginine 36, leucine 36, valine 36, alanine 36, isoleucine 36 Serum GC-MS 35, NMR 36
Alanine, threonine 42 - Urine NMR 42
Taurine 38 - Plasma GC-MS 38 Immune and inflammatory processes Histamine 39, 1-methylhistamine 39, nicotinamide 39
Urocanic acid 45 Urine NMR39, LC-MS 45 Nicotinamide 38, adenosine monophosphate 38, arachidonate 38 - Plasma GC-MS 38 LTB4 (leukotriene B4) 46 - EBC LC-MS 46 Steroid Metabolism - Urocortisone 45, urocortisol 45 Urine LC-MS 45 - 1-stearoylglycerol, dehydroisoandrosterone sulphate, androsterone sulphate, epi-androsterone sulfate 38 Plasma GC-MS 38 Nitrogen Metabolism - Ornithine 35, citrulline
35, formate 36, arginine 36 Serum
GC-MS 35, NMR 36 Glutamate-glutamine metabolism - Ammonia 44 EBC NMR 44
Glutamate, glutamine 36 - Serum NMR 36
Bile acid production pathway Taurine, lathosterol, cholate, glycocholate, glycodeoxycholate, taurocholate 38 - Plasma GC-MS 38 Methyl transfer pathway Methionine 36 Formate, choline, phosphocholine, arginine 36 Serum NMR 36
1.4. Exhaled breath analysis and its potential as a diagnostic tool
Biochemical and biomolecular diagnostic methods used in medicine have their focus on blood and urine analysis. Breath analysis could be an addiction to these currently analysis to help clinicians since it is a non-invasive sampling technique, painless and that can be
14
easily realized by sick patients, including children and elderly persons.48 Therefore, breath analysis is a promising approach that can be performed in either gaseous phase (exhaled breath) or liquid phase (exhaled breath condensate - EBC), to detect volatile organic compounds or non-volatile organic compounds, respectively.
The classic gases found in exhaled breath are nitrogen (78%), oxygen (16%), carbon dioxide (4.5%) and water vapor.49 But there are more substances that can be found in a small fraction of exhaled breath. Pauling et al could discriminate 250 compounds in exhaled breath based on gas-liquid partition chromatography analysis.50 Thus, exhaled breath includes small
inorganic compounds like NO, O2 and CO2 and volatile organic compounds (VOC) like
alkanes, ketones, alcohols, aldehydes and esters; and non-volatile compounds comprising isoprostanes, cytokines, leukotrienes and hydrogen peroxide.51
Hippocrates described an odour of fetor hepaticus as a clinical marker which is now
related with hepatic diseases.52 The compounds related with that smell were later discover by GC-MS. Breath of patients with hepatic problems showed high levels of dimethyl sulphide, acetone, 2-butanone and 2-pentanone and decreased levels of indole and dimethyl selenide.52 Emission of acetone in the breath was also soon related with diabetes problems.53 Therefore, the sense of smell as a diagnostic tool has a long history.
Nowadays, there are some approved breath tests for nitric oxide determination and ethanol and acetaldehyde measurements.54,55 Nitric oxide determination is commonly use to assess airway inflammation and its application has been propose to monitor the response to medication in asthmatics and to predict asthma exacerbations.54 Ethanol and acetaldehyde determination is normally used to evaluate alcohol consumption.55 There are other compounds that can be used to recognize certain diseases. However, it is necessary to know their generation, origin, distribution, biochemical pathways in which they are involved and find a standardised sampling and detection method to make possible its clinical application.56
In short, breath air is composed by hundreds of compounds and in some diseases, breath air can be altered compared to normal healthy subjects, being possible to diagnosis some conditions. This concept is known since the description of fetor hepaticus by
Hippocrates. However, only a few breath tests to detect single compounds are used with
15 1.5. Exhaled breath and potential biomarkers
There is an increased interest to evaluate exhaled volatile organic compounds (VOC) as biomarkers of asthma because collecting breath is a simple, inexpensive and non-invasive methodology which is also easy to perform in sick patients, children and elderly people. However, gas sampling has some disadvantages like presence of exogenous VOC, making this analysis a challenge.
To recognise the potential of exhaled VOC as biomarkers, it is important to understand their origin and how they are related to pathological events. VOC are carbon-based compounds which are volatile at room temperature, “means any compound of carbon
that has a vapor pressure greater than 0.1 millimetres of mercury at standard conditions excluding carbon monoxide, carbon dioxide, carbonic acid, metallic carbides or carbonates, and ammonium carbonates”.57 Their presence in exhaled breath can be endogenous (directly produced by the host organism) or exogenous. Exogenous compounds can arise from microbiota, medication, diet, ambient air and other sources of xenobiotics.58–60 Obesity is also a factor that can influence the composition of the exhaled breath.61 Consequently, determination of the origin of VOC in exhaled breath can be a challenge. Understand biochemical pathways giving rise to each VOC is important to obtain reliable biomarkers and accurate diagnostic tests. Endogenous exhaled VOC arise from lungs, airways, nasal cavity and systemic circulation being exhaled after diffusion from blood to the alveoli.62 Physiological and pathological events can lead to VOC production which in turn enter in bloodstream being excreted in the exhaled breath.
The most promising VOC biomarkers to diagnosis asthma belong to alkanes family being the most studied compounds in this disease.63,64 These compounds, cited in more than
one study, include ethane 65,66, 2,4-dimethylheptane 41,67,68, 2,6,11-trimethyl dodecane 67,69, decane 63,70, dodecane 63,70, tetradecane 63,70, octane 41,68, 2-methylhexane 41,68 and 1,2-dimethylcyclohexane 71,72. Table 4 shows the compounds mentioned above and others that were identified as significantly decrease or increase in the exhaled breath of asthmatics. Pentane and ethane were the primarily discovered biomarkers of asthma and are in high levels in breath.65,73 Nowadays, these compounds are mostly associated with disease severity once they are present at higher concentrations in patients with severe asthma. Acetic acid
67,74, butanoic acid 72,74,75, isoprene 67,70 and 2-butanone 69,74 were significantly increase in
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compounds identified as possible markers that can be caused by variances in the methodology, breath sampling procedures, exposition to different environments and, consequently, exposition to different exogenous VOC. Compounds like 4-methyloctane 67,70, nonanal 63,71, 2,4-dimethylpentane 41,68, 2-undecenal 41,68, 2-methylpentane 41,68 and 2,3,6-trimethyloctane 41,68 and acetone 41,67,68,70 were found upregulated or downregulated in
different studies. Van Vliet et al found increased levels of 2-methylfuran and 3-methylfuran in exhaled breath of asthmatic children being these compounds associated with smoke exposure.71,72 A study conducted by Van Berkel et al identified differences in the exhaled
breath of healthy controls and smokers.76 Four VOC were significantly increase in smokers’ breath including 2,5-dimethyl hexane, dodecane, 2,5-dimethylfuran and 2-methylfuran.
Table 4 summarise exhaled VOC significantly increase or decrease in asthmatics.
Changes in VOC profile of asthmatics are mainly related with chronic airway inflammation and oxidative stress.13 Reactive oxygen species (ROS) are increased in asthmatics and can promote degradation of polyunsaturated fatty acids (PUFA) present in lipidic structures, like bronchial epithelium cell membrane, leading to formation of volatile hydrocarbons (Figure 4).77 Lipid peroxidation is a metabolic process in which ROS induce oxidative deterioration of lipids, especially PUFA since methylene groups are present and these groups contain hydrogen particularly reactive to ROS.78 Membrane lipids
ROS Alkanes, aldehydes CYP450 Alkanes Alcohols Inflammatory cells
Figure 4 – Oxidative stress induces lipid peroxidation of PUFA from cellular membranes leading to formation of hydrocarbons that can be excreted in exhaled breath or be further metabolized by CYP450 enzymes to alcohols. These compounds can enter in blood system and be excreted in the exhaled breath. CYP450: Cytochrome P450; PUFA: polyunsaturated fatty acis. Adapted from.76 Image built with Servier Medical Art (SMART).
17
peroxidation, like linoleic acid and linolenic acid, induce formation of volatile alkanes like pentane.79 Lipid peroxidation can be initiated by hydroxyl radical (HO•) which abstracts a
hydrogen from PUFA, leading to a carbon centred radical which reacts with oxygen forming a peroxide radical. Peroxide radical can gain a hydrogen from another PUFA molecule (reinitiation), forming a hydroperoxide which, in the presence of iron, is converted into alkoxyl radical. In case of linoleic acid, this alkoxyl radical is degraded into an aldehyde and a pentanyl radical. Pentanyl radical gains a hydrogen from other molecule and forms pentane. These compounds are locally released in airways or entered in bloodstream being further oxidized into alcohols by hepatic cytochrome p450 enzymes and excreted in exhaled air.80 Methylated hydrocarbons and aldehydes found in exhaled breath can also be originated
by lipid peroxidation.81 There are other minor sources of hydrocarbons like protein oxidation and bacterial metabolism.77 The source of other compounds is still unknown or not well elucidated yet.
Breath differences between asthmatics and controls are recognised by several studies. However, there is not a consensus of which compounds are increased or decreased and its origin. Nevertheless, it is necessary to pay attention between studies showing dissimilar results due to differences in sampling and analysis methods. Main VOC contributing to these results are alkanes. The origin of alkanes is mainly associated with oxidative stress that induce lipid peroxidation. Alkanes and other VOC can be excreted in the exhaled breath.
Table 4-Summary of exhaled VOC significantly different in asthma patients’ breath.
Ref. Method VOCS Study population
Increase Decrease
73
GC-FID Pentane - 12 acute asthmatics, 11
stable asthmatics, 17 healthy controls
65
GC-FID Ethane - 26 asthmatics (14 on
steroid treatment, 9 with severe asthma, 5 with moderate asthma), 14 controls
66 GC-FID Ethane Isoprene 13 stable asthmatics, 14
healthy controls
67
GC-MS Isoprene, acetone, toluene, acetic acid, 4-methyloctane, 2,4-dimethylheptane, isopropanol, 2,6,11-trimethyl dodecane, 3,7-dimethyl - 20 asthmatics, 20 controls
18 undecane, 2,3-dimethyl heptane 75 GC-MS 1,1’:3’,1’’-Ter(cyclopentane), butanoic acid, 3-(1-methylethyl)-benzene, benzoic acid, tridecane
1-pent-2-one, p-xylene, undecane 63 asthmatic children, 57 healthy controls 70 HS- SPME/GC-qMS 2,2-dimethylhexane, 2,3,6-trimethyldecane, 2,4-dimethyloctane, decane, dodecane, tetradecane, isoprene 2,4-dimethylheptane, 4-methyloctane, acetone
35 children with allergic asthma, 15 healthy controls
69
GC-MS Terpinolene, ethyl 2,2-dimethylacetoacetate, allyl methyl sulphide, 3,4-dihydroxybenzonitrile, 2-butanone, benzyl alcohol, 2,6,11-trimethyldodecane Ethyl 4-nitrobenzoate, 2,6- di-tert-butylquinone, 4-ethyl-o-xylene, 5,5-dibutylnonane, pentadecanal, 2-butylcyclohexanol 35 asthmatics, 23 healthy controls 63 GCxGC-ToFMS Nonane, 2,2,4,6,6-pentamethylheptane, decane, 3,6-dimethyldecane, dodecane, tetradecane 6-methyl-5-hepte-2-one, 1-dodecene, nonanal, decanal, dodecanal
32 children with allergic asthma, 26 healthy control children 82 GC-MS 1-(methylsulfanyl) propane, ethylbenzene, 1,4-dichlorobenzene, 4- isopropenyl-1-methylcyclohexene, 2-octenal, octadecyne, 1- isopropyl-3-methylbenzene, 1,7-dimethylnaphtalene - 11 asthmatics, 12 healthy controls 41 GC-MS 2,4-dimethylpentane, 2,4-dimethylheptane, 2-undecenal, octane, 2-methylpentane, 2-methylhexane Acetone, 2,2,4-trimethylheptane, 1-methyl-4-(1-methylethenyl) cyclohexen, 2,3,6-trimethyloctane, biphenyl, 2-ethenylnaphtalene, 2,6,10-trimethyldodecane
76 children with asthma, 121 children with transient wheezing, 50 controls 71 GC-TOF/MS 1,2-dimethylcyclohexane, 2-ethylhexanal, octanal, 6,10- dimethyl-5,9-undecadien-2-one, nonanal,
19 methylfuran 74 Quantum cascade laser spectroscopy
Acetic acid, butyl ester, ethyl acetate, isobutyl acetate, isopropyl ester, methyl acetate, butanoic acid, 2-butanone, butyric acid, dimethyl carbonate, dimethyl ether, 1hydroxy-3-methylbenzene, propanol, propanoic acid, methanoic acid
- 39 asthmatics children, 35 healthy children 68 GC-TOF/MS Octane, 2-methylhexane, 2,3,6-trimethyloctane, 2,4-dimethylheptane Acetone, 2,6,10-trimethyldodecane, 2,4-dimethylpentane, 2-undecenal, 2-methylpentane 76 asthmatic children, 122 transient wheezing 83 GC-TOF/MS 2-ethyl-1,3-butadiene, cyclohexane, 2-octen-1-ol, 1,2-methyl-4H-1,3-benzoxathiine, benzene - 38 asthmatic children 72 GC-TOF/MS Sulphur dioxide, 3-methylfuran, 2-methylfuran, 2,4-hexadiene, butanoic acid, 1,2-dimethylcyclohexane, tetrachloroethylene, dimethyl sulfone, isopropyl toluene, propyl cyclohexane
- 34 children with controlled asthma, 9 children with uncontrolled asthma
2. Electronic Noses for Clinical Applications
2.1. Clinical evaluation of diagnostic devicesA medical device is, according to WHO, any instrument, apparatus or machine that
is used in the prevention, diagnosis or treatment of illness or disease, or for detecting, measuring, restoring, correcting or modifying the structure or function of the body for some health purpose that is not achieved by pharmacological, immunological or metabolic means.84 Medical devices are classified into class I, II or III according to the risk for users,
20
trials focus on prototype development, being an iterative process since devices can be improved and optimized.86
In general, first exploratory studies are pilot and proof-of-concept studies performed in a small population of healthy volunteers and patients with a confirmed disease to obtain preliminary information on technical, safety and diagnostic performance.86 In confirmatory
trials, patients and clinical setting should be representative of the population in which diagnostic agent is intended to be used. Patients included in this phase are: asymptomatic, patients with suspected but not confirmed disease, patients with a confirmed disease, patients undergoing treatment, previously treated patients and patients with a confirmed recurrence. Larger populations are required to determine effectiveness and adverse effects. After device’s approval, post-approval studies are used to collect long-term data and adverse effects. For a new indication, primary endpoints should include diagnostic performance (sensitivity and specificity), predictive values, likelihood ratios, evaluation of prognosis, impact on diagnostic thinking and impact on patient management or on clinical outcome. Sensitivity represents the ability of a test to detect the condition when it is truly present (probability of a positive result in a patient with the condition) and specificity is the ability to exclude the condition in patients who do not have it (probability of a negative result in a patient without the condition).87 Receiving operator curve (ROC) is a graphical representation of the relationship between sensitivity (true positive) and 1-specificity (false positive) of a diagnostic test and is considered to be a mean for selecting appropriate cut-off point to be used prospectively in confirmatory trials. In clinical practice, it is important to know how good the test is at predicting the true positives. Positive predictive value (PPV) is the probability of a subject to have the condition given that test result is positive and negative predictive value (NPV) is the probability of a subject to not have the condition given that the test result is negative (Table 5).86 Predictive values must be reported cautiously as these values are dependent on the prevalence of the condition in the population. Thus, validation of a new diagnostic test should be performed in the setting of the diagnostic work-up where is intended to be used providing predictive values for that population. Finally, likelihood ratio (LR) is the likelihood that a given test result would be expected in a subject with the condition compared to the likelihood that same result would be expected in a subject without the condition. Positive LR refers to LR in case of positive test (calculated by Sensitivity/(1-specificity)) and negative LR refers to LR in case of negative test ((1-sensitivity)/specificity).
21
Impact on diagnosis thinking is presented numerically by the rate where diagnostic uncertainty with the new agent has decreased as compared to pre-test diagnosis and may influence patient management.86 Impact on patient management should be assessed prospectively by using adequate questionnaires and quantified by the rate of change in patient pre- and post-test. A search performed at clinical trials database (clinicaltrials.gov) using the term “electronic nose” resulted in 46 studies registered being 15 already completed, mainly case-control or proof-of-concept studies covering several diseases, including respiratory diseases (asthma, COPD, tuberculosis, aspergillosis, sinusitis, and cystic fibrosis), multiple sclerosis and some types of cancer.
Table 5- Diagnostic decision matrix.
Test Result Disease Total
Present Absent
Positive A (TP) B (FP) A+B
Negative C (FN) D (TN) C+D
Total A+C B+D
TP: true positive; FP: false positive; FN: false negative; TN: true negative. Positive predictive value (PPV)= A/(A+B); Negative predictive value (NPV)= D/(C+D). Sensitivity=A/(A+C); Specificity=D/(B+D).
2.2. Electronic olfactory system
Electronic nose or eNose is “an instrument which comprises an array of electronic
chemical sensors with partial specificity and an appropriate patter-recognition system, capable of recognising simple or complex odours” (1994).88 Primary works on the development of an instrument to detect odours dates the early-1960’s.89–91 However, the term electronic nose only appeared in 1987, at the 8th International Congress of European chemoreception research.92 This device mimics mammalian olfactory system, which is composed by a hundred million odour transducers.93 Odour transducers act as primary neurons, then secondary neurons conduct and amplify signals to the olfactory bulb that diffuse information to the brain.94 The brain is responsible for applying methods of pattern recognition to identify, classify and quantify the odour of interest. As odour transducers widely overlapping specificity of interaction onto different volatile compounds, brain interprets an odour as a complex pattern of responses.93 Identification of different odours is a result from a comparison between the incoming odour pattern with patterns previously learnt. Based on this principle, the main components of an electronic nose are: a sensor array, a feature extractor and a pattern recognition system. There are differences between devices
