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Acid-base equilibrium in exhaled breath condensate of grain elevator workers Do, Ron 2006

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A C I D - B A S E E Q U I L I B R I U M I N E X H A L E D B R E A T H C O N D E N S A T E O F G R A I N E L E V A T O R W O R K E R S by R O N D O B . S c , University of British Columbia, 2003 A T H E S I S S U B M I T T E D I N P A R T I A L F U L F I L L M E N T O F T H E R E Q U I R E M E N T S F O R T H E D E G R E E O F M A S T E R O F S C I E N C E in T H E F A C U L T Y O F G R A D U A T E S T U D I E S (Experimental Medicine Program) T H E U N I V E R S I T Y OF B R I T I S H C O L U M B I A December 2005 © Ron Do, 2005 ABSTRACT Introduction: Workers in the grain industry have been reported to have adverse respiratory symptoms, primarily due to occupational exposure to grain dust. Exhaled breath condensate ( E B C ) may be a viable method in field studies to sample secretions of the lower airways. It is suggested that these secretions can predict inflammatory responses to inhaled irritants, such as grain dust. Studies have reported that the acid-base equilibrium in E B C varies with the severity o f airway inflammation. The purpose of the present study was to measure E B C p H and ammonium to assess the acid-base equilibrium of the airways in grain elevator workers. Methods: E B C collection was performed using commercially available equipment. Methodological issues pertaining to the collection, storage, and analysis of E B C were evaluated to produce a standard procedure suitable for our laboratory. The field component consisted of sampling E B C from workers employed at terminal elevators in the port of Vancouver. In addition, personal exposure monitoring to inhalable grain dust and endotoxin, completion of a respiratory questionnaire, spirometry and allergy testing were also performed, as part of a larger cross-sectional grain study. Results: 76 workers participated. E B C p H values varied from 4.3 to 8.2 (median: 7.94); ammonium values from 22 to 2384 u M (median: 420.4). Geometric mean dust and endotoxin levels were: 0.9 mg/m3 (GSD: 4.0) and 435 EU/m3 (GSD: 4.9) respectively. p H and ammonium were moderately correlated (1=0.53). Multivariable analysis showed that p H was lower in association with current smoking intensity and obesity, yet higher in current atopics. Lower p H was associated with duration of exposure on the study day before E B C collection and with working in one work area (seed/pellet plant), but not with measured grain dust or endotoxin exposure concentration. Lower ammonium was associated with chronic smoking intensity, duration of exposure on the study day, years of employment in the industry, and working in the seed/pellet plant; but significantly higher in association with grain dust measured on the study day. Conclusion: The collection of E B C is feasible in field studies. E B C p H and ammonium may be useful to measure airway inflammation related to acute and chronic occupational exposures. i i i TABLE OF CONTENTS Abstract " Table of Contents i" List of Tables vii List of Figures ix Acknowledgements xi Chapter 1. Introduction 1 1.1 Overview 1 1.2 Objectives 2 Chapter 2: Background 3 2.1 Grain dust 3 2.1.1 Source, composition, and physical characteristics 3 2.2 Endotoxin 4 2.3 Host defense systems 4 2.3.1 Physical host defense systems: Physical barriers, mucociliary system 4 2.3.2 Biological host defense systems: Immune system 4 2.4 Respiratory health effects of grain dust exposure: Epidemiological studies 5 2.5 Impact of endotoxin on respiratory health -Epidemiological studies 7 2.6 Grain dust, endotoxin, and airway inflammation -Laboratory studies 7 2.6.1 In vitro studies 7 2.6.2 In vivo studies 8 2.7 Measurement of airway inflammation 9 2.8 Traditional methods of sampling secretions from the lower respiratory tract 9 2.9 Exhaled breath condensate: A new method of sampling secretions from the lower respiratory tract 10 2.9.1 Introduction 10 2.9.2 Collection and collection devices 10 2.9.3 Origins of respiratory droplets 11 2.9.4 Mechanisms of aerosolization..' 11 2.9.5 Composition 12 2.10 Methodological considerations for E B C . 12 2.10.1 Duration and temperature of condensation 13 2.10.2 Dilution and concentration of respiratory solutes 13 2.10.3 Oral contamination 14 2.10.4 Nasal/oral inhalation, use of noseclips 14 2.11 Exhaled breath condensate studies of other markers of iv airway inflammation (excluding markers of acid-base equilibrium) 15 2.11.1 Cl inical studies 15 2.11.2 Occupational and environmental studies 20 2.12 Acid-base equilibrium in exhaled breath condensate 21 2.13 Methodological considerations 22 2.13.1 Gas standardisation of p H 22 2.13.2 Oral contamination of ammonia 22 2.14 Relevant studies investigating acid-base equilibrium of the airways 23 2.14.1 Organic dust and airway acidification 23 2.14.2 p H 23 2.14.3 Ammonia/Ammonium 24 2.14.4 Mechanisms of acid-base equilibrium. 24 2.15 Conclusion 25 Chapter 3: Method Development and Evaluation 26 3.1 Overview 26 3.2 Objectives 26 3.3 Participation and confidentiality. 26 3.4 Methods 27 3.5 Exhaled breath condensate collection 27 3.6 Protocol development and assessment 28 3.7 Exhaled breath condensate collection procedure 29 3.8 Argon deaeration procedure 30 3.9 p H measurement procedure 30 3.10 N H / analysis procedure 31 3.11 Evaluation of the standard procedure, evaluation of the within- and between-person variability 31 3.12 Comparison of two different sample storage methods 31 3.12.1 Method A (measuring p H prior to initial sample freezing) 32 3.12.2 Method B (measuring p H after freezing sample for 8 hours) 32 3.13 Data analysis 32 3.14 Results '..33 3.15 Participation '. 33 3.16 Method development and assessment 33 3.17 Effect of sampling time on sample volume 33 3.18 Effect of cooling sleeve temperature on sample volume 34 3.19 Reproducibility of p H measurements 34 3.20 Correlation of p H and N H 4 + 34 3.21 Effect o f condenser temperature on p H and lnNH4+ 35 3.22 Effect of the use of a filter on E B C p H and l n N H 4 + 36 3.23 Effect of the duration and flow-rate of argon deaeration on p H 37 3.24 Effect o f volume on p H and l n N H 4 + 38 3.25 Within and between person variability 40 3.26 Comparison of two sampling storage methods 42 Chapter 4: F ie ld Study 44 4.1 Overview 44 4.2 Objectives 44 4.3 Confidentiality 44 4.4 Study design 44 4.5 Participation and study population 45 4.6 Methods 45 4.7 Personal exposure measurements 45 4.7.1 Grain dust 45 4.7.2 Endotoxin 46 4.8 Health outcome measurements 46 4.8.1 Standardized respiratory questionnaire 46 4.8.2 Spirometry 46 4.8.3 Allergy skin test 47 4.8.4 Exhaled breath condensate collection 47 4.9 Data analysis 47 4.10 Definitions 49 4.11 Results 51 4.12 Eligible subjects 51 4.13 Demographic characteristics 51 4.14 Smoking characteristics 52 4.15 Work and exposure characteristics 53 4.15.1 Grain dust r 53 4.15.2 Endotoxin . . . . .54 4.16 Respiratory health characteristics 54 4.17 Exhaled breath condensate measurement 55 4.17.1 p H analysis 55 4.17.2 N H 4 + a n a l y s i s 56 4.18 Correlation o f p H a n d N H 4 + 56 4.19 Univariate associations between E B C p H or lnNH4+ and other explanatory factors. 58 4.20 Multivariable analysis of p H 60 4.20.1 Exploratory analysis of p H and obesity : 63 4.21 Multivariable analysis of l n N H 4 + 64 4.21.1 Exploratory analysis of l n N H 4 + and obesity 66 4.22 Other multivariable analyses 67 Chapter 5. Discussion 68 5.1 Overview 68 5.2 Method development and evaluation 68 5.3 Test acceptability 68 5.4 Effect of duration of E B C collection on E B C volume 68 5.5 Effect of condenser temperature on E B C volume, and on p H and l n N H 4 + '•• 69 5.6 Effect of use of filter on p H and N H 4 + 70 5.7 Effect of the duration and flow-rate of argon deaeration on p H 70 5.8 Effect of volume on p H and l n N H 4 + 71 5.9 Reliability of final E B C protocol 71 5.10 Reproducibility of p H measurements from the same sample 72 5.11 Effect o f freeze-thaw cycles 72 5.12 Within and between-person variability 72 5.13 Correlation of p H a n d N H 4 + 73 5.14 Summary 73 5.15 Field study .74 5.16 p H / l n N H 4 + and obesity 74 5.17 p H / l n N H 4 + and smoking 75 5.18 p H / l n N H 4 + and asthma/atopy 77 5.19 p H / l n N H 4 + and work area 77 5.20 p H / l n N H 4 + and years of employment in the industry 78 5.21 p H / l n N H 4 + and markers of exposure 78 5.22 Limitations, strengths, future directions 79 5.23 Conclusions 80 References 81 Appendices 97 Appendix 1 Consent form for the laboratory and field component of the study 97 Appendix 2 Instruction sheet for participants in the laboratory component of the study 103 Appendix 3 General questionnaire for participants in the laboratory component of the study 104 Appendix 4 Conversion table for the smoking characteristics of pipe and cigar smokers : 110 Appendix 5 Correlation analysis of the independent variables investigated in the study I l l Appendix 6 Univariate analyses of p H and other independent variables ..117 Appendix 7 Univariate analyses of NH4+ and other independent variables 119 Appendix 8 Univariate analyses of lnNH4+ and other independent variables 121 L I S T O F T A B L E S Table 2.1 Summary of studies investigating adult asthma using exhaled breath condensate 16 Table 2.2 Summary of studies investigating adult C O P D and adult asthma/COPD using exhaled breath condensate. 18 Table 3.1 Methodological considerations investigated in the laboratory study 29 Table 3.2 M i x e d effects model of p H adjusting for smoking status, and sample storage method 42 Table 3.3 M i x e d effects model of I n N H / adjusting for smoking status, and sample storage method 42 Table 4.1 Demographic features of the E B C study and larger grain study 52 Table 4.2 Work Characteristics of the E B C study population. 53 Table 4.3 Exposure Characteristics of the E B C Study Population 54 Table 4.4 Respiratory health characteristics of the E B C study 55 Table 4.5 List o f potential independent variables investigated, categorized accordingly 57 Table 4.6 Univariate associations between E B C p H or lnNHa* and other independent variables 59 Table 4.7 Multiple linear regression model of p H , adjusting for both years worked in the industry and obesity, for study population 61 Table 4.8 Multiple linear regression model of p H , adjusting for years worked in the industry only, for study population 62 Table 4.9 Multiple linear regression model of p H , adjusting for obesity only, for study population (n=75). 63 Table 4.10 Multiple linear regression model of p H for the non-obese population (n=52) only 64 Table 4.11 Multiple linear regression model of I n N H / (ln[uM]), adjusting for both years worked in the industry and obesity, for the study population 65 Table 4.12 Multiple linear regression model of I n N H / (ln[uM]), adjusting for years worked in the industry only, for the study population 65 Table 4.13 Multiple linear regression model of lnNfjV", adjusting for obesity only, for the study population 66 Table 4.14 Multiple linear regression model of l n N H 4 + for the non-obese population only 67 Appendix 4. Conversion table for the smoking characteristics o f pipe and cigar smokers 110 Appendix 5. Correlation analysis of the independent variables investigated in the study I l l Appendix 6. Univariate analyses of p H and other independent variables 117 Appendix 7. Univariate analyses of NH4+ and other independent variables 119 Appendix 8. Univariate analyses of lnNH4+ and other independent variables 121 ix L I S T O F F I G U R E S Figure 2.1. Collection of respiratory droplets by exhaled breath condensation 1 1 Figure 2.2. Acid-base equilibrium of the airways 21 Figure 3.1. Schematic of RTube™ 27 Figure 3.2 Study subject performing the E B C test with the R T u b e ™ 27 Figure 3.3 Effect of E B C collection time on E B C volume 33 Figure 3.4 Effect of initial condenser temperature on E B C volume 34 Figure 3.5 Correlation o f N F L * concentration and p H 35 Figure 3.6 Correlation o f l n N F f / and p H 35 Figure 3.7 Effect of initial condenser temperature on p H 35 Figure 3.8 Effect of initial cooling sleeve temperature on I n N H / 36 Figure 3.9 Effect of the use of a filter on p H 37 Figure 3.10 Effect o f the use of a filter on I n N H / 37 Figure 3.11 Effect o f the duration of argon deaeration at constant 350 mL/min on p H 38 Figure 3.12 Effect of the flow-rate of argon deaeration on p H 38 Figure 3.13 Effect of volume on p H 39 Figure 3.14 Effect of volume on l n N H / 39 Figure 3.1.5 Reliability of the final E B C protocol 40 Figure 3.16 Within- and between-person variabilitity o f p H in non-smokers and current smokers 41 Figure 3.17 Within- and between-person variability of lnNTrl / in non-smokers and current smokers 41 Figure 3.18 Effect of freeze-thaw on p H 42 Figure 3.19 Effect of freeze-thaw on l n N F f / 43 X Figure 4.1 Distribution of personal grain dust exposure levels 53 Figure 4.2 Distribution of the natural log of personal grain dust exposure levels.... 53 Figure 4.3 Distribution of personal endotoxin exposure levels 54 Figure 4.4 Distribution o f the natural log of endotoxin exposure levels 54 Figure 4.5 Distribution of E B C p H 56 Figure 4.6 Distribution o f N H 4 + 56 Figure 4.7 Distribution of the natural log of N H 4 + 56 Figure 4.8 Correlation of N H 4 + and p H 57 Figure 4.9 Correlation of l n N H 4 + and p H 57 Appendix 1. Consent form for the laboratory and field component of the study.... 97 Appendix 2. Instruction sheet for participants in the laboratory component of the study 103 Appendix 3. General questionnaire for participants in the laboratory component of the study 104 XI A C K N O W L E D G E M E N T S I would like to acknowledge the contributions of the many people who helped bring the completion of this study to fruition. Many thanks go out to the study participants, particularly the grain elevator workers who generously volunteered their time to participate in both the grain study and the present study. Thanks also are due to the researchers who were involved in the grain study, particularly Barbara Karlen and Yat Chow, for their help in recruiting volunteers in the field and in retrieving respiratory health information. I am also grateful to Winnie Chu, T i m M a and Tom Barnjak for performing the ammonium analyses on the samples. I would like to especially thank my committee members, Karen Bartlett and Helen Ward, for their on-going help and expert advice throughout all stages of the study. M y sincerest thanks goes to my supervisor, Susan Kennedy, for providing excellent guidance and supervision. Thank you for your incredible devotion to teach, and also in providing me with the motivation and inspiration in continuing on in research. Finally, I would like to thank my family for their support and encouragement, as well as Lisa, who despite being 5000 kilometers away, was always there for me throughout my time at U B C . 1 C H A P T E R 1. I N T R O D U C T I O N 1.1 Overview Workers in the grain industry have been shown to have adverse respiratory effects associated with occupational exposure to grain dust. Both acute and chronic respiratory ailments can be caused by extended exposures to grain dust (Chan-Yeung et al. 1992), but severe single exposures can also cause significant .respiratory problems (Swaine and Riding. 2001). The relationship between grain dust inhalation and its effect on the airways has been well-documented (Alam et al. 1988, Becker et al. 1999, Burvall et al. 2002). Several studies have shown dose-response relationships between airflow obstruction and grain dust exposure (Chan-Yeung et al. 1979, Chan-Yeung et al. 1992). Acute and chronic exposure to grain dust can trigger inflammatory changes in the airways, which can also lead to adverse respiratory symptoms (Becker et al. 1999, Schwartz et al. 1994). Currently, there is a need for the development of new methods in occupational health to assess the risks of exposure at the target organ level and also for the biological monitoring of workers to assess airway inflammation in occupational field studies. Traditional methods of measuring the pathologic changes in the lungs, such as induced sputum and bronchoscopy, have limited applicability in occupational settings due to the risks and high degrees of invasiveness involved. A method that is non-invasive and yet still measures the current state of the airways would be particularly useful. Recent research has shown that exhaled breath condensate (EBC) may be a viable method in field studies to sample secretions of the lower airways (Goldoni et al. 2004). It is believed that these secretions have the potential to predict the inflammatory response to inhaled irritants, including grain dust. Several biomarkers of airway inflammation in exhaled breath condensate have been detected, and changes in the concentrations of these biomarkers have been found in many respiratory illnesses (ie. (Reinhold et al. 1999)). In particular, the acid-base equilibrium in exhaled breath condensate has been shown to vary with the severity of airway inflammation (Carraro et al. 2005b, Gessner et al. 2003). Researchers from the Environmental and Occupational Lung Diseases Research Unit at the University o f British Columbia has been investigating the respiratory health of workers in terminal grain elevators in the port of Vancouver approximately every 3 years since 1975. Typically, these health studies have involved spirometry, respiratory questionnaires, personal exposure monitoring to grain dust and endotoxin, and exposure-response analyses (Chan-Yeung et al. 1992). In 2003, the 9 t h respiratory health study was carried out at five terminal grain elevators in the Port of Vancouver. The purpose of the present study was to investigate the applicability of the exhaled breath condensate test in a subset of workers in this larger cross-sectional grain study. The acid-base status of E B C of workers was measured to assess inflarnrnation in the airways. The airborne dust exposures to workers were selected to be a representative sample of the expected range of airborne dust exposures in terminal grain elevators. The results of this study wi l l be useful in determining whether this test can reliably predict acute or chronic inflammatory changes in the airways of grain elevator workers. 2 1.2 Objectives 1. To evaluate a standard procedure for the collection and measurement o f p H and ammonium in exhaled breath condensate (EBC) that can be applied to occupational field measurements; 2. To measure p H and ammonium in E B C obtained from grain elevator workers at the worksite; 3. To investigate exposure-response relationships between p H and ammonium in E B C and personal exposure to inhalable grain dust and endotoxin; 4. To investigate the role o f other risk factors for inflammation as potential confounders of these associations. 1 3 C H A P T E R 2. B A C K G R O U N D 2.1 G r a i n dust 2.1.1 Source, composition, and physical characteristics Grain dust can be defined as small, solid grain particles that may remain suspended in the air for some time, before settling under their own weight through the effects of gravity. Most grain dust is generated during the handling o f grain, when the wearing, grinding, or rubbing of grain kernels occurs. It has been estimated that in a typical grain elevator, approximately one ton of dust handled can generate three to four pounds of grain dust (Chan-Yeung et al. 1992a). The amount of grain dust in a particular area is dependent on several factors, including the grain type, physical characteristics such as the moisture content, and workplace environmental conditions such as the type of grain handling performed and the type of dust control measures implemented (World Health Organization (WHO) . 1999). Grain dust is a heterogenous substance that is composed of various organic and inorganic elements. Some of the organic elements o f grain dust may include bacteria (and associated endotoxin), kernels, husks, plant products, pollens, moulds, microflora, storage mites,, and animal particles. In addition, the inorganic constituents of grain dust may include sand, silicon dioxide, silica, quartz, and chemicals such as herbicides and pesticides. The physical and chemical composition o f grain dust can depend on the type of soil used, type of chemicals or fertilizers used, methods of irrigation, the weather conditions during the growing season, methods of harvesting and handling, storage conditions, as wel l as many other factors (Ward et al. 2004). The size of grain dust particles is defined by their, aerodynamic diameter, that is, "the diameter of a hypothetical sphere of density 1 g/cm3 having the same terminal settling velocity in calm air as the particle in question, regardless of its geometric size, shape, and true density" (World Health Organization (WHO). 1999). The size of grain dust particulate matter varies from below 1 um to over 100 urn. The aerodynamic diameter largely determines how and where the particles deposit in the respiratory system. Sedimentation, the process by which particulate matter settles, and impaction, the process of striking a surface such as the airway walls, are important mechanisms in determining how grain dust is deposited in the respiratory system (World Health Organization (WHO) . 1999). The size distribution of grain dust in the respiratory system can be categorized into three different fractions: inhalable, thoracic, and respirable particulate fractions. Grain dust particles that are greater than 10 urn are in the inhalable particulate fraction and tend to enter as far as the nose and mouth. Grain dust particles between 3.5 um and 10 um comprise the thoracic particulate fraction and can deposit in the tracheal and bronchial regions. The respirable particulate fraction includes grain dust particles that are less than 3.5 urn and can reach the bronchiolar and alveolar region (Ward et al. 2004). 4 2.2 Endotoxin The contamination o f microbes in grain occurs mainly at the crop growing stage (Lane et al. 2004). The amount of bacteria in grain dust depends largely on the type of grain, moisture content, and conditions of the environment, including growing and storage practices (Ward et al. 2004). Endotoxin is a bacterial toxin that is a component of the outer cell membrane of gram negative bacteria and its function in the microbe is to maintain cell integrity and function. It is a component of many different types of agricultural dusts. Endotoxin is naturally released into the environment as the bacteria replicates and also during cell lysis. Hence, endotoxin is ubiquitous in the environment, and can be found in soil, vegetation, and water. Studies have repeatedly shown that the inflammatory effects of grain dust on the airways in humans are partly attributed to endotoxin and that it can elicit inflammation, fever, malaise, and respiratory symptoms (Thorn. 2001). Endotoxin is comprised of a variable polysaccharide chain and a conserved lipid moiety, l ipid A . The variable polysaccharide chain is believed to aid the toxin in evading the host immune system, while the l ipid moiety region is responsible for the toxic effects of the molecule (Lane et al. 2004). Endotoxin may activate pulmonary macrophages and neutrophils, which then release chemotactic factors that attract inflammatory mediators to the site of interest. This initiates both acute and chronic inflammatory processes. 2.3 Host defense systems 2.3.1 Physical host defense systems: Physical barriers, mucociliary system The epithelium of the respiratory tract comes in direct contact with various particles and pathogens from the physical environment. The body has many different physical host defense mechanisms that limit foreign particles from reaching the lower respiratory tract. In the nasal cavity, there is a mucociliary surface that is lined with mucous and hair that helps to filter larger particles from passing through. In addition, the region from the sinuses o f the nose to the pharynx, as wel l as from the mouth to the pharynx, is "bent" and therefore particles entering the respiratory tract can impact the back of the throat, where the particles are removed by swallowing or sneezing. Particles that have passed into the lower respiratory tract can also be trapped by the mucociliary system lining the airways in the lower respiratory tract (below the tracheal/bronchial region), which sweeps mucous by the beating of cil ia upwards into the upper respiratory tract (oropharyngeal region) for removal. 2.3.2 Biological host defense systems: Immune system Aside from the physical barriers that protect the respiratory tract from foreign particles and pathogens, the body also has a complex host defense system that relies on the recruitment of immune cells and also on changing the surrounding conditions of the airway environment to damage the invading microorganisms, such as the bacteria (and associated endotoxin) that reside in grain dust (Bals and Hiemstra. 2004). However, in the process, inflammation can also damage the human tissue o f the host. Some examples 5 include inflammatory processes that release acids, proteins, and oxidants that are toxic to the microorganism but damage the airway as well . Adverse effects of the airways can include an imbalance in the airway redox system and acid-base equilibrium, dysfunctional surfactant, altered mucous viscosity, eosinophil and neutrophil inflammation, bronchoconstriction, epithelial dysfunction and sloughing (Ng et al. 2004). These adverse effects of the airways are also associated with respiratory symptoms such as cough, wheeze, and congestion. In chronic respiratory diseases, where the inflammatory processes become persistent, a series of persistent structural changes occurring through damage and dysregulated repair to the airways can lead to narrowing of the airways and irreversible decline in respiratory function (Jeffery. 2004). 2.4 Respiratory health effects of grain dust exposure: Epidemiological studies In Canada, there are approximately 30 000 grain elevator workers and each year, more than 5 mil l ion workers in North America are exposed to grain dust (Chan-Yeung et al. 1992). The health effects of grain dust inhalation have been well-known for many centuries. One of the earliest known documents on the impact of grain dust on respiratory health is a discourse by Ramazzini, called "Diseases of Sifters and Measurers of Grain" (Ramazzini. 1964). Since that time, research has repeatedly shown that exposure to grain dust exposure has an adverse affect on the lung health o f grain handlers (Huye ta l . 1991). Occupational exposure to grain dust has been reported to cause acute and chronic effects. This includes diseases such as asthma, grain fever, and chronic bronchitis, as well as respiratory symptoms such as chronic cough, wheeze, and bronchitis, and progressive irreversible airflow obstruction. In general, epidemiologic studies have shown that as the intensity and duration of exposure to grain dust in workers increases, the risk of airflow obstruction, respiratory symptoms, and respiratory diseases also increases (Huy et al. 1991). The acute effects o f occupational exposure to grain dust have been wel l -documented. Asthma-like syndrome is characterized by an acute, decline in F E V 1 (forced expiratory volume in the first second of a forced exhalation) and acute symptoms of chest tightness and breathlessness. Studies have also found a dose-related adverse respiratory effect among grain handlers over a workshift (doPico et al. 1983) and over a lifetime of exposure to grain dust (Huy et al. 1991). Other acute effects of grain dust exposure have also been reported such as skin and mucous membrane irritation (Hogan et al. 1986) and acute respiratory illness (Darke et al. 1976). Schwartz also noted that a decline of 10 % or more in F E V i due to occupational exposure to grain dust has been reported in up to 11 % of grain handlers (Schwartz. 1996). However, the decline in lung function in grain elevator workers may be partially reversible. A study reported declines in lung function in newly hired grain elevator workers after several weeks of working, but then subsequent improvement towards preexposure levels o f lung function (James et al. 1990). 6 Several studies have shown that exposure to grain dust is also associated with occupational asthma. A n early study reported asthmatic responses after inhalation challenges to crude grain dust and grain dust extract in six of 22 grain workers, while none of the control workers were affected (Chan-Yeung et al. 1979) and five of 11 grain workers developed positive bronchial reactions to inhalation challenges o f durum wheat extract, durum wheat airborne dust, and insects/mites in grain (doPico et al. 1982b). Several individual cases o f occupational asthma due to grain dust exposure have also been reported (Davies et al. 1976, Frankland and Lunn. 1965, Warren and Holford-Strevens. 1986, Yap et al. 1994). It has been suggested that grain dust asthma is caused by different allergens in the grain dust and the response varies from grain handler to grain handler (Chan-Yeung et al. 1992a). In general however, the prevalence of grain dust asthma is uncommon among grain elevators workers, because most are either excluded from the grain industry during the hiring stages, or cannot tolerate the constant exposure to the lung irritant and therefore must leave the industry shortly after (healthy worker effect) (Chan-Yeung et al. 1992a). A high level of grain dust exposure is also associated with grain fever, a syndrome of headache, malaise, chills, fever, chest tightness, dyspnea, myalgia and a transient decline in F E V 1 . The illness may also be associated with leukocytosis (doPico et al. 1982a). do Pico and colleagues reported symptoms of grain fever and lung function decline in workers after being exposed to high concentrations of grain dust for 2 hours (doPico et al. 1982a). The prevalence o f grain handlers developing grain fever can vary from 6 to 33 percent (Chan-Yeung et al. 1992a). Grain fever may also be uncommon in long time grain handlers because they tend to become more tolerant to grain dust exposures over time (Chan-Yeung et al. 1980). The chronic effects o f grain dust exposure are typically characterized by irreversible lung damage. Several studies have shown increased prevalence o f chronic cough, phlegm, wheeze and dyspnea in grain elevator workers, when compared to a control group (Chan-Yeung et al. 1992, Cotton et al. 1983). Chronic bronchitis is defined as the long term inflammation, obstruction, and degeneration of the bronchi, and results in chronic cough and mucous production over a prolonged period. Chronic bronchitis is often associated with smoking, but non-smoking grain workers have also developed the disease including a decreased F E V 1 (Dosman et al. 1980). It has been reported that up to 37 % of grain handlers develop chronic bronchitis (doPico et al. 1982b). Studies have consistently shown a greater decline in lung function in grain handlers over a work week (James et al. 1986, Tabona et al. 1984) and these lower levels of lung function were not reversible after cessation of exposure (Kennedy et al. 1994). Strong evidence for the chronic effects of grain dust exposure was also seen in a longitudinal study in which grain elevator workers showed progressively higher prevalences of respiratory symptoms and declines in lung functions, despite the reduction of ambient dust levels over the same years (Chan-Yeung et al. 1992). A s well , the effects of smoking and grain dust exposure on the respiratory health o f workers appears to be additive (Cotton et al. 1983). 7 2.5 Impact of endotoxin on respiratory health - Epidemiological studies Endotoxin exposure has been reported to elicit inflammation, fever, malaise, and respiratory distress. It has been shown that the inflammatory response to endotoxin is dose-related (Michel et al. 1997) and endotoxin exposure has been shown to be associated with declines in lung function in many agricultural industries including grain handlers (Schwartz et al. 1995), swine confinement workers (Donham et al. 1989), poultry workers (Thelin et al. 1984), farm workers (Radon et al. 2001), rice workers (Olenchock et al. 1984), and animal feed workers (Smid et al. 1994). A s wel l , exposure to high concentrations of endotoxin has been associated with cough, chest tightness and shortness of breath in workplace studies and with longitudinal increases in airflow obstruction (Schwartz et al. 1995). These studies suggest that the endotoxin in grain dust contributes to adverse effects on the respiratory health o f agricultural workers. 2.6 Grain Dust, endotoxin, and airway inflammation - Laboratory studies There is very strong evidence that grain dust induces inflammation in the airways, and that the endotoxin content is a key determinant. Several laboratory studies have been performed on in vivo animal and human models, as well as in vitro epithelial cell line models. Grain dust can trigger an immunological response in the airways, where alveolar macrophages and neutrophils are initially recruited to the airways and alveolar spaces. The inflammatory response to endotoxin is characterized by an early phase neutrophilic inflammation with the release of cytokines and chemokines, followed by a latter phase, where monocytes, macrophages, and lymphocyte infiltration occurs (Lane et al. 2004). 2.6.1 In vitro studies The recruitment of neutrophils is a key mechanism during airway inflammation. Direct neutrophil recruitment can occur by the lung irritants, or indirectly by the neutrophil chemoattractant production of C5a via the activation of the complement system, and the release o f factors that attract neutrophils by alveolar macrophages. V o n Essen and colleagues (Von Essen et al. 1988, 921-927) investigated these proposed mechanisms in relation to grain dust exposure in vitro (Von Essen et al. 1988). The authors showed that grain dust extracts can attract human neutrophils directly using a blindwell neutrophil chemotaxis assay, as well as indirectly by activating the complement system by exposing grain dust extract to human serum, and evaluating the cleavage of the complement proteins C3 and properdin factor B (PFB), and the generation o f the cleavage product, C5a. It was also reported that grain dust activated the chemotactic behaviour of alveolar macrophages by exposing grain dust extracts to a cell culture of unstimulated alveolar macrophages (Von Essen et al. 1988). Becker and colleagues (Becker et al. 1999) further reported thatt the inflammatory response to inhaled grain dust is compartmentalized, as bronchial epithelial cells generate IL-8, alveolar macrophages generate IL-1B and IL-6, while both alveolar macrophages and polymorphonuclear cells generate I L - 1 R A . Another study separated L P S and C D E solutions into two fractions of less than or greater than 100 kilodaltons (kDa) and found 8 endotoxin activity predominantly in the greater than 100 k D a fraction. The >100 kilodalton fraction was treated by charged-membrane filtration or polymyxin B to reduce the endotoxin activity by at least 80 %. When an in vitro THP-1 cell line was exposed to the untreated >100 k D a fraction, it caused a greater release o f T N F - a than the <100 k D A fraction or the treated >100 k D A fraction (Jagielo et al. 1996a). Similar results were also reported in mice, where elevated concentrations of bronchoalveolar lavage neutrophils and T N F - a were found when exposed to the untreated >100 k D A fraction (Jagielo et al. 1996a). These results further suggest the role of inflammatory mediators caused by grain dust and endotoxin in airway inflammation. 2.6.2 In vivo studies Many o f the in vivo studies investigating grain dust and airway inflammation have consisted of inhalation challenges of grain dust and endotoxin on humans and mice. Clapp et al. (Clapp et al. 1994) performed inhalation challenges in non-smoking, non-asthmatic, and non-atopic male grain workers to aqueous corn dust extract and buffered saline (separated by 14 days) and found that when compared to buffered saline, corn dust extract caused a significant decline in F E V 1 , as well as significant elevated concentrations of neutrophils, IL-1B, I L - 1 R A , IL-6, IL-8 and TNF-alpha in bronchoalveolar lavage fluid. The inflammatory responses o f grain dust and endotoxin extracts were examined for any differences in the physiologic responses o f these inhaled agents. This rationale was that i f there wasn't a significant difference in the physiologic or inflammatory response to endotoxin by itself compared to grain dust, then this suggests that endotoxin may be an important determinant in grain dust-induced airway inflammation (Jagielo et al. 1996b). Jagielo and colleagues exposed healthy human subjects to corn dust extracts and lipopolysaccharides of equal endotoxin content (separated by at least 3 weeks) and found similar results in respiratory symptoms, decreases in F E V 1 , and increased concentrations in B A L total cell count and mediators (TNF- a , IL-1B, IL-6, IL-8) (Jagielo et al. 1996b). Clapp et al. performed a study comparing exposures to various grain dust extracts (corn and soybean dust extracts) and endotoxin in normal human subjects (Clapp et al. 1993). Although there were differences in the responses to each of the inhaled agents, in general, similar systemic, pulmonary and mucosal inflammatory effects were found in the various grain dust extracts and endotoxin in the subjects. Schwartz and colleagues exposed saline, corn dust extract, sterile corn dust extract, and lipopolysaccharide (LPS) to genetically modified mice that were endotoxin-sensitive and endotoxin resistant (Schwartz et al. 1994, L609-17). The study reported dose-response relationships of total cells, neutrophils, and T N F - a in bronchoalveolar lavage ( B A L ) fluid after inhalation of each of the corn dusts, and L P S , in the endotoxin-sensitive mice, and yet only a higher concentration of T N F - a was reported in the endotoxin-resistant mice when exposed to the corn dusts. A s well , endotoxin-sensitive mice that had been pre-exposed to L P S for four days and then exposed to L P S or sterile corn dust extract on the 5 l day, had significantly lower concentrations of total cells, neutrophils, and T N F - a when compared to similar mice that had been pre-exposed to saline. This suggests that the airways are hyperresponsive to endotoxin initially, but 9 become tolerant o f endotoxin after a certain period of exposure to the agent. Subchronic inhalation of grain dust has been shown to cause chronic airway disease, where "persistent expansion of the airway submucosal cross-sectional area" was reported after exposing endotoxin-sensitive mice to corn dust extract for 8 weeks (George et al. 2001). Woldford-Lenane and colleagues also reported increased cytokine gene expression (TNF-a, I L - l - a , and MJJP-2) after exposing mice to both corn dust extract and L P S (Wohlford-Lenaneetal . 1999). However, despite the strong associations between endotoxin levels and airway inflammation, studies have also reported that there may be other factors in grain dust that may contribute to airway inflammation. V o n Essen and al. reported that when the grain dust extract was depleted of endotoxin, the direct chemofactic activity of neutrophils by the grain dust and the activation of the complement system was still preserved by the grain dust extract, but the chemotactic activity of the alveolar macrophage was significantly decreased (Von Essen et al. 1988). This result was similar to another study that reported varying abilities to recruit neutrophils by different kinds o f grain dusts, and no association between these chemotactic abilities and the respective endotoxin levels in the grain dusts (Von Essen et al. 1995), therefore suggesting that there were other factors besides endotoxin that may play a role in airway inflammation. Taken all together, the consistency of observations from both in vivo and in vitro studies constitute strong evidence that grain dust and endotoxin both contribute to inflammatory responses in the airways. 2.7 Measurement of airway inflammation In occupational field studies, the measurement of airway inflammation is valuable because it evaluates the biological response of the airways at the organ level, as well as assessing risks of health effects associated with exposures to inhaled agents. Cytological analyses of the fluid lining the airway, as well as the airway itself is usually required to evaluate inflammation. 2.8 Traditional methods of sampling secretions from the lower respiratory tract Induced sputum collection is carried out by the inhalation of aerosolized hypertonic saline solution usually after the inhalation of salbutamol to induce expectoration of sputum. Induced sputum collection has been used to sample secretions of the respiratory tract for cytological analysis in patients with a variety of respiratory disorders including asthma, C O P D , idiopathic pulmonary fibrosis, pulmonary tuberculosis, and cystic fibrosis. The procedure typically requires an adequately trained technologist or nurse, can involve some discomfort, and the sputum secretions may not be completely representative o f the entire respiratory tract (Scheicher et al. 2003). Broncho alveolar lavage ( B A L ) is performed by instilling fluid into the lungs and subsequent retrieval of the fluid for cytological analysis to estimate lung damage. This, in combination with bronchoscopy, a procedure used to visually inspect the lungs potentially allows for longitudinal monitoring of a disease as it progresses in an 10 individual, and also for research purposes for assessing the inflammatory processes o f diseases. Clinically, B A L has been used on patients with various airway diseases, including asthma, bronchitis and occupational lung diseases. However, some risks are associated with this procedure, including sedation, impaired gas exchange, and possible inflammation and infection of the respiratory tract (Reynolds. 2000). Because of the high degrees of invasiveness, the associated risks involved in the procedures and the need for specialized facilities, sputum induction and bronchoscopy/BAL are techniques that have very limited applicability in occupational field studies. 2.9 Exhaled breath condensate (EBC): A new method of sampling secretions from the lower respiratory tract 2.9.1 Introduction E B C has shown promise as a simpler alternative to.sputum induction or bronchoscopy/BAL for sampling the epithelial fluid lining the respiratory tract. E B C collection is a simple, non-invasive technique that has no known side effects associated with it. The first reported study involving E B C was performed by Russian researchers that identified the presence of surface-active properties such as pulmonary surfactant in E B C (Sidorenko, Zborovskii, and Levina 1980, 65-68). Another Russian group later characterized physical properties of E B C in patients with chronic bronchitis (Kurik et al. 1987, 37-39). However, it wasn't until the late 1990's that researchers started to seriously consider the benefits of E B C collection (review article: (Effros et al. 2004)). Since then, several papers on E B C have been published, ranging from laboratory studies to clinical studies. E B C may be used to determine the components of airway lining fluid environment, measure airway inflammation and oxidative stress in the respiratory tract, diagnose different lung diseases, and/or monitor responses to therapy. Despite the promise that E B C offers, there are still unresolved questions surrounding the utility of E B C , partly due to the lack of knowledge of the origins of solutes in E B C (ie. lower respiratory tract or upper respiratory tract), varying methodologies between studies in the collection, storage, and processing of the E B C assay, and concerns about the current assays not being sensitive enough for the detection of minute concentrations of solutes in the E B C (Horvath et al. 2005). 2.9.2 Collection and collection devices E B C collection is performed by having the subject breathe through a device that cools the exhaled air to produce a condensed liquid exhalate. The exhaled air is cooled below the dew point, the temperature at which air becomes fully saturated with moisture at a given atmospheric pressure and vapour content, by the transmission of heat onto a cold surface, where respiratory droplets are captured by the newly formed condensed water vapour (see figure 2.1). Unlike bronchoscopy/BAL and sputum induction, the procedure for E B C collection does not irritate the airways and therefore does not have an impact on lung function or airway inflammation. 11 Figure 2.1. Collection of respiratory droplets by exhaled breath condensation. Many researchers employ custom-made devices to collect E B C in their laboratories. Custom-made devices used in early studies generally consisted of a rubber tube immersed in a bucket of ice water. More sophisticated and portable collection devices emerged including condenser tubes with insulator jackets, and glass chambers surrounded by ice with separate openings for inhaling and exhaling (Hunt. 2002). 2.9.3 Origins of respiratory droplets The exact origin of the respiratory droplets captured in E B C is unknown. Scheideler et al. first detected proteins in E B C that appear to have originated from the lower regions of the respiratory tract by analyzing the protein patterns of E B C and saliva from the same subject and revealing proteins that were present in the E B C and yet were absent in the saliva samples (Scheideler et al. 1993). Several studies have also reported similar concentrations of adenosine, ammonia, thromboxaneB 2, and pH present in the E B C collected through the mouth and through tracheostomies, a procedure for breathing that bypasses the upper airways, in the same individuals (Vass et al. 2003, 850-855; Vaughan et al. 2003, 889-894). This further suggests that certain inflammatory mediator levels are derived from the lower airways. However, another study has suggested that the upper airways may influence certain E B C parameters. Marteus and colleagues have studied the origin of nitrite and nitrate in E B C . The authors have suggested that nitrites may originate mostly in the upper respiratory tract, while nitrate may originate in both the lower and upper airways (Marteus et al. 2005). It is generally believed that the respiratory droplets are actually derived from multiple sites of the respiratory tract, including the bronchioles, bronchi, larynx/pharynx, and oral cavity (Effros et al. 2004). 2.9.4 Mechanisms of aerosolization Currently, there are two proposed mechanisms for the aerosolization of airway lining fluid ( A L F ) in the airways. The turbulence theory predicts that airflow in the airways produces sufficient energy to aerosolize respiratory droplets of the A L F in the airways. A s airflow increases in the airways, so does turbulence and the energy applied to the airways. It is believed that the yield and initial size of the aerosols increases as the turbulence in the airways increases (Papineni and Rosenthal. 1997). Hunt and colleagues suggest that generation of aerosols are most likely to occur at anatomic site locations where turbulence is the greatest (Hunt. 2002). During normal tidal breathing, this would 12 mean aerosolization occurs predominantly along the cartilaginous rings o f the bronchi and trachea, as well at the pharynx, glottis, and the first several generations o f the respiratory tract, where the speed and direction of airflow is the greatest (Hunt. 2002). The majority of respiratory droplets have been reported to have particle sizes o f less than 0.3 microns, with less than 2 % being greater than 1 micron (Fairchild and Stampfer. 1987, Papineni and Rosenthal. 1997). In contrast, Corradi et al. suggest that aerosol generation o f E L F can occur during the absence o f airflow. It has been suggested that when closed respiratory bronchioles and alveoli are "popped" open, sufficient energy may be produced to create a fine mist or spray containing tiny particles of E L F (Hunt. 2002). This theory is supported by Corradi and colleagues who report that the concentrations of malondialdehyde ( M D A ) , a biomarker o f airway inflammation, were not statistically different when E B C was collected at different flow rates of 200, 150, 100 and 50 mL/second (Corradi et al. 2003). In addition, a study reported the presence of surfactant in E B C (Sidorenko et al. 1980), a fluid that reduces the surface tension of pulmonary fluids, which suggests that surfactant may also play a significant role in generating aerosols. However, it is not yet known the impact of either of these mechanisms or of surfactant in enhancing aersolization in the airways (Hunt. 2002). 2.9.5 Composition The principal constituent of E B C is condensed water vapour, which accounts for more than ninety-nine percent of the volume (Effros et al. 2002). E B C also contains aerosolized respiratory droplets containing hydrophobic and water-soluble non-volatile compounds, as well as water-soluble volatile compounds (Scheideler et al. 1993). Many of these biological compounds reflect the various biochemical processes that are occurring in the airways at the moment of E B C collection. The concentrations of the compounds can be used as 'indicators' or 'markers' of pathological processes that are occurring in the airways. Non-volatiles are generally derived from the aerosolized respiratory droplets, while volatiles are formed by water-soluble gases that have become trapped in the E B C . Some common non-volatiles that have been measured in E B C include arachidonic acid metabolites (ie. Isoprostanes (8-isoPGF2a), leukotriene B4), interleukins (IL-1 (3, IL-2, IL-4, IL-6, IL-8), T N F - a , H+, urea and acetic acid. The more common volatiles measured in E B C include nitric oxide, ammonia, and hydrogen peroxide (Montuschi and Barnes. 2002a). 2.10 Methodological considerations for EBC Although there is interest in the utility of E B C collection to sample secretions of the airway lining fluid, there is still considerable controversy over the usefulness of the tool, partly due to methodological issues pertaining to the collection, storage and analysis of E B C . A joint taskforce from the American Thoracic Society (ATS) and the European Respiratory Society (ERS) that consisted of an expert panel was created to develop guidelines for E B C collection and analysis. The taskforce met at four meetings over three years to exchange ideas and knowledge about E B C . A s a result of these meetings, a 13 consensus was reached on certain methodological issues of E B C (Horvath et al. 2005). Methodological issues related to the present study only are discussed in the following section. 2.10.1 Duration and temperature of condensation The volume of E B C collected at tidal breathing varies among subjects and is influenced primarily by the duration of collection and temperature o f condenser (Gessner ' et al. 2001). Other factors that affect E B C volume include minute volume (ventilation volume per unit time), method of breathing (Vass et al. 2003), material of condenser, characteristics involving turbulence (Hunt. 2002), temperature of air, and humidity (Kharitonoy and Barnes. 2001). Gessner and colleagues reported a high correlation of total exhaled volume and E B C volume (r=0.95). The authors also reported correlations of E B C volume with total protein (r=0.65) and total urea (r=0.92), suggesting that certain non-volatiles are accumulated in E B C in a similar fashion to expired water vapour (Gessner et al. 2001). This suggests the volume of E B C may have an effect on certain markers of E B C . The stability o f unstable compounds can be affected by the temperature and duration of E B C collection. A s well , the solubility of certain volatiles may be affected by the temperature of condensation. There have been concerns about the temperature of the condenser tube being too cold during E B C collection. Temperatures o f less than - 20 °C could produce frozen water vapour in the E B C . A s the exhaled air comes in contact with the cold condenser surface, this could produce multiple freeze-thaw effects, which could potentially affect the stability o f certain biological compounds (Goldoni et al. 2004). A s well , frozen E B C may lead to less efficient trapping of certain volatiles (such as NH3) in E B C . This could affect biomarker concentrations that are sensitive to the effects of these volatiles (such as the effect o f N H 3 on pH) (Vaughan et al. 2003). Another methodological concern is the influence of temperature on certain E B C parameters and mediator levels. Goldoni et al. reported an increase in E B C volume as the cooling temperature decreased (Goldoni et al. 2005). The authors also reported increases in hydrogen peroxide concentration, malondialdehyde concentration, and conductivity as the cooling temperature increased. Decreases in total hydrogen peroxide, malondialdehyde, and increases in total conductivity as temperature of condensation decreased was also reported. These findings suggest that variation in E B C volume produced by different temperatures o f condensation during E B C collection may influence the concentration of certain mediators of E B C . 2.10.2 Dilution and concentration of respiratory solutes Non-volatiles are derived from aerosolized respiratory droplets, which may be independent of water vapour formation. Due to this, the issue of dilution of certain mediators in E B C has been raised by some researchers (Dwyer. 2004, Effros et al. 2003a). Studies have reported no effect of breathing pattern on protein, nitrite concentrations, p H (McCafferty et al. 2004) and 8-isoprostane (Montuschi et al. 1999) in 14 E B C . In contrast, other studies have reported variable dilutions o f mediator levels in E B C (Effros et al. 2002, Goldoni et al. 2005). Effros has reported a difference o f electrolytes in plasma and E B C , by reporting lower concentrations of electrolytes in E B C o f less than 0.01 % to 2 % than in plasma (Effros et al. 2002) and an average o f a dilution of 20,000:1 for total cation (sum of N A + , K+ , Ca2+, and Mg2+), urea, or conductivity in E B C (Effros et al. 2003a). It has been suggested that the potential problem of the dilution of respiratory solutes can be addressed through the use of a reference marker that is responsive to the dilution effect, and yet unaffected by airway inflammation. Theoretically, the best candidates for dilution markers are when the concentrations of the indicator is the same in both plasma and E B C . In doing this, one can determine the dilution factor by measuring the concentrations o f the marker in plasma and E B C and then dividing the dilution marker concentration of plasma over dilution concentration of E B C . Although there have been efforts to find a suitable dilution marker for E B C , such as concentration o f urea, electrolytes, or conductivity (Effros et al. 2002, Effros et al. 2003b), there is as of yet no dilution marker that has been established and accepted by E B C research groups^ 2.10.3 Oral contamination Many mediators from the lower airways detected in E B C are also present in saliva from the mouth. Therefore, it is reasonable to suggest that mediators from the mouth may be transferred to the lower airways, as well as to E B C directly. Studies have shown that the protein content (Griese et al. 2002) and electrolyte ratios (Effros et al. 2002) in E B C and saliva differ. Effros and colleagues have also observed low concentrations of salivary amylase in E B C , on average o f 0.01 % of that in saliva (Effros et al. 2002). These results suggest that salivary contamination is not a major factor in determining mediator levels in E B C . However, studies have also reported concentrations o f the same proteins being present in E B C and saliva (Griese et al. 2002), prompting some concerns about possible contamination of E B C . Other methods of reducing gross salivary contamination include having the condenser at a higher level than the mouth (Vaughan et al. 2003) and also by separating the mouthpiece and the condenser by tubing, both methods making it more unlikely that saliva reaches the area of E B C collection (Hunt. 2002). 2.10.4 Nasal/oral inhalation, use of noseclips There is also some debate with whether it is better to perform the E B C test with or without noseclips. In studies where noseclips were used, subjects were asked to both inhale and exhale through the mouth. In other studies where noseclips were not used, subjects were asked either to inhale through the mouth or through the nose, and exhale through the mouth. For methods employing inhalation through the nose, there have been concerns of aerosols of nasal secretions containing inflammatory mediators possibly contaminating E B C samples. However, drainage o f nasal secretions into the nasopharyngeal region may still represent another way of nasal aerosols entering E B C 15 samples when the method of inhalation through the mouth is employed during E B C collection (Effros et al. 2004). Vass and colleagues compared the different methods of nasal and oral inhalation during E B C collection and found that the E B C volume was significantly higher when nasal inhalation was employed compared to oral inhalation (Vass et al. 2003). A s wel l , the mediator levels of adenosine, ammonia, and thromboxaneB2 appeared to show no significant difference between the two methods of inhalation. However, in allergic rhinitis patients with upper airway inflammation, adenosine levels were significantly higher during nasal inhalation in comparison to oral inhalation. This suggests that the upper airways inflammation may potentially have an effect on certain mediators in E B C . However, the use of noseclips does not seem to have an effect on other mediators, such as H+ (pH) in E B C . Borr i l l and colleagues reported similar mean p H values without using a noseclip (7.61 (7.52 - 7.70)) compared to using a noseclip (7.59 (7.47- 7.70)) in C O P D patients (Borrill et al. 2005). 2.11 Exha led breath condensate studies of other markers of a i rway inf lammation (excluding markers of acid-base equi l ibr ium) 2.11.1 C l in i ca l studies Several E B C studies have reported abnormal levels of biomarkers of airway inflammation in patients with various lung disorders. Many biological compounds have been detected in E B C , each serving as potential markers of acid, oxidative, and inflammatory stresses that underlie many different pathological processes in various respiratory diseases. The markers that have been investigated include H2O2 (Van Hoydonck et al. 2004), leukotrienes , 8-isoprostane (Carraro et al. 2005a, V a n Hoydonck et al. 2004), nitrothiols/nitrotyrosine (Goen et al. 2005), nitrite/nitrate (Liu and Thomas. 2005), IL-4 (Shahid et al. 2002), IL-6 (Bucchioni et al. 2003), aldehydes (Corradi et'al. 2003) , adenosine (Spicuzza et al. 2003), endothelin (Carpagnano et al. 2003), glutathione (Corradi et al. 2003), and hepatocyte growth factor (Nayeri et al. 2002). The disorders studied have included asthma (Montuschi and Barnes. 2002b), chronic obstructive pulmonary disease (COPD) (Montuschi et al. 2003), acute lung injury (Moloney et al. 2004) , cystic fibrosis (Carpagnano et al. 2003), obstructive sleep apnea (Carpagnano et . al. 2002), idiopathic pulmonary fibrosis (Carpagnano et al. 2003), bronchiectasis (Loukides et al. 1998), ciliary dyskinesia (Csoma et al. 2003), and pneumonia (Majewska et al. 2004). Asthma and chronic obstructive pulmonary disease are respiratory diseases that are relevant to grain elevator workers. The studies that have investigated adult asthma and adult C O P D specifically have been summarized in table 2.1 and 2.2. The consistency of findings o f abnormal levels of inflammatory marker concentrations in studies involving different biomarkers in different lung disorders constitute strong evidence of the utility of E B C to assess the underlying biochemical pathologies that are occurring in these disorders. Table 2.1. Summary of studies investigating adult asthma using exhaled breath condensate. Adult Asthma Reference Study Group Markers Study Design Key Findings (Battaglia et al. 2005) Non-smoking/ex-smoking mild atopic asthma (n=14); healthy controls (n=15) 8-isoprostane Cross sectional 8-isoprostane inversely correlated with FEV1 PP and % vital capacity. (Larstad et al. 2005) Stable, bronchial asthmatics (n=12); healthy controls (n=15) 3-nitrotyrosine Case-control Slight non-significant increase in 3-NT in asthmatics (Csoma et al. 2003) Non-atopic healthy controls (n=8); mild asthma (n=10) adenosine Before and after exercise challenge Exercise-induced bronchoconstriction is associated with increase in EBC adenosine levels. (Sanak et al. 2004) Aspirin-induced asthma (n=14); aspirin-tolerating asthma (n=20); healthy controls (n=10) PG E(2)alpha, F(2 alpha), 9 alpha 11 beta F(2), iso-F(2), cysteinyl leukotrienes Before and after oral aspirin challenge No difference in PG levels by the challenge or between groups, except for lower 9 alpha 11 beta PGF(2) in aspirin-intolerant asthma. (Ojoo et al. 2005) Stable, atopic asthma (n=18); healthy controls (n=15) N02/N03, pH Case-control EBC pH, N02, N03 was similar in both groups. (Bucchioni et al. 2004) Mild asthma (n=13); healthy controls (n=9) Histamine, cys-LT Before and after metacholine and adenosine-5-monophosphate In AMP challenge, cys-LT levels were signficantly higher afterwards in asthmatics, but not in controls. (Cap et al. 2004) Stable asthma (n=28); healthy controls (n=50) LTB(4), LTC(4), LTD(4), LTE(4) Cross-sectional, case-control LTD(4), LTE(40, and LTB(4) in adult asthmatics were significantly higher than in control. (Sandrini et al. 2003) Mild, stable asthma (n=20) ENQ, H202, cys-LTs Randomized, double-blind, crossover clinical trial to 2 weeks of montelukast and placebo treatment Montelukast reduced levels of ENO from baseline during entire treatment period. (Corradi et al. 2001) Stable asthma (n=7), COPD (n=9); non-atopic healthy, non-smoking (n=15) and smoking (n=15) controls N03 Case-control N03 significantly higher in asthmatics than in controls, but not in COPD patients. (Huszar et al. 2002) Steroid-naive (n=23) and steroid-treated (n=20) asthma; healthy controls (n=40) adenosine, eNO Case-control Adenosine higher in steroid-naive patients than in healthy controls and steroid-treated patients. (Kharitonov et al. 2002) Mild, atopic asthma (n=28) eNO, eCO, nitrite/nitrate, S-nitrosothiols, 8-isoprostane double-blind, parallel group, randomized clinical trial to budesonide and placebo treatment Significant reduction in exhaled nitrite/nitrate and S-nitrosothiols after budesonide treatment. (Antczak et al. 2002) Mild-moderate steroid-naive and steroid-treated aspirin-induced asthma (n=31); aspirin-tolerant asthma (n=26); healthy controls (n=16) cys-LT, 8-isoprostane Case-control Cys-LTs, 8-isoprostane significantly higher in - steroid-naive AIA patients than in ATA steroid-naive patients and healthy subjects. (Montuschi and Barnes. 2002b) steroid-naive mild asthma (n=15); healthy controls (n=12) LTB(4), LTE(4), PGE(2), PGD(2), PGF(2)(alpha), Case-control Higher levels of LTE(4), LTB(4), exhaled NO in asthmatics than in controls thromboxane B(2) (Emelyanov et al. 2001) Steroid-naive, unstable atopic asthma (n=70); healthy controls (n=17) H202 Case-control H202 significantly higher in asthma than in controls (Ganas etal. 2001) Steroid-naive (n=30) and ICS-treated (n=20) stable atopic, asthma; healthy controls (n=10) Total N02/N03, H202 Case-control N02/N03 significantly higher in asthma patients than control. (Nightingale et al. 1999) Mild, atopic asthma (n=10); healthy controls (n=10) exhaled NO, nitrite Double-blind, randomized placebo-controlled, crossover study to inhaled ozone Ozone exposure causes no change in either asthmatics or healthy controls. (Montuschi et al. 1999) Mild (n=12), moderate (n=17), severe (n=15) asthma; healthy controls (n=10) 8-isoprostane, exhaled CO, NO Case-control Significant increase 8-isoprostane in mild, moderate, and severe asthmatics. Table 2.2. Summary of studies investigating adult C O P D and adult asthma/COPD using exhaled breath condensate. Adult COPD Reference Year Study Group Markers Study Method Key Findings (Mercken et al. 2005) stable COPD (n=11); age-matched ns controls (n=11) H202 Before and after exercise program Increase of H 2 0 2 in COPD patients than controls. H 2 0 2 incr. after exercise in COPD patients/controls. (Gerritsen et al. 2005) Medium to severe COPD (n=14) H202, IL-8 progressively over one week Before treatment, H 2 0 2 and IL-8 increase in COPD. During treatment, H202 and IL-8 declined significantly. (Carpagnano et al. 2004) Mild - severestable ex-s COPD (n=23); ns healthy controls (n=23) 8-isoprostane, IL-6 Before and after oxygen and ambient air treatment Increased levels of 8-isoprostane and IL-6 after oxygen challenge. (Carpagnano et al. 2004) mild, ex-s COPD with acute exacerbations (n=40); ns controls (n=15) 8-isoprostane, IL-6 Before and after 2 weeks of antibiotic treatment and 6 months mucolytic therapy Significantly higher 8-isoprostane and IL-6 in acute vs. stable COPD. Treated had lower 8-iso./IL-6 than untreated. (Bucchioni et al. 2003) Moderate ex-s COPD patients (n=16); healthy ns controls (n=12) IL-6, T cells, B cells, Case-control Significantly higher IL-6 in COPD than control. (Montuschi et al. 2003) Stable, mild-moderateCOPD patients (steroid-naive n=20, steroid-treated n=25); healthy controls (n=15) LTB(4), LTE(4), PGE(2), PGD(2)-methoxime, PGF(2alpha), Thromboxane B(2) Cross-sectional, case-control Steroid-naive/steroid-treated COPD had higher LTB(4)/PGE(2) than control. (Biernacki et al. 2003) COPD with acute exacerbations (n=30); ns controls (n=12) LTB(4), 8-isoprostane Before and after 2 weeks and 2 months of antibiotic treatment Increased LTB4/ 8-isoprostane during COPD exacerabation and decrease after treatment. (Corradi et al. 2003) Stable, moderate-severe ns COPD (n=20); smoking controls (n=12) MDA, hexanal, heptanal, nonanal Case-control Significantly higher MDA, hexanal, heptanal in COPD than control. (Ferreira et al. 2001) stable, ex-s, COPD (n=20) eNO, H202 random, double-blind, cross-over clinical trial to 2 two-week treatment periods to inhaled beclomethasone and matching placebo Median eNO significantly decreased after 1/2 week of treatment. (Kasielski and Nowak. 2001) mild-moderate COPD (n=44); healthy controls (n=17) H202, TARS Randomized, parallel-group, double-blind, double-dummy, international multicentre trial of 12 vs. 9 month treatment with NAC or placebo After treatment, treatment had sig. low H202 than placebo. (Montuschi et al. 2000) Ex-s (n=25) and cs (n=15) COPD; healthy ns (n=10) and cs (n=12) 8-isoprostane Case-control, before and after 15 mins and 5 hours of smoking COPD had significantly higher 8-isoprostane than control. (Dekhuijzen et al. 1996) stable COPD (n=12); COPD with acute exacerbations (n=19); healthy ns controls (n=10) H202 Case-control COPD with acute exacerbated sign, higher H 2 0 2 than stable COPD. Stable COPD sign, higher H 2 0 2 than control. (Kostikas et al. Non-atopic, cs, stable, reversible EBC, sputum: Leukotriene B4 Prospective cross-sectional Sig. high. LTB(4) in COPD w/o airflow 2005) (n=15), and non-reversible (n=15) COPD ; atopic, cs asthma (n=15); atopic cs control (n=10) case-control reversibility. (Corradi et al. 2004) Mild-moderate asthma (n=10); mild-moderate and severe COPD (n=11); healthy controls (n=9) Aldehydes Case-control MDA was negatively correlated with severe COPD. (Corradiet al. 2001) Mild asthma (n=9); severe asthma (n=8); stable COPD (n=7); ns and cs controls (n=17) Nitrosothiols, exhaled NO, nitrite (NO(2-)) Case-control RS-Nos were significantly higher in severe asthmatics than controls/mild asthmatics/COPD. 20 2.11.2 Occupational and environmental studies There are relatively few studies that have investigated the utility of E B C in an occupational or environmental setting. Russian researchers, Khyshiktuev and Makismenia, showed the diagnostic value o f E B C in an occupational setting, where the research group evaluated the fatty acid composition of E B C in workers of the Kharanor coal stripping industry in relation to coal dust exposure (KJiyshiktuev and Maksimenia. 2001) . Another Russian researcher, Pikas, examined the fatty acid composition of E B C in persons exposed to ionizing radiation at the Chernobyl nuclear power station (Pikas. 2002) . The researchers concluded that "the fatty acid composition of an expired air condensate adequately reflects the changes occurring in the respiratory system upon exposure to dust" (Khyshiktuev and Maksimenia. 2001). E B C has been used for the biomonitoring of environmental exposures in occupational settings. Goldoni and colleagues used E B C to assess lung dose and effects in workers exposed to cobalt and tungsten (Goldoni et al. 2004). The researchers measured malondialdehyde ( M D A ) , a marker of oxidative stress, cobalt, and tungsten in the E B C and urine of the workers at the beginning and end of the work shift. The main findings were that there were generally higher E B C cobalt and tungsten levels post-exposure compared to pre-exposure and there was a dose-response relationship with cobalt and M D A concentrations in E B C . The effect of cobalt was enhanced by co-exposure to tungsten. These findings suggest that E B C may be a promising alternative to biological exposure monitoring using urine or blood to measure elements and toxic metals in occupational and environmental biomonitoring, as wel l as for measuring inflammatory responses to inhaled agents. In addition to occupational studies, there have been some controlled environmental studies that have used E B C to assess the airway inflammatory responses to air pollution. Nightingale and colleagues (Nightingale et al. 2000) used nitrite in E B C as a marker of airway inflammation to study the effects of the inhaled corticosteroid . budesonide, in human subjects that were exposed to ozone. The researchers did not find any changes in nitrite levels after ozone exposure, or between the treatment and placebo groups. These results were similar to an earlier study where Nightingale and colleagues did not find any differences in nitrite levels in normal and atopic asthmatic subjects after exposure to inhaled ozone (Nightingale et al. 1999). However, a study by Montuschi et al. reported a significant change (pO.OOl) in 8-isoprostane levels after exposure to ozone in healthy non-smokers and that pre-treatment of inhaled budesonide before the ozone exposure had no effect on the 8-isoprostane levels (Montuschi et al. 2002). A research group lead by Corradi studied various markers of oxidative stress in E B C (8-isoprostane, thiobarbituric acid-reactive substances ( T B A R S ) , leukotriene B 4 (LTB-4) , p H , and H2O2) in response to controlled ozone exposure in human subjects and found that exposure levels o f ozone comparable to those found in the environment during air pollution episodes in Northern Italy caused an increase in the levels of NAD(P)H:quinine oxidoreductase and Glutathione-S-Transferase in the E B C of only a subgroup of subjects with a certain genotype combination of genes that have been associated with differential responses to inhaled ozone (Corradi et al. 2002). 21 2.12 Acid-base equilibrium in exhaled breath condensate Excessive or uncontrolled acidification of the airways can be caused exogenously by inhalation o f acids (such as acid fog, air pollution, or workplace exposures), or endogenously by disturbance of the airway p H homeostatic regulatory system or gastroesophageal reflux (Ricciardolo et al. 2004). Excessive or uncontrolled acidification o f airway lining fluid is promoted by disease (such as cystic fibrosis) or airway inflammation. Leukocytes recruited to the airways during an inflammatory event may produce metabolic acids. A s well , during airway inflammation, the epithelium of the airways itself may secrete H+ ions through activated ion channels (Ng et al. 2004). A decreased pH in airway lining fluid may cause adverse respiratory effects, such as epithelial sloughing and mucous plugging, in the airways (Ng et al. 2004). The regulation of airway p H is maintained by the production and release of acids and bases in various buffer systems of the airways. Controlled airway acidity is believed to be part of a complicated biological host response system where a fall in pH may play an important innate immunological role by defending against airborne particles (Ricciardolo et al. 2004). In response to the various acids contributing to airway acidity, the airways have mechanisms to counter the acid stresses. There are proteins in the airway lining fluid, such as albumin, that buffer the acidic response. In addition, bicarbonates are secreted into the airways to neutralize the acids. Epithelial cells in the airways can also regulate acidity by producing ammonia ( N H 3 ) via glutaminase activity or urease hydrolysis (Hunt et al. 2002, Kostikas et al. 2002). These mechanisms can function in a coordinated manner to stabilize the p H of the airway lining fluid (see figure 2.2). Figure 2.2. Acid-base equilibrium of the airways. NH3 glut amine ghit amine NH3 NH3 HC03- v j / v j ^ NH3 M B NH3 HC03-H+ N H 3 + H + NH4+ H+ H+ H + H+ NH3 + H - NH4+ H+ H+ H+ N H 3 - H - NH4+ /K sK sK i Airway Epithelium Because the changes in pH of airway lining fluid is not specific to one particular process; there is uncertainty about whether the pH is a reliable biomarker of airway 22 inflammation. Furthermore, because the fluid lining the airways is heterogenous, the various components, as wel l as locations (ie. proximal, distal airways) o f the fluid may have different pH's . In addition, during localized inflammation at a specific site in the airways, changes in p H may occur only in that particular region. Therefore, it is generally believed that the measurement of p H in E B C is not a direct measure of the p H of airway lining fluid, but is rather an "integrated signal representing excessive production and volatilization of acid from one or more locations in the airway" (Ricciardolo et al. 2004). 2.13 Methodological considerations 2.13.1 Gas standardisation of pH The measurement of p H in E B C samples can be performed using a p H electrode. Some studies have directly measured the p H in E B C directly after collection (McCafferty et al. 2004, Tate et al. 2002). However, E B C can sometimes be relatively unstable when measured directly, due to dissolved carbon dioxide (CO2) in the E B C samples. CO2 dissolved in the E B C can also combine with H2O to form carbonic acid (H2CO3), and therefore possibly making the p H of E B C more acidic than the p H of airway lining fluid. To stabilise the reading o f E B C p H , Hunt et al. has suggested purging E B C samples for 10 minutes with a CO2 free inert gas, such as argon, at a flow rate of 350 mL/min to standardize CO2 and H C O 3 - in the E B C samples (Hunt et al. 2000). Hunt et al. showed that p H readings stabilized after this point, suggesting that further CO2 could not be removed. Subsequently, many other studies have used this approach (Carpagnano et al. 2004, Kostikas et al. 2002, N i i m i et al. 2004). There have been concerns about the remaining non-volatile bases and acids, and their effect on the p H (Effros et al. 2004). Despite these concerns, studies have reported that low p H values of E B C before deaeration remains low after deaeration with argon (Hunt et al. 2000, Kostikas et al. 2002). 2.13.2 Oral contamination of ammonia There are concerns about the ammonia (NH3) content in the mouth possibly affecting the NH3 concentrations in E B C (Effros. 2003). Effros and colleagues suggest that there are other factors other than lower airway inflammation that may affect E B C acidification (Effros et al. 2005). One concern is that E B C acidification may be affected by oral N H 3 , since NH3 acts as a basic buffer of p H . The decreased production of N H 3 in the mouth could be related to "drying of mucous membranes of the mucous membranes by dehydration, hyperventilation, and drugs used to treat the underlying respiratory disorder" (Effros et al. 2005). However, Vaughn and colleagues showed that E B C p H measured through a breathing tube in patients undergoing endotracheal intubation for elective surgery was identical to the E B C p H measured just before the intubation (Vaughan et al. 2003). Wells and colleagues have also reported that oral ammonia concentration does not significantly affect E B C p H (Wells et al. 2005)). Effros et al. has also suggested other factors not related to airway acidicification that may affect E B C p H and N H 3 (Effros et al. 2005). The authors propose that less efficient trapping of N H 3 in 23 E B C may be caused by a reduction in end tidal volume or a decreased PCO2 (Effros et al. 2002). However, Vaughn and colleagues have reported that the degree of hyperventilation does not affect the concentration of E B C p H (Vaughan et al. 2003). 2.14 Relevant studies investigating acid-base equilibrium of the airways 2.14.1 Organic dust and airway acidification One study investigated the acidic response of swine containment facility dust in vitro. The authors reported that organic swine dust exposure caused the release of excess protons in a human airway epithelial cell line (Burvall et al. 2002). The authors suggest that the airway acidic response to organic dust is rapid and may occur within minutes, and that airway acidification may be activated through different mechanisms. One of these mechanisms may include protons being released through sodium/proton exchanger activity via a sodium/proton exchange protein 1 (Ricciardolo et al. 2004). Other mechanisms for regulation of p H intracellularly in response to organic swine dust exposure may include N A + independent CI-/HCO3- exchangers (Burvall et al. 2002). These results suggest that there may be a direct response to organic dusts in the airways that may involve acidification. 2.14.2 pH Prior to the use of E B C , the p H of airway lining fluid had not been well investigated in health research, primarily because of the difficulty and invasive nature of the tests. However, since E B C was discovered to be a useful matrix to sample secretions of the airways, several studies have shown that the p H of E B C may be a promising biomarker of acidity in the airways. Acidification of E B C was first reported by Hunt and colleagues in acute asthma patients (n=22) (Hunt et al. 2000). The authors reported that these patients had a mean p H of 5.23, compared to the control group (n=19) who had a mean p H o f 7.65 (p<0.001). However, another group with stable asthma (n=12) had a mean p H of 7.8 (p=0.95 compared with the control group). After systemic glucocorticoid therapy, subsequent normalization was reported in the acute asthma groups (pH=7.4, p<0.001). A subsequent study performed by Kostikas and colleagues found similar results in subjects with asthma, C O P D , and bronchiectasis (Kostikas et al. 2002). The researchers reported that C O P D (pH = 7.2) and bronchiectasis subjects (pH = 7.1) had a significantly lower p H value than asthma (pH = 7.4) and control subjects (mean E B C p H = 7.2) (p < 0.0001). A s well , asthma patients who had been treated with inhaled corticosteroids (pH = 7.6) had a significantly higher E B C p H than steroid nai've patients (pH = 7.3) (p=0.0001). These two publications were the pioneering studies that showed the effects of disease on airway acidity. Since these studies, much research was performed to investigate changes in E B C p H in many types of respiratory disease states. Other diseases that have been investigated include cystic fibrosis where Tate and colleagues reported acidified E B C in patients with stable cystic fibrosis (meanpH 5.9) 24 and in acute cystic fibrosis patients (mean p H = 5.3) (both significantly different when compared with controls (mean p H = 6.2) (p=0.017 and p=0.001, respectively)) (Tate et al. 2002). Ojoo et al. also found similar results between E B C acidification and stable C F , and a further decline in E B C p H after acute exacerbations (Ojoo et al. 2005). Similarly, Carpagnano and colleagues also decreased E B C p H in children with cystic fibrosis and asthma (Carpagnano et al. 2004), while patients with chronic cough also had lower E B C p H than controls (mean p H = 7.9 vs. p H = 8.3, p < 0.0001) (Ni imi et al. 2004). 2.14.3 Ammonia/Ammonium It has been demonstrated that airway epithelial cells expresses the m R N A for two isoforms of glutaminase and that this enzyme catalyzes the reaction that converts glutamine to ammonia in vitro (Hunt et al. 2002). Gessner and colleagues reported that the E B C p H and NH4+ o f patients with acute lung injury were lower (mean p H = 5.9, 26.5 u M respectively), compared to control subjects (mean p H = 7.5, 222.8 u M respectively) (p<0.0001) (Gessner et al. 2003). The authors also reported a significant correlation of p H and N H 4 + (r=0.52, pO.OOl) . Carraro et al. investigated the acid-base equilibrium in E B C by measuring levels of p H and NH3 in stable allergic, asthmatic children. The authors reported significantly lower levels of E B C p H and NH3 in both the steroid-treated and steroid-untreated asthmatic group, when compared to the control group. A s well , E B C p H and N H 3 levels in the steroid-treated asthmatic group had higher levels than the steroid-untreated asthmatic group. The authors also reported a significant positive correlation between N H 3 and p H (Carraro et al. 2005b). In contrast, MacGregor et al. reported in a similar study that no significant difference in E B C p H in children with chronic asthma (median pH=6.1), compared to controls (mean pH=5.9) (p=0.14). A s well , in children treated with corticosteroids during an acute exacerbation of asthma, the authors did not notice a significant difference in E B C p H over time. However, significantly lower concentrations of E B C N H 4 + were found in children with asthma (median 258 u M ) , compared to controls (median 428 uM) . There was also no correlation between N H 4 + and p H (r=-0.253, p=0.052) (MacGregor et al. 2005). 2.14.4 Mechanisms of acid-base equilibrium There are several mechanisms by which protons can accumulate in the airway lining fluid endogenously, one o f which involves inflammation in the airways. The biological mechanisms for p H and airway inflammation in asthma and COPD/bronchiestasis are complex and not entirely known. When the airways become irritated, a range of immune cells (neutrophils and eosinophils) and other cell types are recruited to the site. Particularly in C O P D and bronchiectasis, it has been suggested that acidity in the airways is induced by the enzyme, neutrophil myeloperoxidase, which catalyzes the reaction between hydrogen peroxide and a chloride to form a highly volatile acid in hypochlorous acid (Hunt et al. 2000). The colonization of live bacteria in the airways of C O P D and bronchiectasis patients and leukocyte metabolism could also contribute to the airway fluid acidity (Hunt et al. 2000). These mechanisms could partly explain the low airway p H in C O P D and bronchiecstasis patients. In asthmatic patients, a similar mechanism has been proposed involving eosinophils and neutrophils. During 25 eosinophilic inflammation, the enzyme eosinophil peroxidase catalyzes the reaction between hydrogen peroxide and a halide to form hypohalous acids (Hunt et al. 2000). These hypotheses are supported by Kostikas et al., who have shown that E B C p H values decrease as neutrophil counts increase in the induced sputum o f subjects with C O P D (Kostikas et al. 2002). Similarly, the authors reported a negative correlation of E B C p H and eosinophil counts in induced sputum. Kostikas et al. also notes that these hypotheses are supported by studies that have reported high concentrations of neutrophils in the sputum of patients that had undergone asthma exacerbations (Fahy et al. 1995, Kostikas et al. 2002). 2.15 Conclusion E B C collection holds promise for applicability in occupational field studies due to its simple and non-invasive nature. Although there are debates over some methodological concerns and features of E B C , a diagnostic test that is non-invasive, health risk free, simple to perform, and which could be used to sample fluids from the lower respiratory tract is very appealing. 26 CHAPTER 3. METHOD DEVELOPMENT AND EVALUATION 3.1 Overview Currently, there are many methodological issues relating to the collection, storage, and processing of the E B C test. These issues stem mainly from a lack of standardization for the E B C test. The purpose of the laboratory component of this study was to develop a procedure for our laboratory that would be suitable for an occupational setting to collect, store, and process E B C . The initial stages involved performing repeated E B C tests to understand the function and intrinsic properties of the breath diagnostic tool. Several methodologic factors were evaluated to determine the effects of certain laboratory conditions on the volume, p H , and N H 4 + measurements. The within-and between-person variability o f the p H and N I L * measurements in non-smokers and smokers was also evaluated. Subsequently, a standard procedure suitable for the collection of E B C in grain elevator sites was developed. 3.2 Objectives 1. To develop a standard procedure for our laboratory for the collection of exhaled breath condensate that is suitable for occupational field measurements; 2. To develop a standard procedure for our laboratory for the measurement o f p H and N H 4 + , both biomarkers of airway inflammation, in E B C ; 3. To assess the within-person and between-person variability of p H and N H 4 + in E B C of smokers and non-smokers. 4. To assess the difference of two different storage and collection methods on p H and N H 4 + of E B C . 3.3 Participation and confidentiality The subjects for the laboratory study were recruited by poster advertisement. The subjects for the within- and between-person variability part of the laboratory study were paid a monetary honorarium o f forty dollars for their participation in the study. Before the study began, the subjects gave informed consent that participation in this study was entirely voluntary and that they were able to withdraw at any time during the testing (see appendix 1). The subjects were instructed to not eat acidic foods or drink alcohol prior to their visit (see appendix 2). A s well , the subjects participated in a short respiratory health questionnaire that was adapted from the questionnaire used in the larger grain elevator study (see appendix 3). Personal identifiers were not released and all information was deemed confidential. The study was approved by the Cl inical Research Ethics Board (certificate number: C03-0411) of the University of British Columbia before the beginning of the study. 27 3.4 Methods 3.5 Exhaled breath condensate collection The collection of E B C was performed using the Rtube™ equipped with a 0.3 micron filter, obtained from Respiratory-Research (Charlottesville, V A , U S A ) . The Rtube™ is a hand-held, disposable, polypropylene exhaled breath condensate collector that consists o f a mouthpiece assembly and a collecting tube. A n aluminium cooling sleeve, usually stored in a laboratory freezer, was equipped with an insulator cover and was placed over the Rtube™ to maintain a suitable temperature for the condensation process to occur (see figure 3.1). The mouthpiece assembly is "tee" shaped to reduce gross saliva contamination and the collecting tube contains a one-way duckbill valve that only allows expired air (and not inspired air) from passing through the collecting tube. The Rtube™ is held upright and this results in the condensation chamber to be at a more elevated height than the mouth, to prevent saliva from entering upwards into the area of E B C collection (see figure 3.2). The filter was attached between the mouthvalve assembly and the collecting tube to further minimize saliva contamination and to increase the proportion o f respiratory solutes that emanated from the lower respiratory tract (airways) in comparison to the upper respiratory tract (mouth). Figure 3.1. Schematic of RTube . Figure 3.2. Study subject performing the E B C test with the RTube™. 28 3.6 Protocol development and assessment The development and assessment of a standard procedure for the collection, storage, and processing o f E B C in our laboratory consisted o f several trials that addressed some methodological questions of the E B C assay. These questions include: 1. What is the effect of duration of E B C collection on E B C volume? 2. What is the effect o f condenser temperature on E B C volume, p H , and concentration of N H 4 + ? 3. What is the effect o f the use of a filter on E B C p H or N H 4 + concentration? 4. Does the duration and flow-rate of argon deaeration recommended by Hunt (Hunt et al. 2000, 694-699) stabilize E B C pH? 5. What is the effect of E B C volume on E B C p H and N H 4 + concentration ? Unless otherwise stated, the following conditions were applied for the protocol development and assessment of the E B C test. The E B C device was equipped with a filter and the cooling sleeve was stored in a laboratory freezer at -20 °C overnight. The subjects breathed through the E B C device for 15 minutes at a tidal breathing rate and did not wear noseclips. The subjects were also instructed to inhale through the nose and exhale through the mouth. The condensate was removed from the cooling sleeve and argon was bubbled through the samples at a flow-rate of 350 mL/min for 10 minutes and subsequently, the p H was measured. N H 4 + concentrations of E B C was measured using high performance liquid ion chromatography with conductivity detection. The specific methodological questions were investigated using procedures outlined in table 3.1. The reproducibility of the p H measurement was assessed by measuring the p H of the E B C samples three times consecutively within 5 minutes. A s well , after the E B C samples were removed from the freezer storage after 20 to 24 months and defrosted for N H 4 + analysis, the p H was again measured after argon deaeration at 350 mL/min for 10 minutes and compared with the average o f the initial p H measurements to determine the concordance between the measurements. 29 Table 3.1. Methodological considerations investigated in the laboratory study. Methodological Question Number of Subjects Procedure EBC Parameters Investigated Effect of duration of EBC collection on EBC volume 2 (male, female) 2 tests at each o f 10, 12, 14, 16, 18, 20 mins. (n=24 total) Duration of E B C collection, E B C volume Effect of condenser temperature on EBC volume, pH and lnNH4+ 2 (male, female) 2 tests at each o f 4, -8, and -80 °C (n=12 total) Initial condenser temperature, E B C volume, p H , and l n N H 4 + Effect of filter usage between subject and collection tube on EBC pH and lnNH4+ 2 (male, female) 4 tests each with and without a filter equipped (n=16 total) Filter Usage (Y/N) , . E B C p H and l n N H 4 + Effect of duration of argon deaeration on EBC pH 1 (male) 4 tests; p H measurement after 0, 5, 10, and 15 minutes of argon deaeration (n=4 total) Duration of argon deaeration, E B C p H Effect of flow-rate of argon deaeration on EBC PH 1 (male) 4 tests each at 350 mL/min and 2 L/min (n=8 total) Flow-rate of argon deaeration, E B C p H Effect of sample volume on EBC pH and InNH/ 10(2 male non-smokers and smokers, 3 female non-smokers and smokers) 6 tests each; each test performed on a different day over a period of ~ 1 month (n=60) Sample volume, E B C p H and l n N H 4 + 3.7 Exhaled breath condensate collection procedure From the results of the protocol development and assessment (see results section), a standard procedure for the collection of E B C was developed. The steps are outlined below. 1. Store the cooling tubes in a freezer at -20 °C for at least 6 hours (or overnight) prior to the E B C test. 2. Assemble the E B C breathing device and ensure all the junctions are as tight as possible. 3. Have the subject rinse his/her mouth several times with water immediately prior to the E B C test. 4. Seat the subject on a chair. 5. Instruct the subject to inhale through the nose and exhale through the mouth at a tidal breathing rate when performing the E B C test. 30 6. Have the subject perform the E B C test, without noseclips, at a tidal rate for 15 minutes. Forced breathing should be avoided. 7. Obtain the E B C collecting tube from the subject, and plunge the collecting tube using the plunger provided by RespiratoryReseach (Virginia, C A , U S A ) . 8. Extract the E B C sample from the collection tube using a sterile syringe. 9. Measure the volume of E B C sample using the same sterile syringe. 10. Place the E B C sample into a 3 m L polypropylene vial . 3.8 Argon deaeaeration procedure Argon deaeration was performed on the samples to remove dissolved C O 2 and stabilize p H readings in the E B C samples. Dissolved C O 2 can make the E B C p H more acidic by combining with water to produce H 2 C O 2 and subsequently release H+ and H C O 2 " into the solution. The following steps were used in the procedure: 1. Before the measurement o f p H , the dissolved C O 2 in the E B C was removed by bubbling inert argon gas through the samples. The procedure was followed as described by Hunt et. al (Hunt et al. 2000). 2. The E B C samples were deaerated with argon at 350 mL/min for 10 mins. 3. The flow-rate was adjusted to 350 mL/min by a DryCal D C - L i t e primary flow meter (Bios, Butler, NJ) every sampling day. 4. Plastic tubing was attached to the argon tank and a glass pipette was attached at the other end of the plastic tube. 5. With the flow-rate o f the argon tank adjusted, the glass pipette was placed in the E B C sample for 10 minutes to allow for the bubbling process to occur. The pipette was placed in the center o f the sample such that the surface tension of the sample was broken. 6. The glass pipette was removed from the sample, but was still held close to the surface of the E B C so that argon gas surrounded the surface of the E B C to minimize ambient C O 2 from coming in contact with the sample. This was performed during the entire time of measuring the p H o f the sample. 7. The measurement of p H in the samples was then performed. 3.9 pH measurement procedure A n Orion model 720A p H meter (Orion, Boston M A ) with an Accumet microprobe (Fisher Scientific, Pittsburgh P A ) was calibrated each time a set of E B C samples were to be measured. The steps for the set-up and calibration of the p H meter are outlined below. 1. Calibrate the p H meter using 2 calibrating buffers of p H 4.01 and 7.00. 2. Wash the Accumet microprobe using distilled water. 3. Place the microprobe in the vial containing the E B C sample and stir gently. 4. Wait until the meter reading stabilizes, such that the measured p H fluctuates between two readings. 5 Record the measured p H . 6. For repeats of p H measurement, repeat steps 2 to 6. 31 3.10 NH 4 + analysis procedure N H 4 + concentration was measured by high performance liquid ion chromatography (Dionex, Sunnyvale C A ) with conductivity detection. The procedural steps for batch analysis o f E B C samples are outlined below. 1. Samples were defrosted from the -80 °C freezer. 2. A 125 u L aliquote of each sample was transferred to 0.5 m L Dionex Poly V i a l and diluted with the addition of 575 u L of de-ionized M i l l i Q water (total volume o f 700 uL). Sample factor therefore was 125uL/700 u L which is equal to a sample factor of 5.6. 3. If there was insufficient amount of sample, the final volume of 700 u L was still maintained in the sample vial and the dilution factor was noted. A n appropriate sample factor was applied to the final determined concentration 4. A six point quadratic calibration curve of ammonium choride (NH 4 C1) was run by preparing a set of standards prior to the analysis (reference method: N I O S H Method 6016). 5. A set of calibration standards was run at the beginning and the end o f each batch. 6. After preparation, all the E B C samples and calibration standard were placed in the HP-IC autosampler and run on a Dionex-300 HP-IC in batch mode 7. For every 12 samples, a single calibration standard (quality control run) was repeated to check the performance of the HP- IC during the batch. 8. Duplicate samples were run during the batch analysis for every 18 samples to check method accuracy. The limit o f detection was 0.50 umol/L. 3.11 Evaluation of the standard procedure, evaluation of the within- and between-person variability After a standard procedure for E B C collection had been established, the protocol was checked with six different subjects (3 men, 3 women). This was performed to assess the E B C volume collected on subjects who have performed the E B C test for the first time because of the possibility that subjects who have performed the E B C test multiple times may have become accustomed to breathing through the collection device and therefore, resulting in higher E B C volumes in latter trials in comparison to initial trials. The within and between person variability of E B C p H and N H 4 + concentration was also evaluated in our laboratory by collecting 6 samples (1 per day) from 10 subjects (5 non-smokers and 5 smokers) over a period o f approximately one month. 3.12 Comparison of two different sample storage methods In the field study (see section 4.1), there was difficulty transporting the necessary equipment required to measure the E B C p H directly at the worksite. Therefore, p H analyses for E B C collected in the field were performed after field collection, when the samples were transported to the laboratory. Therefore, to test two different sample storage methods and their effect on E B C p H and l n N H 4 + , the re-assessment was performed on the same 10 subjects who had 32 participated in the within and between person variability tests by performing an additional test immediately following the first test on days one and two. The two different sampling methods are outlined below. 3.12.1 Method A (measuring pH prior to initial sample freezing) 1. Perform the outlined steps of the E B C collection procedure (see section 3.7). 2. Flush the E B C sample with argon gas at a flow-rate of 350 mL/min for 10 minutes (see section 3.8). 3. Perform the outlined steps of the p H measurement procedure (see section 3.9). 4. Pipette 0.005 % (10 uL per 1 m L of sample) butylated hydroxytoluene (BHT) in ethanol into E B C sample. 5. Freeze at -20 °C for 8 hours. 6. Freeze at -80 °C until ready for further lab analysis. 3.12.2 Method B (measuring pH after freezing sample for 8 hours) 1. Perform the outlined steps of the E B C collection procedure (see section 3.7). 2. Freeze the E B C sample at -20 °C for 8 hours. 3. Defrost the E B C sample. 4. Flush the E B C sample with Argon gas at a flow-rate of 350 mL/min for 10 minutes (see section 3.8). -5. Perform the outlined steps of the p H measurement procedure (see section 3.9). 6. Pipette 0.005 % (10 u L per 1 m L of sample) B H T into the E B C sample. 7. Freeze at -80 °C until ready for further lab analysis. 3.13 Data analysis The data were checked for completeness and accuracy and then entered into an excel spreadsheet. A l l analyses were performed using the statistical analysis software, S A S for Windows, version 9.1 (SAS Instititute, Cary N C ) . The analysis for the effect of sampling time on sample volume, the effect of cooling sleeve temperature on sample volume, and the effect of argon duration and its effect on p H was performed qualitatively. The comparison of temperature groups and its effect on E B C p H and I n M L * concentration, as well as the effect of the use of a filter on p H and I n N H / concentration were performed by analysis of variance (Proc G L M with C L A S S statement). Comparison of two different flow-rates of argon deaeration and its effect on p H was analyzed using simple linear regression (Proc R E G ) . The effects of sample volume on p H and I n N H / were analyzed using a mixed effects model (Proc M I X E D ) . A s well , a mixed effects model (Proc M I X E D ) was used to analyze the within and between-person variability of E B C p H and l n N H 4 + concentration in non-smokers and smokers. 33 3.14 Results 3.15 Participation A total of 18 subjects, who had performed a combined total of 146 E B C samples, participated in the laboratory component of the study. Most of the subjects were recruited from the university campus. Most of the subjects responded favourably to performing the E B C test, describing it as simple and easy to perform. Two subjects complained of dizziness when performing the E B C test, which may be attributed to slight hyperventilation. In these instances, the E B C test was simply stopped until the dizziness subsided, after which the test was restarted again. There was a very high compliance rate with the subjects in successfully performing the E B C test, as the only exception was in one instance, there was insufficient E B C volume produced due to faint breathing. In this instance, the test was repeated and the subject was asked to breathe harder, but still at a tidal breathing rate. 3.16 Method development and assessment 3.17 Effect of sampling time on sample volume The evaluation of the timing conditions for the E B C protocol was performed in two subjects. Volumes ranging from 0.8 and 2.1 m L were obtained from the first subject, while values ranging from 0.9 and 2.1 m L (see figure 3.3) were obtained from the second subject. In both cases, there was a non-linear increase in volume as time increased, which appears to plateau at about 18 minutes. Fifteen minutes was chosen for the standard procedure because it provided an adequate volume o f E B C without placing unreasonable demands on the participant's time. Figure 3.3 - Effect of E B C collection time on E B C volume. 2.0H 2.5H 6 8 o 0 o 8 8 E 3 O 1.0-o o o o o o 0 0.5 H 0.0 10 12 14 16 18 20 Duration (mins) 3.18 Effect of cooling sleeve temperature on sample volume Cooler temperatures of the cooling sleeve produced a higher sample volume yield (Figure 3.4). A primary concern was the formation o f ice crystals or snow in the collecting tube during E B C testing, due to the cooling sleeve being too cold. It was observed that the cooling sleeve stored in the -80 °C freezer produced snow during the first 2 minutes of the E B C test in all trials. However, the cooling sleeves stored in the -20 °C freezer and 4 °C fridge did not appear to produce ice crystals or snow. Therefore, a laboratory freezer temperature of -20 °C was used at the grain elevator sites for the storage of the cooling sleeves during field sampling in order to maximize sample volume yield. Figure 3.4. Effect of initial condenser temperature on E B C volume. 3.5-3.0-2.5-_ l E £ > 1.0-1 o 9 Subject O i 02 o o o 0.5H 0 0_, ! ] ! -80 -20 4 Temperature of Cooling Sleeve (Celsius) 3.19 Reproducibility of pH measurements The short term variability of pH was minimal (mean (sd) coefficient of variation of 0.17 % (0.16) with a range of ~0 - 1.2 %). There was also good concordance between the initial p H measurements and the pH measurements after the E B C samples were removed from storage for the laboratory study (mean pH difference -0.007, sd 0.35, range 1.56) and the field study (mean pH difference 0.40, sd 0.33, range 1.44). 3.20 Correlation of pH and NH 4 + There was a significant correlation between E B C p H and N H 4 + (uM) (r=0.37, p<0.0001, n=l 16 total) (see figure 3.5). A higher correlation was found between E B C p H and the natural logarithm of N H 4 + (Ln(pM)) (r=0.63, p<0.0001, n=l 16 total) (see 35 figure 3.6). In both comparisons, low pH values had low NH4 values, but low levels of NH4+ were seen in both low and high pH samples. Figure 3.5. Correlation o f NH.4 + and pH Figure 3.6. Correlation of l n N H 4 + a n d p H . concentration. ,„Su Smff. t 5 Z 4 4r° pH PH 3.21 Effect of condenser temperature on pH and lnNrL;+ The mean (sd) p H values of the condenser temperature groups of -80, -20, and 4 °C were 7.69 (0.068), 7.68 (0.16), and 7.61 (0.16) respectively (see figure 3.7). The means (sd) of the condenser temperature groups of -80, -20, and 4 °C for l n N H 4 + were 5.36 (0.98), 6.27 (0.66), and 5.85 (0.55) respectively (see figure 3.8). There appeared to be no association, as the condenser temperature did not have a significant effect on either the p H (p=0.65) or l n N H 4 + (p=0.28). Figure 3.7. Effect of initial condenser temperature on pH. 8.0H 7.5H © o o o c 8 o o Subject O i 02 Q . 7 . 0 J 6.5 H 6.0 -80 T 4 Temperature of Cooling Sleeve (Celsius) Figure 3.8. Effect of initial cooling sleeve temperature on l n N H 4 + . 7-i o o 3 0 o o o 0 o o o o 4 -80 -20 4 Temperature of Cooling Sleeve (Celsius) 3.22 Effect of the use of a filter on E B C p H and l n N H 4 The mean (sd) pH values for the group that did not equip a filter between the mouthpiece and the collecting tube during E B C collection was 7.70 (0.10), while the mean p H for the group that did equip a filter between the mouthpiece and the collecting tube during E B C collection was 7.68 (0.15) (see figure 3.9.). For l n N H 4 + , the mean (sd) p H values for the groups that did and did not equip a filter between the mouthpiece and the collecting tube during E B C collection was 5.25 (0.79) and 5.57 (0.73) respectively (see figure 3.10). The filter did not have a significant effect on either the p H (p=0.81) or l n N H 4 + (p=0.42). 37 Figure 3.9. Effect of the use of a filter on p H . Subject O i 02 Yes Filter Figure 3.10. Effect of the use of a filter on l n N H 4 + . Subject O i 02 Filter 3.23 Effect of the duration and flow-rate of argon deaeration on p H The pH initially was in the 6.0 to 6.5 range. There was an increase in p H in the range of 7.5 to 8.0 after the first 5 minutes of argon deaeration (See figure 3.11). After this time period, the p H stabilized, remaining in the range of 7.5 to 8.0. In general, deaeration with argon caused an overall increase o f approximately 2 log orders in p H . The mean pH for the 350 mL/min group was 7.91 (0.030), while the mean p H for the 38 2000 mL/min was 7.78 (0.035). The p H of samples collected with flow-rate of 350 mL/min was statistically higher than the flow-rate of 2000 uL/min (p=0.0012) (see figure 3.12). Figure 3.11. Effect of the duration of argon Figure 3.12. Effect of the flow-rate deaeration at constant 350 mL/min on p H . of argon deaeration on p H . 350 2000 Duration of Argon Dearation (mins) Flow-rate of Argon Deaeration (mL/min) 3.24 Effect of volume on p H and l n N H 4 + The relationships between E B C volume and pH or l n N H 4 + are shown in figures 3.13 and 3.14 below. A mixed effects model (to take repeated measures into account) indicated no significant association for E B C volume and either pH (p=0.47) or l n N H 4 + (p=0.77). 39 Figure 3.13. Effect of volume on pH. 8H 7 -I CL 6H pH = - 0.019 * (Volume) + 7.81 o 8 , , , , f— 0.0 0.5 1.0 1.5 2.0 2.5 Volume (mL) Figure 3.14. Effect of volume on l n N H 4 + . 3 0 Subject o r 02 3 0 4 5 _ O s " 07 8 09 OioJ Never Smoker Current Smoker Subject o r 0 2 3 0 4 5 _ 0 6 ~ 07 8 09 OioJ Never Smoker Current Smoker Volume (mL) Confirmation of the overall feasibility of the final E B C sampling protocol was performed on six subjects (3 men and 3 women) (Figure 3.15), who had never performed the E B C test. This was to assess the volume of E B C gathered on subjects who were particularly unfamiliar with this test, similar to what would be expected during field sampling. This was performed to ensure a sample volume o f at least one m L from each subject, which is sufficient volume to perform the required laboratory analyses. A l l six 40 of the subjects had volumes over 1 m L . There was a median of 1.53 m L with a range of 1.28 m L . Figure 3.15. Reliability of the final E B C protocol. 2 .5- o o 2.0-O £ 1-5-3 o O O O > 1.0-0 . 5 -« • » — I — —1 1 1 1 1 1 2 3 4 5 6 Subject 3.25 Within- and between-person variability The variability of E B C pH within- and between-persons was also investigated in non-smokers and smokers (n=5 each) (Figure 3.16). The global mean for non-smokers was 7.61 (SE 0.030). The between-person variability for non-smokers was negligible (~ 0) and the within-person variability was small (variance 0.027, SE 0.0071). The global mean for smokers was 7.25 (SE 0.31), less than the global mean for non-smokers. However, a comparison o f global means o f non-smokers and smokers was not significant (p=0.069). For smokers, the between-person variability (variance 0.36, SE 0.35) and the within-person variability (variance 0.77, SE 0.22) were both larger than that seen in non-smokers. The within- and between-person variability of I n N H / was also investigated in non-smokers and smokers (Figure 3.17). The global mean for non-smokers was 5.88 (SE 0.20), which is slightly higher than the global mean for smokers (5.68, S E 0.43) but not significant (p=0.43). The between person variability for non-smokers was small (variance 0.14, SE 0.14), but the within- person variability was larger than for pH (variance 0.35, SE 0.099). For smokers, the between-person variability (variance 0.84, SE 0.66) and the within-person variability (variance 0.57, SE 0.16) were both larger than among non-smokers and as that seen in the within- and between-person variability for pH. 4 1 Figure 3.16. Within- and between-person variabilitity o f p H in non-smokers and current smokers. Smoking Status O Never Smoker O Current Smoker Subject Figure 3.17. Within- and between-person variability of l n N H 4 + in non-smokers and current smokers. Smoking Status O Never Smoker O Current Smoker Subject Analyses to test whether the apparent differences in p H or l n N H 4 + values between smokers and non-smokers were significantly different (mixed effects models to take repeated values on the same subject into account) showed no significant effects of smoking status (p=0.29 for p H , p=0.70 for l n N H 4 + ) . 42 3.26 Comparison of two sampling storage methods There was no significant effect of different storage methods and freeze-thaw protocols on either p H or l n N H 4 + by itself (p=0.57, p=0.54 respectively), or when adjusting for smoking status (see figure 3.18 and table 3.2 for pH; figure 3.19 and table 3.3 for l n N H 4 + ) . Table 3.2. Mixed effects model of p H adjusting for smoking status, and sample storage method. Variable Coefficient P Intercept 7.63 (0.12) <0.0001 Smoke -0.11 (0.16) 0.51 E B C Method (0=Freeze, l=Freeze/thaw) -0.034 (0.058) 0.57 Table 3.3. Mixed effects model of l n N H 4 + adjusting for smoking status, and sample storage method. Variable Coefficient (SE) P Intercept 6.43 (0.23) <0.0001 Smoke -0.56 (0.32) 0.12 E B C Method (0=Freeze, 1 =Freeze/thaw) 0.083 (0.13) 0.54 Figure 3.18. Effect of freeze-thaw on pH. Day - Storage Method O 1 - Freeze O 1 - Freeze/Thaw 2 - Freeze O 2 - Fieezerthaw Never Smoker Current Smoker Subject Figure 3.19. Effect of freeze-thaw on l n N H 4 + . 8 H ^ 7-s If T'6' X 5 o 0 o o o o o o e G o o R o o 8 Day - Storage Method O 1 - Freeze O 1 - Freeze/Thaw 2 - Freeze O 2 - Freezerthaw "~I 1 1 1 1 1 1 1 1 1 -, 1 2 3 4 5 , , 6 7 8 9 10 | Never Smoker Current Smoker Subject 44 C H A P T E R 4: F I E L D S T U D Y 4.1 Overview The 9 cross-sectional grain study was the most recent in a series o f studies performed by the U B C Occupational Lung Diseases Research Unit to investigate the respiratory health of grain elevator workers in terminal grain elevators in B C . On-site testing of grain elevator workers began in September 2003, and was completed in February 2004. A l l workers in five terminal grain elevators in the port of Vancouver were invited to participate in the study., The study was performed at each site daily for approximately two weeks per site. Two trained interviewers administered a standardized respiratory questionnaires and allergy skin tests. A pulmonary technician conducted spirometry and an occupational hygienist and two assistants performed personal and area exposure monitoring. A report describing the overall results of this study has been submitted to the Vancouver Terminal Elevators' Association (Ward et al. 2004). 4.2 Objectives 1. To measure p H and NH4+, biomarkers of airway inflammation, in exhaled breath condensate among a subset of grain elevator employees at the worksites; 2. To investigate exposure-response relationships between the measures obtained from the exhaled breath condensate test and personal exposure to grain dust and endotoxin; 3. To investigate the role of other risk factors for inflammation as potential confounders of these associations (cigarette smoking, history of asthma, atopy, age). 4.3 Confidentiality Prior to participating in the study, the workers gave informed consent with a consent form that outlined their rights as subjects (see appendix 1). Confidentiality of all personal identifiers was ensured. The field component of the study was approved by the Clinical Research Ethics Board o f U B C (certificate number: C03-0411) before beginning field sampling. 4.4 Study design The field study was 'nested' in the larger grain cross-sectional study o f all eligible employees in five terminal grain elevators in the port of Vancouver, B C , A target sample size of approximately 80 subjects (approximately 16 participants per grain elevator) from the larger cross-sectional study was planned. The E B C test was carried out on approximately eight subjects per day, for a total of two days at each elevator site. The subjects were chosen randomly from within specific job titles. The same subjects also wore personal exposure pumps and completed a short personal sampling form/questionnaire. Grain elevator employees with 8 different job titles were selected as representative of the complete range of worker exposure levels to particulate matter and endotoxin. The job titles that were selected included cleaner, panel control operator/ quality control operator, 45 trackshed, sheetmetal, electrician, millwright, gallery/distributor/bin top/annex, general labourer/sweeper, pellet plant operator, basement, and supervisor. 4.5 Participation and study population The subjects for the field study were recruited with the help o f a work supervisor at the grain elevator site. A total of 88 subjects participated in the study between October, 2003 and December, 2003. These subjects underwent personal exposure sampling on the same day that the E B C test was performed. These subjects also had performed spirometry tests and skin prick tests and answered personal sampling questionnaires and general health questionnaires. 4.6 Methods The procedures for personal exposure monitoring to grain dust, standardized respiratory questionnaire, lung function and allergy testing were performed by personnel from the Environmental and Occupational Lung Diseases Research Unit and the School of Occupational and Environmental Hygiene at the University o f Brit ish Columbia, as part of the larger cross-sectional grain study. These procedures w i l l be summarized below, but more details can be found in a report submitted to the Vancouver Terminal Elevators Association by Ward et al. (Ward et al. 2004). 4.7 Personal exposure measurements All-subjects who were included in the data analysis component of the E B C study had personal exposure monitoring carried out on the same day that the E B C test was performed. Personal exposure monitoring typically covered the entire work shift, which generally lasted at least six hours. It was performed by an occupational hygienist and two assistants. 4.7.1 Grain dust Each subject wore a portable constant-flow sampling pump ( S K C , Eighty-Four, P A , U S A ) that was attached to a 7-Hole inhalable aerosol sampler (JS Holdings Ltd. , Stevanage, U K ) that contained a 25 mm diameter, type A / E glass fiber filter (Pall Gelman Sciences, A n n Arbor, M I , U S A ) . The pump was calibrated at a flow-rate of 2.0 L/min using a rotameter (Matheson Tri-gas, Montgomeryville, P A , U S A ) before and after each sampling shift. Attached to the pumps, were sampling cassettes that contained pre-weighed filters that were equilibrated to a stable temperature and a relative humidity. The pump was attached to the subject's belt and the sampling cassette was attached to their collar, near the breathing zone. The device drew in ambient air during the subject's work shift, which typically covered the beginning and end of the shift. The sampling device was operating during breaks, as well as during the time that the subjects came in to perform the E B C test. The time that the pump was turned on and off, as well as the sampling time that was displayed on the pump, was recorded. After the work shift, the sampling cassettes were transported from the field site to the laboratory, where the filter 46 air samples were desiccated, and re-equilibrated to the same stable temperature and relative humidity pre-weight. Gravimetric measurement of the samples was determined using a micro-balance (M3P, Sartorius, Germany). The samples were stored at 4 °C for endotoxin analysis. 4.7.2 Endotoxin Endotoxin extraction was performed on all filter samples and a kinetic limulus amoebocyte lysate ( L A L ) assay was performed (BioWhittaker Kinetic Q C L ™ , Cambrex Biomedicals). The samples were placed in a 50 m L conical centrifuge tube and 10 m L pyrogen-free water was added to completely immerse the filter. The samples were vortexed briefly, and placed on a rotating shaker platform for 60 minutes. The tubes were then transferred to a sonicator bath for 60 minutes. The tubes were vortexed again followed by centrifugation to remove particulate matter. Supernatant was transferred to pyrogen-free glass vials. Serial dilutions of endotoxin standard (EC 055 :B5) were prepared (50 - 0.049 EU/ml ) . Samples were also serially diluted. Aliquots of 100 uL of standard, samples or pyrogen-free water blanks were placed in a 96 wel l microtitre plate. The plates were incubated at 37 degrees Celsius for 15 minutes, after which 100 u.L L A L reagent was added to all wells. The reaction was read in a Spectromax 190 microplate reader (Molecular Devices, Sunnyvale, C A , U S A ) where rate o f colour development was measured every 30 seconds for 1 V2 hr. The endotoxin concentration was calculated by fitting to a 4-parameter curve of the maximum rate of the colour reaction of the standards. 4.8 Health outcome measurements 4.8.1 Standardized respiratory questionnaire The respiratory questionnaire used in the grain study was based on standardized instruments recommended by the American Thoracic Society (Ferris. 1978)(Ferris 1978, 1-120) and the I U A L T D (Burney et al. 1989). The questionnaire covers health history, including acute and chronic respiratory symptoms such as cough, phlegm and wheeze, as well as smoking habits and other previous illnesses. The questionnaire also included questions about family history, job history, and current work. Two trained interviewers administered the questionnaire. 4.8.2 Spirometry Each subject performed spirometry using a dry rolling seal spirometer (model V R S 2000, S & M Instrument Co.) following a standard protocol based on recommendations from the American Thoracic Society (ATS 1995). While seated and wearing a noseclip, the subjects were asked to inhale to full inspiration, and then forcibly exhale maximally for as long as possible. The forced expiratory volume in the first. second (FEV1) , forced vital capacity ( F V C ) , forced expiratory flow (FEF25-75%), and the ratio of F E V 1 / F V C was measured. These results were calculated as percent of predicted values, adjusting for age, sex, height and race (Crapo et al. 1981). 47 4.8.3 Allergy skin test A n allergy skin test was performed on all the subjects to assess allergic predisposition, using four common allergens: house dust mites (Dermatophagoid.es farinae, Dermatophagoides pteronyssinus), mixed grass pollen, and common weed mix. Histamine and saline were used as a positive and a negative control, respectively. Diameter of the wheal reaction was measured 15 minutes after applying the allergens. Atopy was considered to be at least one positive skin reaction to the allergens that had a diameter of at least 3 mm greater than that of the negative control. 4.8.4 Exhaled breath condensate collection Each subject performed the E B C test once. The testing was carried out at various times throughout the day, following the collection procedure as outlined in the methods section of chapter 3. The subjects rinsed their mouths with water before,performing the test. Subjects performed the E B C test without noseclips for 15 minutes after which the sample was collected and stored in a portable freezer at -20 °C. After field sampling was completed for the day, the samples were stored in an icebox and transported to the U B C S O E H laboratory. The E B C samples were defrosted and p H analyses were carried out at the end of the testing day. The E B C samples were also stored in an -80 °C freezer for 20 to 24 months until NH4+ analyses were carried out. 4.9 Data analysis The following null hypotheses were used to direct the data analysis: Primary null hypothesis 1: There is no association between the concentration of p H or ammonia in exhaled breath condensate and markers of exposure (ie. the concentration of personal exposure to grain dust or endotoxin measured on the same day) among grain elevator workers. Primary null hypothesis 2: There is no association between the concentration of p H or ammonia in exhaled breath condensate and exposure according to work characteristics (ie. job title, number of years employed, number of hours worked before performing the exhaled breath condensate.test) among grain elevator workers. Secondary null hypothesis: The associations between the biomarkers in exhaled breath condensate and exposures are not modified by other factors, such as cigarette smoking, history of asthma, atopy, age, obesity, and F E V 1 % predicted. A l l the data were checked for completeness and accuracy, and then coded for entry into a excel spreadsheet or ascii dataset. A l l analyses were performed using the statistical analysis software, S A S for Windows, version 9.1 (SAS Institute, Cary N C ) . A description of the study population was outlined, detailing certain demographic features and work and exposure characteristics, and respiratory health outcomes of the study population. Certain demographic characteristics of the E B C study population was 48 compared with the larger grain study population to check for any potential selection biases between the two populations. A list o f potential independent variables that were believed to have an effect on E B C biomarkers was generated. The distributions of each independent variable were examined (using Proc U N I V A R I A T E P L O T for continuous variables and Proc F R E Q for categorical variables) to ensure that each distribution contained enough variability. Possible confounding between independent variables was also assessed using a correlation matrix (Proc C O R R ) . Univariate analysis was performed between each independent variable and both p H and lnNH4+. T-tests or analysis of variance (both Proc G L M ) were used to compare categorical distributions with p H and lnNELt"1", while simple linear regression (Proc R E G ) was used to compare continuous variables with p H and lnNH 4 +. Mul t ivar ia te analyses were performed using multiple linear regression (Proc R E G ) , with E B C p H or InNrlV as the dependent variable, and other variables that were significant (p<0.05) or marginally significant (p<0.10) in the univariate analysis as the independent variables. The variables from the primary null hypotheses and variables that were expected to be associated with E B C acid-base equilibrium based on theory or • previous studies, such as asthma and the markers of exposure and exposure according to work characteristics were also tested in the model. As an exploratory analysis, i f an explanatory factor was significantly associated with the health outcome, the population was stratified according to that factor and the same multiple linear regression model was applied to examine the association between the health outcome and the exposure measurements, in stratified samples. 49 4.10 Definitions Obesity (kg/cm2) (as defined by Health Canada (Lemieux et al. 2004)): Obese: > 30 Moderately Obese: 25 - 30 Normal: < 25 Asthma status: 1. Have you ever had asthma? 2. Do you still have it? Current: Yes to both questions 1 and 2 above. Former: Yes and N o respectively to questions 1 and 2 above. Never: N o to both questions 1 and 2 above. Smoking status: 1. Have you ever smoked cigarettes (No means less than 20 packs of 20 cigarettes or less than one cigarette a day for one year), pipe (Yes means more than 12 oz. of tobacco in a lifetime), or cigars (Yes means more than 1 cigar a week for a year)? 2. Do you now smoke cigarettes (as of 1 month ago), pipe (as of 1 month ago), or cigars (as of 1 month ago) Current: Yes to both questions 1 and 2 above. Former: Yes and N o respectively to questions 1 and 2 above. Never: N o to both questions 1 and 2 above. Chronic respiratory symptoms (Yes to the following; each symptom considered separately): Chronic cough: Do you usually cough most days for 3 consecutive months or more during the year? Chronic phlegm: Do you usually bring up phlegm most days for 3 consecutive months or more during the year? Breathlessness: Are you troubled by shortness o f breath when hurrying on the level or walking up a slight hill? Occasional wheeze: Does your chest ever sound wheezy or whistling occasionally apart from colds? Acute respiratory symptoms in the past 12 months (Yes to the following; each symptom considered separately): Woken with chest tightness: Have you woken up with a feeling of tightness in your chest? Woken by cough: Have you been woken by an attack of coughing? Woken by breathlessness: Have you been woken by. an attack of shortness of breath? Breathless during the day: Have you had an attack of shortness of breath that came on during the day when you were not doing anything strenuous? Breathless after exercise: Have you had an attack of shortness of breath that came after you stopped exercising? 50 Other respiratory symptoms in the past 12 months (Yes to the following, each symptom considered separately): Ever wheeze: Have you had wheezing or whistling in your chest, when you did not have a cold? Asthma-like symptoms: Yes , i f 2 or more symptoms of woken with chest tightness, woken by cough, woken by breathlessness, breathless during the day, breathless after exercise, and ever wheeze. Job titles: Office jobs: panel control operator, quality control operator, supervisor, custodian Tradesperson: sheetmetal, electrician, millwright Inside elevator: cleaner, gallery, distributor, bintop, annex Other: trackshed, pellet plant operator, basement Work area: Seed and pellet plant: pellet plant, seedmill/plant Inside elevator: distributor floor, all floors, bintops/annex, gallery, annex, cleaner floor, basement Trackshed: trackshed/pit, other Office: office, panel control operator Maintenance: shops All over: throughout the elevator 51 4.11 Results 4.12 Eligible subjects A total of 88 subjects were scheduled to perform the E B C test between October, 2003 and December, 2003. Workers who did not generate enough E B C volume in the allowable 15 minutes, performed the test for five more minutes with a fresh aluminium cooling tube. Six subjects were excluded from the data analysis because they did not participate in the larger cross-sectional grain study. Two subjects also were excluded from the data analysis because they did not have a complete personal exposure measurement that day. A n additional four subjects were scheduled to perform the E B C test at the beginning o f their shift, but did not come in to complete it during that day. A s well , one subject had performed the E B C test twice and therefore, the second test was excluded from the analysis. Therefore, data from a total of 76 eligible employees from five grain elevator sites in the port of Vancouver were included for the data analysis. 4.13 Demographic characteristics Characteristics of the 76 eligible workers were shown in table 4.1, compared to the rest of the workers who participated in the larger grain elevator study. In the E B C study subset, the majority of workers were Caucasian (85 %) and male (89 %), with a mean age of 47 years, and an average weight of approximately 90 kilograms. Approximately 40 % were atopic, 10 % had current asthma, and 20 % were also current smokers. The distribution of selected variables between the two populations was not statistically different, although there was a trend of a higher percentage o f workers in the E B C study having had asthma in the past and currently. 52 Table 4.1. Demographic features of the E B C study and larger grain study. Demographic Features EBC Study Subset Grain Study P1 n 76 253 age in years, mean (sd) 46.8 (7.50) 46.5 (7.68) 0.8 weight (kg), mean (sd) 87.7(17.1) (n=75) 85.7(17.2) (n=251) 0.4 Body mass index (kg/cm2), n (%) (n=75) (n=250) <25 15 (20.0) 56 (22.4) 2 5 - 3 0 37 (49.3) 138 (55.2) 0.4 >30 23 (30.7) 56 (22.4) female, n (%) 6 (7.9) 25 (9.9) 0.6 non-caucasian, n (%) 11 (14.5) 25 (9.9) 0.3 Atopy, yes, n (%) 33 (43.4) 84 (33.2) 0.1 Asthma, n (%) current asthma 6(7.9) 11 (4.4) former asthma 7 (9.2) 10 (4.0) 0.1 * never asthma 63 (82.9) 232 (91.7) Smoking, n (%) current smoker 15 (19.7) 61 (24.1) former smoker 28 (36.8) 93 (36.8) 0.7 never smoker 33 (43.4) 99 (31.1) p value for statistical test comparing workers who participated in the E B C study to the rest of the grain workers in the larger grain study; t-test for comparing distributions; chi-squared test for comparing proportions. * Fisher exact test used because 33 % of the cells have expected counts less than 5. 4.14 Smoking characteristics The smoking status of subjects who had smoked or are currently smoking cigarettes, pipes, or cigars was also determined. The definitions of never smoker, former smoker, and current smoker are defined in section 4.10. A cigarette conversion factor of 1 cigar equal to 2.5 cigarettes, and 1 gram of tobacco equal to 1 cigarette was used to quantify the smoking background of pipe and/or cigar smokers (Pechacek et al. 1985). The number of years smoked was calculated by subtracting the current age from the initial age of smoking (for current smokers) or from the age since last quit by the age first started smoking (for former smokers). 10 subjects had a history of cigar or pipe smoking, while 2 of these 10 subjects were classified as current smokers. In cases where a former smoker had more than one smoking history of cigarette, pipe, or cigar smoking, the smoking variables were converted to cigarettes based on the conversion factor and then added. For example, to calculate packyears (packs per day * number of years smoked), a subject who had smoked 1 pack of cigarettes per day for 1 year and 7 oz. of pipe tobacco per week for 2 years was assigned 53 a total packyear of 3 ((1 * 1) + (7/7 * 2)). A summary of the calculations for pipe or cigar smokers is outlined in appendix 4. 4.15 Work and exposure characteristics The descriptive results of markers of personal exposure, including work characteristics and personal exposure to grain dust and endotoxin were investigated. The workers' job titles were categorized into 4 categories: Office jobs, Trades person, Inside Elevator, and Other to produce a higher sample size in each of the categories. The workers who participated in the study were fairly evenly spread out among the four job title categories of office jobs (18 %), tradesperson (24 %), inside elevator (37 %), and other (21 %). The workers were experienced, with a mean of 12 years working in the current job and 19 years working in the industry. The average time worked before performing the EBC test was 3 hours approximately (see table 4.2). Table 4.2. Work characteristics of the EBC study population. Job title categories n % office jobs 14 18.4 tradesperson 18 23.7 inside elevator 28 36.8 other 16 21.1 Other work characteristics mean (sd) min - max years in current job 11.5 (8.4) 0-33.0 years in industry 19.2 (9.1) 5-37.0 Hours worked on test day before performing EBC test 3.3 (1.7) 0 -6 .5 4.15.1 Grain dust The distribution of the grain dust personal exposure values for the 76 workers were shown in figure 4.1. The distribution was positively skewed, as is typical for occupational exposures in general. As well, all of the sample results were above the limit of detection (LOD: 0.013 mg/m3). Natural log transformation of personal exposure to grain dust produced a more normalized distribution (see figure 4.2). Figure 4.1. Distribution of personal grain Figure 4.2. Distribution of the natural log of dust exposure levels. personal grain dust exposure levels. -4.5 -3.5 -2.5 - 1 5 -0.5 0.5 1.5 2.5 Grain Dust (mg/m3) Grain Dust (Ln(mg/rrfl)) 54 4.15.2 Endotoxin The distribution of the endotoxin personal exposure values for the 76 workers are shown in figure 4.3. Similar to personal grain dust concentrations, the personal endotoxin exposures are positively skewed. This was expected, since grain dust and endotoxin are highly correlated (r=0.69). The natural log of the endotoxin concentrations produced a more normal-like distribution (See figure 4.4). Figure 4.3. Distribution of personal Figure 4.4. Distribution of the natural log endotoxin exposure levels. of endotoxin exposure levels. Endotoxin (EU/m3) Endotoxin (Ln(BJ/m3)) According to table 4.3, the median for the worker's personal exposure to grain dust and endotoxin was 1.0 mg/m3 and approximately 600 EU/m3. More than half of the workers had personal grain dust exposures of less than 2 mg/m3, while approximately three quarters of the workers had personal endotoxin exposures greater than 200 EU/m3. Table 4.3. Exposure characteristics of the EBC study population. Measured personal exposures min - max median GM GSD grain dust (mg/m3) 0.01 - 13.2 1.0 0.9 4.0 endotoxin (EU/m3) 8.1 - 11438.3 595.8 435.0 4.9 Personal exposure categories n % grain dust (mg/m3) <2 52 68.4 2-4 16 21.1 >4 8 10.5 endotoxin (EU/m3) <50 9 11.8 50 - 200 11 14.4 >200 56 73.7 4.16 Respiratory health characteristics Respiratory symptoms were summarized in the table below (see table 4.4). The most common reported symptom was shortness of breath hurrying on level ground or 55 walking up a slight h i l l . Approximately 10 % also reported asthma-like symptoms, with being woken by cough the most common. On average, the workers had approximately 100% of predicted values for forced expiratory volume, forced vital capacity and maximal mid-expiratory flow rate. Table 4.4. Respiratory health characteristics of the E B C study. Chronic Respiratory Symptoms n % Chronic cough, yes 3 4.0 Chronic phlegm, yes 7 9.2 Breathlessness, yes 19 25.0 Occasional wheeze, yes 15 19.7 Acute Respiratory Symptoms Woken with chest tightness, yes 6 7.9 Woken by cough, yes 10 13.2 Woken breathless,'yes 3 4.0 Breathless during the day, yes 3 4.0 Breathless after exercise, yes 7 9.2 Asthma-like Symptoms, yes 10 13.2 Lung Function (n=72) mean (sd) min - max F E V 1 % predicted 98.1'(13.2) 6 7 . 5 - 138.9 F V C % predicted 101.6(12.1) 73.1 - 136.4 M M F % predicted 91.1 (30.7) 21 .8 -163 .3 4.17 Exhaled breath condensate measurement 4.17.1 pH analysis The distribution of the p H was negatively skewed (see figure 4.5) with the appearance of 2 modes - one between the p H values of 4.5 to 5.5 and another between 7.5 and 8.5. The ph values ranged from 4.3 to 8.2, with a mean of 7.3 (sd 1.3). 56 Figure 4.5. Distribution of E B C pH. 50i PH 4.17.2 N H 4 + a n a l y s i s The distribution of E B C N H 4 + was positively skewed (see figure 4.6), with a range between 22.1 and 2384.1 u M , and a mean of 513.1 (470.6) u M . A l l samples were above the limit of detection (0.5 uM) . Natural log transformation of the N H 4 + distribution produced a more normal-like distribution (see figure 4.7). Figure 4.6. Distribution o f N H 4 . Figure 4.7. Distribution of the natural log of o f N H 4 + . NH4+ (uM) NH4+ (ln[uM]) 4.18 Correlat ion of p H and N H 4 + There was a high correlation between E B C p H and N H 4 (uM) (r=0.53, pO.OOOl) (see figure 4.8), and an even higher correlation between E B C pH and the natural log of N H 4 + (ln(uM)) (r=0.83, p<0.0001) (see figure 4.9). Similar to the laboratory results, low pH samples only had low N H 4 + values, but high pH samples had both low and high N H 4 + values. 57 Figure 4.8. Correlation o f N H 4 + a n d pH. Figure 4.9. Correlation o f l n N H 4 + a n d p H . PH pH A list o f potential independent variables that were believed to possibly influence E B C p H or N H 4 + was generated (See table 4.5) and categorized. Table 4.5. List o f potential independent variables investigated, categorized accordingly. Categorical Variables Demographic features sex, race (caucasian/non-caucasian), grain elevator ( U G G , Pacific, Cascadia, Saskatchewan, JRI), obesity Asthma/atopy atopy, asthma (never, former, current), asthma-like symptoms, current cold Smoking history smoking status (never, former, current), smoked in the last hour Work characteristics job titles (office, trades, inside elevator, other), work area (seed and pellet plant, inside elevator, trackshed, office, maintenance, all over), respirator worn on test day Chronic respiratory symptoms chronic cough, chronic phlegm, breathlessness, occasional wheeze Acute respiratory symptoms woken with chest tightness, woken by cough, woken by breathlessness, breathless during the day, breathless after exercise, asthma-like symptoms Continuous variables Demographic features age Smoking history packs per day now, packyears Work characteristics grain dust, Ln(grain dust), endotoxin, Ln(endotoxin), hours worked on test day before performing E B C test, years worked in the industry Lung function F E V P P , F V C P P , M M F P P The distributions of each independent variable were examined to see i f each variable contains enough variability for further analyses. Categorical variables that had values of less than 5% frequency in a category were 'flagged' during further analyses. Variables for acute respiratory symptoms, particularly "woken by cough" and "woken 58 breathless" did not meet this criteria (both had 4 % in Yes category) and therefore, one variable that included all o f the acute respiratory symptoms ("asthma-like symptoms") was instead examined in further analyses. The distributions of continuous variables were examined qualitatively, and all o f the variables were included in the further analyses. A correlation matrix of the variables was also created to look at associations amongst each variable. The full correlation matrix can be found in appendix 5. There were only a few pairs of highly correlated variables (ie. correlation coefficients > 0.5) among independent variables and most of these were expected (eg. different smoking variables were correlated with each other, different asthma-like symptoms were correlated with each other, grain dust levels were correlated with endotoxin levels, and age was correlated with duration of employment). For these variables, only one was included in modeling at a time. The only other pairs o f highly correlated variables were obesity with age (r=0.33) and with duration of employment (r=0.46). Therefore, models were constructed; including each of these separately. 4.19 Univariate associations between EBC pH or lnNH./ and other explanatory factors Univariate analysis was performed between each independent variable and the dependent variables of E B C p H , N H / , and I n N H / . The full table can be found in appendix 6, 7, and 8. A n abbreviated version of the table can be found in table 4.6 below, where the variables that were significant, as well as other variables that other researchers have found important were compared against p H and l n N H ^ . The chosen a priori variables include: atopy, asthma, asthma-like symptoms, smoking variables (ie. smoking status, packs per day now, packyears, smoked in the last hour), chronic respiratory symptoms (ie. chronic cough, chronic phlegm), grain dust levels, endotoxin levels, duration of employment in the industry, duration of time worked before performing the E B C test, and F E V 1 (as percent of the predicted value). Non-atopics had marginally significantly lower E B C p H than atopics, while there was no apparent association between between E B C p H and asthma or asthma-like symptoms. There was a non-significant difference between the various classes of smoking status, trend of current smokers having lower E B C p H and subjects who smoked in the last hour had a significantly lower E B C p H than those who did not. Subjects who worked in the seed and pellet plant area had a marginally significant lower E B C p H than non-seed and pellet plant workers. Similar results were found for office workers. A s well , there was not a significant difference of E B C p H with chronic cough or chronic phlegm. Obesity was significantly associated with E B C p H , as wel l as packs per day now and packyears. The natural logarithm of personal exposure to grain dust or endotoxin, hours worked on test day before performing the E B C test, and F E V P P was also not significantly associated with E B C p H . Univariate results were similar with l n N H 4 + . Atopics had a higher non-significant lnNFE* than non-atopics. There was also no significant association in lnNIfV in never, former, and current asthmatic groups. Similarly, subjects with asthma-like symptoms had a lower non-significant lnNH .4 + than subjects without. A non-significant association 59 between smoking status and InNEL; was found, while a non-significant decrease in subjects who smoked in the last hour was found. Working in the seed or pellet plant area had a lower, non-significant effect on l n N H 4 + , while working in the office had a lower, marginally significant effect on l n N H 4 + . Subjects with chronic cough had a lower non-significant lnNH4+ than those without. Subjects with chronic phlegm had a lower levels of lnNH4+, which was found to be statistically significant. Obesity, packs per day now, hours worked on test day before performing the E B C test, and F E V P P had negative, non-significant effects on l n N H 4 + . On the other hand, packyears had a negative, significant effect on InNEL;4". The natural logarithm of exposure to grain dust and endotoxin had a positive, non-significant effect while years worked in the industry had a negative, significant effect on l n N H 4 + . Table 4.6. Univariate associations between E B C p H or l r i N H 4 + and other independent variables. PH lnNH4 + (ln[uMl) Categorical Variables Class mean (sd) P1 mean (sd) P1 Demographic features Obese Yes 6.7(1.5) 0.009 5.4(1.1) 0.04 N o 7.6(1.1) 6.0 (0.9) Asthma/Atopy Atopy Yes 7.6(1.0) 0.06 6.0(1.0) 0.1 N o 7.1 (1.4) 5.7(1.0) Asthma Never 7.2(1.3) 0.6 5.8(1.1) 0.7 Former 7.6(1.2) 6.1(1.1) Current 7.7 (0.5) 5.8(0.7) Asthma-like symptoms Yes 7.5 (1.1) 0.6 5.7 (0.7) 0.8 , No 7.3 (1.3) 5.8(1.1) Smoking History Smoking status Never 7.6(1.0) 0.1 5.9(1.0) 0.3 Former 7.3 (1.2) 5.9(1.0) Current 6.7(1.6) 5.4(1.2) Smoked in the last hour Yes 6.6(1.7) 0.04 5.4(1.2) 0.1 N o 7.4(1.1) 5.9(1.0) Exposure Measurements Work Area Seed and pellet plant Yes 6.4(1.6) 0.1 5.2(1.1) 0.1 N o 7.4(1.2) 5.9(1.0) Office Yes 6.4(1.8) 0.06 5.0(1.7) 0.05 N o 7.4(1.2) 5.9 (0.9) Chronic Respiratory Symptoms Chronic cough Yes 6.9(1.6) 0.5 5.0 (0.8) 0.1 No 7.3 (1.3) 5.9(1.0) 60 Chronic phlegm Yes 6.7(1.6) 0.2 5.0(1.0) 0.03 N o 7.4(1.2) 5.9(1.0) Continuous Variables EBC pH = Intercept + (Coefficient x Variable) InNH/ = Intercept + (Coefficient x Variable) Demographic features Coefficient (se) i P Coefficient (se) Body Mass Index (kg/cm 2) -0.08 (0.03) 0.01 -0.04 (0.03) 0.1 Smoking History Packs per day now -0.9 (0.4) 0.03 -0.7 (0.4) 0.07 Packyears ' -0.02 (0.008) 0.02 -0.01 (0.007) 0.04 Personal Exposure L n Grain dust (Ln(mg/m3)) 0.1 (0.6) 0.5 0.1 (0.1) 0.1 L n Endotoxin (Ln(EU/m3)) 0.06 (0.1) 0.5 0.1 (0.1) 0.1 Years worked in the industry -0.03 (0.02) 0.1 -0.03(0.01) . 0.03 Hours worked on test day before performing the E B C test -0.1 (0.1) 0.13 -0.1 (0.1) 0.09 Lung Function F E V P P -0.01 (0.01) 0.2 -0.003 (0.009) 0.8 p-value for statistical test comparing the univariate association of the dependent variable, E B C pH, and an independent variable; t-test (Proc G L M ) for comparing 2 categorical distributions with E B C pH; anova (Proc GLM) for comparing 3 or more categorical distributions; simple linear regression (Proc REG) for comparing continuous variables with E B C pH. 4.20 Multivariable analysis of pH Three versions o f the multivariable models for p H are shown below, with each model differing by having either years worked in the industry (see table 4.8) or obesity (see table 4.9), or both variables (see table 4.7) included. In the p H model, p H was significantly associated with either (but not both) of years worked in the industry or obesity; current smoking, duration o f work on the test day before performing the E B C test; and with working in the seed/pellet plant area of a grain elevator and with atopy. E B C p H was not associated with grain dust or endotoxin exposure measured on study day. When both years worked in the industry and obesity were included in the model, years worked in the industry was non-significant, while obesity remained significant. The instability in the model when both variables was included was due to the moderate correlation between the two variables (r=0.46, p<0.0001). 61 Table 4.7. Multiple linear regression model of p H , adjusting for both years worked in the industry and obesity, for study population (n=75). Model with Grain Dust Model with Endotoxin Variable Coefficient (SE) P Coefficient (SE) P Intercept 8.6 (0.5) O.0001 8.1 (0.7) <0.0001 smoking amount (packs per day now) -1.1 (0.4) 0.01 -1.1 (0.4) 0.01 atopy (Yes/No) 0.5 (0.3) 0.05 0.5 (0.3) 0.06 grain dust (ln(mg/m3)) 0.1 (0.1) 0.3 n/a n/a endotoxin (In (EU/m3)) n/a n/a 0.1 (0.08) 0.5 hours worked before performing E B C test on study day -0.2 (0.08) 0.02 -0.2 (0.08) 0.02 work area: seed/pellet plant -1.0 (0.5) 0.05 -1.0 (0.5) 0.05 years worked in the industry -0.02 (0.016) 0.3 -0.02 (0.017) 0.3 obese (Yes/No) -0.7 (0.3) 0.02 -0.7 (0.3) 0.03 Model R 2 0.3 0.3 Adjusted R 2 0.2 0.2 62 Table 4.8. Multiple linear regression model of p H , adjusting for years worked in the industry only, for study population (n=75). Model with Grain Dust Model with Endotoxin Variable 1 Coefficient (SE) P Coefficient (SE) P Intercept 8.7 (0.5) O.0001 8.1 (0.7) <0.0001 smoking amount (packs per day now) -0.9 (0.4) 0.03 -1.0 (0.4) 0.02 atopy (Yes/No) 0.6 (0.3) 0.04 0.5 (0.3) 0.05 grain dust (ln(mg/m3)) 0.1 (0.1) 0.2 n/a n/a endotoxin (In (EU/m3)) n/a n/a 0.1 (0.1) 0.3 hours worked before performing E B C test on study day -0.2 (0.1) 0.01 -0.2 (0.1) 0.02 work area: seed/pellet plant -1.0 (0.5) 0.04 -1.1 (0.50) 0.04 years worked in the industry -0.04 (0.02) 0.02 -0.03 (0.02) 0.03 Model R 2 0.3 0.3 Adjusted R 2 0.2 0.2 63 Table 4.9. Multiple linear regression model of p H , adjusting for obesity only, for study population (n=75). Model with Grain Dust Model with Endotoxin Variable Coefficient (SE) P Coefficient (SE) P Intercept 8.2 (0.3) <0.0001 7.8 (0.6) <0.0001 smoking amount (packs per day now) - E l ( 0 . 4 ) 0.01 -1.1 (0.4) 0.01 atopy (Yes/No) 0.6 (0.3) 0.04 0.5 (0.3) 0.05 grain dust (In (mg/m3)) 0.1 (0.1) 0.3 n/a n/a endotoxin (In (EU/m3)) n/a n/a 0.1 (0.1) 0.5 hours worked before performing E B C test on study day -0.2 (0.1) 0.03 -0.2(0.1) 0.04 work area: seed/pellet plant -0.9 (0.5) 0.07 -0.9 (0.5) 0.07 obese (Yes/No) -0.9 (0.3) 0.002 -0.9 (0.3) 0.003 Model R 2 0.3 0.3 Adjusted R 2 0.2 0.2 4.20.1 Exploratory analysis of pH and obesity A s an exploratory analysis, the regression model was rerun after excluding obese subjects (n=52 for non-obese) (see table 4.10). In this model, atopy changed from being statistically significant in the original models (p=0.04 for grain dust or p=0.05 for endotoxin model) to being statistically non-significant in the current models (p=0.35 for grain dust or p=0.36). In this model, current smoking, duration o f work on the test day, and years employed in the industry remained significantly associated with lower p H , while atopy became non-significant. 64 Table 4.10. Multiple linear regression model of p H for the non-obese population (n=52) only. Model with Grain Dust Model with Endotoxin Variable Coefficient (SE) P Coefficient (SE) P Intercept 9.0 (0.5) O.0001 9.0 (0.7) O.0001 smoking amount (packs per day now) -0.9 (0.4) 0.02 -0.8 (0.4) 0.02 atopy (Yes/No) 0.3 (0.3) 0.4 0.2 (0.3) 0.4 grain dust (ln(mg/m3)) 0.01 (0.1) 0.9 n/a n/a endotoxin (ln (EU/m3)) n/a n/a -0.009 (0.1) 0.9 hours worked before performing E B C test on study day -0.2 (0.1) 0.01 -0.2 (0.1) 0.01 work area: seed/pellet plant -1.4 (0.5) 0.006 -1.4 (0.5) 0.006 years worked in the industry--0.03 (0.02) 0.03 -0.03 (0.02) 0.03 Model R 2 0.4 0.4 Adjusted R 2 0.3 0.3 4.21 Multivariable analysis of lnNH4+ Similar multivariable analyses were carried out to examine factors associated with l r i N H 4 + . In this model, cumulative smoking (packyears) was included to represent smoking because it was the strongest independent variable amonst the smoking variables in univariate analyses and the model in general became more stabilized. Three versions o f the multivariable model are shown below, with each differing by either years worked in the industry (see table 4.12) or obesity (see table 4.13), or both variables included in the model (see table 4.11). In general, multivariable analysis showed that reduced l n N H 4 + was significantly associated with packyears, hours worked before performing the E B C test on study day, working in the seed/pellet plant area and either (but not both) obesity or years worked in the industry. In contrast to our hypothesis, increased l n N H 4 + was also significantly associated with personal grain dust exposure. When both obesity and years worked in the industry were included in the model, obesity was non-significant, while years worked in the industry remained significant. 65 Table 4.11. Mult iple linear regression model of l n N H 4 + (ln[uM]), adjusting for both years worked in the industry and obesity, for the study population. Model with Grain Dust Model with Endotoxin Variable Coefficient (SE) P Coefficient (SE) P Intercept 7.5 (0.4) O.0001 6.8 (0.6) O.0001 packyears -0.01 (0.01) 0.03 -0.01 (0.007) 0.04 grain dust (ln(mg/m3)) 0.2 (0.1) 0.05 n/a n/a Endotoxin (ln(EU/m3)) n/a n/a 0.09 (0.07) 0.2 hours worked before performing E B C test on study day -0.2 (0.1) 0.0008 -0.2 (0.07) 0.002 work area: seed/pellet plant -0.8 (0.4) 0.05 -0.8 (0.4) 0.05 years worked in the industry -0.03 (0.01) 0.02 -0.03 (0.01) 0.03 Obese (Yes/No) -0.2 (0.3) 0.4 -0.2 (0.3) 0.5 Model R 2 0.3 0.3 Adjusted R 2 0.2 0.2 Table 4.12. Mult iple linear regression model of l n N H 4 + (ln[uM]), adjusting for years worked in the industry only, for the study population. Model with Grain Dust Model with Endotoxin Variable Coefficient (SE) P Coefficient (SE) P Intercept 7.6 (0.4) O.0001 6.9 (0.6) <0.0001 packyears -0.01 (0.01) 0.03 -0.01 (0.006) 0.03 grain dust (ln(mg/m3)) 0.2 (0.1) 0.04 n/a n/a endotoxin (ln(EU/m3)) n/a n/a 0.1 (0.1) 0.2 hours worked before performing E B C test on study day -0.2 (0.1) 0.0005 -0.2 (0.1) 0.001 work area: seed/pellet plant -0.8 (0.4) 0.04 -0.9 (0.4) 0.04 years worked in the industry -0.04 (0.01) 0.003 -0.04(0.01) 0.004 Model R 2 0.3 0.3 Adjusted R 2 0.2 0.2 66 Table 4.13. Multiple linear regression model of I n N H / , adjusting for obesity only, for the study population. Model with Grain Dust Model with Endotoxin Variable Coefficient (SE) P Coefficient (SE) P Intercept 6.8 (0.3) O.0001 6.2 (0.5) O.0001 packyears -0.01 (0.01). 0.05 -0.01 (0.007) 0.06 grain dust (ln(mg/m3)) 0.2 (0.1) 0.07 n/a n/a endotoxin (ln(EU/m3)) n/a n/a 0,1 (0.1) 0.2 hours worked before performing E B C test on study day -0.2 (0.1) 0.004 -0.2 (0.1) 0.008 work area: seed/pellet plant -0.7 (0.4) 0.1 -0.7 (0.4) 0.09 obese (Yes/No) -0.5 (0.2) 0.05 -0.5 (0.2) 0.06 Model R 2 0.2 0.2 Adjusted R 2 0.2 0.2 4.21.1 Exploratory analysis of InNH4+ and Obesity Among non-obese subjects only, similar results were found, except that packyears became marginally significant, while personal grain dust exposure became non-significant (see table 4.14). 67 Table 4.14. Mult iple linear regression model of I n N H / for the non-obese population (n=52) only. Model with Grain Dust Model with Endotoxin Variable Coefficient (SE) P Coefficient (SE) P Intercept 7.6 (0.4) O.0001 7.0 (0.6) O.0001 packyears -0.01 (0.01) 0.08 -0.01 0.1 grain dust (In (mg/m3)) 0.1 (0.1) 0.1 n/a n/a endotoxin (In (EU/m3)) n/a n/a 0.1 (0.1) 0.3 hours worked before performing E B C test on study day -0.2 (0.1) 0.003 -0.2 (0.1) 0.006 work area: seed/pellet plant -1.0 (0.5) 0.03 -1.0(0.5) 0.03 years worked in the industry -0.04 (0.01) 0.009 -0.04 (0.01) 0.01 Model R 2 0.3 0.3 Adjusted R 2 0.2 0.2 4.22 Other multivariable analyses Age, instead o f years worked in the industry and obesity, was also considered in all the models. When this was performed, age was not significant in any of the models (p>0.05). In addition, exploratory analyses by excluding current smoking was performed on both p H and lnNH4+. Similar results were found in the original p H and lnNH4+ models (adjusting for years worked in the industry and obesity). In the grain dust model, decreased p H was moderately associated with not being atopic (p=0.09), increased duration of work before performing the E B C test (p=0.07), working in the seed/pellet plant area (0.07), and obesity (p=0.04), but not associated with increased personal exposure to inhalable grain dust (p=0.6). Similar results were found with the endotoxin model. A s well , decreased lnNFL; + was moderately associated with decreased personal exposure to inhalable grain dust (p=0.06), but not significantly associated with working in the seed/pellet plant area (p=0.11). Decreased I n N H / was significantly associated with increased duration of work before performing the E B C test (p-0.01) and increased years worked in the industry (p=0.02), but not significantly associated with obesity (p=0.50). 68 CHAPTER 5. DISCUSSION 5.1 Overview Currently, despite the large number of E B C clinical studies investigated, there have been very few studies that have investigated the utility of E B C collection to measure airway inflammation in an occupational setting. In addition, although there is a growing number of studies that report some details about methodological aspects o f the E B C test, until Sept 2005, there was no recommended protocol available in the literature. This study attempted to address both these gaps. In the present study, we have evaluated the utility of E B C in workers employed at five terminal grain elevators in the port of Vancouver. The first phase of the study involved assessing various laboratory effects of the E B C test that were particularly relevant to sampling in the field. From this, a standard procedure suitable for our laboratory was developed. The second phase of the study involved collecting E B C samples from grain elevator workers during their work-shift and investigating relationships between the measures of acid-base equilibrium obtained from E B C and personal exposure to grain dust and endotoxin, as well as other risk factors for inflammation. 5.2 Method development and evaluation 5.3 Test acceptability In the present study, over 90% of study subjects (from 222 tests in both the lab and the field) were able to perform the test and generate a sample adequate for analysis. The most common problem issues were very light breathing and/or exhaling through the nose by some subjects. These subjects typically did not generate enough E B C volume for an accurate p H measurement in the 15 minutes given to perform the test. This can simply be avoided by assuring that the subject is not exhaling through his/her nose and instructing the subjects to exhale tidally into the E B C collection system such that they can hear their exhaled breath pass through the top of the collection tube. These subjects were simply asked to repeat the E B C test until sufficient E B C volume was obtained. There were also no i l l effects reported by any of the subjects during sampling. 5.4 Effect of duration of EBC collection on EBC volume Performing the E B C test at longer durations allows for increased total exhaled air passing through the cooling tube and also a longer period of condensation to occur on the exhaled breath. This results in higher volumes of E B C . In this study, volumes appeared to plateau at around 18 minutes, most likely due to the cooling tube becoming warmer from being at room temperature for such an extended period o f time. A collection time of 15 minutes was chosen because the data suggests that this time yields enough volume (at least 1 mL) to perform the necessary laboratory analyses, without placing 69 unreasonable demands on participant time. This sample volume is consistent with other studies using this time frame (Ojoo et al. 2005). 5.5 Effect of condenser temperature on EBC volume, and on pH and lnNHU+ Initial colder temperatures of the cooling tube produced higher volumes, primarily due to more efficient condensation of the exhaled air passing through the collection tube. These results were consistent with Goldoni and colleagues, who reported a progressive increase in E B C volume as the condenser temperatures decreased (Goldoni et al. 2005). However, in all tests, cooling the condensor tube to -80 degrees Celsius produced frozen E B C (or snow) during the first 2 minutes of the E B C test. In this study, there was no significant difference between the temperature of the cooling tube and the p H . This was similar to results found by Vaughn and colleagues (Vaughan et al. 2003) who used the same collection device, the RTube, but with a modified cooling jacket that maintained constant temperatures of+13, -6, -17, and -44 °C for the aluminium cooling tube, to measure the effect of temperature on p H . The authors did not report any significant differences in the p H of E B C collected at the different temperatures. These authors suggested that, in some populations, condenser temperatures of less than -20 C could produce E B C in the solid phase and that "water-soluble volatile components of exhaled air w i l l not be as well trapped as when the condensation occurs in liquid phase at more modest temperatures". Vaughn and colleagues also suggested that " i f certain volatile acids are exhaled only in disease states, when the source fluid (airway lining fluid) p H is low, then E B C collected at too cold a temperature may not reveal the differences between health and disease as well" . However, because our data involved healthy subjects, the effect of cooling tube temperature may not have been evident. Therefore, these data needs to be interpreted with caution and further investigation into this is necessary. Vaughn et al. recommends "collections of E B C at condenser temperatures reasonably close to zero when p H is of primary interest" (Vaughan et al. 2003). Wells et al. reported a significant difference between condenser temperatures of +13 and -44, and -6 and -44 degrees Celsius in E B C N H 3 (p=0.002) (Wells et al. 2005). This is not consistent with our data which suggest that initial condenser temperatures of -80, -20, and 4 °C does not have a significant effect on E B C l n N H ^ concentrations (p=0.28). This discrepancy may be due to the fact that Wells et al. used a specialized modified cooling jackets that maintained a constant temperature, while in the present study, the temperatures o f the cooling tubes did not remain constant, but in fact increased during the collection procedure. A s well , in the present study, there was a relatively low number of samples (n=2 subjects; each performed back to back trials of temperature conditions twice; n=12 total), compared to the study performed by Wells et al. (n=10 subjects; each performed back to back trials o f temperature conditions once; n=40 total). Therefore, the differences between the condenser temperatures in the present study are not as evident, and this can be seen in the non-significant effect o f condenser temperature on I n N H / . 70 5.6 Effect of use of filter on pH and lnNH4+ The effect of the use of a filter was evaluated by performing repeated tests with and without a filter. The filter was used to prevent contamination of saliva, as well as increase the proportion of solutes emanated from the lower airways iri comparison to the upper respiratory tract such as the mouth. This was based on the fact that the majority o f respiratory droplets are less than 0.3 microns and that larger respiratory particles, particularly the ones greater than 5 microns, do not make it to the mouth, as the larger respiratory particles tend to impact the back of the throat (during the 90 degree turn in the pharynx) during exhalation. Some researchers have expressed concern about the use of a filter between the subject and the E B C collection device, suggesting that the filter may not only trap salivary contaminants, but as well as some aerosolized respiratory droplets from the lower airways (Effros. 2001). However, there has not been any studies evaluating the effect of the use of a filter on any markers of E B C . In this study, there was no significant difference found in p H or l n N H 4 + between samples taken with or without a filter. 5.7 Effect of the duration and flow-rate of argon deaeration on pH The measurement of p H in fresh E B C samples is difficult because of the high CO2 content dissolved in the E B C which changes over time and destabilizes the p H measures. Argon deaeration has been shown to reduce the time sensitivity of the p H assay, by removing and standardizing the CO2 content in the E B C (Borril l et al. 2005). In this study, p H measurements appeared to stabilize after just 5 minutes of argon deaeration at 350 mL/min. The p H values prior to argon deaeration were within the range of 6.0 and 6.5, consistent with other studies that have measured the p H of E B C directly without argon deaeration (Cain et al. 2002, Tate et al. 2002). After 5 minutes, the p H values rose to the range of 7.5 and 8.0, where the values remained in that range after 10 and 15 minutes of argon deaeration. These data suggests that the methodology used in the present study, as recommended by Hunt et al. (Hunt et al. 2000) (10 minutes at 350 mL/min) is sufficient to equilibrate the C 0 2 with the atmosphere to obtain a stable reading. Similar results were reported by Borr i l l et al. (Borri l l et al. 2005), who investigated the effects of duration of argon deaeration in eight C O P D subjects by measuring the p H of aliquots of E B C samples after argon deaeration at a flow-rate of 2 L/min for 0, 1,2, 5, 10, and 15 minutes. A significant increase in E B C p H after 5 minutes of argon deaeration was reported, and no significant change was observed after 10 and 15 minutes. Although most studies have performed the argon deaeration step at a flow rate of 350 mL/min, one study performed the step at a flow-rate of 2000 mL/min (Borri l l et al. 2005). This raises the question of whether 350 mL/min is an adequate flow-rate to rid the E B C samples completely of ambient carbon dioxide. Therefore, a comparison of flow rates at 350 mL/min and 2000 mL/min for 10 minutes prior to p H measurement was assessed. The p H measured with argon dearation at a flow-rate of 350 mL/min was statistically higher than at the flow-rate of 2000 mL/min (p=0.0012). However, the mean p H difference between the two flow-rates was small (mean difference o f 0.13 p H units). 71 The data suggests that in future studies, a higher flow-rate for argon deaeration may be preferable to further rid dissolved CO2 in the E B C samples. In either instance, the purposes of the argon deaeration process for the present study was to stabilize the p H measurement (and not to remove all of the CO2 content in the E B C samples). A flow-rate of 350 mL/min of argon deaeration can achieve stability of p H measurement in E B C , as can be seen in the stabilization of p H measurements after 5, 10, and 15 minutes of argon deaeration (see figure 3.11). 5.8 Effect of volume on pH and InNH/ There has been concern about the possibility of variable dilution of respiratory solutes in exhaled breath condensate (EBC) influencing the measured biomarkers (Effros et al. 2002). It is unknown whether the increased E B C volume from colder temperatures of the cooling tube dilutes the sample further or i f it enhances the collection of the respiratory solutes. In this study, differences in E B C volume did not have a significant effect on p H or l n N H 4 + . The lack of effect of volume on p H is consistent with results by Vaughn et al. who reported similar E B C p H values in one group that had E B C volumes range from 250 - 350 u L in comparison to another group that had E B C volumes range from 800 - 1250 u L (p>0.05) (Vaughan et al. 2003). McCafferty and colleagues also noted that a reduced tidal volume was associated with reduced water vapour availability but did not affect solute dilution (McCafferty et al. 2004). This suggests that as condensation of water vapour decreases, so does the aerosolization o f the respiratory droplets. Another study also reported a small intrasubject variability of E B C N a + and K + in subjects with different E B C sample volumes, suggesting that dilution has a minimal effect on E B C mediator concentrations (Zacharasiewicz et al. 2004). These data suggest that the concentrations of solutes remain constant and act independently of E B C volume effects. In contrast, Effros and colleagues have reported considerable variability in the E B C within subjects (Effros et al. 2002). Sophisticated methods for evaluating dilution effects have also been proposed by Effros et al. (Effros et al. 2002, Effros et al. 2003a), who suggest the need to measure a dilution marker in both E B C and plasma to calculate a dilution factor. However, the sampling of plasma is both difficult and associated with certain risks, therefore making the E B C tool less attractive as a simple, non-invasive tool in field studies. 5.9 Reliability of final EBC protocol After the protocol for E B C collection had been established, six different subjects who have not performed the E B C test were recruited to validate the E B C protocol. The goal was to evaluate the volume of E B C collected on subjects performing the test for the first time since it is possible that subjects may become more accustomed to breathing through the E B C collection device in repeated E B C tests performed by a single subject, that the subject becomes more accustomed to breathing through the E B C device, therefore yielding higher E B C volumes. A l l o f the samples exceeded the minimum volume of 1 m L needed to perform the required laboratory analyses. 72 5.10 Reproducibility of pH measurements from the same sample The reproducibility o f E B C p H measurements made from the same sample was very high, with a low inter-pH variability (mean (sd) coefficient o f variation o f 0.17 % (0.16) with a range of - 0 - 1 . 2 %) and good concordance between p H measurements taken immediately after E B C collection and measurements of the same samples repeated after 1.5 years of storage in a -80 °C freezer (mean p H difference -0.007, sd 0.35, range 1.56) and the field study (mean p H difference 0.40, sd 0.33, range 1.44). These results are consistent with those of Borr i l l and colleagues, who reported a within-sample variation of p H (the p H o f two aliquots from the same sample were measured) of a mean difference of 0.08, with limits o f agreement of-0.29 and 0.45 (Borri l l et al. 2005). The authors also reported no effect of freezing on E B C p H , as the mean p H o f E B C samples measured immediately, and after 2 weeks and 3 months of storage at -80 °C. 5.11 Effect of freeze-thaw cycles Some studies that have evaluated the effect of first storing the samples in a freezer and then later defrosting the samples for the analysis of p H . N i i m i et al. (Ni imi et al. 2004) performed a preliminary study that measured the E B C from 11 controls and 8 with cough and reported that defrosted samples that were stored in a -80 °C freezer had a p H that were significantly higher than its corresponding fresh unfrozen samples from the same subject (both had undergone argon deaeration at 350 mL/min). However, the defrosted and fresh p H measurements were highly correlated (r=0.91, p=0.0001). Vaughn et al. have also investigated the effect o f the duration of sample storage on E B C p H and reported a high correlation coefficient of 0.97 (pO.OOl , n=24) between fresh p H measurements and p H measurements of samples stored for one year in -20 Celsius (both times undergoing argon deaeration at 350 mL/min) (Vaughan et al. 2003). A s well , samples stored for 2 years gave a correlation coefficient of 0.98 (pO.OOl , n=l 1) when compared to the fresh p H measurements. These results are consistent with the present data where the effect of storing samples in -20 °C on p H or l n N H 4 + was not significant when freeze-thaw samples were compared to its respective fresh samples in back to back trials. 5.12 Within- and between-person variability The small within person variability for E B C p H and lnNH4+ among non-smokers in this study suggests that the p H assay is highly reproducible, and that a single sample taken in a field study may be a reasonable reflection of airway status. The larger within-and between-person variability for E B C p H and N l n H 4 + in smokers suggests that both assays are capable of potentially distinguishing the inflammatory effects o f smoking on the airways. These findings are consistent with other studies. Vaughn and colleagues investigated the intraweek and intraday variability o f the E B C p H in subjects by collecting E B C before breakfast for seven days and also collecting E B C once before lunch and dinner on the last day (Vaughan et al. 2003). The authors reported an 73 intraweek mean coefficient of variation of 4.5 % (range of 0.9 to 20 %) and an intraday mean coefficient of variation of 3.5 % (range of 0.6 to 23 %). A s well , Kostikas et al. reported high repeatability in the measured p H on consecutive days of healthy subjects, 7.47 (0.12) vs. 7.49 (0.1) (p=0.42), asthma patients, 7.38 (0.19) vs. 7.40 (0.21) (p-0.40), and C O P D patients, 7.24 (0.1) vs. 7.22 (0.1), (p=0.56) (Kostikas et al. 2002). 5.13 Correlation of pH and NH 4 + The mechanisms leading to dysfunction in the acid-base equilibrium of the airways are currently unknown, but interesting hypotheses have been proposed. Hunt et al. showed that glutaminase, an enzyme that reacts with glutamine to produce N H 3 , is expressed in the epithelium of airways in response to endogenous acids to serve as a neutralizing agent (Hunt et al. 2002). N H 3 is a basic buffer that can solubilize in water and react with H + to form N H 4 + . The authors also reported that N H 3 production is inhibited in response to certain inflammatory cytokines, such as interferon-gamma and tumor necrosis factor, suggesting that the acid-base equilibrium in the airways can be regulated. These findings suggest that N H 3 , a product of glutaminase activity, may play a role in p H homeostasis in the airways. In both the laboratory and field components of the present study, E B C p H was moderately correlated with both N H 4 + and with the natural log of N H 4 + . These results are consistent with previous studies that have investigated the acid-base equilibrium in healthy subjects that had undergone asthmatic exacerbations (Hunt et al. 2002), who reported a correlation of r=0.55 between N H 3 concentrations and log transformed p H , and in stable allergic asthmatic children (Carraro et al. 2005b), who also reported a significant correlation of r=0.5 between N H 3 concentrations and p H . Wells et al. also reported a similar correlation of r=0.52 between log transformed N H 3 and p H in randomly selected subjects (Wells et al. 2005). A s we found, these studies also reported that E B C samples with low p H (pH<5) had low N H 3 values, but that samples in the p H o f 7 to 8 range had both high and low N H 3 values. This suggests that N H 3 depletion in the airways may be necessary, but not entirely sufficient for exhaled breath acidification, as samples with a neutral p H may have a low N H 3 concentration (Hunt et al. 2002). Mult iple p H buffering systems may play an important role in this regard. 5.14 Summary In summary, the laboratory results from this project indicate that E B C p H and N H 4 + assays are unaffected by cooling tube temperature, use o f a filter, duration of argon deaeration (after 5 minutes), E B C volume, and storage temperature. These results, together with the within and between person variability findings, suggest that E B C p H is a simple, robust, and reproducible assay that is capable of distinguishing pathological changes in the airways. The results also show that measuring N H 4 + in E B C can be a useful complement to E B C p H data, in predicting the biological state of the airways. Many of the conclusions based on the laboratory results of the present study were similar to the conclusions made by an A T S / E R S task force on E B C in September 2005 74 (Horvath et al. 2005). A s well , the methods employed in the present study based on the laboratory results were similar to the methodological recommendations by the A T S / E R S task force. Similarities include the use of a saliva trap to reduce salivary contamination, the subjects performing E B C collection while sitting down, constant collection time and temperature for repeated samples, the evaluation of intra-subject variability, as well as intra-assay and inter-assay variability, and argon deaeration o f the samples for p H analysis. Differences between recommendations made by the A T S / E R S task force and the methods used in the present study involve the use of filters and noseclips. The A T S / E R S task force recommended not to use filters between the subject and collection tube, without having evaluated the effect of the filter on the markers o f E B C . In the present study, this effect was evaluated and no effect of the use o f a filter was seen on either marker of E B C . A s well , the A T S / E R S task force recommended the use o f noseclips during oral sampling to prevent nasal contamination issues and to prevent exhaled air from exiting the nose. However, the A T S / E R S task force has noted that this recommendation is not supported by any data. One limitation of the laboratory study is that the sample size of the individual experiments was small. However, the fact that our findings are closely concordant with the A T S / E R S task force conclusions suggests that our results are valid. 5.15 Fie ld study The field study involved sampling the E B C of workers from terminal grain elevators in the port of Vancouver. The acid-base equilibrium of E B C was evaluated to assess the impact of occupational exposures and other factors affecting respiratory health on the airways of the workers. In summary, decreased E B C p H was significantly associated with increased smoking intensity, obesity, not being atopic, duration of work before performing E B C collection, and possibly increased duration o f employment in the industry. Decreased E B C l n N H 4 + was significantly associated with increased cumulative smoking amount, increased duration of employment in the industry, duration of work before performing E B C collection, and possibly obesity. However, personal exposure to inhalable grain dust or endotoxin was not significantly associated with either E B C p H or l n N H 4 + . 5.16 p H / l n N H 4 + and obesity There has been only very little research on the effect of obesity on airway inflammation using E B C . One study investigated the relationship between obesity and asthmatic airway inflammation by measuring the exhaled nitric oxide (NO) and leukotriene B4 (LTB(4); marker of oxidative stress) concentrations in the E B C of asthmatic children (Leung et al. 2004). The authors concluded that while exhaled N O and LTB(4) levels were increased in the asthmatic children, there was no significant difference found when the population was stratified according to obesity. In the present study, decreased p H and l n N H 4 + were significantly associated with obesity. It is possible that the association between E B C markers and obesity found in the present study may be due to chronic, systemic inflammation that is associated with 75 obesity. Shore et al. note in a review that obese people tend to have persistent low levels of systemic inflammation that is characterized by an increase in a variety o f inflammatory mediators, which appears to originate from the adipose tissue itself (Shore and Fredberg. 2005). However, there have been no studies examining airway acidity in relation to obesity-related systemic inflammatory processes. Another possibility is that the associations seen here may have been due to the secretion of stomach acids into the esophagus and mouth, an event called gastroesophageal reflux which appears to occur more frequently in obese people. The notion of using E B C to measure gastroesophageal events has been considered by some researchers (Effros et al. 2003b). Gastroesophageal reflux is believed to be an endogenous mechanism that can induce respiratory symptoms. Two mechanisms have been postulated. The reflex theory postulates that after a gastroesophageal reflux episode, the gastric acids that are released in the esophagus are detected by sensory nerves, which are relayed to the central nervous system, and subsequently appropriate motor nerves are activated that trigger a nervous parasympathic response, such as bronchoconstriction and other symptoms seen in asthma. The reflux-aspiration theory postulates that gastric contents are aspirated and released into the esophagus and mouth, where the acid droplets can then be inhaled (Ricciardolo et al. 2004). This would be similar to inhaling acid fogs, air pollution, or workplace exposure, which can cause acidification o f the airways (Ricciardolo et al. 2004). Since stomach acid typically has a p H of 1 or 2, this could possibly explain the low E B C p H values (pH<5) found in some of the samples. Several factors can induce gastric reflux events. These factors include obesity, smoking, lying down, as well as mental and physical stress. Obesity triggers gastro-esophageal events because extra pressure is consistently applied to the abdomen region, which can force stomach acid upwards into the esophagus. Smoking and eating can also relax the gastro-esophageal sphincter, the valve that is between the stomach and esophagus, to allow for stomach acid entering the esophageal region. In addition, stress can induce gastroesophageal reflux by inhibiting the stomach's ability to empty acid from the stomach (Frost-Rude. 1999). A l l these factors may be relevant in gastroesophageal events,,and may also play a significant role in determining variation in E B C p H and N H 4 + levels. 5.17 p H / l n N H 4 + and smoking It has been well-established that tobacco smoking can induce the activation of inflammatory processes in the lung (Garey et al. 2004). Tobacco smoke inhalation induces oxidative stress, including reduction of the antioxidant glutathione after short-term smoke exposure and elevated concentrations of glutathione in regular smokers as the immune system adapts to the chronic smoke exposure (Rahman and MacNee. 1999). Increases in hydrogen peroxide (H2O2) concentration (Guatura et al. 2000) and prostanglandins (Montuschi et al. 2000), reactive oxygen species that are involved in several antimicrobial processes, are also common in response to smoke inhalation. However, the role of acid stress in response to tobacco smoke inhalation is not 76 completely understood. Ricciardolo and colleagues have suggested that "acid stress in the lung might be thought of as parallel and complementary to oxidative stress" (Ricciardolo et al. 2004). Although several studies have investigated markers o f oxidative stress-related inflammation in E B C and smoking, none of these have specifically investigated the effect of smoking on E B C p H . A n early study performed by Kostikas et al. reported a significant decrease in the p H of the E B C of smokers with C O P D when compared to non-smoking control subjects (pO.OOl) (Kostikas et al. 2002), but the role of smoking itself as a potential confounder in the association between disease and p H was not investigated. Several studies have reported a significant increase in H2O2 in healthy smokers compared to healthy non-smokers, and that this increase was even higher in stable C O P D patients (De Benedetto et al. 2000, Dekhuijzen et al. 1996, Nowak et al. 1999). However, among C O P D patients, Nowak and colleagues found no significant difference in E B C hydrogen peroxide comparing current, former, and non-smokers (Nowak et al. 1999). Montuschi and colleagues demonstrated an acute increase in 8-isoprostane, a biomarker o f oxidative stress in healthy smokers in comparison to healthy non-smokers (pO.OOl) (Montuschi et al. 2000). Similar results were found by Carpagnano who reported a significant increase in exhaled IL-6 and LTB(4) in smokers when compared to non-smokers (p<0.05) (Carpagnano et al. 2003). Another study reported significant increases in total protein, nitrite, and neutrophil chemotactic activity (p<0.05), yet no significant differences in IL-1B and T N F - a (p>0.05) in the E B C of smokers when compared to non-smokers (Garey et al. 2004). In the present study, comparison of average p H value by smoking status, showed roughly similar average values in never smokers and former smokers with reduced average p H in current smokers. Although this was not statistically significant in univariate analysis, in multivariable models, there was a significant relationship between markers of smoking and both p H and lnNH4+. In multivariate analysis, various smoking variables were attempted in the multiple linear regression model. For the E B C p H model, there appeared to be a stronger relationship between p H and current smoking amount (packs per day now); but in the model for I n N H / , the relationship with cumulative smoking amount (average packs/day * years smoked) was stronger. However, when this analysis was repeated in the non-obese subset, the association with packyears became only marginally significant. This suggests that there may possibly be an association between obesity and chronic smoking, when the other variables included in the model are adjusted for. The association of decreased E B C p H with increased current smoking amount suggest that the acute airway response to tobacco smoke inhalation may be differentiated by variation in E B C p H in grain elevator workers. A s well , the association of decreased I n N H / with increased cumulative smoking amount suggest that the l n N H 4 + content in the E B C of grain elevator workers may predict the chronic airway response to tobacco smoke inhalation. , 77 5.18 pH/lnNH4+ and asthma/atopy In both univariate and multivariate analysis, there was no significant association between asthma status and either p H or lnNTiV. This is in contrast to previous reports which have suggested a decline in p H in asthmatics in comparison to controls (Hunt et al. 2000, Kostikas et al. 2002). Hunt et al. reported these findings in asthmatics who had been admitted to the hospital for acute bronchospasm, just prior to E B C testing (Hunt et al. 2000), while Kostikas et al. found similar results in patients with moderate asthma, but not in patients with mild , persistent asthma (Kostikas et al. 2002). Carraro et al. studied the acid-base equilibrium in the E B C of allergic asthmatic children and reported significantly lower p H and NH3 values in the asthmatics, compared to controls (p<0.01 and p<0.001 respectively) (Carraro et aL 2005b). In the present study, the degree o f severity of current asthma in the workers is unknown. A s well , there was a relatively low number of workers with current asthma (n=6). Both of these reasons may explain the lack of association between asthma status and p H or lnNH4+. In contrast, in this study being atopic (or having a positive allergy skin test to common environmental allergens) was significantly associated with increased E B C p H , but not lnNH4+ in multivariate analysis. This significant association o f atopy and p H is again in contrast to the study by Carraro et al. who showed significantly lower p H in allergic, asthmatics (Carraro et al. 2005b). One possibility for this discrepancy is the influence of obesity on atopy. In exploratory analyses of obesity, a partial reverse effect of atopy on obesity was found, after the study population was divided into two subpopulations: obese and non-obese. This suggests that there may be a possible link between atopy and obesity, after adjusting for the other variables in the multiple linear regression model. 5.19 pH/lnNH4 and work area In univariate analysis, reduced p H and reduced lnlMTdV was marginally associated with working in the seed or pellet plant area of the grain elevator (p=0.07, and p=0.11 respectively). Similarly, in multivariate analysis, working in the seed/pellet plant area was marginally significant with p H and lnNH4+. The seed/pellet plant area of the grain elevator transforms dust and other grain by-products from the cleaning process into pellets. Higher moisture and temperatures are usually found in the pellet plant, compared to other areas of the grain elevator. Factors such as stress from the high moisture and temperatures, and exposure to fungi and other chemicals (ie. additives) used in the pellet process may play a role in irritating the airways. This may be seen in the reduction of E B C p H and InMfV" in the workers working in this area. The marginal association with work in the seed/pellet plant (despite no association with measured dust or endotoxin exposure levels on the study day) also suggests the need for further exploration of possible links between airway inflammation and chronic exposure. Working in the office area was also significantly related to reduced p H and reduced l n N H 4 + in univariate analysis (p=0.06, p=0.05 respectively), although this effect disappeared in the multivariable models. These observations are in the opposite direction 78 to what was expected, as workers in the office area are generally not exposed to a lot of grain dust and therefore, would not be expected to have greater airway inflammation than other workers not working in that area. However, in the multivariate analysis, after adjusting for the variables present in the model, working in the office area was not significant. This suggests that there is possible confounding between working in the office area and a combination of other factors in the effect of p H and I n N H / . This effect may be explained by older workers having more seniority at the grain elevators. Workers with higher seniority tend to work more in office jobs, due to the nature o f the positions available in that work area and since these workers are older, they are prone to being obese (r=0.33, p=0.0039 for age and obesity). 5.20 pH/lnNH/ and years of employment in the industry In the present study, years of employment in the industry and obesity were both significantly correlated with age (r=0.49 and P=0.46 respectively), which may be attributed to workers gaining more weight and years of employment in the industry as they age. For p H analysis, when both are included in the multiple linear regression model, years employed in the industry became non-significant, while obesity remained significant. This suggests that obesity may have more o f a stronger relationship with decreased p H than years employed in the industry when both have to be considered. However, when the study population was stratified based upon obesity, years employed in the industry was significant, which suggests a chronic effect o f occupational exposures. In contrast, in the multivariate analysis for l n N H 4 + , obesity became non-significant, while years employed in the industry remained significant. A s well , in the non-obese study population only, years employed in the industry was significant with decreased lnNH4+. Age was also considered in the models, in place o f obesity and years worked in the industry, and was not significant in any of the models. The significant association of years employed in the industry on decreased p H in the non-obese population, and on decreased l n N H 4 + in both the non-obese population and the overall study population, and yet no significant association with age in any models, suggests a chronic effect o f occupational exposures on the airways. 5.21 pH/lnNH4+ and markers of exposure In this study, p H was not associated with grain dust or endotoxin, measured on the study day. Curiously, increased lnNH4+ was significantly associated with increased exposure to grain dust, but not significantly associated with increased exposure to endotoxin. Both of these associations were in the opposite direction o f what was expected. However, in the exploratory analysis of lnNH4 + , increased l n N H 4 + was not significantly associated with grain dust in the non-obese sub-population. This suggests that there may be an effect of grain dust exposure on obesity, after adjusting for the variables in the model, which may also be explained by the effect of older workers being more obese and working in the office area. 79 In multivariate analyses, both decreased p H and l n N H 4 + were significantly associated with hours worked before performing the E B C test in the models. The lack of association between either personal grain dust or endotoxin exposure, but the significant association with hours worked before performing the E B C test possibly suggests that the test is capable of measuring airway inflammation in occupational settings. However, it is also possible that acute occupational exposure such as the level o f dust or endotoxin exposure on one study day may perhaps not be the appropriate measure o f the relevant exposure. The fact that duration of employment i n the industry was a better predictor of p H and l n N H 4 + than personal grain dust and endotoxin exposure measured on the test day, suggests that cumulative exposure intensity may play a larger role than acute exposure intensity in determining differences in p H and l n N H 4 + . Biologically, this corresponds wel l with the idea that controlled airway acidity (in response to single episodes of contact to a lung irritant) may play a large role in the innate, immunological host response by clearing invading pathogens in the airways, while excessive airway acidity, which may be caused by chronic, persistent exposures to a lung irritant, may be damaging to the airways. 5.22 Limitations, strengths, future directions A limitation of the study was that there was no other means to measure inflammation in the airways to compare with the E B C markers. It would have been preferable to compare results with other traditional tests that measure airway inflammation, such as bronchoalveolar lavage or sputum induction. However, these tests are not feasible in occupational field studies due to the high degrees o f invasiveness involved and the specialized facilities required. Another important limitation is other factors that may be involved in predicting airway inflammation, such as diet or stress. Adequate control or measurement of these factors can minimize confounding in the results of future studies. Another limitation is that there was no objective measure of acid reflux and therefore, in the present study, we can only speculate about the role of acid reflux on the markers of E B C . A s well , the exposure samples represented the mean values over the entire shift, while E B C samples were collected randomly through the test day. This limitation was due to the need for exposure sampling across a full workshift in the larger grain study, as well as perceiving difficulty in convincing workers to perform the E B C test at the end of the workshift. Another limitation is that the data from the present study suggests that exposure intensity on the test day may not be the best measure of the exposure linked to airway inflammation. Rather, cumulative exposure intensity may be a better measure of exposure linked to airway inflammation. Mult iple comparisons is another limitation, as multiple analyses was performed on the same data. This increases the probability o f an association being attributed to chance rather than a difference to an actual intervention. Sample size restrictions, mainly due to time constraints, was a limitation in the laboratory study. The present study also has a number of strengths. It was one of the first to evaluate the utility o f E B C to measure airway acidity in an occupational field study. The grain elevator population was ideal for this purpose as it allowed us to select a stratified random sample of workers representative of the range of exposures of grain dust and 80 endotoxin expected in these particular occupational settings. The grain dust levels present in these grain elevators have also been linked to airway inflammation in grain workers in other studies. The present study was 'nested' within the larger cross-sectional grain study, and therefore an extensive amount of information pertaining to the workers' respiratory health was available at no additional costs. This information included personal measurements o f grain dust exposure, as well as several measures of pulmonary function. Another strength of the present study is that the sample size of the field study is relatively large, when compared to most E B C clinical studies. A s well , significant associations were seen with markers of acid-base equilibrium in E B C and some expected risk factors for airways inflammation (ie. smoking, exposure duration, obesity). A future direction for the present study is to repeat the analyses using two other markers of oxidative stress (8-isoprostane and malondialdehyde). These results w i l l provide us with a better understanding of the role of oxidative stress in the airways of workers exposed to grain dust. The employment of E B C in longitudinal studies, as well as over different periods o f the work day, are also interesting possibilities that should be investigated. Finally, the measurement of endotoxin (and perhaps grain dust) in the E B C of grain elevator workers may be worthwhile to evaluate, to serve as a biological measurement of occupational exposure to grain dust and endotoxin. This may be used in addition with the sampling pumps and filters used currently to measure occupational exposures to grain dust and endotoxin. 5.23 Conclusions E B C is still an emerging tool in respiratory health and this study was one o f the first o f its kind to evaluate its utility in occupational field studies. The laboratory component of the study proved that the collection of E B C is simple to perform and can be standardized. The markers of E B C , particularly p H and N H 4 + , are not largely influenced by methodological factors, but variable E B C marker levels are rather influenced by pathological changes occurring in the airways. The field component of the study showed the collection of E B C is feasible in occupational field studies. Some interesting and unexpected results were also found between risk factors of airway acidity, such as obesity, and the E B C marker levels. Gastroesophageal events may have played a role in variable E B C marker levels, although we could not assess this factor. In general, no association between personal inhalable grain dust or endotoxin exposure was found with either of the E B C markers. Further research is heeded to optimise the sensitivity and specificity o f the E B C test, such that the test is responsive to the small inflammatory changes in the airways produced by these personal grain dust exposures. However, other markers of exposure, such as hours worked before performing the E B C test, work area (seed/pellet plant), and years employed in the industry were associated with the E B C markers. These results suggest that E B C p H and N H 4 + may be useful markers of airway inflammation related to acute and chronic occupational exposures. 81 REFERENCES A T S . 1995. Standardization of spirometry, 1994 update. American Thoracic Society. A m J Respir Crit Care M e d 152(3): 1107-1136. 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Wohlford-Lenane C L , Deetz D C , Schwartz D A . 1999. Cytokine gene expression after inhalation of corn dust. A m J Physiol 276(5 Pt l):L736-43. World Health Organization (WHO) . 1999. Hazard prevention and control in the work environment: Airborne dust, chapter 1. dust: Definitions and concepts. 2005(18 Oct. 2005):15. Yap JC, Chan C C , Wang Y T , Poh S C , Lee H S , Tan K T . 1994. A case o f occupational asthma due to barley grain dust. A n n Acad M e d Singapore 23(5):734-736. Zacharasiewicz A , Wilson N , Lex C, L i A , Kemp M , Donovan J, Hooper J, Kharitonov S A , Bush A . 2004. Repeatability of sodium and chloride in exhaled breath condensates. Pediatr Pulmonol 37(3):273-275. 99 Because of the nature of the test, there are no individual results that we are able to pass along to volunteers. Therefore, there are no quantifiable benefits to you as a volunteer. Signing this consent form in no way limits your legal rights against the sponsor, investigators, or anyone else. I, the undersigned, have read and understood the above and I have received a copy of this consent form. I agree to participate in the reassessment study of exhaled breath condensate testing. Subject # Name: : : (please print) Signature Date .Witness:. ^ [ (please print) Signature. .Date Designated Representative of Principal Investigator: Name: r _ _ _ (please print) Signature Date In the unlikely event of any emergency associated with this test, please contact your, family doctor or attend your closest hospital emergency room. Consent form C - protocol reassessment: Version III - December 2004 Page 3 of 3 102 " standards pertaining to acceptable, allowable dust levels can be seen to benefit all grain elevator workers. Signing this consent form in no way limits your legal rights against the sponsor^  investigators, or anyone else. I, the undersigned, have read and understood the above and I have received a copy of this consent form. I agree to participate in the exhaled breath condensate portion of the study of lung health among grain elevator workers. , Subject* Name: ' ; (please print) Signature . Date Witness: . (please print) Signature Date Principle Investigator, Susan Kennedy, PhD Professor School of Occupational & Environmental Hygiene and Department of Health Care & Epidemiology In the unlikely event of any emergency associated with any of the tests in this survey, please contact your family doctor or attend your closest hospital emergency room. Consent form B: Version I - July 2003 Page 3 of 3 104 Appendix 3. General questionnaire for participants in the laboratory component of the study. Oct. 16/04 Version 4 R D University of British Columbia Exhaled Breath Condensate Study -General Questionnaire-Study [ ] Subject [ ] Today's Date [ / / 200 _ ] Time [ : _ _ ] A M / P M Ful l Name: Last [ ] First and initials [ ] Telephone Number: Home: [ ] -Cel l : [ ] -Date of Birth: / / d d m m y y y y Sex: 1. Male 2. Female 1) Chest Colds and Chest Illnesses A . Have you had a cold in the last 6 weeks? 1. Yes 2. N o B . Do you currently have a cold? Day 1: Date: 1. Yes 2. No Day 2: Date: 1. Yes 2. N o Day 3: Date: 1. Yes 2. N o Day 4: Date: 1. Yes 2. N o Day 5: Date: •1. Yes 2. N o Day 6: Date: 1. Yes 2. N o 105 2) Tobacco Smoking Smoking by people l iving around you: In your current household: A . How many residents smoke (other than you)? Your smoking: B . Have you ever smoked cigarettes? 1. Yes 0. N o (No means less than 20 packs of cigarettes or less than one cigarette a day for one year.) If Yes to ' 2 B \ ask: C. Do you now smoke cigarettes? 1. Yes 2. N o (as of one month ago) D . How old were you when you first started years regular cigarette smoking? E . I f you have stopped smoking cigarettes years completely, how old were you when you stopped? F. For how many years did you smoke years regularly? G . How many cigarettes do you smoke per day now? cigarettes per day H . On the average of the entire time you smoked, how many cigarettes did you cigarettes per day smoke per day? If Yes to ' 2 C \ ask: I. How many cigarettes have you Day 1: Date: N o : cigs smoked today? Day 2: Date: N o : cigs Day 3: Date: No : cigs Day 4: Date: , N o : cigs Day 5: Date: N o : cigs 106 J. What is the time interval since you last smoked a cigarette? Day 6: Date: No : Day 1: Time Interval: hrs Day 2: Time Interval: hrs Day 3: Time Interval: hrs Day 4: Time Interval: hrs Day 5: Time Interval: hrs Day 6: Time Interval: hrs cigs mms rains mms mms mins mms 3) Pipe smoking A . Have you ever smoked a pipe regularly? If Yes to ' 3 A ' , a s k : B . Do you now smoke a pipe? (as of one month ago) C. How old were you when you first started to smoke a pipe regularly? D . If you have stopped smoking a pipe completely, how old were you when you stopped? E. How much pipe tobacco do you smoke per week now? (one pouch = 2 oz.) F. On the average of the entire time you smoked a pipe, how much pipe tobacco • did you smoke per week? If Yes to ' 3B ' , a sk : I. How much pipe tobacco have Day 1: Date: you smoked today? Day 2: Date: Day 3: Date: 1. Yes 1. Yes 0. N o 0. N o years years ounces per week ounces per week N o : N o : N o : ounces ounces ounces 107 Day 4: Date: N o : ounces Day 5: Date: N o : ounces Day 6: Date: N o : ounces J. What is the time interval since Day 1: Time Interval: hrs • mins you last smoked a pipe? Day 2: Time Interval: hrs mins Day 3: Time Interval: hrs mins Day 4: Time Interval: hrs mins Day 5: Time Interval: hrs mins Day 6: Time Interval: _____ hrs mins 4) Cigar smoking A . Have you ever smoked cigars regularly? 1. Yes 0. N o (Yes means more than 1 cigar a week for a year.) If Yes to '3 A ' , ask: B . Do you now smoke cigars? 1. Yes 0. N o ' (as of one month ago) C. How old were you when you first started years smoking cigars regularly? D . If you have stopped smoking cigars years completely, how old were you when you stopped? E. How many cigars are you smoking per week now? ounces per week F. On the average of the entire time you smoked cigars, how many cigars ounces per week did you smoke per week? If Yes t o ' 4 B ' , ask: r I. How many cigars have Day 1: Date: N o : cigars you smoked today? 108 Day 2: Date: N o : cigars Day 3: Date: N o : cigars Day 4: Date: N o : cigars Day 5: Date: N o : cigars Day 6: Date: No : cigars J. What is the time interval since Day 1: Time Interval: hrs mins you last smoked a pipe? Day 2: Time Interval: hrs mins Day 3: Time Interval: hrs mins Day 4: Time Interval: hrs mins Day 5: Time Interval: hrs mins Day 6: Time Interval: hrs mins 5) Past Illnesses A . Have you ever had asthma? 1. Yes 2. N o I f Y e s t o ' 5 A \ ask: J. Do you still have it? 1. Yes 2. N o K . Was it confirmed by a doctor? 1. Yes 2. N o L . A t what age did it start? years M . If you no longer have it, at what age years did it stop? N . Do you currently use medication for your asthma? 1. Yes 2. N o If Yes to ' 5N ' , ask : O. What is the type of medication that you use for your asthma? Type: P. What is the time interval Day 1: Time Inteval: hrs mms 109 since you last used your medication? Day 2: Time Interval: Day 3: Time Interval: Day 4: Time Interval: Day 5: Time Interval: Day 6: Time Interval: hrs hrs hrs hrs hrs mms. mins mms mms mms Appendix 4. Conversion table for the smoking characteristics of pipe and cigar smokers. Former Smokers (Smoke=l) Cigarettes Pipe Tobacco (converted to cigs) Cigars (converted to cigs) Casel ppday years smoked packyears ppday years smoked packyears Ppday years smoked packyears Yrs since quitting Total pack years 185 0.1 1 0.1 0.606429 1 0.606429 0 0 0 35 0.706428571 242 1 12 12 ** [»*** 0 0 0 0 23 12 . 385 1 12 12 1.212857 2 2.425714 0 0 0 25 14.42571429 708 1 13 13 0 0 0 0.142857 2 0.285714 29 13.28571429 777 0.1 1* 0.1 0.606429 3 1.819286 0.035714 1 0.035714 19 1.955 1106 2 12 24 *** 12 0 ***** 12 0 29 24 1136 0 0 0 0 0 0 0.017857 5 0.089286 5 0.089285714 3010 0 0 0 0.404286 1 0.404286 0.053571 1 0.053571 9 0.457857143 Current Smokers (Smoke=2) * include former smoking history ' Casel ppday years smoked packyears ppday years smoked packyears Ppday years smoked packyears Yrs since quitting Total pack years ^2658 1 37 37 16.98 2 33.96 0 0 0 0 70.96 2727 1.25 13 16.25 0 0 0 0.267857 Q 33******* 0.088407 0 16.338407 * Started and ended at 14 years old - set as one year cig. Smoked. ** No data for this, therefore, set as zero. *** No data for this, set as zero **** Started and ended at 25 yrs old - set as one year pipe smoked ******* Started cigarette smoking at 49 years - to get 0.33, subtracted date of test by date of when subject turned 49 that year Conversion 1 ounce = 28.349 grams 20 cigarettes = 1 pack 10 grams of tobacco = 10 cigarettes = 4 cigars I l l Append ix 5. Corre la t ion analysis o f the independent variab es invest igated i n the study. Variable AGE bmi SEX white atopyl asthma BRDILAT AGE 1.00 0.33 -0.20 -0.01 -0.34 0.00 0.15 bmi 0.33 1.00 -0.36 0.37 -0.02 0.17 0.35 SEX -0.20 -0.36 1.00 -0.02 0.14 0.12 -0.04 white -0.01 0.37 -0.02 1.00 0.06 -0.02 0.05 atopyl -0.34 -0.02 0.14 0.06 1.00 0.21 0.13 asthma 0.00 0.17 0.12 -0.02 0.21 1.00 0.35 BRDILAT 0.15 0.35 -0.04 0.05 0.13 0.35 1.00 SMOKE 0.10 -0.03 -0.04 0.27 -0.08 -0.16 0.04 SMK1HR -0.11 -0.10 0.01 0.18 0.13 -0.18 -0.05 ppdaynow -0.09 -0.20 0.02 0.13 0.09 -0.19 -0.05 ppdayavecigsyrs 0.24 0.10 -0.07 0.22 -0.21 -0.10 -0.07 COLDCURR -0.18 0.09 -0.01 0.10 -0.01 -0.09 -0.06 P C25 -0.11 -0.18 0.03 -0.37 -0.08 0.02 0.03 LNP C25 0.03 -0.10 -0.03 -0.15 -0.14 -0.06 0.09 P EU25 -0.05 -0.24 0.21 -0.24 0.06 -0.04 -0.01 Inp eu25 -0.04 -0.15 0.09 -0.15 -0.06 0.01 0.06 RESP 0.07 -0.17 0.14 -0.17 0.04 0.03 -0.11 ebcworkbeforetesttime -0.09 -0.09 -0.02 -0.08 0.05 0.07 -0.04 indyears 0.49 0.50 -0.30 0.32 -0.13 0.08 0.23 officejob 0.03 0.09 -0.01 0.10 0.13 -0.03 -0.05 trades 0.26 0.20 -0.16 0.14 -0.18 0.03 -0.07 insideelev -0.34 -0.18 0.08 -0.23 0.05 -0.09 -0.09 otherjob 0.11 -0.08 0.09 0.03 0.00 0.11 0.23 seedpellet 0.03 0.08 -0.09 -0.02 -0.06 -0.04 -0.04 elev -0.14 -0.20 -0.05 -0.39 0.01 -0.08 -0.07 track -0.05 -0.20 0.28 -0.02 0.04 0.12 -0.04 office 0.16 0.12 -0.09 0.12 -0.06 -0.12 -0.04 maint 0.13 0.25 -0.05 0.07 0.19 0.35 -0.02 allover 0.00 0.09 0.00 0.26 -0.03 -0.02 0.12 FEVPP 0.04 -0.15 0.02 -0.06 -0.22 -0.26 -0.10 FVCPP -0.01 -0.31 0.04 -0.24 -0.14 -0.10 0.01 MMFPP 0.05 0.05 -0.04 0.15 -0.20 -0.29 -0.16 chroniccoff 0.12 -0.07 -0.06 -0.11 -0.18 0.26 -0.02 chronicflem 0.11 0.14 -0.09 0.13 0.00 0.41 -0.04 SOBHILL 0.13 0.08 0.06 -0.11 0.17 0 .27 1 -0.07 WEEZOCC -0.03 0.12 0.10 0.11 0.10 0.58 0.24 TITE12M -0.03 -0.01 -0.09 0.12 0.04 0.37 -0.04 COFF12M 0.12 0.18 0.03 0.16 -0.11 0.23 -0.05 SOB12M 0.02 0.17 -0.06 0.08 -0.18 -0.09 -0.02 SOBAM12M 0.00 0.16 -0.06 0.08 0.10 0.37 -0.02 SOBX12M -0.15 0.07 0.24 0.13 0.27 0.33 -0.04 asthlikesymptoms -0.11 0.04 0.17 0.16 0.05 0.50 -0.05 112 Variable SMOKE SMK1HR Ppday now Ppdayave cigsyrs COLDCURR P C25 LNP C25 AGE 0.10 -0.11 -0.09 0.24 -0.18 -0.11 0.03 bmi -0.03 -0.10 -0.20 0.10 0.09 -0.18 -0.10 SEX -0.04 0.01 0.02 -0.07 -0.01 0.03 -0.03 white 0.27 0.18 0.13 0.22 0.10 -0.37 -0.15 atopyl -0.08 0.13 0.09 -0.21 -0.01 -0.08 -0.14 asthma -0.16 -0.18 -0.19 -0.10 -0.09 0.02 -0.06 BRDILAT 0.04 -0.05 -0.05 -0.07 -0.06 0.03 0.09 SMOKE 1.00 0.71 0.74 0.53 0.19 -0.04 -0.03 SMK1HR 0.71 1.00 0.88 0.37 0.17 -0.05 -0.02 ppdaynow 0.74 0.88 1.00 0.37 0.16 0.03 0.02 Ppdayave cigsyrs 0.53 0.37 0.37 1.00 0.03 -0.12 -0.13 COLDCURR 0.19 0.17 0.16 0.03 1.00 0.05 -0.03 P C25 -0.04 -0.05 0.03 -0.12 0.05 1.00 0.76 LNP C25 -0.03 -0.02 0.02 -0.13 -0.03 0.76 1.00 P EU25 0.18 0.19 0.25 -0.05 -0.02 0.69 0.57 Inp eu25 0.03 0.08 0.09 -0.17 -0.03 0 63 0.87 RESP -0.15 -0.02 -0.03 -0.14 -0.21 0.19 0.34 Ebcwork beforetesttime -0.02 -0.06 0.09 -0.16 0.01 0.21 0.20 indyears 0.04 -0.10 -0.12 0.07 0.07 -0.19 -0.05 officejob 0.01 -0.11 -0.13 0.15 0.12 -0.32 -0.57 trades 0.01 0.01 -0.03 0.11 0.05 -0.01 0.14 insideelev -0.05 0.04 0.00 -0.14 -0.15 0.33 0.34 otherjob 0.03 0.04 0.15 -0.09 0.00 -0.07 -0.01 seedpellet 0.09 0.14 0.13 0.09 -0.01 -0.13 -0.06 elev -0.23 -0.16 -0.16 -0.21 -0.03 0.17 0.12 track 0.03 0.01 0.13 -0.08 0.11 -0.11 -0.18 office 0.09 0.14 0.12 0.28 0.24 -0.13 -0.22 maint -0.17 -0.07 -0.07 -0.10 0.13 0.02 0.04 allover 0.14 0.00 -0.05 0.06 -0.20 0.05 0.14 FEVPP 0.06 -0.05 -0.05 0.15 -0.06 0.04 0.09 FVCPP 0.06 0.00 0.10 0.14 -0.11 -0.01 0.01 MMFPP 0.01 -0.12 -0.18 0.03 0.12 0.03 0.09 chroniccoff 0.06 0.10 0.14 0.20 -0.10 0.05 0.13 chronicfiem 0.04 -0.01 0.00 0.04 0.08 0.00 0.08 SOBHILL -0.10 0.00 -0.01 0.06 -0.12 0.11 0.02 WEEZOCC 0.11 -0.03 -0.04 0.09 -0.15 -0.12 -0.11 TITE12M -0.04 -0.13 -0.13 0.05 -0.01 -0.04 0.02 COFF12M 0.12 0.04 -0.02 0.09 0.12 0.08 0.07 SOB12M -0.03 -0.09 -0.09 0.02 0.08 -0.08 -0.02 SOBAM12M -0.03 -0.09 -0.09 0.00 -0.10 0.00 0.02 SOBX12M -0.08 -0.14 -0.14 -0.06 -0.03 -0.17 -0.26 asthlikesymptoms 0.02 -0.06 -0.06 0.09 -0.08 -0.01 -0.03 113 Variable P EU25 Inp_eu25 RESP Ebcworkbefore testtime indyears officejob trades AGE -0.05 -0.04 0.07 -0.09 0.49 0.03 0.26 bmi -0.24 -0.15 -0.17 -0.09 0.50 0.09 0.20 SEX 0.21 0.09 0.14 -0.02 -0.30 -0.01 -0.16 white -0.24 -0.15 -0.17 -0.08 0.32 0.10 0.14 atopyl 0.06 -0.06 0.04 0.05 -0.13 0.13 -0.18 asthma -0.04 0.01 0.03 0.07 0.08 -0.03 0.03 BRDILAT -0.01 0.06 -0.11 -0.04 0.23 -0.05 -0.07 SMOKE 0.18 0.03 -0.15 -0.02 0.04 0.01 0.01 SMK1HR 0.19 0.08 -0.02 -0.06 -0.10 -0.11 0.01 ppdaynow 0.25 0.09 -0.03 0.09 -0.12 -0.13 -0.03 ppdayavecigsyrs -0.05 -0.17 -0.14 -0.16 0.07 0.15 0.11 COLDCURR -0.02 -0.03 -0.21 0.01 0.07 0.12 0.05 P C25 0.69 0.63 0.19 0.21 -0.19 -0.32 -0.01 LNP C25 0.57 0.87 0.34 0.20 -0.05 -0.57 0.14 P EU25 1.00 0.70 0.22 0.02 -0.19 -0.23 -0.04 Inp eu25 0.70 1.00 0.36 0.13 -0.12 -0.57 0.10 RESP 0.22 0.36 1.00 -0.03 -0.18 -0.28 -0.18 Ebcworkbefore testtime 0.02 0.13 -0.03 1.00 -0.22 -0.25 0.13 indyears -0.19 -0.12 -0.18 -0.22 1.00 0.24 0.32 officejob -0.23 -0.57 -0.28 -0.25 0.24 1.00 -0.26 trades -0.04 0.10 -0.18 0.13 , 0.32 -0.26 1.00 insideelev 0.30 0.38 0.27 0.08 -0.50 -0.36 -0.43 otherjob -0.10 -0.02 0.13 0.01 0.03 -0.25 -0.29 seedpellet -0.08 -0.02 0.14 -0.17 -0.08 -0.14 -0.16 elev 0.08 0.13 0.14 -0.08 -0.16 -0.11 -0.24 track -0.12 -0.13 -0.06 0.22 -0.08 -0.14 -0.16 office -0.14 -0.32 -0.06 -0.20 0.22 0.49 -0.16 maint 0.03 0.05 0.02 0.07 0.14 -0.08 0.30 allover 0.11 0.13 -0.13 0.12 0.05 0.00 0.37 FEVPP 0.02 0.07 0.11 0.00 -0.06 -0.09 0.16 FVCPP -0.01 0.00 0.17 -0.01 -0.05 -0.10 -0.09 MMFPP 0.02 0.08 -0.01 -0.03 -0.03 -0.04 0.31 chroniccoff 0.05 0.14 0.10 -0.09 0.12 -0.10 0.05 chronicflem -0.05 0.06 0.00 0.16 0.22 -0.03 0.25 SOBHILL 0.02 0.09 0.17 0.00 0.08 0.12 -0.04 WEEZOCC -0.07 -0.01 0.03 -0.02 0.08 0.02 -0.04 TITE12M -0.04 0.01 0.04 -0.02 0.02 0.11 0.07 COFF12M 0.24 0.08 0.05 -0.23 0.17 0.12 0.15 SOB12M -0.09 -0.05 -0.18 -0.17 0.11 0.08 -0.11 SOBAM12M 0.00 0.02 -0.04 0.00 0.03 0.08 0.05 SOBX12M -0.08 -0.09 -0.10 -0.13 -0.04 0.32 -0.07 asthlikesymptoms 0.15 0.06 -0.03 -0.15 -0.02 0.02 0.06 114 Variable insideelev otherjob seedpellet elev track office maint AGE -0.34 0.11 0.03 -0.14 -0.05 0.16 0.13 bmi -0.18 -0.08 0.08 -0.20 -0.20 0.12 0.25 SEX 0.08 0.09 -0.09 -0.05 0.28 -0.09 -0.05 white -0.23 0.03 -0.02 -0.39 -0.02 0.12 0.07 atopyl 0.05 0.00 -0.06 0.01 0.04 -0.06 0.19 asthma -0.09 0.11 -0.04 -0.08 0.12 -0.12 0.35 BRDILAT -0.09 0.23 -0.04 -0.07 -0.04 -0.04 -0.02 SMOKE -0.05 0.03 0.09 -0.23 0.03 0.09 -0.17 SMK1HR 0.04 0.04 0.14 -0.16 0.01 0.14 -0.07 ppdaynow 0.00 0.15 0.13 -0.16 0.13 0.12 -0.07 ppdayavecigsyrs -0.14 -0.09 0.09 -0.21 -0.08 0.28 -0.10 COLDCURR -0.15 0.00 -0.01 -0.03 0.11 0.24 0.13 P C25 0.33 -0.07 -0.13 0.17 -0.11 -0.13 0.02 LNP C25 0.34 -0.01 -0.06 0.12 -0.18 -0.22 0.04 P EU25 0.30 -0.10 -0.08 0.08 -0.12 -0.14 0.03 Inp eu25 0.38 -0.02 -0.02 0.13 -0.13 -0.32 0.05 RESP 0.27 0.13 0.14 0.14 -0.06 -0.06 0.02 Ebcworkbefore testtime 0.08 0.01 -0.17 -0.08 0.22 -0.20 0.07 indyears -0.50 0.03 -0.08 -0.16 -0.08 0.22 0.14 officejob -0.36 -0.25 -0.14 -0.11 -0.14 0.49 -0.08 trades -0.43 -0.29 -0.16 -0.24 -0.16 -0.16 0.30 insideelev 1.00 -0.39 . -0.02 0.47 -0.22 -0.22 -0.13 otherjob -0.39 1.00 0.33 -0.21 0.57 -0.03 -0.08 seedpellet -0.02 0.33 1.00 -0.16 -0.09 -0.09 -0.05 elev 0.47 -0.21 -0.16 1.00 -0.16 -0.16 -0.09 track -0.22 0.57 -0.09 -0.16 1.00 -0.09 -0.05 office -0.22 -0.03 -0.09 -0.16 -0.09 1.00 -0.05 maint -0.13 -0.08 -0.05 -0.09 -0.05 -0.05 1.00 allover -0.11 -0.26 -0.29 -0.56 -0.29 -0.29 -0.16 FEVPP -0.06 -0.02 0.12 0.28 -0.13 -0.03 -0.15 FVCPP 0.06 0.11 0.06 0.26 0.06 -0.03 -0.14 MMFPP -0.12 -0.16 0.10 0.08 -0.23 -0.05 -0.09 chroniccoff -0.01 0.06 -0.06 0.05 -0.06 0.19 -0.03 chronicflem -0.05 -0.16 -0.09 -0.07 -0.09 -0.09 0.52 SOBHILL 0.00 -0.07 -0.17 0.04 0.06 0.06 0.28 WEEZOCC -0.04 0.07 0.10 -0.20 0.10 -0.15 0.13 TITE12M -0.02 -0.15 -0.09 -0.16 -0.09 0.10 0.26 COFF12M -0.06 -0.20 -0.11 -0.22 -0.11 0.17 0.18. SOB12M 0.13 -0.10 -0.06 0.05 -0.06 0.19 -0.03 SOBAM12M -0.01 -0.10 -0.06 -0.11 -0.06 -0.06 0.39 SOBX12M -0.15 -0.05 -0.09 -0.07 0.08 0.08 -0.05 asthlikesymptoms 0.03 -0.11 -0.11 -0.22 0.03 0.03 0.18 115 Variable allover FEVPP FVCPP MMFPP chroniccoff chronicflem SOBHILL AGE 0.00 0.04 -0.01 0.05 0.12 0.11 0.13 bmi 0.09 -0.15 -0.31 0.05 -0.07 0.14 0.08 SEX 0.00 0.02 0.04 -0.04 -0.06 -0.09 0.06 white 0.26 -0.06 -0.24 0.15 -0.11 0.13 -0.11 atopyl -0.03 -0.22 -0.14 -0.20 -0.18 0.00 0.17 asthma -0.02 -0.26 -0.10 -0.29 0.26 0.41 0.27 BRDILAT 0.12 -0.10 0.01 -0.16 -0.02 -0.04 -0.07 SMOKE 0.14 0.06 0.06 0.01 0.06 0.04 -0.10 SMK1HR 0.00 -0.05 0.00 -0.12 0.10 -0.01 0.00 ppdaynow -0.05 -0.05 0.10 -0.18 0.14 0.00 -0.01 ppdayavecigsyrs 0.06 0.15 0.14 0.03 0.20 0.04 0.06 COLDCURR -0.20 -0.06 -0.11 0.12 -0.10 0.08 -0.12 P C25 0.05 0.04 -0.01 0.03 0.05 0.00 0.11 LNP C25 0.14 0.09 0.01 0.09 0.13 0.08 0.02 P EU25 0.11 0.02 -0.01 0.02 0.05 -0.05 0.02 Inp eu25 0.13 0.07 0.00 0.08 0.14 0.06 0.09 RESP -0.13 0.11 0.17 -0.01 0.10 0.00 0.1.7 Ebcworkbefore testtime 0.12 0.00 -0.01 -0.03 -0.09 0.16 0.00 indyears 0.05 -0.06 -0.05 -0.03 0.12 0.22 0.08 officejob 0.00 -0.09 -0.10 -0.04 -0.10 -0.03 0.12 trades 0.37 0.16 -0.09 0.31 0.05 0.25 -0.04 insideelev -0.11 -0.06 0.06 -0.12 -0.01 -0.05 0.00 otherjob -0.26 -0.02 0.11 -0.16 0.06 -0.16 -0.07 seedpellet -0.29 0.12 0.06 0.10 -0.06 -0.09 -0.17 elev -0.56 0.28 0.26 0.08 0.05 -0.07 0.04 track -0.29 -0.13 0.06 -0.23 -0.06 -0.09 0.06 office -0.29 -0.03 -0.03 -0.05 0.19 -0.09 0.06 maint -0.16 -0.15 -0.14 -0.09 -0.03 0.52 0.28 allover 1.00 -0.17 -0.23 0.06 -0.07 0.05 -0.09 FEVPP -0.17 1.00 0.65 0.67 -0.07 -0.12 -0.12 FVCPP -0.23 0.65 1.00 0.05 0.22 -0.08 -0.19 MMFPP 0.06 0.67 0.05 1.00 -0.28 -0.12 -0.02 chroniccoff -0.07 -0.07 0.22 -0.28 1.00 0.17 0.04 chronicflem 0.05 -0.12 -0.08 -0.12 0.17 1.00 0.24 SOBHILL -0.09 -0.12 -0.19 -0.02 0.04 0.24 1.00 WEEZOCC 0.10 -0.15 -0.02 -0.19 0.24 0.30 0.25 TITE12M 0.10 -0.15 -0.17 -0.06 -0.06 0.24 0.28 COFF12M 0.16 -0.10 -0.13 -0.03 0.12 0.28 -0.04 SOB12M -0.07 0.10 0.06 0.06 -0.04 -0.06 -0.12 SOBAM12M 0.07 -0.04 -0.08 0.00 -0.04 0.17 0.20 SOBX12M 0.05 -0.09 -0.17 0.06 0.17 0.06 0.34 asthlikesymptoms 0.16 -0.18 -0.15 -0.14 0.12 0.28 0.22 116 Variable weezocc tite12m coff12m sob12m Sobam12m sobx12m Asthlike symptoms AGE -0.03 -0.03 0.12 0.02 0.00 -0.15 -0.11 bmi 0.12 -0.01 0.18 0.17 0.16 0.07 0.04 SEX 0.10 -0.09 0.03 -0.06 -0.06 0.24 0.17 white 0.11 0.12 0.16 0.08 0.08 0.13 0.16 atopyl 0.10 0.04 -0.11 -0.18 0.10 0.27 0.05 asthma 0.58 0.37 0.23 -0.09 0.37 0.33 0.50 BRDILAT 0.24 -0.04 -0.051 -0.02 -0.02 -0.04 -0.05 SMOKE 0.11 -0.04 0.12 -0.03 -0.03 -0.08 0.02 SMK1HR -0.03 -0.13 0.04 -0.09 -0.09 -0.14 -0.06 ppdaynow -0.04 -0.13 -0.02 -0.09 -0.09 -0.14 -0.06 Ppdayave cigsyrs 0.09 0.05 0.09 0.02 0.00 -0.06 0.09 COLDCURR -0.15 -0.01 0.12 0.08 -0.10 -0.03 -0.08 P C25 -0.12 -0.04 0.08 -0.08 0.00 -0.17 -0.01 LNP C25 -0.11 0.02 0.07 -0.02 0.02 -0.26 -0.03 P EU25 -0.07 -0.04 0.24 -0.09 0.00 -0.08 0.15 Inp eu25 -0.01 0.01 0.08 -0.05 0.02 -0.09 0.06 RESP 0.03 0.04 0.05 -0.18 -0.04 -0.10 -0.03 Ebcworkbefore testtime -0.02 -0.02 -0.23 -0.17 0.00 -0.13 -0.15 indyears 0.08 0.02 0.17 0.11 0.03 -0.04 -0.02 officejob 0.02 0.11 0.12 0.08 0.08 0.32 0.02 trades -0.04 0.07 0.15 -0.11 0.05 -0.07 0.06 insideelev -0.04 -0.02 -0.06 0.13 . -0.01 -0.15 0.03 otherjob 0.07 -0.15 -0.20 -0.10 -0.10 -0.05 -0.11 seedpellet 0.10 -0.09 -0.11 -0.06 -0.06 -0.09 -0.11 elev -0.20 -0.16 -0.22 0.05 -0.11 -0.07 -0.22 track 0.10 -0.09 -0.11 -0.06 -0.06 0.08 0.03 office -0.15 0.10 0.17 0.19 -0.06 0.08 0.03 maint 0.13 0.26 0.18 -0.03 0.39 -0.05 0.18 allover 0.10 0.10 0.16 -0.07 0.07 0.05 0.16 FEVPP -0.15 -0.15 -0.10 0.10 -0.04 -0.09 -0.18 FVCPP -0.02 -0.17 -0.13 0.06 -0.08 -0.17 -0.15 MMFPP -0.19 -0.06 -0.03 0.06 0.00 0.06 -0.14 chroniccoff 0.24 -0.06 0.12 -0.04 -0.04 0.17 0.12 chronicflem 0.30 0.24 0.28 -0.06 0.17 0.06 0.28 SOBHILL 0.25 0.28 -0.04 .. -0.12 0.20 0.34 0.22 WEEZOCC 1.00 0.47 0.10 -0.10 0.24 0.19 0.49 TITE12M 0.47 1.00 0.32 0.19 0.44 0.08 0.75 COFF12M 0.10 0.32 1.00 0.32 0.32 0.01 0.54 SOB12M -0.10 0.19 0.32 1.00 0.31 -0.06 0.32 SOBAM12M 0.24 0.44 0.32 0.31 1.00 0.17 0.52 SOBX12M 0.19 0.08 0.01 -0.06 0.17 1.00 0.28 Asthlike symptoms 0.49 0.75 0.54 0.32 0.52 0.28 1.00 117 Appendix 6. Univariate analyses of p H and other independent variables. Categorical Variable pH mean (sd) P Demographic features Sex Male 7.26 (1.29) 0.2 Female 7.95 (0.38) Race Caucasian 7.21 (1.32) 0.073 Non-caucasian 7.94 (0.30) Grain elevator UGG (1) 7.28(1.00) 0.73 Pacific (4) 7.32 (1.37) Cascadia (2) 7.64 (1.01) Saskatchewan (3) 7.35 (1.44) JRI (5) 7.03 (1.46) Asthma/Atopy Atopy Yes 7.62 (1.02) 0.058 No 7.07.(1.37) Asthma Never 7.24 (1.30) 0.55 Former 7.57 (1.23) Current 7.74 (0.51) Asthma-like symptoms Yes 7.51 (1.08) 0.6 No 7.28 (1.28) Current cold Yes 7.25(1.42) 0.83 No 7.33 (1.22) Smoking History Smoking status Never 7.56(1.03) 0.091 Former 7.33 (1.22) Current 6.71 (1.62) Smoked in the last hour Yes 6.64 (1.67) 0.041 No 7.44 (1.13) Exposure Measurements -Job Titles Office Yes 7.07(1.46) 0.42 No 7.37 (1.21) Trades Yes 7.18 (1.31) 0.6 No 7.35(1.24) Inside elevator Yes 7.38(1.25) 0.7 No 7.27(1.27) Other Yes 7.55 (1.04) 0.39. No 7.25(1.30) Work Area Seed and pellet plant Yes 6.42 (1.62) 0.069 No 7.39 (1.20) Inside elevator Yes 7.59 (1.04) 0.29 No 7.23 (1.31) Trackshed Yes 7.92 (0.16) 0.22 No 7.26 (1.29) Office Yes 6.39(1.80) 0.06 No 7.39 (1.18) Maintenance Yes 7.45 (0.95) 0.88 1 1 8 No 7.31 (1.26) All over Yes 7.36 (1.22) 0.72 No 7.26(1.30) Respirator on test day Yes 7.42 (1.18) 0.51 No 7.23 (1.31) Chronic Respiratory Symptoms Chronic cough Yes 6.85(1.57) 0.52 No 7.33 (1.25) Chronic phlegm Yes 6.73 (1.59) 0.2 No 7.37 (1.21) Breathlessness Yes 7.31 (1.19) 1 No 7.31 (1.28) Occasional wheeze Yes 7.49 (0.94) 0.55 No 7.27(1.32) Acute respiratory symptoms Woken with chest tightness Yes 7.78 (0.51) 0.35 No 7.27 (1.29) Woken by cough Yes 7.25(1.29) 0.88 No 7.32 (1.26) Woken by breathlessness Yes 6.84 (1.89) 0.51 No 7.33 (1.24) Breathless during the day Yes 6.51 (1.71) 0.26 No 7.34 (1.24) Breathless after exercise Yes 7.55 (1.19) 0.61 No 7.29 (1.26) Continuous Variable EBC NH4+ = Intercept + (Coefficient x Variable) Demographic features Intercept (Coefficient, SE), p Coefficient se P Age 8.40 (0.91), p<0.0001 -0.023 0.019 0.23 Body Mass Index 9.57 (0.89), p<0.0001 -0.08 0.031 0.012 Smoking History Packs per day now 7.45 (0.15), p<0.0001 -0.94 0.44 0.034 Packyears 7.53 (0.16), p<0.0001 -0.02 0.0082 0.016 Personal Exposure Grain dust (mg/m3) 7.24 (0.18), p<0.0001 0.04 0.062 0.53 Ln Grain dust (Ln(mg/m3)) 7.32 (0.15), p<0.0001 0.1 0.62 0.54 Endotoxin (EU/m3) 7.26 (0.17), pO.0001 0.000047 0.000082 0.57 Ln Endotoxin (Ln(EU/m3)) 6.95 (0.57), pO.0001 0.059 0.092 0.52 Hours worked on test day before performing the EBC test 7.75 (0.32), p<0.0001 -0.13 0.085 0.13 Years worked in the industry 7.79 (0.33), p<0.0001 -0.025 0.016 0.12 Lung Function FEVPP 8.69 (1.09), pO.0001 -0.014 0.011 0.22 FVCPP 7.97 (1.24), p<0.0001 -0.0061 0.012 0.61 MMFPP 8.04 (0.45), p<0.0001 -0.0076 0.0047 0.11 119 Appendix 7. Univariate analyses of NH4+ and other independent variables. Categorical Variables NH4+ mean (sd) P Demographic features Sex Male 511.09 (489.05) 0.9 Female 536.16(143.11) Race Caucasian 492.41 (496.84) 0.36 Non-caucasian 635.15 (248.61) Grain elevator UGG (1) 496.01 (482.30) 0.87 Pacific (4) 445.78 (275.88) Cascadia (2) 526.24 (404.47) Saskatchewan (3) 649.09 (634.14) JRI (5) 489.81 (553.89) Asthma/Atopy Atopy Yes 585.89 (493.35) 0.24 No 457.18(450.15) Asthma Never 503.67 (466.42) 0.55 Former 684.42 (651.81) Current 411.75(244.36) Asthma-like symptoms Yes 369.32 (205.14) 0.3 No 534.85 (496.01) Current cold Yes 560.88 (584.25) 0.68 No 502.27 (445.96) Smoking History Smoking status Never 504.36 (379.54) 0.53 Former 579.40 (580.60) , Current 408.39 (431.53) Smoked in the last hour Yes 389.76 (445.51) 0.33 No 536.19 (474.90) Exposure Measurements Job Titles Office Yes 427.30 (600.33) 0.45 No 532.43 (439.76) Trades Yes 448.37 (401.66) 0.51 No 533.15(491.46) Inside elevator Yes 603.09 (526.57) 0.2 No 460.56 (431.79) Other Yes 503.38 (292.96) 0.93 No 515.65 (509.55) Work Area Seed and pellet plant Yes 271.66 (257.77) 0.19 No 533.76 (479.98) Inside elevator Yes 625.06 (513.98) 0.25 No 478.31 (455.41) Trackshed Yes 492.56 (176.00) 0.91 No 514.82 (488.28) 120 Office Yes 508.51 (908.37) 0.98 No 513.46 (425.33) Maintenance Yes 361.85 (373.72) 0.65 No 517.15(474.30) All over Yes 510.05 (426.83) 0.96 No 516.09 (516.40) Respirator on test day Yes 622.64 (586.66) 0.075 No 428.98 (341.38) Chronic Respiratory Symptoms Chronic cough Yes 168.66 (103.91) 0.2 No 527.22 (474.58) Chronic phlegm Yes 229.91 (215.07) 0.095 No 541.79(480.70) Breathlessness Yes 507.59 (528.18) 0.95 No 514.89 (454.86) Occasional wheeze Yes 386.70 (253.83) 0.25 No 544.14 (506.75) Acute respiratory symptoms Woken with chest tightness Yes 418.94 (240.85) 0.61 No 521.13 (485.45) Woken by cough Yes 600.20 (755.08) 0.53 No 499.86 (418.60) Woken by breathlessness Yes 333.76 (311.67) 0.5 No 520.44 (476.00) Breathless during the day Yes 247.45 (239.64) 0.32 No 523.98 (475.41) Breathless after exercise Yes 703.53 (786.34) 0.26 No 493.74 (430.78) Cont inuous Variables EBC NH4+ = Intercept + (Coefficient x Variable) Demographic features Intercept (coefficient, se), p Coefficient se P Age 918.13(342.56), p=0.0091 -8.65 7.22 0.24 Body Mass Index 697.76 (348.83), (p=0.049) -6.61 12.05 0.59 Smoking History Packs per day now 547.51 (58.90), p<0.0001 -235.63 166.69 0.16 Packyears 566.03 (62.89), p<0.0001 -5.02 3.15 0.11 Personal Exposure Grain dust (mg/m3) 456.26 (67.88), p<0.0001 31.58 23.11 0.18 Ln Grain dust (Ln(mg/m3)) 512.40 (54.11), pO .0001 50.6 38.86 0.2 Endotoxin (EU/m3) 506.41 (64.65), p<0.0001 0.0059 0.031 0.85 Ln Endotoxin (Ln(EU/m3)) 306.37 (214.90), p=0.16 34.02 34.24 0.32 Hours worked on test day before performing 668.78 (119.16), p<0.0001 -46.69 31.91 0.15 the EBC test Years worked in the industry 684.62 (125.99), pO .0001 -8.96 5.95 0.14 Lung Function FEVPP 306.84 (424.68), p=0.47 2.11 4.29 0.62 FVCPP 422.45 (480.45), p=0.38 0.9 4.69 0.85 MMFPP 483.05(176.97), p=0.0080 0.34 1.84 0.85 121 Appendix 8. Univariate analyses of lnNH4+ and other independent variables. Categorical Variables lnNH4+ mean (sd) P Demographic features Sex Male 5.78 (1.06) 0.28 Female 6.25 (0.27) Race Caucasian 5.72 (1.06) 0.057 Non-caucasian 6.36 (0.51) Grain elevator UGG(1) 5.77(1.09) 0.91 Pacific (4) 5.81 (0.91) Cascadia (2) 5.96 (0.87) Saskatchewan (3) 5.96 (1.23) JRI (5) 5.66 (1.12) Asthma/Atopy Atopy Yes 6.02 (0.98) 0.13 No 5.67 (1.04) Asthma Never 5.78 (1.05) 0.74 Former 6.10 (1.09) Current 5.84 (0.72) Asthma-like symptoms Yes 5.74 (0.67) 0.79 No 5.83 (1.07) Current cold Yes 5.86(1.09) 0.86 No 5.81 (1.02) Smoking History Smoking status Never 5.88 (0.98) 0.27 Former 5.94 (0.96) Current 5.43(1.20) Smoked in the last hour Yes 5.37 (1.21) 0.098 No 5.90 (0.97) Exposure Measurements Job Titles Office Yes 5.39(1.22) 0.086 No 5.91 (0.96) Trades Yes 5.68 (1.04) 0.52 No 5.86(1.02) Inside elevator Yes 6.03 (0.97) 0.17 No 5.69(1.04) Other Yes 5.97 (0.85) 0.5 No 5.77 (1.07) Work Area Seed and pellet plant Yes 5.17(1.05) 0.11 No 5.87 (1.01) Inside elevator Yes 6.12 (0.92) 0.15 No 5.72(1.04) Trackshed Yes 6.15 (0.34) 0.41 No 5.79 (1.06) Office Yes 5.04(1.66) 0.051 No 5.88 (0.94) Maintenance Yes 5.51 (1.31) 0.67 122 No 5.82 (1.02) All over Yes 5.86 (0.96) 0.71 No 5.77(1.10) Respirator on test day Yes 6.00 (1.03) 0.16 No 5.67 (1.00) Chronic Respiratory Symptoms Chronic cough Yes 4.96 (0.75) 0.14 No 5.85(1.02) Chronic phlegm Yes 5.04 (0.99) 0.033 No 5.89 (1.00) Breathlessness Yes 5.74 (1.12) 0.72 No 5.84 (1.00) Occasional wheeze Yes 5.70 (0.80) 0.63 No 5.84 (1.07) Acute respiratory symptoms Woken with chest tightness Yes 5.84 (0.77) 0.96 No 5.81 (1.05) Woken by cough Yes 5.85(1.03) 0.9 No 5.81 (1.03) Woken by breathlessness Yes 5.53 (0.91) 0.62 No 5.83(1.03) Breathless during the day Yes 5.21 (0.91) 0.3 No 5.84 (1.03) Breathless after exercise Yes 5.94 (1.44) 0.74 No 5.80 (0.98) Continuous Variables EBC lnNH4+ = Intercept + (Coefficient x Variable) Demographic features Intercept (coefficient, se), p Coefficient se P Age 7.05 (0.74), p<0.0001 -0.026 0.016 0.094 Body Mass Index 7.00 (0.74), p<0.0001 -0.042 0.026 0.11 Smoking History Packs per day now 5.91 (0.13), p<0.0001 -0.67 0.36 0.067 Packyears 5.96(0.14), p<0.0001 -0.014 0.0068 0.041 Personal Exposure Grain dust (mg/m3) 5.67 (0.15), pO.0001 0.081 0.05 0.11 Ln Grain dust (Ln(mg/m3)) 5.84 (0.12), p<0.0001 0.14 0.084 0.098 Endotoxin (EU/m3) 5.75 (0.14), p<0.0001 0.000054 0.000067 0.42 Ln Endotoxin (Ln(EU/m3)) 5.12 (0.46), p<0.0001 0.12 0.074 0.12 Hours worked on test day before performing 6.21 (0.26), p<0.0001 -0.12 0.069 0.094 the EBC test Years worked in the industry 6.34 (0.27), p<0.0001 -0.027 0.013 0.034 Lung Function FEVPP 6.078 (0.91), p<0.0001 -0.0026 0.0092 0.78 FVCPP 5.98(1.03), p<0.0001 -0.0015 0.01 0.88 MMFPP 6.081 (0.38), pO.0001 -0.0028 0.0039 0.48 

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