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The relationship of particulate matter retention in the lung to the severity of chronic obstructive pulmonary… Ling, Sean Hilton 2009

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THE RELATIONSHIP OF PARTICULATE MATTER RETENTION IN THE LUNG TO THE SEVERITY OF CHRONIC OBSTRUCTIVE PULMONARY DISEASE by SEAN HILTON LING B.Sc., The University of Alberta, 2006 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE in THE FACULTY OF GRADUATE STUDIES (Experimental Medicine) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) August 2009 © Sean Hilton Ling, 2009 Abstract Particulate matter (PM) deposited into the lung is removed predominantly by ciliary action of epithelial cells in the airways and by macrophages that phagocytose these particles in the peripheral air space. We hypothesizethat the particle load or burden in the lungs’ ofpatients with Chronic Obstructive Pulmonary Disease (COPD) are responsible for perpetuating the chronic inflammatory response in the lung ofsubjects with COPD (even after smoking cessation). Samples were selected to cover the whole range of severity of COPD. Quantitative histological methods were used to quantif’ and characterize the particle burden in the lung tissue. The volume fraction (Vv) of PM in the lung tissue, including the parenchyma, airways, alveolar macrophages, blood vessels, and lymphoid follicles was determined using the aforementioned methods. To determine the chemical composition of the PM, Raman spectroscopy was used to analyze samples in situ. PM could be found in virtually all compartments of the lung: the parenchyma, blood vessels, airways, lymphoid follicles, and alveolar macrophages. The total burden of PM in all tissues of the lung was higher in subjects with COPD compared to controls (p<O.OO1) as well as in smokers with normal lung function (p<O.O1). There was an incremental increase in PM with increased COPD severity that peaks at GOLD 2 and then falls off in the GOLD 3/4 group. These fmdings were very similar in analysis to the lung parenchyma, but the same relationship was not found in the blood vessels and lymphoid follicles. An increase in lung PM burden correlated with a decline in FEV1/FVC and pack years smoking. The PM in the lung tissue was found to have a similar Raman spectrum to that of carbonaceous soot. 11 We conclude that PM is retained in the lung of COPD subjects. Whether just the burden of exposure or whether poor clearance of PM from the lungs is responsible, remains unclear from our data. We speculate that this retained PM could perpetuate the chronic inflammatory response in the lung and contribute to the progression of COPD. 111 Table of Contents Abstract.ii Table of Contents iv List of Tables vii List of Figures viii Acknowledgements xi Dedication xii 1 Chapter One: Chronic Obstructive Pulmonary Disease 1 1.1 Definition 1 1.1.1 COPD Severity Categories 2 1.2 Burden of COPD 3 1.2.1 Prevalence 3 1.2.2 Morbidity and Mortality 5 1.2.3 Economic and Social Costs 6 1.3 Risk Factors 7 1.3.1 Smoking 7 1.3.2 Air Pollution 7 1.3.3 Occupational Exposure 8 1.3.4 Gender 9 1.3.5 Genetics 9 1.3.6 Infections 10 1.4 Pathology of COPD 11 1.4.1 Pathogenesis 11 1.4.2 Pathophysiology 15 1.4.3 Exacerbations 18 2 Chapter Two: Particulate Matter 20 2.1 Definition 20 2.1.1 ParticleSize 20 2.1.2 Composition 22 2.2 Sources of Particles 22 2.2.1 Coal 22 2.2.2 Petroleum 23 2.2.3 Traffic 24 2.2.4 Biomass 24 2.3 Epidemiology 26 2.4 Deposition and Clearance of PM from the Lung 28 2.4.1 Deposition 28 2.4.2 Clearance 29 2.5 Mechanisms of PM-induced Lung Inflammation 31 2.5.1 AM Response 31 2.5.2 Lung Epithelial Cell Response 32 2.5.3 PM-induced Lung Inflammation 33 3 Chapter Three: Research 35 3.1 Working Hypothesis 35 iv 3.2 Specific Aims .36 4 Chapter Four: Materials and Methods 38 4.1 Sample Selection 38 4.1.1 iCapture BioBank and Patient Enrollment 38 4.1.2 Tissue Specimen Collection 39 4.1.3 Lung Tissue Processing and Preparation 42 4.1.4 Sectioning of Lung Tissue Cores 43 4.2 Histology 44 4.3 Stereology 46 4.3.1 Concepts 46 4.3.2 Equipment and Software 49 4.3.3 Image Capture Protocol 50 4.3.4 Statistical Analysis 53 4.4 Gene Expression 55 4.4.1 Concepts and Rationale 55 4.4.2 RNA Isolation and Assessment 56 4.4.3 Amplified cDNA 56 4.4.4 Quantitative Polymerase Chain Reaction 57 4.4.5 Gelatin Zymography 57 4.4.6 Statistical Analysis 58 4.5 Raman Microspectroscopy 59 4.5.1 Concepts 59 4.5.2 Rationale 60 4.5.3 Equipment and Software 61 4.5.4 Microscope Protocol 62 5 Chapter Five: Results 65 5.1 Total Lung Burden 65 5.1.1 Observations 65 5.1.2 Comparison to Clinical and Histological Data 67 5.1.3 Comparison to mRNA Expression 71 5.2 Alveolar Wall 71 5.2.1 Comparison to Clinical and Histological Data 71 5.2.2 Comparison to mRNA Expression 75 5.3 Blood Vessel Burden 76 5.3.1 Comparison to Clinical and Histological Data 76 5.3.2 Comparison to mRNA Expression 83 5.4 Lymphoid Follicle Burden 86 5.4.1 Comparison to Clinical and Histological Data 86 5.5 Alveolar Macrophage Burden 90 5.5.1 Comparison to Clinical and Histological Data 90 5.6 Raman Spectroscopy 93 6 Chapter Six: Discussion and Conclusion 94 6.1 PM Burden in the Lung 94 6.1.1 AllTissue 94 6.1.2 Alveolar Wall 96 6.1.3 Blood Vessels 96 6.1.4 Lymphoid Follicles 98 6.1.5 Alveolar Macrophages 98 6.2 Raman Spectroscopy 98 V 6.3 Conclusion .100 References .102 Appendix 115 vi List of Tables Table 1 Classification of COPD based on spirometry as outlined in the GOLD report.2 FEV,: forced expiratory volume in 1 second. FVC: forced vital capacity 3 Table 2 Causes of COPD exacerbations’2’ 19 Table 3 List of cases with accompanying clinical data, NS = non-smoker, ND = not done, NA = not available 40 Table 4 List of wound-healing genes in COPD 58 Table 5 Correlation of PM burden in all compartments of the lung with clinical and histological values 69 Table 6 Correlation of the PM burden in the alveolar wall with clinical and histological values 73 Table 7 Correlation of the PM burden in the blood vessel wall with clinical and histological values 78 Table 8 Correlation of blood vessel wall thickness and clinical and histological values..81 Table 9 Correlation of mRNA expression with blood vessel wall thickness 84 Table 10 Correlation of the PM burden in the lymphoid follicles with clinical and histological values 87 Table 11 Correlation of the PM burden in the alveolar macrophages with clinical and histological values 91 Table 12 List of Abbreviations 115 vii List of Figures Figure 1 Inflammatory mechanisms in COPD77 .15 Figure 2 Mechanism of airflow limitation in COPD77 16 Figure 3 Possible mechanisms for systemic effects of COPD8° 18 Figure 4 Relative contributions of PM by mass133 21 Figure 5 Association between FEV1 (L) or COPD (R) and long-term PM10 exposure (five-year mean). Data points are means of each place and year of study 28 Figure 6 Possible mechanism for PM-induced C0PD2 3 36 Figure 7 Steps in lung tissue preparation and sampling. A) Lung inflated with Cryomatrix and saline B) Lung frozen over liquid nitrogen vapours C) Meat saw D) Hole saw E) Lung slice with missing lung cores F) Frozen lung core 43 Figure 8 A) Cropped digital image of alveolar wall tissue stained with H&E at 20x objective magnification. B) Example of black pigment in the H&E stained tissue at 20x objective magnification 44 Figure 9 A cartoon depicting how as the magnification increases, it decreases (by great amount) the proportion of the object being studied206 46 Figure 10 The hierarchical nature of sampling in microscopy. The need for uniformly random sampling is paramount to make an accurate and precise estimate.206 48 Figure 11 A) Coarse grid (196 points) overlaid onto digital image of tissue. B) Fine grid (1500 points) overlaid onto digital image of tissue at 20x magnfication 49 Figure 12 Fields of view excluded (red) and included (green) in this study 50 Figure 13 Steps in the program for the automated blood vessel analysis. A) Inner lumen traced. B) Inner lumen area quantified (in pixels). C) Al D) Perimeter of adventitia traced. E) Black pigment quantified (in pixels) within the perimeter of the adventitia. F)A5 52 Figure 14 Tissue samples sectioned and melted onto aluminum foil wrapped around uncoated glass slide for Raman microspectroscopy use 62 Figure 15 Images captured from light microscope of the Raman system. A) The lighter colour is tissue, whereas the deep black pigment was the object of interest. B) The crosshairs would indicate the exact point where the laser would strike the tissue. . . .63 Figure 16 PM (black pigment) can be found in (A) the parenchyma, (B) alveolar macrophages, (C) airway wall, (D) blood vessel wall, and (E) lymphoid follicles.. .66 viii Figure 17: PM burden in non-smokers with normal lung function and those with COPD (L) and the PM burden in smokers with normal lung function (GOLD 0) and those with abnormal lung function (GOLD 1-4) (R) 67 Figure 18 Vv of PM in all lung tissues across non-smoking controls and groups of increasing COPD severity. Non-smoking controls and GOLD 2 groups were significantly different (p<0.05) 68 Figure 19 Burden of PM with increasing levels of COPD severity 69 Figure 20 Vv of PM in all tissue A) vs. FEV1/FVC B) vs. FEV1 C) vs. Lm D) vs. airway wall thickness B) vs. age F) vs. pack years 70 Figure 21 Vv of PM in all tissue vs. expression of FGG in the parenchyma 71 Figure 22 Vv of PM in the alveolar wall across the non-smoking group and the COPD severity groups 72 Figure 23 Vv of PM in the alveolar wall vs. A) FEV1/FVC B) vs. FEV1 C) vs. Lm D) vs. airway wall thickness B) vs. age F) vs. pack years. AlvWall = Alveolar wall 74 Figure 24 Vv of PM in all lung tissue vs. Vv of PM in the alveolar wall 75 Figure 25 Vv of PM in the alveolar wall vs. expression of FGG in the alveolar wall 76 Figure 26 Vv of PM in the blood vessel walls across the non-smoking group and the COPD severity groups 77 Figure 27 Vv of PM in the blood vessel wall A) vs. FEV1/FVC B) vs. FEV1 C) vs. Lm D) vs. airway wall thickness E) vs. age F) vs. pack years 79 Figure 28 A) Vv of PM in all lung tissue vs. Vv of PM in the blood vessel wall B) Vv of PM in parenchyma vs. Vv of PM in the blood vessel wall 80 Figure 29 PM area in the blood vessel vs. the wall area of the blood vessel 81 Figure 30 Blood vessel wall area thickness A) vs. FEV1/FVC B) vs. FEy1 C) vs. Lm D) vs. airway wall thickness E) vs. age. F) vs. pack years 82 Figure 31 A) Vv of PM in all lung tissue vs. blood vessel wall area thickness B) Vv of PM in parenchyma vs. blood vessel wall area thickness 83 Figure 32 Blood vessel wall area thickness A) vs. IL-4 B) vs. IL-13 C) vs. PDGFRB D) vs. TGFB1 E) vs. TNF F) vs. VEGF 85 Figure 33 Vv of PM in the lymphoid follicles across COPD severity groups 86 Figure 34 Vv of PM in lymphoid follicles A) vs. FEV1/FVC B) vs. FEy1 C) vs. Lm D) vs. airway wall thickness E) vs. age F) vs. pack years 88 ix Figure 35 Vv of PM in the lymphoid follicles vs. A) blood vessel thickness, B) Vv of PM in the blood vessel wall, C) Vv of PM in the parenchyma, and D) Vv of PM in all tissue 89 Figure 36 Vv of PM in alveolar macrophages across the non-smoking and COPD severity groups 90 Figure 37 Vv of PM in alveolar macrophages A) vs. FEV1/FVC B) vs. FEy1 C) vs. Lm D) vs. airway wall thickness E) vs. age. F) vs. pack years 92 Figure 38 Raman spectra of Case 1984 93 x Acknowledgements First and foremost, I would like to thank my supervisor, Dr. Stephan van Eeden, for his dedication and valued advice in my career as a scientist. His thoughts and presence have helped me through both good and challenging times in my work. Secondly, I would like to thank Dr. James Hogg, who I have worked with as a summer student before I began my undergraduate education and for giving me the opportunity to work in a world-renowned research centre summer after summer, later recommending me to Dr. van Eeden for graduate studies. I would also like to thank my other committee members: Dr. Shizu Hayashi, who supervised me through a directed studies course as a graduate student, and has offered excellent advice and constructive criticism of my methodology and writing skills and Dr. Harvey Coxson who has also offered guidance on this project. I would like to take this opportunity to thank some of the staff and students in the lab. John McDonough has always been willing to help me with my project and offer advice at any time as a colleague, and as a friend. Dr. Mark Elliott and Crystal Leung have offered their invaluable expertise in the histology side of my project. My Raman spectroscopy experiments would not have been possible with the generous donation of time at the Michael Smith Laboratories, and I thank Drs. Michael Blades and Robin Turner, as well as, Kadek Okuda for their help on my project. I would also like to thank my parents, Dr. Hilton and Elizabeth Ling, and my sister, Dr. Bernice Ling, for their unwavering support in all my endeavours. xi To Mom, Dad, and Bernice xli 1 Chapter One: Chronic Obstructive Pulmonary Disease 1.1 Definition Chronic obstructive pulmonary disease (COPD) is clinically defined as “a respiratory disorder” caused by the inhalation of noxious gasses and particulate matter predominantly from cigarette smoking “and is characterized by progressive partial reversible airways obstruction, lung hyperinflation, systemic manifestations and increasing frequency and severity of exacerbations.” Pathologically, COPD is typically a combination of small airways disease (obstructive bronchiolitis) and parenchymal destruction (emphysema).2Both parts of the disease make a varying contribution depending on the individual; but, ultimately, result in the clinical hallmark of COPD: airflow limitation that is not or just partially reversible.3This airflow limitation is typically progressive, and combined with the presence of the continuing inflammation, results in structural changes and narrowing of the airways, and the destruction of the parenchyma. These changes results in the reduction of alveolar connections to the airways and loss of elastic recoil.2 Although these pathological changes are lung-specific, there are a significant number of systemic manifestations such as nutritional abnormalities, weight loss, skeletal muscle dysfunction, and cardiovascular complications4’5which act as co-morbidities impacting disease prognosis.6As mentioned previously, the course of COPD varies from individual to individual, but is generally progressive in nature, particularly if exposure to deleterious particles and gases is maintained.2However, if that exposure is removed, the 1 result can be an improvement in lung function and may even halt the progression of the disease. 1.1.1 COPD Severity Categories With the limitation of airflow being a pillar of the disease, spirometry is the best measurement because of its availability and reproducibility.2Spirometry is the technique to measure the flow and volume of air an individual can inhale and exhale. The report from the GOLD (Global Initiative for Chronic Obstructive Lung Disease) Scientific Committee suggests that the severity of COPD should be delineated into 4 stages based on the individual’s spirometric results (Table 1 )•2 Firstly, Stage I is characterized by mild airflow limitation, possibly with symptoms of a chronic cough and sputum production, and typically the individual is not aware that his lung function is abnormal. Stage II is characterized by deteriorating airflow limitation, shortness of breath after exercise, symptoms of chronic cough and sputum production, and usually a need to seek medical attention because of the symptoms or some form of exacerbation of the disease. Stage III is characterized by poorer airflow limitation, increased incidences of shortness of breath, poor exercise ability, fatigue, and exacerbations that severely affect the individual’s quality of life. Finally, Stage IV is characterized by the most severe airflow limitation and respiratory failure resulting in frequent exacerbations that are potentially fatal. A group that was previously mentioned in earlier GOLD Reports, Stage 0, who were labeled “at risk” for COPD, but had normal lung function, are no longer included as there was inconclusive evidence that they would progress to Stage I. 2 Table 1 Classification of COPD based on spirometry as outlined in the GOLD report.2FEV1: forced expiratory volume in 1 second. FVC: forced vital capacity. Stage Severity Spirometry I Mild FEV1/FVC < 0.70, FEV1 80% predicted II Moderate FEV1/FVC < 0.70, 50 % FEy1 < 80% predicted III Severe FEV1/FVC < 0.70, 30 % FEV1 < 50% predicted Very FEV1/FVC < 0.70, FEV1 < 30% predicted or FEy1 < 50% predicted IV severe + chronic respiratory failure 1.2 Burden of COPD 1.2.1 Prevalence The prevalence of COPD worldwide is estimated to be around 1% of the population across all age groups, but rises dramatically to 9-10% among those 40 years or older.7 From the years 1970 to 2002, the death rates doubled from 21.4 to 43.4 (rates per 100,000 people, age-adjusted) in the United States.8 In a large meta-analysis by Halbert et al.,9 COPD prevalence significantly increases in sub-groups of smokers (15.4%), males (9.8%), and people living in urban settings (10.2%). As COPD is a worldwide problem, major studies looking at the prevalence of the disease have been conducted outside of North America. The Latin American Project for the Investigation of Obstructive Lung Disease (PLATINO), made up of Brazil, Chile, Mexico, Uruguay, and Venezuela, found 3 that Stage I COPD increases strongly with age and found distinct prevalence differences (18.4% to 32.1%) between countries.’0Another study looking at twelve Asia-Pacific countries, found that the overall prevalence rate was much lower at 6.3%. Surprisingly, mild forms and even severe forms of COPD go undiagnosed even though spirometers are relatively inexpensive and usually readily available. Population- based studies confirm that COPD suffers from a lack of treatment and diagnoses, which has been a prevalent and historical belief in the scientific 12 Unfortunately, the morbidity, mortality, and the cost of this particular disease goes neglected compared to other diseases and therefore, the true burden of the disease goes relatively unnoticed by healthcare providers.7On the other hand, this group of individuals may be the most important, as they are usually those that require healthcare services and therefore generate relevant costs.2 One of the major studies to disseminate a standard set of techniques and measurements was the Burden of Obstructive Lung Disease Initiative (BOLD).’3The rationale behind BOLD was to develop a set of methods and practices for measuring the prevalence of COPD to act as a framework available to help train, maintain quality control, and provide data analysis. However, the prevalence of COPD is made more difficult by the heterogeneity in measurements of COPD severity.9’14 Diagnostic definitions can vary between locations and usually underestimate the prevalence of the disease.9Although taking spirometry measurements is convenient and inexpensive, there is variation in the administration of the lung function test and different applications of quality control. In addition, as the severity of the disease increases, the reproducibility of the measurements decreases.’5A study by Viegi et al.,’6 showed that using the various standards for measurement of 4 COPD from the American Thoracic Society (ATS) and the European Thoracic Society (ETS) would result in a range of 11-57% when describing obstruction. In summary, it seems that all forms of measurement, which could include doctor diagnosis, patient- reported diagnosis, or spirometric measurements all affect the reporting of COPD prevalence.’4Ultimately, measurements of COPD prevalence benefit having consistent, reproducible, and standardized techniques. 1.2.2 Morbidity and Mortality Morbidity is defined as another term for the presence of illness or disease and is typically measured in hospital (including the need for hospitalization) and physician visits.2However, with increasing age, an individual afflicted with COPD is likely to have other diseases at the same time, known as co-morbidities.6These co-morbidities act as further challenges to the individual and healthcare system, but may only be related indirectly to COPD.2The problem with looking at morbidity resides in the health care system itself, as the rates of hospitalization are based on the ability of the hospital to provide beds. Mortality, on the other hand, is defined as the fatal outcome of the morbidity. The lack of diagnosis and reporting of the disease also influences mortality information. However, the burden of the disease is undeniable. COPD, as one of the fastest growing chronic diseases in the developed and developing world, is an extremely important public health problem.’7This disease has been projected to be the 3rd leading cause of total mortality and the 5th leading cause of disability by 2020.18, 19 In economically developed countries, this disease is the 4th leading cause of death.’8As the population ages and 5 smoking continues to spread across age groups, the mortality resulting from COPD will increase.20 It has been shown that COPD causes almost as many deaths as HIV/AIDS.2’ 1.2.3 Economic and Social Costs So far, few studies have looked at the relative contributions of the direct and indirect costs of COPD outside of the European Union and North America.22Direct costs are defined as being related to the diagnosis, treatment, and prevention of the given disease.7Indirect costs, on the other hand, account for the morbidity and mortality of the disease and also typically evaluate the reduction in national production. According to a study by Jemal et al.,8 the direct costs of COPD were 18 billion USD and indirect costs accounted for 14.1 billion USD. Although asthma is arguably more studied, it is less prevalent than COPD in adults, and shows in the related health care costs due to a greater amount of hospitalizations.7An important point brought up by the GOLD Report is that all these costs are attributed to services in the hospital, and does not take into account the monetary value of the care given by family members and in-home caregivers.2’3 However, the financial burden is not the only cost of this disease. Disability Adjusted Life Years (DALYs) are defined as the sum of years lost due to premature mortality and years dealing with the disability.’8From 1990, where COPD was the 12th leading cause of DALYs in the world, the disease is projected to be the 5th leading cause of DALYs in 2020. 6 1.3 Risk Factors 1.3.1 Smoking The single greatest risk factor for COPD is cigarette smoking, be it either passive or active.2’45COPD mortality can be predicted by a number of smoking-related factors: age of starting smoking, total pack years smoked, and current smoking status.23 It has been shown that 80-90% of COPD mortality is related to tobacco smoking.26 Studies in China and Japan have shown a dose-response relationship between the risk of developing COPD and active smoking.27’8Smoking causes accelerated lung function decline, and the frequency of smoking seems to adversely affect lung function.23 To further this link, the cessation of smoking is associated with a return to the rate of decline of a normal, non-smoker.26 Although many reviews and textbooks cite that only 15 to 20% of smokers go on to develop COPD, this number is now considered a gross underestimate,29which is likely due to under-diagnosis of the disease. In fact, a study by Lundback and colleagues3° suggests that as much as 50% of elderly smokers have symptomatic COPD. Rennard and Vestbo29 state that nearly all smokers will probably meet the diagnostic criteria for the disease. 1.3.2 Air Pollution Past studies have shown an association between increased levels of outdoor air pollution and the morbidity and mortality of respiratory diseases.31’2Lung development in youth aged between 10 to 18 years was stunted by air pollution and by the time the 7 youth reached adulthood, their lung function was reduced.33 As a consequence of simply banning the sale of coal in Dublin, Ireland, Clancy et al.34 showed that there were around 116 fewer respiratory and 243 fewer cardiovascular deaths in the year following the ban. With respect to COPD, the prevalence rates of this disease rose in urban and polluted locations.3538 Air pollution is not restricted to the outdoors. Indoor air pollution is of great importance as the general population tends to spend the majority of their time indoors.39 Increasingly, biomass smoke from wood or coal burning heating elements in the developing world, such as China, have become more of a problem.40’1Not only do people spend more time indoors, a lack of ventilation may allow concentrations of indoor air pollutants to accumulate and surpass outdoor concentrations.23Liu et al.4° found that there was a significant association between exposure to biomass smoke and COPD. 1.3.3 Occupational Exposure Exposure to many toxic chemicals and fumes, plus organic and inorganic dusts in some occupations can lead to COPD.2Using a Carcinogen Exposure (CAREX) database, which is based on data from the International Labour Organization (ILO), workplace airborne exposure was found to result in 318,000 COPD-related deaths (270,000 men and 78,000 women).42Although, as stated before, cigarette smoking is the greatest contributor to the development of COPD, occupational exposure can double the risk of having the disease, even when accounting for a smoking history.43 Using a population in Australia, Matheson and colleagues44found that subjects exposed to biological dusts had an odds ratio (OR) risk of 2.7 of having COPD. 8 1.3.4 Gender So far, the role of gender as a risk factor for COPD remains elusive.45’6The disease has not been well-studied in women but since gender differences affect other diseases, this factor may have a significant impact on the diagnosis and management of COPD.46 In a study by Xu et al.,45 smoking seemed to negatively affect women more than men. Looking at prevalence data on morbidity and mortality, more men than women typically have the disease; but, over the past 20 years, COPD prevalence has increased quickly in women.47This could partly be due to the fact that in developing countries, the number of women smokers continues to grow, expected to reach 20% by 2025.48 According to Soriano et al.,49 COPD prevalence in men plateaued in the 1990’s, but increased greatly in women older than 65 in the United Kingdom. 1.3.5 Genetics Perhaps the primary example of COPD as a product of a genetic disorder is the alpha (al)-antitrypsin deficiency, which is both common and under-recognized by doctors.5°The protective role of a 1 -antitrypsin is to react with neutrophil elastase in the lung to reduce the elastolytic burden in the lower airways. Typically, the mutation occurs in the SERPINA1 gene and results in a reduction of al-antitrypsin serum levels, which increases the risk for panlobular emphysema5’and liver damage. This disorder accounts for 1-3% of patients with COPD. Other genes have been targeted in COPD, including transforming growth factor-betal (TGF-13 1),52 tumor necrosis factor-alpha (TNF-a),53 and microsomal epoxide hydrolase (mEPHX),54as possible genetic risk factors. 9 It also appears as if genetic factors play a role in the susceptibility of developing COPD (based on a decline of FEy1)in familial correlation studies.23’55Kurzius-Spencer and colleagues56suggested that there must be a genetic component linking smoking and FEy1 because sibling FEV1 slopes were correlated more strongly in smoking siblings than non-smoking siblings. Genetic association and linkage studies have provided conflicting evidence. This evidence suggests that the environment probably plays a large role in regulation of genes leading up to the development of COPD.57’8 1.3.6 Infections In our lab, adenoviral infection has been shown to amplify the cigarette smoking- induced inflammation in alveolar epithelial cells in severe emphysema59and may also induce steroid resistance.6°Seemungal et al.6’ have shown that respiratory viral infections are associated with a greater frequency and severity of exacerbations of COPD. Several studies suggest that children who suffer severe respiratory infections go on to have reduced lung function and other respiratory ailments.62Even though the role of human immunodeficiency virus (HIV), a cause of primary or secondary inflammation in emphysema is unclear, there is a definite association between lung cytotoxic lymphocytes and parenchymal destruction in these patients.63’4COPD can sometimes occur after a tuberculosis (TB) infection and is made worse by smoking.65 10 1.4 Pathology of COPD 1.4.1 Pathogenesis The most widely accepted hypothesis is that disease process starts in the lung with the inhalation of noxious gases and particles.2This results in a lung inflammation, which is a normal response, but this response is amplified in individuals with COPD. Inflammatory Cells in COPD Polymorphonuclear leukocytes (PMNs) Neutrophils may contribute to parenchymal destruction by releasing serine proteases, such as, neutrophil elastase, cathepsin G and proteinase-3, and matrix metalloproteinases (MMP) -8 and 9•66 This type of cell’s role is not clear in COPD, but there is an definite association between an increase in circulating neutrophils and a decline in lung function.67 While the neutrophil’s role remains unclear, the macrophage can be held responsible for most of the features of the disease.68’9 Macrophages In COPD, the numbers of macrophages increase dramatically in the parenchyma, the airways, and bronchial alveolar lavage (BAL) fluid.66 The inflammatory mediators macrophages release indicate a cellular link to COPD, and these secretions are even greater than those from macrophages of normal smokers.70’Alveolar macrophages exposed to ambient air pollution also release pro-inflammatory cytokines, such as TNF a, interleukin (IL) -6, IL-i , and others.72 The increase in numbers of macrophages could be due to monocyte recruitment, but also due to increased propagation and longer survivability.66Although macrophages are meant to play a role in defense via the 11 mechanism of phagocytosis, when this mechanism is impaired in COPD, it could result in increased bacterial or particle burden in the lung. Lymphocytes The total number T-lymphocytes are also higher in the parenchyma and airways. CD8+ T cells have the ability to cause apoptosis of alveolar epithelial cells resulting in emphysema.73It is likely that dendritic cells play an important role in COPD, as they are a key cell in the activation of other, previously mentioned, cells, such as, macrophages, neutrophils, and T-lymphocytes.74Increased numbers of eosinophils have been found in acute exacerbations of COPD,75’6but their role is still unclear.66’77Finally, epithelial cells can be activated by cigarette smoke and secrete various inflammatory mediators and proteases.66 Inflammatory Mediators in COPD Cytokines Studies have shown that proinflainmatory cytokine production increases with small changes in ambient air pollution.78’9This increase in cytokine production leads to an increase in acute-phase protein production and leukocyte release from the bone marrow.80TNF-a is found in large quantities in the sputum in patients with COPD8’and activates nuclear factor kappa-light-chain-enhancer of activated B cells (NF-icB), which in turn, activates epithelial cells and macrophages to secrete other cytokines, chemokines, and proteases.77IL-i acts similarly to TNF-cL and is a powerful macrophage activator.70 A number of other interleukins are considered to be mediators involved in COPD, including IL-6, 9, 10, 12, 13, and 17. Granulocyte-macrophage colony stimulating factor (GM-CSF) levels are above normal in COPD and increase substantially during 12 exacerbations in BAL.82 Expression of interferon-gamma (IFN-y) is also elevated in emphysema.83 Chemokines Chemokines act together to determine an inflammatory response84 and there are a few known chemokines that play a role in COPD via the recruitment of inflammatory cells.85 A chemoattractant of neutrophils, IL-8, has shown increased levels that correlate with neutrophil numbers in COPD8’and even more so in individuals with al-antitrypsin deficiency.86Alveolar macrophages secrete IL-8 in larger quantities in COPD than normal smokers87and neutrophils themselves secrete IL-8, which may cause a perpetual inflammatory state.88 Growth-related oncogene-aipha (GRO-ct) is secreted by alveolar macrophages and airway epithelial cells89 and activates neutrophils, monocytes, basophils, and T-lymphocytes.9°A number of other chemokines may have a role in the disease process, including epithelial cell-derived neutrophil-activating peptide-78 (ENA 78), monocyte chemoattractant protein-i (MCP-i), and eosinophil-selective chemokines.77 Growth Factors One of the hallmarks of COPD is structural change, and a growth factor, such as, TGF-131 could be a part of the fibrosis process in COPD.9’Epidermal growth factor (EGF) regulates mucus secretion92 and could therefore be a target for therapeutic intervention. Vascular endothelial growth factor (VEGF), part of pulmonary vascular remodeling, has increased expression in mild and moderate COPD but suppressed expression in severe COPD.93 Fibroblast growth factor (FGF) also plays a role in pulmonary vascular remodeling.94 13 Proteases Proteases are known to degrade components of connective tissue and elastin degradation is presumed due to a loss of elastic recoil in the lung.77 In a 1 -antitrypsin disorder, NE can induce emphysema in animal models95,but its role has yet to be clarified pending the results of clinical, human trials with NE inhibitors. MMPs regulate extracellular matrix (ECM) degredation96and an increasing body of evidence suggests that they play a vital role in emphysema97and lung function decline.98 Reactive oxygen species (ROS) Oxidative stress seems to play an important role in COPD by amplifying the inflammation and destruction.77Much evidence exists for the increased oxidative stress in the lungs of COPD patients.99’100 ROS activates NF-icB,’°’ constricts airway smooth muscle,’02may reduce the anti-inflammatory effect of corticosteroids,77and induce Other mediators Lipid mediators, such as, prostaglandin (PG) E2 and F2a, thromboxane, leukotrienes, and platelet-activating factor (PAF) also play a role in COPD.77 Nitric oxide (NO) can be expressed in greater quantities by macrophages and in the lung parenchyma in COPD. Peptide mediators, such as endothelins, bradykinin, tachykinins, and complement fragments may play a role in the progression of COPD. An overview of the entire process can be found in Figure 1. 14 Figure 1 Inflammatory mechanisms in COPD77 Cigarette Smoke Epithelial Cells Alveolar Macrophages TGF-bcta Chemotactic fictors, I L-8, chernokincs Fibroblast _______ CD$± lymphocyte Neutrophil \ Neutrophil clastases. PROTEASES MMPs Fibrosis Emphysema Chronic bronchitis 1.4.2 Pathophysiology Airflow limitation is thought to be a result of narrowing of the small airways (Figure 2), emphysema, and mucus plugging in the luminal spaces, each playing a role in COPD. However, the relative contributions of each of these processes are still unclear and depend on the disease stage. Chronic bronchitis Chronic bronchitis is a condition that arises from mucus hypersecretion, but also stems from epithelial structural changes, airway inflammation, bronchial mucus glands, and smooth muscle hypertrophy.104 This condition is typically associated with the epithelium of the central airways.’°5Most of all though, mucus hypersecretion is / .4, 15 characteristic of chronic bronchitis.’°4Data suggests that mucus hypersecretion is associated with airway obstruction,106 but this is Loss of alveolar attachments Mucous hypersecretion andAirway held open by alveolai attahinents obstruction of lumen Small airways obstruction For some time now, it has been shown that there is a marked narrowing of the small airways in COPD.’°8’109 In a study by Hogg and colleagues”0,they concluded that this obstruction is due to a remodeling process that is both a product of tissue repair and a malfunction of mucociliary clearance. Although poorly understood, the fibrosis of the airways is likely a repair mechanism.66According to Ogg,1ithe peripheral airways are the major source of increased airway resistance due to airway narrowing and airway closure. Some studies suggest that mucus plugging in small airways causes airflow obstruction, but these findings could be a postmortem artifact.”2In addition, the presence Figure 2 Mechanism of airflow limitation in COPD77 Normal Disease State 1’ (I 4. (I 16 of lymphoid follicles in between the smooth muscle and lumen will reduce the functional lumen area. Emphysema Emphysema, by definition, is the enlargement of the alveolar space.”3Both types of emphysema, panacinar and centrilobular, may be present in the lungs of smokers.”4 Panacinar emphysema is usually seen in al-antitrypsin deficiency, whereas, centrilobular emphysema is found in cigarette smokers.’°4The reason for tissue destruction can be attributed to an uncontrolled inflammatory response and a protease/antiprotease imbalance. Ultimately, this leads to a loss of elastic recoil in the lung and a decline in lung function and FEy,. Systemic effects Although COPD is a pulmonary disease, it is associated with extrapulmonary effects on other organs and body systems.5’“ The “spillover effect” from the pulmonary inflammation suggests that these inflammatory cells and mediators move into the systemic circulation (Figure 3)5 Markers of ROS increased significantly in the plasma of smokers and individuals with COPD.”6Circulating, activated inflammatory cells, such as, neutrophils and lymphocytes, and cytokines and acute phase proteins all contribute to the systemic inflammation.5In addition to this systemic inflammation, COPD patients suffer from weight loss and nutritional abnormalities. Weight loss is typically from the reduction of skeletal muscle mass117 and nutritional abnormalities probably due to increased basal metabolism with normal caloric intake.’18 Skeletal muscle dysfunction is a common problem in COPD and likely due to two factors: loss of muscle mass and 17 dysfunction of remaining muscle.5Cardiovascular disease risk is increased by two to three times in patients with COPD 119 however, this mechanism remains unclear. Figure 3 Possible mechanisms for systemic effects of COPD8° Lung inflammation PM0 Cigarette Smoke Cells: IL-i, 6,8 • Macrophages TNF • PMNs GM-CSF Bone marrow Liver Leukocytes, platelets Acute phase proteins Systemic inflammation 1.4.3 Exacerbations Exacerbations for COPD are defined as a change in the disease state based on a patient’s dyspnea, cough, or sputum that requires some change in management and intervention. 120 The amount of exacerbations is known to increase as the disease severity worsens,121 and this impacts on a patient’s quality of life’22, as well as the health care system. Increased dyspnea during an exacerbation is said to be due to hyperinflation, air trapping, and reduced expiratory flow.’23 Hypoxemia is also usually present during an exacerbation due to a deteriorating ventilation-perfusion mismatch.’24Etiologic factors 18 that contribute to an exacerbation include viral infections, bacterial infections, and air pollution (Table 2).121 Table 2 Causes of COPD exacerbations’2’ Viruses Bacteria Pollutants Rhinovirus H influenzae Nitrogen dioxide Influenza Spnuemoniae Particulate matter Parainfluenza M catarrhalis Sulphur dioxide Coronovirus Staphylococcus aureus Ozone Adenovirus P aeruginosa Respiratory syncytial virus Cpnuemoniae Based on a number of epidemiological studies, air pollution (composed of sulfur dioxide, nitrogen dioxide, and particulate matter) has been shown to negatively affect chronic respiratory diseases.125’126 Sunyer and colleagues’25 show an increase in hospital admissions during elevated periods of ambient air pollution. Diesel particles have been implicated in a number of studies,127’29with the suggestion that these particles cause increased production of IL-8 and GM-CSF.’28Possible mechanisms exist (explained more fully in the following chapter) that show that increases in air pollution can cause not only exacerbations, but also affect the progression and development of COPD. 19 2 Chapter Two: Particulate Matter 2.1 Definition The Tyrolean Iceman, who lived before the beginning of recorded history 5,300 years ago, was found in 1991 and had carbon and dust retained his jg3OBiomass fuels have been used for centuries by man for cooking and heating.’3’Recently, however, due to rapid urbanization, cigarette smoking, and a number of industrial combustion sources, humans have had to deal with a greater amounts and more complex forms of particles. Urban particulate matter (PM) has been implicated in a number of epidemiological studies to be associated with a number of adverse health effects.’32 Those with chronic lung diseases, such as COPD, are particularly susceptible to exacerbations associated with ambient PM. PM is typically defined in two ways: either by particle size or composition. 2.1.1 Particle Size PM is most often classified by its size. Total suspended particle (TSP) is a term used to define the total amount of airborne particles.’32’4Within TSP, the particles can be divided into smaller and smaller fractions. Particles greater than 30 im do not remain suspended in the air very long, when compared to the smaller fractions. These smaller fractions consist of PM10 (coarse) and PM25 (fine) particles with an aerodynamic diameter of less than 10 pm and 2.5 rim, respectively. The smallest, commonly described as PM0,, are less than 0.1 im and are known as ultrafine particles. PM25 is considered to have the most toxic effect on the human respiratory tract for a number of reasons. Firstly, 20 although PM,0 can penetrate into the lung, it is the fine and ultrafme fractions that are able to penetrate deeper and into the alveolus. As described by Squadrito et al.,’35 particles between 5-8 jim in diameter are deposited in the tracheobronichial region, whereas the particles between 1-5 jim in diameter are deposited in the respiratory bronchioles and alveoli. These findings have been confirmed by electron microscopy in a study by Churg and Brauer,’36who found that around 96% of the PM in lung parenchyma was fine particles, whereas only around 5% was ultrafine particles. However, particles smaller than 5 jim remain airborne due to their diffusivity and settling velocities and can be exhaled out again. Finally, these fine particles have a greater surface area (more contact with tissue) and a porous surface (ability to adsorb toxic elements).’34It is also important to note, that by definition, the larger fractions incorporate the smaller ones (Figure 4)133 Ultrafine particles are typically generated from combustion (automobile exhaust) and photochemical activity, whereas coarse particles are generated by mechanical processes (non-combustible elements).’34 Figure 4 Relative contributions of PM by mass133 Coarse Particles I PM2.5 PM1O TSP UF I I I 21 2.1.2 Composition As mentioned before, particles can also be classified by their chemical or biological composition. Typically made up of a core of carbon, many other elements, such as, organic and inorganic compounds, aerosols, and metals can be adsorbed or attached to the surface.’32 Due to the mechanism that creates TSP and coarse particles, these larger particles are typically from natural materials, such as, insoluble crustal materials, sea salt, pollen, and bacteria. On the other hand, fine and ultra fine particles generally consist of the aforementioned carbonaceous core, with metals and organic compounds adsorbed.’34These organic compounds encompass polycyclic aromatic hydrocarbons (PAH5), metals (iron, nickel, etc.), ions, reactive gases (ozone, peroxides), and biological elements (bacteria, viruses, pollen). 2.2 Sources of Particles 2.2.1 Coal Coal has been used extensively for heating (industrial and residential) and power.’37 Tar and soot are byproducts of the combustion process, and has been known for quite some time to be associated with respiratory, skin, and scrotal cancers. Coal was ultimately the culprit in the infamous London Fog of 1952 in which over 4000 more deaths than normal occurred due to heart and lung conditions,’38and also, previously in the Meuse Valley, where pollution from the many nearby industrialized sources caused 22 the death of 60 people in 3 days in 1930.139 PAl-Is were quickly identified as the carcinogenic and mutagenic properties of the soot and tar. Depending on the location, power plants that burn coal are a significant source of PM, especially in the USA.’4°The carcinogenic and mutagenic properties are well known, but more work is required to further look at the impact of modern power plants and their emissions. 2.2.2 Petroleum Petroleum encompasses a number of other combustible liquids, such as fuel oil, gas, and diesel.137 Residual fuel oil, part of the heavier petroleum products, contains known carcinogens.’4’Combustion of this fuel oil produces residual oil fly ash (ROFA) and is said to give off even more particles and emissions than lighter fuels (jet fuel).’42 When compared to coal fly ash, ROFA usually contains more toxic trace metals. Diesel and gasoline are also petroleum products and account for sizeable portion of air pollution. Virtually all automobiles, construction equipment, and boats use either of these energy sources. When compared, diesel produces 100 times the elemental carbon more than gasoline.’37 In urban centers, traffic-related pollution comes almost entirely from gasoline and diesel emissions.143 Lung, bladder, and lymphatic cancers are all associated with occupational diesel exhaust exposure. According to Lewtas,’37gasoline has not been as well-studied as diesel due to to the lower particle emission rates of gasoline. 23 2.2.3 Traffic Traffic-related PM air pollution has been a major contributor ofPM2.5144 and ultrafine particles.’32Not only do emissions itself contribute to the ambient PM25 concentrations, but the natural wear on tire and roads and resuspension of dust all contribute to the levels ofPM10.’45’146 Traffic density and intensity also play a role in levels and size composition of PM. The greater the intensity of traffic, the greater the levels of ambient PM. de Kok et al.’32 suggest that PM produced from traffic related sources may have a greater capacity to generate ROS based on research by Baulig and colleagues.’47Without a solid cutoff for when levels of ambient PM cause exacerbations of existing health conditions, the belief in the scientific community is that any population will benefit from any kind of reduction through environmental policies.’32 2.2.4 Biomass Biomass burning can include anything from forest fires to cigarette smoking.’37 When compared to the relatively high efficiency combustion of petroleum, biomass smoke contains higher levels of organic carbon and has higher particle emission rates.’48 Wood smoke During the incomplete combustion of wood or during forest fires, the combustion products from lignin and cellulose compose the majority of emissions.149 An important marker for lignin is methoxyphenol and for cellulose is levoglucosan’5°and both are used to determine the origin in atmospheric particles and biomass burning. The burning of wood and other vegetation will also produce mutagenic and carcinogenic PAHs.’5’ 24 However, the type, condition, and location of the combustion all affect the characteristics of the emissions. Agricultural burns are used to quickly destroy old crops or pest plants and have been known to impact nearby communities with the increased ambient air pollution. 137 Cooking Another source of indoor and outdoor pollution are the particles, organic aerosols, and carbon that are produced by cooking (frying, charbroiling).152Typically, byproducts of oils, such as, saturated and unsaturated fatty acids, are the major fraction of organic particulates. According to a number of studies’53,these particulates are considered to be carcinogenic in animals (probably humans). Even in home, indoor cooking, the mere act of broiling steaks in the oven or pan-frying bacon produced mutagenic and carcinogenic PAHs and hetercyclic amines.’54 Tobacco smoke One of the most relevant sources of PM exposure (especially in COPD) is cigarette smoke, which is made up of over 45,000 chemicals.’554000 substances in cigarette smoke are known to be carcinogenic, mutagenic, cytotoxic, and antigenic.’56 Over time, the composition of cigarettes has changed as there have been changing proportions of bright and burley tobacco, and these changes affect the composition of the smoke.’57 Smokers are not the only group affected, as children can be exposed to environmental tobacco smoke (ETS) in schools and public places.’58 ETS is known to adversely affect respiratory health in children and in the fetus causes premature deliveries, low birth weight, and malformatjons.’59 25 2.3 Epidemiology There is strong relationship between levels of increased ambient air pollution and the rate of morbidity and mortality from respiratory diseases.31’2This relationship was first brought to light in the 1950’s, which eventually led to research and development into the 60’s and 70’s, resulting in air pollution guidelines and restrictions in higher-income countries.’60However, increasing traffic and urbanization in these countries, combined with cooking and heating stoves using biomass fuels in low-income countries,40’161 have contributed to the burden of COPD. According to Liu and colleagues,’6’most epidemiological studies focus on short- term exposure studies in high-income countries, and few have looked at the long-term exposures on the development of COPD. The first of these studies looked at the doubling of the daily death rate during the London Fog of 1952 and also found that the large majority of those deaths were due to cardio-respiratory causes.’38 Of all the ambient air pollutants, PM,0 seems to have the strongest association with adverse health effects, even when correcting for a smoking history.3’Even with more stringent air pollution regulations, mortality has continued to increase.161 Schwartz and Dockery’62 found a 19% increase in cause-specific mortality for COPD associated with a 100 ig/m3 increase in TSP. As mentioned before, most of the work has been done to describe the exacerbations of air pollution on pre-existing conditions of COPD. For this disease, exacerbations are the major cause for its morbidity and mortality.’63Although exacerbations are mostly attributed to viral or bacterial infections, there is a growing 26 body of evidence that suggests exposure to ambient PM can initiate or contribute to the infections to cause an exacerbation.’31’163, 164 For every 10 .ig/m3 increase in PM25,there is a doubling in admissions for COPD exacerbations in hospitals.’64It seems as though regardless of the metric used to describe the PM exposure and health endpoints, most studies point to an association between ambient PM and COPD exacerbations.’3’In addition, the mortality rate increases for COPD immediately following exposure to ambient PM. Air quality guidelines can only go so far, as a study from the UK suggests that these levels are consistently above limits and result in 8,000 deaths and 10,000 excess hospital visits for airway disease exacerbation.’65 However, there are few studies that have looked at the association between PM air pollution and a decline in FEV,, as well as, the development of COPD. Schikowski and coworkers38ran a cross-sectional study on women and showed that with a 7 .Lg/m3 increase in ambient PM,0 over 5 years, they had an OR of 1.33 (95% CI, 1.03-1.72) for developing COPD and had a 5.1% more rapid decrease in FEy, (Figure 5). Women who lived near (less than 100 m) major roads were much more likely to have reduced lung function and an OR of 1.79 (95% CI, 1.06-3.02) of developing COPD when compared to women who lived further away. A study by Liu et al.4° assessed two locations in China and found that there was a significant association between the use of biomass fuels for cooking and the risk for developing COPD using both univariate and multivariate analyses. They concluded that biomass fuel is an important risk factor for the development of COPD, especially in China where the use of biomass fuels and poor ventilation is commonplace. Support for Liu et al.’s conclusions also comes from Kiraz and colleagues4’who found that rural Chinese women are more likely to have chronic 27 bronchitis and COPD than women (with a higher prevalence of smoking) who lived in urban areas. These studies suggest that factors other than just cigarette smoke can lead to the development of COPD. Figure 5 Association between FEy, (L) or COPD (R) and long-term PM10 exposure (five-year mean). Data points are means of each place and year of study. 3.0 6 2.9 He86 2.3 DoNW63 I Bo94 Bo86 0 35 40 45 50 55 60 35 40 45 50 55 60 long-term PMIO [pglm3] long-term PMIO [pglm3] 2.4 Deposition and Clearance of PM from the Lung 2.4.1 Deposition The deposition of PM can happen by five different mechanisms: interception, impaction, sedimentation, diffusion, and electrostatic precipitation.’66’167 Of the five, impaction, sedimentation, and diffusion are the most important mechanisms for inhaled particles, as interception usually describes fibrous particles and electrostatic precipitation involves those with high electric mobility (which aerosols have very little of). Impaction typically describes how very large PM (over 100 urn) travel on a given path before a barrier, like a branching airway, stops them. Sedimentation occurs when particles are given the opportunity to fall via gravity and affects particles in the 0.1 tm to 50 tm 28 range. Finally, diffusion occurs via random gas motion and in the small airways and gas exchange regions. The major entry point into the body for PM is the respiratory tract.’68 Any dose of inhaled particles in the lung is a function of its ratio of deposition and clearance. Lippman et al.’67 observed that particles would tend to aggregate in the centrilobular emphysematous lesions. In another study, PM was found to be in the small airway mucosa of non-smokers living in Mexico City, suggesting that high levels of air pollution could result in remodeling of the airway similar to that of COPD.’69 2.4.2 Clearance There are several features of the innate immune system that help to clear and protect the respiratory system from inhaled PM according to Hogg and Timens. These features include: an epithelial lining fluid (ELF), mucociliary clearance in the lower respiratory tract, alveolar macrophages, and the tight junctions that join the epithelial cells. Epithelial liningfluid The respiratory tract is lined with a thin, liquid layer called the ELF that covers the epithelial layer and also contains neutralizing agents, such as, antioxidants, lysozyme defensins, lipids, mucins, and proteins.’70The maj or component of the ELF is surfactant, which can also has the unique property of aggregating PM less than 6 pm in diameter to allow for easier mucociliary clearance.’7’Proteins present in surfactant may help in opsonization and allow macrophages to target PM.’7°Macrophages can more easily 29 phagocytose particles that are greater than 5 p.m in diameter, and as mentioned before, surfactants act to aggregate particles for these cells. Mucociliary clearance Mucus is produced by goblet cells and submucosal glands and contains antimicrobial substances.172 Ciliated cells in the airways can be found among the goblet cells and beat in a synchrony and, as Salvaggio’72suggests, is similar to an escalator. Typically most large and insoluble particles will be moved on the mucus layer up to larynx, where they can either be swallowed or coughed out. Alveolar macrophages The first line of defense in the cellular response to deposited PM in the lung is the alveolar macrophage (AM).’73 AMs can be found on both the airways and alveoli.’74’175 If the PM caimot be coughed out or swallowed, then the PM is phagocytosed by the AMs.’74’176 The primary role of the AM is to act as another barrier to the PM by phagocytosing and intracellularly processing them.’76’177 Generally, the greater the PM burden, the more AMs can be found.’78 Several studies’79’180 published fairly recently have supported Brain’s observations’78from the 1960s. He suggested that the greater the surface area covered by the particles and the larger the number of smaller particles, the more powerful inflammatory response elicited. After phagocytosing PM that constitutes greater than 60% of their total volume, AMs can go into an “overloaded” state’73 where their phagocytic and chemotactic activity is inhibited.’81’182 Even if only 6% of their total volume is taken up by PM, their ability to migrate up the mucociliary elevator was compromised. Furthermore, if the PM is composed of silica, it can irreparably damage the AM, forcing it to release its contents 30 and fuel the inflammatory response.’77The release of these contents, including ROS, proteases, pro-inflammatory mediators and growth-regulating proteins can lead to the progression of acute and long-term lung inflammation.’73’175 2.5 Mechanisms of PM-induced Lung Inflammation AMs and the bronchial and alveolar epithelial cells are the primary cells that process deposited PM in the lung. As part of the processing mechanism, these cells release pro-inflammatory mediators that perpetuate a local, but also, a systemic response.’83’184 2.5.1 AM Response As mentioned earlier, AM exposure to PM results in an increase in oxidant production, release of pro-inflammatory mediators, such as TNF-a and IL-li’84 When incubated ex vivo with ambient particles, AMs produce other cytokines, such as, IL-6, IL-8, MIP-l and GM-CSF.72 IL-lO, a known anti-inflammatory cytokine that inhibits the production of IL-6, IL-8, TNF-a, and IL-13, is interestingly not associated with particle exposure72,perhaps suggesting that PM does not elicit an anti-inflammatory response. Together, these mediators produced by AMs generate an inflammatory response that is passed onto the epithelial and endothelial cells, which will then recruit leukocytes. PM may also inhibit the AM response to bacteria through an oxygen radical-mediated process,’27’129, 185, 186 which suggests that exposure to PM can decrease the lung’s ability 31 to defend itself against biological insult. Ultimately, the burden of PM in the lung can perpetuate and compromise the immune response leading to more COPD exacerbations. 2.5.2 Lung Epithelial Cell Response Lung epithelial cells form a large surface area that is exposed to inhaled PM and play an important role in the processing of these foreign objects. A number of studies,’79’ 187-189 including those from our own laboratory,’89’190 have provided evidence to suggest that lung epithelial cells exposed to PM produce a number of pro-inflammatory mediators, such as, GM-CSF, IL-6, IL-8, MCP-l, and leukemia inhibitory factor (LIF). These mediators can attract leukocytes, and PM exposure of epithelial cells also up- regulate the expression of inter-cellular adhesion molecule-i (ICAM- 1) to further promote leukocyte recruitment in the airspaces. Persistence and inflammation of the El A adenoviral gene in cigarette smoke-induced COPD when exposed to air pollution suggests another pathway for the retention of PM and contribution to chronic inflammation.’90193 Lung epithelial cells, coupled with a response from AMs, interact synergistically to produce GM-CSF and IL-6.’88 In a controlled, human volunteer study, exposure to PM induced an inflammatory response in the airways consisting of an increase in neutrophil trafficking’94and as a consequence of neutrophil attractant cyto/chemokines, production by bronchial epithelium.’95’196 These mediators can result in the damaging of the airways, which makes the airways much more susceptible to bacterial, flingal, or viral infections.’79This situation can ultimately lead to the exacerbation of symptoms in COPD. 32 2.5.3 PM-induced Lung Inflammation A number of similarities exist between the inflammatory mediators that exist in COPD and those that can be associated with PM exposure. There are increased levels of pro-inflammatory mediators such as IL-6, IL-113, TNF-a and IL-8 observed in induced sputum from patients with COPD.8’Macrophages are, by in large, the major contributors of the following mediators: IL-8, IL-113, TNF-cL, GRO-ct, ENA-78, MCP-1, and IL-lO. Epithelial cells produce IL-8, G-CSF, and MCP- 1 and are involved in neutrophil and monocyte recruitment into airspaces)97Elastase and MMP activation associated with neutrophils and macrophages are considered to be important mediators of lung parenchyma tissue destruction in COPD. Recent studies showed that this process is driven by pro-inflammatory cytokines such as TNF-a which appears to be a key initiating mediator.’98Montano et al.,’99 showed macrophage MMP activity and expression was upregulated in COPD patients who had been exposed to wood smoke, suggesting that this situation could result in emphysematous destruction. PM deposited and/or retained in emphysematous regions of the lung could activate the proteolytic pathway (eg. myeloperoxidase, elastase & MIvEP’s) and also stimulate the production of molecules such as IL-8 and ENA-78 involved in neutrophil recruitment and activation. Intratracheal instillation of PM10 in rats resulted in a neutrophil influx with an increase in endothelial permeability.’83This study by Li et a!. showed that PM exposure resulted in free radical activity as well. PM has also been shown to be genotoxic to alveolar epithelial cells, causing both apoptosis and DNA damage through a mitochondria-related death and free radical pathway.20°This oxidative stress could be the result of structural damage inflicted onto the mitochondria by intracellular PM.20’ In 33 addition, PM exposure of macrophages and human bronchial epithelial cells also results in an induction of heme oxygenase- 1 (HO-i), which is a key marker for oxidative stress.20’Oxidative stress appears to be a very important pathway for the deleterious effects of PM exposure.202 34 3 Chapter Three: Research 3.1 Working Hypothesis The general hypothesis that several members in our laboratory work on is that particulate matter are abnormally retained in lung tissues of subjects with COPD and that these retained PM perpetuate the inflammatory response in the lung contributing to progression of lung disease. For our thesis we will address the specific hypothesis that “the particulate matter burden in the lung tissues ofsubjects with COPD relate to the severity ofdisease and the inflammatory response in lung tissues.” We suspect that these particles cause a chronic inflammatory response in the lung, which continually stimulates the release of pro-inflammatory mediators that recruit more leukocytes into the airways and lung tissues (Figure 6). This chronic inflammatory response in the lung could also make the lung more susceptible to invading pathogens responsible for COPD exacerbations causing progressive loss in lung function. We also hypothesize that the majority of the PM is carbonaceous in origin because the lung environment would most likely process any heavy metals or organic compounds. 35 Figure 6 Possible mechanism for PM-induced C0PD2 3 PM10 Airway lumen / Macrophage *4, / UFP, PM25 .. • TLR-4 Epithelial Cells i ( Mast cell Cell death (necrosis, apoptosis) Proinflammatory factors: Tissue damage and TNFo, IL-i 13, IL-8 remodelling COPD Inflammation I 3.2 Specific Aims The overall goal of this project is to quantify the amount of particulate matter in the lung of subjects with COPD and relate it to the severity of the inflammatory response in lung tissues, as well as, the decrease in lung function (severity of COPD as characterized by the GOLD classification). We will pursue the following specific aims: 1) Quantify the particle load or burden of PM in lung tissues of COPD. 2) Determine where in these lung tissues PM are retained (airways, parenchyma, blood vessels, lymphoid tissues, macrophages etc). 3) Correlate particle burden and inflammatory markers with severity of COPD. 4) Determine the chemical composition of the PM retained in lung tissues through a novel in situ method. 36 These studies will determine the importance of particulate matter in the pathogenesis of COPD and improve our understanding of the mechanisms by which PM induces lung inflammation that could lead to novel therapeutic interventions in the future. 37 4 Chapter Four: Materials and Methods 4.1 Sample Selection 4.1.1 iCapture BioBank and Patient Enrollment Established in 1979, our laboratory has had a successful patient registry and lung tissue bank. The iCapture BioBank contains 30 years worth of confidential patient information and associated tissue samples, which allows for studies from both a molecular and pathological standpoint. A digital photography system at the iCapture Centre allows stereological studies with digital histological quantification measurements: the principle methodology used for my studies. Lung samples are collected from individuals who need lung resection surgery mostly for small peripheral nodules. These persons are invited to participate in the lung registry and tissue bank. The purpose of the lung resection surgery is to remove a lung or lobe that contained a lung tumour and after the tumour is removed, the remaining tissues are stored for research purposes. The lung registry also contains lung tissues from Barnes Jewish Hospital, Washington University, St. Louis, United States of America. These lung tissues come from subjects undergoing lung reduction surgery or transplantation. All subjects give consent for use of their tissues for research purposes. After the purpose of the study was explained to each individual, their clinical data, such as, preoperative lung function tests, thoracic CT scans, and smoking and occupational histories is collected (provided they gave written consent). Confidentiality is maintained by restricting access to the BioBank and using encrypted, unique identifiers for each individual. An oversight committee approves all past, present and future studies with registry tissue. This 38 committee continues to monitor the progress of the research that uses this BioBank patient information and tissue. 4.1.2 Tissue Specimen Collection Human lung tissue was obtained from 66 patients in the registry who required lung tissue resection surgery as described above at St. Paul’s Hospital, Vancouver, British Columbia, Canada or removal of an entire lung prior to transplant surgery due to severe, debilitating COPD (Barnes Jewish Hospital, Washington University, St. Louis, United States of America). These cases were chosen to represent the whole range of severity of COPD, from normal lung function to severe impairment requiring lung transplant surgery. To reduce the amount of confounding factors, they were also age and smoking history-matched. Samples from St. Louis were used because GOLD 3 and 4 patients rarely undergo lung resection surgery because of their poor lung function (FEV1 <50% but> 30%, respectively). Patients were then grouped based on their disease severity according to their GOLD classification (Table 3). The GOLD classification is based on the spirometric classification of COPD based on post-bronchodilator volume of air that can be forcibly exhaled in 1 second (FEV1)and also its relationship with forced vital capacity (FEV1/FVC<70%). Patients were grouped into a non-smoking control group, smoking control (formerly GOLD 0, at risk for COPD because they smoke but still have normal lung function), GOLD 1 (mild COPD), GOLD 2 (moderate COPD), and GOLD 3 and 4 (severe and very severe COPD, respectively). GOLD 3 and 4 cases were 39 — rM 0 . C CD CD C) 00 o CD CD 00 C D Cl) Cl) C) i C, ) C ,) CD - C) C ,) It C 0 0 — r) C j ( L’ J L’ J C C Q Q U I U I “ J ) L’ J ‘ J O C C U I U I U I U I L’ J ‘ J s ) ‘ J D C iJ L ) 00 - 1 — ‘ C C C C C 00 0 0 - - C - 1 E’ J C C C C SD SD U I . 1 . 1 4 ‘ J SD SC 0 0 . 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J 00 ‘ . 0 - ON J ’ . 0 . ) C z z z z z z z J L ’ J ’ - ‘ :C a !1 . - 4 - S . - 4 z z z z z z z z z z z z z z z z z z z z z — > 4 . c D - - 4 - 4 - 4 - 4 - 4 - 4 U i U i O N 0 0 J - 4 t % 00 00 00 - . 1 - — . 1 - . . — 1 00 ‘ . 0 00 ‘ J ‘ — — — ‘ ‘ J t’ ) k ) - 1 L . 1 ON U i U i ON — ON - 4.1.3 Lung Tissue Processing and Preparation The lung tissue is processed using a standard operating procedure (SOP) that outlines the standard procedures for personnel to follow when archiving lung specimens from transplant or autopsy. These procedures are important as only appropriately preserved specimens can be used for specific research studies. These techniques have been well recognized as a way to preserve their RNA, DNA, and protein constituents for future analysis. After the lung is received from the operating room, it is transferred to the lab where it is weighed. Samples for pathology, such as, nodes and tumour samples, are removed. At this point, tubing can be inserted in the bronchus with saline and the lung can be lavaged for cells. After the lavage, the whole lung is inflated with Cryomatrix (Shandon, Pittsburgh, PA) diluted 1:1 with saline via the bronchus (Figure 7)205 Cryomatrix is an embedding resin that supports frozen tissue, dissolves in water, does not expand when frozen, and freezes quickly. The Cryomatrix is mixed with saline because it would be too viscous to pump in the lung. After the lungs are frozen solid with liquid nitrogen vapours, they are kept frozen at -70°C. The lungs are then cut into 2 cm thick, transverse slices with a meat saw and then sampled (cored) by using a 1.5 cm radius hole saw. This process leaves a cylinder of lung tissue with a radius of 1.5 cm and a height of 2 cm. These cores are sampled in a uniformly random manner to get a good representation of each slice. 42 Figure 7 Steps in lung tissue preparation and sampling. A) Lung inflated with Cryomatrix and saline B) Lung frozen over liquid nitrogen vapours C) Meat saw D) Hole saw E) Lung slice with missing lung cores F) Frozen lung core 4.1.4 Sectioning of Lung Tissue Cores The cores of lung tissue are then embedded on the cryostat chuck with OCT (Optimum Cutting Temperature) compound (Tissue-Tek, Sakura Finetek, USA, Inc., Torrance, CA). OCT is an optimal cutting medium that is a water-soluble glycol and resins compound that supports the tissue for cryostat sectioning at temperatures of less than -10°C. The cryostat (Leica CM 1950, ThermoShandon) is a chamber, which contains a microtome for sectioning frozen tissue and it also can maintain very low temperatures. After the blade is cooled, adjusted to the correct angle, and set in the blade holder, the sample is trimmed until a complete section can be cut. After cutting the : / 43 sections at a thickness of 10 urn, the sections are adhered on to plain glass slides (kept at room temperature) and are allowed to air dry before staining. 4.2 Histology For microscopic analysis of the lung tissues via the light microscope, the sections were stained with the hemotoxylin and eosin (H&E) stain (Figure 8A). The hemotoxylin stains basophilic structures blue, typically those that contain nucleic acids by a complex, poorly understood mechanism. The eosin stains eosinophilic structures pink, such as the cytoplasm, proteins, and connective fibres. On a qualitative level, H&E allows an observer to distinguish between the various structures in the lung tissue, such as, the parenchyma, small airways, blood vessels, alveolar macrophages, and lymphoid follicles. Figure 8 A) Cropped digital image of alveolar wall tissue stained with H&E at 20x objective magnification. B) Example of black pigment in the H&E stained tissue at 20x objective magnification. For our frozen tissue, the rapid H&E procedure was used, as the typical H&E procedure can overstain certain tissues and in the longer hematoxylin bath step, the tissue A 44 may slough off the slide. Firstly, the tissue is fixed appropriately with 10% neutral buffered formalin (NBF) for 1 minute. This step fixes the tissue and preserves the structure of the tissue. After washing in water for 10 seconds, the slide is placed into a hematoxylin bath for 1 minute. After washing again in water for 10 seconds, the blue sections are placed in lithium carbonate (basic solution) for 10 seconds. After washing in water for 10 seconds, the slides are checked microscopically for adequate nuclear staining (nucleus should be blue to blue-black, can be adjusted in this step). The slides are then dipped in 70% alcohol for 10 seconds to condition the tissue (remove water) and then counterstained with eosin for 10-15 seconds. The excess eosin is drained and then the section is dipped (in sequence) in 80% isopropyl alcohol, 90% isopropyl alcohol, and twice in absolute isopropyl alcohol for 10 seconds each, respectively, to finalize the process of dehydrating the tissue before air-drying and coverslipping. The PM could be differentiated from the tissue as its colour is solid black and could be easily distinguished by eye or by computer from the dark blue hemotoxylin stained nuclei (Figure 8B). Predominately carbonaceous in nature, the PM required no additional staining to be visualized microscopically. 45 4.3 Stereology 4.3.1 Concepts To quantify the PM burden in the lung, we used a stereological method. Stereology is defined as the practical technique(s) for extracting quantitative information about a 3-dimensional (3-D) material from measurements made on a 2-dimensional (2-D) plane.206 We used a light microscope to visually resolve the tissue compartments and the PM in those structures. The use of a microscope, however, introduces a reducing fraction problem (Figure 9). As the magnification increases, a smaller fraction of the object of interest is actually studied. Figure 9 A cartoon depicting how as the magnification increases, it decreases (by great amount) the proportion of the object being studied206 Linear magnification 25x 125x 625x Because the whole object could not be studied by microscopy, a well-defined and structured method is used to select the samples or microscopic field of view. Sampling should be uniformly random (every sample having an equal chance of being selected) and lx 5x j,47th Approximatc fraction of 2-D object in field of view 111200th 1fl30.O(XJth 46 once the samples have been chosen, the same method of extracting data must be used for each sample. Allowing every sample an equal chance of being selected will prevent sampling bias from occurring. Systematic bias (incorrect measurement tool, instrument calibration errors) is prevented by using the same methods of estimation for all fields of view and by comparing results of intra and inter-observer error. A hierarchical system (Figure 10) of sampling is used and our study consists of the lung(s), cores of tissue from the lung, sections cut from the cores, and fields of view digitally captured from the sections. Each donor, lung, core, section, and field of view is different and this introduces variability. The variability between individuals (around 70%) is vastly greater than the variability between sections (around 5%) and fields of view (around 2%).206 By only increasing the number of fields measured, the precision of the measurements will only increase by a relatively small amount. In order to efficiently increase the precision of the measurements, it is important to increase the number of individuals (cases), as opposed to increasing the number of fields of view. 47 /EEEJ I II I • I One of the primary objectives of this study was to look at how much PM was present in any given tissue compartment in the lung. In stereology, points act as probes for volume. These probes are applied in 3-D by physically cutting the specimen into thin sections and then applying a 2-D grid (of points) onto the section. This two-stage process is similar to imaging throwing a 3-D lattice of points into a volume of space. For the sake of efficiency, it is important to use the least number of points, while still maintaining precision and accuracy. By using points, a value for a volume fraction (Vv), which is defined as the volume proportion of one phase within a reference volume, is achieved. For this particular study, the PM is considered to be a rare substance and represents a very small proportion of the reference volume (tissue). Using a coarse grid to estimate the amount of PM would not be very accurate, as much of the PM would be missed. As Figure 10 The hierarchical nature of sampling in microscopy. The need for uniformly random sampling is paramount to make an accurate and precise estimate.206 Obfrct Block Section E I•II Ficldsof I I I I View I II • I I j j L11E Lrn SIll 1111 1111 I II II I I I I • I 48 such, a finer grid (more points) is required and by using a point grid that combines 2 sets of points, the ratio of coarse and fine points can be used to estimate an accurate Vv of PM in each lung tissue compartment (Figure 11). If there were twice as many points on the fine grid (Figure 1 1A) as compared to the coarse grid (Figure 1 1B), the area per point associated with each coarse point is twice that of each fine point. Figure 11 A) Coarse grid (196 points) overlaid onto digital image of tissue. B) Fine grid (1500 points) overlaid onto digital image of tissue at 20x magnfication. 4.3.2 Equipment and Software For the capturing the fields of view digitally, a light microscope (Nikon Eclipse E800) equipped with a digital camera (JVC3-CCD KY F-70, Diagnostic Instruments) was used. To transfer the images to computer, image capture software (KY-FRM) plug- in for Adobe Photoshop CS was required. During the course of my experiments, the digital camera was upgraded to a SPOT Flex digital Camera (Diagnostic Instruments, Sterling Heights, MI) and the image capture system to Diagnostic Instrument’s proprietary SPOT Imaging Software. The upgrade allows for better resolution, colour 49 B rendition, white balance, and streamlined user interface. For image analysis, I used the digital-image-analysis software Image Pro Plus 4.0 (Media Cybernetics, Bethesda, MD). 4.3.3 Image Capture Protocol Of the 66 cases available (Table 3), only those that had 5 or more slides (sections) per case were chosen to capture digital fields of view. To resolve the various structures in the lung, as well as the PM, an objective magnification of 20x was necessary (total magnification = 200x). Fields were randomly captured, with coordinates being chosen by a random XY coordinate generator. Fields that were completely devoid of tissue (no usable Vv) and fields that fall on the perimeter of the lung core sections (Figure 12) were excluded. Two fields of view per slide were captured. Figure 12 Fields of view excluded (red) and included (green) in this study PM burden in all compartments oflung tissues: To determine the burden of the PM in various compartments of the lung, these variables were assigned tags in Image Pro Plus. Section Fields of view excluded Fields of view included 50 A “tag” is a digital marker used to define a certain point on the grid. Using the coarse grid, the alveolar wall, the airspace, and any other type of tissue of interest were tagged (placing a digital tag on each point on the grid) manually. Using the fine grid, the alveolar wall with and without PM, airspace with and without PM, blood vessel wall with and without PM, airway wall with and without PM, alveolar macrophage with and without PM, lymphoid tissue with and without PM were tagged manually. These tag files were then exported to Microsoft Excel (Microsoft) as raw data to be processed. The volume fraction of a defined variable (for example alveolar wall) will then be defined by the number of points falling on that specific object divided by the total number of points on the grid selected. In the case of PM, the total number of points of PM falling on a particular compartment, divided by that compartment, will determine the Vv of PM in a certain compartment of tissue. PM burden in small blood vessels: After analyzing the results from the PM burden in all tissue, it seemed that we were not able to randomly catch enough blood vessels to make an accurate measurement of the PM burden in that specific compartment. Therefore, by biasing the selection to just blood vessels alone, that specific compartment could be studied more precisely. Instead of using a random coordinate generator used to achieve fields of view for the PM burden in all types of tissue, all small blood vessels (between 0.5 mm and 2.0 mm largest diameter, less than 3:1 ratio of largest diameter to smallest diameter) were captured in all cases via a zigzag search. Blood vessels were arbitrarily cut off at those sizes to keep the 20x magnification constant (2.0 mm would fill the whole field of view at this magnfication) and the 3:1 ratio was to exclude blood vessels that had 51 been sectioned obliquely (blood vessel wall would not be representative of the actual dimensions). To quantify the particle burden in these blood vessels, a macro (computer program) was written for Image Pro Plus to automate the process of determining the Vv of PM in the blood vessel wall. Firstly, the inner lumen and the outside of the adventitia of all blood vessels were manually traced and the areas bounded by the tracings were saved as an area of interest (Aol). For this program, each pixel of the image was considered a point. The program uses these areas to calculate the area of the lumen (Al) and subtract it from the area bounded by the adventitia (A5) (Figure 13). The resultant area, which represents the blood vessel wall, would then be the analyzed using a colour segmentation file that would differentiate the black colour from the pink/red/blue tissue via a colour threshold determined prior to running the macro. Colour segmentation has been used successfully in other publications from this lab.207 Figure 13 Steps in the program for the automated blood vessel analysis. A) Inner lumen traced. B) Inner lumen area quantified (in pixels). C) Al D) Perimeter of adventitia traced. E) Black pigment quantified (in pixels) within the perimeter of the adventitia. F) A5 .. A 52 PM burden in lymphoidfollicles: Another structure of interest was the lymphoid follicles. As with the blood vessels, the follicles were rare, so it was prudent to also use a zigzag search to bias the selection toward lymphoid follicles. These images, unlike the blood vessels, were taken at an objective magnification of lOx (total = lOOx) because the majority of follicles are larger than what a 20x objective field of view can capture. The macro written for the PM burden in blood vessels was re-written to remove the step of including and subtracting the Al area. This would allow the program to determine just the area of the follicle and also the area of the PM inside the follicle. 4.3.4 Statistical Analysis With the final data from the PM burden in all tissues, blood vessels, and lymphoid follicles, statistical analysis was done to determine if parts of the hypothesis were supported by the data. Correlations: A scatter diagram helped to determine the relationship between 2 variables. Each dot in such a diagram represents, for example, the PM burden in the blood vessel and FEy1 pair for one case. The strength of the correlation depends on the linear association (correlation coefficient). The closer the association is to 1, the strong the linear association, be it positive (slope up), or negative (slope down). This correlation coefficient is labeled r. For this study, a p-value of less than 0.05 was considered significant. 53 Tukey-Kramer: To compare the PM burden in the tissues between non-smoking and COPD severity groups, I used the Tukey-Kramer method to determine if there were significant differences between the 5 groups. The Tukey-Kramer method is a single-step, multi-comparison procedure used to compare the means of all treatments with the all other treatments and applied to all pairwise comparisons simultaneously, while having unequal sample sizes. The process is similar to a student’s t-test, but corrects for multiple comparisons being made. For this study, a p-value of less than 0.05 was considered significant. Kruskal- Wallis one-way-analysis-of.variance-by-ranks test: This is a non-parametric test to look at the differences of 3 or more independent groups that do not necessarily have to have a normal distribution. The actual data is replaced by rankings, and in this way the calculations are simplified. Student T-test: This test will analyze the means of two, normally distributed means of a population to determine if they are statistically different. Software: All data was compiled initially in Microsoft Excel, and then transferred over to iMP 5.1 Statistical Discovery Software (JMP, Cary, NC) to run all the statistical tests. IMP would output both the correlation coefficents and p values. To create the graphs, the graphing program Sigmaplot 10 (Systat Software Inc., San Jose, CA) was used. 54 4.4 Gene Expression 4.4.1 Concepts and Rationale The definition of gene expression is when information of the gene is translated into functional gene products: typically mRNA and proteins. Often, the amount of gene expression (under or over-expression) can result in major physiological changes. Therefore, it makes sense to look at the gene expression in disease states, such as, COPD, in order to gain an understanding as to which genes may be associated with an increase in severity. Besides looking at the PM burden in the lung as it relates to FEV1 or FEV1/FVC, it is also important to see if this burden is correlated with gene expression known to be associated with both the type of inflammation in lung tissues of patients with COPD as well as the severity of COPD. Because of the chronic nature of the inflammatory response in airways and lung parenchyma in COPD, we selected to look at genes involved in chronic inflammation and the repair process. We specifically looked at these genes (see table 4) in lung parenchyma (that include the smaller blood vessels) and linked and relate it to PM burden in the lungs. Also, for blood vessels only, wall thickness was analyzed against gene expression. All patients (except for the non-smokers) in the current study were part of the patient groups where mRNA gene expression was determined by members of our lab, specifically John Gosselink and colleagues.208 They completed the bench work for this portion of the material and methods section. The following is a brief description of the basic methodology used in that unpublished manuscript, using the same sample tissue used for this study. 55 4.4.2 RNA Isolation and Assessment In the Gosselink et al. study,208 differential gene expression in the airways and the parenchyma (which included the blood vessels) was investigated. Since most of the data generated for this thesis came from the burden of PM in the parenchyma and blood vessels, the PM and morphometric data were correlated with the corresponding patient’s gene expression data from the parenchyma. To separate the two distinct compartments, Gosselink et al.208 used laser capture micro dissection (LCM) to remove the airway from the surrounding parenchyma and stored before RNA isolation. The start of most molecular biology experiments requires high quality, intact RNA. The isolation technique used was an RNeasy Mini kit (Qiagen, Mississauga, Ontario), which allows for the quick purification and a consistent yield of RNA from the given tissue. Using an Agilent 2100 Bioanalyzer (Agilent Technologies, Palo Alto, CA), the isolate was assessed for quality based on internal standards. 4.4.3 Amplified cDNA Before the RNA can be used in quantitative (q) polymerase chain reaction (PCR) assays, it must be first converted to DNA. Because of the small amounts (100 ng) of RNA that were derived from the parenchyma and airways, it was necessary to convert the RNA into eDNA, and then amplify it. The kit used for this process was the Clontech Super SMART eDNA Amplification Kit (Clontech, Mountain View, CA), which is 56 useful for generating eDNA from very small amounts. Gosselink and colleagues209 confirmed that the amplified eDNA maintains the relative expression levels of the original RNA. 4.4.4 Quantitative Polymerase Chain Reaction PCR is a technique that amplifies DNA into quantities that can be used later for molecular analysis. The benefit of doing qPCR is to amplify and quantify target sequence of DNA. The Taqman probe has a quenching dye attached to its 3’ end and a reporter dye on its 5’ end. In the intact Taqman probe, the quenching dye reduces the fluorescence of the reporter dye. However, during the amplification process, the Taq polymerase encounters the Taqman probe that is bound to the DNA being amplified and removes the 5’ fluorescently tagged nucleotide from the probe, distancing the remainder of the probe and continues amplification. This process separates the quencher from the reporter, so the reporter is free to release its energy in the form of light. The more amplification that takes place, the more reporter dye is release and more light is emitted and quantified by computer. The Taqman qPCR assay (Applied Biosystems, Foster City, CA) was used to profile the expression 46 genes chosen from the wound-healing literature (Table 4). 4.4.5 Gelatin Zymography Gelatin zymography is a technique used to monitor enzymatic activity. It is based on sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE), but it includes a substrate, in this case, gelatin, copolymerized with the gel. The zymogram is stained a dark colour, so when the enzyme digests its substrate, the area looks clear. Of 57 the 6 patients with high and 5 patients with low MMP2 mRNA expression, in the Gosselink et al. study,208 MMP2 activity had been measured using 10% zymogram gels with 0.1% gelatin (Biorad, Hercules, CA). The activity was quantified by densitometry of the digested bands with a Chemigenius Bioimaging System (Syngene, Cambridge, UK). 4.4.6 Statistical Analysis Gene expression from the lung parenchyma was correlated with the PM burden in various compartments of the lung using a scatter diagram and subsequent linear association described in Section 4.2.4. Table 4 List of wound-healing genes in COPD Gene Symbol Gene Name ADAM33 ADAM metallopeptidase domain 33 BCL2 BCL-2 COL1A1 collagen 1 alpha 1 COL3A1 collagen 3 alpha 3 CTGF connective tissue growth factor EGF epidermal growth factor EGFR epidermal growth factor receptor EGR1 early growth response 1 F2R coagulation factor II (thrombin) receptor FGF2 fibroblast growth factor 2 FGFR fibroblast growth factor receptor FGG fibrinogen gamma chain FN 1 fibronectin 1 GMCSF granulocyte macrophage colony stimulating factor HBEGF heparin binding epithelial growth factor ICAM1 intercellular adhesion molecule IL-i B interleukin 1 beta IL-4 interleukin 4 IL-6 interleukin 6 IL-8 interleukin 8 IL-i 3 interleukin 13 ITGA1 integrin alpha 1 58 Gene Symbol Gene Name MMP1 matrix metalloproteinase 1 MMP2 matrix metalloproteinase 2 MMP3 matrix metalloproteinase 3 MMP8 matrix metalloproteinase 8 MMP9 matrix metalloproteinase 9 MMP 10 matrix metalloproteinase 10 MMP 12 matrix metalloproteinase 12 MMP 13 matrix metalloproteinase 13 MUC5AC mucin 5 subtypes A and C PDGFA platelet derived growth factor alpha PDGFRA platelet derived growth factor receptor alpha PDGFRB platelet derived growth factor receptor beta PLAU plasminogen activator urokinase PLAUR plasminogen activator urokinase receptor PTGS2 prostaglandin-endoperoxide synthase SERPINE2 serpin peptidase inhibitor, dade B, mem 2 TGFB 1 transforming growth factor beta 1 TGFB2 transforming growth factor beta 2 TGFB3 transforming growth factor beta 3 THBS1 thrombospondin 1 TIMP1 TIMP metalloproteinase inhibitor 1 TIMP2 TIMP metalloproteinase inhibitor 2 TNF tumor necrosis factor VEGF vascular endothelial growth factor 4.5 Raman Microspectroscopy 4.5.1 Concepts Raman spectroscopy is a technique based on the principles of the inelastic scattering of light, typically from a laser source. When photons strike the surface of the given element, they are absorbed and reflected back at a frequency different from that of the original light source. This difference in energy is the basis of the Raman effect. The Raman effect only makes up 0.00 1% incident photons, whereas the Rayleigh scattering (light emitted back at the same frequency) makes up the other 99.999%. Raman 59 spectroscopy is typically used in chemistry to look at specific vibrational energy of chemical bonds in molecules. 45.2 Rationale Although the black pigment in the stained tissue is easily visualized microscopically, the composition of the particles retained in the lung tissues is unclear. This PM could be from cigarette smoke particles or other inhaled air pollution sources. Furthermore, even if one knows the composition of the original PM, post-retention biochemical changes in the tissues could have occurred. We have selected to use this technique in this pilot experiment over other techniques (ie. gas chromatography-mass spectroscopy (GC-MS)) for a number of reasons. Firstly, the technique had been used to describe PM in a study by Batonneau and colleagues210 and had been shown to be useful in that regard. Secondly, it permitted the study of the particle in situ: all other techniques would require some form of tissue manipulation/extraction of the PM that could change their chemical composition. A further benefit of this technique would be that it could be done on the unfixed frozen tissue we used in our study. Finally, it had never been done before with tissue for the purposes of describing the chemical composition of the PM in tissue and may prove to be a novel way to describe the composition of PM. However, the downsides of this technique would be the fact that not all elements, such as some heavy metals, have a Raman spectrum, and would therefore not appear in the spectra. Time and instruction on the Raman instrument system was generously donated by the Chemistry Department in the Michael Smith Laboratories at the University of British Columbia. 60 4.5.3 Equipment and Software For the purposes of this experiment, a Renishaw Ramanscope System 1000 (Renishaw) combined with an infinity-corrected Lecia DMLB microscope (Leica Microsystems, Richmond Hill, Ontario, Canada) was used. The laser in the Ramanscope system was an RL785 diode laser (Renishaw). For the purposes of the study, the 50x10.75 numerical aperture (NA) was used to focus the laser on the PM in the tissue and collect the inelastic scattering of light. The microscope was also equipped with a motorized and programmable stage (ProScan Series, Prior Scientific Inc., MA), which can move in any direction of the XYZ plane. A digital video camera is also attached to the microscope to allow real-time sample positioning via the connected computer monitor. Typically, a Raman system consists of 4 parts: the laser, sample illumination and light collection optics, a wavelength selector, and a detector. In this system, the laser is directed through a beam expander that allows the beam to obtain uniform excitation. The excitation beam and the Raman scattered radiation are both directed to the holographic notch filter (HNF). The HNF lets the excitation beam reflect towards the sample via the microscope and allows Raman scattered radiation (coming back from the sample) to pass through to the detector. The HNF also rejects the Rayleigh scattering. The radiation travels to the grating spectrometer where it is dispersed and picked up by a thermoelectrically cooled AIMO CCDO2-06 CCD array detector (e2v technologies, Essex, UK). The signals detected by the CCD camera are sent to the Renishaw Windows-based Raman Environment (WiRE, version 1.3.30, Renishaw) and Graphic 61 Relational Array Management System software (Grams/32, version 4.14, Level II, Galactic Industries Corporation, Salem, NH). 4.5.4 Microscope Protocol Lung sections 10 um thick of 2 cases were cut from frozen tissue in the same manner explained in Tissue Preparation section. The only difference was after the sections were cut, they were adhered to aluminum foil wrapped around plain glass slides (Figure 14). The reason for this was that silica (glass) has a strong Raman spectrum that would overpower most other elements, whereas the aluminum has virtually no spectra. Figure 14 Tissue samples sectioned and melted onto aluminum foil wrapped around uncoated glass slide for Raman microspectroscopy use. 62 After allowing to air dry, the tissue (without coverslip) would be placed in the stage holder and the stage calibrated to point the laser directly at the black pigment in the tissue (Figure 15). Figure 15 Images captured from light microscope of the Raman system. A) The lighter colour is tissue, whereas the deep black pigment was the object of interest. B) The crosshairs would indicate the exact point where the laser would strike the tissue. II II II 1• — ‘S -. One of the parameters of the microscope that can be controlled is laser power. We hypothesized that the main constituent of this black pigment was carbon, so under these conditions, it was possible to burn the carbon and the surrounding tissue. However, the laser power needed to be strong enough to provide a signal. Another factor to control is the exposure of the sample to the laser. For the best “exposure,” we found that a detector time of 30 seconds and a laser power of 25% seemed to give the best results. By results, the strongest peaks with the least amount of background noise. The microscope was set to a 50x objective lens. The program outputs data in wavelength number vs. arbitrary units of intensity (AUI). a in 7* II A 63 Measurements were taken where the black pigment could be found within the tissue. Because of a lack of staining and processing, it is difficult to say exactly which compartment the black pigment was located. While adjusting the laser power, a new area of black pigment would have to be chosen because of that area might burn (characteristic of carbon). These measurements were taken on two different samples (cases) with black pigment visible to the naked eye. 64 5 Chapter Five: Results 5.1 Total Lung Burden 5.1.1 Observations By observation alone, PM can be found in virtually all compartments of the lung. These compartments include: the parenchyma, airways, blood vessels, alveolar macrophages, and lymphoid follicles (Figure 16). 65 Figure 16 PM (black pigment) can be found in (A) the parenchyma, (B) alveolar macrophages, (C) airway wall, (D) blood vessel wall, and (E) lymphoid follicles. - D 66 Jh %c I 44ff q 1’k2 ‘. .;•_ f ‘ r 4’ ‘S 4% Sfl B C 4 a - b j . E 5.1.2 Comparison to Clinical and Histological Data All compartments of the lung included (alveolar wall, airways, blood vessels, alveolar macrophages, lymphoid follicles), were grouped together for each case to get a total burden of PM. Non-smokers were compared with patients with those with COPD, and there was a significant difference (Student’s T-test, p< 0.0002) between them (Figure 17L). Patients who were smokers who had normal lung function were compared to those smokers with abnormal lung function, and there was also a significant difference (Student’s T-test, p<O.Ol) between these groups (Figure 17R). Figure 17: PM burden in non-smokers with normal lung function and those with COPD (L) and the PM burden in smokers with normal lung function (GOLD 0) and those with abnormal lung function (GOLD 1-4) (R) — 0.025 — 0.025 0002 CO0 0.020 0.020 *p<0.0l ‘I- CO ann4e C C. 10.010 ____ : _________ C __ __ 10.010 0.005 0.005 00000 Nor’mal 0.000 -V — Normal PFT Abnormal PFT Student t-tesf Student t-test When compared to each other, it appeared as if the non-smoking control had the smallest Vv of PM in all lung tissue (Figure 18). The trend of increasing Vv of PM seemed to increase up to GOLD 2, and then decrease in the GOLD 3 and 4 group. However, the only groups that were significantly different from each other were the non smoking control group and the GOLD 2 group (Tukey-Kramer, p<O.O5). 67 0 4- 0 > > Figure 18 Vv of PM in all lung tissues across non-smoking controls and groups of increasing COPD severity. Non-smoking controls and GOLD 2 groups were significantly different (p<O.O5). 0.030 0025 0.020 0.015 0.010 0.005 0.000 COPD Severity If the GOLD 3 and 4 group was removed and the Kruskall-Wallis ANOVA is applied, then there is a significant difference (p<O.0005) between the remaining groups (Figure 19). Non-smoking Smoking GOLD I GOLD 2 GOLD 3+4 68 • 0.03. C) z (0 (0 0.02. ____ z 0.01. 0 0.00• The Vv of PM in each of the cases was also plotted against the clinical and historical data (Table 5). The Vv of PM against FEV1/FVC had an r2 value of 0.13 and a negative slope (-0.0002) (p = 0.02) (Figure 20A). The Vv of PM against pack years had an r2 value of 0.15 and a positive slope (0.0002) (p < 0.01) (Figure 20F). Table 5 Correlation of PM burden in all compartments of the lung with clinical and histological values Clinical/Histological Parameters r2 Slope p-value FEV1/FVC 0.13 -0.0002 0.02 FEV1 0.05 -0.0001 0.053 Lm 0.0004 0.000004 0.89 Airway thickness 0.02 0.00005 0.25 Age 0.02 0.0002 0.17 Pack Years 0.15 0.0002 < 0.01 Figure 19 Burden of PM with increasing levels of COPD severity *p<0 0005 I ::::::::::.:::::::::::::::: I I Non-smker Smokers GOLD I GOLD 2 One way ANOVA (Kruskall.WaIIis test) 69 Figure 20 Vv of PM in all tissue A) vs. FEV1/FVC B) vs. FEV1 C) vs. Lm D) vs. airway wall thickness E) vs. age F) vs. pack years 0.1 0.1- 0.09 009 0.08 0.08 > 0.07 > 0,07 0.06 0.06’ 0.05 0.05 0.04 • 0.04 • 0.03 • 0.03 • • ____________ —0.01 —0.01 I I 20 30 40 50 60 70 80 90100110120130140 10 20 30 40 50 60 70 80 90 1001101: FEV1iFVC A FEV1 B 0.1• 0,1• 0.09 0.09 0.08 0.08 > 0.07 > 0.07 0.06’ 0.06 0.05 0.C5 0.04 0.04- a . . • a . 0.03 • .. . 0.03- • 0 02’ °- 0.02- • 0.01’ . . . . 0’ • 0- • —0.01’ I I I 150 200 250 300 350 400 450 500 50 100 150 200 250 Lrn AWThicness C D 0.1 0.1- 0.09 0,09- 0.08- 0.08- > 0.07- > 0.07- - 0.06- 0.06- 0.05’ 0.05- * .*... 40 45 50 55 60 65 70 75 80 -20 0 20 40 60 80 100 120 140 160 Age Pack Ye8IS E F 70 5.1.3 Comparison to mRNA Expression The only gene where expression in the parenchyma weakly correlated with the particle burden in all compartments of lung was fibrinogen gamma chain (FGG), which is essentially a marker for fibrinogen production. This correlation had an r2 value of 0.22 and a positive slope (0.001) (p <0.01) (Figure 21). Figure 21 Vv of PM in all tissue vs. expression of FGG in the parenchyma 0.1 - ___________________________________ . 0.09- 0.08- 0.07- 0.06- 0.05- °- 0.04- o2s751bi.515 FOG 5.2 Alveolar Wall 5.2.1 Comparison to Clinical and Histological Data Separating the alveolar wall from the total lung burden, the results indicate larger difference between COPD severity groups (Figure 22). The non-smoking control and smoking control groups were significantly different (Tukey-Kramer, p<O.05) from GOLD 2, but not significantly different when compared to GOLD 1 and 3/4. 71 I * Figure 22 Vv of PM in the alveolar wall across the non-smoking group and the COPD severity groups 0.025 * 0.020 0.015 0.010 0.005 0.000 The Vv of PM in the alveolar wall in each of the cases was also plotted against the clinical and historical data (Table 6). The Vv of PM against FEV1/FVC had an r2 value of 0.16 and a negative slope (-0.0002) (p = 0.001) (Figure 23A). The Vv of PM against pack years had an r2 value of 0.13 and a positive slope (0.0001) (p <0.01) (Figure 23F). Non-smoking Smoking GOLD 1 GOLD 2 GOLD 3+4 COPD Severity 72 Table 6 Correlation of the PM burden in the alveolar wall with clinical and histological values Clinical/Histological Parameters r2 Slope p-value FEV1/FVC 0.16 -0.0002 0.001 FEV1 0.05 -0.0001 0.07 Em 0.0004 0.000004 0.95 Airway thickness 0.06 0.00007 0.10 Age 0.0001 0.0002 0.39 Pack Years 0.13 0.0001 <0.01 73 Figure 23 Vv of PM in the alveolar wall vs. A) FEV1IFVC B) vs. FEV1 C) vs. Lm D) vs. airway wall thickness E) vs. age F) vs. pack years. AlvWall = Alveolar wall 008- 008 007- 0.07 0.06- 0.06 > > 005- 0.05- 0.04- 0.04’ 0.03- : 0.03 0.02- —-__ . 0.02’ ... 0 ° —0.01— I I —J01. I 20 30 40 50 60 70 80 90 100110120130140 10 20 30 40 50 60 70 80 90 100 110 12 FEV1JFVC A FEV1 B uvo- 0.08 0.07- 0.07 0.06- 0.06 > > oos- 0.05 004- 0.04’ 0.03- .: . 0.03 . . 0.02- 0.02’ -001- I I -001 -rrm--’r- i 150 200 250 300 350 400 450 50 50 100 150 200 5 Lm AW Thclrness C D 008- 0.07- 0.07 0.06- 006’ > 0.05- > 0.05’ - 004- 0.04- 0.03- . . 0.03- . 0.02- . : . . 0.02- :. • :._— G.0: 0.01 _— —:. . —43.01— I I I I I I 40 45 50 55 60 65 70 75 80 -20 0 20 40 60 80 100 120 140 160 Age Pacl< Years E F 74 In addition, the PM Vv in all lung tissue was compared to the PM Vv in alveolar wall, and had a strong positive correlation (slope .71, p<O.Ol) with an r2 value of 0.74 (Figure 24). Figure 24 Vv of PM in all lung tissue vs. Vv of PM in the alveolar wall 0.08 u _______________________ —0.01• I I I I I I I I -0.01 0 .01 .02 .03 .04 .05 .06 .07 .08 .09 .1 PM1O Tissue Vv 5.2.2 Comparison to mRNA Expression As with the PM burden in all tissue, the only gene that weakly correlated with the particle burden in all compartments of lung was fibrinogen gamma chain (FGG), which is essentially a marker for fibrinogen. This correlation had an r2 value of 0.19 and a positive slope (0.001) (p < 0.01) (Figure 25). 75 Figure 25 Vv of PM in the alveolar wall vs. expression of FGG in the alveolar wall 0.08 O.07 O.06 0.05 O.04 FGG 5.3 Blood Vessel Burden 5.3.1 Comparison to Clinical and Histological Data The majority of PM was observed in the adventitia of the blood vessels. It is unclear where the PM are The PM burden across the COPD severity groups showed a significant difference between the smoking control and GOLD 2 group (p=O.Ol) (Figure 26). All other groups, when compared to each other, were not statistically significant. Because the adventitial tissues are adjacent to alveolar walls, some of these PM may also reside in or maybe part of PM in alveolar walls. The PM in vessel walls may also be in lymphatic channels and be part of the lymphoid system. Further studies are needed to delineate these issues. 76 Figure 26 Vv of PM in the blood vessel walls across the non-smoking group and the COPD severity groups 3.5 3.0 2.5 2.0 1.5 1.0 0.5 0.0 The Vv of PM in the blood vessesi in each of the cases was also plotted against the clinical and historical data (Table 7). The Vv of PM against FEV1/FVC had an value of 0.18 and a negative slope (-0.0002) (p = 0.001) (Figure 27A). The Vv of PM against pack years had an r2 value of 0.13 and a positive slope (0.0001) (p <0.01) (Figure 27F). Non-smoking Smoking GOLD 1 GOLD 2 GOLD 3+4 COPD Severity 77 Table 7 Correlation of the PM burden in the blood vessel wall with clinical and histological values Clinical/Histological Parameters r2 Slope p-value FEV1/FVC 0.18 -0.0002 0.001 FEV1 0.05 -0.0001 0.07 Em 0.0004 0.000004 0.95 Airway thickness 0.06 0.00007 0.10 Age 0.0001 0.0002 0.39 Pack Years 0.13 0.0001 < 0.01 78 Figure 27 Vv of PM in the blood vessel wall A) vs. FEV1IFVC B) vs. FEy1 C) vs. Lm D) vs. airway wall thickness E) vs. age F) vs. pack years I I 20 30 40 50 I I 60 70 80 90 10011012013014 FEVI /FVC When the PM burden in the blood vessels was compared to the PM burden in all tissue and the parenchyma, it had an r2 value of 0.29 and a positive slope (50.62) (p < 79 6 5, 0. 6 5. 0- 150 200 250 300 350 400 450 500 Lrn 6- 5. 3- S S 3, 0- I •I’I I• 10 20 30 40 50 60 70 80 90 100 iiOi FE Vi 6’ 5- 50 100 150 200 250 C 6- 5. 4- 0 I I: -20 0 20 40 60 80 100 120 140 160 D Age E Pack Years F 0.00 1) (Figure 28A) and an r2 value of 0.29 and a positive slope (60.05) (p <0.001) (Figure 28B). Figure 28 A) Vv of PM in all lung tissue vs. Vv of PM in the blood vessel wall B) Vv of PM in parenchyma vs. Vv of PM in the blood vessel wall -0.010 .01 .02 .03 .04 05 .06 07.08 .09 1 -0.010 01 02 03 .04 .05 06 .07 .08 B PM10 Tissue Vv PMlOPJvwaIt Vv With the blood vessels traced, it was also possible to compare the wall area with the PM burden, and that resulted in an r2 value of 0.12 and a positive slope (0.02) (p < 0.00 1) (Figure 29). 80 Figure 29 PM area in the blood vessel vs. the wall area of the blood vessel 1.4e+5 1.2e+5 -j . I . 1.00+6 -f I .. 8Oe+4 -1I . 6.0e+4-f • I •.• • I • • •4.Oe+4-f •?‘ i.•• .• -2.Oe-i-4 I -2.Oe+5 0.0 2.Oe+5 4.Oe+5 6.Oe+5 8.Oe+5 1.Oe+6 1.2e+6 1.4e+6 1.6e+6 Wall Area (Pixels) • Wall Area vs PM Area Plot I Regr Wall area can also be correlated with the clinical data and histological analysis (Table 8). The wall area % against FEV1 had an r2 value of 0.07 and a positive slope (0.11) (p = 0.03) (Figure 30B). Table 8 Correlation of blood vessel wall thickness and clinical and histological values ClinicaLIHistological Parameters r2 Slope p-value FEV1/FVC 0.007 0.04 0.52 FEV1 0.07 0.11 0.03 Lm 0.01 -0.000004 0.34 Airway thickness 0.07 0.08 0.07 Age 0.001 0.04 0.80 Pack Years 0.006 0.006 0.90 81 Figure 30 Blood vessel wall area thickness A) vs. FEV1/FVC B) vs. FEy1 C) vs. Lm D) vs. airway wall thickness E) vs. age. F) vs. pack years 80- • 80 70- 70 • .1 20- I 1 I I 20 I 20 30 40 50 60 70 80 90 100110120130140 10 20 30 40 50 60 70 80 90 100 110 120 FEV1IFVC A FEV1 B 80- 80- 70- • • . 70- 0 200 250 300 350 400 450 500 50 100 150 200 250 Lm C AVY Thickness D 80- • . 80 70- • 70 . •• • •:_ . _____ >60 —---------—-———— 60- • • • • •. •. 5Q 40- • 40 30- • 30 20- I I I 20 I I I I I 40 45 50 55 60 65 70 75 80 -20 0 20 40 60 80 100 120 140 160 Age E Pack Years F When the wall area % of the blood vessels was compared to the PM burden in all tissue and the parenchyma, it had an r2 value of 0.02 and a positive slope (123.14) (p = 82 0.21) (Figure 31A) and an r2 value of 0.06 and a positive slope (217.98) (p = 0.06) (Figure 31 B), respectively. Figure 31 A) Vv of PM in all lung tissue vs. blood vessel wall area thickness B) Vv of PM in parenchyma vs. blood vessel wall area thickness E ——— : 30- 30 20— 20 -0.01O.01.02.03.04.05.0607.08.09.1 0.010 01 .02030405.0607,08 B PM1O Tissue Vv PM1 0 .SJvwall Vv 5.3.2 Comparison to mRNA Expression There were no correlations with the PM burden in the blood vessels and the mRNA expression. However, there were correlations with the blood vessel wall thickness (Table 9). The wall area % against IL-4 had an r2 value of 0.44 and a negative slope (- 1.01) (p <0.01) (Figure 32A). The wall area % against PDGFRB had an r2 value of 0.27 and a negative slope (-0.50) (p < 0.01) (Figure 32C). The wall area % against TGFB1 had an r2 value of 0.23 and a negative slope (-1.72) (p < 0.01) (Figure 32D). The wall area % against TNF had an r2 value of 0.18 and a negative slope (-1.72) (p <0.01) (Figure 32E). The wall area % against VEGF had an r2 value of 0.18 and a negative slope (-0.36) (p <0.01) (Figure 32F). 83 Table 9 Correlation of mRNA expression with blood vessel wall thickness mRNA Expression r2 Slope p-value IL-4 0.44 -1.01 < 0.01 IL-13 0.24 -18.55 0.08 PDGFRb 0.27 -0.50 < 0.01 TGFb1 0.23 -1.72 <0.01 TNF 0.18 -1.72 <0.01 VEGF 0.18 -0.36 < 0.01 84 Figure 32 Blood vessel wall area thickness A) vs. IL-4 B) vs. IL-13 C) vs. PDGFRB D) vs. TGFB1 E) vs. TNF F) vs. VEGF 90- 9a• 80- • 80 70- 1 70 J012b23b340 2001I214 IL-4 IL-13 j3 90 90 80- • 80 0 b 46 56 b 70 20mj PDGFR8 c TGFB1 D 90- 80- • 80- I.. 70-i.. 70-: 2001;l2O TNF E VEGE F 85 5.4 Lymphoid Follicle Burden 5.4.1 Comparison to Clinical and Histological Data U) a) 0 0 U- -o 0 0 E >‘ -J > > In the lymphoid follicles, the PM burden had no significant difference across the COPD severity groups (Figure 33). Non-smoking controls were not included in because they were not present in these patients and the analysis was limited to those cases that had one follicle or more. Figure 33 Vv of PM in the lymphoid follicles across COPD severity groups 7 6 5 4 3 2 0— Vv of PM in the lymphoid follicles can also be correlated with the clinical data and histological analysis (Table 10 and Figure 34). .1 Smoking GOLD 1 COPD GOLD 2 GOLD 3+4 Severity 86 Table 10 Correlation of the PM burden in the lymphoid follicles with clinical and histological values ClinicallHistological Parameters r2 Slope p-value FEV1/FVC 0.04 -0.04 0.35 FEV1 0.07 0.04 0.22 Lm 0.0006 -0.004 0.34 Airway thickness 0.02 0.02 0.07 Age 0.02 0.05 0.80 Pack Years 0.01 0.02 0.90 87 Figure 34 Vv of PM in lymphoid follicles A) vs. FEV1IFVC B) vs. FEy1 C) vs. Lm D) vs. airway wall thickness E) vs. age F) vs. pack years 15- 15 10 :.H.; 20 30 40 50 60 70 80 90 100110120130140 10 20 30 40 50 60 70 80 90 100 110 120 FEV1/FVC A FEV1 B 15- u_10_ a • 5 .. . —. 0- •• . .• 0 I I 150 200 250 300 350 400 450 500 50 100 150 200 250 Ln, C AW Thickness D 15- IS 10- 10 :-:•. 40 45 50 55 60 65 70 75 80 -20 0 20 40 60 80 100 120 140 160 Age Pack Years When the Vv of PM in the lymphoid follicles was compared to the blood vessel wall area and Vv of PM in the blood vessels, it had an r2 value of 0.008 and a negative slope (-0.02) (p 0.67) (Figure 35A) and an r2 value of 0.05 and a negative slope (-0.70) 88 (p = 0.31) (Figure 35B), respectively. When the Vv of PM in the lymphoid follicles was compared to the Vv of PM in the parenchyma and in all tissue, it had an r2 value of 0.002 and a negative slope (-21.55) (p = 0.82) (Figure 35C) and ar2 value of 0.001 and a negative slope (-15.15) (p = 0.87) (Figure 35D), respectively. Figure 35 Vv of PM in the lymphoid follicles vs. A) blood vessel thickness, B) Vv of PM in the blood vessel wall, C) Vv of PM in the parenchyma, and B) Vv of PM in all tissue. s. . ID. Q. • I 20 ID 4:: SI fl 71) IIC c -(I 01 0 01 02 0 04 uS (11 (17 ujii P.q10tJ,-.i . A C I I 1 2 ;i 4 5 %P M Mti 5, — — • I I I I I III 0 01 (12 (lI 04 (15 0i 07 0 B D 89 5.5 Alveolar Macrophage Burden 0 G) (U -c 0 0 C) CU (U 0 G) > 0 ‘S > > 5.5.1 Comparison to Clinical and Histological Data In the alveolar macrophages, the PM burden in the alveolar macrophages showed a significant difference (p = 0.0075, Tukey-Kramer) between the non-smoking and GOLD 1 groups when compared to the GOLD 2 group (Figure 36). Figure 36 Vv of PM in alveolar macrophages across the non-smoking and COPD severity groups 0.35 0.30 0.25 0.20 0.15 0.10 0.05 0.00 The Vv of PM in the alveolar macrophages can also be correlated with the clinical data and histological analysis (Table 11). The Vv of PM against FEV1/FVC had an Non-smoking Smoking GOLD 1 GOLD 2 GOLD 3+4 COPD Seventy 90 value of 0.065 and a negative slope (-0.0002) (p = 0.04) (Figure 37A). The Vv of PM against pack years had an r2 value of 0.24 and a positive slope (0.003) (p <0.01) (Figure 37F). Table 11 Correlation of the PM burden in the alveolar macrophages with clinical and histological values Clinical/Histological Parameters r2 Slope p-value FEV1/FVC 0.07 -0.0002 0.04 FEV1 0.01 -0.0009 0.34 Lm 0.004 0.0002 0.63 Airway thickness 0.02 0.000 1 0.16 Age 0.04 0.003 0.10 Pack Years 0.24 0.003 < 0.01 91 Figure 37 Vv of PM in alveolar macrophages A) vs. FEV1IFVC B) vs. FEy1 C) vs. Lm D) vs. airway wall thickness E) vs. age. F) vs. pack years 0.9- 0.8- 0.8 0.7- 0.7 0.6- • 0.6 0.5 0.4- GA a 0.3 0.3 0- P.. •. 0 — • •. ••S ..... I I I ‘•‘‘ I I I I 20 30 40 50 60 70 80 90 100110120130140 10 20 30 40 50 60 70 80 90 100 110 120 FEV1iFVC A FEV1 B 0.9 0.8- 0.8 07- • 0.7 0.6- • 0.6 04’ 0.3- . . 0.3 • • 0.2- . . . . 0.2’ • . • — 0.1 - 0.1 . • •. . . 0- —. :. . • . 0’ ?.. —0.1- 1 I 150 200 250 300 350 400 450 500 50 100 150 200 250 Lm C AW Thkness D 0.9- 0.8- 0.8 0.7- 0,7 0.6- • 0.6 ______ I I I 40 45 50 55 60 65 70 75 80 -20 0 20 40 60 80 100 120 140 160 Age E PacII Years F 92 5.6 Raman Spectroscopy The Raman spectra showed peaks at 1320 nm and 1590 nm, and also smaller peaks at 2622 nm and 2638 nm (Figure 38). Figure 38 Raman spectra of Case 1984 4000 ‘ 3000 D >, U) C . 2000 C C U) E 1000 D (‘3 I— 1. —1000 I 0 500 1000 1500 2000 2500 3000 3500 4000 Raman Wavelength (nm) 93 6 Chapter Six: Discussion and Conclusion 6.1 PM Burden in the Lung 6.1.1 All Tissue The data showed an incremental increase in PM retained in the lung tissues as COPD severity increases, except in the very severe cases (GOLD 3&4). The amount of PM retained in the lungs seems to plateau off in the severe cases (Figure 18). The bulk of this PM was retained in lung parenchyma, but PM was also retained in blood vessel walls, submucosal tissues, and lymphoid tissues as well as in airway macrophages. GOLD 2 had the highest levels of PM retained in the lung and reached up to 2% of the lung tissues. The reason why the Vv of PM retained in lung tissues decreases in GOLD 3 and 4 groups is unclear. Recent studies from our lab have shown significant lost in lung tissues with progression in COPD specifically in GOLD 3&4 cases. The lung tissues that disappear are specifically small airways and lung parenchyma. This possibly could have happened via apoptosis of lung cells with progression of the disease. It is reasonable to postulate that the tissues with high levels of PM retention are preferentially vulnerable to apoptosis and subsequently lost. With obliteration of the small airways, for example, there may be nothing left for the PM to deposit onto. These findings are novel as there are no studies to our knowledge that have used this technique to quantify the burden of PM in COPD. It is clear from the current data that PM can be deposited or translocated to virtually all compartments of the lung, including the parenchyma, blood vessels, alveolar macrophages, and lymphoid follicles. What is not clear, however, is how long the PM 94 resides in these different compartments and the relative contributions of retained PM in each of the compartments to the documented chronic lung inflammation in There was a positive correlation between lung function data (FEy1 and FEV1/FVC) and the total burden of PM in the lung. These associations fit the hypothesis by suggesting that as the particle burden increases, the lung function decreases. However, these associations were weak and suggest that PM retention in the lung tissues is just one of the potential factors that contribute to the decrease of lung function in COPD. There are potentially multiple pathways between the amount of PM deposited and retained in the lung and the eventual decline in lung function. Future studies could look at the retention of PM in specific compartments (small airways, for example) and alteration of lung function to determine if the location of PM deposition and retention is the determining factor for loss of lung function. Fibrinogen expression in the parenchyma correlated with the PM burden in the lung (Figure 21). Circulating fibrinogen in the blood has been shown to be elevated in the blood stream when subjects have been exposed to ambient air pollution21’and this increased fibrinogen has been implicated in cardiovascular deaths.212 During moderate to severe exacerbations of COPD, fibrinogen levels in the blood have been shown to be elevated.213 Smoking has also been shown to increase the levels of circulating fibrinogen214.My data is the first to suggest that there is activation of fibrinogen production in the lung tissues with an increasing PM-burden in the parenchyma of the lungs. 95 6.1.2 Alveolar Wall The burden of PM in the alveolar wall showed a very similar trend to that of the PM burden in all compartments of the lung, which suggests that most of the PM is being deposited in the parenchyma. This phenomenon could be due to the fact that the greatest tissue volume compartment in the lung is the parenchyma. This predominant deposition of PM in the lung alveolar wall suggests that the majority of PM that is retained in the lung is of smaller size, because it is these smaller particles that have the ability the reach the alveolar spaces. Alternatively, it could also imply that the clearance of PM from the alveolar spaces is not as good as from the airways. There was a significant correlation between PM burden and lung function and pack years of cigarette smoking as already demonstrated in the total lung burden analysis suggesting cigarette smoking significantly contribute to the burden of PM retention in lung alveolar wall. The only mRNA expression data that correlated with PM-burden in the alveolar wall was also FGG, similar to the total lung burden (Figure 25). 6.1.3 Blood Vessels Particulate matter retained in blood vessel walls was predominantly found in the adventitial layer and not in the muscle layer of vessels. The exact location of retained PM in the adventitia is unclear from the histological sections, but it is reasonable to postulate that the particles could be in lymphoid ducts in the adventitial layer seeing that the lymph ducting of the blood vessels is one of the paths of transport for particles. However, 96 further studies are needed to identify their location in vessel walls, specifically in the adventitia layer. Smokers with normal lung function (GOLD 0) have lower levels of PM in vessel walls than smokers with COPD (GOLD 2 group, Figure 26). Interestingly, the relatively large amount of PM found in the blood vessels of non-smokers was similar to smokers with normal lung function (smoking controls). This suggests environmental sources of PM exposure contribute significantly to PM retention in the lungs of normal non-smokers and potentially contribute evenly to the lung burden of PM in non-smokers and smokers alike. The PM burden in the blood vessels more strongly correlates with lung function (FEV1/ VC) than total lung or alveolar wall PM burden do. Generally considered to be an alternate hypothesis for systemic inflammation, the PM has, in at least one study,’8° been shown to translocate via the blood vessels into the bloodstream. There was no correlation with the PM burden found in the blood vessel wall and RNA expression in lung tissues. However, there was some correlation between mRNA expression and blood vessel wall thickness. IL-4 seems to be inversely correlated with blood vessel wall thickness. IL-4 acts by increasing the vascular permeability215 and could promote PM deposition in blood vessel wall via this fashion. TGF-131 expression increases as the blood vessel wall thickness decreases, which may point to a potential apoptotic pathway activated by TGF-3l. The trend for other pro-inflammatory mediators, such as, PDGF3, TNF-a, and VEGF, were also to be higher when vessel walls are thinner. The reason for this inverse relationship between RNA expression of pro inflammatory mediators and thin vessel walls is unclear and needs further investigation. 97 6.1.4 Lymphoid Follicles There seems to be no significant change in the PM burden in the lymphoid follicles between groups. This result may be due to the low number of lymphoid follicles found in the smoking and COPD cases. There were also no correlations between PM burden in the lymphoid follicles and the clinical or histological data, as well as, the mRNA expression. There also seems to be no relationship between the deposition of PM in the lymphoid follicles and the deposition elsewhere in the lung, such as the parenchyma and blood vessels. 6.1.5 Alveolar Macrophages There seems to be no discemable trend in PM burden in the alveolar macrophages across COPD seventies. There is a significant but weak correlation with pack years, which is likely due to a rich smoking history; there is no mRNA expression data that correlates with this data. 6.2 Raman Spectroscopy The Raman spectra showed a pair of peaks that is similar to the spectrum of graphite carbon. Carbon has a number of Raman spectra depending on the bonding of the molecules (diamond only has one peak). The study by Battonneau et al.21° found that carbonaceous soot had a Raman spectrum with peaks at 1324 nm and 1582 nm, which is 98 very nearly the same peaks as found by our experiments. This finding suggests that what is left in the lung is merely the carbon core alone and any other inorganic compounds or metals may have long since been processed or dissolved. What these results also show is that this spectral analysis can be successfully used in the in situ environment. With relatively little background noise, the presence of carbon or other elements with a Raman spectrum can be visualized, without a large degree of processing to separate out the PM from the tissue. The benefit of a lack of processing keeps the PM as close to the original form before sectioning, reducing the steps that may cause a potential loss of PM- associated agglomerates. Unfortunately, there are downsides to Raman spectroscopy. Firstly, the process is not the best for working backwards. More specifically, the process is best used after mass spectroscopy to confirm the presence of certain elements. In addition, not all elements have a Raman spectra, so if some heavy metals were indeed present, this process alone would not discover them. Finally, in this process, it is difficult to say what compartment the PM is coming from, whether it is from the blood vessels, the parenchyma, or airways, because the tissue is unstained and the imaging system does not have a particularly high resolution. Future directions for this technique can be to expand the number of cases to compare the composition between COPD severity groups. Other chemical composition techniques, such as GC-MS, could be done and the results compared. In addition, results obtained after removing the tissue to separate the PM could be compared with the in situ results to see if there is any difference in composition using different techniques. 99 6.3 Conclusion The results from this study show that PM is retained in the lungs of normal non smokers, smokers with normal lung function and COPD patients. In fact, with the exception of GOLD 3/4 patients, there is a graded increase in PM retention between these groups. It is not clear from this study how and by what mechanism the PM are deposited or retained in the lung. It seems as if PM can be found in virtually every tissue compartment of the lung; however, the majority of resides in the parenchyma. Interestingly, those that do not smoke also had significantly observable amounts of PM in their lung tissues, which suggests that PM from other sources, such as the environment, contributes to the PM burden in the lung of smokers and non-smokers. The role of PM deposition and retention in perpetuating lung inflammation and its role in the systemic inflammatory response associated with COPD remains unclear from the results of this study. Future studies would benefit from looking at the expression of genes implicated in COPD by looking at the exact location of the PM retention using Laser Capture Microdissection. Whether or not the inhibition of the clearance of PM from the lung due to COPD is the major contributing factor to an increasing PM burden in lung tissues is unclear from our data. The significant burden of PM in normal non smokers suggests that at least part of the PM retained is due to the magnitude of exposure and not due to the lung disease per Se. Our studies suggest that the PM retained in the lung does elicit an ongoing inflammatory response, but these studies need to be expanded to determine which inflammatory pathways (Figure 1 and 6) are predominantly involved Compositional analysis of retained PM suggests that carbon is the major component of the PM in lung tissues. In controlled animal and human studies, carbon 100 black has been shown to elicit both a local inflammatory response in the lung as well as a systemic inflammatory response. 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Apr 1 2003; 170(7): 3835-3842. 114 Appendix Table 12 List of Abbreviations Abbreviation Full Title AM Alveolar macrophage ATS American Thoracic Society AUI Arbitrary units of intensity BAL Bronchial Alveolar Lavage BOLD Burden of Obstructive Lung Disease Initiative CAREX Carcinogen Exposure COPD Chronic Obstructive Pulmonary Disease cDNA Copy DNA DNA Deoxyribonucleic acid DALYS Disability Adjusted Life Years ETS Environmental tobacco smoke EGF Epidermal growth factor ENA-78 Epithelial cell-derived neutrophil-activating peptide-78 ELF Epithelial lining fluid ERS European Respiratory Society ECM Extracellular Matrix FGF Fibroblast growth factor FEV1 Forced Expiratory Volume in 1 second FVC Forced Vital Capacity GOLD Global Initiative Chronic for Obstructive Lung Diseases GM-C SF Granulocyte-macrophage colony stimulating factor GRO-a Growth-related onocogene-aipha H&E Hematoxylin and Eosin HO-i Heme-oxygenase- 1 HNF Holographic notch filter HIV Human Immunodeficiency Virus ICAM- 1 Inter-cellular adhesion molecule-i IFN Interferon IL Interleukin ILO International Labour Organization LCM Laser capture micro dissection Latin American Project for the Investigation of Obstructive Lung PLATINO Disease LIF Leukemia inhibatory factor MMP Matrix Metalloproteinase mRNA Messenger RNA mEPHX Microsomal epoxide hydrolase MCP- 1 Monocyte chemoattractant protein-i NE Neutrophil Elastase NO Nitric oxide 115 Abbreviation Full Title NF-kB Nuclear Factor kappa-light-chain-enhancer of activated B-cells NA Numerical aperture OR Odds ratio OCT Optimal cutting temperature PM Particulate matter PA}Ts Polyaromatic hydrocarbons PMN Polymorphonuclear Leukocytes qPCR Quantitative polymerase chain reaction ROS Reactive oxygen species ROFA Residual oil fly ash RNA Ribonucleic acid SOP Standard operating procedure 3 -D Three-dimensional TSP Total suspended particles TGFB1 Transforming Growth Factor Beta-i TB Tuberculosis TNFa Tumour Necrosis Factor alpha 2-D Two-dimensional VEGF Vascular endothelial growth factor Vv Volume fraction 116

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