EINDRAPPORT FIJN STOF Steunpunt milieu

 EINDRAPPORT FIJN STOF Steunpunt milieu‐ en gezondheid Lotte Jacobs, Jan Emmerechts, Tim Nawrot, Benoit Nemery en het milieu‐ en gezondheidsconsortium
TABLE OF CONTENTS INTRODUCTION 1 PARTICULATE MATTER AIR POLLUTION 3 EFFECTS OF PM EXPOSURE 6 MECHANISMS 10 SUSCEPTIBLE POPULATIONS 14 AIMS 16 CHAPTER 1 25 Air pollution‐related prothrombotic changes in persons with diabetes 25 CHAPTER 2 49 Traffic air pollution and oxidized LDL 49 CHAPTER 3 67 Air pollution‐associated procoagulant changes: role of circulating microvesicles 67 SAMENVATTING 96 INLEIDING 97 BELANGRIJKSTE RESULTATEN 97 EVALUATIEVRAGEN 10
LIST OF ABBREVIATIONS 95% CI 95% confidence interval ACE‐inhibitor Angiotensin‐converting enzyme ACS American Cancer Study a.d. Aerodynamic diameter ASHMOG Adventist Health Study of Smog APHEA Air Pollution and Health: A European Approach APHENA The Air Pollution and Health: A Combined European and North American Approach BMI Body‐mass index CAC Coronary artery calcification CAPs Concentrated ambient particles CIMT Carotid intima‐media thickness CO Carbon monoxide CRP C‐reactive protein DEP Diesel exhaust particles EDTA Ethylenediaminetetraacetic acid FVC Forced vital capacity HDL High‐density lipoprotein HRV Heart rate variability Il‐6 Interleukin‐6 iNOS Inducible nitric oxide synthase IQR Interquartile range LDL Low‐density lipoprotein MESA Multi‐Ethnic Study of Atherosclerosis NMMAPS National Morbidity and Mortality Air Pollution Study NH3 Ammonia NO Nitric oxide NO2 Nitrogen dioxide NOx Nitrogen oxides O3 Ozone Oxy‐PAH Oxygenated polycyclic aromatic hydrocarbons PAI‐1 Plasminogen activator inhibitor 1 PFA‐100 Platelet Function Analyzer‐100 PM Particulate matter PM0.1 Particulate matter with an aerodynamic diameter smaller than 0.1 µm PM2.5 Particulate matter with an aerodynamic diameter smaller than 2.5 µm PM2.5‐10 Particulate matter with an aerodynamic diameter between 2.5 µm and 10 µm PM10 Particulate matter with an aerodynamic diameter smaller than 10 µm ROS Reactive oxygen species SD Standard deviation SEM Standard error of mean SO2 Sulphur dioxide TSP Total suspended particles UFP Ultrafine particles VOCs Volatile organic compounds INTRODUCTION Introduction 3 PARTICULATE MATTER AIR POLLUTION Air pollution consists of particulate matter (PM) and gaseous pollutants, like nitrogen dioxide (NO2), carbon monoxide (CO), sulphur dioxide (SO2), and ozone (O3). PM air pollution is a complex mixture of solid and liquid particles, suspended in air, which can be inhaled into the lungs. PM is usually categorized according to the size of its aerodynamic diameter (a.d.): PM10 (thoracic particles with a.d < 10 µm), PM2.5 (fine particles with a.d < 2.5 µm), PM0.1 (ultrafine particles with a.d. <0.1 µm). The coarse fraction of PM is defined as all particles between 2.5 and 10 µm (PM2.5‐10).1 Sources Coarse particles are derived mainly from suspension of dust, soil or other crustal material. Fine particles are derived from direct emissions of combustion processes. They also consist of transformation products which are formed of gaseous emissions, like ammonia (NH3), nitrogen oxides (NOx), SO2 or volatile organic compounds (VOCs). Ultrafine particles originate from combustion processes such as vehicle exhaust. They have a very short life and rapidly form aggregates. Inhalation of particles Deposition Inhaled particles can be deposited in various regions of the respiratory tract, depending on primarily the particle diameter, but also on size distribution, shape, charge, density and hygroscopicity. There are five different mechanisms by which particle deposition can occur within the respiratory tract: impaction, sedimentation, diffusion, interception and electrostatic precipitation. In most cases, only impaction, sedimentation and diffusion play an important role.2‐4 4 
Introduction Impaction Impaction occurs when the inhaled particles have enough momentum to keep their trajectory despite changes of the air stream, thereby impacting on airway surfaces. The larger the particle, the more likely it will be deposited by impaction. Impaction is the principal mechanism for deposition of particles having a diameter between a few micrometers and 100 µm.4 The most likely deposition sites are in the upper airways and at or near the large airway bifurcations.2,3 
Sedimentation Sedimentation is a time‐dependent process, in which the particles settle due to gravity. Mainly particles having a diameter between 0.1 and 50 µm undergo sedimentation.4 It is an important mechanism for deposition in the smaller bronchi, the bronchioles and the alveolar spaces, where airways are small and air velocity is low.2,3 
Diffusion Diffusion occurs when particles are small enough to undergo a random motion (Brownian motion) due to molecular bombardement.2 Diffusional deposition is important in small airways and alveoli and at bifurcations for particles smaller than 0.5 µm.3,4 Retention and clearance Retention of particles starts with their wetting and their subsequent displacement from the air into the aqueous phase by surfactant. In general microparticles (0.5‐10 µm) remain on the epithelial surface in airways and alveoli. The retention time depends on the deposition site and on the interaction of the particles with the lung surface. This surface consists of a liquid lining layer (surfactant film and an aqueous phase beneath it), mobile cells (resident airway macrophages submersed in the aqueous phase), the epithelium and the subepithelial connective tissue (containing blood and lymphatic vessels). For particles deposited in the conducting airways, the retention time is Introduction 5 short, because of efficient mucociliary and cough clearance, but the time increases with increasing airway generation number.5 Particles can be cleared from the lungs via two distinct mechanisms: 
Mucociliary transport One of the most important clearance mechanisms is the production of bronchial secretions and the transport of these secretions from the peripheral airways to the oropharynx. Ciliated cells are found in the airways from the trachea to the terminal bronchioles. Mucus is transported by coordinated beating of the cilia.5,6 
Airway macrophages Luminal airway and alveolar macrophages (surface macrophages) are located on the inner surface of the lungs, beneath the surfactant film, close to the air‐liquid interface and are immersed in the aqueous lung lining layer. They are primarily derived from the bone marrow (via blood). Their primary function is the clearance of particles, including microorganisms, by phagocytosis. The clearance time for the particles within macrophages can be weeks to months in the alveolar region. Particle‐laden macrophages can be cleared through mucociliary transport.7,8 Studies in humans show that a fraction of the inhaled particles can be retained for months.9 Studies investigating occupational exposure (mining) found that particles in lung macrophages can be detected months and even years after exposure has ended.10,11 A transplantation study shows that the cytoplasm of lung macrophages contained inclusion bodies characteristic of smokers 2 years after a transplantation from a heavy smoker (donor) into a non‐smoker.12 The capacity of airway macrophages to phagocytose and store particles can thus be used as an indicator for chronic, individual exposure to PM air pollution. A study in children showed that the percentage of particle‐containing airway macrophages was greater in children who lived near a major road.13 The surface area of carbon within airway macrophages, determined by light microscopy, was higher in Ethiopian women and children exposed to biomass smoke, 6 Introduction compared to UK adults.14 Also, a positive association was found between yearly exposure to PM10 and the amount of carbon in airway macrophages, obtained from children by sputum induction.15 EFFECTS OF PM EXPOSURE Short‐term effects Both time‐series studies and case‐crossover studies have shown effects of short‐term exposure to PM on mortality. Time‐series studies evaluate changes in daily mortality counts associated with daily changes in air pollution levels. One of the largest multicity time‐series studies is the National, Morbidity, Mortality and Air Pollution Study (NMMAPS).16 The effect of air pollutants on daily mortality in the 20 largest cities and metropolitan areas in het United States, between 1987 and 1994, was assessed. Each increase in PM10 by 10 µg/m³ was associated with an increase in all‐cause mortality of 0.51 % and 0.68 % for mortality due to cardiovascular and respiratory causes. A second large study was carried out in a population of more than 43 million people living in 29 European cities, the Air Pollution and Health: A European Approach 2 (APHEA‐2) project.17 The estimated increase in daily numbers of deaths was 0.6 %, for an increase in PM10 by 10 µg/m³. For each 10 µg/m³ increase in PM10, the estimated increase in deaths due to cardiovascular disease and respiratory disease was 0.76 % and 0.58 %, respectively.18 The Air Pollution and Health: A Combined European and North American Approach (APHENA) study brought together data from NMMAPS, APHEA‐2 and Canadian studies, showing an effect of PM on all‐cause mortality, ranging from 0.2 % to 0.6 %, for an increase in daily PM10 by 10 µg/m³, with the largest effects in Canada. In Flanders, increases in PM10 were also found to be associated with daily mortality, but with much stronger Introduction 7 associations in summer than in winter.19 Other multicity time‐series studies show similar effects of PM exposure on all‐cause, cardiovascular and respiratory mortality.20‐23 Another, newer method to study mortality effects of daily changes in particulate air pollution is the case‐crossover design, which is characterized by the fact that each subject serves as his own control.24,25 Schwartz26 analyzed data from 14 U.S. cities and found an increase in daily mortality of 0.36 % for each increase in PM10 by 10 µg/m³. Another case‐crossover analysis of 27 communities, between 1997 and 2002, showed a significant effect of an increase in PM2.5 of 10 µg/m³ on all‐cause mortality (1.21 %).27 These studies show small, but consistent effects of short‐term changes in PM on daily mortality, especially from cardiovascular causes.28 Long‐term effects Two important prospective cohort studies investigating the mortality effects of long‐term PM exposure are the Harvard Six Cities study29 and the American Cancer Study (ACS)30. The Six Cities Study followed up 8111 adults over 14 to 16 years. PM was associated with increases in both all‐
cause mortality and in mortality from cardiopulmonary diseases. The excess mortality risk was 26 %, comparing the most polluted city with the least polluted city. The second study used data from the ACS, Cancer Prevention Study II, of more than 500,000 adults who were followed prospectively from 1982 through 1989. Significant associations were observed between PM2.5 and cardiopulmonary mortality and lung cancer mortality. When follow up time was doubled to more than 16 years results show that each increase in PM2.5 by 10 µg/m³ was associated with an increased risk of 4 % in all‐cause mortality, 6 % in cardiopulmonary mortality and 8 % in lung cancer mortality.31 The Adventist Health Study of Smog (AHSMOG)32 studied air pollution‐related mortality in more than 6,000 non‐smoking adults from California . PM10 was significantly associated with all‐cause 8 Introduction mortality and mortality due to nonmalignant respiratory disease and lung cancer, in males but not in females. Further analyses showed stronger associations with PM2.533 and found significant associations between PM and fatal coronary heart disease, among females, but not males.34 In the Women’s Health Initiative Observational Study, 65,893 postmenopausal women without prior cardiovascular disease were followed‐up. A 10 µg/m³ increase in PM2.5 was associated with an increase in both nonfatal (24 %) and fatal (76 %) cardiovascular events.35 In another cohort36, a subset of the Nurses’ Health Study of more than 66,000 women, an increase in 12‐month average exposure to PM10 of 10 µg/m³ was associated with an increase in all‐cause mortality of 7 % and an increase in fatal coronary heart disease of 30 % in fully adjusted models. Several other cohort in both the U.S and Europe also assess the association between long‐term exposure to PM and mortality (Table 1).37‐42 Other cohort studies use distance from the residence to a major road as marker for traffic‐
related exposure and found significant associations with mortality. A Dutch cohort study43 in 5,000 persons, showed that living near a major road was significantly associated with an increase in cardiopulmonary mortality. Analysis of the full cohort (in 120,852 persons) showed smaller effect estimates between cause‐specific mortality and traffic variables.37 Finkelstein et al.44 found that persons living within 50 meters of a major road or within 100 meters of a highway had an increased risk in all‐cause mortality (RR: 1.18, 95% CI:1.02 to 1.38). A study in approximately 4800 German women, found that living within 50 meters of a major road (defined as roads with at least 10,000 cars per day) was associated with increased cardiopulmonary mortality [RR: 1.70 (95% CI:1.02 to 2.81)].40 Maheswaran et al.45 reported an increase in stroke mortality of 5 % for persons living within 200 meters of the nearest main road, compared with persons living more than 1000 meters from the nearest main road. Overall evidence from the different cohorts shows that levels of PM2.5 are in general positively associated with mortality, especially from cardiopulmonary or cardiovascular causes. Introduction 9 Table 1: Summary of cohort study results (% increase in relative risk) % increase (95% CI) in mortality Study Size of cohort Follow‐up period Exposure increment Harvard six cities study, Dockery et al.29 1993 8,111 1976‐1989 American Cancer Study, Pope et al.30 1995 552,138 Adventist Health Study of Smog, Abbey et al.32 1999 All‐cause mortality Cardiovascular mortality 10 µg/m³ PM2.5 13 (4 to 23) 18 (6 to 32) 1982‐1989 10 µg/m³ PM2.5 7 (4 to 10) 12 (7 to 17) (cardiopulmonary) 6,338 1977‐1992 PM10 above 100 µg/m³ (43d/y) 12 (1‐24) ‐ Women’s Health Initiative Observational Study, Miller et al.35 2007 65,893 1994‐1998 10 µg/m³ PM2.5 ‐ 76 (25‐147) Nurses’ Health Study, Puett et al.36 2008 66,250 1992‐2002 10 µg/m³ PM10 7 (‐3 to 18) 30 (1‐71) 11 California counties, Enstrom et al.38 2005 35,789 1973‐2002 10 µg/m³ PM2.5 1973‐1983: 4 (1 to 7) ‐ 1973‐2002: 1(‐0.6 to 2.6)
14,284 1974‐2000 10 µg/m³ TSP 5 (2 to 8) 6 (1‐12) (cardiopulmonary) German women, Gehring et al.40 2006 4,752 1980s, 1990s‐2003 10 µg/m³ PM10 8 (‐6 to 25) 34 (6 to 71) U.S. veteran cohort study Lipfert et al.41 2006 28,635 1997‐2001 10 µg/m³PM2.5 6 (‐6 to 22) ‐ 143,842 1992‐1998 Quartile increase in PM2.5 ‐ Men: 10 (5 to 16) Women: 4 (6 to 21) Dutch cohort, 120,852 Beelen et al.37 2008 1987‐1996 10 µg/m³ PM2.5 6 (‐3 to 16) 4 (‐10 to 21) 7 French cities, Filleul et al.39 2005 Oslo, Norway, Naess et al.42 2007 10 Introduction MECHANISMS There are three main mechanisms through which particles can have effects on the cardiovascular system (Figure 1). Particles can have effects through either direct translocation to the circulation, or through effects on the autonomic nervous system, caused by particulate interactions with lung receptors. More indirect effects can occur due to particle‐induced pulmonary inflammation and oxidative stress, which can lead to systemic inflammation.46,47 Figure 1: Pathophysiological mechanisms of lung‐ and circulation‐mediated cardiovascular toxicity of particulate air pollutants (from Simkhovich et al.48 with permission). Introduction 11 Pulmonary inflammation/oxidative stress Inhalation of particles causes proinflammatory responses in human lungs49,50 and in animal models51,52, in part because of the production of reactive oxygen species (ROS). The pulmonary inflammation causes the release of inflammatory mediators that can contribute to systemic inflammatory responses, through stimulation of the bone marrow and release of leukocytes and platelets into the circulation.53 This hypothesis is strengthened by observations from epidemiological studies, showing significant associations between ambient PM and increases in blood leukocytes, circulating interleukin‐6 (Il‐6) and C‐reactive protein (CRP), all markers of systemic inflammation.54 Particle‐induced inflammatory responses and increased oxidative stress could also play a role in the development and progression of atherosclerosis, as observed in both experimental and epidemiological studies. Sun et al.55 exposed apoliprotein E deficient mice to low concentrations of PM2.5 or to filtered air during 6 months. Mice fed with high fat chow and exposed to PM2.5 developed a larger composite plaque area than mice (on high fat chow diet) exposed to filtered air. Other experiments in apolipoprotein E deficient mice showed that they developed larger atherosclerotic plaques in response to a 75 hour (over 40 days) exposure to ultrafine particles in comparison with exposure to PM2.5 or filtered air.56 The first epidemiological evidence for effects of PM air pollution on atherosclerosis in humans comes from Kunzli et al.57. In almost 800 subjects from two randomized clinical trials, an association between carotid initma‐media thickness (CIMT) and annual PM2.5 was found. They also showed in a follow‐up study, that the progression of atherosclerosis (indicated as a change in CIMT) was associated with exposure to air pollution.58 Hofmann et al.59 showed that subjects living closer to a major road, had a higher risk of having a high coronary artery calcification (CAC), a marker of atherosclerosis. Atherosclerosis is the key underling pathology of cardiovascular diseases and multiple risk factors can play a role in the development of atherosclerosis. High cholesterol, and more specific high low‐density lipoprotein (LDL)‐cholesterol, is one of the primary risk factors for atherosclerosis. 12 Introduction But is has become clear that inflammatory processes also play a major role in the development of atherosclerosis. The initial step in the atherosclerotic process is endothelial dysfunction, which leads to the retention of lipids in the intimal layer. Further oxidative modification of LDL is a key step. Oxidized LDL can be internalized by macrophages leading to the formation of foam cells, with the release of inflammatory mediators. These inflammatory processes will eventually lead to proliferation of smooth muscle cells, stiffening of the arterial wall and calcification of the plaque.60,61 Imbalance of autonomic nervous system Heart rate variability (HRV), resting heart rate and blood pressure are modulated by the autonomic nervous system, via a balance between the sympathetic and the parasympathetic nervous system. Decreased HRV is known to increase the risk of cardiovascular morbidity and mortality, especially in the elderly and those with heart disease.62 Overall, studies have shown decreases in HRV in response to ambient PM exposure.63‐65 The interaction of particles with receptors in the lungs might have an effect on the autonomic nervous system, decreasing parasympathetic input to the heart. Through this mechanism, particles can also affect blood pressure, leading to adverse cardiovascular outcomes.66 However, epidemiological evidence linking ambient PM to blood pressure changes is still limited and inconclusive.67‐69 It is well established that high blood pressure is a primary risk factor for the development of cardiovascular disease such as ischemic heart disease and cerebrovascular accidents. Further it has become clear that, especially in elderly, the difference between systolic blood pressure and diastolic blood pressure (= pulse pressure) is an important predictor of myocardial infarction and stroke.70 Large artery changes result in arterial stiffening and a loss of vascular compliance, thereby reducing the buffering capacity of the arterial system, causing a progressive rise in systolic pressure with age, accompanied by a fall in diastolic pressure and a widening in pulse pressure. Increased pulse Introduction 13 pressure is therefore indicative of large artery disease and is also associated with increased cardiovascular risk.71 Translocation A third mechanism through which inhaled particles can have effects on the cardiovascular system is direct translocation to the systemic circulation. Evidence for this pathway is provided by experimental studies in animals52,72, while evidence for translocation in humans is less clear73,74. Possibly, particles in the circulation can interact with vascular endothelium and blood platelets, which might explain the observed associations between particulate exposure and enhanced platelet activity as shown by studies in both animals and humans. Nemmar et al.75 showed in a hamster model that 30 minutes after intratracheal instillation with diesel exhaust particles (DEP), increased platelet activation was apparent. Moreover, the direct addition of 0.5 µg/mL of DEP to hamster blood in vitro, caused platelet activation within 5 minutes. A controlled exposure study in humans also gives evidence for enhanced platelet activation in response to exposure to DEP. Inhalation of diesel exhaust was associated with larger changes in both in vivo platelet activation and ex vivo thrombus formation, compared to inhalation of filtered air.76 Platelets play an important role in primary haemostasis. The haemostatic system in humans maintains blood in a fluid state under physiological conditions, but reacts to vascular injury by two major pathways: the activation and aggregation of blood platelets (primary haemostasis) and the activation of the coagulation cascade (secondary haemostasis). When vessel injury occurs, circulating platelets bind to subendothelial collagen to form the primary haemostatic platelet plug. Activation of the coagulation cascade, further results in the formation of fibrin strands, which strengthens the platelet plug. Thrombosis occurs when there is a breakdown in the balance between thrombogenic factors and protective mechanisms. Activation of endothelium and increased platelet activity are 14 Introduction important prothrombotic factors.77 Platelets will especially be important in the formation of an arterial thrombus which can lead to cardiovascular ischemic events, such as myocardial infarction.78 SUSCEPTIBLE POPULATIONS Epidemiological research indicates that some populations are more susceptible for the effects of PM. Sacks et al.79 define susceptibility, relating to PM, as: ”Individual and population‐level characteristics that increase the risk of PM‐related health effects in a population including, but not limited to: genetic background, birth outcomes (e.g. low birth weight, birth defects), race, sex, lifestage, lifestyle (e.g. smoking status, nutrition), preexisting disease, socioeconomic status (e.g. educational attainment, reduced access to health care) and characteristics that may modify exposure to PM (e.g. time spent outdoors)”. Diabetes Type 1 diabetes results from autoimmune destruction of insulin‐producing β cells, which leaves the patient dependent on insulin injections for survival. Type 2 diabetes, formerly known as adult‐onset diabetes, occurs when impaired insulin effectiveness (insulin resistance) is accompanied by the failure to produce sufficient β cell insulin. Patients can be placed on regimens to reduce weight or manage diet or treated with medication and, less often, insulin injections. This latter form of diabetes accounts for as much as 95 % of cases. The burden of diabetes is to a large extent the consequence of macrovascular and microvascular complications of the disease, which result in large increases in morbidity and mortality.80 It is well established that persons with diabetes have a higher risk of developing cardiovascular disease. For example, the prevalence of ischemic heart disease is 2–14 times the rate in age‐matched nondiabetics.81 Both atherosclerosis and thrombosis could contribute Introduction 15 to this increased risk.82,83 The abnormal metabolic state in diabetes can cause arterial dysfunction. These abnormalities include chronic hyperglycemia, dyslipidemia and insulin resistance, which makes arteries susceptible to atherosclerosis. Diabetes can alter the functioning of endothelial cells, smooth muscle cells and platelets. It has been shown that platelets in persons with diabetes have a disordered calcium haemostasis, which may contribute to abnormal platelet activity. Moreover, these platelets also show an increased surface expression of glycoprotein Ib, important in the interaction between platelets and von Willebrand factor and glycoprotein IIb/IIIa, which mediates platelet‐fibrin interaction. These mechanisms may explain the enhanced thrombotic characteristic of diabetes.84 As reported earlier, PM also can have effects on these processes of thrombosis and atherosclerosis, which might explain the enhanced susceptibility of persons with diabetes to PM. Epidemiological research shows that the association between PM exposure and hospital admissions for cardiac disease is stronger in patients with diabetes.85 Associations between mortality and exposure to PM2.5, was stronger among patients with diabetes who also had cardiovascular disease.86 Effects of ambient PM on markers of systemic inflammation seemed to be stronger in individuals with diabetes.54 16 Introduction AIMS Exposure to both recent and chronic air pollution has adverse effects on cardiovascular morbidity. We hypothesized that the observed effects of PM on the cardiovascular system might involve prothrombotic, proinflammatory, proatherosclerotic and prohypertensive mechanisms. We selected subgroups, which are more susceptible (patients with diabetes and elderly persons) or more exposed (cyclists) to PM air pollution to test this hypothesis. 
In a cross‐sectional study in patients with diabetes we investigated the effects of recent and chronic exposure to PM air pollution on platelet function, blood leukocyte counts and plasma levels of oxidized LDL to test the hypothesis that PM could have effects on thrombotic and atherosclerotic processes. We used the amount of carbonaceous particles, phagocytosed by airway macrophages to accurately estimate a person’s individual exposure to PM air pollution. 
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(56) Araujo JA, Barajas B, Kleinman M et al. Ambient particulate pollutants in the ultrafine range promote early atherosclerosis and systemic oxidative stress. Circ Res. 2008;102:589‐596. (57) Kunzli N, Jerrett M, Mack WJ et al. Ambient air pollution and atherosclerosis in Los Angeles. Environ Health Perspect. 2005;113:201‐206. (58) Kunzli N, Jerrett M, Garcia‐Esteban R et al. Ambient air pollution and the progression of atherosclerosis in adults. PLoS One. 2010;5:e9096. Introduction 21 (59) Hoffmann B, Moebus S, Stang A et al. Residence close to high traffic and prevalence of coronary heart disease. Eur Heart J. 2006;27:2696‐2702. (60) Libby P. Inflammation in atherosclerosis. Nature. 2002;420:868‐874. (61) Ross R. Atherosclerosis‐an inflammatory disease. N Engl J Med. 1999;340:115‐126. (62) Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology. Heart rate variability: standards of measurement, physiological interpretation and clinical use. Circulation. 1996;93:1043‐1065. (63) Park SK, Auchincloss AH, O'Neill MS et al. Particulate air pollution, metabolic syndrome, and heart rate variability: the multi‐ethnic study of atherosclerosis (MESA). Environ Health Perspect. 2010;118:1406‐1411. (64) Schwartz J, Litonjua A, Suh H et al. Traffic related pollution and heart rate variability in a panel of elderly subjects. Thorax. 2005;60:455‐461. (65) Pope CA III, Verrier RL, Lovett EG et al. Heart rate variability associated with particulate air pollution. Am Heart J. 1999;138:890‐899. (66) Sesso HD, Stampfer MJ, Rosner B et al. Systolic and diastolic blood pressure, pulse pressure, and mean arterial pressure as predictors of cardiovascular disease risk in men. Hypertension. 2000;36:801‐807. (67) Choi JH, Xu QS, Park SY et al. Seasonal variation of effect of air pollution on blood pressure. J Epidemiol Community Health. 2007;61:314‐318. (68) Linn WS, Gong H Jr, Clark KW, Anderson KR. Day‐to‐day particulate exposures and health changes in Los Angeles area residents with severe lung disease. J Air Waste Manag Assoc. 1999;49:108‐115. (69) Madsen C, Nafstad P. Associations between environmental exposure and blood pressure among participants in the Oslo Health Study (HUBRO). Eur J Epidemiol. 2006;21:485‐491. (70) Franklin SS, Larson MG, Khan SA et al. Does the relation of blood pressure to coronary heart disease risk change with aging? The Framingham Heart Study. Circulation. 2001;103:1245‐
1249. (71) Williams B, Lindholm LH, Sever P. Systolic pressure is all that matters. Lancet. 2008;371:2219‐
2221. (72) Oberdörster G, Sharp Z, Atudorei V et al. Extrapulmonary translocation of ultrafine carbon particles following whole‐body inhalation exposure of rats. J Toxicol Environ Health A. 2002;65:1531‐1543. (73) Mills NL, Amin N, Robinson SD et al. Do inhaled carbon nanoparticles translocate directly into the circulation in humans? Am J Respir Crit Care Med. 2006;173:426‐431. 22 Introduction (74) Nemmar A, Hoet PH, Vanquickenborne B et al. Passage of inhaled particles into the blood circulation in humans. Circulation. 2002;105:411‐414. (75) Nemmar A, Hoet PH, Dinsdale D, Vermylen J, Hoylaerts MF, Nemery B. Diesel exhaust particles in lung acutely enhance experimental peripheral thrombosis. Circulation. 2003;107:1202‐1208. (76) Lucking AJ, Lundback M, Mills NL et al. Diesel exhaust inhalation increases thrombus formation in man. Eur Heart J. 2008;29:3043‐3051. (77) Colman RW, Hirsh J, Marder VJ, Salzman EW. Hemostasis and thrombosis. Basic Principles and Clinical Practice. Third ed. 1994. (78) Willoughby S, Holmes A, Loscalzo J. Platelets and cardiovascular disease. Eur J Cardiovasc Nurs. 2002;1:273‐288. (79) Sacks JD, Stanek LW, Luben TJ et al. Particulate matter‐induced health effects: who is susceptible? Environ Health Perspect. 2011;119:446‐454. (80) Permutt MA, Wasson J, Cox N. Genetic epidemiology of diabetes. J Clin Invest. 2005;115:1431‐1439. (81) Engelgau MM, Geiss LS, Saaddine JB et al. The evolving diabetes burden in the United States. Ann Intern Med. 2004;140:945‐950. (82) Colwell JA, Nesto RW. The platelet in diabetes: focus on prevention of ischemic events. Diabetes Care. 2003;26:2181‐2188. (83) Colwell JA. Multifactorial aspects of the treatment of the type II diabetic patient. Metabolism. 1997;46:1‐4. (84) Beckman JA, Creager MA, Libby P. Diabetes and atherosclerosis: epidemiology, pathophysiology, and management. JAMA. 2002;287:2570‐2581. (85) Zanobetti A, Schwartz J. Cardiovascular damage by airborne particles: are diabetics more susceptible? Epidemiology. 2002;13:588‐592. (86) Goldberg MS, Burnett RT, Yale JF, Valois MF, Brook JR. Associations between ambient air pollution and daily mortality among persons with diabetes and cardiovascular disease. Environ Res. 2006;100:255‐267. (87) Goldberg MS, Burnett RT, Bailar JC III et al. The association between daily mortality and ambient air particle pollution in Montreal, Quebec. 1. Nonaccidental mortality. Environ Res. 2001;86:12‐25. (88) Samoli E, Peng R, Ramsay T et al. Acute effects of ambient particulate matter on mortality in Europe and North America: results from the APHENA study. Environ Health Perspect. 2008;116:1480‐1486. Introduction 23 (89) Anderson HR, Atkinson RW, Bremner SA, Marston L. Particulate air pollution and hospital admissions for cardiorespiratory diseases: are the elderly at greater risk? Eur Respir J Suppl. 2003;40:39s‐46s. (90) Pope CA III, Renlund DG, Kfoury AG, May HT, Horne BD. Relation of heart failure hospitalization to exposure to fine particulate air pollution. Am J Cardiol. 2008;102:1230‐
1234. (91) Larrieu S, Jusot JF, Blanchard M et al. Short term effects of air pollution on hospitalizations for cardiovascular diseases in eight French cities: the PSAS program. Sci Total Environ. 2007;387:105‐112. (92) Devlin RB, Ghio AJ, Kehrl H, Sanders G, Cascio W. Elderly humans exposed to concentrated air pollution particles have decreased heart rate variability. Eur Respir J Suppl. 2003;40:76s‐80s. (93) Gong H, Linn WS, Terrell SL et al. Exposures of elderly volunteers with and without chronic obstructive pulmonary disease (COPD) to concentrated ambient fine particulate pollution. Inhal Toxicol. 2004;16:731‐744. (94) Fung KY, Luginaah I, Gorey KM, Webster G. Air pollution and daily hospitalization rates for cardiovascular and respiratory diseases in London, Ontario. Int J Environ Stud. 2005;62:677‐
685. (95) Int Panis L, de Geus B, Vandenbulcke G et al. Exposure to UFP and PM in traffic: a comparison of cylists and car drivers. Atmospheric Environment. 2010;44:2263‐2270. (96) Zuurbier M, Hoek G, van den Hazel P, Brunekreef B. Minute ventilation of cyclists, car and bus passengers: an experimental study. Environ Health. 2009;8:48. (97) Peters A, von Klot S, Heier M et al. Exposure to traffic and the onset of myocardial infarction. N Engl J Med. 2004;351:1721‐1730. (98) McCreanor J, Cullinan P, Nieuwenhuijsen MJ et al. Respiratory effects of exposure to diesel traffic in persons with asthma. N Engl J Med. 2007;357:2348‐2358. (99) Strak M, Boogaard H, Meliefste K et al. Respiratory health effects of ultrafine and fine particle exposure in cyclists. Occup Environ Med. 2010;67:118‐124. (100) Zuurbier M, Hoek G, Oldenwening M, Meliefste K, van den Hazel P, Brunekreef B. Respiratory effects of commuters' exposure to air pollution in traffic. Epidemiology. 2011;22:219‐227. CHAPTER 1 Air pollution‐related prothrombotic changes in persons with diabetes Lotte Jacobs, Jan Emmerechts, Chantal Mathieu, Marc F Hoylaerts, Frans Fierens, Peter H Hoet, Benoit Nemery, Tim S Nawrot Published in Environmental Health Perspectives 2010;118: 191‐6 Chapter 1 27 ABSTRACT Population studies suggest that persons with diabetes are more sensitive to the effects of particulate matter (PM) air pollution. However, the biological mechanisms of a possible prothrombotic effect underlying this enhanced susceptibility remain largely unknown. We hypothesized that exposure to PM causes prothrombotic changes in persons with diabetes, possibly via systemic inflammation. Our study included 137 nonsmoking adults with diabetes who were outpatients at the University Hospital Leuven. Recent exposure (2 hr before examination) to ambient PM was measured at the entrance of the hospital. Individual chronic exposure to PM was assessed by measuring the area occupied by carbon, in airway macrophages obtained by sputum induction. Platelet function was measured ex vivo with the PFA‐100 platelet function analyzer, which simulates a damaged blood vessel; we analyzed the function of platelets in primary hemostasis under high shear conditions. Total and differential blood leukocytes were counted. Independent of antiplatelet medication, an interquartile range (IQR) increase of 39.2 µg/m3 in PM10 (Pm with aerodynamic diameter ≤ 10 µm) concentration measured 2 hr before the clinical examination (recent exposure) was associated with a decrease of 21.1 seconds [95% confidence interval (CI), ‐35.3 to ‐6.8] in the PFA‐100 closure time (i.e., increased platelet activation) and an increase in blood leukocytes of 512 per microliter of blood (95% CI, 45.2 ‐ 979). Each area increase of 0.25 µm2 (IQR) in carbon load of airway macrophages (chronic exposure) was associated with an increase of 687 leukocytes per microliter of blood (95% CI, 224 – 1,150). A relevant increase in recent PM exposure was associated with a change in platelet function toward a greater prothrombotic tendency. The magnitude of the change was about two‐thirds (in the opposite direction) of the average effect of antiplatelet medication. Diabetic patients showed evidence of proinflammatory response to both recent and chronic exposure to PM air pollution. 28 Chapter 1 INTRODUCTION Urban pollution, especially by particulate matter (PM), contributes to respiratory and cardiovascular morbidity and mortality.1‐4 To a large extent, the increase in mortality linked to PM ≤ 10 µm in aerodynamic diameter (PM10) is attributable to cardiovascular diseases.2,5 Persons with diabetes, who also have cardiovascular disease, appear to be more sensitive to the effects of air pollution on daily mortality.6 Zanobetti and Schwartz7 also found stronger associations between increased levels of PM and hospitalizations for heart disease among those who had diabetes compared with those who did not. The risk of coronary heart disease, stroke and peripheral arterial disease is increased in persons with diabetes.8,9 Both atherosclerosis and thrombosis appear to contribute to this increased cardiovascular risk.10,11 Therefore, research on environmental factors that may aggravate the disease, and on the mechanisms underlying this, has substantial public health relevance. One of the problems in epidemiological studies is estimating individual exposure to PM. In this study, the chronic exposure to PM was estimated at an individual level by determining the carbon load of airway macrophages, as described by Kulkarni et al.12. This approach is based on the fact that airway macrophages are the primary phagocytotic cells of inhaled PM. The amount of carbonaceous PM extracted from the lung at autopsy reflects the chronic exposure PM.13 We hypothesized that exposure to PM causes prothrombotic changes in persons with diabetes, possibly via systemic inflammation. METHODS Study population Persons with both type 1 and type 2 diabetes were consecutively recruited from the diabetes outpatient clinic at the University Hospital Leuven. Chapter 1 29 This clinic is a dedicated clinic for the routine 3‐ to 6‐ month follow‐up of patients with diabetes. All patients were invited to participate on days when the investigator was present. They were included if they were ≥ 18 years of age and were non‐smokers. The study was carried out on different days from February 2007 through September 2008. On the study day, patients completed a questionnaire to obtain information on age, occupation, socioeconomic status, exposure to environmental tobacco smoke, alcohol use, use of medication, use of oral contraception, menopausal status, place of residence and means of transportation to the hospital. Socioeconomic status was coded and condensed into a scale with scores ranging from 1 to 3. Use of antiplatelet medication was coded as use of either none or one (or more) of the following substances: acetylsalicylic acid, clopidogrel, ticlopidine or dipyridamole. Distances from the home address to major roads were calculated through geocoding. Living close to a major road was defined as living within 100 m of a N‐road or an E‐road.14 Of the 186 recruited subjects, 137 (74%) took part in the examination (Figure 1). The 49 patients that did not participate, had the same age and sex distribution as the 137 participants. Sufficient numbers of airway macrophages to assess the area occupied by carbon were obtained from 80 of the 119 patients (18 of the 137 patients failed to produce sputum). A blood sample could not be obtained from 11 subjects, and platelet function analysis was not successful in 28 subjects. Ultimately, 63 subjects had data for both the carbon load of airway macrophages and the platelet function analysis. The Ethics Review Board of the Medical Faculty of the University of Leuven approved the study. Participants gave informed consent at recruitment. 30 Chapter 1 225 patients contacted
39 excluded (17%)
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186 fulfilled inclusion criteria (83%) 9 pregnant (23%) 30 smokers (78%) 137 participated 49 refused (74%) (26%) Blood sample 126 (92%) PFA: 98 (78%) Sputum sample: 119 (87%) Carbon load: 80 (67%) Figure 1: Flowchart of study population, consecutively recruited from the diabetes outpatient clinic at the University Hospital Leuven. Patients were included if they were ≥ 18 years of age and non‐smokers; 63 subjects had data on both platelet function (measured by PFA‐100 platelet function analyzer) and carbon load of airway macrophages. Exposure assessment Ambient PM Recent exposure A portable laser‐operated aerosol mass analyzer (Aerocet 53; Met One Instruments Inc, Grants Pass, OR, USA) was used to measure PM2.5 (PM with an aerodynamic diameter of ≤ 2.5 μm) and PM10 concentrations two hr before the patient’s participation in the study. The device had been previously calibrated against a local monitoring station (Flemish Environmental Agency, Borgerhout, Chapter 1 31 Antwerp). The PM concentrations were measured both outside, at the entrance of the hospital, and inside, in the waiting room. Modeled PM10 We calculated the regional background level of PM10 (previous day, week, month, 3 months, 6 months and annual average) for each participant’s home address using a kriging interpolation method.15 This model provides interpolated PM10 values from the Belgian telemetric air quality networks in 4 x 4 km grids. The interpolation was based on a detrended kriging interpolation model that uses landcover data obtained from satellite images (Corine landcover dataset).16 Internal PM Carbon load of airway macrophages obtained by induced sputum To induce sputum, nebulized saline (NaCl 3 %, 4 % or 5 %) was administered through an ultrasonic nebulizer (Ultra‐NebTm2000 model 200HI; De Vilbiss Healtcare, Somerset, PA, USA) in one, two or three 7‐minute inhalation periods. Patients were pretreated with an inhaled β2‐agonist (200 µg Salbutamol). Pulmonary function was measured before each inhalation period for the detection of clinically significant bronchoconstriction.17 To isolate airway macrophages, induced sputum was processed according to a standard technique.18 Dithiothreitol (Sigma Aldrich, St.Louis, Mo, USA) was used as a mucolytic agent, and airway cells were cytocentrifuged (Cytospin, Shandon Scientific, Techgen, Zellik, Belgium) onto glass slides and stained with Diff‐Quick (Medion Diagnostics, Düdingen, Germany). Sputum supernatants were kept at ‐80°C for future analysis. Airway macrophages (Figure 2) were visualized by light microscopy (AxioPlan 2 Imaging, Zeiss, Zaventem, Belgium). Each airway macrophage was initially processed using Paint shop software (version 5.1; Microsoft, Zaventem Belgium). First, the nucleus was removed from the image. Then Scion image software (Scion Corporation, Frederick, MD, USA) was used to calculate the carbon load of airway 32 Chapter 1 macrophages, which was defined as the median area (square micrometers) occupied by carbon, in 50 randomly selected macrophages per patient.12,19 Figure 2: Airway macrophages with no (left), medium (middle) and high (right) carbon load. Airway macrophages were obtained by induced sputum, stained with Diff‐Quik, and viewed with light microscopy. The area occupied by carbon in 50 randomly selected airway macrophages was determined by means of 2
image analysis and the median area (µm ) per cell was calculated. Bar = 20 µm. Clinical measurements Blood collection and analysis A nonfasting blood sample was collected in an EDTA tube and in a tube containing 0.129 M (3.8 %) sodium citrate for platelet function analysis and for differential cell counts, respectively. Blood cell counts (including platelet counts) and differential leukocyte counts were determined using an automated cell counter with flow differential (Cell Dyn 3500, Abbott Diagnostics, Abott Park, IL USA). Blood glucose levels and glycated hemoglobin were measured according to standard clinical procedures. Plasma samples were kept frozen at ‐80°C for future analysis. Platelet Function Analyzer Platelet function was assessed with the PFA‐100 platelet function analyzer (Siemens Healthcare Diagnostics, Deerfield, IL, USA). The PFA‐100 test cartridge consists of a capillary, a blood Chapter 1 33 sample reservoir and a membrane coated with collagen/epinephrine with a central aperture. Whole blood is aspirated through the capillary and the aperture, thus exposing platelets to high shear rates (5,000/sec) and to collagen and epinephrine, causing platelet activation. A platelet thrombus forms at the aperture, thus gradually diminishing and finally arresting blood flow. The time from the start of aspiration until the aperture completely occludes, that is the closure time, reflects platelet aggregation in a shear stress‐dependent way.20 Statistical analysis For database management and statistical analysis, we used SAS software (version 9.1; SAS Institute Inc., Cary, NC, USA). For comparison of means, medians and proportions we applied the Student t‐
test, Wilcoxon test and the chi‐square‐statistic, respectively. We investigated associations between markers of exposure (ambient PM10, PM2.5 and carbon load of airway macrophages) and different endpoints (platelet function, total and differential leukocyte counts, platelet counts) using multiple linear regression. We report results of unadjusted analysis (in figures), results adjusted for age, and results of fully adjusted models. For fully adjusted models covariates were identified by a stepwise regression procedure with the p‐values for variables to enter and to stay in the model set at 0.10. Covariates considered for entry in the model were age, sex, body‐mass index (BMI), socioeconomic status, outdoor temperature, time in traffic on the day of the examination, means of transportation to examination, time in hospital before blood draw, hour of blood draw, use of alcohol, exposure to environmental tobacco smoke, blood glucose level, glycated haemoglobin, menopausal status, oral contraception, use of statins, use of angiotensin‐converting–enzyme (ACE) inhibitors and use of antiplatelet medication. The possible effect modification of type of diabetes on the associations was studied. Regardless of the p‐value, the type of diabetes was forced into the regression models. In a sensitivity analysis we ran a model in which age, sex, BMI and hour of blood draw were further forced into the models. Further, we calculated partial Spearman rank correlation coefficients for non‐
34 Chapter 1 normally distributed variables. Q‐Q plots of the residuals were used to test the assumptions of all linear models. RESULTS Characteristics of study participants We found no major differences between the total group of participants (n=137) and those that had a complete set of measurements (PFA‐100 and carbon load, n=63) (Table 1). In those who consumed alcohol, the median alcohol consumption was 10 g per day [interquartile range (IQR), 22.5 g/day]. Forty women (63 %) reported menopause, and eight (13 %) used oral contraceptives. Among men, 29 (40 %) had type 1 diabetes compared with 31 (48 %) of the women. All patients with type 1 diabetes used insulin, whereas 77 persons (92%) of patients with type 2 diabetes used insulin medication. Eighty patients had with important underlying cardiovascular disease. We found no significant differences in the demographic variables or in the distance from the hospital to the patient’s residence (32.7 vs 30.4 km, p = 0.57) between patients for whom we obtained sufficient numbers of airway macrophages (n = 80) and those for whom we did not (n = 57). Outdoor mean ± SD PM10 measured at the entrance of the hospital on the day of the patient’s visit averaged 56.1 ± 29.0 µg/m3 and the average indoor PM10 concentration measured in the waiting room was 36.6 ± 18.4 µg/m3. Transportation to the hospital was by car for 87 % of the patients and by public transport (bus) for 13 %. The average distance from the patient’s home address to the hospital was 31.3 km (range, 0.7 ‐ 139 km). The corresponding travel time was 26.2 minutes (range, 1 ‐97 minutes). Chapter 1 35 Table 1. Patient characteristics Anthropometrics Total Group (n=137) Group with carbon load and PFA‐100 (n=63) Sex, women 64 (47 %) 35 (56 %) 54.7 (14.4) 51.5 (14.5) Body‐mass index, kg/m 28.4 (5.4) 28.0 (5.2) Type 1 diabetes 60 (44 %) 29 (46 %) Blood glucose, mg/dL 145 (71.9) 151.7 (72.7) Glycated hemoglobin, % 7.4 (1.0) 7.4 (1.1) Lifestyle Regular alcohol use 36 (26 %) 18 (29 %) Exposure to environmental tobacco smoke 27 (20 %) 10 (16 %) Socioeconomic status Low 79 (58 %) 32 (51 %) Middle 44 (32 %) 21 (33 %) High 14 (10 %) 10 (16 %) Use of medication Antiplatelet medication 82 (60 %) 34 (54 %) Statins 88 (64 %) 37 (59 %) ACE inhibitor 60 (44 %) 21 (33 %) Insulin 130 (95 %) 61 (97 %) Antidiabetic medication 50 (36 %) 21 (33 %) 25.1(18.4) 23,7 (16.0) 56.1 (29.0) 53.2 (24.8) Age, years 2
Exposure markers 3 Recent (2 hours) outdoor PM2.5, µg/m
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Six‐month average modeled PM10, µg/m Carbon load in airway macrophages, µm 25.3 (3.7) 25.4 (3.9) 0.19 (0.09‐0.34) 0.20 (0.10‐0.34) Endpoints 2
PFA‐100 closure time, s
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Blood platelets, x10 /µL a
b
140 (47.9) 144 (50.4) c
6010 (2134) c
3706 (1371) 6152 (2027) 3826 (1378) c
164 (138) c
420 (157) c
1170 (739) c
232 (62.4) 169 (163) 417 (151) 1783 (697) 232 (60) Values are number (%) or arithmetic mean (SD), except for the carbon load, which was not normally distributed, for which the median (IQR) is given. Antiplatelet medication included acetylsalicylic acid, clopidogrel, ticlopidine or dipyridamole. a
Data available for 80 subjects, bData available for 98 subjects, cData available for 126 subjects. 36 Carbon load of airway macrophages Chapter 1 The carbon load of airway macrophages did not correlate with age or BMI. We found no significant difference in carbon load of macrophages between men and women. Carbon load in macrophages was not associated with the recent outdoor or indoor PM10. However persons living near a major road (< 100 m) had higher carbon load than did those living farther from a major road (0.29 vs 0.17 µm2; p =0.04). Each increase in modeled 6‐month average PM10 at the participant’s residence was associated with an increase in the carbon load of airway macrophages (r = 0.30, p = 0.008), confirming that carbon load is a good marker of chronic exposure to PM. Platelet function The PFA‐100 closure time was 30.4 seconds [95% confidence interval (CI), 12.3 ‐ 48.5, p = 0.001] higher in patients on antiplatelet therapy than in those not taking antiplatelet medication (n = 55). None of the other studied potential covariates, including hour of blood draw, number of platelets, outdoor temperature and travel time to the hospital, entered the stepwise regression model. Both before adjustment (Figure 3) and after adjustment (Table 2) for the use of antiplatelet medication, the closure time was inversely associated with the recent outdoor PM measured 2 hr before the examination, but not with indexes of chronic exposure. The interaction terms between use of antiplatelet medication and exposure to PM did not reach statistical significance (p ≥ 0.17). We observed no association between the closure time and the carbon load (chronic exposure). In a model, combining recent exposure to PM10 and carbon load of airway macrophages (Table 3), the recent exposure remained negatively associated with the closure time. Forcing age, sex, BMI and hour of blood draw into the stepwise regression models did not alter the reported findings significantly. Chapter 1 37 Recent exposure
A r = -0.24
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Figure 3: Left panels show Pearson correlations between recent exposure (PM10 measured at the study site 2 hr before clinical examination) and platelet function (A) or blood leukocyte counts (C). Right panels show Spearman rank correlations between chronic exposure (as assessed by the carbon load of airway macrophages) and platelet function (B) or blood leukocyte counts (D). Platelet function was assessed by PFA‐
100; decreases in closure time reflect platelet activation (i.e. a prothrombotic tendency). 38 Total and differential blood leukocyte counts Chapter 1 In a stepwise multiple regression, the number of blood leukocytes was significantly higher in persons with type 2 diabetes than in those with type 1 diabetes (767 /µL; 95% CI; 77 – 1,456, p = 0.03), and increased with blood glucose (4.5 /µL per mg/dL glucose; 95% CI ‐0.3 to 9.4, p = 0.07). Both before adjustment (Figure 3) and after adjustment (Table 2) for these covariates, the number of leukocytes correlated positively both with recent exposure and with carbon load of airway macrophages. Even in a model that combined recent exposure to PM10 and chronic exposure (Table 3), as assessed by the carbon load of macrophages, the chronic exposure remained positively associated with the total number of leukocytes. The blood lymphocyte counts showed stronger associations with the carbon load of airway macrophages than with recent exposure to PM10, whereas blood neutrophils were only marginally associated with the carbon load but significantly with recent exposure (Table 2). This was also the case in the combined analysis (Table 3). We observed no significant changes in blood eosinophils and monocytes (data not shown). In further analyses, we studied the associations between platelet function and total blood leukocyte counts. Number of leukocytes was not associated with platelet function, even not after adjusting for the carbon load of airway macrophages. Forcing age, sex, BMI and hour of blood draw into the stepwise regression models did not alter the reported findings significantly. Blood platelet counts We found no association between blood platelets and markers of recent exposure to PM (Table 2). The carbon load was marginally associated with the number of blood platelets (Table 2). In a model (Table 3) with both recent (PM10) and chronic exposure (carbon load), only the chronic exposure was associated with number of blood platelets. Forcing age, sex, BMI and hour of blood draw into the stepwise regression models did not alter the reported findings significantly. Table 2. Change in platelet function and in total or differential blood leukocyte counts and platelet counts for an interquartile range (IQR) increase in recent outdoor PM2.5 or PM10 concentrations or in carbon load of airway macrophages (separate analysis) Endpoint PFA‐100 closure time, s Exposure marker, IQR PM2.5, 22.3 µg/m3 PM10, 39.2 µg/m3 2 Carbon load, 0.25 µm
Total blood leukocyte counts, /µL PM2.5, 22.3 µg/m
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3 3
PM10, 39.2 µg/m 2
Carbon load, 0.25 µm Age‐adjusted difference (95%CI)a ‐12.4 (‐25.8 to 1.0) P‐value 0.07 Difference (95% CI)a ‐16.3 (‐29.0 to ‐3.7) P‐value 0.01 ‐19.0 (‐34.1 to ‐3.8) 0.02 ‐21.1 (‐35.3 to ‐6.8) 0.005 3.2 (‐12.7 to 19.1) 0.69 3.8 (‐11.8 to 19.5) 0.63 544 (104 to 983) 0.02 451 (40.5 to 860) 0.03 577 (79.8 to 1,075) 0.02 512 (45.2 to 979) 0.03 760 (290 to 1,230) 0.002 687 (224 to 1,150) 0.005 318 (18.4 to 618) 0.04 278 (‐2.25 to 558) 0.05 378 (40.4 to 716) 0.03 360 (42.8 to 668) 0.03 353 (33.1 to 673) 0.03 294 (‐20.0 to 609) 0.07 196 (35.7 to 356) 0.02 147 (‐1.0 to 294) 0.05 160 (‐23.5 to 343) 0.09 110 (‐60.1 to 280) 0.21 199 (46.5 to 351) 0.01 221 (72.2 to 370) 0.005 ‐2.7 (‐16.5 to 11.0) 0.70 ‐4.3 (‐17.3 to 8.8) 0.52 0.7 (‐14.9 to 16.2) 0.93 ‐0.7 (‐15.8 to 14.3) 0.92 13.0 (‐1.6 to 27.5) 0.09 14.1 (‐0.3 to 28.5) 0.06 Differences calculated for an IQR increase in exposure variables a
Adjusted for significant (P < 0.10) covariates (see text) identified by stepwise regression. Covariates considered for entry in the model were age, sex, BMI, socioeconomic status, outdoor temperature, time in traffic on day of exam, means of transportation to the exam, time in hospital before blood draw, hour of blood draw, use of alcohol, exposure to environmental tobacco smoke, blood glucose level, glycated hemoglobin, menopausal status, oral contraception, use of statins, use of ACE‐inhibitors and use of antiplatelet medication. Type of diabetes was forced into all models. Table 3. Change in platelet function and total or differential blood leukocyte counts and platelet counts for an interquartile range (IQR) increase in recent outdoor PM10 concentrations and in carbon load of airway macrophages (combined analysis) Endpoint PFA‐100 closure time, s Exposure marker, IQR PM10, 39.2 µg/m3 Age‐adjusted difference (95%CI)a ‐18.8 (‐38.4 to 0.75) P‐value 0.06 Difference (95%CI)a ‐25.4 (‐44.4 to ‐6.3) P‐value 0.01 Carbon load, 0.25 µm2 2.1 (‐13.5 to 17.7) 0.79 2.8 (‐12.2 to 17.7) 0.72 770 (249 to 1,291) 0.005 737 (239 to 1,236) 0.005 806 (356 to 1,255) 0.0008 747 (303 to 1,190) 0.002 462 (102 to 821) 0.01 451 (109 to 793) 0.01 381 (70.4 to 691) 0.02 331 (26.5 to 635) 0.04 245 (75.4 to 414) 0.006 220 (58.0 to 382) 0.01 213 (67.3 to 360) 0.006 242 (97.9 to 386) 0.002 9.2 (‐7.7 to 26.1) 0.29 8.8 (‐7.6 to 25.1) 0.30 13.5 (‐1.1 to 28.1) 0.07 14.7 (0.29 to 29.2) 0.05 Total blood leukocyte counts, /µL 3
PM10, 39.2 µg/m
2
Carbon load, 0.25 µm Neutrophils, /µL 3
PM10, 39.2 µg/m
2
Carbon load, 0.25 µm Lymphocytes, /µL PM10, 39.2 µg/m
2
Carbon load, 0.25 µm 3
Platelets, x10 /µL 3
3
PM10, 39.2 µg/m
2
Carbon load, 0.25 µm Differences calculated for an IQR increase in exposure variables. Table 3 differs from table 2 in that the recent and chronic exposure were analyzed separately in table 2 and combined in table 3. a
Adjusted for significant (P < 0.10) covariates (see text) identified by stepwise regression. Covariates considered for entry in the model were age, sex, BMI, socioeconomic status, outdoor temperature, time in traffic on day of exam, means of transportation to the exam, time in hospital before blood draw, hour of blood draw, use of alcohol, exposure to environmental tobacco smoke, blood glucose level, glycated hemoglobin, menopausal status, oral contraception, use of statins, use of ACE‐inhibitors and use of antiplatelet medication. Type of diabetes was forced into all models. Chapter 1 41 Sensitivity analyses Calculation of partial Spearman rank correlation coefficients for non‐normally distributed variables confirmed our results (data not shown). We studied possible effect modification of type of diabetes on the associations. The interaction term did not reach statistical significance in any of the models (p>0.20). Models in which we replaced the carbon load of airway macrophages with the modeled 6‐
month average PM air pollution near the patient’s home (4 x 4 km grid), showed no significant correlation with the studied effect parameters. DISCUSSION We observed that PM exposure appears to have a rapid prothrombotic effect on platelet function. Recent and chronic exposures to PM were associated with markers of systemic inflammation, seen as an increase in blood leukocyte counts. However, we found no association between the observed prothrombotic effect and markers of systemic inflammation. Currently, it is well recognized that thrombosis underlies most acute complications of atherosclerosis, such as acute myocardial infarction. Peters et al.21 showed that exposure to elevated concentrations of fine PM (PM2.5) for as little as 2 hr increases the risk of myocardial infarction. Long‐term exposure to PM has also been suggested to play a role in the underlying pathologic process, atherosclerosis.14,22,23 The purpose of our study was not to show that persons with diabetes are more susceptible to the effects of PM air pollution, but to verify the hypothesis that PM causes prothrombotic changes in these presumably more susceptible subjects, possibly via systemic inflammation. Therefore, in the present study we combined personal markers of recent exposure (PM measured at the study site) and chronic exposure to PM as assessed by the carbon load of airway macrophages.12 42 Chapter 1 Platelet activation, measured ex vivo with the PFA, allows a quantitative measure of platelet aggregation as the time required to close a small aperture in a biological active membrane by relevant stimuli. The average PFA closure time in our well controlled diabetic population was comparable with the closure time in healthy subjects, reported in literature.24,25 Our study shows that the closure time correlated inversely with the ambient PM air pollution concentration, measured 2 hr before the blood collection. Previously, we showed in an experimental study that the intratracheal instillation of diesel exhaust particles (DEP) in hamsters caused platelet activation within 1 hr and a dose‐dependent enhanced arterial or venous thrombus.26 Recently, Lucking et al.27 showed in a controlled exposure experiment, an association between enhanced thrombus formation ex viv and inhalation of DEP 2hr after exposure. The clinical significance of the association we observed between platelet activation measured ex vivo and air pollution stems from prospective observations that a shorter closure time of the PFA‐100 device predicts recurrent ischemic events in patients who underwent a percutaneous coronary intervention.28 In our study an IQR increase of 39.2 µg/m3 in PM10 was associated with a decrease in the PFA closure time of 25 sec. If we compare this with the average effect of antiplatelet medication, it appears that the magnitude of the pollution effect (‐25 sec) is about two‐thirds (in the opposite direction) of that caused by the antiplatelet medication (36 sec). Intake of a daily dose of 75 mg aspirin, during two weeks caused an increase in the median PFA closure time of 30 sec in 10 healthy individuals.29 Similarly, in a population of 34 patients with type 2 diabetes, the mean PFA closure time significantly increased by 57 sec after daily intake of 100 mg aspirin, during 1 week.30 We also documented systemic inflammatory effects, because we found a positive association between the number of blood leukocytes and both recent and chronic exposure to PM air pollution. Mukae et al.31 showed in rabbits that repeated exposure to ambient PM10 caused an accelerated release of immature polymorphonuclear leukocytes from the bone marrow. The magnitude of the stimulation of the bone marrow by PM10 was related to the quantity of particles phagocytosed by Chapter 1 43 alveolar macrophages. Our findings that the carbon load of airway macrophages is associated with increases in blood leukocytes are in line with these experimental findings. Long‐term changes in leukocyte counts in association with PM have also been investigated in human epidemiological studies. Recent observations of the Third National Health and Nutrition Examination Survey showed a positive association between chronic (1 year) exposure to PM10 and blood leukocyte counts.32 A study of 39 Japanese men traveling to Antarctica, an area with low exposure to PM, showed a 17% decrease in leukocyte counts.33 This study is novel in that it suggests that persons with diabetes, a condition associated with chronic inflammation, may have a short‐term inflammatory response to recent PM air pollution, in addition to the effect of chronic exposure as assessed by the carbon load of airway macrophages. In persons without diabetes, studies looking for short‐term changes in leukocyte counts in relation to air pollution have given inconclusive results. Two studies that reported significant results for leukocyte counts had opposite findings34,35 and other studies reported null associations36‐38. It has been shown that chronic inflammation is involved in the development of atherosclerosis.39 Chronic exposure to PM leading to systemic inflammation might therefore also play a role in the development of atherosclerosis. Exposing apolipoprotein E‐null mice for 6 months to an equivalent concentration of 15.2 µg/m3 PM2.5 over a lifetime, Sun et al.23 found that transverse sections of abdominal aorta increased in percentage plaque area compared with mice exposed to filtered air. Suwa et al.40 showed in rabbits that repeated exposure to PM10 was associated with both systemic inflammation and the progression of the atherosclerotic process, the extent of which correlated with the extent of PM10 phagocytosed by alveolar macrophages. Chronic inflammation is more prominent in type 2 diabetes than in persons with type 1 diabetes. However, we did not find evidence of a higher sensitivity to air pollution‐induced effects on platelet function or leukocyte distribution in persons with type 2 diabetes compared with their type 1 counterparts. O’Neill et al.41 found a stronger association between endothelial function and PM air pollution in type 2 compared 44 Chapter 1 with type 1 diabetes. In our study, patients had well‐controlled glycated haemoglobin levels, which averaged 7.4%. Moreover the insulin use in persons with type 2 diabetes was high. We did not observe a link between leukocyte counts and platelet activation. This suggests that PM may have effects on platelet function independently of systemic inflammation. In experimental conditions, using DEP, Nemmar et al.42 showed a prothrombotic tendency and activation of circulating blood platelets, as well as lung inflammation, which persisted up to 24 hr after instillation of DEP in hamsters. However the prothrombotic tendency observed 1 hr after DEP exposure did not appear to correlate with pulmonary inflammation.42 Our study has limitations. Observational studies do not prove causality, even when exposure is measured on an individual level. Recent exposure to PM was based on measurements at the hospital. We modeled PM data but had no personalized exposure measurements 24 hr before blood draw. The carbon load of airway macrophages may not reflect the load of carbon in more distal alveolar cells, because sputum induction samples macrophages from the larger airways.43 In adults, however, the distribution of PM from the environment in bronchial macrophages is nearly identical to that in alveolar macrophages.44,45 Our limited success rate of 58 % for sputum induction may have introduced bias, but we found no differences in any other measured variables between those from whom sputum was induced successfully and those from whom it was not. Because the method used to assess the carbon load of 50 airway macrophages per persons is labor intensive, our study sample did not include a very large number of participants, but this group size has been shown to be relevant when using this surrogate of personal exposure to PM.12 The carbon load in airway macrophages was associated with modeled six‐month average PM10 exposure at the patient’s home. However, the blood leukocyte counts were not significantly associated with the modeled 6‐month average PM10 concentration, although it was with the carbon load of airway macrophages. This suggests that the latter biomarker of chronic exposure might be a better reflection of personal exposure to PM. For the modeled previous day, week, month, 3‐month Chapter 1 45 and annual average PM10 at the patient’s residence, we found no correlations (p≥0.15) with the carbon load of airway macrophages. Our findings have important implications for understanding the biological mechanisms of air pollution on cardiovascular health and its clinical relevance, because both a prothrombotic tendency and systemic inflammation play an important role in atherosclerosis and cardiovascular disease. The clinical relevance of our findings in persons with diabetes is evident from the observation that a realistic increase in recent PM air pollution exposure was associated with a change in platelet function toward a greater prothrombotic tendency. The magnitude of this change was about two‐
thirds (in opposite direction) of the average effect of antiplatelet medication. 46 Chapter 1 REFERENCES (1) Dominici F, Peng RD, Bell ML et al. Fine particulate air pollution and hospital admission for cardiovascular and respiratory diseases. JAMA. 2006;295:1127‐1134. (2) Maitre A, Bonneterre V, Huillard L, Sabatier P, de Gaudemaris R. Impact of urban atmospheric pollution on coronary disease. Eur Heart J. 2006;27:2275‐2284. (3) Pope CA III, Burnett RT, Thun MJ et al. Lung cancer, cardiopulmonary mortality, and long‐
term exposure to fine particulate air pollution. JAMA. 2002;287:1132‐1141. (4) Simkhovich BZ, Kleinman MT, Kloner RA. Air pollution and cardiovascular injury epidemiology, toxicology, and mechanisms. J Am Coll Cardiol. 2008;52:719‐726. (5) Nawrot TS, Nemmar A, Nemery B. Air pollution: To the heart of the matter. Eur Heart J. 2006;27:2269‐2271. (6) Goldberg MS, Burnett RT, Yale JF, Valois MF, Brook JR. Associations between ambient air pollution and daily mortality among persons with diabetes and cardiovascular disease. Environ Res. 2006;100:255‐267. (7) Zanobetti A, Schwartz J. Cardiovascular damage by airborne particles: are diabetics more susceptible? Epidemiology. 2002;13:588‐592. (8) Brand FN, Abbott RD, Kannel WB. Diabetes, intermittent claudication, and risk of cardiovascular events. The Framingham Study. Diabetes. 1989;38:504‐509. (9) Stamler J, Vaccaro O, Neaton JD, Wentworth D. Diabetes, other risk factors, and 12‐yr cardiovascular mortality for men screened in the Multiple Risk Factor Intervention Trial. Diabetes Care. 1993;16:434‐444. (10) Colwell JA. Multifactorial aspects of the treatment of the type II diabetic patient. Metabolism. 1997;46:1‐4. (11) Colwell JA, Nesto RW. The platelet in diabetes: focus on prevention of ischemic events. Diabetes Care. 2003;26:2181‐2188. (12) Kulkarni N, Pierse N, Rushton L, Grigg J. Carbon in airway macrophages and lung function in children. N Engl J Med. 2006;355:21‐30. (13) Brauer M, Avila‐Casado C, Fortoul TI, Vedal S, Stevens B, Churg A. Air pollution and retained particles in the lung. Environ Health Perspect. 2001;109:1039‐1043. (14) Hoffmann B, Moebus S, Möhlenkamp S et al. Residential exposure to traffic is associated with coronary atherosclerosis. Circulation. 2007;116:489‐496. (15) Janssen S, Dumont G, Fierens F, Mensink C. Spatial interpolation of air pollution measurements using CORINE land cover data. Atmos Environ. 2008;42:4884‐4903. Chapter 1 47 (16) European Environment Agency. Corine Land Cover Project. http://www.eea.europa.eu . 2000. (17) Paggiaro PL, Chanez P, Holz O et al. Sputum induction. Eur Respir J Suppl. 2002;37:3s‐8s. (18) Pizzichini E, Pizzichini MM, Efthimiadis A, Hargreave FE, Dolovich J. Measurement of inflammatory indices in induced sputum: effects of selection of sputum to minimize salivary contamination. Eur Respir J. 1996;9:1174‐1180. (19) Kulkarni N, Prudon B, Panditi SL, Abebe Y, Grigg J. Carbon loading of alveolar macrophages in adults and children exposed to biomass smoke particles. Sci Total Environ. 2005;345:23‐30. (20) Kundu SK, Heilmann EJ, Sio R, Garcia C, Davidson RM, Ostgaard RA. Description of an in vitro platelet function analyzer‐‐PFA‐100. Semin Thromb Hemost. 1995;21 Suppl 2:106‐112. (21) Peters A, Dockery DW, Muller JE, Mittleman MA. Increased particulate air pollution and the triggering of myocardial infarction. Circulation. 2001;103:2810‐2815. (22) Künzli N, Jerrett M, Mack WJ et al. Ambient air pollution and atherosclerosis in Los Angeles. Environ Health Perspect. 2005;113:201‐206. (23) Sun Q, Wang A, Jin X et al. Long‐term air pollution exposure and acceleration of atherosclerosis and vascular inflammation in an animal model. JAMA. 2005;294:3003‐3010. (24) Homoncik M, Blann AD, Hollenstein U, Pernerstorfer T, Eichler HG, Jilma B. Systemic inflammation increases shear stress‐induced platelet plug formation measured by the PFA‐
100. Br J Haematol. 2000;111:1250‐1252. (25) Seyfert UT, Haubelt H, Vogt A, Hellstern P. Variables influencing MultiplateTM whole blood impedance platelet aggregometry and turbidimetric platelet aggregation in healthy individuals. Platelets. 2007;18:199‐206. (26) Nemmar A, Hoet PH, Dinsdale D, Vermylen J, Hoylaerts MF, Nemery B. Diesel exhaust particles in lung acutely enhance experimental peripheral thrombosis. Circulation. 2003;107:1202‐1208. (27) Lucking AJ, Lundback M, Mills NL et al. Diesel exhaust inhalation increases thrombus formation in man. Eur Heart J. 2008;29:3043‐3051. (28) Gianetti J, Parri MS, Sbrana S et al. Platelet activation predicts recurrent ischemic events after percutaneous coronary angioplasty: a 6 months prospective study. Thromb Res. 2006;118:487‐493. (29) Ahmed N, Meek J, Davies GJ. Plasma salicylate level and aspirin resistance in survivors of myocardial infarction. J Thromb Thrombolysis. 2009. (30) Abaci A, Yilmaz Y, Caliskan M et al. Effect of increasing doses of aspirin on platelet function as measured by PFA‐100 in patients with diabetes. Thromb Res. 2005;116:465‐470. 48 Chapter 1 (31) Mukae H, Vincent R, Quinlan K et al. The effect of repeated exposure to particulate air pollution (PM10) on the bone marrow. Am J Respir Crit Care Med. 2001;163:201‐209. (32) Chen JC, Schwartz J. Metabolic syndrome and inflammatory responses to long‐term particulate air pollutants. Environ Health Perspect. 2008;116:612‐617. (33) Sakai M, Sato Y, Sato S et al. Effect of relocating to areas of reduced atmospheric particulate matter levels on the human circulating leukocyte count. J Appl Physiol. 2004;97:1774‐1780. (34) Ghio AJ, Hall A, Bassett MA, Cascio WE, Devlin RB. Exposure to concentrated ambient air particles alters hematologic indices in humans. Inhal Toxicol. 2003;15:1465‐1478. (35) Schwartz J. Air pollution and blood markers of cardiovascular risk. Environ Health Perspect. 2001;109 Suppl 3:405‐409. (36) Holgate ST, Devlin RB, Wilson SJ, Frew AJ. Health effects of acute exposure to air pollution. Part II: Healthy subjects exposed to concentrated ambient particles. Res Rep Health Eff Inst. 2003;31‐50. (37) Pope CA III, Hansen ML, Long RW et al. Ambient particulate air pollution, heart rate variability, and blood markers of inflammation in a panel of elderly subjects. Environ Health Perspect. 2004;112:339‐345. (38) Seaton A, Soutar A, Crawford V et al. Particulate air pollution and the blood. Thorax. 1999;54:1027‐1032. (39) Ross R. Atherosclerosis‐‐an inflammatory disease. N Engl J Med. 1999;340:115‐126. (40) Suwa T, Hogg JC, Quinlan KB, Ohgami A, Vincent R, van Eeden SF. Particulate air pollution induces progression of atherosclerosis. J Am Coll Cardiol. 2002;39:935‐942. (41) O'Neill MS, Veves A, Zanobetti A et al. Diabetes enhances vulnerability to particulate air pollution‐associated impairment in vascular reactivity and endothelial function. Circulation. 2005;111:2913‐2920. (42) Nemmar A, Nemery B, Hoet PH, Vermylen J, Hoylaerts MF. Pulmonary inflammation and thrombogenicity caused by diesel particles in hamsters: role of histamine. Am J Respir Crit Care Med. 2003;168:1366‐1372. (43) Alexis NE, Hu SC, Zeman K, Alter T, Bennett WD. Induced sputum derives from the central airways: confirmation using a radiolabeled aerosol bolus delivery technique. Am J Respir Crit Care Med. 2001;164:1964‐1970. (44) Fireman EM, Lerman Y, Ganor E et al. Induced sputum assessment in New York City firefighters exposed to World Trade Center dust. Environ Health Perspect. 2004;112:1564‐
1569. (45) Lay JC, Bennett WD, Kim CS, Devlin RB, Bromberg PA. Retention and intracellular distribution of instilled iron oxide particles in human alveolar macrophages. Am J Respir Cell Mol Biol. 1998;18:687‐695.
CHAPTER 2 Traffic air pollution and oxidized LDL Lotte Jacobs, Jan Emmerechts, Marc F Hoylaerts, Chantal Mathieu, Peter H Hoet, Benoit Nemery, Tim S Nawrot Published in PLoS One 2011;6:e16200 Chapter 2 51 ABSTRACT Epidemiologic studies indirectly suggest that air pollution accelerates atherosclerosis. We hypothesized that individual exposure to particulate matter (PM) derived from fossil fuel would correlate with plasma concentrations of oxidized low‐density lipoprotein (LDL), taken as a marker of atherosclerosis. We tested this hypothesis in patients with diabetes, who are at high risk for atherosclerosis. In a cross‐sectional study of non‐smoking adult outpatients with diabetes we assessed individual chronic exposure to PM by measuring the area occupied by carbon in airway macrophages, collected by sputum induction and by determining the distance from the patient’s residence to a major road, through geocoding. These exposure indices were regressed against plasma concentrations of oxidized LDL, von Willebrand factor and plasminogen activator inhibitor 1 (PAI‐1). We could assess the carbon load of airway macrophages in 79 subjects (58 percent). Each doubling in the distance of residence from major roads was associated with a 0.027 µm² decrease (95 % confidence interval (CI): ‐0.048 to ‐0.0051) in the carbon load of airway macrophages. Independently from other covariates, we found that each increase of 0.25 µm2 [interquartile range (IQR)] in carbon load was associated with an increase of 7.3 U/L (95% CI: 1.3 to 13.3) in plasma oxidized LDL. Each doubling in distance of residence from major roads was associated with a decrease of ‐2.9 U/L (95% CI: ‐5.2 to ‐0.72) in oxidized LDL. Neither the carbon load of macrophages nor the distance from residence to major roads, were associated with plasma von Willebrand factor or PAI‐1. The observed positive association, in a susceptible group of the general population, between plasma oxidized LDL levels and either the carbon load of airway macrophages or the proximity of the subject’s residence to busy roads suggests a proatherogenic effect of traffic air pollution. 52 Chapter 2 INTRODUCTION Numerous epidemiological studies link various adverse health outcomes with air pollution, especially that caused by particulate matter (PM), which to a considerable extent is caused by traffic.1,2 One of the important recent discoveries has been that exposure to PM is not only harmful to the lungs, but also to the heart and blood vessels.3‐6 This is undoubtedly true for short‐term increases in PM, which are triggers for acute cardiovascular events7, but probably also for long‐lasting exposure to urban PM, which increases the risk of cardiovascular mortality and morbidity4,6, possibly by accelerating atherosclerosis8‐10. A cross‐sectional study in Los Angeles9 suggested a role of air pollution in intima‐
media thickening of the carotid artery and a follow‐up study described an association between traffic proximity and the progression of intima‐media thickness10. In a German study of more than 4000 subjects a strong relation was found between coronary artery calcification and living close to major roads.8 These epidemiological observations strongly suggest that long‐term exposure to PM exerts a proatherogenic effect. Studies in laboratory animals have begun to give experimental plausibility to these epidemiological observations.11,12 However, so far, only few studies have provided mechanistic evidence for an effect of chronic exposure to traffic air pollution on the development of atherosclerosis in human subjects. It is well established that persons with diabetes have a higher risk of developing cardiovascular diseases. A population‐based study showed that persons with diabetes, without previous myocardial infarction, have the same risk of developing myocardial infarction as nondiabetic patients with previous myocardial infarction.13 The metabolic abnormalities caused by diabetes induce vascular dysfunction that predispose these patients to developing atherosclerosis.14 There is also evidence that persons with diabetes and cardiovascular disease are more sensitive to the effects of PM air pollution.15 So it is relevant – and also probably easier – to study the effects of air pollution in this more susceptible fraction of the population. Thus, in a previous study in diabetic subjects, we Chapter 2 53 showed associations between recent exposure to PM and systemic inflammation, and between recent PM and platelet activation, indicative of a prothrombotic tendency.16 A strong point of that study is that we were also able to estimate the participants’ exposure to chronic air pollution at the individual level by the carbon load of airway macrophages obtained by induced sputum. The carbon load of airway macrophage reflects a subject’s exposure to soot derived from the combustion of fossil fuels, as demonstrated in children.17 However, we also wanted to test the hypothesis that chronic air pollution would impact on indices or predictors of atherosclerosis. Therefore, we measured the concentration of oxidized LDL in plasma samples from this same population, because oxidized LDL is a well‐established biomarker of (subclinical) atherosclerosis and plaque formation.18 We also measured plasma von Willebrand factor and plasminogen activator inhibitor‐1 (PAI‐1), as markers for endothelial dysfunction.19,20 We hypothesized that chronic exposure to PM, as assessed by the carbon load of airway macrophages, was associated with an increase in the concentrations of circulating oxidized LDL, in a presumably more susceptible population. METHODS Participants The present study population is drawn from the one previously described.16 Briefly, non‐smoking persons with either type 1 or type 2 diabetes were recruited consecutively from the diabetes outpatient clinic at the University Hospital Leuven. Of the 186 recruited subjects, 137 (74%) consented and took part in the examination. Sufficient numbers of airway macrophages, to assess the area occupied by carbon, were obtained from 80 of the 119 patients (18 of the 137 patients failed to produce sputum). Of these 80 subjects with sufficient numbers of airway macrophages, 54 Chapter 2 oxidized LDL was available in 79, because in one person a blood sample could not be obtained. Patients completed a questionnaire to obtain information on age, occupation, socioeconomic status, exposure to environmental tobacco smoke, alcohol use, use of medication and place of residence. Socioeconomic status was coded and condensed into a scale with scores ranging from 1 to 3, on the basis of education and occupation of the patients. Determination of underlying cardiovascular diseases was based on the tenth International Classification of Diseases (ICD‐10 code: I20‐I89). Ethics The Ethics Review Board of the Medical Faculty of the University of Leuven (K.U.Leuven) approved the study. Participants gave written informed consent at recruitment. Exposure assessment Carbon load of airway macrophages obtained by induced sputum The induction of sputum in the patients and the processing of induced sputum was previously described. Briefly, nebulized saline (NaCl 3, 4 or 5%) was administered through an ultrasonic nebulizer (Ultra‐NebTm2000 model 200HI, De Vilbiss Healtcare, Somerset, PA, USA) in one, two or three 7‐min inhalation periods. To isolate airway macrophages, induced sputum was processed according to a standard technique.21 Airway macrophages were visualized by light microscopy (AxioPlan 2 Imaging, Zeiss, Zaventem, Belgium). Then Scion image software (Scion Corporation, Frederick, MD, USA) was used to calculate the carbon load of airway macrophages (Figure 1A), which was defined as the median area (µm2) occupied by carbon, in 50 randomly selected macrophages per patient.16,17,22 Distance to major roads Chapter 2 55 Distances from the patient’s residence to a major road were calculated through geocoding (the shortest distance is 10 meters). A major road was defined as an N‐road (major traffic road) or an E‐road (motorway/highway).16 Recent exposure A portable laser‐operated aerosol mass analyzer (Aerocet 531, Met One Instruments Inc, Grant Pass, OR, USA) was used to measure PM2.5 (particles with an aerodynamic diameter of less than 2.5 μm) and PM10 concentrations two hours before the patient’s participation in the study. The device had been previously calibrated against a local monitoring station (Flemish Environmental Agency, Borgerhout, Antwerp). The PM concentrations were measured outside, at the entrance of the hospital, as previously described.16 Clinical measurements Blood collection As previously described16, non‐fasting blood samples were collected in an EDTA tube and on 0.129 M (3.8 %) sodium citrate, on the same day as the sputum collection, according to standard clinical procedures. Blood cell counts and differential leukocyte counts were determined using an automated cell counter with flow differential (Cell Dyn 3500, Abbott Diagnostics, Abott Park, IL, USA). Plasma samples were kept frozen at ‐80°C for future analysis. Biochemical analysis Oxidized LDL concentration in plasma was measured by a commercially available sandwich ELISA (Mercodia, Uppsala, Sweden). Antigen levels of plasma von Willebrand factor and PAI‐1 were measured with an in‐house ELISA. Blood glucose levels, glycated haemoglobin, total cholesterol, high‐density lipoprotein (HDL) cholesterol and triglycerides were measured according to standard clinical procedures. LDL was calculated from the Friedewald formula.23 56 Statistical analysis Chapter 2 For database management and statistical analysis, we used SAS Software (version 9.1, SAS Institute Inc, Cary, NC). Non‐normally distributed data were log transformed. We investigated associations between plasma concentrations of oxidized LDL, von Willebrand factor and PAI‐1 and markers of chronic exposure (carbon load of airway macrophages and distance from residence to major roads) using stepwise linear regression in which we set p=0.15 for the independent variables to enter and to stay in the model. Covariates considered for entry in the model were sex, age, body‐mass index (BMI), type of diabetes, socioeconomic status, hour of blood draw, exposure to environmental tobacco smoke, physical activity, LDL, HDL, blood glucose level, glycated haemoglobin, blood leukocyte counts, use of statins, use of angiotensin‐converting–enzyme (ACE) inhibitors and use of antiplatelet medication. Irrespective of selection by the stepwise regression model we forced sex, age, body‐mass index, socioeconomic status, type of diabetes, glycated haemoglobin levels, statin use and blood leukocyte counts into the models. We ran three models: model 1 unadjusted analysis, model 2 adjusted for sex, age, socioeconomic status, LDL and HDL cholesterol and finally a fully adjusted model 3 for which additional covariates were selected by stepwise regression. We applied multiple logistic regression analysis to study the relation between clinical plasma levels of oxidized LDL18 and the carbon load of airway macrophages. We defined high plasma oxidized LDL as levels above the 75th percentile (>117 U/L), which corresponds to a higher risk for moderate to large plaques.18 Potential interactions between carbon load of airway macrophages and type of diabetes, glycated haemoglobin and use of statins on plasma levels of oxidized LDL were investigated. Q‐Q plots of the residuals were used to test the assumptions of all linear models. Chapter 2 57 RESULTS Characteristics of study participants The present study population is drawn from the one previously described.16 The characteristics of the 79 patients (age range: 22‐78 years) in whom the macrophage carbon load could be determined (58%) are described in Table 1. Table 1: Patient characteristics (n=79) Mean (SD) or number (%) Women Age, years 37 (47%) 56.5 (14.3) BMI, kg/m² 28.7 (5.2) Type 1 diabetes 33 (42%) Exposure to environmental tobacco smoke 11 (14%) Socioeconomic status Low 44 (56%) Middle 24 (30%) High 11 (14%) Medication use Antiplatelet medication 46 (58%) Statins 48 (61%) ACE inhibitor 31 (39%) Insulin 75 (95%) Oral antidiabetic medication 33 (42%) Underlying cardiovascular disease 30 (38%) Blood glucose, mg/dL 147 (68) Glycated haemoglobin, % 7.4 (1.0) Total blood leukocytes, /µL 6153 (1996) 3
Blood platelets, x10 /µL 230 (62) von Willebrand factor, µg/mL 13.6 (5.3) PAI‐1, ng/mL 84.4 (66.5) Cholesterol, mg/dL 158 (34) Triglycerides, mg/dL 132 (66) LDL, mg/dL 81.0 (26.2) HDL, mg/dL 50.7 (18.7) Oxidized LDL, U/L 85.6 (31.4) 58 Carbon load of airway macrophages and distance to major road Chapter 2 The median carbon load of our patient’s airway macrophages was 0.20 µm² (25th‐75th percentile: 0.095 to 0.34 µm²) and the median distance from the residence to a major road was 400 meters (25th‐75th percentile: 124 to 839 meters). The relation between carbon load in airway macrophages (expressed as a surface), and distance between residence and major roads is depicted in Figure 1B. Each doubling in distance to major roads was associated with a significant decrease – by 0.027 µm2 (95 % CI, ‐0.048 to ‐0.0051; p=0.02) – in the carbon load of airway macrophages. These data further validate the use of this novel biomarker – proposed in a study of children 17 – as an indicator of a subject’s previous exposure to traffic‐related air pollution. Determinants of oxidized LDL In stepwise regression analysis, plasma oxidized LDL concentration was independently and positively correlated with LDL (regression coefficient  SE, 0.78±0.10 U/L per mg/dL; p<0.001) and inversely correlated with high‐density lipoprotein (HDL) cholesterol levels (‐0.38±0.14 U/L per mg/dL; p=0.01). Although sex, age, socioeconomic status, BMI, type of diabetes, glycated haemoglobin levels, statin use and blood leukocyte counts were not significantly associated with oxidized LDL, we forced these variables, together with LDL and HDL cholesterol levels, into the regression models. Both before adjustment (Figure 1C, Table 2) and after adjustment (Table 2) for the aforementioned variables, plasma oxidized LDL concentrations were positively associated with the carbon load of airway macrophages: an interquartile (IQR) increase in carbon load (0.25 µm2) was associated with an increase of 7.3 U/L (95% CI: 1.3 to 13.3) in oxidized LDL. Distance from residence to major roads tended to be inversely associated with oxidized LDL (Figure 1D, Table 2). After accounting for sex, age, socioeconomic status, BMI, type of diabetes, glycated haemoglobin levels, statin use, blood leukocyte counts and LDL and HDL cholesterol, each doubling in the distance from the patient’s Chapter 2 59 residence to a major road was associated with a decrease of 2.9 U/L (95% CI: ‐5.2 to ‐0.72) in plasma levels of oxidized LDL (Table 2). Oxidized LDL was not associated with total blood leukocyte counts, nor with plasma von Willebrand factor or PAI‐1. B
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Figure 1: An airway macrophage containing carbon particles (A). We determined the surface of the macrophage occupied by carbon (in µm²), in 50 macrophages per person. The carbon load is given as the median carbon load of 50 airway macrophages. Pearson correlation between carbon load of airway macrophages and distance from the residence to a major road (B). (Data leading to panel b have been previously published16). The shortest distance to a major road is 10 meters, by definition. Pearson correlation between plasma concentrations of oxidized LDL and carbon 60 Chapter 2 load of airway macrophages (C) and between plasma concentrations of oxidized LDL and distance from the residence to a major road (D). Table 2: Estimated change in plasma oxidized LDL levels in association with carbon load or distance from residence to major roads Carbon load*, +0.25 µm² Model 1 Estimate 9.3 95% CI 2.1 to 16.4 p‐value 0.01 Model 2 6.7 1.2 to 12.2 0.02 7.3 1.3 to 13.3 0.02 Distance to major road , x2 Model 1 Estimate ‐2.6 95% CI ‐5.5 to 0.31 p‐value 0.08 Model 2 ‐2.9 ‐5.0 to ‐0.73 0.01 ‐2.9 ‐5.2 to ‐0.72 0.01 Model 3 †
Model 3
Estimates reflect the change in oxidized LDL (U/L); CI = confidence interval Model 1: Unadjusted Model 2: Adjusted for sex, age, LDL and HDL cholesterol Model 3: Adjusted for sex, age, socioeconomic status, LDL and HDL cholesterol, BMI, type of diabetes, glycated haemoglobin, statin use and blood leukocyte counts *Effect size calculated for an interquartile range difference in carbon load †Effect size was calculated for a twofold increase in distance from residence to major road (based on a model with log distance) Determinants of von Willebrand factor and PAI‐1 Neither the carbon load of macrophages nor the distance from residence to major roads, were associated with plasma von Willebrand factor or PAI‐1, taken as indices of endothelial dysfunction. Sensitivity analysis Studies have pointed to reduced susceptibility to the effects of air pollution in those that take statins.24,25 We therefore tested the interaction term of carbon load of macrophages by statin use. The interaction term of carbon load and oxidized LDL by statin use tended to be significant (p=0.09) in models that did not account for LDL and HDL cholesterol but did not reach statistical significance (p=0.64) in models that did account for plasma cholesterol levels. Chapter 2 61 There was also no effect‐modification by sex (p=0.51 for interaction), age (p=0.55) type of diabetes (p=0.86), percentage glycated haemoglobin (p=0.47), and BMI (p=0.65) on the association between carbon load and oxidized LDL. Oxidized LDL did not correlate with recent PM air pollution measured at the hospital on the day of the patient’s visit. DISCUSSION The key finding of our study is that plasma oxidized LDL concentration, a molecular marker of subclinical atherosclerosis, is positively associated with the carbon load of airway macrophages, a marker of chronic exposure to carbon particles derived from fossil fuel burning. This association could not be explained by sex, age, socioeconomic status, LDL and HDL cholesterol levels, BMI, type of diabetes, glycated haemoglobin levels, statin use, blood leukocyte counts or any other covariate studied. Experimental work in animals has already shown associations between exposure to air pollution and oxidized LDL. Mice had increased IgM antibody titres to copper oxidized LDL after five weeks of exposure to cigarette smoke.26 Exposure to urban air pollution for four months exacerbated the susceptibility of LDL to oxidation in hyperlipemic mice and levels of anti‐oxidized LDL antibodies were significantly higher in mice on a high fat diet when exposed to urban air pollution.27 We found no association between exposure to chronic air pollution and markers of endothelial function (von Willebrand factor and PAI‐1), and also no association between these endothelial markers and oxidized LDL was found. Further, oxidized LDL was not associated with blood leukocytes, although we previously showed associations between exposure to air pollution and blood leukocyte counts.16 This suggests that the mechanism underlying the association between chronic exposure to PM and oxidized LDL is independent of the one underlying the association between air 62 Chapter 2 pollution and inflammatory changes, such as increases in blood leukocyte counts. In this context, the oxidative potential of air pollutants can play a role in the observed association, since oxidized LDL has been identified as a marker of oxidative stress.28 In susceptible apolipoprotein E‐deficient mice, concentrated ultrafine particles caused systemic oxidative stress, an inhibition of the anti‐
inflammatory capacity of HDL, and larger early atherosclerotic lesions.29 Studies in humans showed associations between plasma homocysteine level and exposure to PM2.5 and black carbon.30 Oxidative modification of LDL, together with increased blood leukocytes and platelets, contributes to the initiation and progression of atherosclerosis.31,32 We showed that exposure to particles can have an effect on both these processes. Increased circulating levels of oxidized LDL are associated with adverse cardiovascular outcomes. In a population‐based prospective study in 326 healthy men, plasma oxidized LDL levels, measured at baseline, predicted the occurrence and size of atherosclerotic plaques in the carotid arteries, three years later.18 In our sample, a quarter of the subjects had oxidized LDL concentrations above 117 U/L, a level previously associated with large risk of having carotid plaques.18 Here, the odds of having plasma oxidized LDL levels above that value increased by 163% for an IQR increase in the carbon load of airway macrophages. Findings from a nested case‐control study suggest that a high plasma oxidized LDL/total cholesterol ratio can be a possible indicator of increased risk for acute myocardial infarction.33 Holvoet et al.34 also showed that patients with coronary artery disease had higher levels of oxidized LDL compared with age‐matched controls without clinical evidence of cardiovascular disease. We did not find evidence of a higher sensitivity to pollution‐induced effects on oxidized LDL in persons with type 2 diabetes compared with their type 1 counterparts. However, our patients had well‐controlled glycated haemoglobin levels (average 7.4%) and insulin use in persons with type 2 diabetes was high (95%). Our study has limitations. Observational studies do not prove causality, even when exposure is estimated on an individual level. Determining the carbon load in 50 randomly selected macrophages per patient is a labour‐intensive technique and suitable sputum samples cannot always Chapter 2 63 be obtained. Although sputum induction was successful in only 58 percent of our patients, this is unlikely to have introduced bias, since there were no differences between those in whom sputum was induced successfully and those in whom it was not.16 We also did not observe any significant differences in exposure (carbon load or proximity to major roads) between the different socioeconomic classes. The exposure markers used here, i.e. carbon load and distances from major road, are surrogates for exposure to traffic‐related air pollution. Although we focus on PM, we cannot exclude a role of gaseous pollutants associated with traffic air pollution (NO, NO2). Our study was performed on purpose in a presumably more susceptible fraction of the population, i.e.; diabetic subjects, and this means that our conclusions do not necessarily apply to healthy subjects (with or without atherosclerosis). We encourage to verify our findings in larger populations, such as the Multi‐Ethnic Study of Atherosclerosis (MESA).35 In conclusion, we showed in a susceptible target population that individually assessed chronic exposure to air pollution is associated with plasma levels of oxidized LDL, a marker of early atherosclerosis. Our findings thus add mechanistic plausibility to the hypothesis that air pollution accelerates the development of atherosclerosis. 64 Chapter 2 REFERENCES (1) Brunekreef B, Holgate ST. Air pollution and health. Lancet. 2002;360:1233‐1242. (2) Pope CA III, Dockery DW. Health effects of fine particulate air pollution: lines that connect. J Air Waste Manag Assoc. 2006;56:709‐742. (3) Alfaro‐Moreno E, Nawrot TS, Nemmar A, Nemery B. Particulate matter in the environment: pulmonary and cardiovascular effects. Curr Opin Pulm Med. 2007;13:98‐106. (4) Miller KA, Siscovick DS, Sheppard L et al. Long‐term exposure to air pollution and incidence of cardiovascular events in women. N Engl J Med. 2007;356:447‐458. (5) Nawrot TS, Nemmar A, Nemery B. Air pollution: To the heart of the matter. Eur Heart J. 2006;27:2269‐2271. (6) Pope CA III, Burnett RT, Thun MJ et al. Lung cancer, cardiopulmonary mortality, and long‐
term exposure to fine particulate air pollution. JAMA. 2002;287:1132‐1141. (7) Peters A, von Klot S, Heier M et al. Exposure to traffic and the onset of myocardial infarction. N Engl J Med. 2004;351:1721‐1730. (8) Hoffmann B, Moebus S, Mohlenkamp S et al. Residential exposure to traffic is associated with coronary atherosclerosis. Circulation. 2007;116:489‐496. (9) Kunzli N, Jerrett M, Mack WJ et al. Ambient air pollution and atherosclerosis in Los Angeles. Environ Health Perspect. 2005;113:201‐206. (10) Kunzli N, Jerrett M, Garcia‐Esteban R et al. Ambient air pollution and the progression of atherosclerosis in adults. PLoS One. 2010;5:e9096. (11) Sun Q, Wang A, Jin X et al. Long‐term air pollution exposure and acceleration of atherosclerosis and vascular inflammation in an animal model. JAMA. 2005;294:3003‐3010. (12) Suwa T, Hogg JC, Quinlan KB, Ohgami A, Vincent R, van Eeden SF. Particulate air pollution induces progression of atherosclerosis. J Am Coll Cardiol. 2002;39:935‐942. (13) Haffner SM, Lehto S, Ronnemaa T, Pyorala K, Laakso M. Mortality from coronary heart disease in subjects with type 2 diabetes and in nondiabetic subjects with and without prior myocardial infarction. N Engl J Med. 1998;339:229‐234. (14) Beckman JA, Creager MA, Libby P. Diabetes and atherosclerosis: epidemiology, pathophysiology, and management. JAMA. 2002;287:2570‐2581. (15) O'Neill MS, Veves A, Zanobetti A et al. Diabetes enhances vulnerability to particulate air pollution‐associated impairment in vascular reactivity and endothelial function. Circulation. 2005;111:2913‐2920. Chapter 2 65 (16) Jacobs L, Emmerechts J, Mathieu C et al. Air pollution related prothrombotic changes in persons with diabetes. Environ Health Perspect. 2010;118:191‐196. (17) Kulkarni N, Pierse N, Rushton L, Grigg J. Carbon in airway macrophages and lung function in children. N Engl J Med. 2006;355:21‐30. (18) Wallenfeldt K, Fagerberg B, Wikstrand J, Hulthe J. Oxidized low‐density lipoprotein in plasma is a prognostic marker of subclinical atherosclerosis development in clinically healthy men. J Intern Med. 2004;256:413‐420. (19) Brodsky SV, Malinowski K, Golightly M, Jesty J, Goligorsky MS. Plasminogen activator inhibitor‐1 promotes formation of endothelial microparticles with procoagulant potential. Circulation. 2002;106:2372‐2378. (20) Horvath B, Hegedus D, Szapary L et al. Measurement of von Willebrand factor as the marker of endothelial dysfunction in vascular diseases. Exp Clin Cardiol. 2004;9:31‐34. (21) Pizzichini E, Pizzichini MM, Efthimiadis A, Hargreave FE, Dolovich J. Measurement of inflammatory indices in induced sputum: effects of selection of sputum to minimize salivary contamination. Eur Respir J. 1996;9:1174‐1180. (22) Kulkarni N, Prudon B, Panditi SL, Abebe Y, Grigg J. Carbon loading of alveolar macrophages in adults and children exposed to biomass smoke particles. Sci Total Environ. 2005;345:23‐30. (23) Friedewald WT, Levy RI, Fredrickson DS. Estimation of the concentration of low‐density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge. Clin Chem. 1972;18:499‐502. (24) Schwartz J, Park SK, O'Neill MS et al. Glutathione‐S‐transferase M1, obesity, statins, and autonomic effects of particles: gene‐by‐drug‐by‐environment interaction. Am J Respir Crit Care Med. 2005;172:1529‐1533. (25) O'Neill MS, Veves A, Sarnat JA et al. Air pollution and inflammation in type 2 diabetes: a mechanism for susceptibility. Occup Environ Med. 2007;64:373‐379. (26) Tani S, Dimayuga PC, Anazawa T et al. Aberrant antibody responses to oxidized LDL and increased intimal thickening in apoE‐/‐ mice exposed to cigarette smoke. Atherosclerosis. 2004;175:7‐14. (27) Soares SR, Carvalho‐Oliveira R, Ramos‐Sanchez E et al. Air pollution and antibodies against modified lipoproteins are associated with atherosclerosis and vascular remodeling in hyperlipemic mice. Atherosclerosis. 2009;207:368‐373. (28) Egert S, Bosy‐Westphal A, Seiberl J et al. Quercetin reduces systolic blood pressure and plasma oxidised low‐density lipoprotein concentrations in overweight subjects with a high‐
cardiovascular disease risk phenotype: a double‐blinded, placebo‐controlled cross‐over study. Br J Nutr. 2009;102:1065‐1074. 66 Chapter 2 (29) Araujo JA, Barajas B, Kleinman M et al. Ambient particulate pollutants in the ultrafine range promote early atherosclerosis and systemic oxidative stress. Circ Res. 2008;102:589‐596. (30) Ren C, Park SK, Vokonas PS et al. Air pollution and homocysteine: more evidence that oxidative stress‐related genes modify effects of particulate air pollution. Epidemiology. 2010;21:198‐206. (31) Stocker R, Keaney JFJr. Role of oxidative modifications in atherosclerosis. Physiol Rev. 2004;84:1381‐1478. (32) Ross R. Atherosclerosis‐an inflammatory disease. N Engl J Med. 1999;340:115‐126. (33) Nordin FG, Hedblad B, Berglund G, Nilsson J. Plasma oxidized LDL: a predictor for acute myocardial infarction? J Intern Med. 2003;253:425‐429. (34) Holvoet P, Mertens A, Verhamme P et al. Circulating oxidized LDL is a useful marker for identifying patients with coronary artery disease. Arterioscler Thromb Vasc Biol. 2001;21:844‐848. (35) Holvoet P, Jenny NS, Schreiner PJ, Tracy RP, Jacobs DR. The relationship between oxidized LDL and other cardiovascular risk factors and subclinical CVD in different ethnic groups: the Multi‐Ethnic Study of Atherosclerosis (MESA). Atherosclerosis. 2007;194:245‐252. CHAPTER 3 Air pollution‐associated procoagulant changes: role of circulating microvesicles Jan Emmerechts*, Lotte Jacobs*, Soetkin Van Kerckhoven, Serena Loyen, Chantal Mathieu, Frans, Fierens, Benoit Nemery, Tim S Nawrot, Marc F Hoylaerts Published in J Thromb Haemost 2012;10: 96‐106 Online data supplement available on http://onlinelibrary.wiley.com/doi/10.1111/j.1538‐7836.2011.04557.x/full * Both authors contributed equally to this work Chapter 3 69 ABSTRACT Background: Epidemiological studies suggest an association between exposure to particulate matter (PM) in air pollution and risk of venous thromboembolism (VTE). Objectives: To investigate the underlying pathophysiological pathways linking PM exposure and VTE. Methods: We assessed potential associations between PM exposure and coagulation and inflammation parameters, including circulating microvesicles, in a group of 233 patients with diabetes. Results: The numbers of circulating blood platelet‐derived and annexin V‐binding microvesicles were inversely associated with the current levels of PM2.5 or PM10, measured on the day of sampling. Recent past exposure to PM10, up to 1 week prior to blood sampling, estimated at the patients' residential addresses, was associated with elevated high‐sensitivity C‐reactive protein (CRP), leukocytes and fibrinogen, as well as with tissue factor‐dependent procoagulant changes in thrombin generation assays. When longer windows of past exposure were considered, up to 1 year preceding blood sampling, procoagulant changes were evident from the strongly increased numbers of red blood cell‐derived circulating microvesicles and annexin V‐binding microvesicles, but they no longer associated with tissue factor. Past PM exposure was never associated with activated partial thromboplastin time (aPTT), prothrombin time (PT), or factor (F) VII, FVIII, FXII or D‐dimers. Residential distance to a major road was only marginally correlated with procoagulant changes in FVIII and thrombin generation. Conclusions: Increases in the number of microvesicles and in their procoagulant properties, rather than increases in coagulation factors per se, seem to contribute to the risk of VTE, developing during prolonged exposure to air pollutants. 70 Chapter 3 INTRODUCTION Ambient environmental air pollutants include gaseous and particulate components. Considering a large body of evidence, the American Heart Association scientific statement on 'Air Pollution and Cardiovascular Disease' concluded that both short‐term and long‐term exposure to the particulate component (particulate matter, PM) are associated with increased mortality and cardiovascular disease1. In addition to the well‐recognized air pollution‐related adverse effects on the arterial vascular system2‐8, recent epidemiological evidence also suggests an association between PM exposure and venous thromboembolism (VTE). Thus, a higher risk for deep vein thrombosis (DVT) was associated with increased annual mean levels of PM with a mean aerodynamic diameter smaller than 10 µm (PM10) in the residential area of the study subjects9. In the same study population, living near major traffic roads was also associated with an increased risk of DVT, even after controlling for the community‐level PM pollution10. These initial epidemiological findings by the group of Baccarelli were recently confirmed in a time‐series analysis in Chile, demonstrating an association between PM exposure and hospital admission for VTE11, although also challenged by others12,13. The pathophysiological mechanisms explaining the observed link between PM exposure and VTE remain largely unknown. Although increases in the levels of coagulation factors seem the most likely explanation, published data for this interpretation are conflicting and unconvincing. In fact, disappointingly few studies reported on positive associations between air pollution exposure and increased levels of coagulation factors, and estimated effect sizes for the reported associations are relatively small14‐23. Therefore, the observed increases in coagulation factors are unlikely to be (solely) responsible for an increased venous thrombogenicity. A potential role for microvesicles (also called microparticles, a term we prefer to avoid in the context of pollution by particles) has been suggested14,24,25. Microvesicles are circulating vesicles with a mean diameter smaller than 1 µm that are released from stimulated or apoptotic cells in the Chapter 3 71 vascular bed. Negatively charged phospholipids and tissue factor (TF) on their membranes create a procoagulant surface on which coagulation factors can bind and be activated to promote coagulation26. Elevated numbers of circulating microvesicles have been demonstrated in patients with VTE27,28. A direct link between air pollution and an elevation in the concentration of circulating microvesicles or their procoagulant potential has hitherto never been shown in humans. In the present study, we hypothesized that microvesicles, through their procoagulant potential, could represent a missing link between air pollution exposure and VTE. We, therefore, investigated associations between PM exposure and markers of inflammation and coagulation, with a focus on microvesicles and microvesicle‐dependent coagulation assays. We investigated these associations in an a priori susceptible population of patients with diabetes, because diabetic subjects are more sensitive to the deleterious effects of PM during air pollution29. METHODS Study population Persons with either type 1 or type 2 diabetes were recruited from the diabetes outpatient clinic at the University Hospital Leuven, Belgium, as a new cohort of patients, different from the cohort of our previous studies30,31. These patients visit the diabetes clinic as part of their routine follow‐up. They were included if they were 18 years or older, current (for >6 months) non‐smokers and not on anticoagulant therapy. Inclusion was done on different days from February 2010 through April 2010. Of 402 patients contacted, 339 agreed to participate (84% participation rate). We excluded 106 patients because of current smoking (n=74), anticoagulant therapy (n=16), accidental lack of blood samples (n=10) or other reasons (n=6). Thus, the final study population consisted of 233 included patients (Figure 1). On the study day, patients completed a questionnaire through a 72 Chapter 3 personal interview to collect information on age, occupation, socioeconomic status, exposure to environmental tobacco smoke, alcohol use, use of medication, use of oral contraception, menopausal status, place of residence and means of transportation to the hospital. Socioeconomic status was encoded and condensed into a scale with scores ranging from 1 to 3, based on educational level. The Ethics Review Board of the Medical Faculty of the University of Leuven (KULeuven) approved the study. Participants gave informed consent at recruitment. Figure 1. Flowchart of the study population The study population was consecutively recruited from the diabetes outpatient clinic at the University Hospital Leuven. The lower right box shows the percentage of samples that were measured per group of analyses. HbA1c=glycated hemoglobin, FACS= flow cytometric analysis, WBC=white blood cells in blood. Chapter 3 73 Exposure assessment Current exposure A portable laser‐operated aerosol mass analyzer (Aerocet 531, Met One Instruments Inc, Grant Pass, OR, USA), previously calibrated against a local monitoring station (Flemish Environmental Agency, Borgerhout, Belgium)31, was used to measure current PM2.5 and PM10 concentrations in the hospital waiting room, one to two hours before the patient’s participation in the study. In general, patients stayed in the waiting room and the neighboring examination room for at least one hour. Subacute, subchronic and chronic exposure The regional background level of PM10 at each patient's residential address was calculated using a kriging interpolation method. This model provides interpolated PM10 values from the Belgian telemetric air quality network in 4x4 km grids (see Figure 2). The interpolation is based on a detrended kriging interpolation model that uses land cover data obtained from satellite images (Corine land cover data set, European Environment Agency, 2000)32. Regional background levels of PM2.5 are not available in Belgium. Mean residential PM10 values were measured for different time windows, and classified in 3 categories of exposure: 1) subacute: mean residential PM10 values on the day of blood sampling ('day 0'), on the first ('day ‐1'), the second ('day ‐2') or the third ('day‐3') day before blood sampling; 2) subchronic: mean residential PM10 values over the preceding week ('mean 1 week') or month ('mean 1 month'); 3) chronic: mean residential PM10 values over the preceding 3 months ('mean 3 months'), 6 months ('mean 6 months') or 12 months ('mean 1 year'). Distances from the home address to major roads (N‐road, a major traffic road or E‐road, a motorway/highway) also reflect chronic PM exposure and were calculated through geocoding (the shortest distance being set at 10 meters). 74 Chapter 3 Figure 2. Location of residences of study subjects Map of Belgium reporting location of the study center (University hospital, Leuven, Belgium) and location of the residences of the study subjects. Background colors represent mean annual PM10 concentrations for 2010 in 4x4 km grids. Clinical measurements All laboratory tests were performed without knowledge of the subject's exposure data. A detailed description and validation of the assays used in this study to identify and characterize microvesicles is given in the online data supplement. Figure S1 schematically summarizes the physiological role of microvesicles in the coagulation cascade and illustrates which assays were performed in this study to evaluate microvesicles. In brief, microvesicle quantification was performed by flow cytometry (see below). To evaluate their procoagulant potential, surface expression of negatively charged phospholipids was evaluated by flow cytometry and surface expression of functional tissue factor by thrombin generation assays (TGA, see below). Chapter 3 75 Blood All blood samples were collected in a restricted time window in the diabetes outpatient clinic (median hour of sampling: 01.50 p.m.), thus reducing the possibility of confounding by circadian rhythms of some parameters. Non‐fasting blood samples were collected using a 21 gauge needle (Terumo, Leuven, Belgium) on EDTA, on sodium fluoride/oxalate, or on sodium citrate (3.8%) tubes (all BD Vacutainer, BD Biosciences, Erembodegem, Belgium). Analysis of blood cell counts and glucose and glycated hemoglobin (HbA1c) levels were performed on fresh full blood or plasma samples. For all other parameters, plasma was stored immediately at ‐80°C for future batch analysis. Citrated samples were centrifuged according to two different protocols: for biochemical analyses, tubes were centrifuged once at 3000 x g. For the analysis of microvesicles, both by flow cytometry and by TGA, tubes were first centrifuged for 10 minutes at 1900 x g, followed by a second centrifugation step of 20 minutes at 1900 x g to obtain blood platelet‐depleted but microvesicle‐rich plasma. All plasma samples were centrifuged within one hour after collection. Blood cell counts and routine biochemical analysis Blood cell counts, coagulation parameters, glucose levels, glycated hemoglobin (HbA1c) and high‐sensitivity CRP (hsCRP) were measured according to standard clinical procedures on automated analyzers. The following "traditional" coagulation parameters were measured: activated partial thromboplastin time (aPTT), prothrombin time (PT), factor (F) VII, FVIII, FXII, fibrinogen and D‐dimers. Thrombin generation assays (TGA) Thrombin generation was measured by means of the Calibrated Automated Thrombography (CAT) method using a Fluoroskan Ascent reader (Thermo Labsystems OY, Helsinki, Finland). Thrombinoscope software (Thrombinoscope BV, Maastricht, The Netherlands) was used to calculate thrombin generation curves, from which four parameters were derived: lag time (initiation phase of coagulation), endogenous thrombin potential (ETP, area under the thrombin generation curve), peak height (maximal reaction) and time to peak33. In this study, only the lag time and the ETP are 76 Chapter 3 reported as representative parameters. To 80 μL of plasma sample, 20 μL of trigger reagent (see below) were added and thrombin generation recording was started upon subsequent addition of 20 μL FluCa, a mixture of calcium chloride ('Ca', 87 mM) and thrombin substrate (Z‐Gly‐Gly‐Arg‐AMC, 2.5 mM , Bachem, Weil‐am‐Rein, Germany). Three different analytical conditions were applied: First, a contact activator ('S', Synthasil, Instrumentation Laboratory, Zaventem, Belgium, final concentration 1/400) was added to trigger the intrinsic coagulation pathway, and 'lag time(Ca,S)' and 'ETP(Ca,S)' were recorded. Second, tissue factor ('TF', Innovin, Siemens, Hamburg, Germany, final concentration 5 pM) was added to trigger primarily the extrinsic coagulation pathway and 'lag time(TF)' and 'ETP(TF)' were recorded. Third, thrombin generation was performed upon simple recalcification of microvesicle‐rich plasma in the absence of an exogenous trigger, to investigate the effect of endogenous coagulation triggers in the plasma sample, including microvesicle‐bound factors such as TF, and 'lag time(Ca)' and 'ETP(Ca)' were recorded. In TGA, especially the lag time is to a large extent determined by the amount of TF present in the assay34. Hence, to functionally asses the endogenous TF in the plasma sample, we additionally measured 'lag time(Ca)' in the presence of 300 ng/mL (final concentration) tissue factor pathway inhibitor (TFPI, R&D Systems, Abingdon, UK). This enabled us to specifically investigate the TF‐
dependency of associations with air pollution exposure, as explained in detail in the online data supplement. All TGA's were performed in the presence of an excess (4 µM) of exogenous phospholipids (phosphatidylserine 30% and phosphatidylcholine 70%, Sigma‐Aldrich, Bornem, Belgium), making thrombin generation independent of the surface expression on microvesicles of negatively charged phospholipids. Chapter 3 77 Microvesicle analysis by flow cytometry Microvesicles were analyzed by flow cytometry following a protocol, standardized by the Scientific and Standardization Subcommittee (SSC) of the International Society on Thrombosis and Haemostasis (ISTH)35 with some adaptations. In brief, to thawed microvesicle‐rich plasma, fluorescein isothiocyanate‐labeled mouse anti‐CD42a (BD Biosciences, Erembodegem, Belgium), phycoerythrin‐
labeled mouse anti‐glycophorein A (GPA, BD Biosciences, Erembodegem, Belgium) and allophycocyanin‐labeled annexin V (AV, Immunotools, Friesoythe, Germany) were added and samples were analyzed on a FACSCantoII flow cytometer (BD Biosciences, Erembodegem, Belgium) to define blood platelet‐derived microvesicles ('BPµV', CD42a+), red blood cell‐derived microvesicles ('RBCµV', GPA+) and microvesicles with a procoagulant, negatively charged phospholipid surface, binding annexin V ('AV+µV'). A detailed description of our microvesicle analysis by flow cytometry is provided in the online data supplement. Tissue factor mRNA in circulating white blood cells TF mRNA expression measurement was performed by quantitative real‐time PCR on the AB 7500 Fast PCR System (Applied Biosystems, Ottignies‐Louvain‐la‐Neuve, Belgium) as described in the online data supplement. Statistical analysis For database management and statistical analysis, we used SAS Software (version 9.1, SAS Institute Inc, Cary, NC). Non‐normally distributed data were log transformed. We investigated associations between plasma markers and recent or chronic exposure parameters using multiple linear regression. In all regression models we included the following a priori chosen covariates: gender, age, body‐mass index, socioeconomic status, type of diabetes, physical activity, blood glucose levels, use of insulin, use of statins, use of antiplatelet medication and temperature and humidity on the day of blood sampling. Potential interactions of type of diabetes, use of statins and use of antiplatelet 78 Chapter 3 medication with the association between air pollution and all measured parameters were investigated. Q‐Q plots of the residuals were used to test the assumptions of all linear models. RESULTS Characteristics of the study population Characteristics of study participants are shown in Table 1. Of the men, 34 (32%) had type 1 diabetes compared to 57 (45%) for the women. All patients with type 1 diabetes used insulin; among type 2 diabetics, 126 persons (89%) used insulin medication. Mean values ±SD for HbA1c were 7.8±1.1% for type 1 diabetics and 7.2±1.2% for type 2 diabetics. Exposure characteristics are shown in Table 2. A representation of the location of the patients' residences and the study center is shown in Figure 2. Clinical measurements The value distribution of clinical parameters for the study population is shown in Table S1 (online data supplement). With the exception of FVIII, mean values for the population were within the normal reference ranges. Figure 3 shows the associations (adjusted for the aforementioned covariates) between air pollution exposure and all outcome parameters, as determined by the regression analysis for different time windows. The corresponding effect sizes for selected time windows are shown in Figures 4 to 6. A stratified analysis for type of diabetes, statin use or antiplatelet use is shown in supplementary Figures S5‐7 (online data supplement). Inflammation parameters and blood cells Significant positive correlations were observed between PM10 exposure at the patient's residence and hsCRP and WBC concentrations for PM10 exposure windows within 1 week (Figure 3), Chapter 3 79 with positive but only borderline significant values (0.05< p <0.10) for the longer time windows up to 6 months. Each 10 g/m3 increase in the mean PM10 concentration over the preceding week at the patient's residence increased the hsCRP by 23% (95%CI: 5‐45) and the WBC by 7% (95%CI: 2‐12) (Figure 5A). Table 1: Population characteristics (n=233) Mean (SD) or number (%) Gender, men 107 (46%) Age, years 57.9 (17.5) BMI, kg/m² 28.9 (5.5)
Type 1 diabetes 91 (39%) Exposure to environmental tobacco smoke 34 (15%) Socioeconomic status Low 158 (68%)
Middle 55 (23.5%) High 17 (7.5%) …Unknown 3 (1%) a
Antiplatelet medication
140 (60%)
Statin 154 (66%) ACE inhibitor 129 (55%) Insulin 217 (93%) Oral antidiabetic medication
106 (46%)
b
139.2 (63.4)c,d Blood glucose , mg/dL Glycated hemoglobin, % a
7.5 (1.2)e,f Antiplatelet medication includes acetylsalicylic acid, clopidogrel, ticlopidine or dipyridamole b
Non‐fasting values c
Data are available for 224 persons d
Reference values (fasting): 55‐100 mg/dL e
Data are available for 229 persons f
Reference values: 4.0‐6.0 % 80 Chapter 3 Table 2: Exposure characteristics of included subjects (n=233). Type of exposure Current indoor PM2.5, g/m3 mean 4.6 median 4.3 range 1.4‐7.6 P10‐P90 2.4‐7.2 IQR 2.6 Current indoor PM10, g/m3 22.1 21.3 12.0‐39.4 15.0‐30.8 5.6 day 0 25.7
26.3
7.3‐52.8
10.7‐36.2 11.4
day ‐1 27.6 28.0 7.2‐55.7 13.0‐40.9 11.5 day ‐2 28.0 27.4 9.9‐85.8 14.2‐42.5 11.4 day ‐3 28.3 26.5 7.7‐72.6 13.1‐47.5 16.2 mean 1 week 25.2
25.8
11.8‐44.4
14.2‐37.8 16.5
mean 1 month 26.3 25.5 11.6‐43.0 19.9‐34.3 8.5 mean 3 months 25.9 25.7 15.0‐38.3 22.9‐29.2 3.08 mean 6 months 22.8 22.6 13.3‐34.6 20.4‐25.5 2.7 mean 1 year 22.1
21.7
12.5‐33.7
19.3‐25.07 2.7
Residential distance to major road, m 689
410
10‐5191
10‐1767 755
3
Residential PM10, g/m IQR: interquartile range, P10: percentile 10, P90: percentile 90. "Traditional" coagulation parameters Current PM10 exposure correlated with a prolongation of the PT (Figure 3). No significant correlations were found between either current, subacute, subchronic or chronic PM exposure and measurements of aPTT, FVII, FVIII, FXII or D‐dimers (Figure 3). Concentrations of fibrinogen correlated positively with PM10 at 'day‐2' and 'day‐3', as well as with the mean PM10 concentration over 1 week (Figure 3). Each 10 g/m3 increase in the mean concentration of PM10 over the preceding week at the patient's residence elevated fibrinogen levels by 4% (95%CI: 1‐7) (Figure 5A). Each halving in residential distance to a major road increased FVIII by 2% (95%CI: 1‐3) (Figure 6). Chapter 3 81 Figure 3. Representation of significant associations between air pollution exposure and outcome parameters Regression analysis was performed to determine the associations between outcome parameters and current PM2.5 and PM10 concentrations measured in the diabetes outpatient clinic's waiting room, residential PM10 concentrations over different time windows preceding blood sampling (as indicated) or residential distance to a major road (N‐ or E‐road). For significant associations, positive and negative slopes are denoted as '+' or '‐' respectively. Significant associations that represent increases in inflammatory parameters or blood cells, or procoagulant changes, are highlighted in green striped (p<0.05) or green plain (p<0.005) boxes. Significant associations that represent decreases in inflammatory parameters or blood cells, or anticoagulant changes, are highlighted in red striped (p<0.05) or red plain (p<0.005) boxes. 82 Chapter 3 Figure 4. Effect sizes for significant associations with current PM2.5 and PM10 concentrations Effect sizes (%, 95%CI) were calculated (A) for each 10 g/m3 increase in current PM2.5 and PM10 concentrations, measured in the diabetes outpatient clinic's waiting room in the hours preceding the blood sampling. Those parameters were selected that showed significant correlations in figure 3. hsCRP=high sensitivity CRP. WBC=white blood cells, RBC=red blood cells, BP=blood platelets, ETP=endogenous thrombin potential, BPµV=BP‐derived microvesicles, RBCµV=RBC‐derived microvesicles, AV+µV=annexin‐V binding microvesicles. Analysis adjusted for covariates. * p<0.05, ** p<0.005. Chapter 3 83 84 Chapter 3 Figure 5 (previous page). Effect sizes for significant associations with residential PM10 concentrations at different time windows before blood sampling Effect sizes (%, 95%CI) were calculated for each 10 g/m3 increase in residential mean PM10 concentrations measured over (A) 1 week, (B) 1 month or (C) 1 year preceding the blood sampling. Those parameters were selected that showed significant correlations in figure 3. hsCRP=high sensitivity CRP. WBC=white blood cells, RBC=red blood cells, BP=blood platelets, ETP=endogenous thrombin potential, BPµV=BP‐derived microvesicles, RBCµV=RBC‐derived microvesicles, AV+µV=annexin‐V binding microvesicles. Analysis adjusted for covariates. * p<0.05, ** p<0.005. Microvesicle analysis The concentrations of current PM2.5 correlated negatively with the concentrations of BPµV (‐
57%, 95%CI: ‐78 to ‐16% per 10 µg/m3 increase in PM2.5) and of AV+µV that express negatively charged phospholipids on their surface (‐74%, 95%CI: ‐85 to ‐56% per 10 µg/m3 increase in PM2.5), while both current PM10 and residential PM10 on 'day ‐3' correlated negatively with the concentration of AV+µV (‐27%, 95%CI: ‐39 to ‐12% per 10 µg/m3 increase in current PM10) (Figure 3 and 4). In contrast, we found positive correlations between mean PM10 concentrations over the chronic exposure windows (preceding 3 months to 1 year) and the concentrations of RBCµV and AV+µV with the highest effect sizes measured for the 1‐year period (+77% 95%CI: 14‐176 and +60% 95%CI: 15‐
123 per 10 µg/m3 increase in yearly PM10, respectively) (Figure 5C). Similar borderline significant results were found for the BPµV. TF mRNA in circulating WBC No significant correlations were observed between air pollution exposure and levels of TF mRNA expression in circulating white blood cells (Figure 3). Chapter 3 85 Figure 6. Effect sizes for significant associations with residential distance to a major road Effect sizes (%, 95%CI) were calculated for each halving in distance from the patient's residence to the nearest major road (N‐ or E‐road). Those parameters were selected that showed significant correlations in figure 3. hsCRP=high sensitivity CRP. WBC=white blood cells, RBC=red blood cells, BP=blood platelets, ETP=endogenous thrombin potential, BPµV=BP‐derived microvesicles, RBCµV=RBC‐derived microvesicles, AV+µV=annexin‐V binding microvesicles. Analysis adjusted for covariates. * p<0.05 Effect‐modification Table 1 demonstrates, for our study population of people with diabetes, the frequent use of different types of medication, some of which (e.g. statins) have been described to influence levels of TF or microvesicles. Therefore, we investigated if type of diabetes, use of statin medication and use of antiplatelet medication induced effect‐modification on the association between PM exposure and outcome variables. Results are shown in Figures S5‐7 of the online data supplement. In general, stratification for type of diabetes (Figure S5) or medication (Figure S6‐7) did not considerably influence the non‐stratified associations described in Figure 3. For patients with type 1 diabetes, increased current PM exposure was associated with decreases in inflammatory parameters (hsCRP, fibrinogen), in thrombin generation ['ETP(Ca,S)' and 'ETP(Ca,TF)'] and microvesicles (BPµV, 86 Chapter 3 RBCµV, AV+µV) that were not, or to a lesser extent, observed in type 2 diabetics, who rather showed increases in inflammatory parameters (Figure S5), compatible with the more inflammatory nature of this type of diabetes. Both statins (Figure S6) and antiplatelet use (Figure S7) tended to decrease the effect size of associations between chronic (1 week‐1 year) PM exposure and inflammatory (WBC, neutrophils) or procoagulant ['ETP(Ca,S)' and 'ETP(Ca,TF)'] changes, as compared to patients not taking these medications. DISCUSSION Parameters of inflammation, coagulation and microvesicles were correlated with measures of current (at blood sampling), subacute (day 0 to day ‐3), subchronic (mean 1 week to 1 month) and chronic (mean 3 months to 1 year) PM exposure and with residential distance to a major road, in patients with diabetes. Especially type 2 diabetes is a chronic inflammatory disease and circulating microvesicles seem to be elevated in these patients36,37. It was, therefore, relevant to measure inflammation parameters and microvesicle numbers in patients with diabetes who manifest increased susceptibility to air pollution29. Current PM levels were associated with lower numbers of circulating microvesicles and with decreased inflammatory parameters, mainly in patients with type 1 diabetes. We even found an isolated prolongation of the PT with increased levels of current PM10, contrasting previous observations14,38. However, the lower number of circulating microvesicles should not necessarily be interpreted as an anti‐inflammatory response to short‐term PM exposure but can be explained by the recruitment of circulating microvesicles to the lung via enhanced expression of adhesive receptors, including P‐selectin39,40 and von Willebrand factor41, by acutely activated pulmonary endothelial cells. Chapter 3 87 In contrast to the current PM exposure, consistent proinflammatory and procoagulant changes were observed for the longer PM exposure windows. Subacute and subchronic exposure up to 1 week were associated with a systemic inflammatory status, evidenced by increased hsCRP, total WBC counts and neutrophil counts. In agreement with other studies15,42,43, and compatible with its role as an acute phase protein, fibrinogen concentrations increased with higher PM exposure levels, within 1 week. We did not measure increases in FVIII, another acute phase protein, but the high mean baseline value for FVIII in a diabetic study population (table S1 and 44), could hinder further increase by PM exposure. Yet, increased fibrinogen concentrations cannot explain the strong correlations observed here between different thrombin generation parameters and subacute and subchronic PM10 exposure up to 1 month, since TGA are not influenced by fibrin(ogen) levels. Likewise, in the absence of procoagulant changes in any of the other "traditional" coagulation parameters (PT, aPTT, FVII, FVIII, FXII, D‐dimers), other processes should be responsible for enhancing thrombin generation with higher levels of PM exposure so consistently. A role for microvesicles, cellular bodies released from stimulated or apoptotic cells, in VTE has been suggested27,45. We assessed the procoagulant potential of microvesicles through measurement of their surface expression of TF in TGA, and through the analysis of the number of red blood cell and blood platelet‐derived microvesicles via flow cytometry. In addition, flow cytometric analysis of annexin V‐binding as undertaken to measure the surface expression of negatively charged phospholipids (mainly phosphatidylserine)26. Specifically the latter measurement has one drawback, i.e. that freezing‐thawing affects the expression of negatively charged phospholipids46,47, and therefore may not provide an accurate index of phosphatidylserine exposure in vivo. However, the consistency of the strong associations of the number of AV+µV with PM exposure over the different 88 Chapter 3 longer time windows indicates that these associations are unlikely to be artificially induced chance findings. Both subacute and subchronic PM exposure correlated strongly (p values <0.0001) with thrombin generation. The most pronounced correlations were found for TGA performed in the absence of an external trigger of coagulation ('lag time(Ca)' and 'ETP(Ca)'), and may therefore depend on the presence of endogenous triggers present in the plasma, such as contact activation or microvesicle‐bound TF, the concentration of the latter having a pronounced effect on the lag time34. In the subacute time window, associations between PM10 and lag time disappeared both in the presence of an excess of exogenous TF ['lag time(Ca,TF)'] and upon inhibition of TF by TFPI ['lag time(Ca)+TFPI']. This points towards exposure‐associated increased levels of circulating TF, most likely on microvesicles48. The source of TF‐bearing microvesicles is a matter of debate, yet with activated monocytes being the most likely candidate49. The remarkable conincidence in the subacute time window of associations of PM exosure with inflammatory parameters and with TF‐dependent changes in TGA adds to the hypothesis of inflammation‐coagulation cross‐talk in the first days following exposure to air pollution. In healthy individuals, microvesicles derived from blood platelets and red blood cells account for almost all circulating microvesicles. Since WBC‐derived microvesicles are extremely low50, we could not quantify these microvesicles via flow cytometry. In the subchronic time window, assocations between PM exposure and thrombin generation were no longer dependent on TF. Associations with lag times were also present upon exogenous TF addition ['lag time(Ca,TF)'] and did not disappear upon addition of TFPI. Moreover, procoagulant changes at 1 month occured in the absence of those inflammatory changes mentioned above. Therefore, the enhanced thrombin generation associated with PM concentrations over several weeks must be explained by (an) other mechanism(s). A recent study in mice suggests that PM promotes early procoagulant changes mostly through a TF‐driven extrinsic pathway of coagulation, whereas long lasting procoagulant effects are predominantly mediated through contact activation of the Chapter 3 89 intrinsic pathway of coagulation by systemically translocated ultra‐fine particles51. Yet, we found no associations between FXII and exposure to PM. An alternative explanation could be offered by downregulation of the anticoagulant pathways, including protein C and antithrombin, but these markers were not assessed in the present study. In the chronic PM exposure window, procoagulant changes were no longer obvious from thrombin generation measurements. Yet, a procoagulant tendency was apparent from the higher microvesicle numbers, both blood‐platelet derived and red blood cell‐derived, and increased microvesicular annexin V binding, reflecting surface expression of negatively charged phospholipids (mainly phosphatidylserine)26. TGA in the present study was performed in the presence of an excess of exogenous phospholipids, and is therefore insensitive to the effects by endogenous negatively charged phospholipids. We found the highest effect size on microvesicle number and procoagulant potential for the mean PM10 measurement over 1 year. Interestingly, in the study by Baccarelli et al.9, a 1‐year exposure time window correlated most strongly with the risk of DVT, while no significant correlations were found for time windows shorter than 9 months. Hence, upregulation of procoagulant microvesicles could, at least partly, be a pathophysiological mechanism underlying the association between long‐term PM exposure and VTE9,27,28. Living near a major road has been associated with increased risk for VTE in a case‐control study10. A recent population‐based prospective cohort study13, also demonstrated an, admittedly, non‐significant 16% increase in the risk of VTE for subjects living within 150 m of a major traffic road. In the present study, the correlations with residential distance to a major road were, although following similar trends, fewer and weaker than for the chronic residential PM10 measurements by the land‐use interpolation model. This is further discussed in the online data supplement. Our study has limitations. First, association studies do not prove causality, and our observations can therefore only suggest that procoagulant changes, consisting of enhanced thrombin generation and higher numbers of procoagulant microvesicles, are induced by exposure to PM. 90 Chapter 3 Second, the “disappearance” of associations between subacute PM exposure and thrombin generation in the presence of TFPI in the assays demonstrates a crucial role for circulating TF, which is not necessarily all microvesicle‐bound. Indeed, TF in plasma is primarily located on microvesicles, but it can also circulate as an alternatively spliced soluble protein48. Nevertheless, plasma depletion of microvesicles by filtration through a 0.1 µm filter significantly prolonged the lag time of thrombin generation assays in previous experiments in our laboratory (data not shown), suggesting that microvesicles are indeed the major source for TF. 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dependent manner. J Thromb Haemost. 2003; 1: 2561‐8. Chapter 3 95 (51) Kilinc E, van Oerle R, Borissoff JI, Oschatz C, Gerlofs‐Nijland ME, Janssen NA, Cassee FR, Sandstrom T, Renne T, Ten Cate H, Spronk HM. Factor XII Activation is Essential to Sustain the Procoagulant Effects of Particulate Matter. J Thromb Haemost. 2011; 9: 1359‐67. 96 SAMENVATTING List of publications Evaluatie 97 INLEIDING Milieufactoren kunnen een belangrijke rol spelen in het ontstaan van cardiovasculaire ziektes. Roken, eetgewoonten en sporten kunnen een aanzienlijke invloed hebben. De gezondheidseffecten van fijn stof of ‘particulate matter’ (PM) zijn kleiner, maar blootstelling aan luchtvervuiling is geen keuze, het is een onvrijwillige milieublootstelling, die de hele bevolking kan treffen. Hoewel luchtvervuiling gedurende de laatste jaren is afgenomen, kunnen huidige concentraties nog steeds negatieve gezondheidseffecten hebben. De inademing van kleine stofdeeltjes heeft effecten op zowel het respiratoir als het cardiovasculair systeem, zoals reeds duidelijk is gebleken uit ‘time‐series’ studies, die de korte termijn effecten van blootstelling aan fijn stof onderzoeken, alsook uit grote cohort studies, die de lange termijn effecten nagaan. Cardiovasculaire ziekten zijn een belangrijke doodsoorzaak, en slagaderverkalking of atherosclerose is de belangrijkste onderliggende pathologie. Het is daarom belangrijk om onderzoek te doen naar milieufactoren die deze onderliggende processen kunnen verergeren. BELANGRIJKSTE RESULTATEN Patiënten met diabetes, die werden gerekruteerd op de diabetes raadpleging van het Universitair Ziekenhuis in Leuven. Recente blootstelling (2 uur voor het onderzoek) aan fijn stof werd gemeten aan de ingang van het ziekenhuis. Individuele chronische blootstelling aan fijn stof werd vastgesteld door de oppervlakte van luchtwegmacrofagen, bezet met koolstof, te meten. Deze macrofagen werden verkregen via sputuminductie. We bepaalden ook de afstand van de woonplaats van de patiënt tot een drukke verkeersweg. Bloedplaatjesfunctie werd ex vivo gemeten met de PFA‐100, een test waarbij beschadiging aan een bloedvat wordt gesimuleerd. Hierdoor kon de functie van bloedplaatjes in primaire hemostase onder ‘high shear’ condities worden gemeten. Totale en differentiële witte bloedcellen werden geteld. Geoxideerd LDL in plasma werd gemeten, als een 98 Samenvatting merker voor atherosclerose. Recente blootstelling aan buiten concentraties fijn stof (2 uur voor het onderzoek), was, onafhankelijk van gebruik van anti‐aggregerende medicatie, geassocieerd met een stijging in bloedplaatjesactiviteit en met een toename in circulerende witte bloedcellen. Een stijging in de koolstoflading van longmacrofagen was geassocieerd met een stijging in circulerende witte bloedcellen en met geoxideerd LDL. De afstand van de woonplaats tot een drukke verkeersweg was geassocieerd met een stijging in geoxideerd LDL. Zowel recente als chronische blootstelling aan fijn stof was geassocieerd met proinlammatoire veranderingen. Meer chronische blootstelling aan met verkeersgerelateerde luchtvervuiling was geassocieerd met een proatherosclerotische respons.
Evaluatie 99 Evaluatievragen

Werd de oorspronkelijke doelstelling bereikt? Indien niet, waarom niet? – lessen uit te trekken
voor nieuwe steunpunt.
Ja, namelijk het bestuderen van effecten van fijn stof bij gevoelige subgroep in de bevolking
en daarbij de nodige aandacht te hebben voor het nauwkeurig inschatten van de langdurige
persoonlijke blootsteling.

Voor welke populatie zijn de resultaten representatief?
De studie is enkel representatief voor personen met diabetes (ongeveer 10% van de
algemene bevolking heeft diabetes).

Werden er dosis-effect verbanden gevonden?
De gevonden associaties bleken lineair te zijn en leverde dus geen bewijs voor een drempel
waarop geen effecten optreden voor de bestudeerde eindpunten.

Werd er klinische relevantie vastgesteld bij blootstellingswaarden die relevant zijn voor
Vlaanderen?
Het vinden van klinisch betekenisvolle effecten bij een gevoelig segment van de bevolking
toont aan dat het zinvol is om maatregelen te nemen die pieken van fijn stof voorkomen naast
het terugdringen van het jaargemiddelde. Onze gegevens tonen aan dat zowel de chronische
als de acute blootstelling de plaatjesfunctie beïnvloedt. Onze resultaten tonen verder de
relevantie aan om maatregelen te nemen tegen blootstelling aan sigarettenrook. De klinische
relevantie werd aangetoond door de effecten van fijn stof te vergelijken met 1/de gunstig
effecten van specifieke medicatie (asaflow) op de plaatjesfunctie; 2/de effecten van de
stijging in geoxideerd-LDL in associatie met PM te vergelijken met prospectieve studies over
geoxideerd-LDL en het ontstaan van atherosclerotische plaques.

Is er een bron gekend voor de blootstelling? Ja, wellicht vooral emissies van het verkeer op
grond van de koostofmetingen in longmacrofagen.

Is de opnameroute gekend? Ja, inhalatoir.

Blijven er veel wetenschappelijke/analytische onzekerheden? Er bestaan nog vele onzekerheid
met de juiste oorsprong van de blootstelling desondanks hebben we een deel van de
onzekerheden weggenomen door de blootstelling in te schatten door het meten van de
koolstoflading in longmacrofagen. Dit voorkomt namelijk voor een deel
blootstellingsmisclassificatie met name bij het schatten van langdurige blootstelling.

Werden er gelijkaardige resultaten gevonden in internationale wetenschappelijke literatuur? Er
zijn geen eerdere studies die specifiek naar plaatjesfunctie ‘ex-vivo’ keken en ook geen
studies die geoxideerd-LDL bestudeerden waarbij de blootstelling werd gemeten via de
koolstoflading van longmacrofagen. De resultaten zijn wel in lijn met de literatuur bv met
studies bij muizen en het ontstaan van atherosclerose alsook ander epidemiologisch
onderzoek (MESA-cohort). De relevante literatuur werd bediscussieerd in het rapport.

Is er een attributieve factor gekend?
100 
Samenvatting Er is een attributieve factor van PM voor het triggeren van hart- en vaatziekten gekend
(Nawrot et al. Lancet 2011). Deze vraag is echter niet van toepassing op de intermediaire
parameters die hier werden bestudeerd, gezien er niet naar ‘harde’ klinische eindpunten werd
gekeken.
Bieden de resultaten mogelijkheid voor een monetaire inschatting? Gedeeltelijk wel, al zal het
moeilijk zijn om vanuit deze intermediaire eindpunten (plaatsjesfunctie en geoxideerd-LDL) en
hun verandering een juist monetair effect te kunnen inschatten.

Werden de resultaten reeds gebruikt of bieden ze toekomstperspectief als basis voor
beleidsmaatregelen in Vlaanderen of (inter)nationaal?
De resultaten zijn relevant voor normering af te stemmen waarbij rekening wordt gehouden
met een gevoelige groep binnen de algemene bevolking. Zie ook Lancet Nawrot et al. 2011
waarbij een inschatting wordt gemaakt voor het aandeel van myocardinfarct door fijn stof.

Zijn de gemaakte aanbevelingen afdoende vertaald van een (strikt) wetenschappelijke naar
een beleidsmatige context?
Beleidsmatige context:
–
–
Het is mogelijk van klinisch belang om bij de meest gevoelige groep medicatie met
anticoagulerende eigenschappen op te drijven tijdens periodes van hoge fijn stof
blootstelling.
Verder zou de patiënt extra aandachtig moeten zijn en tijdens periodes met hoge PM
concentratie nog meer dan anders therapietrouw te zijn aan de voorgeschreven
medicatie.