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Pharmacologically-induced changes in the concentration of high density lipoprotein cholesterol and the… Tancon, Scott MacKenzie Alber 2004

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PHARMACOLOGICALLY-INDUCED CHANGES IN THE CONCENTRATION OF HIGH DENSITY LIPOPROTEIN CHOLESTEROL AND THE RELATIONSHIP WITH CHOLESTEROL EFFLUX by SCOTT MacKENZIE ALBERT TANCON B.Sc.(Hon.), University of British Columbia, 1996 B.Sc, University of Victoria, 1999 A THESIS SUBMITTED IN PARTIAL FULFILMENT OF THE REQUIREMENT FOR THE DEGREE OF MASTER OF SCIENCE in THE FACULTY OF GRADUATE STUDIES (Department of Pathology and Laboratory Medicine) We accept this thesis as conforming to the required standard THE UNIVERSITY OF BRITISH COLUMBIA October 2004 © Scott MacKenzie Albert Tancon, 2004 JUBCl THE UNIVERSITY OF BRITISH COLUMBIA FACULTY OF GRADUATE STUDIES Library Authorization In present ing this thesis in partial fulf i l lment of the requirements for an advanced degree at the University of British Columbia, I agree that the Library shall make it freely avai lable for reference and study. I further agree that permission for extensive copying of this thesis for scholar ly purposes may be granted by the head of my depar tment or by his or her representat ives. It is understood that copying or publ icat ion of this thesis for f inancial gain shall not be al lowed without my writ ten permission. S c o t t W ^ c V ^ ^ e . ftugeie.' \ptt^c^rsA N a m e of Author (please print) _i _i / i / \ Date (dd/mm/yyyy) Title of Thesis: rVvftg.(Y\flcol<aC^CQH.l>( ' 1«^CKxcj£o C > t A ^ G - £ s T k £ C o t X ^ T g f t T f t rJ Degree: Depar tment of The Universi ty of British Co lumbia Vancouver , BC C a n a d a grad.ubc.ca/forms/?formlD=THS page 1 of 1 last updated: 20-Jul-04 ABSTRACT Low concentrations of high-density lipoprotein cholesterol (HDL-C) have been associated with increased risk of atherosclerosis in clinical trials, and pathological, genetic, and epidemiological studies. High-density lipoproteins (HDL) have numerous anti-atherogenic properties; however, the process of removing excess cholesterol from lipid-laden macrophages (Reverse Cholesterol Transport (RCT)) is believed to be the predominant mechanism of cardioprotection. Cholesterol efflux, the first step in RCT, is presumed to be the rate-limiting step and has been extensively studied. Cholesterol efflux is influenced by both the quality and quantity of HDL. Physicians use the clinical measure of HDL-C in assessing patient risk of coronary artery disease. Numerous pharmacological agents can alter HDL-C; however, the effect of these changes on cholesterol efflux has been poorly studied. The present study attempts to measure the functional properties (defined herein as "quality") of HDL in patients with pharmacologically-induced changes in HDL-C, in terms of each particle's ability to promote cholesterol efflux from cells. Most studies have measured cholesterol efflux potential at only a single serum concentration, which fails to differentiate between potential differences in quantity and quality. We use serum dose-response curves to measure cholesterol efflux potential from Fu5AH cells and define the affinity constant, apparent Km, as being a good measure of quality. Twenty-three healthy control subjects were recruited to develop normal ranges for the parameter apparent Km. Finally, forty-three experimental subjects were assigned to one of four experimental groups: high pharmacologically-induced HDL-C (>1.55 mmol/L), high non-pharmacologically-induced HDL-C, low pharmacologically-induced HDL-C (<1.04 mmol/L) and low non-pharmacologically-induced HDL-C. Sera were assayed for fractional esterification rates of the HDL fraction (FER HDL) and serum dose-response curves in cholesterol efflux studies. The intra-assay and inter-assay coefficients of variation (CV) for apparent K m measurements were 6.5% and 20.5%, respectively. A pooled sera standard was included to control for differences between assay days; and the maximal rate of efflux (apparent V m a x) and apparent K m values were calculated relative to this standard. Relative to a pooled sera standard, the apparent V m a x values ranged from 83% -112% in healthy subjects. Two patients with familial LCAT deficiency exhibited 67.4% and ii 62.6% reductions in apparent V m a x , and serum treated with DTNB (an effective LCAT inhibitor) exhibited a 90.2% reduction in apparent V m a x , suggesting a possible role of apparent V m a x in diagnosing HDL-associated genetic defects. These studies demonstrated that the quality of HDL particles changes with HDL-C. Relative apparent Km values (per particle) increase with increasing HDL-C, whereas FERHDL decreases as HDL-C increases. These are compatible findings; smaller HDL have been shown to promote cholesterol efflux from Fu5AH cells to a greater extent than larger HDL. It was hypothesized that HDL quality is a more predominant factor than HDL quantity in determining the rate of cholesterol efflux in vivo; however, this does not seem to be the case if RCT is the major anti-atherogenic property of HDL, since quality cannot account for the epidemiological data. The data suggest that HDL-C is still a good predictor of the cholesterol efflux potential of serum and quality of HDL particles when HDL-C>1.04 mmol/L, regardless of pharmacological intervention. However, patients with pharmacologically-induced changes in HDL-C when HDL-C<1.04 mmol/L, have qualitatively different HDL particles than subjects with matched HDL-C and no pharmacologically-induced change, and may have to be evaluated in a different context. TABLE OF CONTENTS ABSTRACT '. ii TABLE OF CONTENTS ••• iv LIST OF TABLES ix LIST OF FIGURES x ABBREVIATIONS xi PREFACE xiii ACKNOWLEDGEMENTS xiv DEDICATION. xv 1 INTRODUCTION 1 1.1 Atherosclerosis 1 1.1.1 Lesion Formation, Advanced Lesions and Thrombosis 1 1.1.2 Risk Factors 3 1.2 Lipoprotein Metabolism 4 1.2.1 Structure and Classes of Lipoproteins 4 1.2.2 Exogenous Pathway 7 1.2.3 Endogenous Pathway 10 1.3 High-Density Lipoprotein Particles 10 1.3.1 HDL Subclasses 10 1.3.2 Cardioprotective Properties of HDL 12 1.4 Reverse Cholesterol Transport 12 1.4.1 Cholesterol Efflux 14 1.4.1.1 Cellular Cholesterol Distribution. 14 1.4.1.2 Mechanisms of Efflux 15 1.4.1.2.1 Simple Diffusion... 15 1.4.1.2.2 Facilitated Diffusion 15 1.4.1.2.3 Active Transport 18 1.4.1.3 Relative Contribution of SR-BI and ABCA1 -Mediated Efflux 20 1.4.2 Lecithin:Cholesteryl Acyltransferase 21 1.4.3 Phospholipid Transfer Protein 22 1.4.4 Cholesteryl Ester Transfer Protein 22 1.4.5 Cholesterol and Phospholipid Uptake by Hepatocytes 23 iv . . . 1.5 Clinical Measurements of HDL-C 24 1.5.1 Population Variations in HDL-C. 24 1.5.2 Genetic Abnormalities Causing Hypoalphalipoproteinemia 25 1.5.2.1 Tangier Disease 25 1.5.2.2 ApoA-l Deficiencies 25 1.5.2.3 Familial LCAT Deficiency 26 1.5.2.4 Fish-Eye Disease 26 1.5.2.5 Lipoprotein Lipase Deficiency 26 1.5.3 Genetic Abnormalities Causing Hyperalphalipoproteinemia 27 1.5.3.1 CETP Deficiency . 27 1.5.3.2 HL Deficiency 28 1.6 Pharmacologically-Induced Changes in HDL-C Values 28 1.6.1 Pharmacological Agents that Alter HDL-C 28 1.6.1.1 Niacin 29 1.6.1.2 Fibric Acid Derivatives 29 1.6.1.3 Statins.. 29 1.6.1.4 Thiazolidinediones 29 1.6.1.5 HIV Antiretroviral Therapy 30 1.6.1.6 Thiazide Diuretics, Beta-blockers, and Progestational Agents...30 1.6.1.7 Future Therapies 30 1.6.2 Effects of Pharmacological Agents on Cholesterol Efflux 31 1.7 Rationale and Hypothesis 31 1.8 Selection of the Fu5AH Cell Line 33 1.9 Specific Aims 34 1.9.1 Part I: Optimization of the Fu5AH Cholesterol Efflux Assay 34 1.9.2 Part II: Defining Parameters to Measure Function 35 1.9.3 Part III: Recruitment and Testing of Patient Sera 35 2 MATERIALS AND METHODS 36 2.1 Cell Culture 36 v 2.2 Cholesterol Efflux Assay 36 2.2.1 Day 1: Seeding of Cells 36 2.2.2 Day 3: Radiolabeling of Cells 36 2.2.3 Day 5: Equilibration of the Cellular Cholesterol Pools 37 2.2.4 Day 6: Assaying Serum Samples 37 2.3 Extraction of Lipids from Cells 38 2.4 Isolation of Lipids from Serum-Containing Media .....38 2.5 Fractional Esterification Rate ( F E R H D l ) 38 2.6 Thin Layer Chromatography 38 2.7 DTNB Treatment of Serum 39 2.8 Recruitment of Study Participants 39 2.8.1 Obtaining of Serum Samples 39 2.8.2 Lipid Profiling of Serum Samples 40 2.8.3 Chart Analysis 41 2.8.4 Assignment of Patients to Experimental Groups 41 2.9 Data Analyses 41 2.9.1 Dose-Response Curve Analysis 41 2.9.2 Statistical Analyses 42 RESULTS 43 3.1 Optimization of the Fu5AH Cell Line Cholesterol Efflux Assay 43 3.1,1 Conversion of Unesterified Cholesterol to Metabolic Products during Cell Preparation 43 3A .2 Optimization of the Extraction of Cell Lipids 44 3.1.3 Radioisotope Accounting 47 3.1.4 Optimal Assay Length 47 3.1.5 Percentage Efflux Coefficients of Variation ...50 3.1.6 Apparent Vmax and Km Coefficients of Variation 51 3.1.7 Stability of Frozen Sera 51 3.1.8 Post-Assay Wash 54 vi 3.2 Characterizing the Quality-Measuring Parameter of Km 54 3.2.1 Efflux in the Absence of Serum 54 3.2.2 Efflux from the Unesterified Cholesterol Pool 55 3.2.3 Recruitment of Healthy Controls 56 3.2.4 Effect of DTNB Inhibition of LCAT in Control Serum 57 3.2.5 Patients with Homozygous LCAT Deficiency 57 3.3 Study Population Characteristics 59 3.3.1 HDL-C Relationship to V m a x 59 3.3.2 HDL-C Relationship to Km 59 3.3.3 HDL-C Relationship to F E R H D L and TG 62 3.3.4 HDL-C Relationship to Efflux at a Single HDL-C Concentration. 62 3.4 Pharmacologically-Induced Changes in HDL-C 64 DISCUSSION 72 4.1 Optimization of the Fu5AH Cell Line Cholesterol Efflux Assay 72 4.1.1 Seeding the Cells 72 4.1.2 Radiolabeling the Cells 72 4.1.3 Equilibration of the Cellular Cholesterol Pools 73 4.1.4 Initial Rates of Efflux 73 4.1.5 Consistency of Dose-Response Curve Parameters 74 4.1.6 Stability of Frozen Sera 74 4.2 Characterizing the Quality-Measuring Parameter of Km 75 4.2.1 Net Cholesterol Flux 75 4.2.2 Range of Apparent V m a x and Km Values in Healthy Individuals 76 4.2.3 The Effects of LCAT Inhibition on Cholesterol Efflux 77 4.2.4 Homozygous Familial LCAT Deficiency 77 4.2.5 Limitations of Km in Assessing HDL Quality 78 4.3 Study Population Characteristics 79 4.3.1 Study Population Characteristics of Apparent V m a x 79 4.3.2 Study Population Characteristics of Apparent Km 79 4.3.3 HDL-C Relationships with FER H DL and TG 80 4.3.4 Km Compared to the Efflux Ability at a Single Concentration 81 4.4 Pharmacologically-Induced Changes in HDL-C 81 vii 5 REFERENCES 85 6 APPENDICES, 114 6.1 Appendix A: Group I Serum Dose-Response Curves 114 6.2 Appendix B: Group II Serum Dose-Response Curves 117 6.3 Appendix C: Group III Serum Dose-Response Curves 120 6.4 Appendix D: Group IV Serum Dose-Response Curves 124 6.5 Appendix E: CV Distributions of Triplicate Measures for All Assays..127 viii LIST OF TABLES Table 1. Major classes of human lipoproteins and their constituents ....5 Table 2. Percentage uptake of radiolabel by Fu5AH cells 43 Table 3. Assessment of three different techniques for lipid extraction 44 Table 4. Intra-assay and inter-assay coefficients of variation 51 Table 5. Source of effluxed cholesterol 55 Table 6. Characteristics of healthy controls 56 Table?. Lipid profiles of two LCAT"7" patients 57 Table 8. Characteristics of patient groups 65 ix LIST OF FIGURES Figure 1. Response-to-injury hypothesis of atherogenesis 2 Figure 2. Density versus diameter of lipoprotein subclasses 6 Figure 3. The exogenous pathway 8 Figure 4. The endogenous pathway 11 Figure 5. Reverse cholesterol transport 13 Figure 6. Mechanisms of efflux 16 Figure 7. Rates of isopropanol evaporation from 6-well plates 46 Figure 8. Repeated extractions using the drying method 46 Figure 9. Accounting of radioactive label 48 Figure 10. Variations in assay length for three different sera 49 Figure 11. Variations in assay length for different serum concentrations 50 Figure 12. Intra-assay and inter-assay reproducibility 52 Figure 13. Relation between relative apparent Km values for fresh and frozen sera 53 Figure 14. Dose response curve of DTNB-treated serum 58 Figure 15. Dose response curves for two LCAT7" patients 58 Figure 16. HDL-C relationships to relative apparent V m a x ••• 60 Figure 17. HDL-C relationship to relative apparent Km 61 Figure 18. HDL-C relationship to FERHDL and TG 63 Figure 19. HDL-C relationship to 0.075 mmol/L relative efflux. 64 Figure 20. Relative apparent V m a x comparison between groups III and IV 66 Figure 21. Relative apparent Km comparison between groups III and IV 67 Figure 22. Relative apparent 0.075 mM efflux comparison between groups III and IV 68 Figure 23. Relative apparent V m a x comparison between groups I and II 69 Figure 24. Relative apparent Km comparison between groups I and II 70 Figure 25. Relative apparent 0.075 mM efflux comparison between groups I and II 71 x ABBREVIATIONS ABC Adenosine triphosphate-binding cassette transporter ACAT Acyl CoA:cholesterol acyltransferase ADP Adenosine diphosphate ANCOVA Analysis of covariance ANOVA Analysis of variance apo Apolipoprotein ATP Adenosine triphosphate BMI Body mass index BSA Bovine serum albumin CAD Coronary artery disease CE Cholesteryl ester CETP Cholesteryl ester transfer protein CHCI3 Chloroform C 0 2 Carbon dioxide cpm Counts per minute CV Coefficient of variation DMEM Dulbecco's modified eagle's medium DTNB 5,5'-dithio-b/'s-(2-nitrobenzoic acid) E R Endoplasmic reticulum FFA Free fatty acids FBS Fetal bovine serum FERHDL Fractional esterification rate in VLDL/LDL-depleted serum HDL High-density lipoprotein HDL-C High-density lipoprotein cholesterol HL Hepatic lipase HMG-CoA 3-hydroxy-3-methylglufaryl coenzyme A IDL Intermediate-density lipoprotein Km Concentration of HDL-C at which v 0 = 1/2(Vm ax) LCAT Lecithimcholesterol acyl transferase LCAT"7" Homozygous for LCAT deficiency LDL Low-density lipoprotein xi LDL-C Low-density lipoprotein cholesterol LPL Lipoprotein lipase MeOH Methanol MgCI2 Magnesium chloride MTP Microsomal triglyceride transfer protein NaOH Sodium hydroxide NC Not calculated NO Nitric oxide PBS Phosphate-buffered saline PC Phosphatidylcholine Pi Inorganic phosphate PL Phospholipid PLTP Phospholipid transfer protein PPAR Peroxisome proliferator-activated receptor PTA Phosphotungstic acid RCT Reverse cholesterol transport rpm Revolutions per minute SCM Serum-containing medium SD Standard deviation SM Sphingomyelin SR-BI Scavenger receptor, class B type 1 SST Serum separator tube TC Total cholesterol TG Triglyceride TLC Thin layer chromatography TZD Thiazolidinedione UC Unesterified cholesterol VLDL Very low-density lipoprotein Vmax Maximal initial rate of efflux V 0 Initial rate of efflux xii PREFACE This thesis borrows from the concepts of enzyme kinetics by using the parameters Km and V m a x to describe serum dose-response curves. Although the curves can be described quite accurately using Michaelis-Menten kinetics, it should be noted that the parameters K m and V m a x are not defined as they are in enzyme kinetics. The cholesterol efflux system is very complex and can be influenced by many factors that do not normally apply to classical enzyme kinetics. The traditional Km definition of affinity is loosely applied here, but in terms of the assay model, it is described as the affinity of the acceptor particle for unesterified cholesterol, rather than the affinity of an enzyme for a certain substrate. The work enclosed was initiated after many observations by Dr. Greg Bondy in the St. Paul's Hospital Lipid Clinic. He observed that certain patients being treated with both PPAR-a and PPAR-y agonists paradoxically have reduced HDL-C values. To the best of our knowledge, it has not been described if these reduced HDL-C values can be interpreted in the same way as naturally low HDL-C values. xiii ACKNOWLEDGEMENTS I would like to thank all those who helped in the preparation of this thesis. First and foremost, I thank my supervisor, Dr. Greg Bondy, for his continued support and patience throughout this process. As well, the assistance of Dr. Bondy and Dr. Jiri Frohlich in the recruitment of patients for this study was invaluable. I also highly appreciate the guidance of my supervisory committee in the development of this thesis, with special recognition to Dr. Haydn Pritchard and Dr. John Hill for their assistance in the theoretical aspects and design of the laboratory work involved. Sincere gratitude is extended to the Clinical Trials staff at the Healthy Heart Program who assisted me in collecting serum samples (especially Stuart Gray), and to Ruth Grierson in the St. Paul's Lipid Laboratory for her work in lipid profiling patient serum. The support of all of my colleagues at the Atherosclerosis Specialty Laboratory was especially valued during many challenging times. Finally, I would like to thank my family who has continued to support my never-ending quest for more education, and the emotional support they continue to provide. xiv DEDICATION I dedicate this thesis to my soon-to-be wife, Mariko, who has strengthened me in times of hardship and shared with me in times of joy. Your support and understanding has been a foundation from which I have found stability during stressful times. I eagerly anticipate our future marriage and the creation of a loving family. Thank you. xv 1 INTRODUCTION 1.1 Atherosclerosis Atherosclerosis, the primary cause of heart disease and stroke, accounts for approximately 50% of all deaths in westernized societies [1]. It is characterized as a progressive disease, by which lipids and fibrous elements accumulate in large arteries, thereby constricting blood flow. 1.1.1 Lesion Formation, Advanced Lesions and Thrombosis Many initial animal studies of atherosclerotic initiation and progression led to the proposed response-to-injury hypothesis [2] in 1973. Since then, the hypothesis has been modified to centre around endothelial dysfunction [3]. Endothelial dysfunction is the initial "injury" described in the revised response-to-injury hypothesis [3] (Figure 1) and is characterized by the reduced bioavailability of endothelium-derived nitric oxide (NO) [4]. NO mediates endothelium-dependent vasodilation, inhibits leukocyte adhesion, limits platelet adhesion and aggregation, and decreases the expression of plasminogen activator inhibitor-1, which promotes thrombosis [5]. The first stages of atherosclerotic lesion development are characterized by increased endothelial permeability to lipoproteins, monocytes and T lymphocytes via increased expression of adhesion molecules. Once resident in the arterial intima, monocytes transform into macrophages, and increase expression of scavenger proteins such as scavenger receptor A and CD36. This increased expression leads to internalization of modified low-density lipoprotein (LDL), transforming these cells into lipid-laden "foam cells". The "foam cells" present in this initial "fatty streak" release cytokines that stimulate proliferation and migration of smooth-muscle cells that intermix with the area of inflammation to form "intermediate lesions". Foam cells also release cytokines that increase the recruitment of leukocytes to the lesion area and stimulate macrophage proliferation, thereby increasing the size of the lesion. The release of interferon-y and tumour necrosis factor-a by activated T cells and smooth-muscle cells may cause macrophages to undergo apoptosis. The cellular debris forms a necrotic core to the lesion. If the cycle continues unabated, the inflammation transforms from being protective to injurious. Under such circumstances, 1 ^ LDL Monocyte 1. Dysfunctioning endothelium increases the adhesion and permeability of low-density lipoproteins (LDL), monocytes, and T lymphocytes. Once in the intima, monocytes transform into macrophages 2. Modified LDL are taken up by macrophages to form 'loam cells Smooth-Muscle Cell 3. "Foam cells" stimulate the proliferation and migration of smooth-muscle cells into the intima 4. The continued migration of smooth-muscle cells and the aggregation of platelets lead to the formation of an advanced lesion characterized by a necrotic core 5. Erosion of the fibrous cap can lead to plaque rupture and subsequently a thrombotic event Figure 1. Response-to-injury hypothesis of atherogenesis. A schematic of the steps involved in lesion formation and its subsequent rupture. 2 the affected tissue undergoes a restructuring of the lesion through the adherence and aggregation of platelets leading to a fibrous cap, characteristic of "advanced lesions", that overlays the core of lipid and necrotic tissue. This cap essentially walls off the damage into what is known as a plaque. Plaques can increase in complexity through calcification and vascularization. It is the stability of the plaque rather than the severity of occlusion that seems to be the more critical factor in thrombosis. Advanced lesions can either exist as stable plaques, which are often non-occlusive and characterized by a thick fibrous cap, or vulnerable plaques that are at high risk of rupture. Myocardial infarction usually results from the erosion or uneven thinning and subsequent rupture of unstable fibrous caps. Plaque rupture is usually caused by continuing influx and activation of macrophages, or the hemorrhage of plaque microvessels that have grown into the lesion area. 1.1.2 Risk Factors Epidemiological studies have identified numerous genetic and environmental risk factors associated with atherosclerosis. The etiology of the disease is extremely complex with extensive cross-over between genetic and environmental components. It has been suggested that the genetic contribution to atherosclerosis determines the limits under which atherosclerosis develops, while environmental factors actually determine the risk within these limits [6]. The major independent risk factors for atherosclerosis are cigarette smoking, high blood pressure, age, elevated serum low density lipoprotein, cholesterol (LDL-C), low serum high density lipoprotein cholesterol (HDL-C), and diabetes mellitus [7]. Cholesterol has been linked with atherosclerosis for nearly one hundred years [8]. The reduction in LDL-C (in particular, using 3-hydroxy-3-methylglutaryl coenzyme A (HMG-CoA) reductase inhibitors) has been shown to reduce the incidence of cardiovascular events in many lipid-lowering trials [9-15]. Increased levels of LDL-C promote atherosclerosis by a variety of mechanisms. LDL particles are important contributors to lesion development due to their direct effects on lipid influx into the vessel wall [16]. Modified LDL can up-regulate the expression of macrophage colony-stimulating factor [17] and monocyte chemoattractant protein-1 [18], which further increase the inflammatory response by the recruitment of more monocytes and 3 macrophages. A preponderance of small, dense LDL is associated with a 3 to 7-fold increase in risk for coronary artery disease (CAD), independent of LDL-C concentration, largely due to the increased retention of these molecules in the sub-endothelial intima [19] and the fact they are more readily oxidized than larger LDL [20]. The results of the Veterans Affairs High Density Lipoprotein (HDL) Intervention Trial showed that an increase in HDL-C levels significantly decreases the incidence of CAD, independently of LDL-C concentrations [21]. In fact, an increase of 0.3 mmol/L in HDL-C has been estimated to reduce the risk of CAD by 3% [22] - a stronger reduction than any other lipid factor. The Prospective Cardiovascular Munster study has also shown this inverse relationship [23]. Several HDL-mediated cardioprotective mechanisms have been proposed and are discussed further in Section 1.3. Established risk factors are more prevalent in patients with diabetes mellitus and atherosclerosis accounts for almost 80% of all diabetes-related mortality [22]. Patients with non-insulin-dependent diabetes mellitus (Type II diabetes) generally have an atherogenic lipid profile consisting of elevated triglycerides (TG), low HDL-C, and smaller LDL particle size [24]. Physical inactivity and obesity are considered as major risk factors by the American Heart Association [25]. Other evidence-supported, independent risk factors include elevated levels of serum triglycerides, lipoprotein (a), homocysteine, and haemostatic factors; family history of premature CAD; depression and other psychosocial variables; metabolic syndrome; low anti-oxidant levels; a high-fat diet; systemic inflammation; and infectious agents such as Chlamydia pneumoniae or herpesvirus [26]. 1.2 Lipoprotein Metabolism 1.2.1 Structure and Classes of Lipoproteins Lipoproteins provide a means for non-polar lipids to be transported in the aqueous environment of the circulatory system. Mature lipoproteins are spherical particles with a hydrophilic exterior consisting of a monolayer of phospholipids (PL), unesterified cholesterol (UC) and apolipoproteins (apo), and a hydrophobic interior consisting of mainly cholesteryl esters (CE) and triglycerides. Lipoproteins vary greatly in size and density (Figure 2), and are named and divided into five major classes based 4 on their densities. Lipoprotein density is inversely proportional to size, due to the relative contents of the lower-density non-polar core lipids and higher-density surface proteins (Table 1). Apolipoproteins are the primary function-defining component on each lipoprotein, and the apolipoprotein make-up of each class differs (Table 1). Most of the apolipoproteins present in lipoproteins are amphipathic, often caused by the presence of numerous amphipathic oc-helices, and are thus, at least partially water soluble. The one major exception is the B apolipoproteins (B-48 and B-100). These proteins are derived from a single gene and contain large stretches of hydrophobic amino acid residues. Unlike all the other apolipoproteins, they are unable to be transferred between lipoprotein particles. Lipoprotein Major Apolipoproteins Protein T G T C P L Chylomicrons Apo A-l, A-ll, A-IV Apo B-48 ApoC-l, C-ll, C-lll ApoE 1% 90% 5% 4% VLDL ApoB-100 ApoC-l, C-ll, C-lll ApoE 10% 65% 13% 13% IDL ApoB-100 ApoC-l, C-ll, C-lll ApoE 18% 31% 22% 22% LDL ApoB-100 25% 10% 45% 23% HDL ApoA-l, A-ll, A-IV ApoC-l, C-ll, C-lll ApoE 50% 2% 18% 30% Table 1. Major classes of human lipoproteins and their constituents. 5 Figure 2. Density versus diameter of lipoprotein subclasses. Diameter increases and density decreases from the relatively cholesteryl ester-rich and triglyceride-poor HDL subclasses to the triglyceride-rich and cholesteryl ester-poor chylomicrons and very-low-density lipoproteins. A single lipoprotein does not obligatorily belong to one class; most lipoproteins can be remodeled into forming a particle of a different class. Chylomicrons, containing apoB-48, and very low-density lipoproteins (VLDL), containing apoB-100, are the largest and least dense lipoproteins, and are the only lipoproteins to be secreted in their mature form. Intermediate-density lipoproteins (IDL) and LDL particles result from VLDL metabolism, while HDL precursors can be synthesized by the liver and intestines. Other components of mature HDL are initially carried by chylomicrons. Lipoprotein (a) is an LDL particle bridged to a large, polymorphic glycoprotein (apo(a)) via disulfide bonds. The lipids contained in lipoproteins can be either obtained from the diet, or endogenously made; the majority of endogenous lipids are produced in hepatocytes. 1.2.2 Exogenous Pathway Cholesterol is a vital membrane component of all cells that helps to create membrane rigidity and prevent membrane crystallization. The total cholesterol content of a 70 kg adult is approximately 140 g of which only about 1% is metabolized daily [27]. The body is fully capable of synthesizing all of its cholesterol needs; however, the diet contains an additional source of cholesterol. The typical Western diet for an adult involves the daily absorption of 300 to 500 mg dietary cholesterol and 800 to 1200 mg of biliary cholesterol into enterocytes [28]. Depending on the food source, dietary cholesterol is predominantly in the form of UC, with a small proportion existing as CE. Dietary lipids present in the gastrointestinal tract are normally absorbed into enterocytes before being processed by the exogenous pathway (Figure 3). Triglycerides are energy-rich molecules that represent the most efficient form of energy storage. TG absorption begins with hydrolysis by lingual and gastric lipases in the stomach and pancreatic lipases in the intestinal lumen to yield free fatty acids (FFA) and monoglycerides [29]. These products form an emulsion in the small intestine that mixes with bile acid and phospholipids to create mixed micelles. Cholesteryl esters are first hydrolyzed by cholesterol esterase in the intestinal lumen to form FFA and UC [30]. UC has very low solubility in aqueous environments and requires the incorporation into mixed micelles to diffuse across the unstirred water layer that lies between the mucosal cell membrane and bulk water phase [31]. Micelle disaggregation occurs at the brush border membrane where lipid uptake is mediated by 7 A / V W S A A A A A A A A A A Cholesteryl Esters Triglycerides 4 Unesterified Cholesterol V Lipases Cholesterol esterase A A A A A A A A A A Free Fatty Acids ^ Mixed Micelle uc Bile acid FFA Intestinal Lumen Brush Border Membrane 1 A C A T 2 M T P U C i ^ ^ ^ - C E Enterocyte Via lymph to circulation Figure 3. The exogenous pathway. Dietary lipids are digested by lipases and cholesterol esterase into unesterified cholesterol (UC) and free fatty acids (FFA). These products form an emulsion in the intestinal lumen with bile acids released from the liver creating mixed micelles. The contents of mixed micelles are absorbed through the brush border membrane. UC in the enterocyte is re-esterified by ACAT2 and packaged with triglycerides (TG) into chylomicrons by MTP. Chylomicrons travel via the lymph to the circulation where TG and PL are hydrolyzed by LPL and HL. Chylomicron remnants are taken up by hepatocytes via the LDL receptor or LDL receptor-related protein. 8 unknown proteins. Some evidence suggests scavenger receptor class B, type I (SR-BI) -is the major transporter responsible for UC absorption [32, 33], although recent evidence using the pharmacological agent, ezetimibe, and SR-BI knock-out mice suggests it is not a major contributor [34, 35]. Two half transporters have also been recently discovered belonging to the adenosine triphosphate-binding cassette transporter (ABC) family (ABCG5 and ABCG8) that seem to be responsible for the efflux of plant and shellfish sterols from the enterocyte back to the intestinal lumen and explains the net selectivity of UC absorption over other sterols [36, 37]. ABCG5 and ABCG8 are also responsible for the release of cholesterol into bile in hepatocytes [38]. Once lipids have entered the enterocyte, they migrate to the endoplasmic reticulum (ER) where UC is re-esterified by acyl CoA:cholesterol acyltransferase-2 (ACAT2) [39]. This newly formed CE, combines with apoB-48, UC, triglycerides and the A apolipoproteins to form nascent chylomicrons that are excreted into the lymph - an assembly mediated by microsomal triglyceride transfer protein (MTP) in the Golgi apparatus [40]. Once in the blood plasma, chylomicrons may acquire apoC-l, apoC-ll, apoC-lll, and apoE from HDL particles [41]. Chylomicrons can activate, via apoC-ll, lipoprotein lipase (LPL), expressed on many peripheral cell types including skeletal muscles, adipocytes, and macrophages [42]. This lipase induces rapid hydrolysis of the TG contained within the particle, and the FFA products are taken up by the peripheral cells for either storage or energy utilization. During TG hydrolysis, the chylomicron sheds excess phospholipids and the A apolipoproteins by concomitant transfer to HDL. As well, chylomicrons lose their affinity for the C apolipoproteins as they decrease in size and these proteins are also transferred to HDL particles. The resulting chylomicron remnant can be further depleted of lipids by hepatic lipase (HL). The loss of apoC-l, combined with the decreased particle size allows the remnants to pass through the endothelial fenestrae and be taken up by hepatocytes via LDL receptor or LDL receptor-related protein-mediated endocytosis - a process requiring the presence of apoE [43]. Remnant particles are then metabolized within the hepatocyte with the exception of cholesterol which can undergo many metabolic fates. 9 1.2.3 Endogenous Pathway All cells are capable of producing cholesterol; however, the majority of de novo cholesterol is created in the hepatocyte. In the hepatocyte, this newly formed cholesterol, along with acquired cholesterol from chylomicron remnants, can be metabolized into bile acids and secreted into bile, incorporated into nascent lipoproteins, oxidized into products that control further cholesterol synthesis, or esterified into CE and stored in intracellular lipid droplets. Nascent lipoproteins in the form of VLDL are exported to the circulation for delivery of components to the peripheral cells (Figure 4). VLDL are important in the export of excess TG from hepatocytes. VLDL are produced much in the same way as chylomicrons with an absolute requirement of MTP and apoB-100 for successful secretion into the circulation [44]. VLDL can also acquire additional C and E apolipoproteins from HDL once in the circulation [41]. VLDL metabolism in the plasma is also like that of chylomicrons. The triglycerides contained within are hydrolyzed by LPL to form smaller VLDL remnants or IDL. As particles decrease in size, the C apolipoproteins are once again transferred to HDL, as well as some apoE. The loss of apoE accounts for the longer resident times in the circulation for smaller apoB-containing particles. VLDL remnants and IDL can be taken up by, hepatocytes through the LDL receptor, or further hydrolyzed by HL to form the smaller pro-atherogenic LDL particles [45]. LDL particles have by far the longest resident time in the circulation (approximately 3 days) before uptake by the LDL receptor. 1.3 High-Density Lipoprotein Particles 1.3.1 HDL Subclasses The class of HDL particles can be subdivided into subclasses based on either their density, size, or apolipoprotein content [46]. Mature HDL divided by ultracentrifugation (on the basis of density) have been separated into two main subclasses HDL2 {d= 1.063 - 1.125 g/mL) and HDL3 (d= 1.125 - 1.250 g/mL), but these subclasses can be further subdivided (on the basis of size) by non-denaturing gradient polyacrylamide gel electrophoresis (HDL2b, HDL 2 a , H D U a , HDL3 b, and HDL3 c, in order of decreasing size). The larger, less dense HDL2 particles are generally 10 Vascular Endothelium Figure 4. The endogenous pathway. The liver synthesizes the majority of de novo unesterified cholesterol. Newly synthesized cholesterol can be: (1) packaged with TG into VLDL by MTP and then exported to the circulation; (2) released into the intestinal lumen as bile acids for excretion; or (3) esterified by ACAT to form cholesteryl esters (CE) that are stored in lipid droplets. VLDL deliver free fatty acids to peripheral tissue after the hydrolysis of triglycerides by lipoprotein lipase (LPL). The resultant IDL can be either taken up by hepatocytes by the LDL receptor or further hydrolyzed by hepatic lipase (HL) to form LDL. 11 believed to be more atheroprotective than the smaller HDL3 particles [47]. Mature HDL divided by immunoaffinity chromatography have been separated based on their apoA-l and apoA-ll content. ApoA-l is present on all mature HDL, whereas approximately 60% of mature HDL contain apoA-ll [48]. The two subclasses are therefore designated LpA-l and LpA-l:A-ll. All mature forms of HDL migrate with a-electrophoretic mobility. Nascent HDL particles are lipid-poor, and usually consist of one or two apolipoproteins and a few molecules of sphingomyelin (SM) and phosphatidylcholine (PC) [46]. These precursors to mature HDL migrate with pre-(3-electrophoretic mobility, and can be classified based on their increasing size as pre-p rHDL, pre-p2-HDL, or pre-p3-HDL. 1.3.2 Cardioprotective Properties of HDL Extrahepatic cells lack the ability to catabolize cholesterol. HDL, through a process called Reverse Cholesterol Transport, is able to remove cholesterol from these cells and deliver it back to the liver or steroidogenic tissues for further processing. HDL are also able to induce the removal of cholesterol from macrophages, and is generally considered the main reason for the anti-atherogenic associations of HDL. More recently, other cardioprotective properties of HDL have been proposed: inhibition of LDL oxidation [49-53], restoration of endothelial function [54-59], anti-inflammatory [60-63], antithrombotic and profibrinolytic [64-70], and mitogenic properties [64, 71, 72]. 1.4 Reverse Cholesterol Transport Glomset initially proposed the concept of Reverse Cholesterol Transport (RCT) in 1968 [73], after discovering the major role of lecithin:cholesterol acytransferase (LCAT) in esterifying cholesterol into the HDL fraction a few years prior [74]. He proposed RCT to be the means of delivery for cholesterol from peripheral cells to the liver. Since then, the concept of RCT has grown in complexity with the discovery of the involvement of many different enzymes. RCT from lipid-laden macrophages is still generally accepted as being the major method by which HDL exerts its anti-atherogenic potential (Figure 5). 12 Figure 5. Reverse cholesterol transport. Cholesterol released from peripheral cells or macrophages is taken up by lipid-free apoA-l or HDL particles. UC is converted to CE via the action of LCAT to form mature HDL3 particles. PLTP and LCAT reorganize the PL and UC creating larger HDL2 particles. Cholesterol is delivered to the liver for excretion in bile by one of two pathways: CETP-mediated exchange of TG and CE between HDL particles and apoB-containing lipoproteins, followed by the uptake of these particles by the LDL receptor, or LDL receptor-related protein; or selective uptake of CE from HDL particles via SR-BI and HL. Lipid-free apoA-l and prep-HDL particles are regenerated during PLTP rearrangement, or PL hydrolysis by HL or LPL. 1.4.1 Cholesterol Efflux The first step in RCT is the efflux of cholesterol from the peripheral cell to an extracellular carrier. This process has been shown to be quite complex differing among different cell types and involving more than one pool of effluxable cholesterol. 1.4.1.1 Cellular Cholesterol Distribution Cholesterol can be synthesized in the ER of all nucleated cells and then distributed to specific membranes. Cholesterol provides rigidity to membranes enabling the membrane to maintain its critical function as a barrier to the environment and to segregate proteins [75]. However, a membrane must still be able to perform various functions such as vesicle fusion and fission. This is achieved by uneven distributions of the lipids on the membrane. The plasma membrane has been estimated to contain 65-80% of the cellular cholesterol [76] and is more cholesterol and sphingomyelin-rich than intracellular membranes, with the exception of the trans-Go\g\ network, which has a comparable distribution [77]. Cholesterol is not a static molecule; the entire plasma membrane cholesterol pool is cycled to the ER and back in an estimated half-time of 40 minutes [78]. The plasma membrane also has an assymetrical distribution of cholesterol between the inner and outer leaflets. The relative distribution is a topic of debate, and seems to be cell specific, but the exofacial leaflet in the majority of cells has been estimated at only 3-5% of the cell's total UC [79]. The lateral cholesterol distribution on the plasma membrane is also uneven. Cholesterol tends to concentrate more in lipid rafts and caveolae, and is relatively absent from clathrin-coated pits [75, 79]. This phenomenon is best explained by the high affinity of cholesterol for sphingolipids and certain proteins such as caveolin [80, 81]. Segregated cholesterol domains may help to produce different concentration gradients on the same plasma membranes, particularly in cells like hepatocytes. Nascent cholesterol synthesized in the ER is preferentially esterified by ACAT to form CE [82]; excess UC is toxic to a cell [83]. CE is stored in cytoplasmic lipid droplets and is in rapid equilibrium with the cell's regulatory pool of UC through the activity of neutral cholesterol esterase [84]. UC can be transported from the ER to the plasma membrane by Golgi (assembly of lipid rafts) and Golgi-independent mechanisms [85]. 14 1.4.1.2 Mechanisms of Efflux There are three known distinctly different mechanisms (Figure 6) for the desorption of UC from the plasma membrane to an extracellular particle: simple diffusion, facilitated diffusion, and active transport. 1.4.1.2.1 Simple Diffusion The simplest of the three mechanisms of cholesterol efflux is simple diffusion. , Synthetic cyclodextrins and protein-free phospholipids vesicles can induce a slow and unsaturable cholesterol efflux from all cell types [86]. Cholesterol is sufficiently water soluble to be able to diffuse across the unstirred water layer that immediately surrounds membranes [87]. This efflux is independent of intracellular vesicular transport and does not involve any plasma membrane proteins [86]. Simple diffusion is dependent on the concentration and structure of the acceptor particle and is driven by the concentration gradient [87]. Small particles are more efficient acceptors of cholesterol in a simple diffusion process because they can diffuse closer to the plasma membrane [88]. When cholesterol-containing acceptor particles are presented to plasma membranes, a bi-directional flux occurs, regardless of the net transfer [89]. 1.4.1.2.2 Facilitated Diffusion Because of its polar head group, UC does not readily diffuse from the cytofacial leaflet to the exofacial leaflet; therefore, a transport protein is required to mediate any rapid transfers. There are large differences in the rates of cholesterol efflux from different cells [86], directly attributable to the level of SR-BI expression [90, 91]. SR-BI was originally identified for its key role in CE uptake in hepatocytes and steroidogenic tissues [92] (discussed further in Section 1.4.5). However, SR-BI can also facilitate the bi-directional flux of UC, with net flux being dependent on the direction of the cholesterol gradient [93]. SR-BI was discovered a decade ago as a scavenger receptor with 30% homology to the CD36 family of proteins [94]. It consists of a large heavily-glycosylated extracellular domain and two transmembrane domains at each terminus 15 Figure 6. Mechanisms of efflux. Three mechanisms of cholesterol efflux to extracellular acceptors are currently known. Active transport involves the transport of unesterified cholesterol (UC) and phospholipid (PL) across the membrane to lipid-poor acceptor particles - a process driven by ATP hydrolysis . Net cholesterol flux in passive diffusion and facilitated diffusion depend on direction of the cholesterol concentration gradient. Passive diffusion is a slow dissociation of cholesterol from the exofacial leaflet, while SR-BI mediates a re-organization of unesterified cholesterol in the plasma membrane to create a much faster dissociation to PL-containing acceptor particles in facilitated diffusion. Cylinders represent a-helices. with very short cytoplasmic extensions [95, 96]. SR-BI/CD36 chimeric studies have shown the extracellular domain of SR-BI to be crucial for mediating the bidirectional flux of UC [97]. The exact mechanism of transfer is still under debate. De la Llera-Moya et al. [98] found UC flux could occur independently of acceptor binding, whereas Gu et al: [99] found that the binding of the extracellular acceptor to SR-BI is necessary for efflux to occur. In the former study, the authors suggest it is the re-organization of membrane lipids by SR-BI that facilitates the observed increased efflux. However, Gu et al. showed UC efflux is binding-dependent in conditions of low acceptor concentrations. A recent study verified that at low concentrations of acceptor molecules, UC efflux is predominantly binding-dependent, whereas when the binding to SR-BI is saturated, the rate of UC efflux becomes binding-independent [100]. There are currently three proposed mechanisms as to how lipid transfer occurs via SR-BI: (1) by hemi-fusion between the phospholipids monolayer of the extracellular particle and the exofacial leaflet of the plasma membrane [101]; (2) by formation of a non-aqueous channel, involving the extracellular domain of SR-BI, between the plasma membrane and extracellular particles through which cholesterol can travel down its concentration gradient [102]; (3) by a process of retroendocytosis in hepatocytes after which the particle is returned to the extracellular space [103]. Recent research has confirmed the existence of the retroendocytosis mechanism, although it was estimated to be a minor contributor to the total lipid exchange process [104]. The hemi-fusion mechanism was proposed to explain CE uptake; it seems unlikely that this process could occur for UC efflux. Therefore, the main mechanism of UC efflux is likely the hydrophobic channel mechanism, which is supported by other recent findings in SR-BI mutational studies [105, 106]. SR-BI does mediate a re-organization of membrane lipids [107]. Different kinetic pools of UC have been shown to exist [108], but their exact location on the plasma membrane remains to be elucidated. SR-BI expression increases the size of the fast kinetic pool [107] and increases the fraction of membrane cholesterol that is available for exogenous cholesterol oxidase [98]. It was originally assumed that SR-BI was important for the formation of caveolae after a portion of SR-BI was discovered to localize to these cholesterol-rich invaginations in the membrane [109, 110]. However, more recent evidence suggests that SR-BI localization in caveolae is not required for its 17 lipid transfer activities [111,112]. Also, a very recent study using fluorescence confocal microscopy has shown that SR-BI is clustered in cell-surface microvillar extensions of the plasma membrane, and not caveolae of lipid rafts [104]. The authors argue that SR-BI-mediated lipid flux would be energetically more favourable in a non-cholesterol-rich domain. SR-BI binds and mediates lipid exchange for a large variety of acceptor molecules including HDL, LDL, oxidized LDL, acetylated LDL, and small unilamellar vesicles [113]. Despite also binding lipid-free apoA-l, SR-BI does not facilitate any lipid exchange with this molecule; therefore, the presence of phospholipids is required for cholesterol efflux via this mechanism [98]. This concept has been supported by the findings that the rates of SR-BI-mediated efflux correlate better with the PL content of the HDL, than HDL-C or apolipoprotein content [114-117]. In fact, the exact phospholipids composition plays a key role in this process. HDL particles containing predominantly PC are a much better acceptor than those particles enriched with SM [117]. The apolipoprotein composition of the HDL has also been shown to be of importance. SR-BI has higher affinity for LpA-l:A-ll particles, but lipid transfer is mediated at a faster rate with LpA-l particles [118]. It has been shown that high affinity binding of HDL is insufficient to mediate lipid transfer [119]; correct orientation of apoA-l is required for optimal SR-BI-mediated lipid transfer [100, 119]. In accordance with this, it has been proposed that apoA-ll is a negative modulator of SR-BI-mediated efflux [120], perhaps by interfering with apoA-l orientation. The size of the acceptor particle has also been shown to affect the rate of efflux. When the PL content of particles is controlled for, small acceptor particles are more efficient acceptors of SR-BI-mediated cholesterol efflux than larger particles [121]. This is likely due to the increased ability of smaller particles to cross the unstirred water layer and access the cell membrane surface. 1.4.1.2.3 Active Transport The unidirectional transport of phospholipid (PL) and cholesterol to extracellular lipid-free apolipoproteins with the efficient reduction in cytosolic cholesterol esters was shown many years before the identification of the specific transporter [122-125]. This 18 mechanism is defective in Tangier disease [126], which led to the identification of the adenosine triphosphate-binding cassette (ABC) transporter A1 as being the defective transporter responsible [127-129]. ABCA1 belongs to a large family of adenosine triphosphate (ATP) binding cassette transporters that use the energy of ATP to transport a variety of substrates [130]. ABC transporters can exist as one molecule (full-size transporter) or as a two separate polypeptide chains (half transporters) that cooperate in order to function [131]. ABCA1 is a full-size transporter with two transmembrane domains of six a-helices each and two intracellular ATP-binding domains [131]. ABCA1 is also predicted to have two large highly-glycosylated extracellular loops located between a-helices 1 and 2, and a-helices 8 and 9 [132] that likely play a key role in apolipoprotein binding [133]. ABCA1 is not associated with membrane lipid rafts or caveolae [134], but do seem to be associated with distinct membrane domains enriched in cholesterol and unsaturated fatty acid-enriched PC [135]. The expression of ABCA1 is responsive to the amount of cholesterol in the cell, thereby allowing cells to regulate their cellular cholesterol content'[136]. All of the exchangeable apolipoproteins (A apolipoproteins, C apolipoproteins, and apoE) in lipid-poor form can act as extracellular acceptors for ABCA1 efflux of PL and UC [125, 137-140]. These apolipoproteins consist of 11 to 22 amino acid repeats of amphipathic a-helices that facilitate the removal of phospholipids from the cell surface to form disc-shaped, nascent HDL particles [132]. Mature HDL particles have also been shown to stimulate ABCA1 cholesterol efflux in some cases [141], but this has recently been suggested to be due to the dissociation of lipid-free apolipoproteins from these particles [142]. The mechanism of efflux is still unknown, but PL efflux has been generally accepted to either precede UC efflux, or happen simultaneously [87]. Other ABC transporters have been implicated in cholesterol efflux. As mentioned, the two half transporters ABCG5 and ABCG8 cooperate to efflux plant and shellfish sterols from the enterocyte back to the intestinal lumen [36, 37]. In addition, hepatic overexpression of these transporters resulted in increased biliary secretion [143]. Interestingly, two other transporters, ABCG1 and ABCG4, stimulate cholesterol efflux to mature HDL particles, but not lipid-free apolipoproteins [144]. These transporters may offer early protection from atherogenesis in macrophages when the 19 cholesterol content of the cells is still low and the concentration gradient is not sufficient for cholesterol efflux via SR-BI. 1.4.1.4 Relative Contribution of SR-BI and ABCA1 -Mediated Efflux The expression of SR-BI and ABCA1 is cell dependent. SR-BI is expressed at high levels in liver and steroidogenic cells where cholesteryl ester uptake is most important, and at lower levels in many other cell types including macrophage foam cells and endothelial cells [145]. ABCA1 is expressed highest in fetal tissues, placenta, liver, lung, small intestine, adrenal glands and brain [141, 146]. ABCA1 can be expressed in most cell types; in particular, oxidized LDL can upregulate ABCA1 expression in macrophages [147]. Therefore, in terms of protecting against atherosclerosis, SR-B1 and ABCA1-mediated cholesterol efflux are both functioning in the two sites of interest: macrophage-derived foam cells and the liver. The relative contribution of each mechanism is a current topic of debate. SR-BI-deficient mice have massive accumulations of cholesterol-rich HDL in their sera, and evidence of increased susceptibility to atherosclerosis in the arterial wall [148]. These observations indicate the importance of SR-BI in both macrophage and hepatocytes in protecting against atherosclerosis. Conversely, patients with mutations in ABCA1 (Tangier disease) also are more susceptible to premature atherosclerosis due to a severe deficiency or absence of HDL-C in the circulation [149], indicating ABCA1 also plays a major role in atherogenic protection in peripheral cells. In support of this, ABCA1 knockout mice show a lower level of efflux from peritoneal macrophages than wild-type mice [141]. In the liver, hepatic ABCA1 has been proposed to be a major determinant of plasma HDL-C [150]. This may seem counter-intuitive to the process of RCT; however, recent evidence suggests that nascent apolipoproteins produced by hepatocytes are lipidated to form HDL precursors that could further enhance peripheral cholesterol efflux [151]. As well, apoA-l interaction with hepatic ABCA1 decreases the secretion of VLDL particles in hepatocytes, presumably because intracellular cholesterol is diverted to the ABCA1 pathway [151]. It appears that both mechanisms act cooperatively in protecting against atherosclerosis. The only study to investigate the relative contribution of SR-BI and ABCA1 in the same experiment concluded that SR-BI inhibits ABCA1 -mediated 20 cholesterol efflux, but not phospholipids efflux from macrophages [152]. However, the formation of HDL precursors from lipid-poor apolipoproteins by ABCA1 is now presumed to be of key importance to SR-BI-mediated cholesterol efflux, which incidentally may be the faster mechanism of efflux in lipid-laden macrophages. 1.4.2 Lecithin:Cholesterol Acyl Transferase The second step in RCT is the esterification of UC by lecithin:cholesterol acyltransferase (LCAT) and its subsequent movement to the hydrophobic interior of the lipoprotein. This action prevents the diffusion of UC back to the cellular membrane and maintains a concentration gradient in favour of efflux in the case of the facilitated diffusion mechanism. A recent in vivo study indicates that more than 95% of CE in human plasma is a product of LCAT esterification in HDL [153]. LCAT, a 416 amino acid polypeptide chain, is synthesized predominantly in the liver where it is glycosylated before being secreted [154]. LCAT has some degree of solubility, but is more hydrophobic than plasma apolipoproteins. LCAT preferentially binds to HDL, with higher affinity for HDL3 particles than HDL2 particles, but has also been shown to bind to LDL with lower affinity [155]. The most efficient activator of LCAT is apoA-l; however, apoE, apoA-IV, apoD, and apoC-l have also been shown to activate LCAT, albeit less effectively [156, 157]. The presence of apoA-ll on an HDL particle significantly decreases LCAT's binding affinity [158]. LCAT catalyzes the transesterification reaction that converts UC and PC into CE and lysophosphatidylcholine, respectively [154]. Following the activation of LCAT by apoA-l, PC binds to the active site, and is cleaved into lysophosphatidylcholine. The cleaved acyl chain remains in the active site until it is transferred to UC. The rate-limiting step seems to be the initial binding of PC [159]. LCAT can also effectively utilize phosphatidylethanolamine as the acyl chain donor [160], whereas other sterols can act as acyl chain acceptors [161]. Evidence suggests that this series of reactions is reversible [162], although the reverse reaction operates at a much lower efficiency (10%) compared to the forward reaction. 21 1.4.3 Phospholipid Transfer Protein There is increasing need for PL as HDL particles increase in size via the insertion of CE into the hydrophobic interior by LCAT. PL efflux from the cell membrane initially sustains this need, but as particles become larger, their ability to interact with the cell membrane decreases. Therefore, an extracellular source of PL is needed. Phospholipid transfer protein (PLTP) is an enzyme that catalyzes the transfer of PL between lipoprotein particles, and is a key enzyme in the conversion of HDL3 to HDL2 [163, 164]. PLTP consists of 476 amino acids in its mature form and has several glycosylation sites [165]. It is synthesized by a variety of cell types [165], and secreted into the circulation. PLTP is primarily associated with the plasma HDL subtraction, particularly HDL2 particles [166]. PLTP likely binds to these lipoproteins via hydrophobic interactions and ionic interactions between two arginine residues (Arg218 and Arg 245) and the negatively-charged surface of HDL particles [167]. PLTP mediates the fusion of two smaller HDL particles into a large, unstable fusion product [168]. This unstable particle can then either rearrange into stable, multiple, smaller particles, or molecules of apoA-l can dissociate from the particle to increase its stability [168]. This mechanism is confirmed by an increase in the generation of prep-HDL particles with increased PLTP activity [169,170]. In addition to its contribution to PL exchange between lipoproteins, PLTP also mediates PL exchange between apoB-containing lipoproteins and HDL during lipolysis [171], aids in ABCA1-mediated PL efflux [172], and may facilitate VLDL secretion in hepatocytes [173]. 1.4.4 Cholesteryl Ester Transfer Protein Approximately 50% of the CE in HDL are delivered to the liver via apoB-containing lipoproteins, although the relative amount is highly variable depending on numerous factors. Cholesteryl ester transfer protein (CETP) is the enzyme responsible for the transfer of CE from HDL to apoB-containing lipoproteins with a reciprocal exchange of TG. CETP, a 476 amino acid polypeptide, is structurally homologous to PLTP, consisting of large hydrophobic domains, multiple glycosylation sites and two important 22 positively-charged amino acid residues (Lys233 and Arg259) key to lipoprotein binding [167, 174]. Plasma CETP is synthesized and secreted primarily by the liver [175], but is also synthesized by other cell types including macrophages, and adipocytes [174]. CETP is also primarily associated with the plasma HDL fraction, but in contrast to PLTP, is associated particularly with HDL3 particles [166]. CETP mediates the exchange of neutral lipids (namely CE and TG) between apoB-containing lipoproteins and HDL. This exchange is preferentially directed towards LDL particles in normolipidemic sera; however, in hypertriglyceridemic states, the exchange is predominantly with VLDL [176]. CETP can also mediate exchange between VLDL and LDL, although apoF specifically inhibits this process [177]. ApoC-l is a more general inhibitor of CETP, and may regulate the exchange with HDL [178]. Interestingly, CETP activity is increased in hypertriglyceridemic states, despite no increase in CETP mass [179]. 1.4.5 Cholesterol and Phospholipid Uptake by Hepatocytes The final step in RCT is the delivery of cholesterol to hepatocytes for biliary excretion, or to steroidogenic tissues for steroid synthesis. The HDL CE that is transferred to apoB-containing lipoproteins is delivered primarily to the liver via holoparticle uptake, as described earlier. The remaining CE and phospholipids in HDL can be taken up by the liver through selective lipid uptake and recycling of the HDL particle, or possibly even holoparticle uptake. The predominant pathway for the delivery of HDL cholesterol to hepatocytes and steroidogenic tissues is via selective uptake by SR-B1. In mice, which do not express CETP, 90% of the HDL CE is delivered by this pathway [180]. The interaction of SR-B1 with lipoproteins and possible mechanisms of this process were previously discussed in Section 1.4.1.2.2. The selective uptake process-is facilitated by hepatic lipase, by both its catalytic function and binding properties of HDL [181]. HL hydrolyzes PL on the HDL exterior thereby enabling the neutral lipids in the lipoprotein core to access the plasma membrane [146]. SR-BI can also selectively uptake lipids from LDL [182]. SR-BI is also able to selectively uptake lipids other than CE, including PL [183, 184], CE hydroxides [185], 23 and TG [184]. The enhancement of HDL with TG by CETP also increases the selective uptake process [186]. This occurs through increased lipolysis by HL [187]; however, direct competition between TG and CE uptake by SR-BI has been observed, which diminishes the rate at which CE uptake can occur [188]. Once the CE released from the lipoprotein associates with the plasma membrane, it is rapidly hydrolyzed by a membrane-associated neutral CE hydrolase [189] - a process which seems to be directed by the C-terminal transmembrane domain [106]. Approximately two-thirds of selectively uptaken CEs join the CE pool after re-esterification by ACAT [190].The remnant HDL particle has been shown to rapidly re-associate with existing HDL particles independent of enzyme action [191]. Holoparticle uptake of HDL is another likely delivery method to hepatocytes, although no other HDL receptors have been conclusively identified [146]. SR-BII is one candidate HDL receptor that may mediate holoparticle uptake and is currently under investigation [192]. 1.5 Clinical Measurements of HDL-C Lipid profiling is a common clinical method of assessing patient risk for CAD. The'number of HDL particles in the circulation cannot be measured directly, so clinicians rely on the measurements of the cholesterol content (e.g. HDL-C) of these particles as being reflective of their relative abundance. This may not always be the case if the distribution between subclasses is not similar. A patient with large particles, but few in number, may have a high HDL-C, while a patient with many, smaller particles may have a low HDL-C. As shown in cholesterol efflux studies, smaller particles act as better initial acceptors of UC due to their higher association with LCAT and their better ability to diffuse cross the unstirred water layer surrounding cells. Therefore, HDL-C may not always be an accurate predictor of the quality of the HDL. 1.5.1 Population Variations in HDL-C HDL-C varies greatly from patient to patient. Attempts to elucidate the relative contribution of genetic factors and environmental factors on HDL-C levels have been undertaken in twin studies. HDL-C levels have been estimated to be approximately 60 - 65% genetically determined [193-195], with environmental influences increasing 24 with age [195]. Environmental factors that contribute to decreases in HDL-C include diet (elevated serum triglycerides and very high carbohydrate intakes), overweight and obesity, physical inactivity, cigarette smoking, Type II diabetes, and the use of certain pharmacological agents [196]. Genetic determinants of HDL-C are numerous due to the involvement of many different enzymes in HDL metabolism and their regulation. Numerous genetic abnormalities result in hypoalphalipoproteinemia (low HDL-C), whereas a few genetic abnormalities actually result in hyperalphalipoproteinemia (high HDL-C). 1.5.2 Genetic Abnormalities Causing Hypoalphalipoproteinemia Many genetic mutations and polymorphisms in genes directly or indirectly involved in HDL metabolism that have modest effects on HDL-C have been identified, but are too numerous too mention. However, five particular conditions caused by genetic abnormalities cause severe HDL deficiency and provide valuable information on the contribution of the affected gene to HDL metabolism: Tangier disease, apoA-l deficiencies, LCAT deficiency, fish-eye disease, and LPL deficiency. 1.5.2.1 Tangier Disease Tangier disease is a rare autosomal recessive genetic disorder that results in a non-functional ABCA1 transporter because of a mutation in the ABCA1 gene [197]. The hallmark of the disease is the presence of large yellow-orange tonsils that are engorged with cholesterol esters and virtually no HDL-C or lipid-free apoA-l [198]. Patients with Tangier disease often have hypertriglyceridemia and are at high risk for CAD [199]. Homozygous patients over the age of 30 have a 6-fold higher incidence of CAD than normolipidemic subjects [200]. Tangier disease signifies the importance of ABCA1 transporter in the formation of mature HDL. 1.5.2.2 ApoA-l Deficiencies A number of mutations in the apoA-l gene have been described that prevent synthesis and secretion of apoA-l [201-204]. Patients present with complete absence of HDL-C; therefore, native apoA-l is critical in the formation of HDL. Interestingly, not all patients have CAD, presumably because they also present with low LDL-C [205]. 25 Cholesterol efflux is partly maintained by an increase in the lipid-poor y-LpE particles [205], which can efficiently accept cholesterol via the ABCA1 pathway. 1.5.2.3 Familial LCAT Deficiency LCAT deficiencies can arise from a number of different mutations in the LCAT gene. Familial LCAT deficiency is characterized by the complete absence of plasma LCAT activity, a severe reduction in HDL-C without the loss of all apoA-l, and severe reductions in plasma CE concentration [206]. Like the apoA-l deficiencies, patients with familial LCAT deficiency often don't present with premature atherosclerosis [205, 207, 208] because of a low LDL-C and high concentration of y-LpE particles [205]. However, at least a few cases of marked atherosclerosis have been documented [209, 210]. The importance of these y-LpE particles in protecting against atherosclerosis is emphasized by apoE knockout mice that develop accelerated atherosclerosis with LCAT deficiency [211]. 1.5.2.4 Fish-Eye Disease Patients with fish-eye disease have specific mutations in the LCAT gene that result in the loss of only the HDL-associated LCAT activity [206]. LCAT is still functional in the LDL fraction and thus contributes to the formation of the proatherogenic small, dense particles. Not surprisingly, these patients are at increased risk for CAD [206]. Fish-eye disease is hallmarked by extensive corneal opacities and severe HDL deficiency [206]. Despite this, fish-eye disease patients have near normal levels of total cholesterol (TC) and CE [212]. 1.5.2.5 , Lipoprotein Lipase Deficiency Homozygous LPL deficiency is a very rare autosomal recessive genetic disorder that results in the complete absence of plasma LPL mass [213]. The disease is characterized by severely elevated TG, low TC, and severe reductions in HDL-C [214]. LPL deficiency is also associated with increased CETP activity and reduced cholesterol efflux via the SR-BI-mediated pathway [213]. The incidence of atherosclerosis in 26 patients with LPL deficiency has not been well enough studied, and remains inconclusive [214]. 1.5.3 Genetic Abnormalities Causing Hyperalphalipoproteinemia Hyperalphalipoproteinemia has been much less studied than hypoalphalipoproteinemia. The most common genetic abnormality causing hyperalphalipoproteinemia is CETP deficiency, although rare genetic variations in HL have also been associated with elevated HDL-C [215]. Other candidate genes that may account for hyperalphalipoproteinemia are the genes encoding endothelial lipase and SR-BI. Endothelial lipase-knockout mice have nearly two-fold increases in HDL-C [216]; however, only a polymorphism in the endothelial lipase gene resulting in slight increases in HDL-C has been documented [216]. SR-BI deficiency has been shown to be associated with elevated HDL-C in mice [217], but the existence of homozygous SR-BI deficiency has yet to be documented in humans [215]. This is presumed to be because SR-BI plays a key role in the formation of steroids critical for reproduction; SR-Bl-deficient female mice are infertile [218]. 1.5.3.1 CETP Deficiency CETP deficiency has been most commonly identified in the Japanese population [219]. CETP deficiency has been estimated to account for 62% of all severe hyperalphalipoproteinemia [220]. At least 15 mutations in the human CETP gene have been identified that result in decreased CETP activity [219]. Complete CETP deficiency is associated with a 3 to 6-fold higher HDL-C than normal [221], elevated plasma levels of TC, apoA-l, apoA-ll, apoC-lll, and apoE [222, 223], and decreased LDL-C and apoB [224]. Interestingly, it is only the levels of the HDL2 subtraction that are increased, and not HDL3 [224]. It is currently debated whether CETP deficiency is protective against CAD [225], or pro-atherogenic [226]; patients with CETP deficiency without increased HDL-C have an increased risk of 50% of CAD, whereas those with elevated HDL-C have no increased risk [223]. It could be assumed that CETP-deficient patients with j elevated HDL-C should live longer if this is truly cardioprotective; however, life longevity is not associated with CETP deficiency [227]. 27 1.5.3.2 HL Deficiency Unlike the possibly cardioprotective increase in HDL-C in patients with CETP deficiency, patients with HL deficiency and a secondary hyperlipidemic factor have increased risk of premature CAD despite significant elevations in HDL-C [228]. HL-deficient patients present with increased levels of IDL, decreased LDL, and increased HDL [229]. In addition, LDL and HDL are typically large and buoyant [230], stressing the importance of HL in the size reduction of these lipoproteins. 1.6 Pharmacologically-Induced Changes in HDL-C Values LDL-C remains the primary target for intervention in the third Adult Treatment Panel guidelines of the US National Cholesterol Education Program (ATP III) [196]. The appropriate level of intervention is assessed on the presence of other risk factors. TG concentration and HDL-C are two such risk factors used in this assessment. The current guidelines outlined by ATP III state that an HDL-C < 1.04 mmol/L is a positive risk factor in this assessment, whereas an HDL-C > 1.55 mmol/L results in the deduction of one risk factor [196]. Pharmacological agents used to treat elevated LDL-C or the metabolic syndrome, a secondary target for intervention, often have altering effects on HDL-C as well. 1.6.1 Pharmacological Agents that Alter HDL-C There are currently four major classes of drugs widely prescribed to treat dyslipidemias: statins, fibric acid derivatives, bile acid sequestrants, and niacin [196]. Of these, the bile acid sequestrants are the only class to have little effect on raising HDL-C [231]. Ezetimibe, a cholesterol absorption inhibitor acting at the brush border of the enterocyte, has been recently approved for the treatment of high cholesterol, but also has minimal effects on raising HDL-C (2.5-5%) [232]. Thiazolidinediones, HIV-protease inhibitors, certain beta-blockers, thiazide diuretics, and progestational agents have differing effects on HDL-C [196]. Future therapies being considered include the use of CETP inhibitors, 1,2-dimyristoyl-sn-glycero-phosphocholine, and gemcabene, and are currently undergoing clinical trials [47]. 28 1.6.1.1 Niacin Niacin (nicotinic acid) exerts the most beneficial effect on HDL-C of all the currently prescribed therapies. Clinical trials have shown niacin to increase HDL-C by 15-35%, decrease TG by 20-50%, and decrease LDL-C by 5-25% [233]. Niacin primarily affects HDL-C by decreasing the uptake and subsequent catabolism of apoA-l in the hepatocyte [234]. Niacin also inhibits diacylglycerol acyltransferase 2 (the rate-limiting enzyme in the synthesis of TG and VLDL) in the liver [235]. 1.6.1.2 Fibric Acid Derivatives The peroxisome proliferator activated receptor (PPAR) family of nuclear receptors act as transcription factors and is known to regulate the expression of many HDL-modifying proteins including apoA-l, SR-B1, LPL, apoC-lll, and ABCA1 [47]. Fibric acid derivatives (fibrates) are synthetic PPAR-a ligands that are thought to primarily affect HDL metabolism through increased expression of apoA-l and apoA-ll, and decreased expression of apoC-lll [236]. Clinical trials have shown fibrates raise HDL-C by 10-35%, lower LDL-C by 5-20%, and reduce TG by 20-50% [196]. 1.6.1.3 Statins Statins (HMG-CoA reductase inhibitors) are the most widely-prescribed class of lipid-lowering medications. Statins inhibit the action of HMG-CoA reductase, the first committal step in the synthesis of cholesterol, although indirect activation of PPAR-a can also occur via a Rho-signaling pathway [236]. Statins may also inhibit CETP-mediated CE transfer from HDL to apoB-containing lipoproteins [237]. Statins modestly raise HDL-C by 5-15%, lower LDL-C by 18-55%, and decrease TG by 7-30% [196]. 1.6.1.4 Thiazolidinediones Thiazolidinediones (TZDs) are another synthetic ligand of PPAR receptors. TZDs specifically activate PPAR-y, which primarily regulates adipocyte function and sensitizes patients to insulin [238]. Meta-analysis of clinical trials involving TZDs has revealed that pioglitazone is associated with the greatest increase in HDL-C (10%), while rosiglitazone has only modest HDL-C increasing effects (6%) [239]. Surprisingly, 29 some patients on a combination therapy of a fibrate and TZD have been observed to exhibit paradoxical drops in HDL-C to much lower levels than baseline (unpublished observations of the Healthy Heart Lipid Clinic, St. Paul's Hospital, Vancouver). This observation led to the initiation of this study. 1.6.1.5 HIV Antiretroviral Therapy HIV-positive patients receiving antiretroviral therapy that includes protease inhibitors or non-nucleoside reverse transcriptase inhibitors often develop a dyslipidemic profile [240]. This includes increased TG, TC, and LDL-C, and decreased HDL-C [241]. The severity of the dyslipidemia depends on many factors including the type of protease inhibitors prescribed, especially nelfinavir [242]. Interestingly, HIV patients receiving the protease inhibitor nelfinavir or the non-nucleoside reverse transcriptase inhibitor nevirapine, have significant increases in their HDL-C (20% and 44%, respectively) [243]. It has been proposed that these HIV medications affect HDL metabolism indirectly by interfering with adipocyte function and inducing apoptosis in some areas of the body [240]. 1.6.1.6 Thiazide Diuretics, Beta-blockers, and Progestational Agents Certain antihypertensive medications like thiazide diuretics and beta-blockers can increase dyslipidemias, including lowering HDL-C [244]. Oral contraceptives that include the progestogen, desogestrel, and hormone replacement therapy have been shown to significantly increase HDL-C [245, 246]. Anabolic steroids can induce hypoalphalipoproteinemia [247], and anti-psychotic agents like phenothiazines have been reported to have adverse effects on HDL-C [248]. 1.6.1.7 Future Therapies CETP inhibitors are currently being tested in clinical trials for their efficacy in improving dyslipidemic profiles. Two CETP inhibitors, torcetrapib and JTT-705, have been associated with large increases in HDL-C (16-91%) [47, 249]. 1,2-dimyristoyl-sn-glycero-phosphocholine, a synthetic phospholipid, can induce transcription of apoA-l, thereby increasing HDL-C 2.3-fold [47]. Finally, gemcabene is a novel PPAR agonist that is capable of increasing HDL-C by 17.6% in patients with high TG [250]. 30 1.6.2 Effects of Pharmacological Agents on Cholesterol Efflux Although the effects on HDL-C and other lipid parameters of most lipid-altering pharmacological agents have been extensively studied, very little research has been dedicated to investigating the direct effects of these drugs on cholesterol efflux. Two pharmacological agents, Tibolone and Acipimox, have been shown to reduce HDL-C, but with differing effects on SR-BI-mediated cholesterol efflux. Tibolone, a progestin-derivative used in the treatment of post-menopausal women, reduces HDL-C by 20-52%, but does not affect the rate of cholesterol efflux [251]. Tibolone likely produces this effect by increasing HL activity, thereby increasing the clearance of HDL particles [252]. In contrast, treatment with Acipimox, an anti-lipolytic diabetic agent used to treat high TG, results in a similar reduction in HDL-C and rate of cholesterol efflux [253]. Acipimox has been shown to impair plasma PLTP activity, thereby decreasing, in part, the formation of prep-HDL particles [253]. A few studies have investigated the effects on cholesterol efflux when a drug causes an increase in HDL-C. Ciprofibrate, bezafibrate, atorvastatin, and sequential estrogen-progestin replacement therapy are associated with significant increases in SR-BI-mediated cholesterol efflux that are comparable to the increases in HDL-C [254-257]. 1.7 Rationale and Hypothesis Physicians use the clinical measure of HDL-C as one risk factor for CAD in assessing the need for pharmacological intervention [258]. The use of this lipid parameter relies on the assumption that HDL-C is reflective of the cardioprotective ability of HDL particles. The role of HDL in RCT is believed to be one of the largest contributors to this anti-atherogenic potential; in fact, serum cholesterol efflux potential has been shown to be a good predictor of severity and extent of CAD [259, 260]. In accordance with this concept, over the last ten years much attention has focused on cholesterol efflux studies, assumed to be the rate-limiting step of RCT. A typical cholesterol efflux assay involves the pre-loading of a specific cell line with radioactively-labeled cholesterol, followed by assaying the cells with an extracellular acceptor and measuring how much cholesterol is released from the cells over a set length of time. Early cholesterol efflux studies investigated the mechanism of efflux by synthesizing or 31 isolating various serum components and assessing their ability to induce efflux [121, 261-264], or by genetically-altering the expression of various enzymes involved in RCT in animal models [120, 140, 265-270]. More recently, cholesterol efflux studies have been applied to the sera from patients with various pathological diseases [179, 271-278]. As well, the influences of various environmental factors, such as diet or alcohol intake, on cholesterol efflux have been assessed [279-285]. HDL is the predominant acceptor of effluxed cholesterol. Two factors define how well HDL performs this function: the quantity and the quality of HDL. HDL-C has been shown to correlate strongly with cholesterol efflux [114], suggesting that the quantity of HDL particles is the more predominant factor in vitro. Qualitative assessments of HDL have centred around measuring many HDL-related variables: the relative distribution of HDL subclasses, the activities of CETP, LCAT, and PLTP, the content of apolipoproteins, TG, CE, and PL, and the species of PL contained on the HDL [179]. Each of these variables could potentially influence the rate of efflux. Measuring each variable in a cholesterol efflux study is laborious and assessing the overall effect of qualitative changes is extremely complicated and requires simplification. HDL are not static particles. They undergo continual remodeling by interacting with numerous serum components. Cholesterol efflux studies that isolate single serum components as the extracellular acceptors are useful in the investigation of efflux mechanism, but do not reflect the HDL's complete ability to uptake cholesterol; therefore, in assessing the difference between cholesterol efflux ability in different patients, the use of whole sera is more meaningful. Cholesterol efflux studies that have used whole sera have been predominantly conducted at a single serum concentration. The serum concentration is generally chosen at a concentration that approximates the needed concentration (Km) to achieve half the maximal rate of efflux (Vm ax) [114]. The rationale behind this selection is that barring any genetic defects, V m a x should be similar for all sera; therefore, Km should be the concentration at which differences between sera should be most apparent [114]. If a cholesterol efflux system can become saturated (i.e. approach V m a x) with increasing serum concentration in vitro, then it is not unreasonable to believe the same might be achieved with whole serum in vivo. Increasing the quantity of HDL particles in a saturated system would have no effect on cholesterol efflux, and differences between sera would solely be attributable to the quality of the HDL. However, the access of HDL 32 to the peripheral cells is limited by the permeability of the vascular wall and the continuous movement of the circulation; yet, it is still reasonable to assume that the quality of the HDL plays the more predominant role in vivo. The use of a single serum concentration to measure differences in cholesterol efflux does not control for differences in the quantity of HDL particles. Franco etal. [286] attempted to measure the quality of HDL particles directly by assaying HDL at a single protein concentration (on a "per particle" basis). To understand why this measures quality rather than quantity, consider the following scenario: if all the qualitative parameters of HDL were equivalent between samples, then it would be expected that the cholesterol efflux of sera with different number of HDL particles would still be the same. That is, this method would control for variations in quantity. Therefore, differences measured using HDL concentration instead of serum concentration should be an assessment of differences in quality. Jaspard et al. [287] have also attempted to measure quality directly by using the parameter Km from serum dose-response curves. It is our belief that the use of K m is the best assessment of HDL quality. During pharmacological treatment, HDL-C is often altered. The current ATP III guidelines do not make provisions in risk assessment for pharmacologically-induced changes in HDL-C. Therefore, physicians must assume the change in HDL-C is as informative in risk assessment as non-pharmacologically-induced HDL-C levels. However, studies that have investigated the effect of pharmacologically-induced changes in HDL-C on cholesterol efflux have found that the change in HDL-C is not always reflective of a similar change in cholesterol efflux ability. These few studies have used the traditional single serum concentration in their assays; direct measurements in the quality of the HDL particles have yet to be investigated. . The hypothesis of the current study is that pharmacologically-induced changes in HDL-C create qualitatively different particles than particles of non-pharmacologically-induced HDL-C, as measured by the Km of serum dose-response curves. 1.8 Selection of the Fu5AH Cell Line Probably the two most commonly used cell lines in research for cholesterol efflux studies are the Fu5AH rat hepatoma cell line and the J774 mouse macrophage cell line. Fu5AH cells are enriched in SR-BI receptor [90], and lack functional ABCA1 33 transporters [1.41]. Conversely, ABCA1 expression in J774 cells can be upregulated to very high levels with cyclic adenosine mono-phosphate [141]. Therefore, using either of these cell lines allows a researcher to isolate one of the two major mechanisms of cholesterol efflux. Of all the major cell lines used in cholesterol efflux studies, Fu5AH has the fastest half-time rate for cholesterol efflux (approximately 4 hours) reducing the time required to assay serum samples [288]. Another attractive feature of Fu5AH cells is that they respond to phospholipid concentrations with the highest stimulation of cholesterol efflux [288]. Although of hepatic origin, Fu5AH are relatively dedifferentiated [114]. Fu5AH cells do not secrete any appreciable amounts of lipoprotein [289], bile acid [289], or LCAT [114]. Fu5AH also do not have a functional LDL receptor [290]; therefore there seems to be no holoparticle uptake of any lipoproteins by these cells. However, Fu5AH do synthesize functional HL [291] that assists in the selective uptake mechanism by SR-B1. The fact that Fu5AH cells have no lipoprotein secretion or holoparticle uptake makes this cell line appealing for this study. The release of radiolabel from pre-labeled cells should only be due to SR-B1-mediated cholesterol efflux. In addition, the simultaneous transfer of unlabeled cholesterol back into the cells via SR-B1-mediated selective CE uptake allows the larger HDL particles to be recycled back to smaller particles and continue cholesterol efflux, which is more representative of in vivo kinetics. This bidirectional flux concept in this assay is supported by de la Llera Moya et al. [114] who found that the average cholesterol content of Fu5AH cells when incubated with test sera for four hours did not significantly change. 1.9 Specific Aims 1.9.1 Part I: Optimization of the Fu5AH Cholesterol Efflux Assay 1. Develop a cholesterol efflux assay, using the Fu5AH cell line, which is highly reproducible and meaningful (by ensuring all radioactivity is accounted for) 2. Establish consistency in constructing serum dose-response curves using the rate of cholesterol efflux at eight different serum concentrations 3. Validate the use of frozen sera instead of fresh samples 34 1.9.2 Part II: Characterizing the Quality-Measuring Parameter of Km 4. Verify the bidirectional flux of cholesterol across the plasma membrane 5. Recruit a sample of healthy controls to establish "normal" ranges for the values of V m a x and K m 6. Inhibit the LCAT activity of healthy serum with the inhibitor 5,5'-dithio-£>/s-(2-nitrobenzoic acid) (DTNB) to test the contribution of LCAT to cholesterol efflux 7. Compare the cholesterol efflux of DTNB-treated serum with the sera from two patients with familial LCAT deficiency (LCAT7") 8. Characterize the quality-measuring parameter Km, in terms of what it measures in the assay, by using the results of aims 4-7. s 1.9.3 Part III: Recruitment and Testing of Patient Sera 9. Recruit patients of high and low HDL-C that have a greater than 15% change in HDL-C directly attributable to a medication they were taking, and patients whose HDL-C has not changed 10. Assay each serum sample for cholesterol efflux ability and fractional esterification rates of the HDL fraction (FERHDL) 11. Compare the Km of patients with pharmacologically-induced changes in HDL-C versus the K m of patients without pharmacologically-induced changes in HDL-C 12. Evaluate the use of a single serum concentration in measuring cholesterol efflux as an assessment of HDL quality versus the use of serum dose-response curves and the parameter Km. 35 2 MATERIALS AND METHODS 2.1 Cell Culture The Fu5AH rat hepatoma cell line was generously donated by Dr. George Rothblat (University of Pennsylvania School of Medicine). Cells initially recovered from cryopreservation were grown for several passages on 100 mm tissue culture plates in Dulbecco's Modified Eagle's Media (DMEM, containing 4500 mg glucose/L, 110 mg sodium pyruvate/L, and L-glutamine) supplemented with 5% fetal bovine serum (FBS, Gibco), 1% Antibiotic-Antimycotic (Gibco), and 0.1% Fungizone (Gibco). Cells of the same passage were then frozen once again until needed. Cells recovered from cryopreservation were grown for at least one passage before use in assays and never grown for more than five passages. 2.2 Cholesterol Efflux Assay Sera was assayed for cholesterol efflux ability using the protocol of de la Llera Moya et al. [114] described here in detail with minor modifications. 2.2.1 Day 1: Seeding of Cells Fu5AH cells were seeded on 6-well tissue culture plates (Starstedt) using approximately 150 000 cells per well. This was achieved by pipetting 25-75 uL of a concentrated suspension of cells to each well (concentration calculated by triplicate counting estimates using a hemacytometer) and then subsequent dilution with 2 mL DMEM (5% FBS, 1% Antibiotic-Antimycotic, and 0.1% Fungizone). Cells were grown for two days at 37°C in a humidified 5% C 0 2 atmosphere. 2.2.2 Day 3: Radiolabeling of Cells An appropriate aliquot (10 uCi/plate) of toluene-suspended radiolabeled cholesterol ([7(n)-3H]-cholesterol, Amersham Biosciences) was first dried under a stream of nitrogen. Radiolabeled cholesterol was then re-suspended into 100% ethanol, and subsequently diluted twice in DMEM (5% FBS, 1% Antibiotic-Antimycotic, and 0.1% Fungizone) to a final concentration of 0.1% ethanol. The final volume of the 36 second dilution (the first dilution was separated into 750 LIL aliquots) was always enough media for four plates to ensure every serum sample was assayed with cells radiolabeled with the same diluted source. The media on each plate was replaced with this radiolabeling media and grown to confluence over another two days at 37°C in a humidified 5% C O 2 atmosphere. 2.2.3 Day 5: Equilibration of the Cellular Cholesterol Pools Confluent cell monolayers were briefly washed once with phosphate-buffered saline (PBS, Sigma), and the media replaced with DMEM (1% Antibiotic-Antimycotic, and 0.1% Fungizone) containing 1% bovine serum albumin (BSA, Sigma). Cells were incubated for a further 18-20 hours at 37° C in a humidified 5% C 0 2 atmosphere. 2.2.4 Day 6: Assaying Serum Samples Frozen serum samples were quickly thawed and thoroughly mixed just prior to assaying. Samples were diluted to eight different concentrations (0.5%, 0.65%, 0.9%, 1.25%, 2.5%, 5%, 10%, 20%) with DMEM (1% Antibiotic-Antimycotic). Cells were exposed to the diluted serum for four hours, unless otherwise stated, at 37°C in a humidified 5% C 0 2 atmosphere. Each dilution was run in triplicate on the same plate -a total of four plates being used per sample. After four hours of incubation, the serum-containing medium (SCM) was removed from each well and placed in a pre-chilled 1.5 mL microcentrifuge tube on ice. Cells were washed with 2 mL PBS and left to dry until lipid extraction at some later date. The SCM was centrifuged at 4°C for five minutes at 2000 rpm to remove any floating cells. 40 LIL of the cell-free medium was removed for quantification of the radioisotope via standard liquid scintillation counting using a Beckman Coulter LS6500 Multi-Purpose Scintillation Counter. The radioactivity remaining in the cells was quantified the same way after extracting the lipids as described below. The percentage efflux was calculated as: % Efflux = (com of serum-containing medium (SCM)) x 100 (cpm of SCM) + (cpm of cellular lipids) 37 2.3 Extraction of Lipids from Cells Lipids were extracted from the dried cells using 2 mL 99.5% isopropanol/well. Plates were sealed with the lid and two wraps of parafilm to prevent evaporation. Plates ,were left overnight in a fume hood, after which time the plates were mixed using a slow rocker (15 minutes) and 40 LIL of the resulting lipid suspension was then measured for radioactivity. 2.4 Isolation of Lipids from Serum-Containing Media Lipids were extracted from SCM using a procedure based on the method of Bligh and Dyer [292]. 1.5 mL of 1:2 CHCI3/MeOH was added to 400 jiL of the SCM and mixed for one minute. 0.5 mL of CHCI3 was then added and mixed for 20 seconds followed by 0.5 mL of H 2 0 being added and a further 20 seconds of mixing. The final 1:1:0.9 (CHCI3/MeOH/H20) mixture was centrifuged briefly at 3000 rpm to separate the phases, and the lower layer (containing the lipids) was transferred to a new tube and dried under a stream of air until further analysis. 2.5 Fractional Esterification Rate (FERHDL) FERHDL was measured as described by Dobiasova and Frohlich [293] for each serum sample to estimate the size distribution of HDL subclasses. Briefly, the apoB-containing lipoproteins were precipitated using phosphotungstic acid (PTA) and MgCI2. The HDL-containing supernatant was radioactively labeled via immersion with a [7(n)-3H]-cholesterol labeled disc at 0°C for a minimum of 18 hours. Samples were then incubated in a 37°C water bath for 30 minutes, at which time the assay was terminated by adding cold 98% ethanol. HDL lipids were isolated following centrifugation at 3000 rpm for ten minutes. Isolated lipids were dried under a stream of air until further analysis. 2.6 Thin Layer Chromatography Dried isolated lipids were re-suspended in a chloroform solution containing non-radioactive unesterified cholesterol and cholesteryl oleate. Lipids were separated by thin layer chromatography (TLC) on Silica gel 60 (EM Science) using a 210:36:3 38 petroleum ether/diethyl ether/acetic acid solvent phase. Bands were visualized using iodine crystals. Bands were cut from plates and dissolved in 5 mL toluene with 4 g/L omnifluor for 24 hours before the counting of radioactivity in the Beckman Coulter LS6500 Multi-Purpose Scintillation Counter. 2.7 DTNB Treatment of Serum To inhibit LCAT activity, 2.7 mL pooled serum standard was incubated for 2 hours at 37°C with 34.5 mg of 5,5'-dithio-b/s-(2-nitrobenzoic acid) (DTNB). Following the incubation, the serum was diluted to 8 different serum concentrations as described before. The average final concentration of DTNB was 1.7 mM. 2.8 Recruitment of Study Participants All study participants were recruited as per the guidelines and approval of the Research Ethics Board of St. Paul's Hospital. All participants signed forms of informed consent permitting the acquisition of one serum sample, the testing of that serum sample with HDL-related assays, and in the case of recruited patients, allowing a review of the clinical chart for pharmacological and lipid profile history. Healthy control volunteers (n=23) resided in the Greater Vancouver area and represented individuals from a number of ethnic groups. Forty-three study patients were recruited from the Lipid and HIV metabolic clinics at St. Paul's Hospital. Possible candidates were identified by either having an HDL-C<1.04 mmol/L, or an HDL-C>1.55 mmol/L through a brief review of the patient's last lipid profile. Patients were approached following their regular clinic appointment if they indicated an interest in the study to the attending physician, and the physician identified them as not suffering from any ongoing serious illness, hypothyroidism, or uncontrolled diabetes. HIV patients were excluded if they exhibited CD4 counts below 200. The study was explained to the candidates, and final recruitment was only achieved after receiving signed informed consent. 2.8.1 Obtaining of Serum Samples Phlebotomy was conducted by the trained personnel in the St. Paul's Hospital Laboratory. In the majority of cases, sera were collected on the same day as the clinic 39 appointment. The majority of patients recruited attended a morning clinic and had not eaten any large meals in the last twelve hours. Serum samples were collected using standard venipuncture into serum separator tubes (SST). Freshly collected samples were kept at 4°C until pick up. Sera from healthy volunteers were collected by the Clinical Trials Research Staff at the Healthy Heart Clinic, St. Paul's Hospital. All volunteers presented in a twelve-hour fasting state. All further accessioning was conducted by myself. Samples were allowed to clot for one hour at 4°C. SST tubes were centrifuged at 3000 rpm for 15 minutes, before the resulting isolated sera were divided into 1.5 mL aliquots. Aliquots were frozen at -80°C until needed. Samples were thawed only once just prior to use in assays. Two of the pooled sera samples (HDL-C=0.84 and HDL-C=2.20 mmol/L) that were used in the optimization assays were obtained from the St. Paul's Hospital Laboratory collected over several days. The third pooled sample used in the optimization assays (HDL-C=1.09 mmol/L) and the pooled standard (HDL-C=1.21 mmol/L) were drawn from healthy volunteers (n=4 and n=6, respectively) and were collected and frozen as described for individual samples. The two serum samples of LCAT7" patients had been previously obtained and characterized by the Atherosclerosis Specialty Laboratory. Both individuals designated as homozygotes III-6 and III-7 had been previously described [294]. Serum samples were collected in April 2001 and October 2001, respectively, and maintained frozen at -80°C. 2.8.2 Lipid Profiling of Serum Samples Total cholesterol (TC), HDL-C, TG, calculated LDL-C, total apoA-l, and apoB values were measured by St. Paul's Hospital Laboratory Clinical Department, as per their routine protocols. Briefly, TC, HDL-C, and TG were assayed using enzymatic methods and concentration measured colorimetrically using a Hitachi 911 spectrophotometer. ApoA-l and apoB were immunoprecipitated and concentration measured by rate nephelometry (Beckman Array Systems). LDL-C was calculated using the Friedewald formula [295]. All lipid profiles were conducted on previously frozen samples. 40 The HDL-C concentrations of the three pooled samples used in the optimization assays were measured by me. The concentrations were measured colorimetrically using a Beckman DU Series 500 spectrophotometer after treatment with enzymatic reagents (Sigma-Aldrich). 2.8.3 Chart Analysis A database was created containing the chart information of all study patients. Clinical charts were reviewed for lipid profile history, pharmacological history, weight changes, and diagnosis of any major illnesses. BMI calculations used the patient's weight measured at the clinical visit when the subject was recruited. 2.8.4 Assignment of Patients to Experimental Groups Patients were assigned to one of four groups based on the review of the pharmacological history and their measured HDL-C. The ATP III criteria for HDL-C as a positive or negative risk factor were used as HDL-C cutoff points for each group. Patients with a greater than 10 kg weight change in the six months prior to serum collection were excluded. The group assignments were as follows: Group I: HDL-C<1.04 mmol/L with greater than 15% recent change in HDL-C directly attributable to a medication they were taking Group II: HDL-C<1.04 mmol/L with less than 15% change for at least two recent HDL-C measurements Group III: HDL-C>1.55 mmol/L with greater than 15% recent change in HDL-C directly attributable to a medication they were taking Group IV: HDL-C>1.55 mmol/L with less than 15% change for at least two recent HDL-C measurements 2.9 Data Analyses 2.9.1 Dose-Response Curve Analysis Kinetic constants were determined by non-linear regression analysis using GraphPad Prism version 4.00 for Windows, GraphPad Software, San Diego California USA, www.graphpad.com. Curves were fit to the Michaelis-Menten equation using the minimizing-absolute-distances-squared method of weighting. All points were used in 41 generating the curve with the exception of known experimental errors (to view curves, see Appendices A-D). Apparent V m a x and Km estimates were computer generated from these curves. Apparent Km estimates were always converted to HDL-C concentrations, unless otherwise indicated. For patients 013 and 017, one trial was discarded due to an experimental error that resulted in no cholesterol efflux values for the 10% and 20% serum concentrations making the curves poorly defined and apparent V m a x and Km estimates invalid. 2.9.2 Statistical Analyses All statistical analyses were performed by GraphPad Prism version 4.00 for Windows, GraphPad Software, San Diego California USA, www.graphpad.com. All comparisons of means were performed using an independent-samples t-test. Due to statistically significant differences between sample variances, the comparison of means for the two isopropanol extraction techniques, and the TC/HDL ratios and apparent K m values for groups I and II were corrected for with Welch's correction. Due to its skewed distribution, TG comparisons were logarithmically transformed before comparisons of means (reported means are untransformed). One-way analysis of variance (ANOVA) with Tukey's post test analysis was performed for the repeated lipid extractions data. All linear and non-linear regressions used the minimizing-absolute-distances-squared method of weighting. Comparison of linear regressions for fresh versus frozen sera, and K m and 0.075 mM efflux for patient group comparisons were analyzed using analysis of co-variance (ANCOVA). Significance for all tests was defined as p<0.05 and all analyses were two-tailed. 42 3 RESULTS 3.1 Optimization of the Fu5AH Cell Line Cholesterol Efflux Assay 3.1.1 Conversion of UC to Other Products during Cell Preparation The conversion of 3H-radiolabelled UC into CE and oxidized cholesterol was confirmed through separation of cellular lipids by thin-layer chromatography and subsequent liquid scintillation counting of the resultant bands. The source vial of [7(n)-3H]-cholesterol was found to contain 99.9% UC. The uptake of radiolabel increased throughout the 48-hour labeling period (Table 2). The proportion of radiolabel existing as UC and CE did not change when measured at 12-hour intervals. A third band remaining at the spotting origin (believed to be oxidized cholesterol) appeared in TLC plate analysis during the equilibration phase, and represented a larger pool than the CE. Preparation phase Elapsed Time Percentage of Initial Radiolabel Cellular Form of Radiolabel Remaining in Media Uptake by Cells UC C E Other Labe l i ng p h a s e 12 hr 8 7 . 4 4 + 1.56% 10.72 ± 1 . 5 4 % 8 5 . 6 8 % 1 4 . 3 2 % N V B 2 4 hr 75 .48 + 0 . 6 3 % 21 .65 + 1.64% 8 2 . 4 7 % 1 7 . 5 3 % N V B 3 6 hr 6 7 . 9 9 ± 2 . 3 9 % 3 0 . 4 6 ± 1.29% 8 6 . 3 8 % 1 3 . 6 2 % N V B 4 8 hr 4 9 . 0 5 + 2 . 2 4 % 4 6 . 2 9 + 3 . 3 5 % 8 5 . 7 9 % 1 4 . 2 1 % N V B Equi l ib ra t ion p h a s e 66 hr 2.81 ± 0 . 2 7 % 3 8 . 4 6 ± 5 . 6 8 % 8 4 . 2 3 % 5 . 4 5 % 1 0 . 3 2 % Table 2. Percentage uptake of radiolabel by Fu5AH cells. Fu5AH cells grown for two days on six-well plates were subjected to 5% FBS growth media supplemented with [7(n)-3H]-cholesterol (t = 0 of elapsed time). After every twelve hours, one plate was removed from incubation and the amount of radiolabel present in the media and in the cells was measured as described in Materials and Methods. Values are expressed as the mean ± SD percentage of initially presented radiolabel for the six wells on each plate. An aliquot of the cellular extracted lipids was separated using TLC as described in Materials and Methods, and the resultant bands measured for radioactivity. Values are expressed as the mean percentage of the total radiolabel present in the cells (n=6). NVB = no visible band. 43 3.1.2 Optimization of the Extraction of Cell Lipids Initial attempts at this assay using the procedure described by de la Llera Moya etal. [114] resulted in great inconsistency in repeat measurements, most of which was attributable to the cell lipid extraction. It was hypothesized that the cholesterol efflux assay inconsistency observed was a result of evaporation of the isopropanol solvent during overnight extraction. Three different extraction procedures were designed that theoretically should have minimized the evaporation effect: (1) the original procedure using isopropanol was modified by sealing the plate with two wraps of parafilm; (2) the isopropanol extracting the lipids was allowed to dry, and then the dried lipids were re-suspended in a fresh 2 mL isopropanol; (3) overnight lipid extraction into 0.1 M NaOH (non-volatile) has also been described for this cell line [252, 257, 260, 286]. The overnight isopropanol and parafilm technique was found to be the most consistent (Table 3), followed by the drying technique. The overnight extraction into 0.2 M NaOH was found to be the least consistent. It was expected that each technique would maintain its 2 mL volume which would result in very similar means of measured cell radioactivity. Surprisingly, all of the techniques resulted in significantly different means. The different results from the 0.2 M NaOH overnight method were attributed to the fact that the NaOH seemed to dissolve all cellular components (as opposed to isopropanol dissolving only lipid-soluble components) creating a high viscosity suspension that was difficult to accurately pipette. Extraction Technique Mean Measured S.D. Ceil Radioactivity Overnight Isopropanol 20330 cpm 655.4 cpm Drying Isopropanol Method 17250 cpm 1410.6 cpm Overnight 0.2 M NaOH 13410 cpm 3265.6 cpm Table 3. Assessment of three different techniques for cell lipid extraction. Cells containing [7(n)-3H]-cholesterol were grown on four separate six-well plates under identical conditions and assayed for 4 hours using a pooled serum of HDL-C = 2.20 mmol/L. Cell lipids were extracted by either overnight extraction in 2 mL isopropanol (using two wraps of parafilm to seal the plate), the drying method (initial 2 mL isopropanol dried completely, followed by re-suspension in a fresh 2 mL isopropanol), or overnight extraction into 0.2 M NaOH. Mean values represent counts per minute of 40 LXL of the resultant extract for 8 different wells. 44 Comparing the two isopropanol techniques, the overnight extraction had a significantly higher mean than the drying method (t=5.605, p<0.001). To elucidate which technique represented the more accurate measurement, the rate of isopropanol evaporation was measured, and repeat dryings were conducted on the same plates. There was minimal loss of isopropanol when plates were wrapped with parafilm (Figure 7). Sealing the plate with parafilm resulted in a loss of only 0.56% of the initial isopropanol added over an 18-hour period, as compared to 19.39% without. When the drying technique was repeated three times on the same six-well plate (Figure 8), the amount of re-suspended radiolabel became significantly less (F=2.395, p=0.0004) each time. Tukey's multiple comparison test reveals that the mean cpm of the radiolabel in the first drying was significantly different than the mean cpm of the radiolabel in the second drying (p<0.01), and significantly different than the mean cpm of the radiolabel in the third drying (p<0.001). Since there was no significant difference in total weight following each drying, it can be assumed that the released cholesterol from the cells during isopropanol extraction forms strong hydrophobic interactions with the plate once dry and is more difficult to re-suspend following each subsequent drying. This would lead to an underestimate of the total radioactivity remaining in the cells, thereby invalidating the use of such a technique. To ensure proper mixing of the cell lipid suspension, plates were placed on a slow rocker for fifteen minutes. Interestingly, when a plate was moved periodically during the extraction process, the loss of isopropanol increased to 32.78% over 18 hours (Figure 7). Rocking in excess of fifteen minutes produced more variable results and noticeable condensation on the underside of the plate lid. 45 60H c re a o »_ a. o * 40H 20H No Parafilm; Periodic Movement — Plate sealed with Parafilm • • • • No Parafilm and no Movement 0.0 5.0 —i— 7.5 20.0 2.5 10.0 12.5 15.0 17.5 Hours Elapsed Figure 7. Rates of isopropanol evaporation from 6-well plates. 2 mL of isopropanol was added to each well of four six-well plates containing dried cells. Two plates each were sealed with (solid line) or without (dotted line) parafilm. Plates were transported to a weigh scale every 1.5 hours; one plate of each condition being read from 0 to 9 hours, and the second being read from 9 to 18 hours. On a separate day, 2 mL of isopropanol was added to each well of a six-well plate and the plate was left on the weigh scale for the entire 18 hour period with measurements being taken every hour (dashed line). 1 2 3 4 5 6 Well Number Figure 8. Repeated extractions using the drying method. 2 mL of isopropanol was added to each well of a six-well plate containing dried cells. 40 uL of the resulting re-suspension was removed for liquid scintillation counting (cpm of cell lipids is for 40 uL). The remaining isopropanol was left to dry, before the procedure was repeated twice more. 46 3.1.3 Radioisotope Accounting To ensure percent efflux values obtained in this assay were a percentage of the total radioactivity, it was necessary to account for all radioactivity used during the preparation and the execution of the assay. Radioactivity was measured in the media after each step in the preparation of the assay, and in the cell lipids and serum-containing media following the 4-hour incubation with serum (Figure 9). This procedure was repeated for four different variations of the assay using the lipid extraction procedure described in the Materials and Methods: • length of the assay was varied from 2 minutes to 5 hours (Figure 9, Panel A) • serum concentration was varied from 0% to 17.39% (Figure 9, Panel B) • three different pooled sera were used of varying HDL-C (Figure 9, Panel C) • no assay conducted - termination after equilibration step (Figure 9, Panel D) Combining the data from all four variations, 99.76% of the radiolabel was accounted for. The slight loss of radioactivity can easily be attributable to random liquid scintillation counting, particularly the counting of the original labeling media to be placed over the cells (the theoretical starting value). 3.1.4 Optimal Assay Length In order to measure the initial rates of efflux (v0), the amount of cholesterol released over the course of the assay needed to approximate linear kinetics. Three different pooled serum samples demonstrated approximate linear kinetics to at least five hours (Figure 10). To maximize the different percentage efflux values between sera and to compare to other published results, an assay length of four hours was chosen for all subsequent assays. The amount of cholesterol released over the course of the assay also approximated linear kinetics up to an assay length of four hours when different serum concentrations were used of the same pooled serum (Figure 11). However, there does seem to be an initial greater efflux rate happening during the first half hour, after which the rate stabilizes over at least the next four hours. 47 5 h r 4 . 5 h r 4 h r 3 . 5 h r 3 h r 2 . 5 h r 2 h r 1 .5 h r 1 h r 0 . 5 h r 0 . 0 3 3 h r Assay Length i l l f'lf • I | I I I _ • I -2 . 2 0 m M EM L a b e l i n g M e d i a r ^ B S A M e d i a B P o s t - A s s a y W a s h E 2 J L a b e l i n g M e d i a S B S A M e d i a • i P o s t - A s s a y W a s h E E ! P o s t - L a b e l W a s h a A s s a y M e d i a C S C e l l L i p i d s B3 P o s t - L a b e l W a s h A s s a y M e d i a E S 3 C e l l L i p i d s CO B I i l 11 i l i i i • i i 1! I 1 1 1 I III Mil in ill ill 0 . 5 2 % 1 . 3 0 % 2 . 5 6 % 5 % Serum Concentration 9 . 5 2 % 1 7 . 3 9 % E 3 L a b e l i n g M e d i a B B S A M e d i a M P o s t - A s s a y W a s h E S I P o s t - L a b e l W a s h • A s s a y M e d i a B 3 C e l l L i p i d s No Assay H L a b e l i n g M e d i a B B S A M e d i a • 1 P o s t - A s s a y W a s h ~ P o s t - L a b e l W a s h Q A s s a y M e d i a C e l l L i p i d s Figure 9. Accounting of radioactive label. Fu5AH cell monolayers were labeled with [7(n)-3H]-cholesterol. The amount of radiolabel present in the labeling media prior to presentation to the cells (to calculate the initial amount of radiolabel (horizontal line)), and after all subsequent steps was measured using standard liquid scintillation counting. Values were converted to percentages of the initial radiolabel. This procedure was repeated for four variations of the assay (Panels A-D). All procedures are described in the "Materials and Methods". A 30-25-Length of Assay (hrs) <H 1 1 1 1 — • i 0 1 2 3 4 5 6 Length of Assay (hrs) 01 i i i i • 0 1 2 3 4 . 5 6 Length of Assay (hrs) Figure 10. Variations in assay length for three different sera. Assay length was varied in half hour increments using the described assay procedure in "Materials and Methods". This procedure was repeated for three different pooled sera of varying HDL-C values at a 5% serum concentration: HDL-C = 0.84 mmol/L (Panel A), HDL-C = 1.09 mmol/L (Panel B), and HDL-C = 2.20 mmol/L (Panel C). Symbols represent the mean of triplicate measurements, with standard deviations indicated by error bars. The solid lines represent linear regression analysis. 49 Figure 11. Variations in assay length for different serum concentrations. Assay length was varied in half hour increments using the described assay procedure in "Materials and Methods". This procedure was repeated for four different serum concentrations of a pooled serum with HDL-C = 1.21 mmol/L. Symbols represent the mean of triplicate measurements, with the standard deviation indicated by error bars. The solid lines represent linear regression analysis. Dotted lines indicate a separate and larger initial rate of efflux over the first 0.5 hr. 3.1.5 Percentage Efflux Coefficients of Variation Percentage efflux calculations made on the same assay plate demonstrated very reproducible results (Table 4) with coefficients of variation (CV) ranging from 1.4% to 4.4% for the eight different concentrations used in generating serum dose response curves. However, a single serum dose response curve requires the use of four 6-well plates per sample. Therefore, it was also necessary that the same sample run on different plates would yield consistent values at all eight different concentrations in order to form a meaningful curve. Intra-assay inter-plate CVs ranged from 2.1% to 4.6% (Table 4; distributions in Appendix E). Inter-assay variation was much greater suggesting the need for a pooled standard so that daily fluctuations could be adjusted for. 50 Serum Intra-assay Inter-assay Concentration Mean Intra-plate C V Inter-plate C V C V (n=5) (n=5) (n=15) 0.50% 4.4% 4.6% 21.8% 0.65% 3.2% 2.9% 18.7% 0.90% 2.4% 2.4% 19.7% 1.25% 4.0% 2.9% 17.6% 2.50% 2.4% 2.1% 15.8% 5.00% 2.8% 4.6% 15.2% 10.00% 1.7% 2.6% 13.0% 20.00% 2.2% 2.1% 10.0% Table 4. Intra-assay and inter-assay coefficients of variation. Cholesterol efflux assays were conducted as described in "Materials and Methods" for eight different serum concentrations of a pooled sample with HDL-C = 1.21 mmol/L. Mean intra-plate CVs were calculated using the CVs for each serum concentration on a single plate (n=3) and then averaging the values obtained for 5 separate plates. Inter-plate CVs and inter-assay CVs were calculated using the average of triplicate, measurements on five different plates on the same day and on one plate on fifteen different days, respectively. 3.1.6 Apparent V m a x and Km Coefficients of Variation The intra-assay CVs for apparent V m a x and Km measurements made on the same sample (Figure 12, Panel A) were 5.3% and 6.5%, respectively (n=5). The inter-assay CVs for apparent V m a x and Km measurements made on the same sample (Figure 12, Panel B), but on different days, over a ten-month period were 7.3% and 20.5%, respectively (n=15). 3.1.7 Stability of Frozen Sera Due to the lengthy preparation time for the cholesterol efflux assay, and the intention to assay each serum sample in three separate trials, it was not feasible to use fresh serum. Therefore, freshly drawn samples were frozen in 1.5 mL aliquots at -80° C using the protocol described in Materials and Methods, and thawed only once just prior to assay. 51 Figure 12. Intra-assay and inter-assay reproducibility. Dose response curves were generated by conducting triplicate cholesterol efflux assays as described in "Materials and Methods" for eight different serum concentrations. Intra-assay CVs (Panel A) were calculated from five curves assayed on the same day, and inter-assay CVs (Panel B) were calculated from fifteen curves assayed on separate days. All assays used a pooled serum sample with HDL-C = 1.21 mmol/L. 52 Figure 13. Relation between relative apparent Km values for fresh and frozen serum. Serum from seven individuals was collected and assayed for efflux ability as described in Materials and Methods. Each sample was assayed as a fresh sample (within 6 hours of collection), and then again ten days later after freezing at -80° C . Dose-response curves were generated and apparent Km values estimated using Graphpad Prism 4.00 software. Measured apparent Km values were converted to relative apparent Km values by normalizing the absolute values to a frozen pooled serum standard set at a value of 1.0. Dotted line represents the expected results if relative apparent K m values remained constant after freezing. To assess the effect of freezing on apparent K m values, seven fresh serum samples were collected and assayed within six hours. An aliquot from each sample was also frozen and assayed ten days later. Because the inter-assay C V for apparent Km is quite high, it was unreasonable to expect the same measured values on two separate days. Therefore, a frozen standard pooled serum was included in both assays for comparison. There was a good correlation (r = .95) between the relative values of fresh and frozen serum (Figure 13). However, there was a significant decrease in each relative apparent Km value after one cycle of freezing and thawing (p<0.001). There were no further observed directional trends in efflux ability over a ten-month period. 53 3.1.8 Post-Assay Wash The post-assay wash was found to contain, on average, 0.7% of the total radioactivity present during the assay (data not presented). This small amount of radioactivity is likely due to incomplete removal of the assayed serum-containing medium, but could also conceivably contain dead cells. A second and third wash contained less than 0.3% of the total radioactivity present during the assay. It was deemed sufficient to only include a single wash in order to conserve PBS, because any further washings were observed to have very little effect on results. 3.2 Characterizing the Quality-Measuring Parameter of Km To verify what apparent K m was actually measuring, assumptions regarding the assay were tested. Measurements of apparent Km and V m a x were also made on a group of seventeen healthy individuals, two LCAT-deficient individuals, and DTNB-treated serum to gain insight into the limitations of using apparent Km to assess quality. 3.2.1 Efflux in the Absence of Serum As a control assay, the cells were assayed as described in the Materials and Methods in the absence of serum (media only). The percentage^efflux over 4 hours was 0.81% ± 0.24% (mean ± SD). This portion of released cholesterol is likely due to simple diffusion from the exofacial leaflet of the plasma membrane to the surrounding medium. Since the aim of this study was to measure the effect of HDL on efflux, this background value was deducted from all subsequent four-hour assay values. 54 Band Pre-Assay Post-Assay P Unesterified Cholesterol 74.59 ± 2.66% 56.63 ±1.14% <.0001 Cholesteryl Esters 9.84 ± 1.89% 11.25 ± 0.87% NS Triglycerides 2.01 ± 0.44% 1.17 ±0.18% <.01 Other 13.56 ±1.45% 6.37 ± 0.74% <.0001 Serum-containing media - 24.77 + 0.40% Table 5. Source of effluxed cholesterol. A pooled serum control of HDL-C = 2.20 mmol/L was assayed for cholesterol efflux ability as described in Materials and Methods. The cells on one six-well plate were lipid extracted prior to the assay while a second six-well plate (matched for total radioactivity) was lipid extracted following the four-hour assay. The resultant lipid suspensions were separated by TLC analysis, and the four visible bands counted for radioactivity. Values are expressed as the mean (± SD) percentage (n=6) of initial radiolabel applied to the cells, p values are for unpaired t-test comparisons between pre-assay and post-assay cells. 3.2.2 Efflux from the Unesterified Cholesterol Pool To identify the source of the effluxed radiolabel within the cells, lipids extracted from the cells before and after the assay were identified and quantified. Four bands appeared on the TLC plate (Table 5). By comparing to known standards, three of the bands were identified as esterified cholesterol, triglycerides, and unesterified cholesterol, in order of decreasing distance traveled. The fourth band remained at the spotting origin, and was believed to be an oxysterol. The majority of the effluxed radiolabel was in the form of UC (73%), while the remainder was accounted for by this oxysterol band. 55 n Mean ± SD Range Age 18 29 ±7 19 - 4 5 TC (mmol/L) 18 4.37 ± 0.78 2.97 -5.50 TG (mmol/L) 18 0.91 ±0.32 0.44 - 1.55 LDL-C (mmol/L) 18 2.55 ± 0.58 1.53 -3.40 HDL-C (mmol/L) 18 1.40 ±0.36 0.94 -2.33 TC/HDL-C (mmol/L) 18 3.21 ± 0.59 1.94 -4.16 apoB (g/L) 18 0.74 ±0.17 0.44 -1.10 Total apoA-l (g/L) 18 1.32 ±0.16 0.99 -1.59 FERHDL 17 13.2% ±3.9% 8.1%- 21.4% Relative V m a x 17 1.02 ± 0.07 0.83 -1.12 Relative Km 17 1.12 ±0.27 0.67 - 1.71 Relative 0.075 mM Efflux 17 0.96 ± 0.09 0.77 -1.12 Table 6. Characteristics of healthy controls. 23 healthy volunteers donated sera for the estimation of the natural variation in the relative apparent V m a x and Km values that exist when generating serum dose-response curves from healthy individuals. Each frozen sample was assayed as described in Materials and Methods. Five volunteers were excluded from this analysis for having at least one risk factor for heart disease. One healthy volunteer was unable to donate enough sera for apparent V m a x and Km determinations, while the FERHDL was unable to be assayed on a separate serum sample. 3.2.3 Recruitment of Healthy Controls 23 apparently healthy volunteers (15 males, 8 females) donated serum for use in cholesterol efflux assays in order to gain an estimate of what the ranges of apparent Vmax and Km values are in healthy individuals. All 23 individuals identified themselves as non-obese, non-smokers, and were not on any lipid-lowering medications. After serum lipid analysis, five of these individuals (4 males, 1 female) were identified as having at least one risk factor for coronary heart disease and were not included in the generation of these ranges. The average lipid parameters and ranges of these individuals are summarized in Table 6. 56 3.2.4 Effect of DTNB Inhibition of LCAT in Control Serum To determine the contribution of LCAT to the overall efflux rate, the pooled sera standard was assayed in the presence and absence of DTNB (average final concentration 1.7 mM). DTNB is an effective reversible inhibitor of LCAT, reducing its activity by more than 99% at a 1.7 mM concentration [296]. Serum in the presence of DTNB exhibited a 90.2% reduction in apparent V m a x and a 93.7% reduction in apparent Km as compared to serum in the absence of DTNB (Figure 14). 3.2.5 Patients with Homozygous LCAT Deficiency Serum samples from two siblings homozygous for LCAT deficiency were assayed for cholesterol efflux ability for comparison with the DTNB-treated sera. Patient III-6 and Patient III-7 exhibited 67.4% and 62.6% reductions in apparent V m a x, respectively, and 96.7% and 92.6% reductions in apparent Km, respectively, as compared to the pooled sera standard (Figure 15). A lack of available serum from these patients for the assay prevented the measurement of cholesterol efflux at high concentrations; however, the concentrations assayed were deemed adequate enough to define the upper region of the serum dose-response curves. The lipid profiles for each patient are shown in Table 7. Patient HDL-C LDL-C TC TG TC/HDL-C apoB III-6 O06 "Ml Z84 3^ 64 47^ 3 O30~ 111-7 0.14 2.21 2.81 0.99 20.1 0.36 Table 7. Lipid profiles of two LCAT7' patients. Lipid profiles of two homozygotes for LCAT-deficiency were measured in April 2001 and October 2001 for siblings III-0 and III-7, respectively. The family tree can be found elsewhere [294]. 57 Figure 14. Dose-response curve of DTNB-treated serum. The pooled serum standard (HDL-C=1.21 mmol/L) was assayed in the presence and in the absence of DTNB, a strong inhibitor of LCAT. 2.7 mL of serum was incubated at 37° C for 2 hours with 34.5 mg of DTNB before diluting to appropriate serum concentrations (average final concentration 1.7 mM). Serum dose-response curves were assayed and generated as described in Materials and Methods. Figure 15. Dose-response curves for two LCAT7' patients. Serum samples previously acquired from two patients homozygous for LCAT deficiency were assayed as described in Materials and Methods. The volume of available sera was inadequate to perform the assay at the higher concentrations. 58 I 3.3 Study Population Characteristics Forty-three patients were recruited for this study. Each patient's serum was assayed for cholesterol efflux ability on three separate trials (see Appendices A-D), and assayed once for FERHDL- All values reported reflect the means of the three trials with the following exceptions: only two serum dose-response curves were able to be generated for patients 029 and 048 due to a lack of sufficient sera and for patient 017 due to an experimental error in the first trial. Four determinations were made for patient 028. When combined with the data obtained from the twenty-three healthy volunteers, these data represented a wide distribution of HDL-C values. 3.3.1 HDL-C Relationship to V m a x The majority of patients exhibited a relative apparent Vmax in the range of the , healthy controls (Figure 16), although a few patients with hypoalphalipoproteinemia exhibited a substantial reduction. The overall trend seems to be curvilinear approximating Michaelis-Menten curve characteristics: Excluding the patients with a relative apparent V m a x outside of the range described for the healthy volunteers, there was a slight positive linear trend with increasing HDL-C. 3.3.2 HDL-C Relationship to Km When apparent K m was expressed in terms of percent serum concentration (Figure 17, Panel A), a strong negative linear relationship with HDL-C was observed. When apparent Km was expressed in terms of HDL-C concentration (Figure 17, Panel B), a strong positive curvilinear relationship with HDL-C was observed that approximated Michaelis-Menten curve characteristics. 59 Figure 16. HDL-C relationship to relative apparent Vm ax. Sera from 66 participants were assayed for cholesterol efflux potential as described in Materials and Methods. Apparent V m a x values were estimated from serum dose-response curves using Graphpad Prism 4.00 software. Non-linear regression was fit to the Michaelis-Menten equation. The gray lines indicate the range of healthy volunteers (0.83 -1.12). The dotted line represents the linear regression of only the data within the healthy range (gray lines) as estimated by the healthy volunteers. All values are the means of triplicate measurements. 60 6 1.75' 1.50 * 1.25 c 5 1.00 a. < o> 0.75-| w v 0.50 OC 0.25H O.OOM 0.0 2.00-1.75-E 1.50-c a> 1.25-<5 Q. a 1.00-< _> 0.75-n a> 0.50-GC 0.25-0.00-0.0 Apparent K m calculated using % serum concentration — i i i i i i i i 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 HDL-C (mmol/L) • J Apparent K m calculated using HDL-C concentration — i 1 i i i i i i 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 HDL-C (mmol/L) Figure 17. HDL-C relationship to relative apparent Km. Sera from 66 participants were assayed for cholesterol efflux potential as described in Materials and Methods. Apparent Km values were estimated from serum dose-response curves using Graphpad Prism 4.00 software and calculated using percentage serum concentration (Panel A), or the concentration of HDL-C (Panel B). Non-linear regression was fit to the Michaelis-Menten equation. 61 3.3.3 HDL-C Relationship to FERHDL and TG HDL-C exhibited very similar relationships to the FERHDL (Figure 19, Panel A) and TG concentration (Figure 19, Panel B). Both relationships were curvilinear and approximated one-phase exponential decay curve characteristics. 3.3.4 HDL-C Relationship to Efflux at a Single HDL-C Concentration . When the rate of cholesterol efflux was calculated from the serum dose-response curves at HDL-C = 0.075 mmol/L, a strong curvilinear relationship was observed (Figure 18). 3.4 Pharmacologically-Induced Changes in HDL-C Patients were assigned into the four groups as described in Materials and Methods on the basis of two separate variables: HDL-C (high vs. low) and whether their current lipid levels were directly attributable to a pharmacologically-induced change in HDL-C. Groups I to IV were assigned as follows: Group I: HDL-C<1.04 mmol/L with greater than 15% recent change in HDL-C directly attributable to a medication they were taking Group II: HDL-C<1.04 mmol/L with less than 15% change for at least two recent HDL-C measurements Group III: HDL-C>1.55 mmol/L with greater than 15% recent change in HDL-C directly attributable to a medication they were taking Group IV: HDL-C>1.55 mmol/L with less than 15% change for at least two recent HDL-C measurements 62 Figure 18. HDL-C relationship to FERhdl and TG. Sera from 66 participants were assayed for fractional esterification rates as.described in Materials and Methods. Triglyceride and HDL-C concentrations were measured by the St. Paul's Hospital Laboratory. Panel A represents the relationship between HDL-C and FERHDL- Panel B represents the relationship between HDL-C and TG. All non-linear regression was fit to one-phase exponential decay. 63 1.50-T O g 0.50-it) Is-o o 0.25-0.001 i i i i i i i i 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 HDL-C (mmol/L) Figure 19. HDL-C relationship to 0.075 mmol/L relative efflux. Sera from 66 participants were assayed for cholesterol efflux potential as described in Materials and Methods. Serum dose-response curves were generated for each sample using Graphpad Prism 4.00 software. 0.075 mmol/L efflux rate was calculated from the serum-dose response curve. All non-linear regression was fit to one-phase exponential decay. All values are the means of triplicate measurements. Groups of the same HDL-C category were compared on a number of different parameters (Table 8). Groups III and IV were statistically significantly different with respect to their TC and LDL-C lipid measurements. All other comparisons were not significant. No significant differences were observed between groups III and IV when compared on the parameters apparent V m a X (Figure 20), apparent Km (Figure 21) and 0.075 mM relative efflux (Figure 22). Comparisons on the same parameters were made between groups I and II with and without the patient that had exhibited severe reduction in apparent V m a x . No statistically significant differences were observed for apparent Vmax (Figure 23) and apparent K m (Figure 24); however, the two groups did significantly differ in terms of the 0.075 mM apparent efflux (p=0.036) when the one patient was excluded (Figure 25). 64 Patients with Low HDL-C Group 1 (n=10) Mean ± S D Range Group II (n=10) Mean ± SD Range P Age 45 ±10 29-64 51 ±12 27-74 0.23 BMI (kg/m2) 30.1 ± 3.9 25.2 - 37.5 27.9 ± 3.9 24.9 - 37.0 0.26 TC (mmol/L) 6.48 ± 2.35 3.88-10.44 5.25 ± 1.56 3.35 - 8.28 0.19 TG (mmol/L)** 7.15±5.13 1.80-19.03 5.59 ±2.97 2.50-10.26 0.56 LDL-C (mmol/L) 3.21 + 2.50 0.78 - 7.42 2.38 ± 1.31 0.55 - 3.70 0.45 HDL-C (mmol/L) 0.67 + 0.18 0.40 - 0.92 0.75 ± 0.27 0.24 - 1.07 0.49 TC/HDL-C (mmol/L) 10.03 ±3.55 5.1 - 15.3 9.32 ± 9.08 3.7 - 34.5 0.82 Total apoA-l (g/L) 0.90 ± 0.23 0.54-1.16 1.00 ±0.33 0.27 - 1.34 0.47 FERHDL (in %) 35.4 ± 9.5 16.7-50;3 36.3 ± 7.3 27.0-51.6 0.79 Relative Apparent V m a x 0.88 ±0.12 0.63-1.00 0.88 ±0.18 0.42-1.12 0.99 Relative Apparent Km 0.62 ±0.15 0.38 - 0.81 0.72 ± 0.32 0.11 - 1.23 0.40 Relative 0.075 mM Efflux 1.15±0.14 0.87 - 1.37 1.08 ±0.18 0.82-1.46 0.33 Patients with High HDL-C Group II Mean ± S D l(n=11) Range Group IV (n=10) Mean ± SD Range P Age 64 ±7 53-74 57 ±11 38-76 0.12 BMI (kg/m2) 27.4 ± 4.5 23.2 - 37.9 25.5 ± 3.6 20.7 - 30.9 0.28 TC (mmol/L) 5.68 ± 1.06 3.82 - 6.98 7.36 ±1.77 5.13-10.97 0.015* TG (mmol/L)** 1.30 + 0.62 0.68 - 2.99 1.38 ±0.68 0.80 - 2.65 0.82 LDL-C (mmol/L) 2.91 ±0.99 1.14-3.95 4.31 ±1.53 2.61 - 7.51 0.021* HDL-C (mmol/L) 2.18 ±0.37 1.73-2.95 2.43 ±0.59 1.71 -3.50 0.25 TC/HDL-C (mmol/L) 2.7 ±0.6 1.6-3.5 3.13 ±0.70 2.2 - 3.9 0.12 Total apoA-l (g/L) 1.87 ± 0.23 1.62 - 2.39 1.96 ±0.40 1.45 - 2.65 0.54 FERHDL (in %) 11.4 ±3.8 4.7-18.4 10.7 ±3.5 5.8-17.0 0.43 Relative Apparent V m a x 1.04 ± 0.06 0.97-1.14 1.03 ±0.07 0.91 - 1.13 0.84 Relative Apparent Km 1.34 ±0.14 1.10-1.46 1.33 ± 0.22 1.00-1.83 0.93 Relative 0.075 mM Efflux 0.89 ± 0.06 0.80 - 0.95 0.88 ± 0.06 0.79 - 0.97 0.80 Table 8. Characteristics of patient groups. Patients recruited for the study were assigned into one of four groups by the criteria described in Materials and Methods. All values listed were measured as described in Materials and Methods. * Bold p values indicate those that are significant differences (p<0.05). ** TG values were logarithmically transformed for statistical analysis. Reported means represent untransformed values. 65 B X CO E > c 0) i_ CB a a. < I re o c a> i_ re Q. Q. < JS a> DC 1.25-1.00-0.75-0.50-0.25-0.00-4 1 1.25-1 1.00-0.75-0.50-0.25-0.00 1.5 2.0 2.5 3.0 HDL-C (mmol/L) —T— 3.5 -1 4.0 4 r f — I l l I I l 1 1.50 1.75 2.00 2.25 2.50 2.75 3.00 3.25 HDL-C (mmol/L) X CO E > c o re a. a < I re <u IT 1.25-1.00-0.75-0.50-0.25-0.00" 1.5 Non-pharmacological Pharmacologically-1 nduc ed 2.0 2.5 3.0 HDL-C 3.5 4.0 Figure 20. Relative apparent V m a x comparison between groups III and IV. Linear regression analyses of Group IV (Panel A), Group III (Panel B), and the linear regressions plotted together (Panel C). Values are the mean (± SD) of three determinations. Analysis of Covariance indicated no statistically significant difference. 66 I I 2.25-2.00-1.75-1.50-1.25-1.00-0.75-0.50-0.25-0.00-1.5 2.0 2.5 3.0 HDL-C (mmol/L) 3.5 4.0 B E C o CD Q. CL < > 1 o cc 1.75-1 1.50-1 1.25 1.00-0.75-0.50-0.25-0.00 —I 1 1 1 1 1 1 1.50 1.75 2.00 2.25 2.50 2.75 3.00 3.25 HDL-C (mmol/L) E c <D i-CO Q. Q. < > 0) DC 2.25-2.00-1.75-1.50-1.25 1.00H 0.75 0.50H 0.25 0.00 1.5 - Non-pharmacological Pharmacologically-Induced 2.0 —f— 2.5 —J— 3.0 3.5 4.0 HDL-C (mmol/L) Figure 21. Relative apparent Km comparison between groups III and IV. Linear regression analyses of Group IV (Panel A), Group III (Panel B), and the linear regressions plotted together (Panel C). Values are the mean (+ SD) of three determinations. Analysis of Covariance indicated no statistically significant difference. 67 1.25-0.75-s a) E > m 0.50-is o g O 0.25-0.00 | i I I l I 1.5 2.0 2.5 3.0 3.5 4.0 H D L - C (mmol/L) B i.25n E * 1.00H a, g •iS 0.75H o> £ > m 0.50-1 iS o g o 0.25-1 0.00-1.50 1.75 2.00 2.25 2.50 2.75 H D L - C (mmol/L) 3.00 3.25 9 3 0.95< .£ 0.70-1 QJ E > m 0.45-0.20-j 1.5 Non-pharmacological Pharmacologically-Induced 2.0 —1— 2.5 - T -3.0 3.5 - I 4.0 H D L - C (mmol/L) Figure 21. Relative apparent 0.075 mM efflux comparison between groups III and IV. Linear regression analyses of Group IV (Panel A), Group III (Panel B), and the linear regressions plotted together (Panel C). Values are the mean (± SD) of three determinations. Analysis of Covariance indicated no statistically significant difference. 6 8 > ra a a . < > ra 1.25-1.00-0 . 7 5 -0.50-0.25-O.OO 0.25 050 075 Too 1^ 25 HDL -C (mmol/L) B 1.25i X > 1.0<H s !S 0.75 0.50H ai > _ 0.25' 0.0CH 0.00 0.25 0.50 0.75 HDL -C (mmol /L) 1.00 1.25-1 > 1.00-1 2! > a> or 0.75-1 0.50H 0.25-1 0.00 0.00 Non-pharmacobgical Pharmacologically-Induced 0.25 0.50 0.75 HDL -C (mmol /L) 1.00 1.25 CD CD 1.25n X ra E > 1.00' c a> 0.75H 0.5CH to Q, a. < 75 0.25H a> OC o.ooH 0.00 0.25 —I— 0.50 -r 0.75 HDL-C (mmol/L) - i — 1.00 1.25 1.25n X <u e > 1.00-0.75-1 0.50-CD > 0.25-0.00' 0.00 Non-pharmacological • Pharmacologically-Induced 0.25 0.50 0.75 HDL-C (mmol/L) — i — 1.00 1.25 Figure 22. Relative apparent V m a x comparison between groups I and II. Linear regression analyses of Group II (Panel A), Group I (Panel B), and the linear regressions plotted together (Panel C). One patient was removed from Group II (Panel D), which altered the linear regression plot comparison (Panel E). Values are the mean (± SD) of three determinations. Analysis of Covariance indicated no statistically significant difference. A B C — Non-pharmacological H D L - C ( m m o l / L ) HDL - C (mmol /L ) Figure 23. Relative apparent Km comparison between groups I and II. Linear regression analyses of Group II (Panel A), Group I (Panel B), and the linear regressions plotted together (Panel C). One patient was removed from Group II (Panel D), which altered the linear regression plot comparison (Panel E). Values are the mean (± SD) of three determinations. Analysis of Covariance indicated no statistically significant difference. B Ii a) E > in 1.50-1 1.25-1 i.oo-| 0.75 0.50-1 0.25-1 0.00' 0.00 0.25 0.50 0.75 HDL -C (mmol/L) — i — 0.75 1.25 1.50-irent lux 1.25-I s 1.00-< 1 0.75-> m r-o 0.50-i d LJ= 0.25-0.00' 1.50-| g 1.25-§.£ LOO-K'S 0 E 0.75-1 Lfi 13 0.50-1 1 0.25-0.CX> 0.00 0.25 0.50 0.75 HDL -C (mmol /L) —1~~ 1.00 0.00 1.25 I 0.25 I 0.50 0.75 1.00 HDL -C (mmol/L) E (1) d m < 5 1.75-1 1.50-1 1.25 1.00-1 0.75 0.50-j 0.25-J O.OO 0.00 0.25 E 1-50-1 e 11.25. S 1.00-1 ^ q 0.50H 0.00' Non-pharmacological — Pharmacologically-Induced o.oo — i — 0.25 —I— 0.50 I 0.75 1.00 1.25 HDL-C (mmol/L) Non-pharmacological • Pharmacological ly- Induced 0.50 0.75 1.00 HDL-C (mmol /L ) 1.25 Figure 24. Relative apparent 0.075 mM efflux comparison between groups I and II. Linear regression analyses of Group II (Panel A), Group I (Panel B), and the linear regressions plotted together (Panel C). One patient was removed from Group II (Panel D), which altered the linear regression plot comparison (Panel E). Values are the mean (± SD) of three determinations. Analysis of Covariance indicated the slopes of the two linear regression lines in Panel E were statistically significant different (p=0.036). 4 DISCUSSION 4.1 Optimization of the Fu5AH Cell Line Cholesterol Efflux Assay Before the Fu5AH cell line cholesterol efflux assay could be applied to patient serum, it was necessary to optimize the procedure. 4.1.1 Seeding the Cells A confluent cell monolayer was always used for the assay to limit the influence of confounding variables. Dividing cells synthesize significant amounts of cholesterol to meet the requirements of newiy-forming membranes [288]. The growth of confluent cells is inhibited by lack of space, thereby limiting the production of newly synthesized cholesterol. When the assay was run in the absence of cells, a small, but significant, amount of radiolabel was present on the plates and in the SCM following the assay (data not presented). This suggests that UC has the ability to bind non-specifically to the tissue culture plate. By having a confluent cell layer, the amount of plate surface area exposed to the serum-containing media is minimized, thereby decreasing the possibility of non-specific binding. 4.1.2 Radiolabeling the Cells The initial form of the radiolabel presented to the cells was unesterified cholesterol (UC). Over the approximately 48 hours of labeling, this UC was increasingly taken up by cells. The percentage of uptake was quite variable; one trial measured the label absorption to be just under 50% (Table 2), whereas a second trial suggested as much as 85% (Figure 9). The same ratio of UC:CE exists throughout the labeling process, supporting the findings that newly acquired cholesterol is assimilated into the cell's regulatory pool of UC, which has been shown to be in rapid equilibrium with the CE pool [84]. Therefore, the observed increases in uptake over time were likely to be only a result of increasing cell number, and not due to a slow rate of influx. 72 4.1.3 Equilibration of the Cellular Cholesterol Pools During the equilibration phase of the cell preparation, the percentage of. cholesteryl esters present in the cells substantially decreased. From the TLC analysis (Table 2), it was observed that a third band that remained at the spotting origin appeared at this time. The proportion of radioactivity in this third band was proportional to the loss in the CE band. Polar molecules tend to stay in the solid phase (silica gel) and less time in the mobile phase (solvent); therefore, the band represented a molecule that was more polar than unesterified cholesterol. Since this band was radioactive, the lipid it contained must have been a metabolized product of the original radiolabeled UC. Fu5AH cells do not synthesize significant amounts of bile acid [289]; therefore, it was believed to be an oxidized derivative of cholesterol (oxysterol). In support of this, oxysterols have been shown to be natural ligands for nuclear liver X-receptor a, which in part regulates biosynthesis and catabolism of cholesterol in hepatocytes [297]. Also, Fu5AH cells were observed to metabolize cholesterol and cholesterol derivatives into more polar oxysterols [298]. 4.1.4 Initial Rates of Efflux The observed initial larger efflux rate that occurs in the first half hour of the assay noticeably increases as the concentration increases (Figure 12). It is hypothesized that this initial efflux is a relatively rapid equilibration between the exofacial leaflet of the plasma membrane and the lipoprotein particles present in the media. The UC located on the plasma membrane is predominantly on the cytofacial leaflet [79]. Therefore, if the efflux from the exofacial leaflet represents a fast kinetic pool of UC, it would be reasonable to see an initial rapid efflux of relatively short duration. In support of this, distinct kinetic pools have been shown to exist [108], but the exact location of these pools still remains unknown. Another potential reason for this initial faster rate is that SR-BI has been shown to be able to bind apoB containing particles with high affinity [94, 290]. This binding results in selective uptake of LDL cholesteryl esters [182], and the bi-directional flux of UC with LDL [99]. This latter flux could be a component of this initial faster rate of efflux. It is unlikely that this exchange with LDL has continuing effects on the overall efflux because LDL are not internalized in Fu5AH cells [290] and the majority of LCAT 73 would be HDL-associated [155]. This is supported by the lack of correlation between efflux potential and LDL-C in Fu5AH cells [114]. 4.1.5 Consistency of Dose-Response Curve Parameters The cholesterol efflux at single serum concentrations produced intra-assay reproducibility comparable to other studies [114, 299]. However, the CVs of inter-assay measurements of apparent V m a x and Km were more variable. The upper-end of the serum dose-response curves was not well defined; therefore, the estimates of Vm a x and Km lacked a high degree of accuracy. A concentration of 20% serum was not exceeded because whole serum is cytotoxic to this cell line [114, 287]. Most serum dose-response curves still had substantial slope at 20% serum concentration; therefore, slight variations in individual measurements, especially in the 2.5% -10% serum concentration range, had significant effects on the extrapolated value of apparent V m a x . Since apparent Km was determined using the extrapolated apparent Vm ax value, it was subject to even more variation. To decrease the effect of outlier points on the calculated apparent V m a x and K m values, three trials of cholesterol efflux assays for each serum sample were conducted, and the mean value used for analysis. Some outlier points on the serum dose-response curves were likely due to pipetting error as evidenced by a significant decrease in total assay radioactivity for that well; however, exclusion of these points resulted in the same overall conclusions, so they were not excluded from curve generation. 4.1.6 Stability of Frozen Sera Over a 10-month period, the pooled sera standard maintained comparable efflux ability after a single cycle of freezing and thawing, consistent with the findings of others [114, 287]. However, there was a significant decrease in relative apparent Km values observed between fresh and frozen sera. A decrease in Km value signifies an increase in acceptor particle affinity. This is a rather surprising finding considering any changes in acceptor affinity would be expected to arise from a decrease in enzyme activity of LCAT or CETP which would theoretically decrease the efficiency at which the acceptor particle could accept UC. 74 Two possible explanations might account for this unexpected result. The simplest explanation is that the pooled standard that each assay was standardized against may have been estimated to have a higher Km than actual on the day that the frozen samples were assayed. The influence of outlier points on the value of Km have already been discussed; however, this is unlikely since the standard curves for the pooled sera standard had high values of goodness-of-fit on both days (R2=0.996 and R2=0.997). Due to the logistics of how this experiment was performed, fresh serum samples remained in a thawed state longer than frozen samples; therefore, it is possible that an enzyme such as PLTP may have fused smaller HDL particles creating larger particles with less affinity for accepting effluxed cholesterol. Despite the reduction in Km value, the slopes of the two linear regressions are very similar; therefore, relative comparisons made between sera do not significantly change for fresh and frozen sera. 4.2 Characterizing the Quality-Measuring Parameter of Km 4:2.1 Net Cholesterol Flux Cholesterol efflux assays seem deceptively simple in design. The name implies that cholesterol is mobilized from the cell and unidirectionally effluxed to an extracellular acceptor. SR-BI-mediated efflux is bidirectional; therefore, the rate of influx must also be assessed. When lipid-free apolipoproteins, cyclodextrins, phospholipid vesicles, or apolipoprotein/phospholipid complexes are used as the extracellular acceptors, a unidirectional efflux of cholesterol is stimulated in Fu5AH cells with a concomitant depletion of CE stores [288]. Thus, the net change in CE stores can be used to determine the direction of net cholesterol flux because these cells do not significantly metabolize any cholesterol. In this assay, SR-BI-mediated efflux drew from the UC pool and the oxysterol pool, but not the CE pool (Table 5). The fact that CE stores did not decrease suggests that there was no net efflux in this assay. This is supported by de la Llera Moya et al. [114] who found that the average cholesterol content of Fu5AH cells when incubated with test sera for four hours did not significantly change. The release of radiolabeled cholesterol to the serum is not surprising. Estimates suggest 50% of the total UC 75 leaves a cell every five to fifteen hours when synthesis of new cholesterol and holoparticle uptake of lipoproteins are suppressed [300]. Therefore, the data suggest there is bidirectional exchange of lipids. There was a greater proportional efflux from the oxysterol pool than the UC pool. Bjorkhem etal. [301] also found cells to more readily efflux oxysterols than UC. The significant change in TG content over the course of the assay observed in the same experiment is likely just by chance rather than reflective of any net flux. There is no evidence supporting the conversion of radiolabeled UC into TG in Fu5AH cells. When this quantification of radiolabel distribution before and after the assay was repeated using a serum of low HDL-C, no significant difference was detected. 4.2.2 Range of Apparent V m a x and Km Values in Healthy Individuals If the net efflux is truly zero in this assay, then the HDL is likely continuously recycled to form more acceptor particles as it delivers unlabeled cholesterol back to the cells. Two components exist in this assay: the cellular component that governs the release and subsequent uptake of cholesterol, and the serum component that dictates the rate at which HDL particles are remodeled to become efficient acceptors. Both components remain discrete from each other in Fu5AH cells with the exception of the transfer of lipid between the two. The rate-limiting step in this assay is largely believed to be this transport of cholesterol across the membrane [89, 302]. Under saturated concentrations of acceptor particle, the rate of cholesterol movement to extracellular particles is V m a x . The movement of cholesterol across the membrane is a cellular component of the assay and should not differ from assay to assay. Therefore, as long as the rate-limiting step remains the transport rate of cholesterol across the membrane, V m a x should be the same for all sera. The range of relative apparent Vm ax values obtained from the 17 healthy individuals was 83% -112%. The observed variation can be attributed to the poor definition of the serum-dose response curves in the higher ranges. For this reason, extrapolating V m a x from these curves would be inaccurate to some degree. The range of relative apparent Km values is expectedly a much wider range (67% -171%). The quality of the HDL is a serum-component and would likely greatly differ from individual to individual. 76 4.2.3 The Effects of LCAT Inhibition on Cholesterol Efflux DTNB is an effective reversible inhibitor of LCAT, reducing its activity by more than 99% at a 1.7 mM concentration [296]. When the pooled sera standard was treated with 1.7 mM DTNB, apparent V m a x was reduced by 90.2% (Figure 14). This severe impairment in cholesterol efflux emphasizes the importance LCAT plays in maintaining the concentration gradient in favour of efflux. The underlying assumption of all serum dose-response curves is that the cholesterol efflux maintains linear kinetics for at least four hours. It is almost certain that in the absence of functioning LCAT, the rate of cholesterol efflux is not maintained for four hours. It would be expected that the concentration gradient would be lost after an initial equilibration between the UC pools of the plasma membrane and the surface of lipoprotein particles. Therefore, the use of the parameter V m a x would not be a measure of a true rate, and should not be used. The rate-limiting step, in this example, has now shifted to a serum component and is why apparent V m a x was so drastically reduced under saturated conditions. Apparent Km values would also fail to be meaningful measurements when the rate-limiting step has switched to a serum component because of their dependence on apparent V m a x to be calculated. 4.2.4 Homozygous Familial LCAT Deficiency The sera of two patients homozygous for LCAT deficiency were also assayed using this cholesterol efflux assay for comparison to the DTNB-treated sera. The reduction in V m a x (Figure 15) was substantially less (67.4% and 62.6% reductions for LCAT7" III-6 and LCAT7" III-7, respectively) than the reduction observed with DTNB-treated serum (90.2%) when compared to the control pooled sera. As mentioned, these V m a x values are likely not an accurate measure of efflux rate. Despite this, the LCAT7" serum withdrew substantially more radiolabel from the cells than the DTNB-treated serum. Patients with LCAT deficiencies were shown to have an increased plasma concentration of phospholipid [303] compared to normolipidemic subjects. Therefore, LCAT7" serum has a higher carrying capacity than DTNB-treated serum. The lipid profiles of these patients (Table 7) are typical of LCAT7" individuals: severe absence of HDL, a non-elevated quantity of LDL particles, and a very elevated 77 TC/HDL-C ratio. In contrast, the DTNB-treated serum had an HDL-C=1.21 mmol/L. This difference in HDL-C emphasizes the importance of other qualitative factors, such as the phospholipid content. LCAT"7" patients lack HDL2 particles, but have a significant increase in the small, discoidal y-LpE particles [205]. One study that looked at the cholesterol efflux ability of a single LCAT"7" patient found that the rate of cellular cholesterol removal was not impaired in this patient compared to normal [207]. One weakness of that study was that they only investigated cholesterol efflux using an active transport mechanism (ABCA1). Prep-HDL and y-LpE particles can be very efficient acceptors of cholesterol from ABCA1 [87], but not from SR-BI [98, 304]. This difference emphasizes the different roles the two major mechanisms of efflux play in the overall process of RCT, and the fact that both methods should be investigated when assessing the cholesterol efflux ability of sera. 4.2.5 Limitations of Km in Assessing HDL Quality HDL's affinity for desorbed cholesterol (Km) results not only from the initial status of HDL and how well suited it is to receiving effluxed cholesterol, but also from how quickly another suitable acceptor particle can be regenerated. All the qualitative assessments of HDL (the relative distribution of HDL subclasses, the activities of CETP, LCAT, and PLTP, the content of apolipoproteins, TG, CE, and PL, and the species of PL contained on the HDL) belong to the serum component of the assay system used in this study. Because the serum component and the cell component are distinct from each other, and because simultaneous lipid uptake and efflux allows most of the HDL components to continue exerting their effect on the efflux rate, the Fu5AH cell line is suitable for assessing quality. In this study, Km is expressed in two different units. In terms of serum concentration, it gives an indication of the overall affinity of the serum for desorbed cholesterol. In terms of HDL-C concentration, it approximates each HDL particle's affinity for desorbed cholesterol. However, as evidenced by the data on DTNB-treated serum and sera from LCAT"7" patients, V m a x no longer remains constant, suggesting it is no longer an estimate of the maximal initial rate. Since the Km is calculated based on the value of Vmax, Km estimations are meaningless when V m a x is no longer constant. 78 4.3 Study Population Characteristics 4.3.1 Study Population Characteristics of Apparent V m a x As expected, the majority of sera assayed generated an estimated relative apparent V m a x within the range described for healthy controls (Figure 16). One patient exhibited a severe reduction in apparent V m a x (58%), while five others exhibited mild reductions in the range of 17-37% compared to the pooled sera standard. As previously reasoned, if the rate-limiting step is the transport of cholesterol across the plasma membrane, then all V m a x should be approximately the same. Therefore, it is believed that a large reduction in V m a x is the result of a shift in the rate-limiting step from the cellular component to a step in the serum component. The extremely low HDL-C (0.24 mmol/L) of the patient with the severe reduction is likely caused by a genetic defect in this serum component. The problem is not simply a lack of sufficient HDL particles to approach Vmax, because the serum from'one patient with an HDL-C = 0.39 mmol/L was still able to achieve an apparent V m a x well within the normal range. Even after the patients with a proposed dysfunctional serum component were removed from the data set, a slight positive linear trend (Figure 16) still exists in the data. This was surprising because all sera were expected to have the same V m a x . Despite the rate of efflux already being adjusted for the simple diffusion rate into the media, there is likely another simple diffusion rate down the concentration gradient to the extracellular particles that is maintained because of LCAT. If increasing HDL-C represents an increasing number of HDL particles, then the results are reflective of an increasing rate of simple diffusion with a greater number of particles (greater concentration gradient). 4.3.2 Study Population Characteristics of Apparent Km There is a strong negative linear relationship between apparent Km and HDL-C when K m is expressed in terms of percentage serum concentration (Figure 17, Panel A). That is, with increasing HDL-C, the serum exhibits greater affinity for desorbed UC. Because variations in quantity are not controlled for, two possible explanations can explain this result. First, an increase in the quantity of available acceptor particles in serum with high HDL-C would result in the assay system becoming saturated much 79 faster than serum with low HDL-C. Second, serum with high HDL-C might contain HDL particles with greater affinity for the. desorbed UC. To further investigate the contribution of quality to the overall efflux rate, apparent Km was also calculated in terms of HDL-C concentration (Figure 17, Panel B) to assess a "per particle" comparison. Somewhat surprisingly, it was found that HDL particles in patients with low HDL-C had higher affinity for desorbed UC than patients with high HDL-C. The relationship contradicts the inverse relationship between HDL-C and the degree of CAD [305]. Although the data fits Michaelis-Menten curve characteristics very well, there seems to be two components to this curve with the boundary between the two coincidentally around the risk factor cut-off of HDL=1.04 mmol/L. The upper end of the curve (HDL-C>1.1 mmol/L) exhibits only slight increases in apparent Km with increasing HDL-C, while the lower end of the curve (HDL-C<1.1 mmol/L) has much more slope. Further investigation into what was accounting for the seemingly paradoxical increased affinity at low HDL-C concentrations was carried out. 4.3.3 HDL-C Relationships with FERHDL and TG The fractional esterification rate of apoB-depleted serum has been shown to be a good predictor of HDL particle size distribution [293]. Patients with a high relative concentration of HDL3 particles have a higher FERHDL than patients with predominantly HDL2 particles. Our findings (Figure 18, Panel A) suggest that patients with HDL<1.1 mmol/L have an increasingly higher proportion of HDL3 particles. Although there seems to be no clear difference between the affinity of HDL subclasses for SR-Bl-mediated cholesterol efflux [114], HDU particles have been shown to have higher binding affinity for LCAT [155]. Therefore, the maintenance of the UC concentration gradient is not uniform across subclasses, and as a result HDL3 particles are a better extracellular cholesterol acceptor of desorbed UC than HDL2. This FERHDL data is consistent with the efflux data. The decrease in HDL particle size in patients with low HDL-C makes the HDL a better extracellular acceptor of cholesterol and increases HDL's affinity for desorbed cholesterol on a "per particle" basis. The relationship between TG and HDL-C (Figure 18, Panel B) provides a i possible explanation of why these patients have smaller HDL particles. The strong inverse association between TG and HDL-C concentrations has been well documented 80 [306], and is caused by increased activity of CETP in patients with hypertriglyceridemia, despite no change in CETP mass when compared with normotriglyceridemics [179]. The exchange of HDL cholesteryl esters with apoB-containing lipoprotein triglycerides would result in TG-rich HDL particles that are then hydrolyzed by HL into smaller H D L 3 particles [307]. 4.3.4 K m Compared to the Efflux Ability at a Single Concentration The cholesterol efflux capacity at a single serum concentration (0.075 mM HDL-C concentration) was calculated from each serum dose-response curve in order to compare with the obtained results for apparent Km. Most studies that have used the Fu5AH cholesterol efflux assay have assayed their test sera at a serum concentration of 5% only [251, 253, 256, 278, 283]. However, to measure the quality of HDL, it was reasoned that the resultsmust be calculated on a "per particle" basis and expressed in terms of HDL-C concentration. The average HDL-C concentration of all the patients at 5% serum concentration was 0.075 mM, so this was the concentration chosen. A curvilinear relationship was observed between 0.075 mM relative efflux and HDL-C (Figure 19) that was consistent with the HDL-C and Km relationship. The curves may seem to contradict each other by diverting in opposite directions; however, an increase in 0.075 mM relative efflux implies a greater potential for efflux, while a decrease in Km implies a higher affinity for cholesterol. From this simple comparison, it seems assaying sera at a single concentration has as much predictive power of "quality" as using apparent Km values. 4.4 Pharmacologically-Induced Changes in HDL-C Almost all of the parameters measured between groups I and II, and groups III and IV were not statistically significant. The statistically significant differences in TC and LDL-C between groups III and IV is not all that surprising. Many of the patients in group IV had natural levels of very high HDL-C, were not currently taking any medications, and could be generally described as healthy. However, the patients in group III were usually being treated for high LDL-C and/or elevated TC with a statin, which caused the significantly lower LDL-C and TC and increased HDL-C. Despite 81 some non-significant differences in other parameters, the two pairs of groups were fairly similar in characteristic, and comparisons were assumed to be valid. The differences between groups III and IV are unremarkable. As would be expected, apparent V m a x and apparent Km were quite consistent due to little difference in the quality of HDL above 1.1 mmol/L (Figure 17, Panel B). The slight positive slopes for the linear regressions of apparent V m a x and Km and slight negative slope for the linear regression of 0.075 mM efflux rate are completely compatible with the overall trends of the entire study population. The linear regression analysis of apparent V m a x in Group II demonstrated very equivalent values of apparent V m a x across the entire range of HDL-C for this group (Figure 22, Panel D). In contrast, the apparent V m a x values of group I were much more variable, theoretically because the pharmacological agents were in some way altering the serum component in these individuals. Despite the seemingly more random distribution of the apparent V m a x values in group I, there were still no significant differences between the two linear regressions (group I vs. group II). The patient with HDL-C = 0.24 was excluded from group II for the comparisons between groups I and II (Panel D of Figures 23-25) because of the severe reduction in V m a x and a suspected genetic defect in his serum component. This has been argued to invalidate the Km and 0.075 mmol/L efflux values. A comparison between the linear regressions of apparent Km values for groups I and II revealed no significant difference (Figure 24), and the comparison is largely unremarkable. However, when a single serum concentration of 0.075 mM was used to compare groups I and II (Figure 25), a significant difference was discovered. The negative linear relationship between relative apparent 0.075 mM efflux and HDL-C has already been described and reasons given for this trend. No such trend was observed in group I with a normalization of all the values to an efflux rate that is comparable to normal individuals. It should be noted that the two linear regressions (Figure 25, Panel E) intersect near the median HDL-C concentration for each group. Four patients had an increase in HDL-C due to their pharmacological agents, and the resultant HDL-C values were located to the higher side of this intersection point. Conversely, the other six patients had decreases in HDL-C due to their pharmacological agents, and the resultant HDL-C concentrations were all located to the lower side. Using the theory presented in the last section, this would suggest that 82 pharmacologically-induced changes in patients with HDL-C<1.04 mmol/L represent HDL particles that better compare to non-pharmacologically affected patients at the baseline HDL-C rather than the resultant changed HDL-C. It is highly unlikely that no HDL properties change as a result of pharmacological intervention. However, the data suggests that the interpretation of HDL-C values that are a result of a pharmacologically-induced change should perhaps be interpreted differently than non-pharmacologically induced values in patients with HDL-C<1.04 mmol/L. The study was not designed to single out any particular medication and further investigation into specific pharmacological effects is needed to characterize this difference. The fact that a single serum concentration was able to detect a difference between groups I and II, while apparent K m was not, was surprising. It was hypothesized that the use of the parameter Km would be a more thorough investigation into the quality of the HDL particles. However, as previously mentioned, the serum dose-response curves were poorly defined in the upper regions creating inaccurate estimates of apparent V m a x and K m . This inaccuracy of any individual measurement is reflected by the large standard deviations for K m values as compared to the 0.075 mM relative efflux values. Theoretically, the use of these two variables should still be a better assessment of the quality of the serum and HDL particles; however, the methodology used in this experiment seems to undermine this notion. Despite the lack of significant findings using apparent Km, V m a x may still be useful in diagnosing patients with genetic defects in their serum component. Further research is required to test this hypothesis. In summary, the quality of HDL particles is shown here to change with HDL-C. HDL3 have been previously shown to be better acceptors of cellular cholesterol than the larger HDL2 subtraction. The FERHDL of each serum sample predicts that as HDL-C decreases, HDL particles decrease in size. Compatible with this, the cholesterol efflux parameters show that as HDL-C decreases, the particles become better acceptors of cellular cholesterol via the SR-BI-mediated pathway. This is likely due to a relative increase in the PL/TC ratio of each particle as size decreases. This seems paradoxical that patients with lower HDL-C and typically higher incidence of CAD would generally have HDL particles with greater affinity for cholesterol desorption. It was hypothesized that HDL quality is a more predominant factor than HDL quantity in determining the rate of cholesterol efflux in vivo; however, this does not seem to be the case if RCT is the 83 major anti-atherogenic property of HDL, since quality cannot account for the increased rate of cardiovascular disease in patients with HDL-C<1.04 mmol/L. The data suggest that HDL-C is still a good predictor of the cholesterol efflux potential of serum and quality of HDL particles when HDL-C>1.04 mmol/L, regardless of pharmacological intervention. However, patients with pharmacologically-induced changes in HDL-C when HDL-C<1.04 mmol/L, have qualitatively different HDL particles than subjects with matched HDL-C and no pharmacologically-induced change, and may have to be considered differently. The measurement of Km to predict quality of HDL needs refinement under the current methodology. However, the use of serum dose-response curves may still prove useful. 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Abnormal capacity to induce cholesterol efflux and a new LpA-l pre-beta particle in type 2 diabetic patients. Clinica Chimica Acta, 279:1-14. 277. Dullaart, R.P. and van Tol, A., 2001. Twenty four hour insulin infusion impairs the ability of plasma from healthy subjects and Type 2 diabetic patients to promote cellular cholesterol efflux. Atherosclerosis, 157:49-56. 278. Fournier, N., Francone, O., Rothblat, G., Goudouneche, D., Cambillau, M., Kellner-Weibel, G., Robinet, P., Royer, L., Moatti, N., Simon, A., and Paul, J.L., 2003. Enhanced efflux of cholesterol from ABCA1 -expressing macrophages to serum from type IV hypertriglyceridemic subjects. Atherosclerosis, 171:287-293. 279. Sakr, S.W., Senault, C, Vacher, D., Fournier, N., and Girard-Globa, A., 1996. Oleic acid-rich fats increase the capacity of postprandial serum to promote cholesterol efflux from Fu5AH cells. 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Decreased activity of lecithin.cholesterol acyltransferase and hepatic lipase in chronic hypothyroid rats: implications for reverse cholesterol transport. Molecular and Cellular Biochemistry, 246:51 -56. 287. Jaspard, B., Fournier, N., Vieitez, G., Atger, V., Barbaras, R., Vieu, C , Manent, J., Chap, H., Perret, B., and Collet, X., 1997. Structural and functional comparison of HDL from homologous human plasma and follicular fluid. A model for extravascular fluid. Arteriosclerosis, Thrombosis, and Vascular Biology, 17:1605-1613. 288. Rothblat, G.H., de la Llera-Moya, M., Favari, E., Yancey, P.G., and Kellner-Weibel, G.; 2002. Cellular cholesterol flux studies: methodological considerations. Atherosclerosis, 163:1-8. 289. Rothblat, G.H. and Phillips, M.C, 1982. Mechanism of cholesterol efflux from cells. Effects of acceptor structure and concentration. Journal of Biological Chemistry, 257:4775-4782. 290. Friedman, G., Wernette-Hammond, M.E., Hui, D.Y., Mahley, R.W., and Innerarity, T.L., 1987. Characterization of lipoprotein receptors on rat Fu5AH hepatoma cells. Journal of Lipid Research, 28:1482-1494. 291. Cisar, L.A. and Bensadoun, A., 1987. Characterization of the intracellular processing and secretion of hepatic lipase in FU5AH rat hepatoma cells. Biochimica et Biophysica Acta, 927:305-314. 292. Bligh, E.G. and Dyer, W.J., 1959. A rapid method of total lipid extraction and purification. Canadian Journal of Medical Sciences, 37:911-917. 293. Dobiasova, M. and Frohlich, J., 1996. Measurement of fractional esterification rate of cholesterol in plasma depleted of apoprotein B containing lipoprotein: methods and normal values. Physiological Research, 45:65-73. 294. Frohlich, J., McLeod, Ft., Pritchard, P.H., Fesmire, J., and McConathy, W., 1988. Plasma lipoprotein abnormalities in heterozygotes for familial lecithin:cholesterol acyltransferase deficiency. Metabolism, 37:3-8. 295. Friedewald, W.T., Levy, R.I., and Fredrickson, D.S., 1972. Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge. Clinical Chemistry, 18:499-502. 112 296. Bielicki, J.K. and Forte, T.M., 1999. Evidence that lipid hydroperoxides inhibit plasma lecithin:cholesterol acyltransferase activity. Journal of Lipid Research, 40:948-954. 297. Alberti, S., Schuster, G., Parini, P., Feltkamp, D., Diczfalusy, U., Rudling, M., Angelin, B., Bjorkhem, I., Pettersson, S., and Gustafsson, J.A., 2001. Hepatic cholesterol metabolism and resistance to dietary cholesterol in LXRbeta-deficient mice. Journal of Clinical Investigation, 107:565-573. 298. Kilsdonk, E.P., Morel, D.W., Johnson, W.J., and Rothblat, G.H., 1995. Inhibition of cellular cholesterol efflux by 25-hydroxycholesterol. Journal of Lipid Research, 36:505-516. 299. Fournier, N., Atger, V., Cogny, A., Vedie, B., Giral, P., Simon, A., Moatti, N., and Paul, J.L., 2001. 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Clinica Chimica Acta, 286:243-255. 113 6 APPENDICES 6.1 Appendix A: Group I Serum Dose-Response Curves Patient #001: Patient #001 Trial #1 Patient #001 Trial #2 Patient #001 Trial #3 * Lab Pool V~,= 62.00% Km =121.8 | i M • Patient #001 l/™»= 52.22% Km = 63.3 U.M 20 Lab Pool VM = 59.39% K„ = 91.2u.M Patient # 0 0 1 «W- 4 8 ' 6 0 % /<„ > 59.0 U.M 20 25 • Lab Pool V™*= 58.67% Km = 137.0 U.M • Patient #001 Vmx- 41.59% K m = 51 .6pM HDL-C=0.60 mM TC=9.18mM LDL-C=NC TG=10.71 mM apo-AI=0.54 g/L Patient #003: Patient #003 Trial #1 Patient #003 Trial #2 Lab Pool Vm= 65.43% K „ = 9 3 . 9 M M Patient # 0 0 3 V m x = 66.36% K m = 68.7u.M Patient #003 Trial #3 Lab P xy Km,* 5 8 . 6 7 % K „ = 1 3 6 . 9 | i M Patient # 0 0 3 V ™ , = 5 7 . 1 0 % K „ , = 7 8 . 9 ( i M 20 20 25 HDL-C=0.63mM TC=5.33 mM LDL-C=NC TG=10.71 mM apo-AI=1.01 g/L Patient #007: Patient #007 Trial #1 Patient #007 Trial #2 Patient #007 Trial #3 Lab Pool Vmx= 72.23% K„ = 95.4u.M Patient # 0 0 7 V r a , = 58.11% «•„ = 38.1 MM 20 Lab Pool V „ , = 69.12% K m = 104.3 uM Patient # 0 0 7 66.92% K m = 65.9 nM 20 25 Lab Pool Vm= 5 8 . 6 7 % Km= 1 3 7 . 0 (lM Patient # 0 0 7 1 / ™ , = 4 8 . 2 1 % K „ = 7 0 . 1 M M 20 25 HDL-C=0.92mM TC=10.44mM LDL-C=7.42 mM TG=4.56 mM apo-AI=0.99 g/L 114 Patient #012: Patient #012 Trial #1 l a b Poo! V™«= 65.10% K„m 148.6 nM Patient #012 Vm,= 56.87% Km= 101.2 nM Patient #012 Trial #2 Patient #012 Trial #3 20 25 • Lab Pool 63.45% /("„,= 115.2 (iM • Patient #012 V „ , = 50.51% K „ = 8 6 . 6 u . M 20 2? HDL-C=0.76 mM TC=4.37 mM LDL-C=1.77 mM TG=4.00 mM apo-AI=0.99 g/L Patient #018: Patient #018 Trial #1 Patient #018 Trial #2 Patient #018 Trial #3 K m = 148.6 nM Patient #018 !/„,»= 47.75% K„=57 .9u .M • Lab Pool 11-^ ,= 53.00% Km = 61.7u.M • Patient #018 46.75% Km=30.3nM 25 HDL-C=0.65 mM TC=8.02 mM LDL-C=5.80 mM TG=3.41 mM apo-AI=0.73 g/L Patient #023: Patient #023 Trial #1 Patient #023 Trial #2 Patient #023 Trial #3 Lab Pool I/™, = 65.20% Km=113.9nM Patient #023 V™,= 69.78% K„,= 88.8nM 20 25 • U b Pool 1^,= 69.12% K m =867nM ' Patient #023 V™«= 69.01 % Km=89.9u.M 20 25 Lab Pool Vm.' 57.64% /C„=75.1 nM Patient #023 1/™,= 52.84% K „ = 46 .6 t iM HDL-C=0.93mM TC=4.70 mM LDL-C=2.94 mM TG=1.80mM apo-AI=1.16 g/L 115 Patient #037: Patient #037 Trial #1 Lab Pool Vma= 65.12% «•„. 107.1 (lM Patient #037 Vm„ = 62.94% K„ = 77.4 U.M Patient #037 Trial #2 20 25 I..30 POOl Vm= 72.39% Km= 122.5 U.M Patient #037 I/™, = 66.21% K„ = 87.6nM Patient #037 Trial #3 20 25 Lab Pool Vm = 58.65% K„ = 72.2nM Patient #037 V W , = 65.02% K m = 71.5u.M 20 21 HDL-C=0.82mM TC=5.59 mM LDL-C=2.75 mM TG=4.40 mM apo-AI=1.14 g/L Patient #039: Patient #039 Trial #1 Patient #039 Trial #2 Patient #039 Trial #3 Lab Pool V r a x = 65.12% Km= 107.1 nM Patient #039 V r a > = 62.25% K„ = 64.4u.M 20 Lab Pool V™,= 72.39% K„= 122.5 nM Patient #039 ! / „ , = 73.99% K„ = 70 .0pM 20 25 Vm,- 50.28% Km= 117.0 nM Patient #039 V r a , = 51.50% K m = 6 6 . 6 l i M 20 25 HDL-C=0.58mM TC=8.63 mM LDL-C=NC TG=19.03mM apo-AI=0.97 g/L Patient #042: Patient #042 Trial #1 Patient #042 Trial #2 Patient #042 Trial #3 I 3 - Lab Pool ! V„,= 65.43% K„ = 93.9nM ' Patient #042 i Vm= 40.34% K„=36.5nM * • Lab Poo! V„m 60.61 % K„ = 65.5nM ' Patient #042 V„,= 37.88% HDL-C=0.44mM TC=4.67 mM LDL-C=0.78 mM TG=7.49 mM apo-AI=0.56 g/L Patient #048: Patient #048 Trial #1 • Lab Pool V»»= 63.00% K„ = 61.7nM • Patient #048 = 41.21% K„=18.3 U.M Patient #048 Trial #2 Lab Pool I W - 50.28% /Cm=117.0nM Patient #048 V„„= 49.93% K „ = 5 3 . 2 u . M HDL-C=0.40mM TC=3.88 mM LDL-C=1.02 mM TG=5.34 mM apo-AI=Not Done 116 6.2 Appendix B: Group II Serum Dose-Response Curves Patient #010: Patient #010 Trial #1 Patient #010 Trial #2 Patient #010 Trial #3 Lab Pool Vm = 58.67% K„, = 137.0 iiM Patient #010 V T O = 22.00% K m =10.5l lM HDL-C=0.24 mM TC=8.28 mM LDL-C=NC TG=8.94 mM apo-AI=0.27 g/L Patient #011: Patient #011 Trial #1 Patient #011 Trial #2 Patient #011 Trial #3 Lab Pool 65.10% K „ = 148.6 \M Patient #011 ! / „ ,= 49.09% Km = 60.9 nM HDL-C=0.65 mM TC=5.51 mM LDL-C=3.28 mM TG=3.44 mM apo-AI=0.72 g/L Patient #014: Patient #014 Trial #1 Patient #014 Trial #2 Patient #014 Trial #3 Lab Pool Vm,= 65.10% « „ = 1 4 8 . 6 n M Patient #014 V U , = 54.28% K„, = 8 7 . 5 | i M Lab Pool ^ = 6 0 . 6 1 % K„ - 65.5 U.M Patient #014 iU,.. 49.07% « „ = 41 .5pM 20 25 HDL-C=0.85mM TC=5.44 mM LDL-C=3.16mM TG=3.10mM apo-AI=1.10 g/L 117 Patient #024: Patient #024 Trial #1 Patient #024 Trial #3 Patient #024 Trial #2 * Lab Pool Vm, = 53.45% K m = 1 1 5 . 2 u . M ' Patient #024 Vm,- 57.60% K m = 5 7 . 0 u . M HDL-C=0.39 mM TC=4.21 mM LDL-C=NC TG=10.26mM apo-AI=0.82 g/L Patient #029: Patient #029 Trial #1 Patient #029 Trial #2 • Lab Poo l Vm,- 68.20% /C„ = 77.5(iM • Patient #029 Vm,- 57.18% K m = 77.6u.M Lab Pool Vm,. 57.64% K m = 7 5 . 1 jtM Patient #029 Vm,- 54.27% Km- 58.0MM 20 25 20 HDL-C=0.78mM TC=3.35 mM LDL-C=0.55 mM TG=4.39 mM apo-AI=1.16 g/L Patient #032: Patient #032 Trial #1 Patient #032 Trial #2 Patient #032 Trial #3 Lzib Fool Vm,= 59.39% K m = 91.2u.M Patient #032 Vm,- 70.02% K„ = 94.1 | i M Lab Pool Km, = 53.45% K„,= 115.2u.M Patient #032 V™*= 61.29% K„,= 100.9u.M Lab Pva\ Vm,- 58.65% Km=7Z2\M Patient #032 Vm,- 60-32% K„,= 50.0u.M HDL-C=0.71 mM TC=4.90 mM LDL-C=NC TG=9.78 mM apo-AI=1.10 g/L Patient #041: Patient #041 Trial #1 • Lab Pool V„,= 65.12% K„ = 107.1 (iM • Patient #041 V„,= 59.31% K„ = 71.9 U.M Patient #041 Trial #2 20 -1 Lab Pool Vm,- 72.39% = 122.5 (lM Patient #041 1 ^ = 60.95% K m = 7 5 . 3 U.M Patient #041 Trial #3 20 Lab Pool V r a x = 50.28% /<m=117.0u.M Patient #041 V™*= 50.72% K„,= 102.5 U.M HDL-C=1.06mM TC=7.40 mM LDL-C=3.70 mM TG=5.73 mM apo-AI=1.34 g/L 118 Patient #043: Patient #043 Trial #1 Patient #043 Trial #2 Patient #043 Trial #3 Lab Pool V„a,= 60.61% K m = 6 5 . 5 u . M Patient #043 1/™,= 51.93% K m = 118.1 MM 25 HDL-C=1.07 mM TC=3.94 mM LDL-C=0.78 mM TG=4.55 mM apo-AI=1.23 g/L Patient #044: Patient #044 Trial #1 Patient #044 Trial #2 Patient #044 Trial #3 Lab Poo l V™»= 65.43% K m = 93.9 pM Patient #044 Vm= 59.63% tfm = 63.8 20 29 Lab Pool V * . - 60.61% K m = 65.5 \M Patient #044 V m x = 54.24% K m = 88.4 uM 20 25 Lab Poo l 1/™X= 50.28% Km=117.0|lM Patient #044 V™»= 48.49% K„ - 90.8 nM 20 25 HDL-C=0.93mM TC=5.44 mM LDL-C=3.36 mM TG=2.50 mM apo-AI=1.30 g/L Patient #045: Patient #045 Trial #1 Lab Pool V„,= 65.43% K m = 93.9u.M Patient #045 1/™,= 62.20% K„ = 672 U.M Patient #045 Trial #2 20 25 . Lab Pool V « « = 60.61 % K„, = 65.5u.M > Patient #045 Vmt= 54.93% K„ = 46.2nM Patient #045 Trial #3 20 25 Lab Pool V™,= 50.28% K „ = 1 1 7 . 0 p M Patient #045 V_= 51.60% K m = 9 0 . 0 u M 20 HDL-C=0.77mM TC=4.07 mM LDL-C=1.82 mM TG=3.21 mM apo-AI=0.92 g/L 119 6.3 Appendix C: Group III Serum Dose-Response Curves Patient #004: Patient #004 Trial #1 Patient #004 Trial #2 Patient #004 Trial #3 ,ab Pool V™,= 72.23% /<„=122 .7 j iM Patient #004 Vm»= 72.20% K m = 95 .4 | jM • Lai) Poo l Vm,= 65.43% K m = 9 3 . 9 u M • Patient #004 Vm.* 73.98% Km = 153.5 nM 20 25 Lab Pool Vm,' 56.67% X m = 137.0 ^iM Patient #004 Vm.= 61.50% « m = 200.3 | i M 20 25 HDL-C=2.95 mM TC=4.59 mM LDL-C=1.14mM TG=1.09mM apo-AI=2.08 g/L Patient #005: Patient #005 Trial #1 Patient #005 Trial #2 Patient #005 Trial #3 ab Pool Vm.= 72.23% /<"„,= 95.4 nM Patient #005 Vmax= 70.49% Km= 120.4 pM 20 25 Lab Pool Vma*= 65.43% K„,= 93.9 u-M Patient #005 V™,= 71.06% Km- 131.8MM Lab Pool V™»= 58.67% Km- 137.0MM Patient #005 56.87% K m = 160.6MM 20 25 HDL-C=2.26mM TC=5.63 mM LDL-C=3.06 mM TG=0.68 mM apo-AI=1.89 g/L Patient #013: Patient #013 Trial #2 Patient #013 Trial #3 Patient #013 Trial #4 Lab Pool Vm.= 59.39% Km = 9 1 . 2 M M Patient #013 Vm.' 58.38% Km= 125.8 M M 20 25 Lab Pool Vmax = 6 0 . 6 1 % K „ - 6 5 . 5 M M Patient #013 V ™ » = 6 6 . 4 6 % ff„= 1 0 5 . 7 M M 20 25 Lab Pool Vm.' 44.41% /C„= 125.5MM Patient #013 V m x = 45.52% Km= 166.9MM 20 HDL-C=2.34mM TC=6.67 mM LDL-C=3.92 mM TG=0.90 mM apo-AI=1.82 g/L 120 Patient #017: Patient #017 Trial #2 Patient #017 Trial #3 Lab Pool l / m , = 69.12% K m = 8 6 . 7 u . M Patient #017 Vmx= 77.70% K„,= 118.4| jM 20 Lab Pool Vm= 53.00% K„, = 61.7 (iM Patient #017 I/™, = 60.88% « „ = 91 .7nM 20 HDL-C=2.22 mM TC=5.27 mM LDL-C=2.32 mM TG=1.59mM apo-AI=1.85 g/L Patient #019: Patient #019 Trial #1 Patient #019 Trial #2 Patient #019 Trial #3 Lab Pool V„,= 69.12% K m = 8 6 . 7 u . M Patient #019 1^ ,= 78.30% *C m =150.2 | iM "max-/rm=ei.7|iM Patient #019 Vm,= 60.63% K„ = 90.4u.M 20 20 25 HDL-C=2.24mM TC=5.47 mM LDL-C=2.75 mM TG=1.05mM apo-AI=1.69 g/L Patient #021: Patient #021 Trial #1 Patient #021 Trial #2 Patient #021 Trial #3 Lab Poof Vmx= 65.20% Km = 113.9 uM Patient #021 !/„,,= 54.78% Km= 125.1 uM 20 25 Lab Pool l / r a > = 69.12% K„ = 86.7 uM Patient #021 !/„,,= 77.33% Km =131.3 MM 20 25 HDL-C=2.57mM TC=6.90 mM LDL-C=3.84 mM TG=1.07mM apo-AI=1.69 g/L 121 Patient #025: Patient #025 Trial #1 Las Pool V™,= 65.05% Km=75.8nM Patient #025 Vmx= 63.65% K m = 9 4 . 0 u . M Patient #025 Trial #2 Patient #025 Trial #3 20 25 • Lab Poo l V„,= 53.45% K m = 1 1 5 . 2 u M • Patient #025 V^. 53.53% K m = 1 3 0 . 9 l i M US Poo: V™»= 57.64% K„ = 7 5 . 1 uM Patient #025 Vm,- 65.46% K „ = 7 0 . 0 n M 20 20 25 HDL-C=1.73mM TC=5.90 mM LDL-C=3.60 mM TG=1.23mM apo-AI=1.62 g/L Patient #028: Patient #028 Trial #1 Patient #028 Trial #2 Lab Pool V ™ , - 6 5 . 1 2 % Km= 107.1 lM Patient #028 V „ „ = 66.27% Km - 111.4 U.M 20 25 Las Pool Vnw,= 72.39% Km- 122.5 \M Patient #028 Vm,- 70.86% Km = 121.3 (iM 2C Patient #028 Trial #3 Patient #028 Trial #4 Lab Pool Vm,- 53.45% K„=115 .2u :M Patient #028 V„,- 59.56% K „ = 162.4 U.M 20 25 HDL-C=2.04 mM TC=6.68 mM LDL-C=3.95 mM TG=1.51 mM apo-AI=2.39 g/L Patient #030: Patient #030 Trial #1 Patient #030 Trial #2 Patient #030 Trial #3 V„,- 65.12% K m = 107.1 U.M Patient #030 ^ , = 60.48% K m =111 .4nM Lab Poo l Vm,- 72.39% Km= 122.5 U.M Patient #030 Vm,-72.18% K „ = 1 1 7 . 3 u . M 25 Lab Pool V„,- 57.64% K m = 7 5 . 1 | i M Patient #030 Vm- 58.73% K m =98 .1 U.M HDL-C=1.75mM TC=4.56 mM LDL-C=2.22 mM TG=1.28mM apo-AI=1.77 g/L 122 Patient #038: Patient #038 Trial #1 Patient #038 Trial #2 Patient #038 Trial #3 Lab Pool V„,*6S.W% Km* 107.1 nM Patient #038 Vm,* 63.18% K„=152.0u .M 20 25 Lab Pool Vm,* 72.39% /< m =170 .6nM Patient #038 1/™,= 68 .70% Km = 122.5 l iM 20 Lab Pool V „ „ = 58.65% 9 n M Patient #038 Vm,* 58.15% X „ = 7 2 2 M M HDL-C=1.84 mM TC=3.82 mM LDL-C=1.56mM TG=0.91 mM apo-AI=1.70 g/L Patient #046: Patient #046 Trial #1 Patient #046 Trial #2 Patient #046 Trial #3 Lab Pool Vm,* 50.28% *fm=117.0 \M Patient #046 Vm,* 55.35% Km* 144.8MM 20 25 HDL-C=2.00mM TC=6.98 mM LDL-C=3.60 mM TG=2.99 mM apo-AI=2.12 g/L 123 6.4 Appendix D: Group IV Serum Dose-Response Curves Patient #008: Patient #008 Trial #1 Patient #008 Trial #2 Patient #008 Trial #3 Lab Poo! 6 9 . 1 2 % «4= 8 6 . 7 M M Patient #008 Vm,= 7 4 . 1 9 % Km- 1 3 9 . 3 U.M Lab Poo! Vm.- 58.67% Km= 137.0 U.M Patient # 0 0 8 l / m , = 60.48% / C M = 177.1 M M 20 HDL-C=0.24 mM TC=8.28 mM LDL-C=NC TG=8.94 mM apo-AI=0.27 g/L Patient #015: Patient #015 Trial #1 Patient #015 Trial #2 Patient #015 Trial #3 Lab Pool Vm,- 7 0 . 4 2 % Km- 1 0 2 . 0 M M Patient # 0 1 5 Vm,- 7 4 . 1 5 % K R A = 1 8 1 . 0 M M Lab Poo' V ^ , . 5 8 . 2 0 % K „ = 7 7 . 5 M M Patient #015 V „ „ = 6 8 . 1 9 % K „ = 1 5 3 . 0 M M * Lab Pool V „ „ = 5 3 . 0 0 % K M = 6 1 . 7 M M • Patient #015 V ™ , = 6 1 . 9 9 % K M = 1 0 6 . 9 M M 20 25 HDL-C=0.24mM TC=8.28 mM LDL-C=NC TG=8.94 mM apo-AI=0.27 g/L Patient #020: Patient #020 Trial #1 Patient #020 Trial #2 Patient #020 Trial #3 Lab Pool Vm.- 6 5 . 2 0 % K M = 1 1 3 . 9 M M Patient # 0 2 0 Vm.- 6 5 . 2 1 % K„- 1 4 5 . 0 M M 20 25 Lab Poo! Vm.-69.12% « „ = 8 6 7 M M Patient # 0 2 0 Vm.- 7 5 . 3 2 % Km- 1 3 4 . 8 M M 20 25 * Lab Pool V „ » , = 5 3 . 0 0 % « „ = 6 1 . 7 M M • Patient # 0 2 0 Vm,- 6 0 . 6 0 % K „ = 8 3 . 8 M M 20 25 HDL-C=0.24mM TC=8.28 mM LDL-C=NC TG=8.94 mM apo-AI=0.27 g/L 124 Patient #031: Patient #031 Tr ia l #1 Patient #031 Trial #2 Patient #031 Tr ia l #3 Lab Poo! Vm- 65.20% « „ = 1 1 3 . 9 M M Patient # 0 3 1 Vm= 45.83% « m = 62.2(iM 20 25 Lab Poo! Vmx= 53.45% Patient #031 V™,= 50.11% Km = 122.6 U-M 20 - Lab Pool V™ x = 58.65% Km = 722\iM • Patient # 0 3 1 1/™,= 63.68% K „ = 1 0 1 . 2 u M 20 25 HDL-C=0.24mM TC=8.28 mM LDL-C=NC TG=8.94 mM apo-AI=0.27 g/L Patient #033: Patient #033 Tr ia l #1 Patient #033 Tr ia l #2 Patient #033 Tr ia l #3 Lab Poo! V „ , = 59.39% K„,= 135 .9MM Patient # 0 3 3 V « » = 58.19% K m = 91 .2 l iM 20 25 Lab Pool VmK = 5 8 . 6 5 % « „ = 7 2 2 ( l M Patient # 0 3 3 Vm= 6 1 . 6 2 % /C m = 1 1 5 . 1 n M HDL-C=0.24mM TC=8.28 mM LDL-C=NC TG=8.94 mM apo-AI=0.27 g/L Patient #034: Patient #034 Trial #1 Patient #034 Trial #2 Patient #034 Trial #3 Lab Poo! 65.20% K„ = 113.9 U.M Patient # 0 3 4 vmu* 59.69% Km = 102.9 MM 20 25 Lab Pool 53.45% Km•1155 M M Patient # 0 3 4 ^rox= 64.27% K m - 117.9 MM 25 Lai; Pool V m , = 58.65% K m = 72 .2nM Patient # 0 3 4 75.10% K m = 128.7MM 20 25 HDL-C=0.24mM TC=8.28 mM LDL-C=NC TG=8.94 mM apo-AI=0.27 g/L 125 Patient #035: Patient #035 Trial #1 Patient #035 Trial #2 Patient #035 Trial #3 • Lab Poof Vmx- 65.12% K m = 107.1 u M • Patient #035 Vrm- 61.46% K„,= 130.3uM 20 25 Lab Pool 72.39% K „ = 122.5 \M Patient #035 / ™ , = 71.92% K„= 182.8 U.M LoO Poo: 58.65% K „ = 7 2 2 M M Patient #035 = 59.92% K „ = 9 4 . 5 u M 20 25 HDL-C=0.24mM TC=8.28 mM LDL-C=NC TG=8.94 mM apo-AI=0.27 g/L Patient #036: Patient #036 Trial #1 Lab Poo! 1/™,= 65.12% Km= 107.1 uM Patient #036 Vmx= 65.75% Km= 126.5 uM Patient #036 Trial #2 20 25 Lab Pool 72.39% « m = 122.5 uM Patient #036 V*_- 70.95% K m = 1 2 2 2 | i M 05 Patient #036 Trial #3 "max -K m = 7 2 . 2 | i M Patient #036 V W = 69.84% Km= 112.8 J0.M 20 25 20 25 HDL-C=0.24mM TC=8.28 mM LDL-C=NC TG=8.94 mM apo-AI=0.27 g/L Patient #047: Patient #047 Trial #1 * Lab Pool V^- 53.00% « „ = 61 .7nM " Patient #047 Vnyu = 61.40% K„ = 64.7u.M Patient #047 Trial #2 20 • Lab Poo l Vm„= 57.64% K„ = 75.1 uM • Patient #047 V™»= 64.86% K m = 109.8 uM Patient #047 Trial #3 Lab Pool 50.29% K „ = 1 2 4 . 4 u . M Patient #047 V™ x = 53.21% Km= 149.9 U.M HDL-C=0.24mM TC=8.28 mM LDL-C=NC TG=8.94 mM apo-AI=0.27 g/L Patient #049: Patient #049 Trial #1 Lab Pool ^ , = 50.29% Km= 124.4 uM Patient #049 V„,,= 48.65% «„,= 146.0 U.M Patient #049 Trial #2 20 25 • Lab Pool Vm,= 44.41% K„= 125.5 U.M • Patient #049 v ™ , = 40.56% K m =139 .8u .M Patient #049 Trial #3 20 Lab Pool l/™»= 44.41% /<„= 146.1 U.M Patient #049 Vm,= 43.36% « m = 125.5 uM 20 : HDL-C=0.24mM TC=8.28 mM LDL-C=NC TG=8.94 mM apo-AI=0.27 g/L 126 CD Relative Frequency Relative Frequency Relative Frequency Relative Frequency 

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