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Record for a UF thesis. Title & abstract won't display until thesis is accessible after 2011-12-31.

Permanent Link: http://ufdc.ufl.edu/UFE0024972/00001

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Title: Record for a UF thesis. Title & abstract won't display until thesis is accessible after 2011-12-31.
Physical Description: Book
Language: english
Creator: Price, Elvin
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2009

Subjects

Subjects / Keywords: Pharmaceutics -- Dissertations, Academic -- UF
Genre: Pharmaceutical Sciences thesis, Ph.D.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Statement of Responsibility: by Elvin Price.
Thesis: Thesis (Ph.D.)--University of Florida, 2009.
Local: Adviser: Zineh, Issam.
Local: Co-adviser: Johnson, Julie A.
Electronic Access: INACCESSIBLE UNTIL 2011-12-31

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2009
System ID: UFE0024972:00001

Permanent Link: http://ufdc.ufl.edu/UFE0024972/00001

Material Information

Title: Record for a UF thesis. Title & abstract won't display until thesis is accessible after 2011-12-31.
Physical Description: Book
Language: english
Creator: Price, Elvin
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2009

Subjects

Subjects / Keywords: Pharmaceutics -- Dissertations, Academic -- UF
Genre: Pharmaceutical Sciences thesis, Ph.D.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Statement of Responsibility: by Elvin Price.
Thesis: Thesis (Ph.D.)--University of Florida, 2009.
Local: Adviser: Zineh, Issam.
Local: Co-adviser: Johnson, Julie A.
Electronic Access: INACCESSIBLE UNTIL 2011-12-31

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2009
System ID: UFE0024972:00001


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1 LIVER X RECEPTOR ALPHA (LXRA) GENE POLYMORPHISMS IN CARDIOVASCULAR DISEASE AND FENOFIBRATE RESPONSE By ELVIN TYRONE PRICE A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2009

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2 2009 Elvin T. Price

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3 Dedicated to my lord and savior Jesus Christ

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4 ACKNOWLEDGMENTS I thank my wife, son, parents, grandparents and all of my family and friends. I would like to thank Dr. Julie A. Johnson for extending the opportunity for me to join this graduate program and her personal mentorship. I would like to thank Dr. Issam Zineh for his mentorship with the d evelopment and execution of this project. Furthermore, I would like to thank him for sharing with me his enthusiastic approach to science and life. I would like to thank Dr. Reginald F. Frye for his support throughout my development as a graduate student. My first scientific works were in his laboratory and this resulted in my passion for nuclear receptors. I would like to thank Dr. Hendeles for his support over the years. I have admired his professionalism and passion for science also. I would like to thank him for sharing his personal advice on starting a career and balancing family life. I would like to thank Dr. Marian C. Limacher for her support during my development as a graduate student. The time that she dedicated to this project was valuable an d I will never forget her willingness to collaborate. Furthermore, I would like to thank her for the lessons on writing and presentation of data. I would like to thank Dr. Gregory Welder for his personal sacrifices and time with this project. I would like to thank the graduate students of the College of Pharmacy in Pharmaceutics for the support over the years. I would like to thank my church family at Greater Bethel A.M.E. Church for continuous encouragement and support for the time that I have been a gra duate student at the University of Florida.

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5 TABLE OF CONTENTS page ACKNOWLEDGMENTS ................................ ................................ ................................ ........... 4 LIST OF TABLES ................................ ................................ ................................ ...................... 8 LIST OF FIGURES ................................ ................................ ................................ .................... 9 ABSTRACT ................................ ................................ ................................ ............................. 11 CHAPTER 1 INTRODUCTION/BACKGROUND CHAPTER ................................ ............................... 13 Liver X Receptor: A Central Regulator of Cardiometabolic Homeostasis ........................... 13 Liver X Receptor Alpha and Cholesterol and Lipid Homeostasis ................................ 14 Liver X Receptor Alpha and Vascular Homeostasis ................................ ..................... 14 Liver X Receptor Alpha and Inflammation ................................ ................................ .. 15 LXR A/NR1H3 as a CVD Susceptibility Gene ................................ ................................ .... 16 The Effects of Fenofibrate on Neutrophil Chemokines ................................ ....................... 17 Significance ................................ ................................ ................................ ....................... 18 2 LIVER X RECEPTOR ALPHA GENE PLOYMORPHISMS AND VARIABLE RISK IN PATIENTS TREATED WITH ANTIHYPERTENSIVE THERAPY: RESULTS FROM THE INVEST GENES STUDY ................................ ................................ ............. 23 Introduction ................................ ................................ ................................ ........................ 23 Methods ................................ ................................ ................................ ............................. 24 Study Participants ................................ ................................ ................................ ........ 24 The INVE ST GENES Case Control Population ................................ ................... 25 DNA Collection and Genotyping ................................ ................................ .......... 25 Statistics ................................ ................................ ................................ ...................... 26 Results ................................ ................................ ................................ ............................... 27 Associations of LXRA Genotypes and Primary/Secondary Outcomes ......................... 27 Pharmacogenetic Associations with LXRA Genotypes ................................ ................ 28 LXRA Diplotypes and Primary Outcomes by Treatment Strategy ................................ 29 Discussion ................................ ................................ ................................ .......................... 29 3 EFFECT OF FENOFIBRATE ON ENDOTHELIAL PRODUCTION OF NEUTROPHIL CHEMOKINES IL 8 AND ENA 78 ................................ ......................... 40 Introduction ................................ ................................ ................................ ........................ 40 Materials and Methods ................................ ................................ ................................ ....... 41 Cell Culture Experiments ................................ ................................ ............................ 41 Protein Quantification and Gene Expression ................................ ................................ 42 Statistical Analysis ................................ ................................ ................................ ...... 42

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6 Results ................................ ................................ ................................ ............................... 43 Fenofibrate Effects on Endothelial IL 8 and E NA 78 Production ................................ 43 Fenofibrate Effects ENA 78 mRNA Production ................................ .......................... 43 Discussion ................................ ................................ ................................ .......................... 44 4 EFFECT OF FENOFIBRATE ON NEUTROPHIL CHEMOKINES IN PEOPLE WITH SUB OPTIMAL LIPOPROTEIN PROFILES: EXPLORATORY ANALYSIS OF A RANDOMIZED, DOUBLE BLIND, PLACEBO CONTROLLED STUDY ...................... 51 Introduction ................................ ................................ ................................ ........................ 51 Subjects and Methods ................................ ................................ ................................ ......... 52 Subjects ................................ ................................ ................................ ....................... 52 Blood Samp ling and Analysis ................................ ................................ ...................... 54 Statistical Design/Considerations ................................ ................................ ................ 54 Results ................................ ................................ ................................ ............................... 55 Discussion ................................ ................................ ................................ .......................... 56 5 CONCLUSIONS ................................ ................................ ................................ ................ 65 Final Conclusions ................................ ................................ ................................ ............... 68 APPENDIX A PRELIMINARY DATA: STATINS AND LXRA ................................ .............................. 70 A bstracts ................................ ................................ ................................ ..................... 70 B NR1H3 GENE POLYMORPHISMS AND INVEST GENES: SUPPLEMENTARY DATA ................................ ................................ ................................ ................................ 72 Effect of LXRA Genotypes and Primary Outcomes Stratified by Race ........................ 72 C SUPPLEMENTARY DATA AND ABSTRACTS FROM IN VITRO ANALYSES ........... 74 PPARA and LXRA cross talk in HUVECs ................................ ................................ .. 74 The Effects of Fenofibrate on PPARA and LXRA Gene Expression ............................ 74 Abstracts ................................ ................................ ................................ ..................... 76 D A DDITIONAL E XPLORATORY HUVEC M ANUSCRIPT P REPARED FOR SUBMISSION ................................ ................................ ................................ ................... 80 Effe cts of Fenofibrate on the Diseased Endothelium ................................ .................... 80 E E FFECT OF F ENOFIBRATE ON N EUTROPHIL C HEMOKINES IN P EOPLE WITH SUB OPTIMAL L IPOPROTEIN P ROFILES : E XPLORATORY A NALYSIS OF A R ANDOMIZED D OUBLE B LIND P LACEBO C ONTROLLED STUDY : S UPPLEMENTARY F IGURES ................................ ................................ ......................... 88

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7 LIST OF REFERENCES ................................ ................................ ................................ .......... 92 BIOGRAPHICAL SKETCH ................................ ................................ ................................ ... 101

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8 LIST OF TABLES Table page 1 1 Partial list of LXRA gene t argets ................................ ................................ ................... 22 1 2 Coding region SNPs in the NR1H3 gene e ncoding LXRA ................................ ............. 22 1 3 Effects of fibrates on lipid and inflammatory b iomarkers ................................ ............... 22 1 4 Synthetic LXR a gonists ................................ ................................ ................................ 22 2 1 Demographics of INVEST GENES case control data s et ................................ .............. 33 2 2 LXRA gene ( NR1H3 ) polymorphi sm frequencies in INVEST GENES case control d ata Set ................................ ................................ ................................ .......................... 34 2 3 Unadjusted and adjusted odds ratios (ORs) and 95% confidence intervals (CIs) for primary outcomes by genotype ................................ ................................ ...................... 34 2 4 Prim ary and s econdary outcomes by LXRA SNPs ................................ ......................... 35 2 5 LXRA gene ( NR1H3 ) diplotype frequencies in INVEST GENES case control data set ................................ ................................ ................................ ................................ .. 35 4 1 Demographics, chemical and biochemical c haracteristics ................................ ............... 60 4 2 Effect of four weeks of f enofibrate 160mg or placebo on lipoprotein related p arameters ................................ ................................ ................................ ..................... 61 A 1 Primary outcome by LXRA g enotype and race ................................ .............................. 72

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9 LIST OF FIGURES Figure page 1 1 Liver X Receptors and gene e xpressi on ................................ ................................ ......... 19 1 2 LXRA and cholesterol h omeostasis ................................ ................................ ............... 20 1 3 LXRA regulates cholesterol homeostasis and inflammation in immune cells ................. 21 2 1 Odds ratios of polymorphisms for primary outcome within racial groups ....................... 36 2 2 Adjusted odds ratios for primary outcome w ithin treatment strategy .............................. 37 2 3 Adjusted odds ratios for primary outcome within racial groups and treatment strategy ... 38 2 4 Adjusted odds ratios for primary outcome based on common diplotypes ........................ 39 3 1 Effect of fenofibrate on endothelial cell viability ................................ ........................... 47 3 2 Effects of fenofibrate on IL stimulated IL 8 protein production. ............................... 48 3 3 Effect of fenofibrate on IL stimulated ENA 78 protein production. .......................... 49 3 4 Effects of fenofibrate on ENA 78 gene expression ................................ ......................... 50 4 1 Clinical study d esign. ................................ ................................ ................................ .... 62 4 2 IL 8 concentrations observed in subject serum ................................ ............................... 63 4 3 IL 8 concentrations observed in subject leukocyte culture ................................ ............. 63 4 4 ENA 78 co ncentrations observed in subject serum ................................ ........................ 64 4 5 ENA 78 concentrations observed in subject leukocyte culture ................................ ....... 64 A 1 Adjusted odds ratios for secondary outcomes based on genotypes ................................ .. 73 A 2 The effects of fenofibrate on PPARA and LXRA gene expression ................................ 75 A 4 Feno fibrate attenuates IL ................................ ........... 79 A 5a TNF g ene expression ................................ ................................ ................................ 85 A 5b TNF p rotein production ................................ ................................ ............................. 85 A 6a RANTES gene expression ................................ ................................ ............................. 86 A 6b RANTES protein production ................................ ................................ ......................... 86

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10 A 7a GM C SF g ene expression ................................ ................................ .............................. 87 A 7b GM CSF protein production ................................ ................................ .......................... 87 A 8a ENA 78 serum concentrations in subjects that received fenofibrate a s the initial treatment. ................................ ................................ ................................ ...................... 88 A 8b ENA 78 serum concentrations in subjects that received placebo as the initial treatment ................................ ................................ ................................ ....................... 88 A 9 ENA 78 serum concentrations. ................................ ................................ ...................... 89 A 10a Triglyceride concentrations in subjects receiving fenofibrate as treatment 1. .................. 90 A 10b Tri glyceride concentrations in subjects receiving placebo as treatment 1. ....................... 90 A 11 Triglyceride concentrations. ................................ ................................ ........................... 91

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11 Abstract of Dissertation Presented to the Grad uate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy LIVER X RECEPTOR ALPHA (LXRA) GENE POLYMORPHISMS IN CARDIOVASCULAR DISEASE AND FENOFIBRATE RESPONSE By Elvin Tyrone Price December 2009 Chair: Issam Zineh Co chair: Julie Johnson Major: Pharmaceutical Sciences Substantial evidence indicates that abnormal lipoprotein (cholesterol) levels and inflammation are linked to CVD pathogenesis. Liver X receptor nuclear receptor that function s as a lipid sensor in human s and serves as a regulator of lipid homeostasis vascular homeostasis and is a suppressor of inflammation. LXRA is encoded by the NR1H3 gene. We investigate d whether common NR1H3 gene polymorphis ms are associated with adverse (INVEST GENES). Furthermore we explored the cohort to see if NR1H3 polymorphisms contributed to variable risk based on antihyperte nsive treatment strategy. We observed associations with two SNPs in the INVEST GENES cohort. The variant T allele of SNP rs2279238 was associated with excess risk of the primary outcome in this study (T/T carriers Adjusted OR: 2.4, 95% CI: 1.34 4.32,p=0.0 03). The variant G allele carriers for SNP rs11039149 were at reduced risk of having a primary outcome event in this study (A/G carriers OR:0.68, 95% CI:0.49 0.93 and G/G carriers OR:0.46, 95% CI: 0.23 0.94, p=0.011) Furthermore, the rs2279238 SNP appea red to have a significant pharmacogenetic effect for patients treated with the Verapamil strategy. This supports doing further studies to determine if

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12 the results are a true pharmacogenetic interaction or if the beta blocker strategy masked the detrimenta l effects of the allele in the patients of this strategy. Haplotype analyses revealed that the SNPs (rs2279238 and rs11039149) are rarely co inherited and thus the interesting findings appear valid and warrant further study. In independent experiments, we further tested novel in vitro and in vivo pharmacological properties of fenofibrate, a commonly used cholesterol modulating drug and modulator of LXRA activity. The in vitro experiments were conducted using fenofibrate in human umbilical vein endothelial cells (HUVECs) under basal and inflammatory conditions typical of CVD. Fenofibrate significantly lowered basal and IL CXCL 5 and the production of it s protein ENA 78 while having a neutral effect on IL 8 Fenofibrate at concentrat ions of 10 78 production between 80 90% (p<0.001 for all concentrations). Basal CXC L 5 gene expression was reduced 5 fold (p=0.0003) by fenofibrate and IL CXCL 5 expression was reduced 12 fold (p<0.0001). A rand omized double blind placebo controlled clinical study was conducted to test whether the endothelial effects of fenofibrate translated to observable effects during clinical treatment. In eleven patients with sub optimal lipid profiles that were treated wit h 4 weeks of fenofibrate and placebo we did not replicate our ENA 78 findings while observing a neutral effect on IL 8. Overall we have added to the evidence supporting LXRA as a contributor to cardiovascular risk and elucidated novel pharmacological prope rties of fenofibrate. Finally, future research directions are proposed and conclusions are provided.

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13 CHAPTER 1 INTRODUCTION/BACKGRO UND CHAPTER Liver X Receptor: A Central Regulator of Cardiometabolic Homeostasis Cardiovascular disease (CVD) is the lea ding cause of mortality in industrialized countries, accounting for approximately 50% of all deaths 1 Atherosclerotic vascular disease exists in the majority of individuals diagnosed with CVD. Atherosclerosis is a multi factorial pathologic al process where dyslipidemia, hypertension, vascular dysfunction, and inflammation have been implicated as risk factors 2 Risk factors for the development of atherosclerosis often cluster in patients being treated for CVD 3 5 Thus major therapeutic agents for preventing and treati ng CVD are aimed at targets modulating multiple pathological factors (e.g., dyslipidemia, vascular dysfunction, and inflammat ion) in at risk populations including those with sub optimal lipid profiles and/or hypertension The liver X receptors (LXRs) ar e a class of nuclear receptors that have implications in lipid homeostasis, vascular homeostasis, and inflammation 6 9 There are two LXRs, LXRA and LXRB (encoded by the NR1H3 and NR1H2 genes, respectively). While, LXRB is ubiquitously expressed, LXRA predominates in the liver, heart, adipose tissues, adrenal glands, brain, intestines and macrophages 6 8 LXRs function as whole body cholesterol sensors and their natural ligands include cholesterol metabolites, such as oxysterols. LXRs are partnered with retinoid X receptors (RXR) in the nucleus where they are bound to LXR response elements in target genes 8 Upon binding of endogenous (and presumably exogenous) ligands to the LXR/RXR co mplex, LXRs undergo conformational changes that induce the expression of a number of genes that protect cells from excess cholesterol 10 (Figure 1 1 ). LXRA, in particular, is expressed in tissues important in cardiometabolic function. Major LXRA target genes are involved in lipid and vascular homeostasis ( Table 1 1; columns A & B). I n addition, LXRA has

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14 been characterized as a regulator of macrophage inflammatory pathways. Numerous pro inflammatory genes are regulated by LXRA ( Table 1 1; column C) To the extent that LXRA is important in cardiovascular homeostasis and immune regulat ion (both crucial elements of atherosclerotic processes) it stands to reason that LXRA and its encoding gene ( NR1H3 ) may be important in cardiovascular drug responses and CVD initiation or pathogenesis Liver X Receptor Alpha and Cholesterol and Lipid Home ostasis The importance of LXRA in cholesterol homeostasis was established by several groups via m ouse studies 11, 12 LXRA / mice demonstrated impaired expression of hepatic genes central to cholesterol and fatt y acid metabolism while LXRB / mice failed to show this phenotype 11, 12 Many of the genes were discovered to be under direct control by LXRA. Further studies revealed that LXRA regulated genes are involved with cholesterol synthesis and reverse cholesterol transport. The effects of LXRA on genes that regulate reverse cholesterol transport are beneficial to lipid homeostasis (Figure 1 2 ) and have led to the development of tissue specific LXRA agonists by the p har maceutical industry LXRA positively regulates the following genes central to reverse cholesterol transport : CYP7A CETP APOE ABCA1 ABCG1 ABCG5 and ABCG8 Genetic abnormalities in several of these targets result in dyslipidemia and excessive CVD ris k. With LXRA being established as a central mediator of reverse cholesterol transport in the intestines, macrophages, testis and adrenals, tissue specific development of LXRA modulators are being pursued with considerable effort. The reverse cholesterol t ransport pathway has been a target of the pharmaceutical industry because of the potential gains of increasing the levels of circulating HDL levels. Liver X Receptor Alpha and Vascular Homeostasis Dyslipidemia and vascular dysfunction often coexist in p atients with CVD. As ment ioned earlier in this chapter, c holesterol is the central component of lipid homeostasis and is

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15 also required for production of hormones central to vascular homeostasis. LXRA regulates the production of steroid hormones from chol esterol which ultimately contribute to vascular homeostasis. LXRA regulates production of the following: CYP11A1 (cholesterol desmolase) which catalyzes the conversion of cholesterol to pregnenolone, the first and rate limiting step in the synthesis of th e steroid hormones; ( a ldosterone s ynthase) which p referentially catalyzes the conversion of 11 deoxycorticosterone to aldosterone via corticosterone and 18 hydroxycorticosterone; HSD 1 (11 beta hydroxysteroid dehydrogenase 1) which reversibly catalyzes the convers ion of cortisol to the inactive meta bolite cortisone; and HSD3B2 (3 b eta hydroxysteroid dehydrogenase type II) which is a bi directional enzyme that catalyzes conversion of all classes of hormonal steroids 13, 14 Genetic variation in these targets has been linked to adrenal insufficiency, impaired cortisol synthesis, hypertension and obesity 15 Furthermore, LXRA positively regulates r enin production via direct interaction with its promoter 16 Renin is a key mediator of vascular homeostasis via the r enin a ngi otensin a ldosterone s ystem (RAAS) and components of this pathway are proposed mediators of lipid homeostasis and blood pressure With regulation of targets crucial to vascular homeostasis blood pressure and cholesterol metabolism the potential for LXRA t o influence the development of CVD is gaining interest. Furthermore, the influence of LXRA on homeostasis of the aforementioned pathways, justifies performing analyses to investigate the influence of NR1H3 polymorphisms on the risks associated with CVD. Liver X Receptor Alpha and Inflammation Inflammation is known to have a prominent role in the pathogenesis of CVD. Circulating levels of several inflammatory molecules correlate with increased risk of CVD. CRP levels independently predict CVD risk and r ecently statins have been shown to decrease risk associated with increased levels of CRP. It was recently shown that treatment with LXRA agonists

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16 represses IL been shown that inf lammation mediated by IL production of LXRA 17 Furthermore, LXRA is expressed in human immune cells where it represses production of inflammatory mediators and regulates ext ra hepatic reverse cholesterol transport when monocytes become lipid loaded 18 ( Figure 1 3 ). In the immune cells, cholesterol homeostasis can become altered in the presence of excess cytokine production. This process contributes to the presence of harmful fat loaded foam cells. This process has been attenuated when monocytes have been treated with LXRA agonists and drugs known to favorably modulate LXRA 18 (statins and fibrates). Furthermor e, the observations that statins and fibrates favorably modulate LXRA while decreasing lipid loads from foam cells has provided a potential pathway to explore in order to characterize some of their pleiotropic effects. LXRA/NR1H3 as a CVD Susceptibility Ge ne LXRA is encoded by NR1H3 (OMIM 602423) which is approximately 20 kb in size and is located at chromosomal position 11p11.2. The gene region is polymorphic with 70 SNPs identified in the most recent iteration of dbSNP, 6 of which have been identified in the NR1H3 coding region (Table 2). While there have been numerous polymorphisms identified in NR1H3 there is a paucity of functional data to accompany them. In recent epidemiological studies it has been observed that polymorphisms and haplotypes of NR1 H3 are associated with body mass index (BMI), baseline LDL and t otal cholesterol levels, HDL levels, CRP expression, and at risk metabolic phenotypes 19 22 The aforementioned associations with established biomarke rs of cardiovascular homeostasis/risk support the exploration of NR1H3 as a potential cardiovascular disease and therapeutic biomarker. Residual cardiovascular morbidity and mortality risks remain in patients with known coronary disease that are treated fo r established risk factors ( e g ., hypertension, dyslipidemia diabetes etc) and therefore the need to establish additional

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17 predictors of disease and therapeutic response remains. We therefore sought to examine the effects of LXRA gene polymorphisms in th genetic cohort (INVEST GENES) (Chapter 2 ). In INVEST patients were randomized to a beta blocker or calcium channel blocker treatment strategy and followed for the occurrence of a primary outco me of non f atal myocardial infarction ( NFMI ) stroke, or d eath. The treatment strategies were equally efficacious in controlling blood pressure and thus CVD risk associated with the SNPs without confounding by blood pressure control, could be determined. In additio n, there has not been a single drug genotype association study involving NR1H3 in the published literature Therefore we also analyze d the relationship of NR1H3 and risk based on treatment strategy in INVEST. Calcium channel blockers are associated with f ew incidences of metabolic adverse events while b eta blockers have been associated with metabolic disturbances. This may provide pharmacogenetic insight into the role of LXRA in patients treated with either class of drugs. The Effects of Fenofibrate on N eutrophil Chemokines Large clinical trials have reported variable rates of efficacy of fibrates in favorably modulating lipoprotein concentrations associated with CVD 23, 24 However, the ability of this class of drugs to reduce morbidity and mortality associated with CVD rema ins debatable 25 Treatment with fenofibrate (our drug of interest) produces reductions in total cholesterol, LDL, VLDL, triglycerides, and apoB while increasing HDL, apoAI, and apoAII. The lipid modulating effects of fibrates have been at tributed to activation of PPAR (PPARA) In addition to direct effects o n PPAR A fibrates modulate LXRA through a PPAR response element in the promoter of the NR1H3 gene 26, 27 In general, activation of PPAR A induces NR1H3 gene expres sion in hepatocytes and adipocytes 28, 29 There is tremendous

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18 complexity in cross talk between the PPAR and LXRA systems 30 Furthermore, the effects of PPAR agonists on LXRA may be as important to pharmacologic response as PPAR agonism. While fibrate use, on aver age, results in improved lipoprotein profiles and reduction in biomarkers of inflammation there is tremendous heterogeneity in response ( Table 1 3 ). In fact, studies have shown that some individuals experience unchanged or worsening of lipoprotein profil es and biomarkers of inflammation concentrations 31 The mechanisms contributing to this variability are not fully known However, some researchers have decided to explore additional biomarkers to associate with fibrate response. Identifying additional biomarkers of resp onse to fibrates may help to identify subsets of patients most likely to benefit from this class of drugs. As such, we studied the novel anti inflammatory effects of fenofibrate in human endothelial cells and in human subjects with sub optimal lipid profi les ( Chapters 3&4 ). We characterize d the effects of fenofibrate on inflammatory chemokines produced in the endothelial cells using cell culture techniques developed in our laboratory ( Chapters 3& 4 ). We further tested whether these in vitro observations were seen in fenofibrate treated patients. These experiments will ultimately serve as the basis for future clinical studies to elucidate the role of LXRA in cardiovascular drug responses. Significance CVD exacts tremendous clinical, economic, and humanis tic tolls worldwide. To decrease CVD burden, efforts must be made to discover novel prog nostic CVD biomarkers. The LXR s are being explored as potentially druggable targets (Table 4) However, the role of LXRs, particularly LXRA, as a disease gene and its pleiotropic effects have not been fully elucidated. We addressed some of these issues in this dissertation project. Not only did this project support will also serve to expand on the currently limited literature regar ding LXRA and CVD risk.

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19 Fig ure 1 1. Liver X Receptors and gene e xpression LXRs form heterodimers with RXR at Liver X Receptor response elements (LXREs) in regulatory regions of genes where they influence transcription 10

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20 Figure 1 2. LXRA and cholesterol h omeostasis LXRA regulates many genes that are established regulators of cholesterol homeostasis including the following: ABCG5/8, CYP7A1, CETP, ABCG1, APOE, and ABCA1 10

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21 Figure 1 3. LXRA regulates cholesterol homeostasis and inflammation in immune cells LXRA regulates reverse cholesterol transport in the immune system via similar pathways observed in the liver and a drenal glands For example, many of the gene targets recognized in figure 1 2 are also expressed in immune cells and contribute to cholesterol homeostasis in the immune cell 18 Figure used with permission from Debbie Maizels (Artwork D. J. Maizels, Zoobotanica (2002)

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22 Table 1 3. Effects of fibrates on lipid and inflammatory b iomarkers Treatment LDL (%) HDL (%) TG (%) TC (%) CRP (%) Fibrates 1 20 10 20 20 50 4 19 1 2 35 Table 1 4. Synthetic LXR a gonists Synthetic LXR Agonist Status Company T0901317 Pre clinical development Glaxo GW3965 Pre clinical development Glaxo LXR 623 First in man clinical trials Wyeth/Karo Bio Table 1 1. Partial list of LXRA gene t argets A. Lipid Homeost asis B. Vascular Homeostasis C. Inflammation ABCA1 RENIN MCP 1 ABCG1 CYP1 2 CCL3 ABCG5 HSD1 1 CCL7 ABCG8 UCP 1 CXCL10 APOE ANGPTL3 IL APOC1 ARG2 IL6 CETP SCD 1 MMP9 CYP7A1 ENG NOS2A LPL FSCN1 COX 2 Table 1 2. Coding r egion SNPs in the NR1H3 gene e ncoding LXRA Region mRNA Position dbSNP rs# Function Polymorphism Exon 1 30 rs11039155 Synonymous 5' UTR Exon 1 36 Synonymous Start Codon Exon 2 150 rs11545529 Non synonymous Ile39>Val Exon 2 190 rs41481445 Non synonymous Gly52>Val Exon 3 332 rs2279238 Synonymous Ser99>Ser Exon 3 368 rs3497416 Synonymous Asn111>Asn Exon 3 425 rs34806350 Synonymous Ala130>Ala

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23 CHAPTER 2 LIVER X RECEPTOR ALP HA GENE PLOYMORPHISM S AND VARIABLE RISK IN PATIENTS TREATED WIT H ANTIHYPERTENSIVE T HE R APY: RESULTS FROM THE INVEST GENES STUDY Introduction Cardiovascular disease (CVD) is the leading cause of mortality in industrialized co untries, accounting for approximately 50% of all deaths 1 Risk factors for the development of atherosclerosis are attributed to both genetic and environmental causes. Epidemiological studies have consistently id entified decreased HDL cholesterol and increased LDL cholesterol and triglycerides as major contributors to atherogenesis. Furthermore, over the past decade it has been shown that inflammation plays a prominent role in CVD and its complications 2, 32 Even with aggressive cardiovascular strategies for treatment substantial risks still re main. P athways central to lipids and inflammation must be explored to understand what contributes to the remaining risk for CVD. The l iver X receptors (LXRs) are a class of nuclear receptors that regulate pathways central to lipid homeostasis, glucose homeostasis, inflammation and immunity 6 9 The two LXRs, LXRA and LXRB are encod ed by t he NR1H3 and NR1H2 genes, respectively While, LXRB has ubiquitous tissue expression, LXRA predominates in the liver, heart, adrenal glands, adipose tissues, intestines and macrophages 6 8 LXRs function as whole body cholesterol sensors and their natural ligands include cholesterol metabolites, such as oxysterols. LXRs are partnered with retinoid X receptors (RXR) in the nucleus where they are bound to LXR response elements in target genes 8 Upon binding of endogenous (and presumably exogenous) ligands to the LXR/RXR complex, LXRs undergo conformational changes that induce the expression of a number of genes that protect cells from excess cholesterol 23

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24 It has been observed i n recent epidemiological studies that polymorph isms and haplotypes of NR1H3 are associated with body mass index (BMI), baseline cholesterol levels, CRP expression and at risk metabolic phenotypes 19 21, 33 It is plausible that NR1H3 genetic variability may c ontribute to CVD morbidity and mortality in patients with known coronary disease that are otherwise treated for the risk factors, (e g hypertension dyslipidemia diabetes etc). W e therefore sought to examine the association of NR1H3 gene polymorphisms w ith adverse cardiovascular outcomes in the genetic cohort of the International Verapamil SR Trandolapril Study ( INVEST GENES ) In INVEST patients were randomized to a beta blocker or calcium channel blocker treatment strategy and followed for the occurr ence of a primary outcome of non fatal myocardial infarction stroke or d eath. The treatment strategies were equally efficacious in controlling blood pressure and thus CVD risk associated with NR1H3 gene variants in the absence of confounding by blood pre ssure response could be determined. Furthermore, the treatment strategies work via distinct pathways so we decided to also analyze the relationship of NR1H3 and risk based on treatment strategy in INVEST. Calcium channel blockers are associated with few incidences of metabolic adverse events while b eta blockers have been associated with metabolic disturbances. This pharmacogenetic analysis may provide insight into the role of NR1H3 in patients treated with either class of drugs. Therefore, the INVEST GE NES cohort served a role in providing genetic and pharmacogenetic insight into NR1H3 Methods Study Participants The INVEST was a prospective, randomized, open label, blinded endpoint trial of beta blocker versus calcium channel blocker based antihyperten sive therapy in 22,576 patients with hypertension and documented coronary artery disease (CAD) 34 Patients were eligible if they

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25 were over 50 years of age, were diagnosed with hypertension, and had documented CAD as defined by the following: stable angina, remote history of myocardial infarction (MI) (>3 months), abnormal stress test, or >50% stenosis on coronary angiography. Patients were randomly assigned to treatment with atenolol or verapamil SR. Hydrochloroth iazide and/or trandolopril were added as needed to achieve JNC VI blood pressure targets. The primary outcome was a composite of all cause mortality, nonfatal MI, and nonfatal stroke. The treatments strategies were equivalent in terms of the extent of bl ood pressure control at 24 months and the incidence of the primary outcome 34 The INVEST GENES Case Control Population Consent for genetic studies was obtained and DNA samples were collected for 5 979 patients pa rticipating in the INVEST in the United States and Puerto Rico. Within this cohort, 2 97 patients experienced a primary outcome event after a mean (SD) of 2.8 (0.7) years of follow up. All events constituting the primary outcome were adjudicated by an end point committee blinded to treatment strategy. Controls were randomly selected from p atients not experiencing a primary outcome event during the follow up period were selected at a ratio of approximately 2.5 controls per case (n=7 62 ). Controls were frequ ency matched to cases by age, sex, race/ethnicity. DNA Collection and Genotyping Buccal tissue samples were obtained by mouthwash and genomic DNA was isolated as previously described 35 We selected the following seven polymorphisms in the LXRA gene region (NR1H3) using a t ag SNP approach (Haploview software): rs11039149, rs12221497, rs2279238, rs7120118, rs326213, rs11039159 and rs10501321. The minor allele freque ncy was set at 10% and r 2 was set at 80% for SNP selection. Genotyping was performed using Taqman (Applied Biosystems, 7900, Foster City, CA). Genotype accuracy was verified by blind duplicate re genotyping of 5% of the samples and concordance was 100%

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26 Statistics Hardy Weinberg equilibrium was tested within 2 analysis. Linkage disequilibrium (LD; r 2 ) between the SNPs in each racial/ethnic group was estimated using Haploview. Demographic and baseline clinical characteris tics were compared by genotype 2 tests for categorical data, and analysis of variance or a nonparametric equivalent for continuous data. Logistic regression was performed to estimate odds ratios (OR) and 95% confidence intervals (95%CI) for each co py of the variant allele relative to wild type homozyogtes. Associations with the primary and secondary outcomes were tested using stepwise logistic regression models. The models adjusted for age, sex, race/ethnicity, were selected using the stepwise pr ocedure (P<0.1 for entry, P<0.05 for retention) with the following covariates that were previously found significant considered for potential inclusion in the model : history of heart failure, previous MI, diabetes, stroke or transient ischemic attack, rena l insufficiency, dyslipidemia, left ventricular hypertrophy, peripheral vascular disease, stable angina, unstable angina, arrhythmia, cancer, ever smoking, body mass index, and baseline systolic and diastolic blood pressures. The threshold for significanc e was set at P<0.05 for testing in the overall population Previous studies have found four of the seven selected SNPs (rs12221497, rs2279238, rs7120118, and rs11039149) to be associated with conditions where the sequelae is CVD morbidity and mortality 19 21 Therefore, the P<0.05 was considered appropriate for replication of previous findings. We selected an adjusted p value of 0.007 as significance for the remaining SNPs that would produce novel findings (p=0.05 /7). Stratified logistic regression was used to estimate g enotype risks in each treatment stratum. Furthermore, analyses were performed using racial stratification and ancestral informative markers (AIMs) to control for the variability in inheritance pre dicted in the subpopulations of INVEST GENES subjects. All statistical analyses were performed using SPSS 11.0 ( SPSS, Chicago, IL ).

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27 R esults The baseline characteristics for the INVEST GENES case control group are listed in table 2 1. 36 Successful genotyping for all loci was achieved in over 90% of the individuals in the data set and allele frequencies are listed in table 2 2 Associations of LXRA Genotypes and Primary/Secondary Outcomes The data for the effects of the seven SNPs selected on primary outcomes are represented in table 3. Two of the seven SNPs (rs2279238 and rs11039149) were associated with significant effects on risk for the primary outcome. A SNP association occurred with exon 5 SNP rs2279238, wh ich was significantly associated with the odds of a primary outcome event (p=0.01 2 ). Patients carrying two variant alleles (T/T) had more than a 2 fold excess risk compared with those carrying two wild type alleles (C/C) ( Adjusted OR : 2.4, 95% CI: 1.34 4.3 2, p=0.00 3). Patients carrying only one variant allele (C/T) showed intermediate risk compared with the reference group ( Adjusted OR : 1. 2, 95% CI: 0.87 1.65 ) suggesting additive risk for each T allele a patient carried A second significant association w as identified for promoter SNP rs11039149, in which the variant G allele was associated with decreased risk of having the primary outcome event (p=0.011, Table 3). Specifically, compared with A/A patients the adjusted ORs for A/G and G/G were 0.68 (CI: 0. 49 0.93) and 0.46 (CI: 0.23 0.94), respectively. After the initial analysis, the seven SNPs selected were analyzed for the primary outcomes in the cohort grouped by race. The data for the five SNPs not associated with primary outcomes remained unchanged when the cohort was analyzed separately by race and genotype. The SNPs that were significant from the combined analysis of primary outcomes (rs2279238 and rs11039149) were associated with similar trends when the cohort was analyzed by racial groups (Figur e 2 1). As shown in figure 2 1, the observed effects of both SNPs were strongest in whites

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28 (the group with the most power), consistent though not significant in Hispanics and not observed in Blacks. Therefore, Blacks were not included in subsequent analy ses of secondary outcomes. In analysis of secondary outcomes, The T/T genotype of rs2279238 was associated with an increased risk of death (OR: 3.1, CI: 1.46 6.50, p=0.0071). However, there were no statistically significant associations with stroke or MI, although the point estimates of stroke and MI were consistent with that of death (Table 2 4). The G allele of SNP rs11039149 was associated with a reduction in risk for death (A/G carriers Adjusted OR: 0.64, CI: 0.46 0.89 and G/G carriers Adjusted OR: 0.4 7, CI: 0.23 0.92, p=0.0062) and there was also an association with occurrence of non fatal stroke (A/G carriers OR: 0.55, CI: 0.31 0.97 and G/G carriers OR: 0.31, CI: 0.07 1.33, p=0.048). Pharmacogenetic Associations with LXRA G enotypes The variant T allel e for rs2279238 was associated with variable risk of outcome based upon treatment strategy (verapamil SR vs atenolol) (Figure 2 2) In the verapamil SR treatment strategy patients, the presence of the T allele was associated with increased risk for a prim ary event (C/T vs. C/C OR : 1. 95, CI: 1.24 3.01, p=0.0 05 and T/T vs. C/C OR : 3.79 CI: 1.32 10.85, p=0.0 13 ) in a manner consistent with the that observed for the overall sample, but there was no increased risk associated with genotype in the atenolol strate gy (Figure 2 2). The observed effects in the verapamil strategy were confirmed in the white subgroup which represented the largest racial subgroup ( C/T vs. C/C OR: 2.61, CI: 1.48 4.59, p=0.00089 and T/T vs. C/C OR: 9.74, CI: 2.36 40.21, p=0.0017 See Figu re 2 3 ) A statistical significant gene*treatment strategy interaction was present for the rs2279238 polymorphism (p=0.019). There were no differences in genotype associations by treatment strategy for rs11039149 overall (Figure 2 3).

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29 LXRA Diplotypes and P rimary O utcomes by T reatment S trategy Phase software was used to form diplotypes for SNPs rs11039149 (A>G) and rs2279238 (C>T) for risk of primary outcome and pharmacogen e tic predictions The frequencies of the diplotypes are listed in table 5. There wer e six diplotypes (D) with frequencies above five percent. D1, which contained the wild type allele for both SNPs was selected as the reference for the logistic regression analyses. D3 and D9 were associated with a reduced risk of the primary outcome (fig ure 4). D5 was associated with an increased risk of the primary outcome (figure 4). Similar trends were observed when the diplotypes were analyzed in the population stratified by race and treatment strategy (data not shown). D iscussion In this study we demonstrated variable CVD outcomes based on LXRA genotypes. We observed a protective association with the variant allele of rs11039149 Specifically, individuals with one or two copies of the protective G variant demonstrated lower rates of the INVEST co mposite endpoint, as well as decreased risk of non fatal stroke and death. Recent studies lend mechanistic evidence to this finding in the treatment of experimental stroke with LXRA agonists in animal models 37, 38 Saez et al ., reported neuroprotection associated with the use of an experimental LXRA agonist in a rat model of acute brain ischemia 38 Further support from animal models came when Chen et al ., reported that treatment of experimental stroke in mice with the LXRA agonist TO90317 resulted in improved outcomes. The treatment with the LXRA agonist resulted in improved vascular maturation, increased angiogenesis, increased levels of HDL and increased eNOS phosphorylation in the ischemic portions of the brain 37 With the s e data supporting a potential role for LXRA agonists in improving the function of the vasculature of the brain, it may be plausible that gain of function alleles in NR1H3 may contribute similar protective effects. However, i n silico analyses fail to suggest putative functionality for

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30 rs11039149 (data not shown) and therefore further studies should be performed to identify potential functionality of this SNP. Rs2279238 variants were associated with increased risk of the primary outcome. Secondary analyses revealed a trend towards increased risk with the presence of each variant allele for each secondary outcome. This effect was predominantly driven by risk of death from any cause I n silico analyses suggest that rs2279238 is l ocated at an exon splicing enhancer (ESE) of NR1H3 where splicing factor SRp55 binds. Several splice variants of NR1H3 have been identified but their contributions to normal physiology or disease pathogenesis has not been fully explored. Further functiona l studies and analyses of linkage disequilibrium may add clarity to function of rs2279238 in normal physiology and pathogenesis of cardiovascular disease. Subgroup analysis revealed similar trends of risk based on race There were considerably more whites in the study than Hispanics or Blacks and thus some trends may have been significant if there were more patients in each group. Ancestral informative markers (AIMs) were selected to help delineate Native American, European and African ancestry for patien ts in the INVEST GENES study. AIMs were used to control for population stratification to reduce the possibility of spurious associations. AIMs were used to adjust ORs for each of the ancestries but had minimal effects on the results observed. Diplotype a nalyses did not provide further insights regarding risks not evident from the single SNP analyses. However the analysis did reveal that the variant alleles of rs2279238 and rs11039149 are rarely co inherited jointly. This provides support for the opposit e findings observed in the single SNP analyses. The pharmacogenetic association observed with rs2279238 genotype and significant risk of outcomes in the verapamil treatment strategy have plausible support by recent discoveries of LXRA function in vascula r homeostasis. LXRA regulates several enzymes and proteins

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31 involved with vascular homeostasis 13, 14, 39, 40 For example, LXRA has been discovered to regulate production of renin via control of a response element in the promoter of the renin gene 41 Furthermore, recent explorations of LXRA regulation of adrenal gland homeostasis has resulted in the support of LXRA for regulating steroidogenesis and aldosterone synthesis 13, 14, 39, 40 If this pathway is altered it could ultimately lead to hyperaldosteronism (from the adrenal cortex) and increased catecholamine production (from the adrenal medulla), both of which are associated w ith morbidity and mortality associated with CVD 15, 40, 42 The atenolol treatment strategy may have favorably modulated these pathways and resulted in a decrease in the risk associated with LXRA variants. The afor ementioned pathways could both be favorably modulated by beta blockade 40, 43 46 For example, it has been well established that corticosteroids increase expression of adrenergic receptors in the vascular wall and potentiates the action of catecholamines on them 43, 44, 46 Beta blockade could theoretically benefit the variant carriers of rs2279238 if this SNP is associated with excess corticosteroids or catecholamines from the adrenal gland. Contrarily, Beta blockade has been associated with metabolic disturbances and excessive cardiovascular risk including death in hypertensive patients 47, 48 and thus beta blockade may have masked t he risk associated with rs2279238 in patients treated with the atenolol strategy. Furthermore, it has been reported that even though calcium channel blockers are not associated with many reported metabolic disturbances they can cause a paradoxical increas e in production of catecholamines 49 Theoretically, this could potentiate pathological processes that could exist if LXRA dysfunction was present. Finally, c orticosteroids have been proven to regulate production of the cytochrome P450 3A (CYP3A) subfamily 50, 51 Cortisol is a substrate of CYP3A4 while corticosterone is an inducer of CYP3A4. LXRA regulates production of the bidirectional enzyme responsible for the conversion of cortisol to corticosterone. Verapamil is a

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32 substrate for CYP3A4 and the excess of either endogenous corticosteroid could theoretically have pharmacokinetic interactions with this therapy. Furthe r investigation will help to clarify the results of these findings. Future studies designed with novel biomarkers will be able to provide more insight. In this study we demonstrated variable CVD outcomes based on NR1H3 genotypes. We observed a protective a ssociation with the variant allele of rs11039149 and increased risk of adverse cardiovascular outcomes with the variant allele of rs2279238 Furthermore, we observed a potential pharmacogenetic interaction between the rs2279238 variant allele and treatmen t strategy. To our knowledge this was the first evaluation of NR1H3 polymorphisms and drug response. Collectively, these findings support the exploration of transcription factors involved in cardiovascular homeostasis as potential contributors to develop ment of CVD and response to drugs used to treat CVD. Specifically, this study provides support for further studies to confirm NR1H3 gene variants as involved in cardiovascular homeostasis, cardiovascular disease pathogenesis and pharmacological response.

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33 Table 2 1. Demographics of INVEST GENES case control data s et Characteristic (N, % unless otherwise noted) Cases (N=297) Controls (N=762) Age, mean (SD), years 71.4 (9.8) 70.2 (9.3) Women 148 (49.8) 387 (50.8) BP, mean (SD), mm HG Systolic 150.6 ( 18.7) 147.4 (18.9) Diastolic 83.3 (11) 83.4 (11.1) Race/ethnicity White 185 (62.3) 462 (60.6) Hispanic 70 (23.6) 197 (25.9) Black 41 (13.8) 100 (13.1) Other/multiracial 1 (0.3) 3 (0.4) BMI, mean (SD), kg/m2 27.5 (4.8) 28.9 (5.5) Medical history Pr ior myocardial infarction 107 (36) 225 (29.5) Stable angina 181 (60.9) 476 (62.5) Prior stroke/TIA 44 (14.8) 67 (8.8) Left Ventricular Hypertrophy 56 (18.9) 132 (17.3) Heart failure (class I III) 31 (10.4) 27 (3.5) Peripheral vascular disease 50 (16.8 ) 86 (11.3) Smoking Ever 154 (51.9) 349 (45.8) Diabetes 90 (30.3) 170 (22.3) Hypercholesterolemia 184 (62) 475 (62.3) Renal Impairment 15 (5.1) 17 (2.2) Cancer 25 (8.4) 44 (5.8)

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34 Table 2 2 LXRA gene ( NR1H3 ) polymorphism frequencies in INVEST GE NES case control data s et Polymorphism Position Genotype Success Rate Minor Allele Frequency Whites Hispanics Blacks rs11039149 (A>G) 97% 0.23 0.18 0.20 0.06 rs12221497 (G>A) Intron 2/Promoter 94% 0.11 0.13 0.07 0.07 rs2279238 (C>T) Exon 5 97% 0 .22 0.15 0.26 0.42 rs7120118 (C>T) Intron 7 90% 0.33 0.18 0.35 0.52 rs326213 (C>A) Intron 7 93% 0.01 0.01 0.02 0.05 rs11039159 (G>T) 91% 0.33 0.39 0.23 0.13 rs10501321 (G>T) 92% 0.36 0.30 0.37 0.59 Table 2 3. Unadjusted and adjus ted odds ratios (ORs) and 95% confidence intervals (CIs) for primary outcomes by genotype Unadjusted OR (95% CI) Adjusted OR (95% CI) rs11039149 (A/G vs. A/A) 0.71 (0.525 0.95) 0.68 (0.49 0.93) rs11039149 (G/G vs. A/A) 0.48 (0.25 0.94) 0.47 (0.23 0.9 4) rs12221497 (G/A vs. G/G) 0.71 (0.48 1.03) 0.68 (0.46 1.02) rs12221497 (A/A vs. G/G) 2.74 (0.17 44.13) 1.27 (0.07 21.47) rs2279238 (C/T vs. C/C) 1.11 (0.83 1.5) 1.2 (0.87 1.65) rs2279238 (T/T vs. C/C) 2.22 (1.30 3.77) 2.4 (1.34 4.32) rs7120118 (C/T vs. C/C) 1.12 (0.82 1.53) 1.16 (0.84 1.61) rs7120118 (T/T vs. C/C) 1.18 (0.73 1.91) 1.14 (0.68 1.91) rs326213 (C/A vs. C/C) 1.02 (0.37 2.87) 1.2 (0.41 3.58) rs11039159 (G/T vs. G/G) 0.87 (0.64 1.19) 0.82 (0.59 1.14) rs110391 59 (T/T vs. G/G) 0.85 (0.54 1.35) 0.81 (0.49 1.31) rs10501321 (G/T vs. G/G) 1.16 (0.85 1.58) 1.19 (0.86 1.65) rs10501321 (T/T vs. G/G) 1.21 (0.77 1.92) 1.17 (0.70 1.94) Odds Ratios (OR) from logistic regression adjusted for: age, sex, race/ethnicity BMI,INVEST treatment strategy, history of CHF, history of MI and history of diabetes at baseline

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35 Table 2 4 Primary and s econdary outcomes by LXRA SNPs rs11039149 rs2279238 Primary Outcome Event 0.011 A/G (0.676, 0.49 0.93) G/G (0.46, 0.23 0.94) 0.0 12 C/T (1.20, 0.88 1.65) T/T (2.40, 1.34 4.32) Secondary Outcomes Death 0.0062 A/G (0.64, 0.46 0.89) G/G (0.47, 0.23 0.92) 0.0071 C/T (1.31, 0.93 1.84) T/T (3.1, 1.46 6.50) Non Fatal Stroke 0.048 A/G (0.55, 0.31 0.97) G/G (0.31, 0.07 1.33) 0.13 C/T (1 .62, 0.94 2.79) T/T (2.12, 0.69 6.48) Non Fatal MI 0.36 A/G (0.66, 0.37 1.17) G/G (0.95, 0.38 2.42) 0.59 C/T (1.33, 0.76 2.33) T/T (1.26, 0.35 4.51) p values and odds ratios (OR) with 95% CI from logistic regression adjusted for: age, sex, race/ethnicit y, BMI,INVEST treatment strategy, history of CHF, history of MI and history of diabetes at baseline Table 2 5 LXRA gene ( NR1H3 ) diplotype frequencies in INVEST GENES case control data set Diplotype rs11039149 (A>G) & rs2279238 (C>T) Diplotype frequency N (%) D 1 AC/AC 335 ( 31.6 ) D 2 AC/AT 241 ( 22. 8) D 3 AC/GC 262 ( 24.7 ) D 4 AT/AC 6 ( 0.5 7) D 5 AT/AT 61 ( 5. 8) D 6 AT/GC 86 ( 8.1 ) D 7 AT/GT 1 ( 0.09 ) D8 GC/AC 5 ( 0.47 ) D9 GC/GC 62 ( 5. 9)

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36 Figure 2 1. Odds ratios of polymorphisms for primary outcome within racial groups

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37 Figure 2 2. Adjusted odds ratios for primary outcome within treatment strategy

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38 Figure 2 3 Adjusted odds ra tios fo r primary outcome withi n racial groups and treatment strategy

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39 Figure 2 4 Adjusted odds ratios for primary outcome based on common diplotypes

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40 CHAPTER 3 EFFECT OF FENOFIBRAT E ON ENDOTHELIAL PRO DUCTION OF NEUTROPHIL CHEMOKINES IL 8 AND ENA 78 Introduction The PPAR agonists, or fibrates, are a class of lipoprotein modulating drugs commonly used in the treatment of dyslipidemia. 52 By virtue of their ability to increase peripheral lipolysis and decrease hepatic triglyceride production, the fibrates are among the best agents for lowering triglycerides and increasing high density lipoprotein cholesterol (HDL C) in patients with mixe d dyslipidemias. In addition, intervention trials have shown fibrates to slow atherosclerotic progression and improve cardiovascular outcomes in some patient subsets 53 58 It has been hypothesized that the protective effects of fibrates in select populations are partly due to anti inflammatory effects. In fact, fibrates ha ve been shown to blunt inflammatory processes in monocytes and macrophages, T lymphocytes, endothelial cells, vascular smooth muscle cells, and adipocytes, largely through down regulation of cascades involving inflammatory cytokines. 59 While the majority of studies have investigated modulatory roles of fibrates on adhesion molecules and monocytic chemokines, there is a paucity of data regarding the effect of fibrates on neutrophil chemokines su ch as interleukin (IL) 8 and epithelial neutrophil activating protein (ENA 78). These cytokines are important in the recruitment of neutrophils to sites of endothelial injury and propagating the effects of neutrophil activation. To the extent that neutro phils are among the most important leukocyte subtype s in cardiovascular disease risk IL 8 and ENA 78 represent potentially important mediators of cardiovascular disease risk. 60 In fact, IL 8 has been implicated in cardiovascular disease pathogenesis, and ENA 78 has been implicated in ischemic stroke and other cardio vascular related conditions. 61 65 Furthermore, IL 8 and ENA 78 may be important targets for cardiovascular drug therapy. W e have shown the HMG CoA reductase inhibitor atorvastatin to lower basal endothelial production

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41 of both IL 8 and ENA 78 as well as lower production of endothelial ENA 78 in a model of cardiovascular inflammation 66, 67 However, data for fibrate effects on cellular production of IL 8 are scarce and conflicting 68 70 whil e data on ENA 78 are non existent. As such, we investigated the influence of fenofibrate on IL 8 and ENA 78 from human endothelial cells. Materials and Methods Cell Culture Experiments Our human umbilical vein endothelial cell (HUVEC) cultur e methods ha ve been previously described 66, 67 In brief, HUVECs ( Lonza ; Walkersville Inc, Walkersville, MD, USA ) at pass two were seeded at a density of 2.5 x 10 4 cells/cm 2 and cultured to 80% confluence in growth media ( EGM 2, Lonza ) at physiological temperature and 5% CO 2 Serum free media ( EBM 2, Lonza ) was used 24 hours prior to treatment and EBM 2 supplemented to a final 2% fetal bovine serum concentration was used for treatment conditions. Cell viability was assessed by trypan blue staining for HUVECs treated with fenofibrate 1 200 M All working solutions of fenofibrate were dissolved in dimethyl sulfoxide. Concentrations of fenofibrate that reduced nated from subsequent studies. We tested the concentration dependent effects of fenofibrate on IL stimulated production of IL 8 and ENA 78 proteins. IL 8 and ENA 78 are highly inducible by this cytokine 66 and IL in cardiovascular disease pathophysiology. Treatment groups included control (untreated), IL 2 ng/mL alone, fenofibrate 1 50 M, and fenofibrate plus IL Fenofibrate and IL obtained from Sigma Aldrich ( St. Louis, MO) Each experiment was performed six times. To test the effects of fenofibrate on inflammatory gene expression, experimental groups included unstimulated control, IL 10 M), and fenofibrate plus IL

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42 We selected the lowest fenofibrate concentration associated with significant findings in the concentration ranging studies (10 M) to serve as the treatment concentration in the gene expression studies Each experiment was performed four times. Protein Quantification and Gene Expression IL 8 and ENA 78 protein concentrations were measured in duplicate by multiplex immunofluorescence detection as previously described (R&D Systems, Minneapolis, USA for the Luminex 100Is Luminex Corporation, Austin, USA) and normalized to total protein content as previously described. 67 The assay had a range of detection of 3600 pg/ml to 4.9 pg/ml of IL 8 and a range of detection of 6000 pg/ml to 8pg/ml for ENA 78. If fenofibrate induced changes in protein concentrations, gene expression studies were performed. Ribonucleic acid (RNA) was isolated usin g a commercially available kit (RNeasy mini kit, Qiagen Inc., Valencia, USA). Complementary deoxyribonucleic acid (cDNA) conversion was performed by high capacity cDNA reverse transcription per protocol using 500ng of total RNA (Applied Biosystems, Foster City, USA). RNA and cDNA quality were assessed by absorbance and polymerase chain reaction (PCR) respectively. Real time PCR (RT PCR) was performed using primer and probe sets for the ENA 78 gene ( CXCL5 ) as well as the housekeeping gene glyceraldehyde 3 phosphate dehydrogenase (GAPDH; Taqman Gene Expression Assays, Applied Biosystems Inc.). IL8 gene expression was not studied as fenofibrate did not modulate IL 8 protein concentrations (see Results). Statistical Analysis IL 8 and ENA 78 protein conce ntrations were compared by one way ANOVA with CXCL5 gene expression was reported using the 2 Ct test. Statistical analyses were performed using SPPS version 11.0 (SPSS Inc., Chicago, USA).

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43 Results Fenofibrate Effects on Endothelial IL 8 and ENA 78 Production HUVEC viability w as not significantly different for any tested fenofibrate concentration relative to control (Figure 3 1); however, cell viability was less than 80% of control at concentration s were excluded from further experiments. As expected, endothelial production of both IL 8 and ENA 78 was highly induced by the pro inflammatory cytokine IL Figures 3 2 and 3 3, respectively ). Specifically, IL 8 concentrations by over 5 fold (meanSEM: 6145860 pg/mg vs. 1160201 pg/mg; p=0.0003). ENA 78 concentrations increased by more than 160 fold over constitutively produced ENA 78 upon IL (10,1291591 pg/mg vs. 61.69.5 pg/mg; p<0.0001). Fenofibrate had no signif icant effect on IL stimulated IL 8 production at the concentrations tested ( Figure 3 2 ). In contrast, fenofibrate significantly reduced ENA 78 production ( Figure 3 3 stimulated endo thelial ENA 78 production by 81% (p=0.001), 82% (p=0.001), and 90% (p<0.0004), respectively. There was no reduction of ENA concentration. Fenofibrate Effects ENA 78 mRNA Production After exhibiting ENA 78 protein lowering eff ects, we tested whether fenofibrate lowered basal or stimulated CXCL5 mRNA expression. Fenofibrate decreased basal and stimulated CXCL5 expression (Figure 3 4). Specifically, fenofibrate reduced basal relative CXCL5 expression 5 fold compared with untreat ed control (p=0.0003). Further, fenofibrate

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44 reduced IL stimulated CXCL5 production 12 fold compared to the IL alone (p<0.0001). Discussion Fibrates are commonly used to treat mixed dyslipidemias because of their ability to favora bly modulate HDL cholesterol and triglycerides. In addition, evidence of fibrate anti inflammatory effects continues to emerge 71 76 While fibrates affect myriad inflammatory molecules, their effects on the neutr ophil chemokine IL 8 have been inconsistent, while their effect on ENA 78 is unknown In the current experimental model of endothelial inflammation, we examined the effects of fenofibrate o n IL stimulated production of IL 8 and ENA 78 at physiologic drug concentrations. 77 In the current study we observed no significant effects of fenofibrate on IL 8 IL 8 was highly induced by IL ect was not abolished by fenofibrate. Previous reports of fibrate effects on IL 8 have been conflicting. For example, Lee et al ., reported that the synthetic PPAR 8 production in human aortic endothelial cells. Treatment of t he cells with Wy14,643 resulted in increased production of mRNA and protein of IL 8. To add support for their findings, they repeated the experiments in aortic endothelial cells from PPAR 8, adding m echanistic support to the ability of this specific PPAR 8 68 However, Ryoo et al ., reported induced IL 8 production in human aortic smooth mu scle cells 69 This group reported decreased IL 8 mRNA and protein production and examined potential mechanistic pathways responsible for the observations. The investigators assessed the effects of fenofibrate on the transcriptional activities of AP 1 and NF transcriptional factors known to influence IL 8 expression. There were no observed effects on

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45 NF induced luciferase activity of AP 1 69 Finally, Shu et al reported that fenofibrate had no effect on LPS stimulated IL 8 production while lowering matrix metalloproteinase 9 (MMP 9) in THP 1 cells 70 Paradoxical small increases in IL 8 were reported while reductions in MMP 9 were observed 70 While we showed no effect of fenofibrate on endothelial production of IL 8, it appears as though PPAR 8 production, if they exist, are conditional on the tissue and experimental conditions tested. In previous data from our group it was shown that atorvastatin 1 8 by 26 89 % in a mevalonate dependant fashion. 67 While we have not directly tested the relative effects of fenofibrate and atorvastatin on IL 8 in identical conditions, differences in their ability to modulate IL 8 may be important and should be tested in future experiments. In contrast to the lack of effect on IL 8, fenofibrate blocked the ability of IL ENA 78 production from endothelial cells. Specifically, fenofibrate reduced ENA 78 production by 81 90% at concentrations ranging from 10 response relationship is consistent with other in vitro fenofibrate studies which showed similar results in separate cell lines 78, 79 These data are generally consistent with our previou s data on atorvastatin in which IL induced ENA 78 production was reduced by 38 99% 66 Interestingly, the statin effect was dose dependent while the fenofibrate effect was not. In addition to the effect s on pro tein levels fenofibrate lowered basal and IL induced CXCL5 expression. The effect of fenofibrate on basal CXCL5 is consistent with our previously observed effect of atorvastatin. However, unlike with fenofibrate, atorvastatin had no significant effect on IL stimulated expression of CXCL5, perhaps owing to the known dependence of IL mevalonate metabolites. 66

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46 The reason for disparate effects of fenofibrate on IL 8 and ENA 78 pr oduction is unknown. Previous reports have shown that, while IL 8 and ENA 78 share some homology, the promoter regions of the IL8 and CXCL5 genes are not identical and are regulated by different transcription factors 80 Specifically, ENA 78 production is driven by a non selective NF response element in CXCL5 promoter region, which allows for a number of combinations of the NF 8 production is induced by homodimers of a few select NF NF 2 or C Rel homodimers) and a C/EBP response element 80 Fenofibrate has been shown to have variable effects on gene expression of different members of the NF 81 The differences in gene regulation may lend mechanistic support to the results that we are currently reporting. In conclusion, we have observed a novel anti inflammatory effect of fenofibrate. In an endothelial model of cardiovascular inflammation, f enofibrate lowered the production and gene expression of the potent neutrophilic chemokine ENA 78, with no effect on IL 8. The clinical 78 should be tested in patien ts with diseases that have a significant neutrophilic component or in which ENA 78 levels have been elevated.

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47 Figure 3 1. Effect of fenofibrate on endothelial cell viability

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48 Figure 3 2. Effects of fenofibrate on IL stimulated IL 8 protein production IL 8 (p<0.0005, denoted by *). Fenofibrate at increasing concentrations does not significantly lower the production of IL 8 (Levels remained significantly elevated comp ared to control).

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49 Figure 3 3. Effect of fenofibrate on IL stimulated ENA 78 protein production IL 78 (p<0.0001). Fenofibrate 10 significantly decreased IL induced productio n of ENA 78 (p<0.001, denoted by *).

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50 Figure 3 4. Effects of fenofibrate on ENA 78 gene expression expression over basal levels (p<0.0001). Significance compared to basal expression is denoted by and significance vs IL indicated by +.

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51 CHAPTER 4 EFFECT OF FENOFIBRAT E ON NEUTROPHIL CHEM OKINES IN PEOPLE WITH SUB OPTIMAL LIPOPROTEIN PROFILES: EXPLORATOR Y ANALYSIS OF A RAND OMIZED, DOUBLE BLIND, PLACEBO CONTROLLED STUDY Introduction Cardiovascular disease (CVD) is responsible for over 17 million deaths per year globally. This represents approximately 30% o f deaths world wide 1 The major etiol ogy of CVD morbidity and mortal ity is atherosclerotic coronary heart disease (CHD) 32 Epidemiological studies have consistently identified decreased HDL cholesterol and increased LDL cholesterol and triglycerides as major contributors to atherogenesis. Furthermore, over the past decade it has been shown that inflammation plays a prominent role in CVD and its complications 2, 32, 82 The inflammatory pathways associated with CVD are potentiated by the production of cytokines which continue to rec ruit inflammatory cells to areas of tissue damage 61, 83 85 In addition to monocyte involvement in CVD pathogenesis, neutrophils are recruited by chemotactic cytokines, such as epithelial neutrophil activating pep tide 78 (ENA 78) and interleukin 8 (IL 8), to areas of vascular damage where they are hypothesized to contribute to the pathogenesis of CVD. This hypothesis is supported by the fact that neutrophil counts have shown to have prognostic value in CVD 60, 86 Specifically, Horne et al ., reported that neutrophil:lymphocyte ratio provides the greatest risk prediction of CV risk of the subtypes of white blood cells in patients undergoing cardiac catheterization 60 Neutrophil count also adds prognostic i nformation to major cardiac events in patients with the acute coronary syndrome (ACS) 86 In addition to recruiting neutrophils to areas of vascular insult, ENA 78 and IL 8 promote their adherence to the endothelium and also activate them to release enzymes that can cause tissue injury 61 87, 88 In recent reports by our group and others it has been shown that ENA

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52 78 gene variants and protein concentrations are associated with prognosis after acute coronary syndromes, heart failure severity, risk of diabetes and severity of ischemic str oke 61, 63, 66, 89, 90 Evidence supports a role for IL 8 in various stages of CVD. For instance, IL 8 has been identified in sites of vascular injury and foam cells of atherosclerotic plaques 91, 92 Furthermore, increased IL 8 levels have been associated with unstable angina, acute myocardial infarction, and risk of cardiovascular events in patients with coronary artery disease (CAD) 93 96 Finally, evidence supporting a role for IL 8 in patients at high risk without apparent CAD has been provided 97 Furthermore, cardioprotective drugs like statins have been shown to lower ENA 78 and IL 8 concentrations in human endothelial cells. Therefore, neutrophil chemokines may be important targets for CVD drug treatment. F ibrates have been shown to favorably modulat e lipoprotein concentrations but, unlike with the statins, their anti inflammatory properties are not well elucidated 23, 24, 53, 54, 98 100 We h ave recently reported the effects of fenofibrate on reducing ENA 78 production in an in vitro model of endothelial inflammation, with no effect on IL 8 (Chapter3) 98 Here we t ested whether fenofibrate treatment modulates ENA 78 concentrations in people with suboptimal lipid profiles. We also tested whether the neutral effect of fenofibrate on IL 8 in vitro is observed in vivo. Subjects and Methods Subjects The study protocol was reviewed and approved by the University of Florida Institutional (GCRC) Scientific Advisory Committee. I n order to be eligible for study participation, subject s were required to have fasting triglycerides > 150 mg/dL and/or low HDL (<44 mg/dL for men or <54 mg/dL for women) and be at least 18 years of age Selection criteria for elevated lipid levels are based on criteria proposed by the National Cholesterol Edu cation Program (NCEP) Adult

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53 Treatment Panel III (ATP III) and NHANES III for abnormal thresholds of triglycerides and HDL, respectively 101, 102 Subjects were excluded if they had known CHD, symptomatic carotid ar tery disease, peripheral artery disease, abdominal aortic aneurysm, diabetes, Framingham 10 triglycerides exceed ed 400 mg/dL or if LDL was above the treatment thresholds as recommended by NCEP. Other exclusions were pregnancy ruled out by blood or urine HCG test malignancy, liver dysfunction (AST or ALT > the upper limit of normal), renal dysfunction (creatinine clearance < 30 ml/min by Cockroft Gault calculation), active alcohol abus e, history of unexplained muscle pain, and current treatment with lipid lowering therapy. Women of child bearing potential were required to agree to active use of a reliable method of birth control for the study duration. Subjects on estrogens, androgens progestins (other than contraceptives), thiazide diuretics, beta blockers, glucocorticoids (other than inhaled), anti histamines, or other chronic anti inflammatory drugs were excluded from the study. Patients were also excluded if they were taking any of the following interacting drugs: ursodeoxycholic acid, ursodiol, cholestyramine, red yeast rice, glyburide, glipizide, warfarin, or cyclosporine. A double blind, randomized, placebo controlled cross over design was used (Figure 1) Eligible subjects w ere randomized within two weeks of screening to receive micronized f enofibrate 160 mg or matching placebo for four weeks After the initial four week period, subjects returned to clinic for laboratory measurements and were washed out for a period of four weeks. At the end of washout, subjects returned to clinic for repeat laboratory measurements and were crossed over to the alternative treatment for a final four week treatment period. All patients were counseled to take their capsules by mouth once daily and to inform the investigators of any changes in health or if they planned to start any new medication, vitamins,

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54 minerals, supplements, or alternative medicines. Randomization in blocks of 4 was conducted by the GCRC data support group and the randomiza tion scheme was provided directly to an independent compounding pharmacy preparing the treatments. Investigators were blinded to treatment assignments Blood Sampling and Analysis Study visits for participants required fasting and blood was drawn between t he hours of 7am and 2pm at the GCRC of Shands Hospital at the University of Florida. Clinical labs including fasting lipid panels, liver function tests and complete blood counts with differentials were obtained by standard protocols of the hospital core l aboratory. In addition, serum and plasma were collected in serum separator and EDTA tubes respectively and stored at 80C. Leukocytes for ex vivo cell culture were obtained from 10 ml EDTA vaccutainer blood collection tubes and cultured as previously des cribed 103 After 24 hours, the leukocytes were centrifuged and the resulting supernatant was collected for protein analysis. ENA 78 and IL 8 from serum and leukocyte culture medi a were analyzed in duplicate by multiplex cytometric fluorescence detection (R&D Systems, Minneapolis, MN) and leukocyte media cytokine values were normalized to total protein conten t as previously described 67 Statistical Design/Considerations The current report represents a substudy analysis of a larger NR1H3 genotype stratified pharmacogenetic study of fenofibrate. The pharmacogenetic study w as originally designed to enroll thirty subjects to provide 80% power to detect a between genotype effect size of 0.5 at p=0.05, two sided. However due to challenges with finding participants that met our strict enrollment criteria and more importantly du e to the tested formulation of 160 mg fenofibrate tablet no longer being commercially available, we decided to end enrollment early. Ending enrollment early reduced our estimated power to reject our original null hypothesis to 42%.

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55 However, if we assume that the data from the eleven patients that we have enrolled could be used to project the 95% confidence interval for the effect size if we had enrolled 30 patients, we would have an estimated 87 100 % power to disprove our null hypothesis ( which was that fenofibrate and placebo would have equal effects on ENA 78 and IL 8 levels ) The cytokine analyses were our primary aims in this study with the idea in mind that any significant findings would require secondary studies for support. For the measurement of ENA 78 and IL 8 we accepted a p value below 0.05 two sided as significant. A Welch corrected t test (for unequal variance) was employed and t reatment order was also compared using the general linear model. Data for the traditional clinical biomarkers are represented as mean standard deviation and the data for the cytokine analysis is presented as median with inter quartile range. Results Thirteen of forty six screened participants were eligible. Two of the eligible subjects elected not to particip ate in the treatment phase of the study (one subject joined a fitness weight loss challenge and the other did not provide a reason for discontinuing) and therefore eleven subjects were randomized to the treatment phases of the study. The study sample was comprised of six white, three Asian, one black, and one Hispanic participant. The mean age of participants was 2811 years with 6 men and 5 women. Baseline characteristics for the subjects that participated in the treatment phases of the study are listed i n Table 4 1. Consistent with our previous in vitro data (Chapter 3), fenofibrate had no significant effects on IL 8 serum concentrations or production of IL (Figures 4 2 and 4 3) Specifically, median IL 8 levels in serum were 13.5 pg/ml (IQR=9 27 pg/ml) at baseline, 12 pg/ml (IQR=12 23 pg/ml) after placebo and 19 pg/ml (IQR=14 23 pg/ml) after fenofibrate (p=0.099). Furthermore, median IL 8 levels in leukocytes were 645 pg/mg

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56 (IQR=420 1460 pg/mg) at baseline, 951 pg/mg (IQR=706 1713 pg/mg) after placebo and 786 pg/mg (IQR=410 1929 pg/mg) after fenofibrate (p=0.198). Median ENA 78 serum levels were 1290 pg/ml at baseline (IQR =779 1840 pg/ml), 1190 pg/ml after placebo (IQR =952 1760 pg/ml) and 1550 pg/ml after fenofibrate (IQR =997 2440 pg/ml). This represented an estimated 27% increase (95% CI: 5.9 to 52.1%) in ENA 78 production after fenofibrate compared with placebo (p=0.015 Figure 4 4 ). Contrarily, ENA 78 production from leukocytes was nominally, though not significantly, lower after treatment with fenofibrate compared to placebo Median ENA 78 levels from leukocytes were 446 pg/mg (IQR=304 669 pg/mg) at baseline, 579 pg/mg (IQR=364 1449 pg/mg) after placebo and 433 pg/mg after fenofibrate (IQR=329 687 pg/mg) (p=0.056 95 % CI: 55 to 1%, Figure 4 5 ). The effects of fenofibrate on lipoprotein effects were directionally consistent with the known effects of the drug on these parameters. Total cholesterol, LDL, and triglycerides were non significantly decreased and HDL nonsi gnificantly increased after fenofibrate; CRP was unchanged by fenofibrate treatment (Table 4 2). Statistical tests for treatment order effect did not reveal any significant differences of any parameters measured. Discus sion The pleiotropic anti inflammato ry properties of fibrates have not been well characterized. Therefore we designed a double blind, placebo controlled crossover study using fenofibrate 160 mg as the active treatment. We investigated fenofibrate effects on IL 8 and ENA 78 because of their putative roles in CVD and our previous work to showing these chemokines are modulated by beneficial CVD drugs such as the statins. We have also shown through in vitro studies that fenofibrate had direct endothelial effects on ENA 78 production while not effecting IL 8 production. The disparate effects of fenofibrate on the endothelial production of these neutrophil

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57 chemokines makes them an interesting choice to study anti inflammatory effects in our clinical study. IL 8 and ENA 78 were not consistently m odulated by fenofibrate in this clinical study. For example, as with our previous in vitro study, fenofibrate did not significantly affect production of IL 8. However, serum levels of ENA 78 were significantly elevated after 4 weeks of fenofibrate while leukocyte production of ENA 78 was not significantly elevated compared to placebo. Disparate effects of fenofibrate on IL 8 versus ENA 78 are plausible because their respective genes have different regulatory pathways despite sharing a considerable amount of sequence homology. Furthermore the previously published effects of fenofibrate on IL 8 production have been variable and this report did not find an effect of fenofibrate on IL 8. We have recently reported that fenofibrate modulates ENA 78 production in human endothelial cells 98 however the effects of fenofibrate on other sources of ENA 78 have not been well studied. For example, ENA 78 is also produced by monocytes, neutr ophils, and platelets which may have different regulatory mechanisms controlling ENA 78 production. Damas et al ., published work supporting this thought process in patients with congestive heart failure (CHF). In their study it was observed that ENA 78 p lasma levels were correlated with increasing New York Heart Association functional classification. The researchers decided to measure the ability 78 in response to inflammatory stimuli. The purp ose of their experiment was to determine the role of the respective cell types in progression of CHF. The researchers discovered that stimulated monocytes from the patients with CHF released large amounts of ENA 78 while the stimulated platelets did not 61 In work from our laboratory we reported significant concentration dependent reductions in ENA 78 production from endothelial cells by atorvastatin 67 However when we trea ted 74 CVD free

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58 patients with 80 mg of atorvastatin for 16 weeks, we only observed a modest 6% decrease in production of systemic ENA 78 levels 104 This could indicate that the circulating levels of ENA 78 are not w ell correlated with the production from the endothelium. Therefore, it may be reasonable to consider tissue specific approaches to assess the effects of pharmacologic agents on production of ENA 78. There are relevant limitations that should be considere d while reading this report. As reported earlier, we abandoned our initial enrollment plan due to recruitment and primarily drug supply limitations. With eleven patients overall this resulted in unequa l numbers of patients that received each treatment fi rst (5 patients received fenofibrate first vs 6 that received placebo first ). When sample sizes differ based on the order of treatment you theoretically introduce bias to your comparisons in a cross over study. Furthermore, smaller studies are at increase d risk of over estimating or underestimating treatment effects due to type I and II error. We observed a reduced power to reject our null hypothesis in this study which must also be considered when drawing conclusions from this report. However, we also ca lculated a conditional power estimate which predicted that if the study was performed to completion we would have observed similar findings with excellent power. Conditional power is not considered static and could change as data accrues (for example if th e remaining 19 patients had been enrolled). Therefore the investigators have considerable doubt as to whether the final result would have been significant or not. T his should be also considered while taking conclusions from this report. The study enroll ed subjects with suboptimal lipid levels that were not severe enough to require pharmacologic therapy. To our knowledge this was the first study exploring the effects of a fibrate on ENA 78 and maybe the results would have differed if a more severe phenot ype was chosen.

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59 Conclusion s and Future Directions In this study we report further evidence supporting the lack of significant effects of fenofibrate on circulating levels and leukocyte production of IL 8. The previously observed in vitro effects of fen ofibrate on ENA 78 did not translate to observable reductions in ENA 78 in this clinical study. Future studies with larger sample sizes and different phenotypes of patients could be beneficial for establishing the clinical effects of fenofibrate on ENA 78.

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60 Table 4 1 Demographics, chemical and biochemical c haracteristics Characteristics Baseline Age (years) 2811 Gender (men/women) 6/5 Race (% white) 45 Systolic blood pressure (mm Hg) 11812 Diastolic blood pressure (mm Hg) 738 BMI (kg/m 2 ) 2 76 Waist circumference (Inches) 334 Hip Circumference (Inches) 384 Total Cholesterol (mg/dl) 18441 LDL Cholesterol (mg/dl) 11234 HDL Cholesterol (mg/dl) 428 Triglycerides (mg/dl) 15355 Apolipoprotein A 1 (mg/dl) 14918 Apolipoprotein B (mg/d l) 9320 WBC (x10 9 L 1 ) 7.12 Neutrophil Proportion (%) 616 Lymphocyte Proportion (%) 286 Monocyte Proportion (%) 52 Eosinophil Proportion (%) 32 Basophil Proportion (%) 0.80.3 Platelets (x10 9 L 1 ) 29961 hsCRP (mg/l) 1.891.9

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61 Table 4 2. E ffect of four weeks of f enofibrate 160mg or placebo on lipoprotein related p arameters Characteristics Baseline (B) After Placebo (P) After fenofibrate (F) P value F vs. P Total Cholesterol (mg/dl) 18441 18935 16938 0.1035 LDL Cholesterol (mg/dl) 112 34 11130 10331 0.3202 HDL Cholesterol (mg/dl) 428 434 459 0.3214 Triglycerides (mg/dl) 15355 13062 9952 0.0887 Apolipoprotein A 1 (mg/dl) 14918 13611 14020 0.470 Apolipoprotein B (mg/dl) 9320 9319 9024 0.0655 hsCRP (mg/l) 1.891.9 1.71. 4 1.41.3 0.58

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62 Figure 4 1. Clinical study d esign

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63 Figure 4 2. IL 8 concentrations observed in subject serum (Line indicates median value) Figure 4 3. IL 8 concentrations observed in subject leukocyte culture (Line indicates median value)

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64 Figure 4 4. ENA 78 concentrations observed in subject serum (Line indicates median value) Figure 4 5. ENA 78 concentrations observed in subject leukocyte culture (Line indicates median value)

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65 CHAPTER 5 CONCLUSIONS CVD remains the leading cause of death and disability in industrialized countries. Major efforts to reduce the burden of CVD exist but the prevalence of the myriad of disea ses contributing to CVD are not dramatically decreasing. Therefore, efforts to understand the contribution of genetics to cardiovascular risk and variable response to pharmacologic therapy are increasing. The nuclear receptor LXRA has been proven critical to cardiovascular homeostasis. It has been discovered that LXRA has regulatory roles in cholesterol homeostasis, vascular homeostasis and the inflammatory/immune response. Furthermore, LXRA may be important for cardiovascular risk and pharmacogenetic pre diction. In this dissertation we have added evidence to support the role of LXRA genetic variants in risk of CVD and pharmacogenetic response. In this study we demonstrated variable CVD outcomes based on NR1H3 genotypes. We observed a protective associati on with the variant allele of rs11039149. In secondary analyses, the variant allele of rs11039149 was associated with decreased risk of n on fatal stroke and d eath R s2279238 variants were associated with increased risk of the primary outcome. Secondary a nalyses revealed a trend towards increased risk with the presence of each variant alle le for each secondary outcome, h owever this effect was only significant for risk of death. The pharmacogenetic association observed with rs2279238 genotype and risk of th e primary outcome are supported by recent discoveries of LXRA function in vascular homeostasis. Further investigation will help to clarif y the results of these findings and potentially answer pharmacogenetic interests created by this study. The initial s teps for planned follow up studies include a functional analysis of the SNPs associated with outcomes in the study. Based upon in silico estimations, rs2279238 is located at an exon splicing enhancer (ESE) of NR1H3 where the

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66 splicing factor SRp55 binds. It is well known that LXRA has several splice variants that are expressed at varying levels in different tissues. Therefore it would be logical to explore the potential of rs2279238 to influence alternative splicing of LXRA. Another option for measuring functional consequences of the SNPs identified would be to perform allelic expression imbalance analyses. This method measures mRNA expression of each allele using pyrosequencing and has been previously used in our laboratory. Each allele should be expre ssed in equal amounts when normalized to DNA, however variant SNPs can result in expression or stability abnormalities of the mRNA of the variant allele. This technique may provide insight into the influence of this SNP on the variable risk observed. Fur thermore it would be important to replicate the clinical results observed from INVEST GENES in a similar study with a beta blocker and a calcium channel blocker. Replication cohorts are challenging to find for genetic hypertension studies so maybe a small er study to examine mechanistic interactions of beta blockers and calcium channel blockers with NR1H3 pathways may be desirable. A clinical study that would be potentially significant would be based upon the hypothesis that SNPs in NR1H3 result in dysregul ation of the cholesterol aldosterone cortisol pathway (described in the introduction chapter) and these patients would be good candidates for beta blockade. Preliminary data for the initial hypothesis can be obtained from the Pharmacogenomic Evaluation o f Antihypertensive Responses Study (PEAR). The NR1H3 genotypes for the initial 400 patients enrolled in PEAR are available and thus we could quantify biomarkers of choice (e g ., cortisol levels, plasma renin activity, etc) to support the cholesterol aldso sterone cortisol pathway hypothesis. Furthermore, we could test the association of blood pressure and response to treatment with the SNPs of NR1H3 If this hypothesis is supported by the results from the proposed study, this would provide substantial

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67 mec hanistic su pport for the initial results from INVEST blockade treatment strategy was not associated with risk based upon NR1H3 genotypes). Fenofibrate was selected as our pharmacologic agent for our in vitro and clinical studies because of its modulatory e ffects on LXRA. We did not observe any effects of fenofibrate on the production of IL 8. However, w e have observed novel effects of fenofibrate on the production of the neutrophilic chemokine ENA 78 in endothelial cells Fenofibrate decreased production of the neutrophil chemokine ENA 78 at protein and mRNA levels. This finding is interesting because fenofibrate has been increasingly associated with improved outcomes of microvascular disease over the last several years 58, 106, 107 However, the effects of fenofibrate have not correlated with decreased occurrences of macrovascular outcomes 58 Based upon the findings from our study and the published literature we can desig n future in vitro experiments to better inform the clinical observations associated with fibrate therapy. Our initial experiments were conducted in HUVECs which were treated with fenofibrate at concentrations equivalent to clinically observed plasma level s. Fenofibrate was chosen because of its regulatory effects on LXRA and its once daily dosage regimen. In future studies it will be beneficial to study the effects of fenofibrate in several tissues simultaneously. For example, similar experiments can be performed in human aortic endothelial cells (HAECs), human coronary artery endothelial cells (HCAECs), human cardiac microvascular endothelial cells (HMVEC C), human aortic smooth muscle cells (AoSMCs) or human coronary artery smooth muscle cells (CASMC). The available cell lines provide in vitro opportunities to expand our initial observations to microvascular and macrovascular tissues. The effects of fenofibrate (and other LXRA agonists) could be observed under basal conditions and diseased conditions induc ed by inflammation (IL induced). The effects of fenofibrate observed in the separate cell lines may provide valuable

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68 insight into the mechanisms driving variable risk reductions observed between microvascular and macrovascular outcomes. The clinical study that we designed for this dissertation was forced to end enrollment early which may have limited power to detect meaningful drug responses in our study. In our clinical study we observed directional trends of traditional lipid biomar kers consistent with fibrate response. Consistent with our in vitro experiments we observed no significant effects of fen ofibrate on IL 8. However, we did not observe significant effects of fenofibrate on ENA 78 in the clinical study to support our repor ted in vitro results. The study was designed as a double blind placebo controlled cross over study and this would have been beneficial to complete. However a simpler approach may be required to generate preliminary data and then the results could be u sed as preliminary data to submit a larger funding proposal or sub study proposal to an existing fibrate study. For example, The GOLDN study has 800 patients that were treated with 21 days of fenofibrate 160 mg daily. We have a proposal ready for submiss ion to perform genotyping on all 800 patients of the study. This will allow for analysis of the effects of NR1H3 polymorphisms on traditional biomarkers of lipid response and pleiotropic inflammatory effects of fenofibrate. Final Conclusions We set out wi th the goal to add evidence to the literature that LXRA is important for CVD risk prediction and response to drugs commonly used in CVD risk reduction. We provided support for genetic associations of CVD risk with NR1H3 genotypes and to our knowledge the first data supporting the exploration of pharmacogenetic associations with NR1H3 genotypes. Furthermore, we have provided a novel effect of fenofibrate on ENA 78 production in the human endothelium. This finding lends new evidence to the direct vascular effects of fenofibrate and potentially a link between ENA 78 and LXRA. Focused efforts in future experiments will

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69 improve our understanding of the mechanistic contribution of LXRA in cardiovascular diseases. Overall LXRA appears to be gaining support as an important biomarker for risk prediction and pharmacogenetic response.

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70 APPENDIX PRELIMINARY DATA: ST ATINS AND LXRA ABSTRACTS Abstract 1. Presented as a poster at the ACCP 2006 Annual meeting in St. Louis, MO Liver X receptor sponse to intensive lipid lowering therapy with statins Elvin T. Price, Pharm.D., Christopher B. Arant, M.D., Timothy R. Wessel, M.D., Richard S. Schofield, M.D., Issam Zineh, Pharm.D. University of Florida College of Pharmacy Dept of Pharmacy Practice a nd Center for Pharmacogenomics; University of Florida College of Medicine, Division of Cardiovascular Medicine; Gainesville, Florida PURPOSE: Intensive lipid lowering with statins is a preferred treatment strategy in certain patient populations. The bene fit of high dose treatment is thought to be due to both greater low density lipoprotein (LDL) and C reactive protein (CRP) reduction. However, variability in LDL and CRP responses exist, and genetic factors may contribute. We investigated whether a singl e nucleotide polymorphism (SNP) in the LXRA gene, a potential nuclear site of statin action, is associated with either LDL or CRP responses to atorvastatin 80 mg. METHODS: Subjects were eligible if they were at least 18 years old without CHD, or CHD risk equivalents, or contraindications to statins. Subjects received atorvastatin 80 mg daily for 8 weeks. Baseline and 8 week lipids and CRP were obtained from the university hospital clinical laboratory. Genotype determination of the LXRA rs12221497 G/A S NP was performed by pyrosequencing. Biomarker changes were tested by t test and multivariate analysis. RESULTS: A total of 61 subjects (59% women; 79% white) were analyzed. Baseline age, total cholesterol, LDL, HDL, triglycerides, and CRP were 3213 years, 17838 mg/dl, 9831 mg/dl, 6218 mg/dl, 9754 mg/dl, and 1.82.9 mg/L, respectively. The variant A allele frequency was 16 %. There were no differences in lipid changes by genotype (not shown). However, wild type homozygotes (G/G) had an 11% redu ction in CRP compared with a 25% increase in variant carriers (p= 0.047). In multivariate analysis, age (p=0.01), baseline CRP (p=0.02), and LXRA genotype (p=0.04) were significant predictors of CRP response (model p=0.002; r2=0.23). CONCLUSIONS: LXRA genotype did not affect LDL response to 8 weeks of high dose atorvastatin. However, LXRA genotype was associated with the atorvastatin mediated CRP changes. This is the first study to demonstrate a genetic association with the CRP statin response and sho uld be further evaluated.

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71 Abstract 2. Presented as a poster presentation at the 2007 ASCPT Annual meeting, Anaheim, Ca. Liver X Receptor reactive protein response to atorvastatin Elvin T. Price, PharmD, Amber L. Beitelshees, PharmD, MPH, Issam Zineh, PharmD, University of Florida, Gainesville, FL, Washington University School of Medicine, St Louis MO PURPOSE: Statin therapy has been shown to reduce morbidity and mortality associated with cardiovascular disease (CVD) independently of lipid lowering effects. Reduction in C reactive protein (CRP) levels has been observed as a beneficial anti inflam matory effect of statins. Liver X receptor is a transcription factor involved in cholesterol homeostasis, and we previously found an association between a single nucleotide polymorphism (SNP1, rs12221497) in LXRA and CRP response to atorvastatin. We th us considered whether a second SNP2 (rs7120118;) or LXRA haplotypes (using the two SNPs) would be more informative than consideration of single SNPs alone. METHODS: Subjects were eligible if they were at least 18 years old, normocholesterolemic, without coronary heart disease. Subjects received atorvastatin 80 mg daily for 8 weeks. Baseline and 8 week high sensitivity CRP concentrations were measured. Genotype determination was performed by pyrosequencing. Haplotypes were constructed with PHASE softw are. Percent change in CRP was compared by genotype groups by analysis of covariance controlling for age and baseline CRP. RESULTS: A total of 58 subjects (60% women; 79% white) were analyzed. Baseline age, total cholesterol, LDL, HDL, triglycerides, and CRP were 3214 years, 18338 mg/dl, 10132 mg/dl, 6118 mg/dl, 9955 mg/dl, and 2.23.5 mg/L, respectively. SNP1 and SNP2 variant allele frequencies were: A=14% and C=27%. SNP1 and SNP2 variant allele carriers experienced attenuated CRP reductions c ompared to wild type homozygotes ( 1.5% vs 17.9% & 10.6% vs 16.2% respectively). Attenuated CRP response was driven by the SNP1 variant A allele, and consideration of haplotypes was no more informative than consideration of SNP1 genotype alone (data no t shown). CONCLUSIONS: Consistent with our previous report, LXRA SNP1 genotype appears to be associated with CRP response to atorvastatin. Consideration of SNP2 or derived haplotypes was not more informative. Our analysis was limited by small sample s ize and requires further investigation in larger cohorts.

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72 NR1H3 GENE POLYMORPHISMS A ND INVEST GENES : SUPPLEMENTARY DATA Effect of LXRA Genotypes and Primary Outcomes Stratified by Race For rs2279238 the findings were significant for variant carri ers and variant homozygote carriers in whites (C/T genotype OR: 1.61, CI: 1.06 2.43, p=0.024 and T/T genotype OR: 3.85, CI: 1.45 10.23, p=0.007). The effects were not evident in Hispanics and Blacks. The G allele of SNP rs11039149 was associated with a re duction in risk for primary outcomes in whites (A/G carriers OR: 0.70, CI: 0.48 1.04, p=0.076 and G/G carriers OR: 0.45, CI: 0.21 0.98, p=0.04). Similar trends were observed for rs11039149 in the Hispanic subjects but not in the Blacks. Table A 1. Pri mary outcome by LXRA g enotype and race SNP/Genotype Whites Hispanics Blacks rs11039149 (A>G) A/G 0.70 (0.48 1.04) 0.56 (0.29 1.10) 1.14 (0.32 4.03) G/G 0.45 (0.21 0.98) 0.44 (0.08 2.52) N/A rs2279238(C>T) C/T 1.61 (1.07 2.43) 0.83 (0.45 1.55) 0.79 (0.29 2.15) T/T 3.85 (1.45 10.23) 2.50 (0.76 8.25) 1.28 (0.42 3.93) Odds ratios/95% CI (For each genotype with Wild Type carriers serving as reference) from logistic regression adjusted for: age, sex, race/ethnicity, BMI,INVEST treatment strategy, history of CHF, history of MI and history of diabetes at baseline

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73 Figure A 1. Adjusted odds ratios for secondary outcomes based on genotypes

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74 SUPPLEMENTARY DATA A ND ABSTRACTS FROM IN V ITRO ANALYSES PPAR A and LXR A cross talk in HUVE Cs A recent report suggests that fenofibrate selectively modulates LXRA prior to being 79 Fenofibrate is antagonistic to LXRA via directly binding to the ligand binding domain 79 but fenofibric acid serves as an agonist to LXRA via PPARA agonism and favorably modulating a PPARA response element in the promoter region 26 2 9 Both pathways have been hypothesized as potential contributors to fibrate response, therefore decided to examine the effects of fenofibrate on PPARA and LXRA mRNA production in our experiments. Furthermore the results would indicate if fenofibrate was we examined the effects of Fenofibrate on transcriptional changes in PPARA and LXRA to explore the contribution of nuclear receptor cross talk on the effects observed on ENA 78 and IL 8. The Effects of Fenofibrate on PPARA and LXRA Gene Expression As shown in Figure A 2, There was a greater effect of fenofibrate observed on PPARA i ncreased 157% compared to control expression, while LXRA was increased 114%. In the cells co treated with IL expression, while LXRA was increased 65% (Figure A 2).

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75 Figure A 2. The effects of fenofibrate on PPARA and LXRA gene expression

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76 Abstracts Fenofibrate modulates interleukin stimulated Granulocyte macr ophage colony stimulating factor ( GMCSF) production in the human endothelium El vin T. Price, Pharm.D., Gregory Welder, Issam Zineh, Pharm.D. University of Florida College of Pharmacy Dept of Pharmacy Practice and Center for Pharmacogenomics; Gainesville, Florida PURPOSE: The early atherosclerotic process is characterized by a cycle of endothelial dysfunction and inflammation. Inflammatory cytokines including the colony stimulating factors (e g ., GCSF, GMCSF) help stimulate the production of macrophages and other immune cells which are recruited to the site of endothelial dysfunction and subsequently can contribute to atherosclerotic plaque formation. Fibrates are a class of lipid lowering drugs with anti inflammatory effects. It has been hypothesized that the cardioprotective effects of fibrates are partially due to these anti infl ammatory effects. Their ability to affect IL mediated endothelial GCSF and GMCSF expression is unknown. We examined the effects of fenofibrate on the production of these chemokines. METHODS: Human umbilical vein endothelial cells (HUVECS) were cultured and treated wit h IL 2ng/mL) to induce an inflammatory response, and with fenofibrate 1 50uM. GCSF and GMCSF production were measured in the cell culture supernate by cytometric immunofluorescence. ANOVA with post hoc Tukey were performed, and significance was set a t P<0.05. RESULTS: As expected, GCSF and GMCSF production were significantly induced by IL 1 cells treated with IL 1 (meanSEM=13.062.97 pg/mg vs 3468.341551.08 pg/mg, p<0.005) a nd GMCSF was over 3000 times higher than control (meanSEM=2.075780.108 pg/mg vs 7201.80615.6 pg/mg, p<0.001). Fenofibrate significantly reduced GMCSF at concentrations 10 50uM (Figure A 3) with no effect on GCSF (Data not Shown). CONCLUSIONS: Feno fibrate blunts IL 1 mediated GMCSF production with no effect on GCSF. This represents a novel mechanism fenofibrate anti inflammatory effect and should be further explored.

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77 Figure A 3. Effects of fenofibrate on GM CSF.

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78 Abstract 2. Presented as a p oster at the 2008 ASCPT annual meeting in Orlando fl. Fenofibrate attenuates interleukin endothelium Author Block: Elvin T. Price, Greg ory J. Welder, Issam Zineh, University of Florida Gainesville F L Ob jectives: RANTES (CCL5) is a chemokine implicated in many diseases with an inflammatory component, including cardiovascular disease. Endothelial RANTES expression is highly inducible by inflammatory proteins such as IL1 Fibrates are a class of lipid l owering drugs with some anti inflammatory effects. Their ability to affect IL mediated endothelial RANTES expression is unknown. We examined the effects of fenofibrate on the production of this chemokine. Methods: Human umbilical vein endothelial ce lls (HUVECS) were cultured and treated with IL 2ng/mL) to induce an inflammatory response, and with fenofibrate 1 50uM. RANTES production was measured in the cell culture supernate by cytometric immunofluorescence. SPSS version 11.0 was used to perfo (Significance was set at P<0.05). Results: As expected, RANTES production was significantly induced by IL 1 with IL 1 ntrol (meanSEM=2.660.523 pg/mg vs 628.475 pg/mg, p<0.001). Fenofibrate significantly reduced production of RANTES at concentrations 10 50uM (Figure A 4). Conclusions : Endothelial RANTES was induced by IL 1 fenofibr ate. The clinical significance of these findings should be further explored.

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79 Figure A 4. Fenofibrate attenuates IL

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80 ADDITIONAL E XPLORATORY HUVEC M ANUSCRIPT PREPARED FOR S UBMISSION Effects of Fenofi brate on the Diseased Endothelium BACKGROUND/AIMS: The fibrates are a class of lipoprotein modulating drugs commonly used in the treatment of dyslipidemia. Fibrates work by binding to the nuclear receptor PPAR and thus influence transcr rget genes. Therefore, fibrates influence expres sion of enzymes that metabolize fatty acids and attenuate inflamma tion in several organ systems. However, variable results to reach primary outcomes have been observed in fibrate clinical trials. In patients with higher levels of inflammatory biomarkers the production of PPAR is decreased. This decrease in the production of PPAR could be linked to atherosclerosis and the observed variable results to fibrates. W e decided to explore the effects of inflamm ation on the response to fenofibrate in human endothelial cells. METHODS: Human umbilical vein endothelial cells (HUVECS) were cultured until 80% confluence, treate d with IL 2ng/mL) to induce an inflammatory response, and subsequently with fenofibrate 10uM. TNF CSF and RANTES protein production were measured in the cell culture supernate by cytometric immunofluorescence and the rate of gene expression was measured via RT PCR. ANOVA with post hoc Tukey was performed, and significance was set at P<0.05. RESULTS: RT PCR and protein quantification were used to observe the effects of IL inducing inflammation in endothelial cells. We found that IL nificantly induced gene expression and production of inflammatory cytokines and chemokines. The pathways affected are consistent with clinical observations associated with CVD. We treated the inflamed cells to down regulate th e inflammatory process es Fenofibrate significantly lowered IL induced protein production of TNF CSF and RANTES ( 94%, 78%, and 96% respectively) with no apparent effects on their respective gene expression. CONCLUSIONS : Fenofibrate exhibited anti inflammatory properties in the presence of inflammatio n induced by IL 1 The clinical significance of these findings should be further explored.

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81 Effects of Fenofibrate On The Diseased Endothelium Introduction The fibrates are a class of lipoprotein modulating drugs commonly used in the treatme nt of dyslipidemia. Fibrates work by binding to the nuclear receptor PPAR (PPARA) and thus influence transcription of its target genes. Therefore, fibrates influence expression of enzymes that metabolize fatty acids and attenuate inflammation in several organ systems. The cardiovascular system is one of the organ systems where the receptors are highly expressed 27, 109 111 However, in patients with higher levels of inflammatory biomarkers the production of PPA RA is decreased. This decrease in the production of PPARA could be linked to atherosclerosis and variable results associated with the large clinical trials of fibrates 112 For example, in the FIELD trial where nearly 10,000 diabetics were enrolled to treatmen t with fenofibrate or placebo the effects on HDL were smaller than expected and cardiovascular outcomes were not reduced. FIELD was comprised of diabetics who typically have higher levels of inflammatory biomarkers than healthy individuals 113 Hence inflammation may have contributed to the poor response to fenofibrate in FIELD. We designed a series of in vitro studies to explore the potential effects of inflammation on poor response to fenofibrate. Human umbilical vein endothelial cells (HUVECs) are commonly used for in vitro studies of inflammation and atherosclerotic disease processes. HUVECs are known to express biomarkers of inflammation associated with CVD/diabetes and thus may provide insight relevant to the poor response observed in fibrate clinical trials. Methods Cell Culture and Treatment

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82 The methods used for culturing HUVECs are published in prior papers from our group 67 In brief we cultured HUVECs to 80% confluenc e in growth media at physiological temperature and 5% CO 2 Serum free media was used 24 hours prior to treatment in 2% fetal bovine serum media. Treatment groups included un stimulated control, fenofibrate (Sigma Aldrich, St. Louis, MO) 10M, and fenofibr ate 10M in cells pretreated with 2ng/mL IL Each experimental condition was repeated six times (N=6). Cytokine levels were measured in triplicate using cytometric fluorescence detection (R&D Systems, Minneapolis, MN; Luminex 100IS, Luminex Corp., Aus tin, TX; Fig. 1a) and normalized to total protein (Pierce, Rockford, IL). Gene expression was measured using RT PCR ( Applied Biosystems, Foster City, CA, USA). Protein Quantification and Gene Expression After 24 hours of treatment, media was removed for p rotein measurement and ribonucleic acid (RNA) was isolated from the HUVECs using an RNeasy Mini Kit (Qiagen Inc., Valencia, CA, USA) per manufacturer protocol. RANTES, GM CSF, and TNF measured and normalized to total protein content in cell culture supernates by multiplex immunofluorescence detection as previously described (R&D Systems, Minneapolis, USA for the Luminex 100Is, Luminex Corporation, Austin, USA). RNA concentration and absorbance ratios were assessed using a Nanodrop (N anodrop Technologies, Wilmington, DE, USA) spectrophotometer. A total of 500ng of total RNA was reverse transcribed to complementary DNA (cDNA) using an RT 2 First Strand Kit (SABiosciences Corp., Frederick, MD, USA) for subsequent analysis in a pathway fo cused, real time polymerase chain reaction (RT PCR) based array (Atherosclerosis PCR Array, SABiosciences). The RT PCR reaction was performed in a 7300 real time system for 40 cycles (Applied Biosystems, Foster City, CA, USA). All plates

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83 were normalized to the same threshold value and baseline. Any threshold cycle (Ct) equal to or greater than 35 on average for a gene was considered to be non expressed. Statistical Analysis One way ANOVA with post test were performed were appro priate; P<0.05 was considered significant. Results We found that fenofibrate did not reduce IL 1 induced gene expression of TNF (Figure A 5a), RANTES (Figure A 6a), or GM CSF (Figure A 7a). However, fenofibrate did significantly reduce IL 1 induced pr otein production of TNF (figure A 5b), RANTES (figure A 6b), and GM CSF (figure A 7b). Fenofibrate reduced IL and RANTES to their respective pre induction ranges. Post treatment levels of GM CSF were significantly lower after fenofibrate treatment but did not approach pre IL 1 induction range. Discussion We found that IL inflammatory cytokines and chemokines. The pathways affected are consistent with clinical observations associated with CV D. We selected cytokines/chemokines associated with CVD/diabetes to serve as biomarkers of interest in the response to fenofibrate. TNF RANTES, and GM CSF established biomarkers were highly induced by IL fenofibrate decreased pro tein levels of TNF CSF significantly without in several ways. The reduction of the classical inflammatory biomarker TNF fenofi brate actually worked in the presence of an inflamed endothelium. Inflammation alone

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84 may not be responsible for variable outcomes associated with fibrates. Future clinical and in vitro studies designed to address this issue should be conducted.

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85 Figure A 5a. TNF g ene expression Figure A 5b. TNF p rotein production

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86 Figure A 6a. RANTES gene exp ression Figure A 6b. RANTES protein production

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87 Figure A 7a. GM CSF g ene expression Figure A 7b. GM CSF protein production

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88 EFFECT OF FENOFIBRATE ON NEUTR OPHIL CHEMOKINES IN PEOPLE WITH SUB OPTIMAL LIPOPROTEIN PROFILES: EXPLORATOR Y ANALYSIS OF A RAND OMIZED, DOUBLE BLIND, PLACEBO CONTROLLED STUDY: SUPPLEMENTARY FIGURE S Figure A 8a. ENA 78 serum con centrations in subjects that received fenofibrate as the initial treatment. Figure A 8b. ENA 78 serum concentrations in subjects that received placebo as the initial treatment

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89 Fi gure A 9 ENA 78 serum concentrations. Patients 25 144 received placebo as treatment 1 followed by fenofibrate as treatment 2 (Post Placebo= Visit 2, Post fenofibrate=Visit 4)

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90 Figure A 10a. Triglyceride concentrations in subjects receiving fenofibrate as treatment 1. Figure A 10b. Triglyceride concentrations in subjects receiving placebo as treatment 1.

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91 F igure A 11. Triglyceride concentrations. Patients 25 144 received placebo as treatment 1 followed by fenofibrate as treatment 2 (Post Placebo= Visit 2, Post fenofibrate=Visit 4 )

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101 BIOGRAPHICAL SKETCH Elvin Tyrone Price is a native of Quincy Florida where he was born to the parents Ronnie and Carrie Price. He was educated in public school system of the Gadsden County where he attended St. John Elementary School, Carter Parramore Middle School, James A. Shanks High School and Dual Enrollment at Tallahassee Community Coll ege. Upon graduating high school he attended Florida A&M University where he obtained the Doctor of Pharmacy Degree in 2004. He married the former Andrea Smith on July 29, 2006 and their union has produced one son Henry Elvin Price. Elvin plans to dedi cate his career to academic medicine as a faculty member.