1 GENETIC VARIATION OF BETA ADRENERGIC RECEPTOR KINASE 1 AND BETA ARRESTIN 1: DEFINITION, FUNCTIONAL CONSEQUENCES, CLINICAL IMPLICATIONS By MAXIMILIAN T HOMAS LOBMEYER 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
2 2009 Max i milian T homas Lobmeyer
3 To my family, my mother Helga Lobmeyer Wankerl, my father Gerhard Wankerl, and my brother Ludwig Wankerl
4 ACKNOWLEDG E MENTS I would like to express my sincere thanks to my mentor Dr. Julie Johnson for giving me the opportunity to conduct my doct oral research in her laboratory. I highly appreciate her guidance, experience and dedication which helped me pursuing my goals while working on this project. I would also like to thank my supervisory committee members Dr. Stephen Baker, Dr. Hartmut Derendorf Dr Taimour Langaee and, Dr. I ssam Zineh for their expertise, advice, and encouragement. The completion of this dissertation would not be possible without their timely feedback and advice. My gratitude goes to all present and former faculty members and staff in the department of Pharm acy Practice for their support and for all they taught me during my time at the University of Florida. In particular, Dr. Yan Gong Dr. Amber Beitelshees and Dr. Jaekyu Shin were great sources of inspiration and always willing to provide their advice. I would like to acknowledge Mr. Ben Burkley and Ms. Lynda Stauffer and my fellow graduate students for their great support and assistance. I would like to acknowledge Dr. David Moraga, Dr. William Farmerie, Mrs. Nedka Panayotova, and Mr. Patrick Thimote at the University of Florida Interdisciplinary Center for Biotechnology for their support in performing the sequencing and chip genotyping. I would like to extend my thanks to Dr. Hende les, Mrs. Carmen Stowell, and M s. Alice Boyette for their help with the c linical studies. Furthermore, I would like to thank Dr. Richard W einshilboum and Dr. Liewei Wang at Mayo Clinic College of Medicine My personal thanks go to my family for their love, support, guidance and encouragement throughout my life. Finally, I would like to express my sincere gratefulness to my girlfriend Sara for her support, friendship, kindness and love.
5 TABLE OF CONTENTS page ACKNOWLEDGEMENTS ................................ ................................ ................................ ......... 4 LIST OF TABLES ................................ ................................ ................................ ...................... 8 LIST OF FIGURES ................................ ................................ ................................ .................... 9 ABSTRACT ................................ ................................ ................................ ............................. 10 CHAPTER 1 INTRODUCTION AND BACKGROUND ................................ ................................ ........ 12 Hypertension ................................ ................................ ................................ ...................... 12 blocker Pharmacogenetics ................................ ................................ ............................... 12 Arrestin 1 ................................ ................................ ............... 14 ADRBK1 and ARRB1 Organization and Variation ................................ .............................. 16 Summary and Significance ................................ ................................ ................................ 17 2 MATERIALS AND METHODS ................................ ................................ ........................ 20 Resequencing of ADRBK1 Regions ................................ ................................ .................... 20 Samples ................................ ................................ ................................ ....................... 20 Polymerase Chain Reactio n (PCR) Primer Design and Optimization ........................... 20 Resequencing Using 454 Technology ................................ ................................ .......... 21 Resequencing Using Sanger Sequencing ................................ ................................ ..... 23 Genotyping of Reported ADRBK1 Single Nucleotide Polymorphisms (SNPs) ............. 24 Determination of Linkage Disequilibrium Structure in ADRBK1 and ARRB1 ..................... 25 Structural Analysis of ADRBK1 ................................ ................................ ................... 25 Structural Analysis of ARRB1 ................................ ................................ ...................... 25 ADRBK1 and ARRB1 Expression in Healthy Volunteers ................................ .................... 26 Study Population ................................ ................................ ................................ ......... 26 DNA Isolation, Normalization, and Genotyping ................................ .......................... 27 RNA Isolation, Reverse Transcription, and Real time PCR ................................ ......... 28 Data Analysis ................................ ................................ ................................ .............. 29 ADRBK1 Expression in Lymphoblastoid Cell Lines ................................ ........................... 30 Samples ................................ ................................ ................................ ....................... 30 Genotyping ................................ ................................ ................................ ................. 30 ADRBK1 Expression ................................ ................................ ................................ ... 30 Data Analysis ................................ ................................ ................................ .............. 30 The Effect of ADRBK1 and ARRB1 Polymorphisms on the Clinical Response to Antihypertensive Therapy Pharmacogenomic Evaluation o f Antihypertensive Responses (PEAR) ................................ ................................ ................................ ......... 31 Study Population ................................ ................................ ................................ ......... 31 Genotyping ................................ ................................ ................................ ................. 31
6 SNPs for investigation in clinical studies ................................ .............................. 31 DNA isolation, quantification, and normalization ................................ ................. 32 TaqMan genotyping ................................ ................................ ............................. 33 ............................ 33 Custom SNP array ................................ ................................ ................................ 35 Data Analysis ................................ ................................ ................................ .............. 36 The Effect of ADRBK1 and ARRB1 Polymorphisms on Adverse Cardiovascular Outcomes in Patients with Hypertension and Coronary Artery Disease In ternational Ve rapamil SR /Trandolapril St udy (INVEST) ................................ ................................ 37 Study Population ................................ ................................ ................................ ......... 37 Genotyping ................................ ................................ ................................ ................. 38 Data Analysis ................................ ................................ ................................ .............. 38 3 DEFINITION: RESEQUENCING OF ADRBK1 AND DETERMINATION OF LINKAGE DISEQUILIBRIUM STRUCTURE IN ADRBK1 AND ARRB1 ........................ 40 Introduction ................................ ................................ ................................ ........................ 40 Resequencing of ADRB K1 ................................ ................................ ................................ .. 41 Resequencing Using 454 Technology ................................ ................................ .......... 41 Resequencing Using Sanger Sequencing ................................ ................................ ..... 42 Genotyping of Reported ADRBK1 SNPs ................................ ................................ ..... 43 Determination of Linkage Disequilibrium Structure in ADRBK1 and ARRB1 ..................... 43 Structural Analysis of ADRBK1 ................................ ................................ ................... 43 Structural Analysis of ARRB1 ................................ ................................ ...................... 43 Discussion ................................ ................................ ................................ .......................... 44 4 FUNCTIONAL CONSEQUEN CES: VARIATION IN ARRB1 AND ADRBK1 EXPRESSION ................................ ................................ ................................ ................... 53 Introduction ................................ ................................ ................................ ........................ 53 ADRBK1 and ARRB1 Expression in Healthy Volunteers ................................ .................... 54 ADRBK1 Expression in Lymphoblastoid Cell Lines ................................ ........................... 55 Discussion ................................ ................................ ................................ .......................... 55 5 CLINICAL IMPLICATIONS: THE EFFECT OF ADRBK1 AND ARRB1 POLYMORPHISMS ON THE CLINICAL RESPONSE TO ANTIHY PERTENSIVE THERAPY AND ADVERSE CARDIOVASCULAR OUTCOMES ................................ .. 63 Introduction ................................ ................................ ................................ ........................ 63 The Effect of ADRBK1 and ARRB1 Polymorphism on the Clinical Response to Antihypertensive Therapy PEAR ................................ ................................ .................. 64 Genotype Quality Control ................................ ................................ ........................... 64 Blood Pressure Response ................................ ................................ ............................. 64 The Effect of ADRBK1 and ARRB1 Polymorphisms on Adverse Cardiovascular Outcomes in Patients with Hypertension and Coronary Artery Disease INVEST .......... 70 Genotype Qua lity Control ................................ ................................ ........................... 7 0 Primary Outcome ................................ ................................ ................................ ........ 70
7 Discussion ................................ ................................ ................................ .......................... 71 6 SUMMARY AND CONCLUSION ................................ ................................ .................... 91 APPENDIX ................................ ................................ ................................ .............................. 93 LIST OF REFERENCES ................................ ................................ ................................ .......... 97 BIOGRAPHICAL SKETCH ................................ ................................ ................................ ... 105
8 LIST OF TABLES Table page 3 1 454 sequencing runs ................................ ................................ ................................ ...... 47 3 2 454 FLX sequen cing: Detection of high quality differences between individual B and reference sequence ................................ ................................ ................................ ......... 47 3 2 Novel and confirmed ADRBK1 SNPs ................................ ................................ ............ 48 4 1 Healthy volunteer study: Baseline demographics ................................ ........................... 58 5 1 PEAR: Genotyping quality control of the IBC chip and the custom SNP array .............. 78 5 2 PEAR: Baseline characteristics ................................ ................................ ...................... 78 5 3 PEAR: SNPs identified to influence diastolic blood pressure reduction (monotherapy) ................................ ................................ ................................ ............... 79 5 4 PEAR: SNPs identified to influence systolic blood pressure reduction (monotherapy) ... 81 5 5 ADRBK1 SNPs identified to influence heart rate response (monotherapy) ...................... 82 5 6 ARRB1 SNPs identified to influence heart rate response (monotherapy) ......................... 83 5 7 INVEST: Baseline characteristics case control ................................ ............................... 84 A 1 Samples used for sequencing ................................ ................................ ......................... 93 A 2 Primer sequences, amplicon sizes, and annealing temperatures for Sanger and 454 Sequencing ................................ ................................ ................................ .................... 94 A 3 Sequencing primer sequences, amplicon sizes, and annealing temperatures for confirmed SNPs ................................ ................................ ................................ ............. 95 A 4 Pyrosequencing primer sequences,and annealing tem peratures SNPs to be confirmed and in the expression study ................................ ................................ ............................ 96
9 LIST OF FIGURES Figure page 1 1 adrenergic signaling. ................................ ................................ ................................ .. 19 3 1 Haploview generated LD map of twelve ADRBK1 SNPs in blacks. ............................... 49 3 2 Haploview generated LD map of four ADRBK1 SNPs in whites. ................................ ... 50 3 3 Haploview generated LD map of 86 ARRB1 SNPs in samples from Yoruba in Ibadan, Nigeria (YRI population). ................................ ................................ ................. 51 3 4 Haploview generated LD map of 79 ARRB1 SNPs in samples from Utah residents with ancestry from northern and western Europe (CEU population). .............................. 52 4 1 Relative ADRBK1 expres sion in healthy volunteers by race. ................................ .......... 59 4 2 Relative ARRB1 expression in healthy volunteers by race. ................................ ............. 60 4 3 Relative ADRBK1 expression in lymphoblastoid cell lines ( ADRBK1 703 T/C). ........... 61 4 4 Relative ADRBK1 expression in lymphoblastoid cell lines (rs4930416) ........................ 62 5 1 Blood pressure (BP) response to atenolol monotherapy by ADRBK1 rs1894111 genotype. ................................ ................................ ................................ ....................... 86 5 2 Blood pressure (BP) response to hydrochlorothiazide by ADRBK1 rs1894111 genotype. ................................ ................................ ................................ ....................... 87 5 3 Blood pressure (BP) response to atenol ol monotherapy by ARRB1 CAT haplotype. ....... 88 5 4 Blood pressure (BP) response to hydrochlorothiazide monotherapy by ARRB1 CAT haplotype ................................ ................................ ................................ ...................... 89 5 5 Adjusted odds ratio for minor allele carriers on probability of experiencing the INVEST primary outcome (first occurrence of death, nonfatal myocardial infarction, or stroke). ................................ ................................ ................................ ...................... 90
10 Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy GENETIC VARIATION OF BE T A ADRENGERIC RECEPTOR KINASE 1 AND BETA ARRESTIN 1: DEFINITION, FUNCTIONAL CONSEQUENCES, CLINICAL IMPLICATIONS By Maximilian T homas Lobmeyer May 2009 Chair: Julie A. Johnson Major: Pharmaceutic al Sciences B eta adrenergic receptor kinase 1 (beta ARK 1) and beta arrestin 1 are pivotal regulators in beta adrenergic signaling O ur stud y identified a new polymorphism in the promoter region of bet a ARK 1 gene ( ADRBK1 ) This T>C transition is located at position chr.11:66789808 ( 703 relative to ADRBK1 ) and only common in subjects with African Ancestry. Although, t his polymorphism is predicted to be in a transcription factor binding site, it does n ot influence beta ARK 1 expression levels in lymphoblastoid cell lines. T his is the first comprehensive study to assess whether genetic variations in ADRBK1 or the beta arrestin 1 ( ARRB1 ) contribute to the variability in blood pressure response in patients treated with beta blockers. In the Pharmacogenomic Evaluation of Antihypertensive Re ponses trial we could identify a common ARRB1 haplotype altering blood pressure response in blacks re ceiving atenolol. After adjustment for age, sex, body mass index and baseline diastolic blood pressure ( D BP) black patients with 1 or 2 copies of the ARRB1 CAT haplotype had a D BP reduction of 5.825.66 mmHg compared to a reduction of 2.086.82 mmHg in black patients with no copy of the ARRB1 CAT haplotype ( P = 0.0173 ). Additionally, rs1894111 in ADRBK1 was shown to influence blood pressure response in whites receiving hydrochlorothiazide. The
11 polymorphism is present in 1.3% of the white population. However, p atients who were G/A heterozygote had a greater DBP reduction ( 11.293.74 mmHg) compared to G/G homozygotes ( 4.264.79 mmHg, P = 0.0034). These findings held for false discovery rate adjustment. This is the first study to investigate whether genetic variations in ADRBK1 and ARRB1 have influence on death, myocardial infarction or stroke in treated hypertensive patients in the In ternational Ve rapamil SR /Trandolapril St udy (INVEST) genetic case cont rol substudy A signal was detected for two ARRB1 SNPs. The i ntronic SNP rs 542645 was associated with a 50.1% risk reduction (adjusted odds ratio 0.499, 95% confidence interval 0.288 0.867, P = 0.0136 ). In calcium channel blocker arm, rs17133921 showed a 1.7 fold risk increase of the primary outcome. However, for both clinical studies multiple testing has to be taken into account. Thus, given the borderline findings we have to temper our conclusion s suggesting the need for replicat ion
12 CHAPTER 1 INTRODUCTION AND BACKGROUND Hypertension Hypertension is the most prevalent chronic disorder in the United States and is defined as a persistent systolic blood pressure of greater than or equal to 140 mmHg or diastolic blood pressure of greater or equal than 90 mmHg, or blood pressure ( BP ) that is controlled to guideline recommended levels using antihypertensive medication. 1, 2 Hypertension has tremendous n egative economic and clinical impact on public health. Nearly one in three American adults has hypertension, putting 7 0 .6 million Americans at an increased risk of myocardial infarction stroke, heart and kidney failure 2, 3 In addition to the risk for the individual, the direct and indirect costs to the American health car e system are enormous ($ 73 4 billion, estimated for 2009 ). 2 Despite availability of numerous antihypertensive medications, overall BP control remains poor in hypertensive patients (34%, 1 999 2000). 1 Currently, blockers are commonly used agents for the treatment of hypertension. 1 blocker therapy varies widely among individuals. For example, i n a randomize d double blind study only 51% of the patients achieved adequate BP control with atenolol monotherapy. 4 Some of this variability results from differences in renin levels, race and pharmacokinetics. Genetic polymorphisms are an additional factor. b locker Pharmacogenetics Two non synonymous single nucleotide polymorphisms (SNPs) in gene o f the drug target, 1 adrenergic receptor gene ( ADRB1 ), have been extensively studied. 5 8 The first SNP (rs1805052) is a common A>G polymorphism at position (145) resulting in an amino acid change at codon 49 ( Serine>G lycine) in the N terminal region of the receptor. In an in vitro
13 study, t he G ( gl y cine Gly) variant showed an increased agonist promoted receptor downregulation compared to the A variant ( serine, Ser) 9 The second ADRB1 SNP (rs185053) is a common C>G SNP polymorphism (C1165G) resulting in an arginine (Arg) for Gly substitutio n at codon 389 (C terminus). In vitro the C ( Arg ) variant ha d shown a two fold higher basal receptor activity compared to the G ( Gly ) variant 10 A fter isoproterenol stimulation this diffe re nce was even greater (three to four times). 10 Pharmacogenetic associations with these two SNPs have been well established, but do not account for all genetic variability in the response to blocker therapy. F or example, in a study with 40 hypertensive patients who were treated with metoprolol, rs1805052 (partial R 2 = 0.046) and rs1805053 (partial R 2 = 0.158) were significant predictors of daytime diastolic blood pressure in a linear regression model 11 blocker 2 adrenergic receptor ( ADRB2 ), G GNAS ), G GNB3 ), angiotensinogen ( AGT ), or aldosterone synthase ( CYP11B2 ). However, results are inconclusive. For example, one retrospective study reported on the association of polymorphisms in GNB3 w ith blood pressure to atenolol treatment in hypertensive patients. 12 The same study di d not show an association with polymorphisms in the ADRB2 polymorphisms 12 Furthermore in 5895 coronary artery disease patients treated with atenolol or verapamil the event rates did not differ by ADRB2 rs1042713 or rs1042714 genotypes. 13 On the other hand, ADRB2 polymorphisms might play a role in the response to carvedilol in patients treated for heart failure. 14 Th 1 adrenergic receptor polymorphisms in hypertension and heart failure. In particular, patients homozygous for the C variant of rs185053 (C/C, Arg/Arg) showed a bette r response to blocker treatment. Hypertensive C/C
14 homozygotes had a greater blood pressure reduction, 11, 15, 16 C/C heart failure patients experienced a greater improvement in left ventricular end diastolic diamete r, 17, 18 or fewer adverse outcomes compared to G (Gly) carriers. 19 Recently a non synonymous SNP ( A>T, rs17098707) in the G protein coupled receptor kinase 5 ( GRK5 ) gene has been associated different survival of heart failure patients. 20 This SNP results in a n amino acid change at codon 41 ( glutamine > leucine ). The T (leucine, Leu) allele of adrenergic signaling gene is common in African Americans but not in Caucasians In this blocker treated patients with either GRK5 genotype had the same favorable heart failure outcome as did African Americans with one or two T alleles blockers arrestin 1 and polymorphisms in their genes, ADRBK1 and ARRB1 might also blocker therapy as both proteins are important in the regulation of the drug target. Func tions A rrestin 1 G protein coupled receptors represent one of the largest families of heptahelical proteins with approximately 1000 coding genes in the human genome. This family mediates a wide variety of biological processes. 21 Adrenergic receptors are prototypic of many members of this family and mediate the physiological effects of the hormone ep inephrine and the neurotransmitter norepinephrine. 1 2 adrenergic receptors are subtypes of the adrenergic receptors. When occupied by an agonist, both subtypes couple to the stimulatory G protein (Gs) ( Figure 1 1 ). 22 The Gs subunit activates adenylyl cyclase, which increases intracellular cyclic adenosine monophosphate (cAMP) and activates prote in kinase A ( Figure 1 1 : step 1). In the heart, th e phosphorylation leads ultimately to enhanced inotropy and chronotropy. However, this scenario is very complex and can be viewed as a network consisting of switches, amplifiers,
15 potentiometers, and atten uators in parallel and in series. Of particular relevance to this network are GRKs. 23 27 These kinases are known by several names: GRK 2 ( adrenergic receptor kinase 1 1), GRK 2), GRK 4 (IT11 ), GRK 5, GRK 6, and the two phototransduction kinases GRK 1 (rhodopsin kinase) and GRK 7 (cone opsin kinase). 1, was considered to be of agonist promoted desensitization. 21 1 consists of 689 amino acids (79668 Da) and phosphorylates agonist occupied receptors at specific serines or threonines ( Figure 1 1 : step 2). blocker therapy decreases 1 expression and activity. 28 31 arrestins, which inhibit sterically further G protein coupling ( Figure 1 1 : step 3). Four arrestins (arrestin 1 4) exist. Th e expression of arrestin 1 and 4 is restricted to the retinal rods and cones, whereas arrestin 2) are expressed ubiquitously. Two isoforms arrestin 1 arrestin 1A consists of 418 amino acids (47066 arrestin 1B is 8 amino acids shorter (410 amino acids). After receptor internalization ( Figure 1 1 : step 4), the receptor is dephosphorylated ( Figure 1 1 : step 5) and either recycled back to the membrane ( Figure 1 1 : step 6) or degraded ( F igure 1 1 : step 7). arrestin 1 within the cells. adrenergic signaling depends on GRKs and arrestins, arrestin 1. 32, 33 Expression and activit 1 have also been shown to be elevated in hypertension. 34 36 1 plays a role not only in agonist induced desensitization and down regulation, but also for the antagonist induced restoration. 28, 29 Thus, we hypothesiz 1 gene ( ADRBK1 ) and arrestin 1 gene ( ARRB1
16 arrestin 1, respectively. We further hypothesize that both genes are important determinants of clinica blocker therapy in patients with hypertension and of adverse cardiovascular outcomes in patients with hypertension and coronary artery disease (CAD). ADRBK1 and ARRB1 O rganization and V ariation ADRBK1 the gene for 1 is located on chro mosome 11q13.2. 37 It is approximately 21 kb in size with 21 exons ranging in size from 52 b ase p airs (bp) (exon 7) to over 1,200 bp (exon 21) 38 The exons are interrupted by 20 introns. Intron sizes range from 68 bp (intron 12) promoter region showed a GC box instead of a TATA box, absent or nonstandard positioned CAAT box and a high GC content (>80%) all 38 However, signals that underlie changes in 1 mRNA expression in different tissues and under pathological and physiological situations have only recently begun to be investigated. 26 Mitogenic stimulation of T cells, for 1 mRNA expression and a study mea suring mRNA levels in failing human hearts showed a threefold increase. 39, 40 Variations in ADRBK1 exist. The ( NCBI ) dbSNP database reports 42 SNPs, the Ensembl project lists 52 SNPs in the ge ne region. 41, 42 However, most of these SNPs have not been validated which means they could present sequencing error s ra ther than actual SNPs allele frequencies for only 16 intronic SNPs, one synonymous SNP and one SNP in the UTR). 41 For the International HapMap project (HAPMAP), 19 SNPs were geno 43 Fifteen SNPs wer e located in introns, two promoter region one UTR and on e further downstream Most of these SNPs are not common in humans The Pharmacogenetics and Pharmacogenomics Knowledge Base (PharmGKB) reports allele
17 frequencies for 13 SNPs. 44 However, for some SNPs, the study population is not dive rse and sample size is very low (e.g. rs 11227756 eight blacks ). In addition, the existence of one non synonymous SNP (Gly>valine, exon 8 rs1009943 ) is question able as databases list it as monogenic ( e.g. P database ) ARRB1 is also located on chromosome 11 about 7.8 Mb downstream from ADRBK1 The gene is about 86 kb in size. Isoform 1A has 16 exons. 45 Isoform B is created by alternative splicing and has 15 exons. Southern blot analysis in untreated human smooth muscles cells showed that the mRNA ratio 1A/1B is approximately 1:5. 45 The levels of both isoforms were increased after stimulation with forskolin However, the ratio changed to 1:2 suggesting a preferre ntial arrestin 1A. ARRB1 Genetic variation is predominantly found in intronic regions of the gene. The two exonic SNPs are synonymous. HAPMAP lists 112 SNPs. In the African ancestral population (YRI: samples from Yoruba in Ibadan, Nigeria), 70 SNPs have a minor allele frequency (MAF) of greater than 0.0 5. Seventy six SNPs are common (MAF>0.05) in the European population (CEU: samples from Utah residents with ancestry from northern and western Europe). In a recent family based study, an ARRB1 haplotype was associated with nicotine dependence (heaviness of smoking, Fagerstrom t est score ) in European Americans. 46 Summary and Significance adrenergic signaling. However, the role of genetic variation in the two gen es ( ADRBK1 and ARRB1 ) in antihypertensive therapy and adverse cardiovascular outcomes is unknown. Our study is significant from a number of perspectives. First, we identify new and verify known polymorphisms in ADRBK1 This approach help s in characteriz ing the structures in ADRBK1 and identifying the most appropriate
18 set of SNPs to be used in future genetic association studies. Second, the research includes ARK arr estin 1 in healthy individuals and lymphoblastoid cell lines. Third, this is the first comprehensive study to assess whether genetic variations of ADRBK1 or ARRB1 contribute to blockers This is also the first study to investigate whether genetic variations in ADRBK1 and ARRB1 have influence on death, myocardial infarction or stroke in treated hypertensive patients. Finally, and of broad consequence, definition of ADRBK1 and ARRB1 genet ic variation, functional consequence of such variation and clinical implications of ADRBK1 and ARRB1 polymorphisms lays groundwork for a greater understanding of the role of these key enzymes in adrenergic receptor G protein adenylyl cylase pathway a nd their contribution to a variety of diseases and drug responses.
19 Figure 1 1 adrenergic signaling couple to the stimulatory G subunit activates adenylyl cyclase (AC), which increases intracellular cyclic adenosine monophosphate (cAMP) 1 phosphorylates the agonist occupied receptors at specific serines or threonines. After phosphorylation, the receptor binds arrestins, which inhibit sterically further G protein coupling (step2, step 3). After recept or internalization ( step 4), the receptor i s dephosphorylated ( step 5) and either recycled ba ck to the membrane ( s tep 6) or degraded ( step 7).
20 CHAPTER 2 MATERIALS AND METHODS Resequencing of ADRBK1 R egions Samples Genomic DNA from 24 whites and 24 blacks were sequenced ( N= 48 Table A 1 ). All samples are commercially available and were obtained from the Coriell Institute for Medical Research Human Variation Collec tions of the NIGMS Repository (Coriell Institute for Medical Research, Camden, NJ USA) The samples were stored at 20C Polymerase Ch ain R eac tion (PCR) Primer D esign and O ptimization ADRBK1 r eference sequence s were downloaded from database, the Ensembl project and the University of California, Santa Cruz (UCSC) Genome Browser. 42, 47, 48 Sequences were compared using ClustalW software to ensu re concordance. 49 Oligo Primer Analysis Software ( Version 6 .71 Molecular Biology Insights, Cascade, CO USA ) was used to design polymerase cha in reaction (PCR) oligonucleotides ( primers ) Primer pairs ( forward and reverse primer) were design ed to generate overlapping amplicons with maximum possible length for 454 sequencing (up to 20 kb) or 400 600 bp for Sanger sequencing. Primers were synthesized by Eurofins MWG Operon (Huntsville, AL USA ) Specific polymerase kits were used to optimally amplify GC rich regions ( HotStarTaq, Qiagen, Valencia, CA USA ) or regions greater than 2 .5 kb (LA PCR Kit Ver.2.1, T akara Bio, Shiga, Japan) The HotStarTaq PCR reaction mix (15 included 20 ng genomic DNA, water, Solution (Qiagen) and 2 primers (10 This PCR was performed under the following conditions: 95 C for 15 min; 40 cycles consisting of denaturation at 95 C for 35 sec, annealing at 55 72 C for 30 sec and extension at 72 C for 45 sec; and final extension for 7 min. The LA PCR mix (25
21 included 20 ng genomic DNA, 15.45 10X LaPCR Buffer II ( T akara Bio) deoxynucleotides ( dNTPs ) primers (10 and DNA polymerase (Takara Bio). The LA PCR was performed under the following conditions: 9 4 C for 3 min; 9 cycles consisting of denaturation at 9 4 C for 12 sec, annealing at 55 72 C for 30 sec and extension at 68 C for 1 min per 1000 bp, and an additional 27 cycles consisting of denaturation at 94 C for 12 sec, annealing at 55 72 C for 30 sec and extension at 68 C for 1 min per 1000 bp (with an increase of 1 5 sec per cycle) ; and final extension for 7 min. Primer sequences, amplicon sizes, and annea ling temperatures are shown in T able A 2 Accurate PCR amplicon size w as visually identified by 1% agarose gel electrophoresis Agarose was dissolved in 1x TAE buffer by boiling. After cooling to approximately 55 C 0.3 ng/mL ethidiumbromide was added The polymerized gel s w ere covered with 1x TAE buffer and the wells were loaded with a mixture of 3 1x loading dye ( Agarose Gel Loading D ye, 6X Fisher BioReagents Pittsburgh, PA USA ) In addition, appropriate size markers were loaded ( e.g. Logic DNA Marker, Lamda Biotech, St. Louis, MO USA ) G el electrophoresis was carried out at 100 V. After the run PCR bands were visualized under UV light and documented with a camera. Resequencing U sing 454 T echnology 454 Life Sciences has miniaturized the three enzyme system of pyrosequencing, enabling more than hundreds of thousands sequencing reactions to be performed on a single chip. This technology is 100 times faster than the conventional capillary based sequencing and is able to deliver 20 30 million bases (20 30 Mb) of high quality DNA sequence. 50 To use this technology cost effectively, w e chose to sequence a total of approximately 341kb in ADRBK1 ARRB1 A TP2A2 and RYR2 Five a mplicons were designed to cover the entire ADRBK1 region. These amplicons were p ooled equimolarly with amplicons from the
22 other genes Here, PCR products were purified using the MinElute 96 UF PCR Purification kit ( Qiagen ). This k it can be used for amplicons greater than 100 bp and separates PCR reaction components (e.g. primers) from amplicons using an ultrafiltation membrane. Conc entrations were then determined using PicoGreen DNA Quantification ( see The effect of ADRBK1 and ARRB1 polymorphisms on the clinical response to antihypertensive therapy, Genotyping, D NA isolation and, normalization) Molar concentrations were calculated for each amplicon b ase d on the amplicon size in bp and a n average molecular weight for double str anded DNA of 656. 6 g/mol per bp. The amplicons were then pooled equimolarly resulting in a pool of and per sample At the University of Florida Interdisciplinary Center for Biotechnology Research (UF ICBR), t he amplicon poo l s were fragmented by nebuliz ation, which shears doublestranded DNA into fragments ranging from 300 to 800 b p ends. The ends were made blunt by T4 DNA polymerase and 5 ends were phosphorylated using the T4 polynucleotide kinase Adaptor s (A and B) were ligated to the DNA fragments. The adaptors support amplification and the nucleotide sequencing reaction. Ada ptor B is biotinylated allowing the immobilization of the DNA fragments via streptavidin coated beads As the adaptors are not phosphorylated, a s trand displacing DNA polymerase was used to fill in gaps that are present at the 3 DNA adaptor junctions The isolation of single stranded DNA sequencing templates is carried out using sodium hydroxide and acetic acid solutions. This procedure generates a so called library consisting of a single stranded template DNA molecules flanked with a daptor A at the 5 end and a daptor B at the 3 end. These libraries are the starting
23 material for the emulsion based clonal amplification reaction was assessed using the Agilent 2100 BioAnalyzer ( Quantum Analytics, Foster City, CA, U SA) The libraries were annealed to DNA capturing beads. Amplification was carried out in an oil in water emulsion used as a microreactor and resulted in approximately 10 million clonal copys on each bead. The emulsion was broken and DNA positive beads (a mplified DNA beads contain a biotinylated primer ) were enriched using streptavidin coated magnetic enrichment beads. As a result the DNA is bound to the DNA capture bead (biotin/avidin) and covalently bound to the original bead. The covalent bond was cle aved, the sequencing primers were annealed and picotiter plates were loaded The principle of 454 sequencing reaction is pyrosequencing, a sequencing by synthesis method. 51 The pyrosequencing enzyme mix consists of a DNA polymerase and the follo wing three enzymes: (1) s ulfurylase t o catalyze the reaction between pyro phosphate and adenylylsulfate (APS) to a denosine 5' triphosphate and su lfate (2) luciferace to turn luciferin and ATP in luciferin adenylate and pyr ophosphate and to turn luciferi n adenylate and oxygen in oxyluciferin, a denosine 5' mono phosphate and light, (3) apyrase to hydrolyze unincorporated dNTPs. During the 454 sequencing reaction, dNTPs were repeatedly added in a certain pattern (T A C G) and photons generated from in each picotiter well were captured by a camera after each cycle. The signal strength is proportional to the number of incorporated nucleotides and the w ere translated base calls and sequence data were compared with reference sequences for the ADRBK1 Resequencing U sing Sanger S equencing Sequencing was done in one direction (forward) and in the other direction (reverse) if the first run yielded a novel polymorphism. Se quencing reactions were carried out at the UF ICBR
24 using a 3730 DNA Analyzer (Applied Biosystems, Foster City, CA USA ) Seven amplicons were designed to cover 2 kb in the ADRBK1 promoter region and 1.5kb downstream including the 3 UTR. Using methods similar to those previously described, a n additional four amplicons were designed to confirm SNPs that were previously reported (Table A 3) Th e 3730 DNA Analyzer s ystem is based on dye termination sequencing, a modified Sanger method, and is the gold stan dard in medium to high throughput DNA analysis. Here, each of the four dideoxynucleotide chain terminators is labelled with a different fluorescent dye, each fluorescing at a different wavelength. The reaction was carried out on a 96 well plate format ( t wo amplicons, 48 samples). The reacti on total reaction volume was 20 containing 8 Terminator ready reaction mix (Applied Biosystems ) 4 (for ward for forward sequencing), 7 GeneAmp PCR System 9700 was used to heat the mix at 95 C for 5 min followed by 50 cycles of 95 C for 30 sec, followed by 50 55 C for 10 sec and 60 C for 4 min. The plates were centrifuged at 2000 g for 1 min followed by an electrokinetic injection. After capillary electrophore sis, the data output is a fluorescent peak trace chromatogram. The chromatogram was analyzed using software programs (e.g. Sequencer 4.7, Gene Codes Corporation, Ann Arbor, MI USA ). Genotyping of R eported ADRBK1 Single Nucleotide P olymorphisms ( SNPs ) F ive pyrosequencing assays were designed to confirm f ive common ADRBK1 SNPs ( Table A 4 ). The pyrosequencing method is generally described in Chapter 2: Resequencing of ADRBK1 Regions Resequencing using 454 technology : We used the standard manufacturer p rotocol (Biotage AB, Uppsala, Sweden). Here, 3 8 ere immobilized on streptavidin coated Sepharose beads. After incubation, beads were isolated by hand held vacuum probe, treated with 700 mL/L ethanol, denaturation buffer, wash buffer and finally released into a mixture of annealing buffer containing 10 pmol of sequencing p rimer.
25 This solution was heated at 80C for 2.5 min and cooled to room temperature. Pyrosequencing reaction was performed for sequence determination a nd allele designation in a Biotage PSQ HS 96 System and d ata were captured with PSQ HS 96 SNP software. Determination of Linkage Disequilibrium Structure in ADRBK1 and ARRB1 Structural A nalysis of ADRBK1 Structural analysis of ADRBK1 was done separately by race. Information (identifier, chromosomal location, and genotype data) on new ly identified and confirmed SNPs w ere used for the analysis The analysis and visualization of linkage disequilbrium ( LD ) was performed using Haploview 4.1. 52 Each SNP was tested for Hardy Weinberg equilibrium (HWE) in each race Only SNPs with MAF > 0.05 were included, with the minimal acceptable pairwise correlation coefficient r 2 of 0.8. Both D and r 2 w ere computed for pairwise LD evaluation. Haplotype blocks wer 53 Here, the algorithm creates 95% confidence bounds on D prime and each comparison is called "strong LD". A block is created if 95% of informative comparisons are "strong LD". The algorithm sorts the list of a ll possible blocks by starting with the largest blocks. Blocks are added as long as they do not overlap with an already declared block. Pairwise tagging SNPs were computed using MAF > 0.05 and r 2 of 0.8. Structural A nalysis of A RRB 1 As described above, genetic variation of ARRB1 has been documented in several public domain databases. However, HAPMAP data were used for the analysis as this high quality dataset has genotype data available The analysis was done separately in YRI and CEU populations Ge notype data files in these populations were downloaded from HAPMAP The region covered chromosome 11 position 74654130 to 74740521 a region adding 2 kb upstream and downstream of ARRB1 SNPs with
26 a MAF > 0.05 were selected for constructing haplotypes in their respective populations. To assess the most informative set of SNPs, two haplotype tagging strategies were pursued Although the employed algorithms differ between software programs we assume their result s to be comparable One used PHASE and Best Enumeration SNP Tags ( BES T ) the other Haploview and Tagger. In t h e PHASE/BEST analysis, PHASE (version 2.1 ) was used to reconstruct haplotypes from YRI or CEU population genotype data 54 The most efficient set of SNPs to tag these haploty pes was determined using BEST software. 55 In the Haploview/Tagger approach, Haploview was used as described above. In Tagger, the aggressive tagging function was used. This function uses 2 and 3 marker haplotypes to generate the most efficient set of tagging SNPs. In addition to the haplotype tagging approaches, we used a pairwise tagging SNP approach. The minimal acceptable r 2 was 0.8 and only SNPs with MAF > 0.05 were included. MultiPop Ta gSelect a lgorithm was used to generate a tagging SNP list that most effectively captures ARRB1 SNPs in CEU and YRI. 56 As previously described, ADRBK1 and A RR B1 are located approximately 7.8 Mb apart on the same chromosome. S trong LD can occur over larger distances 57 Thus, we also determined the LD structure between the two genes in YRI and CEU populations. ADRBK1 and ARRB1 E xpressi on in Healthy V olunteers Study P opulation Healthy men and women aged 18 years or older were eligible for study participation. There was no exclusion based on race, sex, or ethnicity. The subjects could not have any medical problems or take any prescription drugs. Other exclusion criteria include d active infection or history of recurrent infection, BP greater than 140/90 mmHg, body mass index (BMI) greater than 30 kg/m 2 smoking, and illicit drug or alcohol abuse. To recruit potential
27 subjects, an institutional review board ( IRB ) approved advertisement was placed throughout the campus of the University of Florida and around the Gainesville area, or handed out in person. Potential subjects contact ed the investigators via the contact numbers provided in the IRB approved advertisement (printed or email) and w ere scheduled to come to our clinical research lab in the Health Science Center (medication use, smoking status, and use of alcohol etc.) and height, weigh t, hip and waist circumference were obtained. BP and heart rate were measured using an automatic blood pressure monitor (Om ron, Bannockburn, IL USA ). Venipuncture was done by a trained phlebotomist. A total of 30mL blood was collected. Here we used the PAXgene Blood RNA System tubes ( BD/Qiagen) for RNA collection and two 10mL V acutainer tubes ( Becton, Dickinson and Company (BD), Franklin Lakes, NJ USA ) containing EDTA as the anticoagulant DNA Isolation, N ormalization, and G enotyping Genomic DNA was isolated from 3 mL whole blood using the FlexiGene DNA kit (Qiagen) Briefly 7.5 mL l ysis buffer were added to the sample followed by centrifugation (2000 g ). The pellet was resuspended in 1.5 mL 1% protease buffer solution (Qiagen) denaturation and incubated at 65 C f or 10 min. D NA was precipitated by addition of 1.5 mL isopropanol. After centrifugation at 2000 g the pellet was washed in 1.5 mL 70% ethanol The pellet was dried for 15 min and resuspended overnight in hydration buffer (10 mM Tris.Cl, pH 8.5). DNA c oncentrations were determined in duplicates using the NanoDrop 1000 Spectrophotometer (Thermo Scientific, Wilmington, DE). DNA was normalized to 20 ng/ Pyrosequencing was used to genotype the healthy volunteer population for ADRBK1 SNPs that showed an association with BP response, heart rate response or cardiovascular outcomes in
28 our clinical studies. The pyrosequencing genotyping method is described above Table A 4 shows the forward, reverse and sequencing primers for the respective SNPs. RNA Isolation, Reverse T r anscription, and R eal time PCR The PAXgene Blood RNA System tube kit (Qiagen) was used for RNA isolation. After the blood draw, PAXgene Blood RNA System tubes were stored at room temperature for 1 h and frozen at 20 C until assayed. After storage tubes were stored for at least 2 h at room temperature to ensure complete lysis of blood cells. The PAXgene Blood RNA Tube s were centrifuged for 10 min at 4000 g The supernatant was removed and the pellet resuspended in 4 m L RNAse free water. Centrifugation and removal of the supernatant was repeated. Resuspension buffer (350 ) was added to the pellet. The solution was incubated with 300 b uffer and 40 proteinase k at 55 C for 10 min. After protein digestion, the lysate was homogenized with centrifugation using a PAXgene Shredder spin column (Qiagen). The supernatant was transferred in a microcentrifuge tube and 350 of 95% ethanol were added. The mixture was transferred to a PAXgene RNA spin column (Qiagen), washed and incubated with DNAse I for 15 min to remove DNA. After the wash steps, RNA was eluted in hydration buffer. RNA concentrations were determined immediately in duplicate s amples using the NanoDrop 1000 Spectropho tometer. RNA was stored at 20 C until assayed. RNA was converted into complementary DNA (cDNA) using the High Capacity cDNA Reverse Transcription Kit (Applied Biosystems). The reverse transcription (RT) mix (100 ) included 10 RT buffer, 4 dNTPs mix (100 nM), 10 RT random primers, 5 MultiScribe Reverse Transcriptase (Applied Biosystems) 21 nuclease free water and 50 RNA/ nuclease free water mix (containing 500 ng of RNA). RT was performed in a thermal cycler using the following conditions: incubation at 25 C for10 min, incubation at 37 C for 120 min, and incubation at 85 C for 5 min.
29 Real time PCR was carried out using the 7300 Real Time PCR system (Applied Biosystems). E xon specific oligonucleotide probes (fluorescently labe led) for ADRBK1 ( Hs00176395_m1 ), ARRB1 ( Hs00930523_mH ), and GAPDH ( endogenous control) were used and each sample was analyzed in duplicate for each probe. The real time reaction mix (50 ) consisted of 25 TaqMan Gene Expression Master Mix (Applied Bio systems), 17.5 water, 2.5 oligonucleotide probe and 5 of cDNA template. Real time PCR was carried out using the following conditions: incubation at 50 C for 2 min, initial denaturation at 95 C for 10 min and 40 cycles of denaturation at 95 C for 10 sec and annealing at 60 C for 1 min. Data A nalysis The 7300 Real Time PCR system monitors the fluorescence emitted during the reaction as an indicator of amplicon production at each PCR cycle in real time. Graphs were generated f or each probe in e ach sample The graphs have three phases: no detectable fluorescence, exponential phase, and plateau phase. The cycle at which a significant increase in fluorescence signal is first detected is called the threshold cycle (C T ). The C T correlates to the i nitial amount of target template For the analysis the relative quantification (RQ) method was used. The probes for ADRBK1 and ARRB1 were used as target probes. GAPDH was used as the endogenous control. Delta C T values for each sample equals average ta rget C T minus the average endogenous control C T One sample was randomly chosen as the internal calibrator and expression is expressed relative to this individual. The calibrator has an expression of 1. Normalized cycle change between sample and calibr ator or d elta delta C T values were calculated by the following formula: delta C T (sample X) minus delta C T (calibrator). RQ values express the fold change: RQ = 2 (delta delta CT values ) RQ values were compared by sex and race. RQ values for each sex or racial group w ere compared using Kurskal Wallis test Statis ti cal analysis was
30 done using Statistical Analysis System (SAS Version 9.1, SAS Institute, Cary, NC USA ) and P <0.05 was considered statically significant. ADRBK1 E xpression in Lymphoblastoid C ell L ines Samples Forty five African American samples were obtained from the Coriell Institute for Medical Research Human Variation Collections of the NIGMS Repository The genomics samples were obtained by the UF Center for Pharmacogenomics, the lympho blastoid cell lines of the same sample were obtained by Mayo Clinic College of Medicine Genotyping Genotyping was performed at the UF Center for Pharmacogenomics using pyrosequencing as described above (Resequencing of ADRBK1 Regions Genotyping of reported ADRBK1 SNPs ). Genotyping was performed with ADRBK1 SNPs that were associated with BP response, heart rate response or cardiovascular outcomes in the clinical studies. ADRBK1 E xpression ADRBK1 expression analysis was performed at Mayo Clinic College of Medicine (Rochester, MN USA ) Total RNA was extracted from untreated lymphoblastoid cell lines corresponding to the DNA samples and analyzed using the Affymetrix U133 Plus 2.0 GeneChips (Affymetrix Santa Clara, CA USA ). 58 The Affymetrix U133 Pro2 probe set ( 201401_s _at) for ADRBK1 was used. Data A nalysis As previously described expression data had been log transformed 58 Therefore, d ifferences in ADRBK1 expression by genotype group (homozygote common allele vs. minor allele carrier) were examined using test. Statis ti cal analysis was done using SAS Version 9.1 and P <0.05 was considered sta t i sti cally significant.
31 The E ffect of ADRBK1 and ARRB1 Polymorphisms on the Clinical R esponse to Antihypertensive T herapy Pharmacogenomic Evaluation of Antihypertensive Responses (PEAR ) Study P opulation A general overview of the Pharmacogenomic Evaluation of Antihypertensive Responses (PEAR) has been previously described. 59 Briefly, recruitment of this study began in 2006 and includes enrollment of subjects at the University of Florida, the Mayo Clinic (Rochester, MN USA ) and Emory University (Atlanta, GA USA ). The anticipated study sample is 800 males or females with mild to moderate essential hypertension, of any race or ethnicity, between the ages of 17 and 65. Subjects are randomize d to either hydrochlorthiazide or atenolol. BP data are collected using home and ambulatory BP (HBP, ABP) monitors at baseline, the e nd of monotherapy and the end of combination therapy. A total of 418 samples were analyzed for this project and the end of monotherapy was used as a study endpoint Genotyping S NP s for investigation in clinical studies Eighteen ADRBK1 and 60 ARRB1 SNPs we re selected. Eight of the 14 confirmed ADRBK1 SNPs are present on Illumina HumanCVD Genotyping BeadChip (Illumina, San Diego, CA USA ) that was developed by the Institute of Translational Medicine and Therapeutics (ITMAT, Philadelphia, PA, USA), the Broad Institute (Cambridge, MA, USA), and Candidate gene Association Resource (CARE) Consortium (supported by National Heart Lung and Blood Institute) 60 More information about the ITMAT/Broad/CARE (IBC) chip is described under IBC chip genotyping. This IBC chip lists an additional four ADRB K1 SNPs Two SNPs ( rs12283002 rs12791853 ) are located more than 2 kb upstream fr om the starting position and were not included in the resequencing approach The HAPMAP project reports low minor allele frequencies for the other two SNPs ( rs3730140 : MAF< 1%, rs 4930416 : MAF<5%,
32 blacks only) These SNPs were also included in the analysis. The IBC chip does not include ARRB1 SNPs. Therefore, a custom SNP array (olgio pool all, OPA) was designed u sing the Illumina Assay Design Tool (ADT) The OPA also con tained an additional eight ADRBK1 SNPs The rs numbers or flanking sequences of total of 68 SNPs were uploaded in one file to As the OPA is designed for exactly 96 SNPs, additional SNPs from the following genes were uploaded: SLC2A2 S LC2A5 SLC2A9 and KHK Here, the ADT algorithm added MAF and validation s tatus (e.g. SNP validated by the HAPMAP project). In addition, a SNP design score and design r ank were added and the file returned. The design rank can have three values (0, 0.5, and 1) and are based on the design score (0 1). SNPs with design rank s of 0 ha ve low success rate and are high risk for the entire OPA. These SNPs were excluded. SNPs with moderate (design rank =0.5) and high (design rank=1) success rate were included. If SNPs were lower or equal to 60 nucleotides away from one another the SNP with the lower design score was excluded. After SNPs failed the ADT analysis, the structural analysis for ADRBK1 and ARRB1 was repeated to replace these SNPs with SNPs from the same bin. The ADT analysis was repeated until no failure codes were reported and all uploaded SNPs had a design rank of greater or equal to 0.5. TaqMan assays were designed for two SNP that could not be replaced. These SNPs had to be in a putative functional region of the gene or have a MAF >0.1 DNA isolation quantification, and normalization DNA isolation has been described above. Concentrations were determined using PicoGreen DNA Quantification. Quant iT Pic oGreen dsDNA reagent (Invitrogen, Carlsbad, CA USA ) is a fluorescent dye It is also a nucleic acid stain that is ultra sensitive for double stranded DNA. Therefore, 5 DNA was diluted with 95 of water and 2 was used for the
33 measurement Each s ample was measured in triplicate. A serial dilution of Lambda DNA standard (Invitrogen) was used for absolute quantification. The serial dilution had the following concentrations: 75 ng/ 50 ng/ 25 ng/ 12.5 ng/ 6.25 ng/ 3.12 ng/ 1.56 ng/ 0 ng/ The serial dilution was measured in triplicate. The assay was performed on a 384 well plate using the Synergy HT Multi Mode Microplate Reader ( BioTek Winooski VT USA ) DNA was normalized to 50 ng/ for the IBC chip and OPA genotyping. A DNA concentration of 20 ng/ was used for TaqMan genotyping. TaqMan genotyping TaqMan allelic discrimination uses two probes, one fluorescently labeled oligonucleotide probe for each allele in a two allele system. In addition to the fluorescent reporte r dye at the 5 end, each probe is labeled with a 3 quencher dye that suppresses the reporter fluorescence primarily by Foerster type energy transfer 61 During PCR the probes hybridize to allele specific sequences 3 exonuclease activity and an increase in fluorescence signal is emitted Here, the probes for ADRBK1 rs10896164 and ARRB 1 rs12274033 were used. The PCR reaction mix (5 ) contained 2.5 TaqMan Genotyping Master Mix (Applied Biosystems), 0.0625 probe, 1.438 water, and 1 normalized genomic DNA. PCR was performed in a thermal cycler using the following conditions : initial steps for 50 C for 2 min and 95 C for 10 min (denaturation) followed by 40 cycles of 95 C for 15 sec (denaturation) and 58 C for 1 min (annealing). The products were analyzed using the 7900HT Fast Real Time PCR system (Applied Biosystems). Illumina h uman cardiovascular disease genotyping bead c hip cardiovascular disease ( CVD ) genotyping bead chip ( IBC chip ) contains 49,094 markers in approximately 2100 genes. A total of 12 samples can be analyzed
34 simultaneously. The target regions were chosen based on their previous association with a range of CV, metabolic, and inflammatory syndromes. Four hundred thirty five genes showed previous associ ations, 1,349 loci are potentially involved in CV or other related phenotyp es and an additional 232 larger genes were picked by CVD consortium Additionally, t he IBC chip contains 15 00 ancestry informative markers (African vs. European) Analysis of these SNPs was Infinium II c hemistry The basic concept is based on direct hybridization of whole genome amplified (WGA) genomic DNA to a bead array of locus specific primers. 62, 63 Normalized DNA (50 ng/ ) was prepared at the Center for Pharmacogenomics as described above and transferred t o the UF ICBR. Here, DNA underwent whole genome amplification, fragmentation, precipitation, resuspension, hybridization on the IBC chip, and extension chip was scanned using the BeadArray Reader (Illumina). Resulting image files were transferred to the Center for Pharmacogenomics Image analysis was performed using Beadstudio Genotyping Analysis Module 3.3.7 (Illumina). The SNPs were clustered using a Gen Call Threshold of 0.15. Contaminated samples were excluded using the Genome Viewer function in Beadstudio. Parent parent child error rates were determined using a mother father child trio (Coriell samples). The trio was excluded from further analysis. GenTrainScore were estima ted for each SNP. The GenTrainScore is dependent on angel, dispersion, overlap, and intensity of the genotype clusters SNPs with poor clustering scores ( GenTrainScore <0.3 ) were removed. Samples with call rates<0.95 were removed followed by removal of s amples that had sex gender estimate mismatches. Monomorphic SNPs were excluded and autosomal SNPs with a missing rate>0.1 were removed. HWE was estimated for all autosomal SNPs. The HWE analysis was stratified
35 by race (black or white subjects only) and SNPs with a HWE P value of lower than 10 5 were flagged. Final genotyping report files were created and imported into SAS JMP genomics 3.2 (SAS Institute, Cary, NC USA ) C ustom SNP array C ustom OPA design and DNA normalization to 50ng/ are described above. SNP precipitation of single stranded DNA) the OPA is hybridized to DNA. The OPA contains 3 primers for each of the 96 SNPs. Two primers are allele specific, one primer is locus specific. After extension and ligation, PCR is performed using universal fluorescently labeled primers and uracil DNA glycosylase (UDG) Cy3 and Cy5 w ere used as fluorescent dyes and UDG was used to prevent uracil contamination of the PCR product. PCR was carried out in thermal cycler using the following conditions: 37 C for 10 min (UDG activation), 95 C for 3 min (initial denaturation), and 34 cycl es of denaturation at 95 C for 35 sec, annealing at 56 C for 35 sec, and extension at 72 C for 2 min, followed by final extension at 72 C for 10 min. After washing t he PCR product was hy bridized onto VeraCode beads (Illumina). The VeraCode bead plate was scanned using the BeadXpress Station (Illumina). Resulting intensity files were analyzed using Beadstudio Genotyping Analysis Module 3.3.7 (Illumina). The SNPs were clustered using a Gen Call Threshold of 0.25. Parent parent child error rates w ere determined using a mother father child trio (Coriell samples). The trio was excluded from further analysis. SNPs with poor clustering scores ( GenTrainScore <0.3 ) were removed. Samples with call rates<0.90 were removed. Monomorphic SNPs were exclude d and autosomal SNPs with a missing rate>0.1 were removed. HWE was estimated for all autosomal SNPs. The HWE analysis was stratified by race (black or white subjects only) and
36 SNPs with a HWE P value of lower than 10 2 were flagged. Final genotyping re port files were created and imported into SAS JMP genomics 3.2 (SAS Institute) Data A nalysis Data w ere analyzed using SAS JMP genomics 3.2 ( SAS Institute ) Data were stratified a priori by race (blacks or whites) and treatment arm ( hydrochlorothiazide or atenolol) The stratification was done for the following reasons: First, most SNPs in ADRBK1 are only common in blacks and blacks in PEAR responded poorly to atenolol monotherapy (unpublished data). This race trait association biases a SNP trait ass ociation Therefore, stratification by race is needed. Second, both genes are involved in adrenergic signaling. Thus, we expect to see opposite effects in the treatment arms ( hydrochlorothiazide : adrenergic signaling reflex activation; atenolol: a drenergic blockade). As t hese effects cancel each other out we would not be able to detect them if we would analyze the entire cohort without stratification by drug For the SNP trait association multiple models were used First, t he difference (delta) b etween baseline and end of mono therapy w as determined. Genotypes were compared for the delta in home systolic blood pressure (SBP), home diastolic blood pressure ( DBP), or home heart rate (HR) using unadjusted analysis of varia n ce (ANOVA) and linear regre ssion models. In the ANOVA the three possible genotypes (homozygote common allele, heterozygote, and homozygote minor allele) are treated as three categories (nominal), whereas the linear regression (LR) model uses ordinal data. Th ese procedure s yield P values for genotype (ANOVA) and P values for trend (LR). In addition, we performed models wi th age, sex, BMI, and baseline SBP, DBP or HR, respectively, as fixed effects. Haplotypes were constructed in each race with SNPs that were identified to alter BP response using PHASE (version 2.1 ) B lood pressure response to monotherapy was compared in
37 patients with 1 or 2 copies and patients with 0 copies of the haplotype of interest using the same adjusted models that were used for the individual SNP analysis. In PEAR, we tested the effect of multiple SNPs (N=7 3 before quality control procedure) in two genes on BP response simultaneously. As so many tests are being conducted, care must be taken to avoid type I errors due to multiplicity. Traditional approaches include strong control of family wise error rates using techniques such as the Bonferroni adjustment 64 The Bonferroni adjustment corrects for the family wise error rate by testing each of n individual hypotheses at a statistical significance level of 1/n times what it would be if only one hypothesis were tested However, in most cases this adjustment is too stringent. 64 The Benjamini and Hochberg false discovery rate method ( FDR ) provides an alternative quantification of error under multiplicity of comparisons. 65 At an FDR of 0.05, we expect that 5% of the SNPs that were declared significant are false positives, on average. ARRB1 has more SNPs than ADRBK1 but the functional importance is not dependent on the number of SNPs in a gene Thus, we decided to adjust P value s separately by gene. FDR was performed using SAS Version 9.1 The E ffect of ADRBK1 and ARRB1 P olymorphisms on Adverse Cardiovascular Outcomes in Patients with H ypertens ion and Coronary A rtery D isease I n ternational V e rapamil SR /Trandolapril St udy ( INVEST ) Study P opulation Our laboratory has 5,979 genomic DNA samples that were collected from participants of the I n ternational V e rapamil SR /Trandolapril St udy ( INVEST ) to test various pharmacogenetic hypotheses. INVEST was a randomized, open label, blinded end point study of 2 2,576 hypertensive CAD patients aged 50 year or older. INVEST was conducted between September 1997 and February 2003 at 862 sites in 14 countries. Detailed patient characteristics and design h ave been published previously. 66 The primary study outcome was the first occurrence of death (all cause), nonfatal MI or nonfatal stroke. To achieve Joint National Committee on Prevention,
38 Detection, Evaluation, and Treatment of High Blood Pressure ( JNC ) VI BP goal, patients were random ized to one of two multi drug hypertension treatment strategies, a calcium antagonist blocker (atenolol) strategy with addition of hydrochlorothiazide or trandolopril allowed in either arm of the study. Between June 2001 and February 20 03, consent for pharmacogenomic studies was obtained and genetic samples were collected for 5,979 subjects from 184 sites in the Unites States and Puerto Rico. The INVEST GENEtic Substudy ( INVEST GENES ) population is relatively similar to the entire INVE ST but is unique in comparison to most existing genetic cohorts in that it contains a diverse population including a high percentage of Hispanics. From this genetic database, numerous investigations are ongoing. These include the analysis of the influence of genotype on adverse outcomes (e.g. death, myocardial infarction stroke). We selected a cohort of 894 individuals to create a nested case control cohort design. Genotyping SNP selection, DNA isolation and normalization, use of several genotyping platforms has been described above. We used the same set SNPs and the same platforms for the INVEST GENES case control cohort as described for the PEAR study. Data A nalysis Data were analyzed using SAS JMP genomics 3.2 (SAS Insti tute ) The case control cohort was analyzed for allele risk estimates of primary study outcome (first occu rrence of death from all 2 tests. In addition, d ata were stratified a priori by treatment strategy ( ve rapamil or atenolol) to test the effect in different treatment arms. The effect of each allele (common allele homozyote vs. minor allele carrier) wa s tested in an unadjusted model. We then tested the effect of each genotype in logistic regression models controlling for the following covariates: age, sex, race/ethnicity, p revious MI, prior heart failure.
39 These five covariates were significant predictors of adverse outcomes in INVEST. 66 The models were also adjusted for BMI, pr evious stroke or transient ischemic attack, history of peripheral vascular d isease smoking, diabetes, renal insufficiency, and coronary artery bypass graft surgery using a stepwise selection procedure (P<0.02 inclusio n, P<0.05 stay) SNPs with P value < 0.05 w ere reported, if they had not previously been flagged (HWE analysis) or the MAF was not lower than 2% (if SNP was significant in this race). Similar to PEAR, INVEST tested multiple SNPs for associations. As descri bed above, adjustment is necessary to avoid type I errors due to multiplicity. Thus, P values were adjusted by performing FDR SAS Version 9.1 was used.
40 CHAPTER 3 DEFINITION: RESEQUENCING OF ADRBK1 AND DETERMINATION OF LINKAGE DISEQUILIBRIUM ST RUCTURE IN ADRBK1 AND ARRB1 Introduction Sequencing technology has made enormous improvements in the last decade. Sanger Sequencing had been the gold standard in sequencing in the 1980s and 1990s but shortly after the publication of the Human Genome Project in 2001 several new technologies were introduced for mainstream applications 67, 68 The se next generation technologies are characterized by a high er overall sequencing throughput leading to a shorter project time and lower total project costs. Since their introduction, these next generation technologies have been used to sequence eukaryotic and prokaryotic genomes. One of these technologies i s based on pyrosequencing chemistry and was commercialized by 454 Life Sciences ( Branford, CT ), a Roche company. In the past couple of years 454 sequencing has been used extensively, and among other genomes has lead to fully sequence the genome of James D Watson. 69 Nevertheless, utilizing 454 technology for SNP discovery is more challenging as several individuals are needed. Here, sequencing complete genomes remains too expensive. Therefore, our goal was to amplify the licons, and to analyze 16 individuals in one 454 sequencing run. We chose to sequence a total of approximately 341 kb in ADRBK1 ARRB1 ATP2A2 and RYR2 This approach should ensure sufficient depth coverage necessary for accurate base call and a cost ef fective use of 454 Genome Sequencer FLX instrument ( throughput of 100 million bases per run ). A n advantage of this approach was to cover the entire sequence of ADRBK1 As a similar utilization of t he 454 sequencing technology had not been tested before, we decided to also resequence ADRBK1 regions using Sanger sequencing. Here, we decided to focus on 5 ADRBK1 In addition we used pyrosequening to confirm reported SNPs.
41 Although the number of common polymorphisms in ADRBK1 and ARRB1 are finite, the throughput and costs of current genotyping technology does not allow genotyping all common variants in large clinical populations. Traditionally, candidate SNPs were selected for association studies based on known or potential functional effects. However, a lack of association with one of these SNPs does not rule out functionally important changes at nearby SNPs (not genotyped), except those that are in tight LD (r 2 >0.8) with the candidate SNP. LD describes the relationship between genot ypes at a pair of polymorphic sites. Haplotype blocks are segments of strong LD within which there is little evidence for ancestral recombination events. In an approach that is state of the art, all common SNPs of ADRBK1 and ARRB1 are tested a priori for LD. Based on the LD patterns, a smaller number of SNPs can be selected that are represent ative of numerous other SNPs, leading to efficiencies in genotyping, while allowing the investigator to capture most of the common variability in the gene. These SNP s are referred to as tagSNPs, because by genotyping them, they also provide information on other SNPs that are in advance d by the recent publication of the HAPMAP proj ect. We used HAPMAP data to determine the LD structure of ARRB1 Novel and confirmed ADRBK1 SNPs were incorporated in the structural analysis of ADRBK1 Resequencing of ADRBK1 Resequenc ing Using 454 T echnology Here, we report the results for individuals A (NA 06991 ) and B ( NA07019 ) Thirty one amplicons cover ed regions of RYR2 ten of ATP2A2 five of ARRB1 and four of ADRBK1 The average amplicon size was approximately 7 kb. The average concentration after purification was 13 x 10 9 molecules/L. High concentration differences (up to 200 fold) were seen between
42 amplicons but not between individuals. Table 3 1 shows the results of three sequencing runs. Approximately 885 kb (=2.6 x 341 kb) were sequenced with 454 Genome Sequencer 2 0 system (454 Life Sciences ) Here, the average coverage with unique matched sequences was only 71% as some regions were sequenced multiple times and others were left out. This process was random and higher coverage can be achieved by an increase in base s sequenced. Therefore, an increase in average read length is necessary. For the GS 20 runs, the average depth coverage was 2.6 fold. Individua l B library was also used for a t hird run using 454 Genome Sequencer FLX upgrade. The FLX achieved higher av erage depth coverage (9.6 fold) resulting from a higher average read length and a higher number of bases sequenced. Thus, we were able to detect high quality differences between the individual B and the reference sequence (Table 3 2 ). However the covera ge with unique matched sequences was 84% for all genes using the FLX and 54 kb were not sequenced. ADRBK1 was covered to 96.8% with a wide range of depth coverage (1 fold to greater than 80 fold) It remains unclear, if other individuals would show similar results as the project turn out to be too expensive and had to be canceled Resequencing U sing Sanger Sequencing All 48 individuals were successfully sequenced for the 3530 bases in the ADRBK1 region. Th e regions for SNP discovery inc a total of 2096 bases and parts of exon 20, intron 20, exon 21 including the UTR with a total of 1434 bases. Here, we identified a novel T>C transition a t position chr.11:66789808 ( 703 re lative to ADRBK1 ) This SNP is relatively common, and it could be confirmed by sequencing in both directions. However, allele frequencies differ by race. In blacks the MAF is 0. 326 compared to
43 0.021 in whites. Furthermore, we could confirm the existenc e of two additional promoter SNPs ( rs11605263 and rs12286664 ). In, the UTR only one SNP was confirmed ( rs4370946 ) Additional SNPs were confirmed by sequencing different ADRBK1 regions One synonymous SNP ( rs11227756 isoleucine/isoleucine) was confirmed in exon 1 and rs12805999 in intron 1. In intron 2, we validated the existence of rs948988 and rs4930416 Additional intronic SNPs are rs3730309 (intron 5), rs3730310 (intron 6), rs3730145 (intron 13) and rs2071007 (intron 14). Genotyping o f R eported ADRBK1 SNPs The following four SNPs were confirmed by geno typ ing : rs1894111, rs7128315, rs1274774, and rs10896164. Table 3 3 lists all novel and confirmed SNPs with allele frequencies in blacks and whites. All SNPs were in HWE. Determination o f Linkage Disequilibrium Structure in ADRBK1 and ARRB1 Structural A nalysis of ADRBK1 Thirteen of 14 ADRBK1 SNPs have a MAF>0.05 in blacks. Figure 3 1 shows the LD plot in blacks. As the LD is low only one bin with three SNPs could be identified. It contains rs7128315 703 T/C and rs948988 (correlation coefficient r 2 >0.8) There was no haplotype block defined by Gabriel et al. 53 (default option in Haploview 4.1). In whites, only four of 14 SNPs a re common. Figure 3 2 shows the LD plot in whites. There are no tagging SNPs. Furthermore, there was no LD between ADRBK1 and ARRB1 Structural A nalysis of A RRB1 Here, we used two haplotype tagging approaches. The PHASE/BEST analysis resulted in 112 ha plotypes and 17 tagSNPs in YRI. In CEU, 95 haplotypes and 16 tagSNPs were computed. Twenty five SNPs we re necessary for genotyping to cover all variability as 10 tagSNPs occur in both populations. The Haplotype/Tagger analysis showed 37 haplotypes in ei ght blocks and 42
44 tagSNPs in YRI. Figure 3 3 shows the LD plot in YRI. In CEU, there were 36 haplotypes in eight blocks and 28 tagSNPs. The LD plot is shown in figure 3 4. Seventeen tagSNPs are common in both populations. Therefore, 53 SNPs are necess ary for genotyping based on the Haplotype/Tagger analysis. These 53 SNPs contain all 25 SNPs resulting from the PHASE/BEST approach. Although relatively few tagSNPs would capture the haplotype diversity with either strategy, no common (>0.1) haplotypes c an be found in ARRB1 Therefore, we used a pairwise tagging procedure that resulted in 60 tag SNPs for both populations. Discussion W e were not able to utilize 454 technology for SNP discovery However, our final resequencing approach yielded the discovery of a novel ADRBK1 promoter SNP. Here, we were also able to show that common polymorphism s exist in ADRBK1 In addition, both genes ADRBK1 and ARRB1 have low LD in blacks and whites. However, 60 tag SNPs in ARRB1 and 14 SNPs in ADRBK1 w ere selected for further evaluat ion in our clinical populations (Chapter 5). Several reasons le d to the decision that 454 technology c ould n ot be used cost effectively for SNP discovery. First, the amplicon design was time consuming. To use 454 technology in a cost effective way, long ra nge PCRs were designed. If amplification wa s not optimal, new amplicons we re designed. These new amplicons we re generally smaller and therefore, more PCRs were necessary to cover the ta rget sequence. This procedure wa s not o nly time consuming, but also le d to a rapid increase in overall project costs. Second, the coverage with unique matched sequences was 84% (FLX upgrade) and 54kb were not sequenced. The results looked better for ADRBK1 (96% coverage). However, i t remains unclear if this observation would only been seen in i ndividual B or if this i s systematic error (e.g. in the nebulization process) that would show similar results in additional runs Thus, it is possible that missing regions would need to be sequenced in additional runs (with different amplicons) or by using the
45 Sanger sequencing method. Third, for each individual an individual library needs to be constructed, as for each individual the amplicon concentrations need to be measured and each plicons are incorporated via PCR and identify each individual is not a cost effective alternative as it would increase the number of amplicons from 50 to 850. Therefore, we conclude d tha t using the 454 technology (FLX upgrade) wa s not cos t effective for SNP discovery, especially if PCR products (amplicons) are used as starting material. Other next generation sequencing technologies exist. Among those, t he sequencing by ligation platform SOLiD (Applied Biosystems ) could be an available alternative at ICBR. However, cost intensive and time consuming long range PCRs are also necessary for this approach. Recently, 454 technology has been used in combination with custom high density oligonuc leotide microarrays ( Roche NimbleGen, Inc. Madison, WI USA ) 70 Here, the microarray i s used to enrich genomic target sequences (including 6 700 exons of 500 bases length total 5 Mb ) followed by multiplex PCR and 454 sequencing. In a similar approach the micro array might be used to target candidate genes and the multiplex PCR could be used to unclear how cost effective this procedure would be as for each individual a new microarray with different multiplex PCR needs to be used. Soon, third generation sequencing technology will be available. For example, Pacific Biosciences developed a method that enables the real time detection of the inco o peration of nucleotides in a single DNA molecule. 71 This technology has a potential read length of 100,000 bases and would sequence 1Gb in less than 1 hour. 67 Thus, an approach of sequencing target regions might soon b ecome obsolete.
46 In our resequencing approach, we were able to discover a novel SNP in the ADRBK1 promoter region. As we focused on 5 ADRBK1 it is possible that other undiscovered SNPs exist in the ADRBK1 region However ADRBK1 does not have non synonymous SNPs. 20 Undiscovered intronic SNP s could be functional by unknown mechanisms or appear functional as they are in linkage with functional SNP in our target regions. It is possible, that common functional SNPs are further up or downstream. However, sequencing larger regions with Sanger sequencing is not cost effective as discussed above.
47 Table 3 1. 454 sequencing runs Individual Bases sequenced Sequences Average read length [bases] Coverage (%) A (NA06991) 899,846 9172 98.11 69.27 B (NA07019) 869,662 8498 102.34 72.54 Average (GS 20) 884,754 8835 100.225 70.905 B (FLX upgrade) 3,230,248 16563 195 83.5 Table 3 2. 454 FLX sequencing: Detection of high quality differences between individual B and reference sequence Amplicon Position SNP N umber of reads Number of variant reads (%) SNP ID ARRB1.Pr2 535 G>T 29 29 (100) ARRB1.Pr2 577 G>A 24 24 (100) ARRB1.Pr2 5073 T>C 47 47 (100) ARRB1.Pr2 5502 A>G 27 27 (100) ARRB1.Pr2 7334 G>T 65 65 (100) ARRB1.Pr2 7951 G>C 33 23 (70) ADRBK1.1_4 3519 T>C 80 80 (100) rs1894111 RYR2.7_8 865 C>G 26 26 (100) RYR2.7_8 1025 A>G 22 14 (64) RYR2.E95_98 3049 T>G 12 12 (100) Abbreviation : SNP single nucleotide polymorphism
48 Table 3 2. Novel and confirmed ADRBK1 SNPs GP Position db SNP ID Variant Feature MAF Blacks MAF Whites MAF YRI* MAF CEU* chr11:66789652 rs11605263 C>T Promoter 0 .000 0.063 0.00 0 0.050 chr11:66789725 rs12286664 G>A Promoter 0. 26 1 0.000 0.262 0.000 chr11:66789808 703*** T>C Promoter 0.326 0.021 chr11:66790842 rs11227756 ** C>A Ile/Ile 0.14 7 0. 842 0.124 0.916 chr11:66795188 rs1894111 C>T Intron 0.191 0.046 0.200 0.025 chr11:66797774 rs7128315 G>A Intron 0.318 0.000 0.35 8 0.000 chr11:66802048 rs948988 G>A Intron 0.292 0.000 0.358 0.00 0 chr11:66803077 rs12274774 ** G>T Intron 0.300 0.000 0.451 0.027 chr11:66803824 rs3730309 T>C Intron 0.375 0.000 chr11:66803976 rs3730310 G>C Intron 0.271 0.000 chr11:66806699 rs3730145 T>G Intron 0.432 0.000 0.44 0 0.034 chr11:66806868 rs2071007 G>A Intron 0.290 0. 90 0 0.158 0. 898 chr11:66809042 rs10896164 G>A Intron 0.304 0.881 chr11:66809714 rs4370946 C>T UTR 0.200 0.000 Abbreviations: GP golden path, CEU samples from Utah residents with ancestry from northern and western Europe Ile Isoleucine, MAF minor allele frequency, SNP single nucleotide polymorphism, UTR untranslated region, YRI samples from Yoruba in Ibadan, Nigeria *International HapMap Project, ** added in the International HapMap Project Phase III, *** novel variant
49 Figure 3 1 Haploview generated LD map of twelve ADR BK1 SNPs in blacks The numbers within boxes indicate the r 2 values between the two corresponding SNPs. Haplotype blocks were defined by Haploview software with the default option of using the haplotype block definition used by Gabriel et al. 53 Three SNPs ( rs7128315 703 T/C and rs948988 ) have a correlation coefficient r 2 >0.8.
50 Figure 3 2 Haploview generated LD map of four ADRBK1 SNPs in whites The numbers within boxes indicate the r 2 values between the two corresponding SNPs. Haplotype blocks were defined by Haploview software with the default option of using the haplotype block definition used by Gabriel et al. 53
51 Figure 3 3 Haploview generated LD map of 86 ARRB1 SNPs in samples from Yoruba in Ibadan, Nigeria ( YRI population) Darker boxes indicate higher r 2 values between the two corresponding SNPs. Haplotype blocks were defined by Haploview software with the default option of using the haplotype block definition used by Gabri el et al. 53
52 Figure 3 4 Haploview generated LD map of 79 ARRB1 SNPs in samples from Utah residents with ancestry from northern and western Europe ( C EU population) Darker boxes indicate higher r 2 values between the two corresponding SNPs. Haplotype blocks were defined by Haploview software with the default option of using the haplotype block definition used by Gabriel et al. 53
53 CHAPTER 4 F UNCTIONAL CONSEQUENC ES: VARIATION IN ARRB1 AND ADRBK1 EXPRESSION Introduction Polymorphisms can cause amino acid changes (e.g. non synonymous SNP) or affect gene transcription, mRNA processing (e.g. alternative splicing), and translation (e.g. stop codon). 72 SNPs represent the most frequent type of sequence variation. Non synonymous SNPs can alter protein functions, but appear insuffi cient to account for all the differences in drug response among individuals On the other hand, gene expression is highly variable and heritable in humans. 73 Altered gene expression can be caused by cis and trans acting elements. Cis acting elements can be polymorphisms in the flanking region of the gene of interest or methylation differences. These cis acting elements affect gene expression (e.g. promoter polymorphisms with different affinities to transcription factors) or mRNA processing (e.g. changes mRNA structure affecting stability). Trans acting elements can be transcription factors that are themselves r egulated by other genetic factors or the cell environment. As non synonymous SNPs are not present in both genes, t he purpose of this aim was to determine how genetic variation in ADRBK1 and ARRB1 1 and arrestin 1, respect ively. 1 has shown to be elevated in lymphocytes. 34, 35 adrenergic receptor signaling, the properties of the system in circulating lymphocytes appear to mirror those in solid tissue 74 thus making lymphocytes an excellent, accessible tissue source for the proposed studies. In addition, AR signaling and to make extrapolations to the cardiac function. 75 78 As both genes are expressed in lymphocytes, w e used isolated lymphocytes from healthy volunteers to measure ADRBK1 and ARRB1 expression levels. In addition, we used
54 lymphobl astoid cell lines from from individuals of African ancestry to determine ADRBK1 expression differences. A DRBK1 and ARRB1 E xpression in H ealthy V olunteers Forty seven subjects participated and 43 healthy volunteers were determined eligible Table 4 1 shows the baseline demographics. The subjects did not have any medical problems or take any prescription drugs. In addition, no subject had an active infection or history of recurrent infection. The mean BP was SBP was 111.813.1 mmHg and the mean DBP was 68 .28.5. No subject had a BP of greater than 140/90 mmHg. The mean BMI was 24.12.8 kg/m 2 No subject was a smoker, illicit drug addict or alcohol ic The majority of the study participants was white (58%). Thirteen subjects identified themselves as black Thirty eight subjects had complete mRNA expression data. Sample 006 (white, female) was chosen as a calibrator ( ADRBK1 expression=1, ARRB1 expression=1). Women had a ADRBK1 expression of 0. 92460.3738 Men had an expression of 0.9 2700.2539 The median ADRBK1 expression was not different by sex (women: 0.8112, men: 0.9026 P = 0.50 56 ). In addition, me dian ARRB1 expression did not differ by sex (women: 1. 2 344 men: 1.4984 P= 0. 1087 ). There was no correlation between ADRBK1 or ARRB1 expression levels and BMI (r 2 =0.00003, r 2 =0 .00114) SBP (r 2 =0.00124 r 2 =0.03931 ) DBP (r 2 =0.00057 r 2 =0.00160 ) or HR (r 2 <10 5 r 2 =0.00014 ). Figure 4 1 shows the relative ADRBK1 expression by race. Asians had a me dian expression of 0.7689. The median ex pression was higher in blacks (0.8101) vs. whites (0.90 85). However, there was no statistical difference (P=0.1976). ARRB1 expression is shown in Figure 4 2. The median expression was not differen t by race (Asians: 1.2653, blacks: 1.1631, whites: 1.2536 P=0.6830). Expression data was not analyzed by genotype as the low number of black subjects was too low. In addition, our clinical findings (Chapter 5) need to be replicated to yield further candidate SNPs.
55 ADRBK1 Expression in L ymphoblastoid C ell L ines As most ADRBK1 SNPs are only common in blacks and only 13 blacks were recruited we decided to compare ADRBK1 expression levels by genotype in lymphoblastoid cell lines. The Affymetrix U133 Plus 2.0 GeneChips (Affymetrix) analysis has been described p reviously 58 ADRBK1 expression levels are given in arbitrary units. The mean expression was 240.4867.01. All 45 samples were successfully genotyped f or the novel ADRBK1 703 T/C and rs4930416 Both SNPs had been identified in the clinical association studies (see C hapter 5). As both SNPs have low MAFs comparison was done between common allele homozygotes and minor allele carriers. Figure 4 3 shows the relative ADRBK1 expression for ADRBK1 703 T / T homozygotes and C carriers M e a n ADRBK1 expression was similar in ADRBK1 70 3 T / T homozygotes ( 253.2781.05 ) compared to C carriers ( 238.9643.01, P = 0. 7715 ) In addition, relative ADRBK1 expression did not differ in rs4930416 T / T homozygotes (236.8359.34) and G carriers (266.67112.25, P = 0. 2745 Figure 4 4) Discussion We could confirm that the ADRBK1 and ARRB1 are expressed in leukocytes obtained from healthy volunteers In addition, ADRBK1 is expressed in lymphoblastoid cell lines. The expression for both genes did not differ by sex or race. We were not a ble to compare expression by genotype as the allele s to be tested are not frequent in the healthy volunteer population ( ARRB1 rs12274033 : CEU MAF = 0 .026, YRI MAF = 0 .1, ADRBK1 rs 4930416 : CEU MAF = 0 YRI MAF= 0.051, ADRBK1 703 T/C: CEU MAF = 0 .021, YRI MAF= 0.326 ) Although we had targeted especially blacks including African Americans, we were not able to recruit many African American healthy volunteers. We focused on this group for three main reasons First, African Americans are underrepresented in medical research in the United States Second, it is well known that blacks blocker mono therapy. 79 83 Third, most of the
56 polymorphisms in ADRBK1 are common in blacks. There are only a few polymorphisms in ADRBK1 that are common in whites. Thus, ADRBK1 polymorphisms might explain the poor response in blacks. We were able to test ADRBK1 expression difference by ADRBK1 rs4930416 or 703 T/C genotypes in lymphoblastoid cell lines as these were obtained from 45 African American subjects. Power analysis revealed a greater than 90% power to detect a 20% expression However, expression did not differ by genotype. It is possible that the Epstein Barr virus transformation of the lymphocytes alter ed the expression ADRBK1 which could have lead to negative findings. However, numerous other g roups have used similarly transformed cells for in vitro functional studies and the cells are believed to behave normally. 84 86 In addition, it is very difficult to pro ve that these polymorphisms affect gene expression o btaining in a cis acting fashion. Expression variance can be heavily influenced by environmental or trans acting factors. We investigated these two ADRBK1 SNP for putative transcription factor binding sites using the JASPAR database. 87 ADRBK1 703 wa s predicted to be located in a binding site for the c hicken ovalbumin upstream promoter transcription factor 1 (COUP TF1= NR2F1 ) This transcription factor is expressed ubiqui tously and can act as repressor or activator of gene expression. 88 However, it remains unclear if ADRK1 expression is affect ed by NR2F1 Our study did not detect ADRBK1 expression differences by rs4930416. This SNP is located in intron 1 of ADRBK1 JASPAR predicted no putative functional site for this SNP. However, in the YRI population rs4930416 is in complete LD with rs7396248, a SNP located 4682 bases upstream of t he ADRBK1 start codon. JASPAR predicted the following transcription factors for the locus surrounding rs7396248: reticuloendotheliosis viral oncogene homolog A
57 (RELA), E26 transformation specific transcription factor 1 (ETS 1), and transcriptional enhance r activator domain (TEAD). RELA is expressed ubiquitously. 89 ETS 1 is expressed in lymphoid organs, brain, and vascular endothelial cells. 90 TEAD can activate enha ncers and promoters in mammals and is present in a wide variety of tissues. 91 As rs4930416 is in complete LD with rs7396248 we conclude that ADRBK1 expression is not different by rs7396248 in lymphoblastoid cell lines. It is possible that rs7396248 is functional in other tissues. We did not test the impact of ARRB1 genetic variation from Chapter 5 ( ARRB1 CAT haplotype, ARRB1 rs542645, or ARRB1 rs171 33921 ) on ARRB1 expression levels. If the findings with these variant s in our clinical studies are replicated, further research should test if these variants are associated with altered expression. However, assessing these is challenging. For example, the following t hree transcription factors were predicted for rs12274033 ( a SNP of the ARRB1 CAT haplotype) : mesenchymal transcription factor forkhead homologue 6 (FKH6) pancreatic duodenal homeobox 1 (PDX1), and neurokinin 3 transcription factor 1 (NKX3 1 expressed in prostate gland). None of these is expressed in lymphocytes. 92 94 Thus ideally these relationships must be studied in appropriate target tissues since gene regulation and mRNA processing are tissue specific events.
58 Table 4 1. Healthy volunteer study: B aseline demographics Variable Number of Participants 43 Age (years) 28.49.1 Men 17 (40) Race White 25 (58) Black 13 (30) Asian 5 (12) Ethnicity Hispanics 4 (9) Non Hispanics 39(91) Body mass index (kg/m 2 ) 24.12.8 Blood pressure (mmHg) Systolic 111.813.1 Diastolic 68.28.5 Heart rate (BPM) 68.08.8 Abbreviations: BPM, beats per minute; Data are given as mean standard deviation or N (%)
59 Figure 4 1 Relative ADRBK1 expression in healthy volunteers by race. Sample 006 (white, female) was chosen as calibrator (expression=1). relative expression. Boxes, median expression values (horizontal line) and 25 th and 75 th percentiles; whiskers, distances from the end of the box to the largest and smallest observed values that are <1.5 box lengths from e ither end of the box AU arbitrary unit
60 Figure 4 2 Relative A R RB1 expression in healthy volunteers by race. Sample 006 (white, female) was chosen as calibrator (expression=1). relative expression. Boxes, median expre ssion values (horizontal line) and 25 th and 75 th percentiles; whiskers, distances from the end of the box to the largest and smallest observed values that are <1.5 box lengths from either end of the box AU arbitrary unit
61 Figure 4 3 Relative ADRBK1 expression in lymphoblastoid cell lines ( ADRBK1 703 T/C) values (horizontal line) and 25 th and 75 th percentiles; whiskers, distances from the end of the box to the largest and smallest observed values that are <1.5 box lengths from either end of the box AU arbitrary unit
62 Figure 4 4 Relative ADRBK1 expression in lymphoblastoid cell lines (rs4930416) Dots pression values (horizontal line) and 25 th and 75 th percentiles; whiskers, distances from the end of the box to the largest and smallest observed values that are <1.5 box lengths from either end of the box AU arbitrary unit
63 CHAPTER 5 CLINICAL IM PLICATIONS: THE EFFE CT OF ADRBK1 AND ARRB1 POLYMORPHISMS ON THE CLINICAL RESPONS E TO ANTIHYPERTENSIV E THERAPY AND ADVERS E CARDIOVASCULAR OUTCO MES Introduction No comprehensive study has been directed at ascertaining whether genetic variations of ADRBK1 or ARRB1 blockers. Furthermore, no studies have investigate d whether genetic variations in ADRBK1 or ARRB1 have influence on mortality myocardial infarction or stroke in treated hyperte nsive patients. Here, we addressed these questions in the two clinical trials (PEAR and INVEST GENES case control). One objective of PEAR is to identify the genetic determinants of the antihypertensive response to atenolol and h ydrochlorothiazide 59 R ecruitment started in 2006 with the goal to enroll 800 i ndividuals with uncomplicated hypertension. Subjects were between 17 and 65 years old Current antihypertensive therapy was discontinued a nd hypertension was confirmed After collection of baseline data s ubjects were then randomized to either hydrochlorothiazide or atenolol Data collection included clinical, home and 24 hour ambulatory BP. In addition, biological samples (DNA, plasma, urine) were collected. The response to therapy was assessed after at least 6 weeks on the target dose (one titration step) A fter monotherapy, the second drug was added with similar dose titration and r esponse assessment procedures. INVEST GENES was part of INVEST. INVEST was a multicenter international clinical trial between 1997 and 2003. Here, 22,576 patients with coronary artery disease and hypertension were recruited. After an extensive cardiovascular history and physical examination, these patients were randomly assigned to either a verapamil SR or an atenolol based multidrug antihypertensive strategy. Tra ndolapril and/or hydrochlorothiazide were added
64 if needed for BP control. The primary outcome was defined as all cause death, nonfatal myocardial infarction, or nonfatal stroke 66 Genetic samples were collected on 5,979 sub jects from the United States and Puerto Rico. The E ffect of ADRBK1 and ARRB1 P oly morphism on the C linical Response to Antihypertensive T herapy PEAR Genotype Quality C ontrol DNA was isolated for f our hundred eighteen samples One sample could not be genotyped with IBC chip and the custom array as it did not meet the concentration and quality criteria Table 5 1 lists the quality control procedure for the IBC chip For the IBC chip, one sample showed contamination and a low call rate (< 90% ) An additional sample had to be excluded because of sex gender mismatch. Therefore, c omplete IBC chip genotype data was available for 415 PEAR samples. Three samples failed due to low call rate (<90%) on the custom SNP array. In addition, f or one of these three samples sex and gender did not match. This sample was the same sample that had to be excluded on the IBC chip. Thus, the 414 PEAR samples had genotype data for the custom array. Fours SNPs had a call rate lower than 90% and three SNPs had a low SNP cluster score (GenTrainScore<0.3 custom SNP array ). These seven SNPs were excluded from the analysis. Additionally, we excluded six SNPs that were out of HWE in one of the racial groups Both SNPs genotyped with TaqMan were in HWE. Sixty th ree SNPs remained for the analysis. These SNPs consisted of 4 9 ARRB1 SNPs and 1 4 ADRBK1 SNPs. Blood Pressure R esponse Baseline demographics of 418 PEAR patients are shown in Table 5 2 At baseline, patients in the hydrochlorothiazide arm were not different from patients in the atenolol arm for the following variables: age, proportion of women, home heart rate, d uration of hypertension and patients who were t aking antihypertensive drug at study entry However, more patients in
65 the atenolol arm had a family history of hypertension ( 8 2 4% vs. 74 .9 %, P = 0.048). Additionally, home SBP was higher in patients in the hydrochlorothiazide arm (147.511.2 mmHg vs. 144.510.3 mmHg P = 0.0047) In these pati ents DBP was also higher than in patients in the atenolol arm (94.56.4 mmHg vs. 92.66.3 mmHg P = 0.0024) In each arm and race genotypes of s everal polymorphisms were identified with different BP response However the P values reported in the tables are not adjusted for multiple comparisons using FDR (see Chapter 2 ) Here, we report on SNPs with P values of less than 0.05 with and without controlling for age, sex, BMI and baseline BP. In blacks, t wo ADRBK1 SNPs have different DBP respo nse by genotype (Table 5 3). However, only rs4930416 was also identified to influence SBP reduction (Table 5 4). This SNP is not common in whites and only two white patient s w ere heterozygote s (A/C) in PEAR. N o patie nt was minor allele (C) homozygote (M AF blacks: 0.09). Baseline DBP between rs4930416 genotypes was not different (A/A: 94.23 6.87 mmHg vs. A/C 96 00 8.6 6 mmHg, P = 0.2353 ). DBP reduction differed by genotype for ADRBK1 rs4930416 for both treatment arms in the black PEAR population In the atenolol arm, t he DBP reduction was 3.116.51 mmHg in patients that wer e homozygote for the common allele. In contrast, a greater reduction ( 7.485.84 mmHg ) was detected in heterozygotes ( P genotype = 0.0394 P Trend = 0.0394). After adjusting for age, s ex, BMI, and baseline DBP the findings did not change ( P genotype = 0.0413 P Trend = 0.0413 ). FDR adjustment was performed with 14 ADRBK1 SNPs that remained after q uality control FDR adjusted P value were P = 0.3094 for both genotype and trend. A similar trend for the rs4930416 was seen in the hydrochlorothiazide arm. T he DBP reduction in the common all ele homozygote patients was 6.356.58 mmHg compared to 11.326.34 mmHg for heterozygotes ( (P genotype = 0.0058 P Trend = 0.0058 ). Th e se finding remained significant after adjustment for age, sex, BMI
66 and baseline DBP ( P genotype = 0.00 89, P Trend = 0.00 89) but not after FDR adjust ment ( P genotype = 0. 1335, P Trend = 0 1335). In this study, rs4930416 genotype groups were not different in baseline SBP (A/A: 146.47 12.00 m mHg vs. 1 46.77 11.87 m m Hg, P = 0.9037 ). However, a trend by rs4930416 was also seen for SBP reduction under atenolol (A/A 1.39 11.23 mmHg vs.A/C 5.95 8.95 mmH g ) In addition black A/A homozygotes showed a 11.299.76 mmHg reduction under hydrochlorothiazide. Th is reduction was greater in black heterozygote patients ( 16.848.83 mmHg, ( P genotype = 0.0337 P Trend = 0.0337 ) in the same treatment arm. T he difference in SBP reduction remained significant after adjusting for age, sex, BMI and baseline SBP ( P genotype = 0. 0492, P Trend = 0. 0492). However, these findings did not hold FDR adjustment The SNP rs4930416 is intronic and JASPAR does not predict a putative transcription factor binding site. In the HAPMAP YRI population, this SNPs is in complete LD (r 2 =1) with a SNP that is located approximately 4.7 kb upstream of the ADRBK1 start codon (rs7396248, chromosome 11, position 66785799). In whites, we co uld identify two ADRBK1 SNP that were associated with different DBP response (Table 5 3). The SNP rs1894111 was also associated with SBP response in white patients receiving hydrochlorothiazide (Table 5 4, Figure 5 2 ) This SNP was not associated to alte r BP response to atenolol (Figure 5 1 ). In this study, white patients who were G/A heterozygotes had a greater BP response to hydrochlorothiazide compared to G/G homozygotes (Table 5 3, Table 5 4). The se results remained significant after adjust ment for age, sex, BMI and baseline BP (DBP: 11.293.74 mmHg (G/A) vs. 4.264.79 mmHg (G/G), P genotype = 0.0034 and SBP: 18.3714.90 mmHg (G/A), 8.117.55 mmHg (G/G), P genotype = 0.0191) Furthermore, t he DBP association h e ld after FDR adjustment (P genoty pe = 0.0342, P Trend = 0.0342).
67 Th is SNP is not in LD with other ADRBK1 SNPs. However, it is in linkage with several SNPs (including rs3741189, synonymous) in the F box and leucine rich repeat protein 11 gene ( FBXL11 ). FBXL11 is 137643 bases large (21 exons) and is located approximately 8.8 kb upstream of ADRBK1. However, rs1894111 is not very common in whites given that only six patients in PEAR were heterozygotes (MAF= 0.013). Thus analyses in larger populations are necessary to validate our fi ndings. Ten ADRBK1 SNPs showed an ass ociation with change in HR to monotherapy (Table 5 5 ). Most associations were seen in black patients treated with hydrochlorothiazide A fter adjustment for age, sex, BMI and baseline HR and further FDR adjustment the follow ing two SNPs remained significant: rs12274774 and rs3730145 After hydrochlorothiazide treatment black patients who were homozygotes for the rs12274774 common allele (C/C) had no change in HR ( 0.126.41 beats/min). However, C/A heterozygotes had an increase by 3.214.99 beats/min and A/A homozygotes an increase by 5.544.53 beats/min. release, both SNPs are in strong LD in the YRI population (r 2 =0.96). Thus, simil ar re sults were seen for rs3730 145 (Table 5 5). In black patients treated with hydrochlorothiazide the median change in plasma renin activity was the lowest in rs12274774 C/C homozygotes (0.3915 ng/mL/h ). C/A heterozygotes had a median change of 1.148 ng/mL/ h and A/A homozygotes a median change of 0.694 ng/mL/h However, these differences only represent a trend (P = 0.0965 ). On the other hand, plasma renin activities were different by rs3730145 genotype A/A homozygote patients had a median increase of pl asma renin activity by 0.329 ng/mL/h A/C heterozygotes a median increase by plasma renin activity of 1.291 ng/mL/h and C/C homozygotes a median increase plasma renin activity of 0.694 ng/mL/h ( P = 0.0220) The analyses for both SNPs were only adjusted for baseline renin activity levels
68 One ADRBK1 SNP was associated with altered HR response in the atenolol arm (Table 5 5) and seven ARRB1 SNPs. (Table 5 6). However, these findings did not hold after adjustment (cofactors and FDR). Ten ARRB1 SNPs that ha d unadjusted P value of lower than 0.05 are listed in Table 5 3 In blacks treated with atenolol three SNPs showed differences by genotype. Of these three SNPs, rs546812 was also identified to alter SBP response in blacks under atenolol. Interestingly, this SNP has a similar effect in whites treated with atenolol. Here, G/G homozygotes have the lowest response (Table 5 3 ). However, these results are only significantly different in the unadjusted model and do not hold after FDR adjustment The second ARRB1 SNP that was identified to alter DBP reduction in blacks treated with atenolol shows an opposite effect in the hydrochlorothiazide arm. In the atenolol arm, rs1676884 A/C heterozygotes had a lower BP reduction ( 0.818.39 mmHg) than homozygotes C/C ( 4.166.05 mmHg, P = 0.0325 after adjust ment ). In the hydrochlorothiazide arm the reduction was greater for A/C heterozygotes ( 11.576.17 mmHg vs. 6.136.52 mmHg, P = 0.0024 unadjusted). However, these results do not remain significant after adjustin g for age, sex, BMI and baseline DBP. The third SNP to influence DBP in blacks treated with atenolol is rs12274033. T/C heterozygotes show the lowest response ( 0.99 4 85 m mHg) compared to T/T homozygotes ( 4 656.57 mmHg) and the one C/C homozygote patient ( 4 .1 2 mmHg). The findings remain significant after adjusting for cofactors but not after FDR adjustment. Two common haplotypes were inferred from the se three ARRB1 SNPs that showed an association with BP in blacks (rs1676884, rs546812, and rs1227 4033). The first haplotype ( CGT ) has a frequency of 0.60 90 and the second haplotype (CAT) has a frequency of 0.22 05 The CAT haplotype was significantly associated with altered BP response in blacks. After
69 adjustment for age, sex, BMI and baseline SBP, black patients with 1 or 2 copies of the CAT haplotype had a SBP reduction of 5.8 49 92 mmHg compared to an increase of 1.08 10.89 mmHg in black patients with no copy of the CAT haplotype (P = 0.0207 Figure 5 3 ). In contrast, black patients did not have a different SBP response to hydrochlorothiazide based on CAT haplotype ( patients with 1 or 2 copies: 12.3 8 10.6 5 mmHg vs. patients with no cop y : 12.48 9.55 mmHg P = 0.8680 Figure 5 4 ). In addition, black patients with 1 or 2 copies of the CAT ha plotype ha d a greater DBP reduction after atenolol treatment ( 5.82 5.66 mmHg vs. 2.08 6.82 mmHg in patients with no copy P = 0.0173 ) Similar ly to the finding with SBP, DBP response in the hydrochlorothiazide arm did not differ by CAT haplotype ( 7.3 37 .04 mmHg vs. 7.69 6.9 2 mmHg, P = 0.6810 Figure 5 4 ). In whites this haplotype wa s also common (frequency: 0.486 ) and showed a trend in atenolol response. SBP reduction was greater in whites with 1 or 2 copies ( 11.37 8.52 mmHg) compared to whites with no copy ( 6.927.88 mmHg, P = 0.0890). Furthermore, DBP reduction had a similar trend ( 10.1 6 5.66 mmHg vs. 6.36 5.28 mmHg, P = 0.0792). In the hydrochlorothiazide arm, no difference in SBP reduction by CAT haplotype was detected. However, DBP reduction show ed a trend ( 5.02 4.8 7 mmHg vs. 3.25 4.95 mmHg, P = 0.0731 ). The eight additional SNPs that were associated with BP response to atenolol in whites did not result in common haplotypes. However, the three SNPs (rs2276310, rs271216, rs546812) with the strong est signal yielded in two common haplotypes in whites (GGA frequency: 0.478, GGG frequency: 0.236). The GGG haplotype is also common in blacks (frequency: 0. 315 ). None of these haplotypes was associated with BP response. In conclusion, one ADRBK1 SNP and the ARRB1 CAT haplotype showed trends in BP response to atenolol. However, given the problem of false positives due to multiple tests, these SNPs (or the haplotype) represent only interesting candidates for further studies.
70 The E ffect of ADRBK1 an d ARRB1 P olymorphisms on A dverse C ardiovascular Outcomes in Patients with H ypertension and C or onary Artery D isease INVEST Genotype Quality C ontrol The case control subset consisted of 894 samples. IBC chip genotyping was performed successfully with 859 INVEST case control cohort samples. Forty seven samples were removed due to low call rate ( <90%) or contamination Thus, genotype data was available for 812 samples. We genotyped 886 samples on the custom SNP array and 20 samples were removed (low call rate, contamination). Eight hundred sixty six INVEST samples had genotype data for the custom array. Several SNPs were excluded. Two SNPs (IBC chip: rs12283002, rs1894111 ) w ere excluded from the analysis due to low call rate (<90%) Seven SNPs were excluded due to poor clustering (custom SNP array). Ten SNPs were out of HWE in one of the racial groups and were excluded from the analysis. Both SNPs genotyped with TaqMan were in HWE. Thus, a total of 5 7 SNPs ( ten ADRBK1 and 4 7 ARRB 1 SNPs) w ere analyzed. Primary O utcome INVEST GENES included a large proportion of elderly, diabetic and female patients who were ethnically diverse The baseline demographics of the patients selected as cases and controls are similar to INVEST GENES (Tab le 5 7). O ne ADRBK1 SNP and two ARRB1 SNPs were identified to influence the first occurrence of death from all cause, myocardial infarction and stroke (Table 5 8). The adjusted odds ratios for all SNPs associated with the primary outcome are shown in Figu re 5 5 The first ARRB1 SNP (rs542645) was associated with a 50.1 % risk reduction (adjusted odds ratio 0.499 95% confidence interval 0.288 0.867 P = 0.0136 ) However, these results do not remain significant after FDR adjustment. The minor allele of this SNP sh owed also a protective trend in both treatment strategies. Patients w ho were assigned to the calcium channel blocker strategy had a
71 risk reduction of 51.3% (adjusted odds ration 0.487 95% confidence interval 0.227 1.047) and patients who w blocker strategy a 49.5% risk reduction (Figure 5 5 ). However, the findings by treatment arm are not significant. The second SNP i n ARRB1 is rs17133921 In calcium channel blocker arm, this SNP showed a 1. 8 fold risk increase of the pri mary outcome. Adjustment did not affect this association (adjusted odds ratio 1.821 95% confidence interval 1.134 2.92 4, P = 0.0132 ). However, the findings did not remain after adjusting for 47 tests. blocker arm, t he C allele of ADRBK1 703 T/C shows a two fold risk (unadjusted odds ratio: 2.020, 95% confidence interval 1.061 3.847, P = 0.0323) The results do not remain significant a fter adjusting for cofactors ( adjusted odds ratio: 1.854, 95% confidence interval 0.857 4.00 9). However, t he same allele has shown a trend to increase HR under hydrochlorothiazide monotherapy (PEAR). This trend did not remain significant after adjustment In conclusion, one ADRBK1 SNP and two ARRB1 SNPs are associated using unadjusted models and two the AR RB1 remain significant after adjustment for other factors. However, none of the SNP remains significant after FDR adjustment. Discussion To our knowledge, this is the first cardiovascular research study that has investigated the clinical implications of polymorphisms in ADRBK1 and ARRB1 Here, w e were able to identify several polymorphisms in ADRBK1 and ARRB1 to influence home BP response under antihypertensive therapy and to modify the risk for adverse cardiovascular outcomes in patients with hypertension and coronary a rtery d isease. BP response was different by rs4930416 and rs1894111 ( ADRBK1 ) genotypes and the ARRB1 CAT haplotype. We could also show that ARRB1 rs542645 and rs17133921 modify the risk for all cause death, nonfatal MI or nonfa tal stroke in CAD patients treated under antihypertensive therapy. However we must temper our
72 conclusions given the presence of some borderline findings that do not remain significant after adjusting for multiple testing. At best, these findings represe nt interesting candidate SNPs/haplotypes for further replication studies In PEAR rs49 30416 (A/C) in ADRBK1 showed a signal with SBP and DBP re sponse At baseline, SBP and DBP were not different between A/A and A/C genotypes. No patient was carrying two minor alleles (C/C). The difference in BP reduction reached statistical significance in both treatment arms for DBP but only in the hydrochlorothiazide arm for SBP. A possible explanation is that our model only adjusted for age, sex, BMI and ba seline BP. Thus, the association with rs4930416 should be tested in an additional statistical model adjusting for all relevant clinical factors. Additionally, PEAR has not been completed and additional patients are currently being enrolled (goal: N=800). A greater number of patients in each genotype group will help to reduce the BP variation in each group and therefore it is likely that the SBP difference by genotype in the atenolol also becomes significan t I n both treatment arms A/C heterozygotes had a greater response compared to A/A homozygotes. Thus, the effect of the allele is not specific to atenolol or hydrochlorothiazide treatment. These finding are contrary to our assumption that ADRBK1 variation would influence BP response to atenolol. Thus it is likely that these findings are spurious as a result from multiple testing. In addition, t his SNP is located in intron 1 of ADRBK1 at position 66802154 on chromosome 11 and the function of intronic SNPs is not completely understood. However, sever al studies have reported that transcriptional regulatory elements are located in introns 95 97 Thus, we also investigated this SNP for putative transcription factor binding sites using the JASPAR database 87 However, rs4930416 is not located in a putative transcription factor binding site. T his SNP was present in the black population ( MAF = 0 .09) Two white patients (one in each treatment arm) w ere
73 heterozygote s. Our observed allele frequency data are relative close to HAPMA P data, although the minor allele is slightly higher in our black population compared to the YRI population ( MAF = 0 .05, CEU : MAF= 0). However our frequency data matches data release (Phase III) for another SNP rs7396248 ( MAF = 0 .09) in a new HAPMAP population, the African Ancestry in Southwest United States population ( ASW). This population consists of 12 parent adult child trios, 23 parent adult child duos and eight individuals ( N = 90) and samples were collected in the Southwestern U nited States from individuals who identified themselves primarily as African American. There are no frequency data for rs4930416 in this population. On the other hand, i n the YRI population rs4930416 is in complete LD with rs7396248, a SNP located 4682 bases upstream of the ADRBK1 start codon. This SNP was not on our custom array or the IBC chip. African American samples show very similar LD patterns to those observed in the YRI population. 53 Assuming a similar LD structure in ASW and YRI rs4930416 and rs7396248 are likely in LD in a n African American population (PEAR) Thus, rs7396248 could be the functional SNP JASPAR predict ed the following transcription factors for the locus surrounding rs7396248: reticuloendotheliosis viral oncogene homolog A (RELA), E26 transformation specific transcription factor 1 (ETS 1), and transcriptional enhancer activator domain (TEAD). RELA is expressed ubiquitously 89 ETS 1 is expressed in l ymphoid organs, brain, and vascular endothelial cells 90 TEAD can activate play a enhancers and promoters in mammals and is present in a wide variety of tissue s. 91 However, it remains unclear if ADRBK1 expression levels differ by rs7396248 genotype in the specific tissue Ano ther ADRBK1 SNP (rs1894111) was associated with BP response. The association was only seen in whites receiving hydrochlorothiazide. Although rs1894111 is only present in
74 1.3% of the white population, it remained significant after adjusting for age, sex, baseline BP and FDR. It is not linked to other ADRBK1 SNPs However, LD exists with SNPs in FBXL11 a gene located upstream of ADRBK1 As FBXL11 is relatively close to ADRBK1 (approximately 8.8 kb), these SNPs could influence ADRBK1 expression. However a larger population is necessary to validate our findings with rs1894111. We did not test rs1894111 in INVEST as this SNPs failed due to low call rate (81.3%). Two additional ADRBK1 SNPs showed a strong association with change in HR to monotherapy in bl ack patients treated with hydrochlorothiazide. Diuretics are known to increase sympathetic nervous system activation. This activation was enhanced in black patients carrying at least one variant allele of rs12274774 or rs3730145. Both SNPs do not occur in whites. T he mechanism might be explained by an increase d ARK 1 in these patients after ARK 1 expression result s in dysfunctional adrenal a 2 adren ergic rec eptor regulation as previously described in experimental heart failure model s (calsequestrin transgenic mice, rats with chronic heart failure following myocardial infarction ) 98 The dysregulation of a 2 adrenergic receptors leads to higher catecholamine levels and the observed HR increase. These findings were not seen in patients receiv ing atenolol which 1 receptors. However, rs12274774 and rs3730145 are located in ADRBK1 intron 2 and ADRBK1 intron 13, respectively. Therefore, these SNPs are no t directly affecting ADRBK1 expression. However, rs12274774 tags rs3730145 and four other SNPs in FBXL11 ( rs6591235, rs9630209, rs12282264, and rs12285582). Similarly to t he findings with rs1894111, these FBXL11 SNP s could influence ADRBK1 expression. We were also able to identify a haplotype in ARRB1 that alters BP response under atenolol treatment. The findings are stronger in blacks than in whites but would not hold for multiple
75 testing In both racial groups, patients carrying one or two copies of the CAT haplotype had a greater SBP and DBP response than patients with no copy of this haplotype. No difference was observed under hydrochlorothiazide treatment. Thus, an interaction between atenolol treatment and the ARRB1 CAT haplotype cannot be ru led out. The haplotype was inferred from three SNPs that had been associated or showed a trend in DBP and/or SBP response to atenolol One SNP (rs12274033) is located upstream of ARRB1 another one is located in intron 1 of ARRB1 (rs546812) and one is located in intron 3 (rs1676884) As previously described rs12274033 is located in the ARRB1 promoter region. JASPAR predicts transcription factor binding sites for FKH6 PDX1, and NKX3 1 However, we did not test t he effect of this SNP on expression as i ts MAF was too low in our study population (CEU MAF = 0 .026, YRI MAF = 0 .1). More importantly none of the predicted transcription factors is expressed in lymphocytes. In CEU, this SNP is linked to rs12290287 (chromosome 11, position 74748434) This SNP is located further upstream (7913 bases) from the ARRB1 start codon and a putative binding site for RELA which is expressed ubiquitously. Thus, rs12290287 could be functional. However, this would not explain the results seen in blacks. In addition, this SNP is not very common in CEU ( MAF = 0 .025) and Y RI ( MAF = 0 .066). T he other two SNPs of the ARRB1 CAT haplotype could have functional consequences. Here, rs546812 ha s a predicted site for PDX1 and NKX3 1. However, its impact on ARRB1 expression is questionable as it is located in intron 1 of ARRB1 This SNP is in LD with rs508435, rs518232 and rs472112. The SNP rs472112 is also located in intron 1 and was positively associated with nicotine dependence (heaviness of smoking index). 46 Interestingly, the same study also identified a haplotype to be associated with nicotine dependence in European Americans 46 The CGCGGT haplotype consisted of the following six SNPs: rs528833,
76 rs1320709, rs480174, rs578 130, rs611908, and rs472112. We could n ot test this haplotype for association in our population as the article was published after custom array design had been completed The third ARRB1 CAT SNP is rs1676884 which is located in intron 3 and predicted to be a binding site for PDX1. Interestingly, rs1676884 tags a SNP in the CGCGGT haplotype (rs1320709) Furthermore, rs1676844 tags rs2279130 in the CEU population. This SNP is located in the ARRB1 UTR. Unfortunately, this SNP failed on our custom array because of poor clustering. Therefore, we were unable to test the direct effect of this SNP on BP response. However, rs2279130 could be a functional SNP by affecting mRNA stability and consequently ARRB1 expression levels. Although the function of the ARRB1 CAT haplotype remains unclear, the impact on BP response should be tested in the remaining PEA R samples Further analyses should also assess the role of this haplotype on the BP response to atenolol when given as add on therapy. In the INVEST GENES case control cohort two ARRB1 SNPs were identified to alter the primary outcome a composite endpoint consisting of first occurrence of death, nonfatal MI, or nonfatal stroke. No ADRBK1 SNP remained statistically significant in the final model. However, this does not preclude that ADRBK1 SNPs alter adverse cardiovascular outcomes. I n particular the positively associated SNPs in the unadjusted model and the SNP alter ing BP response should be further evaluated on their effects on adverse cardiovascular outcomes if their findings remain significant in the entire PEAR cohort However INVEST might not be ideal to address these questions. The relative ly low number of black subjects could be one explanation why we were unable to detect an effect of ADRBK1 SNPs in the INVEST GENES case control cohort.
77 The findings with both ARRB1 SNPs a re difficult to explain. Although the C allele of first ARRB1 SNP ( rs542645 ) had a protective effect i n the overall cohort the findings did not remain significant after multiple testing is considered. This SNP was not associated with BP or HR response i n PEAR. It is located in intron 1 and a putative binding site for forkhead box C1 ( FOXC1 ). This transcription factor is expressed ubiquitously and plays an essential role in cardiac and renal morphogenesis. 99 However, it remains unclea r how ARRB1 expression is affected by rs542645. This SNP is also not in LD with other SNPs in the HAPMAP database In the calcium channel blocker arm, c arriers of the rs17133921 A allele had a n increase d risk to experience the primary outcome. It is als o located in intron 1, not in LD with other SNPs (CEU or YRI) and a putative binding site FOXC1 As the association is only seen the calcium channel blockers biased the increased risk of the allele. However the underlying biological function of this SNP remains unclear. In conclusion w e must temper our conclusions given the presence of some borderline findings suggesting the need for replication. One of these studies could be the remaining 372 samples in PEAR and the SNPs identified in this research (e.g. ADRBK1 rs1894111) and the ARRB1 CAT haplotype would be chosen a priori However recruitment is still going on
78 Table 5 1. PEAR: Genotyping quality control of the IBC chip and the custom SNP array Variable IBC chip Custom SNP array Samples genotyped 417 417 Sample excluded call rate<90% / contamination 1 3 sex gender mismatch 1 0 Project SNPs (Total) 8 ( 49,094 ) 63 (96) Project SNPs excluded GenTrainScore <0.3 0 3 call rate<90% 0 4 Project SNPs flagged (out of HWE)* blacks 0 2 whites 0 4 Abbreviations: IBC ITMAT/Broad/CARE HWE Hardy Weinberg equilibrium, SNP single nucleotide polymorphism HWE p value cut off: IBC chip: P<10 5 custom SNP array P<10 2 Table 5 2. PEAR : B aseline characteristics Both arms (N=418) ATEN ( N = 210 ) HCTZ ( N = 208 ) Age 50.18.8 49.79.0 50.58.6 Women 236 (56.5) 125 (59.5) 111 (53.4) White 237 (56.7) 121 (57.6) 116 (55.8) Black 167 (40.0) 82 (39.1) 85 (40.9) Asian 5 (1.2) 4 (1.9) 1 (0.5) Other/multiracial 9 (2.1) 3 (1.4) 6 (2.9) Duration of hypertension (years) 8.1 (7.7) 8.3 (7.7) 7.8 (7.7) Family history of hypertension 329 (78.7) 173 (82.4) 156 (74.9) Taking antihypertensive drug at entry 317 (75.84) 182 (86.6) 172 (82.9) BMI (kg/m 2 ) 31.05.7 31.26.3 30.95.0 SBP (mmHg) 146.010.8 144.510.3 147.511.2 DBP (mmHg) 93.66.4 92.66.3 94.56.4 HR (beats/min) 76.78.8 77.18.6 76.49.1 Abbreviations: ATEN atenolol, BMI body mass index, DBP diastolic blood pressure (home), HCTZ hydorchlorot hiazide, HR heart rate (home), SBP systolic blood pressure (home); Data are given as mean standard deviation or N (%)
79 Table 5 3 PEAR: SNPs identified to influence diastolic blood pressure reduction (monotherapy) Gene SNP name Race Arm dDBP AA [mmHg] dDBP AB [mmHg] dDBP BB [mmHg] Data P value (ANOVA) P value (LR) ADRBK1 rs4930416 black ATEN 3.116.51 7.485.84 unadjusted 0.0394 0.0394 adjusted* 0.0413 0.0413 black HCTZ 6.356.58 11.326.34 unadjusted** 0.0058 0.0058 adjusted*/** 0.0089 0.0089 ADRBK1 rs3730140 black ATEN 3.206.46 7.935.94 unadjusted 0.0468 0.0157 adjusted* 0.0322 0.0322 black HCTZ 6.846.87 10.116.04 21.67 unadjusted 0.0328 0.0168 adjusted* NS NS ADRBK1 rs10896164 white ATEN 9.545.74 7.954.79 23.75 unadjusted NS NS adjusted* 0.0191 NS ADRBK1 rs1894111 white HCTZ 4.264.79 11.293.74 u nadjusted ** 0.0016 0.0016 adjusted* /** 0.0034 0.0034 ARRB1 rs546812 black ATEN 6.192.75 5.615.83 2.036.90 unadjusted** 0.0445 0.0161 adjusted* NS NS white ATEN 10.135.99 10.175.57 6.365.28 unadjusted 0.0191 0.0319 adjusted* NS NS ARRB1 rs12274033 black ATEN 4.656.57 0.994.85 4. 12 unadjusted 0.0220 0.0182 adjusted* 0.0321 0.0299 Abbreviations: AA homozygote major allele, AB heterozygote, ANOVA analysis of variance, ATEN atenolol, B homozygote minor allele, dDBP delta diastolic blood pressure, HCTZ hydrochlorothiazide, LR linear regression, MAF minor allele frequency, NS P>0.05, SNP single nucleotide polymorphism blood pressure d ata are given as mean standard deviation adjusted for age, sex, body mass index and baseline diastolic blood pressure, ** associated with dS BP
80 Table 5 3 .Continued Gene SNP name Race Arm dDBP AA [mmHg] dDBP AB [mmHg] dDBP BB [mmHg] Data P value (ANOVA) P value (LR) ARRB1 rs1676884 black ATEN 4.166.05 0.818.39 unadjusted NS NS adjusted* 0.0325 0.0325 black HCTZ 6.136.52 11.576.17 unadjusted 0.0024 0.0024 adjusted* NS NS ARRB1 rs12721493 black HCTZ 7.796.67 1.688.02 unadjusted NS NS adjusted* /** 0.0223 0.0223 ARRB1 rs2276310 white ATEN 8.885.52 12.276.21 unadjusted 0.0132 0.0132 adjusted* 0.0163 0.0163 ARRB1 rs518115 white ATEN 8.026.29 10.425.57 7.584.85 unadjusted NS NS adjusted* 0.0256 NS ARRB1 rs2371216 white ATEN 4.742.67 8.465.76 10.315.73 unadjusted** 0.0439 0.0149 adjusted* NS NS ARRB1 rs526013 white ATEN 9.165.54 10.465.67 6.867.65 unadjusted NS NS adjusted* 0.0325 NS ARRB1 rs611908 white ATEN 8.706.27 10.805.65 8.555.70 unadjusted NS NS adjusted* 0.0213 NS ARRB1 rs578130 white HCTZ 6.194.71 5.124.99 2.844.56 unadjusted 0.0279 0.0093 adjusted* 0.0359 0.0122 Abbreviations: AA homozygote major allele, AB heterozygote, ANOVA analysis of variance, ATEN atenolol, B homozygote minor allele, dDBP delta diastolic blood pressure, HCTZ hydrochlorothiazide, LR linear regression, MAF minor allele frequency, NS P>0.05, SNP single nucleotide polymorphism blood pressure d ata are given as mean standard deviation adjusted for age, sex, body mass index and baseline diastolic blood pressure, ** associated with dS BP
81 Table 5 4 PEAR: SNPs identified to influence systolic blood pressure reduction (monotherapy) Gene SNP Race Arm dSBP AA [mmHg] dSBP AB [mmHg] dSBP BB [mmHg] Data P value (ANOVA) P value (LR) ADRBK1 rs49 30416 black HCTZ 11.299.76 16.848.83 unadjusted** 0.0337 0.0337 adjusted*/** 0.0492 0.0492 ADRBK1 rs1894111 white HCTZ 8.11 7.55 18.37 14.90 unadjusted** 0.0055 0.0055 adjusted*/** 0.0191 0.0191 ARRB1 rs546812 black ATEN 5.226.65 5.7110.27 1.1311.01 unadjusted** 0.0206 0.0091 adjusted* NS NS ARRB1 rs2371216 white ATEN 3.684.22 9.068.72 11.818.41 unadjusted** 0.0468 0.0157 adjusted* NS NS ARRB1 rs12721493 black HCTZ 12.779.53 8.5314.94 unadjusted NS NS adjusted* /** 0.0448 0.0448 ARRB1 rs527106 white ATEN 7.517.74 12.398.77 7.476.81 unadjusted NS NS adjusted* 0.0082 NS ARRB1 rs2510894 white ATEN 7.148.05 12.258.61 7.817.06 unadjusted NS NS adjusted* 0.0054 NS Abbreviations: AA homozygote major allele, AB heterozygote, ANOVA analysis of variance, ATEN atenolol, B homozygote minor allele, HCTZ hydrochlorothiazide, LR linear regression, NS P>0.05, SNP s ingle nucleotide polymorphism, dSBP delta systolic blood pressure ; blood pressure d ata are given as mean standard deviation adjusted for age, sex, body mass index and baseline systolic blood pressure, ** associated with dDBP
82 Table 5 5. ADRBK1 SNPs identified to influence heart rate response (monotherapy) Gene SNP name Race Arm dHR AA [beats/min] dHR AB [beats/min] dHR BB [beats/min] Data P value (ANOVA) P value (LR) ADRBK1 rs3730145 black HCTZ 0.356.59 3.304.95 5.544.53 unadjusted 0.0040 0.0010 adjusted* 0.0088 0.0023 ADRBK1 rs12274774 black HCTZ 0. 12 6. 41 3.21 4.9 9 5.54 4.53 unadjusted 0.0057 0.0013 adjusted* 0.0062 0.001 6 ADRBK1 rs2071007 black HCTZ 2.995.14 1.506.38 7.714.76 unadjusted 0.0073 0.0135 adjusted* 0.0093 0.0170 ADRBK1 rs11227756 black HCTZ 9.754.53 1.466.03 3.656.04 unadjusted 0.0087 0.0126 adjusted* 0.0330 0.0265 ADRBK1 703 T/C black HCTZ 0.156.60 3.914.76 4.814.01 unadjusted 0.0126 0.0047 adjusted* 0.0134 0.0134 ADRBK1 rs4370946 black HCTZ 0.206.62 3.304.90 6.184.24 unadjusted 0.0141 0.0034 adjusted* 0.0249 0.0073 ADRBK1 rs948988 black HCTZ 0.576.56 2.974.98 5.513.91 unadjusted 0.0395 0.0108 adjusted* 0.0337 0.0127 ADRBK1 rs3730309 black HCTZ 0.526.21 2.865.85 5.513.91 unadjusted 0.0478 0.0134 adjusted* 0.046 5 0.019 6 ADRBK1 rs12791853 white ATEN 12.335.39 15.584.62 unadjusted NS NS adjusted* 0.0387 0.0387 ADRBK1 rs10896164 white HCTZ 2.245.10 1.674.84 4.138.02 unadjusted 0.0334 0.0334 adjusted NS NS Abbreviations: AA homozygote A allele, AB heterozygote, ANOVA analysis of variance, ATEN atenolol, B homozygote B allele, dDBP delta diastolic blood pressure, HCTZ hydrochlorothiazide, LR linear regression, MAF minor allele frequency, NS P>0.05, SNP single nucleotide polymorphism heart rate d ata are given as mean standard deviation adjusted for age, sex, body mass index and bas eline diastolic blood pressure
83 Table 5 6 A RRB 1 SNPs identified to influence heart rate response (monotherapy) Gene SNP name Race Arm dHR AA [beats/min] dHR AB [beats/min] dHR BB [beats/min] Data P value (ANOVA) P value (LR) ARRB1 rs750465 white HCTZ 1.545.24 3.534.72 10.920 unadjusted 0.0419 0.0203 adjusted* NS 0.0375 ARRB1 rs512797 white HCTZ 3.195.35 1.144.29 1.735.76 unadjusted 0.0151 0.0039 adjusted* 0.0256 0.0069 ARRB1 rs578130 white HCTZ 3.705.82 1.844.15 0.116.37 unadjusted 0.0352 0.0095 adjusted* 0.0407 0.0157 ARRB1 rs1676887 white HCTZ 2.955.59 2.035.11 unadjusted 0.0205 0.0205 adjusted* NS NS ARRB1 rs643523 white ATEN 12.195.36 12.585.55 13.214.99 unadjusted NS NS adjusted* 0.0388 NS ARRB1 rs504683 black HCTZ 1.365.73 3.636.97 5.712.98 unadjusted NS NS adjusted* NS 0.0498 ARRB1 rs12274033 black ATEN 11.435.92 6.747.48 8.08 unadjusted NS NS adjusted* 0.0437 0.0130 Abbreviations: AA homozygote A allele, AB heterozygote, ANOVA analysis of variance, ATEN atenolol, B homozygote B allele, dDBP delta diastolic blood pressure, HCTZ hydrochlorothiazide, LR linear regression, MAF minor allele frequency, NS not significant (P>0.05), SNP sin gle nucleotide polymorphism heart rate d ata are given as mean standard deviation adjusted for age, sex, body mass index and baseline diastolic blood pressure
84 Table 5 7 INVEST: Baseline characteristics case control Variable Overall INVEST (N=22,576) INVEST GENES (N=5486) Cases (N=307) Controls (N=587) Age (years) 66.29.7 66.19.7 71.39.8 69.69.7 Women 11770 (52.1) 3047 (55.5) 149 (48.5) 265 (45.1) White 10925 (48.4) 2076 (37.8) 187 (61.0) 360 (61.3) Black 3029 (13.4) 588 (10.7) 43 (14.0) 86 (14.6) Hispanic 8045 (35.6) 2598 (47.4) 76 (24.8) 141 (24.0) Other/multiracial 577 (2.6) 224 (4.1) 1 (0.3) 0 (0) BMI (kg/m 2 ) 29.27.1 29.35.5 27.54.8 28.95.3 Myocardial infarction 7218 (32.0) 1281 (23.4) 112 (36.5) 166 (28.3) Stroke/TIA 1629 (7.2) 381 (6.9) 45 (14.7) 32 (5.5) Left ventricular hypertrophy 4948 (21.9) 823 (15.0) 56 (18.2) 85 (14.5) Heart failure (class I III) 1256 (5.6) 179 (3.3) 32 (10.4) 20 (3.4) Peripheral vascular disease 2699 (12.0) 607 (11.1) 53 (17.3) 44 (7.5) Smoker 12122 (53.7) 3221 (58.7) 161 (52.4) 233 (39.7) Diabetes 6401 (28.4) 1542 (28.1) 115 (37.5) 143 (24.4) Hypercholesterolemia 12448 (55.1) 2998 (54.7) 190 (61.9) 370 (63.0) Renal impairment 424 (1.9) 85 (1.6) 18 (5.8) 6 (1.0) Revascularization > 1month 6166 (27.3) 783 (14.3) 73 (23.78) 102 (17.38) SBP (mmHg) 150.919.5 148.018.4 150.318.5 146.718.2 DBP (mmHg) 87.211.9 85.410.7 83.2811.1 83.3210.7 Abbreviations: BMI body mass index, DBP diastolic blood pressure, SBP systolic blood pressure, TIA transient ischemic attack; Data are given as mean standard deviation or n (%)
85 Table 5 8. INVEST: SNPs identified to influence primary outcome (case control substudy) Gene SNP MA RA Status WT HET VA Arm Odds ratio 95% Confidence intervall P value ARRB1 rs542645 C T Case 280 18 2 ALL 0.517 0.307 0.869 0.0128 Control 492 64 4 CCB 0.501 0.244 1.027 NS BB 0.529 0.248 1.128 NS ALL* 0.499 0.288 0.867 0.0136 CCB* 0.487 0.227 1.047 NS BB 0.505 0.227 1.122 NS ARRB1 rs17133921 A G Case 121 42 2 ALL 1.279 0.901 1.816 NS Control 203 41 1 CCB 1.758 1.089 2.838 0.0210 BB 0.820 0.475 1.417 NS ALL* 0.956 0.661 1.382 NS CCB* 1.943 1.155 3.268 0.0123 BB 0.674 0.368 1.235 NS ADRBK1 703 T/C C T Case 120 15 4 ALL 1.444 0.914 2.280 NS Control 291 22 1 CCB 1.025 0.535 1.963 NS BB 2.020 1.061 3.847 0.0323 ALL* 1.560 0.884 2.754 NS CCB* 1.291 0.542 3.077 NS BB 1.854 0.857 4.009 NS Abbreviations: ALL both treatment strategies, B B blocker strategy CCB calcium channel blocker strategy, HET heterozygote, MA minor allele, NS P value greater than 0.05, RA reference allele, SNP single nucleotide polymorphism VA homozygot e minor allele, WT homozygote common allele adjusted for age, sex, race/ethnicity, previous myocardial infarction prior heart failure, model also used a stepwise selection proced ure with the following variables: body mass index previous stroke or transient ischemic attack, history of peripheral vascular disease, smoking, diabetes, renal insufficiency, and coronary artery bypass graft surgery
86 Figure 5 1 Blood pressure (BP) response to atenolol monotherapy by A DRBK 1 rs1894111 geno type. Data are presented as mean change from baseline with standard error. Dark bars ADRBK1 rs1894111 G/G ; light bars ADRBK1 rs189 4111 G/A; white bars ADRBK1 rs1894111 A/A SBP systolic blood pressure; DBP diastolic blood pressure Statistical comparisons between ADRBK1 genotype groups were adjusted for baseline BP, age, sex and body mass index
87 Figure 5 2 Blood pressure (BP) response to hydrochlorothiazide by ADRBK1 rs1894111 genotype Data are presented as mean change from baseline with standard error. Dark bars ADRBK1 rs1894111 G / G ; light bars ADRBK1 rs1894111 G/A; white bars ADRBK1 rs18941 11 A/A SBP systolic blood pressure; DBP diastolic blood pressure; Asterisk denotes P = 0.0191 Dagger denotes P = 0.0034 Statistical comparisons between ADRBK1 genotype groups were adjusted for baseline BP, age, sex and body mass index
88 Figure 5 3 B lood pressure (BP) response to atenolol monotherapy by ARRB1 CAT haplotype. Data are presented as mean change from baseline with standard error. Dark bars ARRB1 CAT carriers ( 1 or 2 copies of the ARRB1 CAT haplotype); light bars ARRB1 no CAT ( no copy of the ARRB1 CAT haplotype ) SBP systolic blood pressure; DBP diastolic blood pressure; Asterisk denotes P = 0.0207 Dagger denotes P = 0.0173 Statistical comparisons between ARRB1 CAT carriers and ARRB1 no CAT were adjusted for baseline BP, age, sex and body mass index
89 Figure 5 4 Blood pressure (BP) response to hydrochlorothiazide monotherapy by ARRB1 CAT haplotype. Data are presented as mean change from baseline with standard error. Dark bars ARRB1 CAT carriers (1 or 2 copies of the ARRB1 CAT haplotype); light bars ARRB1 no CAT (no copy of the ARRB1 CAT haplotype). SBP systolic blood pressure; DBP di astolic blood pressure; Statistical comparisons between ARRB1 CAT carriers and ARRB1 no CAT were adjusted for baseline BP, age, sex and body mass index
90 Figure 5 5 Adjusted odds ratio for minor allele carriers on p robability of experiencing the INVEST primary outcome (first occurrence of death, nonfatal myocardial infarction, or stroke). Odds ratios smaller than 1 indicate lower likelihood of minor allele carriers experiencing the INVEST primary outcome. Odds rati os greater than 1 indicate greater likelihood of minor allele carriers experiencing the INVEST primar y outcome. ALL entire cohort, BB blocker strategy, CCB calcium channel blocker strategy. Asterisk denotes P = 0.0136 Dagger denotes P = 0.0123 Statistical comparisons are between patients who were homozygote for the common allele and patients who were minor allele carriers. Analyses were adjusted for age, sex, race/ethnicity, previous myocardial infarction prior heart failure; the model also us ed a stepwise selection procedure with the following variables: body mass index previous stroke or transient ischemic attack, history of peripheral vascular disease, smoking, diabetes, renal insufficiency, and coronary artery bypass graft surgery
91 CHA PTER 6 SUMMARY AND CONCLUSION This study was significant from a number of perspectives. First, our stud y identified a new polymorphism in the promoter region ADRBK1 and provided comprehensive SNP data for the common SNPs in the two major ancestral populations. However this SNP ( ADRBK1 703 T>C ) ARK1 expressi on in lymphoblastoid cell lines In addition, the association with the primary outcome blocker strategy did not hold after adjusting for other clinical factors. T his was also the first comprehensive study to assess whether genetic variations of ADRBK1 or ARRB1 contribute to the variability in blood pressure response in patients treated blockers. In addition, we investigate d whether genetic variations in ADRBK1 and ARRB1 have influence on death, myocardial infarction or stroke in treated hypertensive patients. In PEAR, African American p atients with one or two copies of ARRB1 CAT haplotype had better response to atenolol than African American patients with no copy of the ARRB1 CAT haplotype Additionally, rs1894111 in ADRBK1 was shown to influence blood pressure response in whites receiv ing hydrochlorothiazide. However, rs1894111 is only present in 1.3% of the white population have and our findings need to be replicated in a larger population. In INVEST two ARRB1 SNPs were identified. The first SNP (rs542645) was associated with a redu ced risk for the primary outcome in the entire cohort. The second SNP showed a risk increase of the primary outcome in patients assigned to calcium channel blocker strategy. However, the exact mechanism of action of these polymorphisms remains unclear. M ost importantly, most of our clinical associations represent borderline findings that do not hold significance after adjusting for multiple tests. In addition, all SNPs are intronic and
92 some SNPs are not in linkage with other SNPs in putative functional r egions making it difficult to draw conclusion about the functionality of these SNPs I n conclusion, the genotype/haplotype phenotype associations of this study should be considered exploratory. Thus, these SNPs might be included as candidate SNPs in fur ther research studies assess ing the role of genetic variations on the response to antihypertensive therapy or on the risk for clinical outcomes like death nonfatal myocardial infarction or nonfatal stroke. As PEAR is still ongoing, this study might be considered to further assess the impact of these ADRBK1 or ARRB1 candidate SNPs.
93 APPENDIX Table A 1 Samples used for sequencing Catalog ID Race Catalog ID Race NA18516 black NA00536 white NA18517 black NA00546 white NA19035 black NA00558 white NA19036 black NA00607 white NA19206 black NA00621 white NA19207 black NA00893 white NA19238 black NA06991 white NA19239 black NA07019 white NA19309 black NA07029 white NA19310 black NA07048 white NA19444 black NA07348 white NA19445 black NA10846 white NA19700 black NA10847 white NA19701 black NA10851 white NA19916 black NA10854 white NA19917 black NA10855 white NA20340 black NA10856 white NA20341 black NA10857 white NA17140 black NA10859 white NA17141 black NA10865 white NA17142 black NA12335 white NA17143 black NA12336 white NA17132 black NA12375 white NA17131 black NA12376 white
94 Table A 2. Primer sequences, amplicon sizes, and annealing temperatures for Sanger and 454 Sequencing SEQ M ethod Covered region* Primer sequence Primer type Ta [C] Amplicon size [bp] Position start** Position end** Sanger GGAGGTGAGTCTTAGCGGATG Forward 57 544 66788506 66789050 CGCCACCCATATACCCATGTC Reverse GTATATGGGTGGCGAGTGACTCA Forward 58 532 66789036 66789568 AAGGCCCACTCAGGATCAA Reverse ACAGGGAAGGGAGCTGCCAAGAG Forward 61 485 66789468 66789953 AACGCCATACCCAGACTGC Reverse TGGGGGTCTGAGGTGAGTGTCGC Forward 63 690 66789912 66790602 exon1 CTCGCCGCCGCTCACAG Reverse exon 20 ATTTTGCAGTGCGATGTGAGT Forward 55 823 66809221 66810044 exon 21 CCCTTATTCAGGAAAAGCC Reverse exon 21 CGGGTGCCCAAGATGAAGAAC Forward 59 683 66809405 66810088 CGCAGTGTCAGGGAAGTGGGAGT Reverse exon 21 TCCACAGTGTTGGCGAGAG Forward 60 707 66809948 66810655 UTR CAGAAGCTGAAAAGGGGTCAC Reverse 454 TTGGGCAGAGTGTGGTGAGTCCTA Forward 61 2160 66788730 66790890 exon 1 TACCTGATGGCCATGGAGAAGA Reverse exon 1 GGATCCAGAGATGTGACCCGAGGTT Forward 61 2188 66790208 66792396 intron 1 GGCCTTTTCAAAATGCAGACCAA Reverse intron 1 GCCGCCTCTGTAAGACAACTG Forward 60 3991 66791669 66795660 TCAAATGTCACGGCTTCTTCACAAA Reverse intron 1 ACTCTGCTGCAACTGAGATACTAAAA Forward 59 11040 66795300 66806340 exon12 GCTTCTTCTTGGAGAAGTCACAGG Reverse exon 11 GGAGCACATGCACAACCGCTTCGT Forward 64 6696 66805956 66812652 3 TTGAGGAGGGCCAGCTAGCTTGAG Reverse Abbreviation s : bp basepair, SEQ sequencing, Ta annealing temperature, UTR untranslated region Sanger SEQ cover e region, 1434 bp exon 20 SEQ covered 23922 bp ** Position on chromosome 11
95 Table A 3. Sequencing primer sequences, amplicon sizes, and annealing temperatures for confirmed SNPs Covered SNPs (region) Primer sequence Primer type Ta [C] Amplicon size [bp] Position start* Position end* rs11227756, rs12805999 (exon1 intron1) ACCTGGAGGCGGTGCTGG Forward 65 590 66790753 66791343 AAGCGAGTGCCGTGAGCAGGGAC Reverse rs948988, rs4930416 (intron2) GGCCCTCTTTGTAAGCAAC Forward 58 576 66801791 66802367 TCCAGTCTGACACGGGTAACCAG Reverse rs3730309, rs3730310 (intron5 intron 6) CTGTGTGCTGGCCCAGAGTCA Forward 60 600 66803587 66803587 GGAGCTAGGAGACTGCCAG Reverse rs3730145, rs2071007 (exon13 intron14) GCCGACTGGTTCTCTCTGGG Forward 58 465 66806542 66807007 GGGCAGGAGGTCTGTCTCAGAGG Reverse Abbreviations: bp basepairs, Seq Sequencing, SNP single nucleotide polymorphism, Ta annealing temperature Position on chromosome 11
96 Table A 4. Pyrosequencing primer sequences,and annealing temperatures SNPs to be confirmed and in the expression study Covered SNPs Primer sequence Primer type Ta [C] rs1894111 CGCTTGGCTGTTGCTTTCA Forward 58 [BioTEG] CATCCAGCAGTGGAAACTGACC Reverse CACAGTGTAGCCCTTGA SEQ rs7128315 TTGGGGGCCTTCCATTCA Forward 58 [BioTEG] ATTCTTCCCAGCCCACAGC Reverse TCTTTTTAAGGAAGAAAGT SEQ rs1274774 [BioTEG] GGCCCCAACCCAGAATCC Forward 58 ACAGAGCCACGCCTCTCTCA Reverse AAGGCTGCTGCCAAC SEQ rs1977982 [BioTEG]AAAGAGAGCCCCTTTTTCCG Forward 54 TCATCGAAGGAGCCAATGT Reverse GCCGCAGACTGTTAC SEQ rs10896164 TCTCTCGCCTCAGACTACGC Forward 60 [BioTEG] GGGTGGTGCAGGTAAGAGC Reverse GGCCCCGGTAAGGAG SEQ rs4390416* [BioTEG] GGGGAGTCGGTGTGTCAAG Forward 60 GCGGCCATCATTTCAGTC Reverse CACAGTCGGACTCATG SEQ 703 T/C AAGGATTCTGGGTCCAGTGTG Forward 58 [ BioTEG] CTCGATCCCATCCTGGTTACTG Reverse AGTCCTGACCCCAAG SEQ Abbreviations: BioTEG biotin tetraethylene glycol bp basepairs, Seq Sequencing, SNP single nucleotide polymorphism, Ta annealing temperature SNP to be genotyped for the expression study
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105 BIOGRAPHICAL SKETCH Maximilian Thomas Lobmeyer was born and raised in Regensburg, Germany. He holds a Bachelor of Pharmacy degree from the University of Regensburg. In 2004, he started the clinical pharmaceutical sciences graduate program in the Department of Pharmaceutics a t University of Florida, Gainesville. Maximilian has authored and coauthored several peer reviewed publications and presented at national and international conferences. He worked under the supervision of Dr. Julie Johnson on b locker pharmacogenomics.