CYP2C9, VKORC1 AND CYP4F2 VARIANT FREQUENCIES IN PATIENTS ON EITHER LOW OR HIGH STABLE WARFARIN MAINTENANCE THERAPY IN THE GHANAIAN POPULATION BY SAMUEL YAO AHORHORLU (10363287) THIS THESIS IS SUBMITTED TO THE UNIVERSITY OF GHANA, LEGON IN PARTIAL FULFILLMENT OF THE REQUIREMENT FOR THE AWARD OF MPHIL MEDICAL BIOCHEMISTRY DEGREE MARCH, 2014 University of Ghana http://ugspace.ug.edu.gh I DECLARATION I, Samuel Yao Ahorhorlu of the Department of Medical Biochemistry, University of Ghana Medical School, do hereby declare that, with the exception of quoted articles and references, this work was duly carried out by me and the results obtained herein are true reflection of the work done under the supervision of Dr. Bartholomew Dzudzor at the Department of Medical Biochemistry of the University of Ghana Medical School, Dr. William Kudzi at the Center for Tropical Clinical Pharmacology and Therapeutics of the University of Ghana Medical School and Dr. Edeghonghon Olayemi at the Department of Haematology, University of Ghana Medical School. Signature: ……………………………...Date…………………………… Samuel Yao Ahorhorlu (Student) Signature:……………………………....Date…………………………… Dr. Bartholomew Dzudzor (Supervisor) Signature:……………………………….Date…………………………… Dr. William Kudzi (Supervisor) University of Ghana http://ugspace.ug.edu.gh II DEDICATION I dedicate this work to Emefa my beloved wife for her understanding, care and support during the long hours of absence from home in pursuit of this research work. Thanks a lot “Sweetness”. I also dedicate this work to my parents Mr. George K. Ahorhorlu and Mrs. Alice Kwadzo for their love and care. University of Ghana http://ugspace.ug.edu.gh III ACKNOWLEDGEMENTS My profound gratitude goes to my Lord and Savior Jesus for granting me strength in the inner man to execute this research successfully. My heartfelt thanks also go to Dr. William Kudzi at Center for Tropical Clinical Pharmacology and Therapeutics (CTCPT) of the University of Ghana Medical School for conceiving this work and going the extra mile to provide all the reagents and materials needed to carry out this work. I am also very grateful to Dr. Bartholomew Dzudzor at the Department of Medical Biochemistry of the University of Ghana Medical School for his technical guidance, support and encouragement during the pursuit of this research. My sincere thanks also go to Dr. Edeghonghon Olayemi at the Department of Haematology of the University of Ghana Medical School for his role in screening patients for recruitment into the project as well as his guidance and support. I also thank Richard Harry Asmah at the Department of Medical Laboratory Sciences, School of Allied Health Sciences of the University of Ghana for his role in optimizing protocols used in this research. To all staff of the Anticoagulation Laboratory at the Cardiothoracic Center of the Korle-Bu Teaching Hospital, I say thank you for your role in the sampling process. I also thank Dr. Achel and all staff of RAMSRI Applied Radiation Biology Center of Ghana Atomic Energy Commission (GAEC) for their support during the laboratory analysis of the research samples. I extend special thanks to Mr. Rudolf Mba at GAEC for his uncommon help and support during the laboratory analysis of the research samples. Dr. George Obeng Adjei, Dr N.B. Quashie and all staff of the Center for Tropical Clinical Pharmacology and Therapeutics are duly acknowledged for their support and guidance during this research work. My utmost gratitude goes to Mr. Gideon Wise Ahorhorlu for his care, guidance and support throughout my entire life. May the good Lord bless you all. University of Ghana http://ugspace.ug.edu.gh IV ABSTRACT Warfarin is the most commonly prescribed oral anticoagulant drug for reducing thromboembolic events that often give rise to stroke, deep vein thrombosis, pulmonary embolism, or serious coronary malfunctions. Warfarin has a narrow therapeutic / toxic ratio and genetic factors have been associated with inter-individual variability in warfarin dose / response in different ethnic populations. The initiation of this drug has been associated with one of the highest adverse event rates for any single drug, particularly in the elderly. The aim of this study was to determine the frequency of CYP2C9, VKORC1 and CYP4F2 variant alleles in the Ghanaian population as bases to estimate the potential impact of these polymorphisms on warfarin maintenance dose. The study also sought to determine the clinical and demographic factors associated with warfarin maintenance dose in indigenous Ghanaian patients. One hundred and forty three adult Ghanaian patients on stable warfarin therapy at the Korle-Bu Teaching Hospital were genotyped for CYP2C9 (*2, *3), CYP4F2 rs2108622, and VKORC1_1639G > A polymorphisms using PCR-RFLP assay methods. The most common indications for warfarin use were valve replacement (n = 63, 44%), deep vein thrombosis (n = 52, 36.4%), pulmonary embolism (n = 18, 12.6%), and atrial fibrillation (n = 10, 7.0%). Warfarin dose was negatively correlated with patient age but not statistically significant (r = - 0.024, 95% CI (-0.052-0.004), p = 0.090). Women were found to be taking a higher mean daily warfarin dose of 5.75mg (95% CI, 5.174-6.326) than males who took 5.46mg (95% CI, 4.907-6.022) although this was not statistically significant, p = 0.479). Warfarin dose was positively correlated with patient height but not statistically significant (r = 0.010, [-0.031- 0.052], p = 0.630). BMI was found to have no influence on mean daily warfarin dose (OR: 0.571, p = 0.513) in this study population. Allelic frequencies for CYP2C9*3 were observed University of Ghana http://ugspace.ug.edu.gh V at (23%) while genotype frequencies for CYP2C9*3 were observed at (10.87%). CYP2C9*2 alleles and genotypes were not detected in this study population. Allele frequencies for VKORC1_1639A were observed at (6%) however, the VKORC1_1639A genotype was not detected in this study. Allele frequencies for CYP4F2 rs2108622 (T) was observed at (41%) and its genotype (T/T) frequencies were observed at (6.84%). According to the combined effect of the CYP2C9, VKORC1 and CYP4F2 genotypes, patients having the wild-type (*1/*1) genotype of CYP2C9 in combination with the homozygous mutant (T/T) genotype of CYP4F2 and the wild-type (G/G) genotype of VKORC1 required the highest mean daily warfarin dose of 7.50mg/day (95% CI, 7.50-7.50, p = 0.096). It was also observed that patients with a combination of CYP2C9 wild-type (*1/*1), CYP4F2 wild-type (C/C) and VKORC1 wild-type (G/G) genotypes were treated with the lowest mean daily warfarin dose of 4.79mg/day (95% CI, 3.02-6.55, p = 0.096). Interestingly, carriers of the heterozygous genotype of CYP2C9*1/*3, and CYP4F2 (C/T), and VKORC1 wild-type (G/G) genotype were given 6.50mg (95% CI, 5.40-7.60, p = 0.027). This study has established for the first time the combined effect of genotypes of CYP2C9, VKORC1 and CYP4F2 genes on mean daily warfarin dose in Ghanaian patients. VKORC1 and CYP4F2 variant alleles to our knowledge are being reported for the first time among the indigenous Ghanaian population. University of Ghana http://ugspace.ug.edu.gh VI TABLE OF CONTENTS DECLARATION ................................................................................................................................ I DEDICATION .................................................................................................................................. II ACKNOWLEDGEMENTS ............................................................................................................. III ABSTRACT ..................................................................................................................................... IV LIST OF TABLES ........................................................................................................................... XI LIST OF FIGURES ...................................................................................................................... XIII ABBREVIATIONS ...................................................................................................................... XIV CHAPTER ONE ................................................................................................................................ 1 1.0 INTRODUCTION ....................................................................................................................... 1 1.1 Background .................................................................................................................................. 1 1.2 Pharmacogenetics and Warfarin maintenance dose ..................................................................... 3 1.2.1 CYP2C9 and Warfarin maintenance dose................................................................................. 4 1.2.2 CYP4F2 and Warfarin maintenance dose ................................................................................. 5 1.2.3 VKORC1 and Warfarin maintenance dose ............................................................................... 5 1.2.4 Clinical Implications of the Genetic Mutation .......................................................................... 7 1.3 Problem Statement ..................................................................................................................... 10 1.4 Justification ................................................................................................................................ 11 1.5 Aim ............................................................................................................................................. 11 1.6 Specific Objectives..................................................................................................................... 11 University of Ghana http://ugspace.ug.edu.gh VII CHAPTER TWO ............................................................................................................................. 13 2.0 LITERATURE REVIEW .......................................................................................................... 13 2.1 Genetic Effect on Drug Efficacy ................................................................................................ 13 2.2 Pharmacogenetics and Pharmacogenomics................................................................................ 14 2.3 Warfarin’s Mechanism of Action............................................................................................... 15 2.4 Pharmacokinetics and Pharmacodynamics of Warfarin ............................................................ 16 2.5 Warfarin Multiple Interactions with other Drugs, Diet, and Disease States .............................. 18 2.5.1 Concomitant diseases .............................................................................................................. 19 2.6 INR Monitoring and Warfarin dose determination .................................................................... 19 2.6.1 Adherence, missed doses ........................................................................................................ 19 2.7 The Cytochrome P450 2C9 Gene .............................................................................................. 20 2.8 The Vitamin K Epoxide Reductase complex subunit 1 Gene (VKORC1) ................................ 24 2.9 The Cytochrome P450 4F2 Gene (CYP4F2) ............................................................................. 25 2.10 Pharmacogenomics in Africa ................................................................................................... 25 2.11 Amplicon sizes of Genes under study and the Expected Restriction digest fragment Sizes ... 26 2.12 Hardy-Weinberg Equilibrium (HWE) Determinations ............................................................ 28 2.12.1 Hardy-Weinberg Equation .................................................................................................... 29 CHAPTER THREE .......................................................................................................................... 31 3.0 METHODS ................................................................................................................................ 31 3.1 Study Design .............................................................................................................................. 31 University of Ghana http://ugspace.ug.edu.gh VIII 3.2 Study site and study population ................................................................................................. 31 3.3 Inclusion Criteria ........................................................................................................................ 32 3.4 Exclusion Criteria....................................................................................................................... 32 3.5 Procedures .................................................................................................................................. 32 3.5.1 INR Measurement ................................................................................................................... 33 3.5.2 Genomic DNA Extraction ....................................................................................................... 34 3.5.3 Genotyping .............................................................................................................................. 34 3.5.4 PCR for Genes under study ..................................................................................................... 35 3.5.5 Gel Electrophoresis of PCR Products ..................................................................................... 35 3.5.6 PCR protocol for CYP4F2 rs2108622 .................................................................................... 36 3.5.7 PCR protocol for VKORC1 _1639G ˃ A ............................................................................... 37 3.5.8 PCR protocol for CYP2C9*2 .................................................................................................. 38 3.5.9 PCR protocol for CYP2C9*3 .................................................................................................. 39 3.5.10 Restriction Fragment Length Polymorphism (RFLP) For Genes under Study ..................... 40 3.6 Statistical Analysis ..................................................................................................................... 40 CHAPTER FOUR ............................................................................................................................ 41 4.0 RESULTS .................................................................................................................................. 41 4.1 Demographic and Clinical Data ................................................................................................. 41 4.2 PCR-RFLP Gel Electrophoreses Results ................................................................................... 43 4.3 Allele and Genotype Frequencies for CYP2C9 ......................................................................... 45 University of Ghana http://ugspace.ug.edu.gh IX 4.3.1 CYP2C9*3 .............................................................................................................................. 45 4.3.2 CYP2C9*2 .............................................................................................................................. 46 4.4 Allele and Genotype Frequencies for VKORC1 ........................................................................ 47 4.4 Allele and Genotype Frequencies for CYP4F2 .......................................................................... 48 4.5 Prevalence of CYP2C9, VKORC1 and CYP4F2 genotypes and Mean Daily Warfarin Dosage .............................................................................................................................................. 49 4.6 The Mean Daily Warfarin Dosage According to Combined CY2C9, VKORC1 and CYP4F2 Gene Variants .................................................................................................................... 50 CHAPTER FIVE .............................................................................................................................. 53 5.0 DISCUSSION AND CONCLUSIONS ..................................................................................... 53 5.1 DISCUSSION ............................................................................................................................ 53 5.2 LIMITATIONS .......................................................................................................................... 59 5.3 CONCLUSIONS ........................................................................................................................ 59 5.4 RECOMMENDATIONS ........................................................................................................... 60 REFERENCES ................................................................................................................................. 61 APPENDIX I .................................................................................................................................... 78 PRIMER SEQUENCES, AMPLICON SIZES AND RESTRICTION ENZYMES USED ............ 78 APPENDIX II .................................................................................................................................. 79 COMMON POTENTIAL DRUG-DRUG INTERACTIONS WITH WARFARIN ....................... 79 APPENDIX III ................................................................................................................................. 81 University of Ghana http://ugspace.ug.edu.gh X CONSENT FORM ........................................................................................................................... 81 APPENDIX IV ................................................................................................................................. 83 DATA COLLECTION SHEET ....................................................................................................... 83 APPENDIX V .................................................................................................................................. 86 REAGENTS AND MATERIALS USED ........................................................................................ 86 APPENDIX VI ................................................................................................................................. 88 PREPARATION OF REAGENTS .................................................................................................. 88 Primer stock solutions ...................................................................................................................... 88 Working Primer solutions ................................................................................................................ 90 Preparation of dNTP Set .................................................................................................................. 91 Preparation of 0.5M Ethylenediaminetetra acetic acid (EDTA) ...................................................... 91 Preparation of 50X Tris-acetate-EDTA (TAE) Buffer Stock .......................................................... 91 Preparation of 1X TAE Buffer from 50X TAE Buffer Stock .......................................................... 92 Two Percent (2%) Agarose Gel Preparation and Casting ................................................................ 92 University of Ghana http://ugspace.ug.edu.gh XI LIST OF TABLES Table 1.1: CYP2C9 and VKORC1 Polymorphism and Sensitivity……………………………8 Table 2.1: CYP2C9 Genotyping with Restriction Enzymes………………………………….28 Table 3.1: Reaction Composition / mix for CYP4F2…………………………………………36 Table 3.1.1: Thermal Cycling conditions for CYP4F2……………………………………….36 Table 3.2: Reaction Composition / mix for VKORC1...….………………………………….37 Table 3.2.1: Thermal Cycling conditions for VKORC1……………………………………...37 Table 3.3: Reaction Composition / mix for CYP2C9*2……………………………………...38 Table 3.3.1: Thermal Cycling conditions for CYP2C9*2……………………………………38 Table 3.4: Reaction Composition / mix for CYP2C9*3……………………………………...39 Table 3.4.1: Thermal Cycling conditions for CYP2C9*3……………………………………39 Table 4.1: Comparison of High and Low Warfarin dose Patient Populations………………..42 Table 4.2: Relationship between some patient-specific factors and daily warfarin dose ……42 Table 4.3: Gender versus Mean daily warfarin dose (mg)……………………………………43 Table 4.4: Allele and Genotype Frequencies of CYP2C9*3…………………………………46 Table 4.5: Allele and Genotype frequencies for CYP2C9*2 …….…………………………..47 Table 4.6: Allele and Genotype Frequencies for VKORC1………………………………….48 Table 4.7: Allele and Genotype Frequencies for CYP4F2…………………………………...49 University of Ghana http://ugspace.ug.edu.gh XII Table 4.8: The prevalence of CYP2C9, VKORC1 and CYP4F2 Genotypes and Mean Daily Warfarin Dosage……………………………………………………………………………...50 Table 4.9: The Mean Daily Warfarin Dosage According to Combined CYP2C9, VKORC1 and CYP4F2 Gene Variants………………………………………………………………….51 Table 4:10: Frequency distribution for CYP2C9 alleles in Ghanaian and other previously studied populations…………………………………………………………………………...52 University of Ghana http://ugspace.ug.edu.gh XIII LIST OF FIGURES Figure 2.1: How warfarin blocks the vitamin K Cycle………………………………………16 Figure 2.2: Genes involved in the pharmacokinetics and pharmacodynamics of warfarin….18 Figure 4.1: CYP4F2 PCR-RFLP Gel Electrophoregram…………………………………….43 Figure 4.2: VKORC1 PCR-RFLP Gel Electrophoregram…………………………………..44 Figure 4.3: CYP2C9*2 PCR-RFLP Gel Electrophoregram…………………………………44 Figure 4.4: CYP2C9*3 PCR-RFLP Gel Electrophoregram…………………………………45 University of Ghana http://ugspace.ug.edu.gh XIV ABBREVIATIONS ADRs Adverse Drug Reactions AF Atrial Fibrillations CYP2C9 Cytochrome P450 isoenzyme 2C9 CYP4F2 Cytochrome P450 isoenzyme 4F2 dATP Deoxyadenosine triphosphate dCTP Deoxycytidine triphosphate dGTP Deoxyguanosine triphosphate DMEs Drug Metabolizing Enzymes DNA Deoxyribonucleic acid dNTPs Deoxynucleotide triphosphates dTTP Deoxythymidine triphosphate EDTA Ethylenediaminetetra acetic acid EtBr Ethidium Bromide HGP Human Genome Project HWE Hardy-Weinberg Equilibrium INR International Normalized Ratio KBTH Korle-Bu Teaching Hospital PCR Polymerase Chain Reaction PGENI Pharmacogenetics for Every Nation Initiative RFLP Restriction Fragment Length Polymorphism University of Ghana http://ugspace.ug.edu.gh XV SNPs Single Nucleotide Polymorphisms TAE Tris acetate EDTA Taq Thermus aquaticus USA United States of America VKORC1 Vitamin K Epoxide Reductase complex subunit 1 University of Ghana http://ugspace.ug.edu.gh 1 CHAPTER ONE 1.0 INTRODUCTION 1.1 Background Variations in the response of patients to medications have been noticed and documented since the 1950s (Alving et al., 1956). This observation has been partly explained by factors such as age, body size, race, concurrent diseases, medications and genes of patients. Polymorphisms in genes coding for Drug Metabolizing Enzymes (DMEs) has also been shown to significantly influence patients’ variability in drug response (Wadelius et al., 2007). Increasing numbers of relevant polymorphisms are being discovered. It is also known that the frequencies and distributions of both harmful and protective polymorphisms vary greatly between human populations (Nebert & Menon, 2001; Wilson et al., 2001). Given all the above, it is valid to study traits that are predominantly expressed in specific populations (Nebert & Menon, 2001). It has also been established that genetic variations within DMEs, drug transporters and drug targets do influence both the efficacy of drugs and the likelihood of Adverse Drug Reactions (ADRs) (Pirmohamed & Park, 2003). Knowledge of the allelic frequency distribution within a specified population can be useful in identifying potential risk groups for ADRs and appropriate dose adjustments could be made to achieve therapeutic efficacy. Warfarin is the most commonly prescribed oral anticoagulant drug for reducing thromboembolic events that often give rise to stroke, deep vein thrombosis, pulmonary embolism, or serious coronary malfunctions (Daly & King, 2003). Although it has been used University of Ghana http://ugspace.ug.edu.gh 2 for more than 50 years, initiation of therapy remains problematic because of inter-individual variability in the degree of anticoagulation achieved in response to standard warfarin dose. An appropriate warfarin dose in one patient may induce a haemorrhagic event in another. Warfarin has a narrow therapeutic window between too much and too little effect such that a small change in its dose can have quite a large effect on blood coagulation (Takahashi et al., 2006b). For instance, overdosing and under-dosing can result in life-threatening events such as bleeding or thrombosis. It is estimated that 1% of patients die due to bleeding complications associated with warfarin and up to 15% of patients experience minor bleeding complications (Takahashi et al., 2006b). Warfarin initiation has been associated with one of the highest adverse event rates for any single drug, particularly in the elderly (Takahashi et al., 2006b). Physicians, therefore, find it very challenging to initiate therapy in patients where it is needed. It has been estimated that almost half of all atrial fibrillation (AF) patients who are eligible for and would benefit from warfarin therapy are not receiving the drug because of the associated risks and monitoring costs (Gedge et al., 2000). The efficacy of warfarin is dependent on maintaining a patient’s anticoagulation within acceptable therapeutic range. Dose adjustments are often necessary and are based on measuring the prothrombin time in blood and calculating the International Normalized Ratio (INR), which gives an indication of the time it takes for the patient’s blood to clot. Genetic factors have been associated with inter-individual variability in warfarin dose in different ethnic populations (Kamali et al., 2004). University of Ghana http://ugspace.ug.edu.gh 3 1.2 Pharmacogenetics and Warfarin maintenance dose Warfarin is an anticoagulant used in the prevention of thrombosis (the abnormal formation of blood clot in living vessels) and thromboembolism (the migration of blood clot in blood vessels to other parts of the body). It was introduced in 1948 as a pesticide against rats and mice but was found in the early 1950s to be effective and relatively safe for preventing thrombosis and embolism (Holbrook et al., 2005). Warfarin exists as a racemic mixture of two enantiomers (optical isomers) in equal amounts (Buckley & Dawson, 1992). These enantiomers are metabolized by different pathways and have different half-lives and potencies. The S (-) enantiomer of warfarin is 3-5 times more potent than the R (+) enantiomer (Buckley & Dawson, 1992). The cytochrome P450 2C9 subfamily is responsible for the metabolism of S-warfarin. The cytochrome P450 isozymes 1A2, 3A4 and 2C are responsible for the metabolism of R- warfarin. S-warfarin is almost entirely oxidized to form S-7-hydroxywarfarin and some S-6- hydroxywarfarin (Buckley & Dawson, 1992). R-warfarin is oxidized and reduced to R-6- hydroxywarfarin and some R-7- hydroxywarfarin via the oxidative pathway and R, S-warfarin alcohol via the reductive pathway (Buckley & Dawson, 1992). Some warfarin metabolites are excreted in the bile, and there is significant enterohepatic circulation. Most warfarin metabolites are excreted in the urine. A number of genes have been reported in a recent review by Wadelius and Pirmohamed to be involved in the biological pathway of warfarin (Wadelius & Pirmohamed, 2007a). The most University of Ghana http://ugspace.ug.edu.gh 4 important of these genes are Cytochrome P450 isozyme 2C9 (CYP2C9), Vitamin K epoxide reductase (VKORC1) and Cytochrome P450 isozyme 4F2 (CYP4F2). 1.2.1 CYP2C9 and Warfarin maintenance dose The primary enzyme involved in metabolism and subsequent inactivation of S-warfarin is the CYP2C9 which account for nearly 10% of the differences in people's responses to the drug (Wadelius et al., 2007). CYP2C9 gene has two common variants, CYP2C9*2 (430C˃T) and CYP2C9*3 (1075 A˃C). These variants result in a protein with decreased function and nearly abolished function, respectively (Wadelius et al., 2007). Patients with variant CYP2C9*2 alleles have been shown to have reduced enzyme activity up to 12% compared to patients described as extensive metabolizers of warfarin with two wild- type CYP2C9*1 alleles. Patients with variant CYP2C9*3 alleles have been shown to have reduced activity up to 5% compared to extensive metabolizers (Crespi & Miller, 1997; Haining et al., 1996). Patients with these variant alleles will require a lower dose of warfarin. Patients who carry these CYP2C9 gene variants are more likely to require more time to achieve steady state and a stable INR due to the longer half-life of the drug. Thus, dosing adjustments and INR determinations can be made when CYP2C9 variants are known to allow steady-state concentrations to be achieved more efficiently. University of Ghana http://ugspace.ug.edu.gh 5 1.2.2 CYP4F2 and Warfarin maintenance dose A newly discovered gene, CYP4F2 was also found to contribute 1% - 2% of the variability in warfarin dose and has an impact on stable warfarin dose (Takeuchi et al., 2009). Cytochrome P450 4F2 (CYP4F2) is a vitamin K1 (VK1) oxidase. Carriers of the V433M polymorphism (rs2108622: C>T nucleotide substitution) have lower hepatic concentrations of the enzyme, resulting in a reduced capacity to metabolise VK1. Elevated hepatic levels of VK1 are thought to render these individuals less sensitive to the anticoagulant effects of warfarin (McDonald et al., 2009). Patients with homozygote mutant (T/T) alleles of CYP4F2 will require approximately 1 mg/day more of warfarin than those who carry the homozygote wild type allele (CC) (Caldwell et al., 2007). Results from the first genome-wide association study (GWAS) which searched the entire genome, reported that additional genes having a major influence on warfarin dose might not exist or be found in the near-term in Caucasians. Hence, clinical trials assessing patient benefit from individualized dose forecasting based on a patient’s genetic makeup at VKORC1, CYP2C9 and possibly CYP4F2 could provide state-of-the-art clinical benchmarks for warfarin use during the foreseeable future (Takeuchi et al., 2009). 1.2.3 VKORC1 and Warfarin maintenance dose Vitamin K epoxide reductase (VKOR) is the site of action for warfarin and it is estimated that nearly 30% of warfarin dose variance is due to Single Nucleotide Polymorphisms (SNPs) in the warfarin drug target VKORC1 (D'Andrea et al., 2005). The associated gene, VKORC1, has a common promoter variant (1639G>A) which reduces the expression of the gene, and University of Ghana http://ugspace.ug.edu.gh 6 therefore lowers the amount of VKOR and leads to warfarin sensitivity. Variations in VKORC1 have been associated with both warfarin sensitivity and warfarin resistance. VKORC1 codes for an enzyme that recycles reduced vitamin K making it available for use by vitamin K-dependent coagulation factors and the mutant A allele decreases its action. In the VKORC1 _1639 SNP, the common G allele is replaced by the A allele. Because people with an A allele produce less VKORC1 than people with the G allele, lower warfarin doses are needed to inhibit VKORC1 and to produce an anticoagulant effect in carriers of the A allele (Rieder et al., 2005). The prevalence of these variants have been reported in literature to vary by race; 37% of Caucasians and 14% of Africans carry the A allele (Rieder et al., 2005). The anticoagulant activity of warfarin is due to inhibition of the VKORC1 enzyme (Scott et al., 2010). The common promoter mutation of G to A at position 1639 may explain much of the pharmacological variability in warfarin sensitivity. CYP2C9 and VKORC1 polymorphisms occur frequently in patients who are warfarin "sensitive" and require lower doses, whereas patients with VKORC1 missense mutations are warfarin "resistant" and require higher doses (Scott et al., 2010). The combination of the two CYP2C9 variants (*2 and *3) with the VKORC1 promoter mutation is estimated to account for 40% – 63% of the variability in therapeutic warfarin dose (Rieder et al., 2005; Sconce et al., 2005). Recent genome wide association studies have not only confirmed these observations but also identified a novel association between reduced hepatic CYP4F2, higher levels of hepatic vitamin K, and higher warfarin dose requirements (Singh et al., 2011). University of Ghana http://ugspace.ug.edu.gh 7 1.2.4 Clinical Implications of the Genetic Mutation The three SNPs (CYP2C9*2, CYP2C9*3, and VKORC1 1639G˃A) play key roles in determining (1) the dose of warfarin required to produce a therapeutic INR (typically 2.0 to 3.0); (2) the risk of bleeding or of producing supra-therapeutic INR (>4.0); and (3) the time required to achieve a stable therapeutic dose (Roth et al., 2013). Carriers of CYP2C9*2 and CYP2C9*3 require, on average, a 19% and 33% reduction of warfarin respectively, per allele in warfarin dose verses those who carry the CYP2C9*1 allele (Higashi et al., 2002; Schwarz et al., 2008). Carriers of the VKORC1 A allele require, on average, a 28% reduction of warfarin per allele in their warfarin dose compared to those who carry none (Higashi et al., 2002; Schwarz et al., 2008). The effect of CYP2C9 and VKORC1 variants on warfarin dosage were reported by (Scibona et al., 2012) (Table 1.1). As expected, using standard dosing algorithms in patients with these variants leads to adverse clinical and laboratory outcomes because of their genetically mediated sensitivity to the drug. In particular, standard dosing algorithms lead, on average, to a 2- to 3-fold increased risk of serious or life threatening bleeding or an out-of-range INR (>4.0) in carriers of the *2 or *3 alleles of CYP2C9 (Higashi et al., 2002). Similarly, carriers of the VKORC1 A allele are also at a 2- to 3-fold higher risk of an INR >4.0 during initiation of warfarin therapy when standard dosing algorithms are used (Schwarz et al., 2008). Finally, as a result of the sensitivity of these patients to warfarin and the additional dose adjustments required, the time required to achieve a "stable" INR between 2.0 and 3.0 is significantly delayed in carriers of all three SNPs (CYP2C9*2, CYP2C9*3, and VKORC1 1639G˃A) (Higashi et al., 2002; Schwarz et al., 2008). Overall, using a combination of University of Ghana http://ugspace.ug.edu.gh 8 genetic and clinical factors to predict the warfarin maintenance dose may be more accurate than using clinical factors alone (Klein et al., 2009). Table 1.1: CYP2C9 and VKORC1 Polymorphism and Sensitivity to Warfarin CYP2C9 VKORC1_1639G>A Sensitivity to Warfarin CYP2C9*1 G/G Low CYP2C9*2 G/A Intermediate CYP2C9*3 A/A High Source: (Scibona et al., 2012). Genetic polymorphisms of CYP2C9 and VKORC1 variants have been reported in different ethnic populations. CYP2C9*2 (430C>T) variant allele is found in 8% -13% of Caucasian, 2% - 6% of Asian and less than 1% of African- Americans populations. CYP2C9*3 (1075A>C) variant is 6% - 10% in Caucasians, less than 1% in Asians and 1% - 4% in African-American population (Takahashi et al., 2006b). VKORC1 (1639G>A) is 42% in Caucasians, 89% in Asians and 8% in African Americans populations (Takahashi et al., 2006b). While the Asian population generally has the low-dose variation of VKORC1, African- Americans have the high-dose version. European Americans fell in the middle between the Asians and African Americans (Rettie & Tai, 2006; Rieder et al., 2005). Some of these studies mentioned earlier investigated the influence of pharmacogenetics on warfarin treatment response focusing only on variants within individual CYP2C9, VKORC1 or CYP4F2 genes. Other studies however assessed the combined effect of these variants in these genes together with various environmental factors (Higgins, 2005; Lee et al., 2006; University of Ghana http://ugspace.ug.edu.gh 9 Takahashi et al., 2006a; Wadelius et al., 2005). Based on the outcome of some of these investigations, several warfarin dosing procedures incorporating polymorphisms of VKORC1, CYP2C9 and in some cases, CYP4F2 as covariates, were explored in a study by Jonas and McLeod (Jonas & McLeod, 2009). The predictive power of these warfarin dosing procedures were observed to have varied markedly across different populations. The study compared the combined frequency of variant VKORC1, CYP2C9 and CYP4F2 alleles among African- Americans, Asian, Caucasian, Hispanic and Ashkenazi Jewish populations (Scott et al., 2010). This approach was further extended to populations that are consistently under- represented in pharmacogenetics databases, namely Amerindians (Native Americans), sub- Saharan Africans (Mozambicans) and an admixed Brazilian cohort, with African, European and Amerindian ancestral roots (Vargens et al., 2011). The study revealed that Mozambicans and African-Americans differed significantly in the frequency of CYP2C9 and VKORC1 polymorphisms. This observation was explained in part by the authors as a European admixture in African-Americans (Suarez-Kurtz, 2005) and may be reflecting the genetic diversity of sub-Saharan African populations (Tishkoff et al., 2009). It was established that in the context of warfarin dosing algorithms, VKORC1, CYP2C9*2 and CYP2C9*3 are rare or absent in Mozambicans (Tishkoff et al., 2009). Considering the major contribution of these SNPs to the performance of most warfarin algorithms, it might be anticipated that such algorithms will perform poorly in Mozambicans, as they do in other cohorts of African descent (Cavallari et al., 2010; Gage & Lesko, 2008; Klein et al., 2009). There is very limited pharmacogenetics data on warfarin dose requirement in many other indigenous African populations. There is currently no pharmacogenetics data University of Ghana http://ugspace.ug.edu.gh 10 on warfarin metabolism to assist in the management of warfarin patients in the Ghanaian population. Therefore it will be of clinical relevance to explore the impact of VKORC1, CYP2C9, and CYP4F2 polymorphisms on warfarin dosage to ascertain patient sensitivity or resistance. 1.3 Problem Statement Warfarin, the most commonly prescribed anticoagulant, exhibits large interpatient variability in dose requirements (Kaminsky & Zhang, 1997). Patient-specific factors such as age, body weight, race, concurrent diseases, and medications, explain some of the variability in warfarin dose but genetic factors influencing warfarin response explain a significantly higher proportion of the variability in dose (Wadelius & Pirmohamed, 2007b). Candidate-gene association studies (Sconce et al., 2005) have identified 2 genes: CYP2C9, which codes for the enzyme cytochrome P450 2C9 that metabolizes S-warfarin (Kaminsky & Zhang, 1997), and VKORC1, which codes for warfarin’s target, vitamin K epoxide reductase (Li et al., 2004), as responsible for the main proportion of the genetic effect. The influence of CYP2C9 and VKORC1 has also been confirmed by genome-wide association studies among Caucasians (Takeuchi et al., 2009). Personal communication with Physicians at Korle-Bu Teaching Hospital revealed that there are some Ghanaian patients on high warfarin maintenance dose (>5mg per day) and others on low warfarin maintenance dose (≤5mg per day). Warfarin has a narrow therapeutic window and patient response varies widely. Giving a high dose of warfarin to a patient who requires a low dose, may induce bleeding events whilst administering a low dose of warfarin to a patient University of Ghana http://ugspace.ug.edu.gh 11 who requires a high dose may lead to thrombosis both of which may be life-threatening. Specific alleles have been reported to be distributed differently in different race/ethnic populations (Kittles & Weiss, 2003). However, pharmacogenetic data on these clinically relevant genes which could help in managing warfarin patients are scarce in indigenous African populations and are unavailable in Ghana. 1.4 Justification It is expected that genetic information, especially for CYP2C9 and VKORC1 genes in addition to patient-specific factors such as age, body size, race, concurrent diseases, and medications could potentially improve management of warfarin dose/response in Ghanaian patients on either high or low warfarin maintenance dose. 1.5 Aim To determine the frequency of CYP2C9, VKORC1 and CYP4F2 variant alleles in the Ghanaian population as basis to estimate the potential impact of these polymorphisms in patients on either low or high warfarin maintenance dose. 1.6 Specific Objectives 1. To determine the clinical and demographic factors associated with both high and low stable warfarin doses in indigenous Ghanaian patients. 2. To genotype CYP2C9, VKORC1 and CYP4F2 variants in patients on high warfarin maintenance dose (>5mg per day), and those on low warfarin maintenance dose (≤ 5mg per day). University of Ghana http://ugspace.ug.edu.gh 12 3. To ascertain the genetic effect on dose variation for patients who are warfarin ‘sensitive’ and those who are warfarin ‘resistant’. University of Ghana http://ugspace.ug.edu.gh 13 CHAPTER TWO 2.0 LITERATURE REVIEW 2.1 Genetic Effect on Drug Efficacy Research over the past 50 years have shown that variation between individuals that is influenced by genes and other factors is relevant to the efficacy of all drugs (Meyer, 2004). It is now known that metabolic enzymes are affected not only by Single Nucleotide Polymorphisms, SNPs (of which the human genome contains more than 10 million), but also by other genomic variation, such as gene duplications and deletions, mutations in regulatory genes, and probably by recently-described large-scale copy number variations (Iafrate et al., 2004; Sebat, 2004). Such Pharmacogenomics studies might provide a molecular basis for population differences in DMEs for example Cytochrome P450 (Xie et al., 2001), sulfotransferases (Falany, 1997) and methyltransferases (Weinshilboum, 2003), transporters such as ABC1 (Ameyaw et al., 2001), receptors such as adrenergic receptors (Tate & Goldstein, 2004) and other factors that are involved in differential drug responses and disease susceptibility. Many of the population- group differences that are documented are likely to have important medical and public-health implications (Taylor, 2004). It is evident that drugs for which the metabolism is carried out by a polymorphic enzyme and where pronounced differences exist because of genetic variations, data generated in one population cannot be extrapolated into other populations. The responses to drugs vary between individuals and differences have also been shown to exist between different populations (Vesell, 1989). These differences in response to drugs can be partially attributed to physiological and environmental factors such as age, renal and liver function, University of Ghana http://ugspace.ug.edu.gh 14 drug interactions, and the presence of disease. Investigating the genetic variation within genes encoding DMEs, drug transporters and drug targets by studying key polymorphisms help in understanding the genotype-phenotype correlation and the allelic frequency distribution within different populations. Pharmacogenetics information of this nature is increasingly becoming useful for improving drug therapy and explaining individual and inter-ethnic differences due to drug response (Grasmäder et al., 2004). It is also being used to predict and explain ADRs which are estimated to account for about 106,000 deaths in the USA each year, which was more than auto accidents, suicides, and homicides combined (Landow, 1998). ADRs are one of the top six causes of death in the USA (Marwick, 1997). 2.2 Pharmacogenetics and Pharmacogenomics The field of pharmacogenetics, deals with inherited variations in drug responses and refers to genetic differences in metabolic pathways which can affect individuals responses to drugs, both in terms of therapeutic as well as adverse effects (Klotz, 2007). Pharmacogenomics reflects the evolution of pharmacogenetics into the study of the entire spectrum of genes that determine drug efficacy and safety. The ultimate aim of pharmacogenetics is to lead to personalized treatment of individual patients based on their genetic profile; “the right drug at the right dose to the right patient at the right time” (Evans & Relling, 1999). However, the identification of individual genetic differences (polymorphisms) within populations can also be useful in improving the quality of healthcare in that specified population. It is becoming increasingly important to derive data from different populations to build a database which can then be used in epidemiological investigations to better understand the genetic risk factors University of Ghana http://ugspace.ug.edu.gh 15 which affect many diseases and to be in a better position to predict these risk factors in the future (Nebert, 1999). The proteins CYP2C9, CYP4F2, VKOR, and calumenin are encoded by polymorphic genes that provide significant contributions to warfarin disposition ( CYP2C9), vitamin K disposition ( CYP4F2), and clotting factor activation ( VKOR and calumenin). CYP = cytochrome P450; VKOR = vitamin K epoxide reductase (Fig. 2.2). With the progress of pharmacotherapy in the world, it is now known that inter-ethnic differences in clinical outcome are often greater than inter-individual differences, and it is well-accepted that clinical outcome of pharmacotherapy depends on genetic factors (Evans & McLeod, 2003; Kalow, 2002). Since the completion of the Human Genome Project (HGP), pharmacogenetics has been expanding rapidly over the past 10 years with great potential for improving drug efficacy and the ultimate goal of individualized therapy. It is also due to improved genotyping technologies over this period. The HGP is an international scientific research project initiated by the USA with a primary goal of determining the sequence of the chemical base pairs which make up DNA, and of identifying and mapping the approximately 20,000-25,000 genes of the human genome from both a physical and functional standpoint (Arledge et al., 2001). 2.3 Warfarin’s Mechanism of Action Warfarin, a coumarin derivative, inhibits clotting by limiting hepatic production of the biologically active vitamin K-dependent clotting factors which are activated factors II, VII, IX, and X (Hirsh et al., 2001). Precursors of these factors undergo a carboxylation reaction to be converted to their activated forms. Warfarin is a vitamin K antagonist which interferes with University of Ghana http://ugspace.ug.edu.gh 16 this reaction. Reduction in the amount and activity of these factors produces the anticoagulant response. However, warfarin also interferes with production of the body’s natural anticoagulants, protein C and protein S, and can therefore sometimes exert a procoagulant response (Hirsh et al., 2001) (Fig. 2.1). Fig. 2.1: How warfarin blocks the vitamin K cycle. Source: (Osinbowale et al., 2009) 2.4 Pharmacokinetics and Pharmacodynamics of Warfarin Warfarin is a racemic mixture of a right-handed and a left-handed stereoisomer, designated R and S respectively. This racemic mixture has a half-life of approximately 36 to 42 hours University of Ghana http://ugspace.ug.edu.gh 17 (Jaffer & Bragg, 2003). The S-isomer is five times more potent as a vitamin K antagonist than the R-isomer (Breckenridge et al., 1974). Absorption of warfarin is rapid and complete. It is highly protein bound (> 98%), primarily to albumin. Only the free drug is pharmacologically active (O'Reilly, 1969). If the serum albumin level is low such as in the nephrotic syndrome, the free fraction of warfarin is increased, but so is its plasma clearance (Ganeval et al., 1986). Therefore, such conditions are not likely to lead to significant changes in the INR. The hepatic metabolism of the two isomers differs, with clinically significant implications for drug interactions. The S-isomer is primarily metabolized by cytochrome P450 2C9 (and to a lesser degree by P450 3A4) and is eliminated in the bile (Hirsh et al., 2001). The R-isomer, in contrast, is primarily metabolized by cytochrome P450 1A2 and P450 3A4 and is excreted in the urine as inactive metabolites. Since the S-isomer is much more potent than the R-isomer, medications that inhibit or induce the P450 2C9 pathway lead to the most significant drug interactions. Most drug interactions that affect the R-isomer are not significant (Hirsh et al., 2001). University of Ghana http://ugspace.ug.edu.gh 18 Fig. 2.2: Genes involved in the pharmacokinetics and pharmacodynamics of warfarin. Source: Pharmacotherapy ©2011, Pharmacotherapy publications 2.5 Warfarin Multiple Interactions with other Drugs, Diet, and Disease States There are many causes of high or low INR values. The most common, that is likely to lead to significant changes in the INR and increase the propensity for bleeding or clotting are drug interactions (Jaffer & Bragg, 2003). Drug interactions with warfarin can be defined as either pharmacokinetic or pharmacodynamic. Pharmacokinetic interactions involve alterations in the absorption, protein binding, and hepatic metabolism of warfarin. Conversely, pharmacodynamic interactions affect the tendency for bleeding or clotting through either antiplatelet effects or increases or decreases in vitamin K catabolism (Jaffer & Bragg, 2003). A list of common drugs that interacts with warfarin can be found in appendix II. Excessive vitamin K consumption can promote increased production of the vitamin K clotting factors, University of Ghana http://ugspace.ug.edu.gh 19 decreasing the anticoagulant response to warfarin (Booth et al., 1997). Alternatively, decreased vitamin K consumption can increase the anticoagulant response to warfarin. The foods that contain the highest amount of vitamin K per serving are the green leafy vegetables such as spinach, broccoli, and turnip greens (Booth et al., 1997). 2.5.1 Concomitant diseases Certain diseases can influence anticoagulation control (Demirkan et al., 2000). Congestive heart failure can cause hepatic congestion of blood flow and inhibit warfarin metabolism. This can be troublesome in patients with frequent exacerbations of heart failure. Hypothyroidism decreases the catabolism of the vitamin K clotting factors. Therefore, hypothyroidism of new onset or due to inadequate replacement therapy could be suspected if there is a general trend toward decreased INR values with a need for increased warfarin doses (Jaffer & Bragg, 2003). Hyperthyroidism, on the other hand, increases the catabolism of the vitamin K clotting factors and could be suspected if there is a general trend toward increased INR values with a need for decreased warfarin doses (Demirkan et al., 2000). Hepatic failure may significantly elevate the INR due to decreased production of clotting factors. 2.6 INR Monitoring and Warfarin dose determination 2.6.1 Adherence, missed doses High or Low INR could mean that the patient is not taking the warfarin medication as required. The actual dose of warfarin taken can be confirmed by ruling out the possibility that the patient took a higher or lower than the prescribed dose. The possibility of a missed warfarin dose could also affect the INR results. In general, a missed dose of warfarin may be University of Ghana http://ugspace.ug.edu.gh 20 reflected in the INR within 2 to 5 days after the dose is missed (Jaffer & Bragg, 2003). This could be important even though the INR value of the patient may be in the therapeutic range. For example, a patient with a therapeutic INR value who reports missing a dose of warfarin 2 days ago would very likely have had a higher than the therapeutic INR if he or she had not missed the dose (Jaffer & Bragg, 2003). This is particularly essential when interpreting INR results of a patient recently started on warfarin. The patient’s response to warfarin as reflected by the INR determines his or her warfarin dose required to attain therapeutic levels. The frequency of INR testing is dictated by dose response and current clinical information. High INR predisposes patients to increased risk of bleeding while low INR means a patient is at risk of thrombosis. 2.7 The Cytochrome P450 2C9 Gene The human CYP enzymes are involved in the metabolism of a wide range of substances including pharmaceutical agents usually leading to their inactivation and excretion (Nelson et al., 1996). They can also activate prodrugs or transform exogenous compounds into reactive intermediates that can act as therapeutic agents or as carcinogens. CYP enzymes are highly polymorphic and responsible for the metabolism of nearly 20% of clinically used drugs (Goldstein, 2001). Understanding these polymorphic variations within different populations is becoming increasingly important because of the drug interactions that result from enzyme inhibitions or inductions. The official name of this gene is “cytochrome P450, family 2, subfamily C, polypeptide 9” and its official symbol is CYP2C9. This gene encodes a member of the cytochrome P450 superfamily of enzymes. The cytochrome P450 proteins are monooxygenases which catalyze University of Ghana http://ugspace.ug.edu.gh 21 many reactions involved in drug metabolism and synthesis of cholesterol, steroids and other lipids (Guengerich, 2008). This protein localizes to the endoplasmic reticulum and its expression is induced by rifampin (Vormfelde et al., 2009). The enzyme is known to metabolize many xenobiotics, including phenytoin, tolbutamide, ibuprofen and S-warfarin (Miners & Birkett, 1998). Studies identifying individuals who are poor metabolizers of phenytoin and tolbutamide suggest that this gene is polymorphic. The gene is located within a cluster of cytochrome P450 genes on chromosome 10q24 (Gray et al., 1995). The CYP2C9 gene helps the body to break down warfarin. There are several variants in the CYP2C9 gene that can cause the CYP2C9 enzyme to be less active. When the CYP2C9 enzyme is less active, warfarin stays in the body for a longer period of time. This means that lower warfarin doses are needed in people with certain (reduced function) CYP2C9 genetic variants. Variation in the CYP2C9 gene is responsible for up to 18% of variability in warfarin response (Johnson et al., 2011). The nomenclature for the CYP2C9 SNPs is unique: the normal, or wild-type, variant is referred to as *1 ("star 1"), the two polymorphic versions are *2 ("star 2") and *3 ("star 3"), and each person can carry any two versions of the SNP. For example, a person with two normal copies would be *1/*1, a person with only one polymorphism could be *1/*2, and a person with both polymorphisms could be *2/*3. The prevalence of each variant varies by race; 10% and 6% of Caucasians carry the *2 and *3 variants, respectively, but both variants are rare (< 2%) in those of African or Asian descent (Au & Rettie, 2008). University of Ghana http://ugspace.ug.edu.gh 22 The CYP2C9 gene constitutes 50% of the CYP2C enzyme subfamily and is the most abundant member of this subfamily (Gerbal-Chaloin et al., 2001). The CYP2C9 gene is located on chromosome 10q24.2 and spans approximately 55kb with 9 exons and encodes a protein of 490 amino acids (De Morais et al., 1994). The CYP2C9 gene is predominantly expressed within the liver and also in smooth muscle and endothelial cells. It metabolizes approximately 10% of the clinically important drugs such as warfarin, tolbutamide, glipizide, losartan and phenytoin (Miners & Birkett, 1998). It also plays an important role in the metabolism of endogenous substances such as arachidonic acid (Miners & Birkett, 1998). The CYP2C9 gene exhibits inter-individual variability in its expression and catalytic activity due to genetic variations (Lindh et al., 2005). This can result in either drug toxicity or therapeutic failure in some patients. CYP2C9*1 metabolizes warfarin normally, CYP2C9*2 reduces warfarin metabolism by 30%, and CYP2C9*3 reduces warfarin metabolism by 90% (Shah & Voora, 2013). Because warfarin given to patients with *2 or *3 variants will be metabolized less efficiently, the drug will remain in circulation longer, so lower warfarin doses will be needed to achieve anticoagulation. The CYP2C9*2 and CYP2C9*3 variants alleles are the most common and are associated with decreased metabolism of different substrates (Xie et al., 2002). The CYP2C9*2 variant allele, a C to T polymorphism at position 430 within exon 3, results in an arginine to cysteine substitution and impaired enzyme activity (Sullivan-Klose et al., 1996). The CYP2C9*3 variant allele is an A to C polymorphism within exon7 at position 1075 which encodes for an isoleucine to leucine amino acid change also leading to impaired enzyme activity (Sullivan-Klose et al., 1996). University of Ghana http://ugspace.ug.edu.gh 23 Earlier studies have shown CYP2C9 polymorphisms leading to amino acid changes in the composition of this enzyme affecting both activity and specificity of the enzyme and therefore leading to inter-individual variability in the elimination of CYP2C9 substrates in different ethnic groups (Xie et al., 2002; Yasar et al., 1999). This genetic variability can lead to drug toxicity such as warfarin induced bleeding complications and to inadequate drug efficacy or therapeutic failure in some patients (Goldstein, 2001; Schwarz, 2003). CYP2C9*2 and CYP2C9*3 allele variants show decrease clearance for warfarin and phenytoin compared with the wild type allele (CYP2C9*1). Identifying individuals with this allele could help to predict the dose requirements of these drugs. Standard 5mg/day dosing of warfarin in patients with CYP2C9 and/or VKORC1 variants can lead to excessive warfarin exposure, resulting in an exaggerated anticoagulant response and a risk of serious or life-threatening bleeding complications (Takahashi et al., 2006b; Voora et al., 2005). Patients with CYP2C9 variants are more likely to require more time to achieve steady state and a stable INR due to the longer half-life of the drug. Thus, dosing adjustments and INR determinations can be made when CYP2C9 variants are known to allow steady-state concentrations to be achieved more efficiently. A recently evaluated warfarin genetics (WARG) cohort in approximately 1500 Swedish patients, the largest study to date, has shown likely benefit from genetic forecasting of dose (Wadelius et al., 2009). The report also confirmed that SNPs in VKORC1 and CYP2C9 predict approximately 40% of dose variance while non-genetic factors (age, sex, body mass University of Ghana http://ugspace.ug.edu.gh 24 index) jointly account for another nearly 15%. The robust and now widely replicated associations of warfarin dose with VKORC1 and CYP2C9 have provided one of the most successful applications of pharmacogenetics to date (Rettie & Tai, 2006) and offer promise for genetic prediction of required dose in a clinical setting (Wadelius et al., 2009). A previous study showed that a combination of genetic and non-genetic factors cause Caucasians to exhibit 20-fold inter-individual variation in warfarin dose needed to achieve the usual therapeutic level of anticoagulation as measured by the prothrombin INR (Takahashi & Echizen, 2003). Thus, in the absence of genotypic, clinical and other relevant information for predicting each patient’s required warfarin dose, initial prescribed doses may be too low or too high. Warfarin’s risks of serious side effects, narrow therapeutic range, and wide inter- individual variation in dosage, have focused attention on the need to better predict dose in the initial stage(s) of treatment (Bozina, 2010). 2.8 The Vitamin K Epoxide Reductase complex subunit 1 Gene (VKORC1) The human body uses vitamin K in the blood clotting process. If vitamin K recycling is less efficient, then a person’s blood will not clot easily. The VKORC1 gene codes for an enzyme that helps with the recycling of vitamin K. Genetic variation in VKORC1 can reduce the ability of this enzyme to recycle vitamin K. If the ability of the blood to clot is reduced, then a lower dose of warfarin may be needed. Higher doses of warfarin could be dangerous, because too much warfarin could slow clotting to the point where bleeding cannot stop (Johnson et al., 2011). University of Ghana http://ugspace.ug.edu.gh 25 The "A" variant (rs9923231) of the VKORC1 gene causes less efficient vitamin K recycling. This variant is responsible for 10% to 30% of the variability in warfarin response (Johnson et al., 2011). 2.9 The Cytochrome P450 4F2 Gene (CYP4F2) The CYP4F2 gene also plays a role in helping the body use vitamin K in the blood clotting process. CYP4F2 helps to reduce blood clotting by decreasing the amount of vitamin K. People with the ‘T’ variant in the CYP4F2 gene could have increased vitamin K levels and may therefore need a higher warfarin dose to prevent clotting (Borgiani et al., 2009). The differences in CYP4F2 genotype account for approximately 1-7% of the variability in warfarin response between individuals (Borgiani et al., 2009; Pautas et al., 2010). 2.10 Pharmacogenomics in Africa CYP2C8, CYP2C9 and CYP2C19 polymorphisms were characterized in a healthy Ghanaian population. Allele frequency distributions for CYP2C8, CYP2C9 and CYP2C19 among the Ghanaian population were comparable to data previously reported in other populations of African origin but differ from that observed in Caucasian and Asian populations (Kudzi et al., 2009). Variant allele frequencies for CYP2C9 and CYP2C19 were reported for the first time among indigenous Ghanaian population (Kudzi et al., 2009). Allelic frequencies were obtained for CYP2C8*2 (17%), CYP2C8*3 (0%), CYP2C8*4 (0%), CYP2C9*2 (0%), CYP2C9*3 (0%), CYP2C9*4 (0%), CYP2C9*5 (0%), CYP2C9*11 (2%), CYP2C19*2 (6%) and CYP2C19*3 (0%) (Kudzi et al., 2009). University of Ghana http://ugspace.ug.edu.gh 26 These results provide additional information on polymorphisms of this CYP2C subfamily of enzymes in an indigenous African population which is scarce in published literature (Kudzi et al., 2009). Information regarding genetic influences of warfarin dosage variability in the South African black population is very little. Novel CYP2C9 and VKORC1 gene variants associated with warfarin dosage variability in the South African black population were determined for patients on warfarin therapy (Mitchell et al., 2011). Findings from that research indicated that 26 novel SNPs and seven previously described CYP2C9 variants and three previously described but not novel VKORC1 SNPs were observed (Mitchell et al., 2011). Only 11 of the CYP2C9 variants and two of the VKORC1 variants were observed at high enough allele frequencies to assess their impact on warfarin dosage (Mitchell et al., 2011). The researchers demonstrated that CYP2C9*8 and two novel CYP2C9 SNPs (g.16179 and g.46028) were associated with a decrease in warfarin dosage, β-blockers were independently associated with a decrease in warfarin dosage and two known VKORC1 variants (rs7200749 and rs7294) were associated with an increase in warfarin dosage. The CYP2C9 and VKORC1 variants and a small subset of environmental factors used in the study explained approximately 45% of warfarin dosage variability in the South African black population (Mitchell et al., 2011). 2.11 Amplicon sizes of Genes under study and the Expected Restriction digest fragment Sizes The CYP2C9*2 variant allele, a ‘C to T’ polymorphism at position 430 within exon 3, results in an arginine to cysteine substitution and impaired enzyme activity (Sullivan-Klose et al., University of Ghana http://ugspace.ug.edu.gh 27 1996). In CYP2C9*2 genotyping, the C430 > T substitution in exon 3 ‘abolishes’ the AvaII restriction site (GGACC). Treatment of the 375 bp PCR product generated by the primer sets with AvaII leaves the fragment undigested at 375 bp when run on a 2% agarose gel. The wild- type (CYP2C9*1) and the mutant (CYP2C9*3) alleles were digested by AvaII restriction enzyme to give two smaller fragments of 296 bp and 79 bp (Seng et al., 2003). The CYP2C9*3 variant allele is an ‘A to C’ polymorphism within exon 7 at position 1075 which encodes an isoleucine to leucine amino acid change also leading to impaired enzyme activity (Sullivan-Klose et al., 1996). In CYP2C9*3 genotyping, the A1075 >C substitution in exon 7 creates a KpnI restriction site (GGTACC). Samples containing CYP2C9*3 produced 85 bp and 20 bp KpnI digestion products. However, samples containing CYP2C9*1 and CYP2C9*2 produce a single undigested fragment of 105 bp. These possible outcomes were reported in a study by (Scibona et al., 2012) (Table 2.1). VKORC1 wild-type has two NciI sequence recognition sites. An NciI restriction enzyme treatment of the 636 bp PCR product generated smaller fragments of 472 bp, 114 bp and 50 bp for the wild-type allele (G/G). A ‘G to A’ polymorphism at position 1639 abolishes one of the NciI restriction sites leading to only two smaller fragments of 522 bp and 114 bp being produced in the mutant allele (A/A). The heterozygous genotype with one wild-type and one variant allele (G/A) leads to four DNA fragments being resolved on the agarose gel (522 bp, 472 bp, 114 bp and 50 bp) (Aomori et al., 2009). University of Ghana http://ugspace.ug.edu.gh 28 CYP4F2 wild-type has a single PvuII sequence recognition site. A PvuII restriction enzyme digestion of the 439 bp PCR product generated two smaller fragments of 379 bp and 60 bp for the wild-type allele (C/C). A ‘C to T’ Polymorphism abolishes this recognition site and treatment with PvuII restriction enzyme leaves the mutant allele (T/T) undigested. The heterozygous genotype with one wild-type and one variant allele (C/T) results in three DNA fragments being resolved on the agarose gel (439 bp, 379 bp and 60 bp). Table 2.1: CYP2C9 genotyping with restriction enzymes Genotypes *1/*1 *1/*2 *1/*3 *2/*2 *2/*3 *3/*3 AvaII KpnI AvaII KpnI AvaII KpnI AvaII KpnI AvaII KpnI AvaII KpnI 105 375 105 105 375 105 375 105 296 296 296 85 296 85 296 85 79 79 79 20 79 20 79 20 Restriction fragment sizes in base pairs (bp) generated during CYP2C9 genotyping using AvaII and KpnI restriction enzymes. Source: (Scibona et al., 2012). 2.12 Hardy-Weinberg Equilibrium (HWE) Determinations In 1908, two scientists, Godfrey H. Hardy, an English mathematician, and Wilhelm Weinberg, a German physician, independently worked out a mathematical relationship that related genotypes to allele frequencies (Dorak, 2005). Their mathematical concept, called the Hardy-Weinberg (HWE) principle, is a crucial concept in population genetics. It predicts how gene frequencies will be inherited from generation to University of Ghana http://ugspace.ug.edu.gh 29 generation given a specific set of assumptions (McClean, 1997). The Hardy-Weinberg principle states that in a large randomly breeding population, allelic frequencies will remain the same from generation to generation assuming that there is no mutation, gene migration, selection or genetic drift (Thompson et al., 1991). This principle is important because it gives biologists a standard from which to measure changes in allele frequency in a population. It is employed in genetic association study, to guard against genotyping errors and population stratification. HWE is an ideal state that never occurs in nature because there is always a disturbing influence present in nature. Examples of disturbing influences include: non-random mating, mutations, selection, limited population size, random genetic drift, and gene flow. The observed and the expected allele frequencies in a studied population are said to be in HWE if p > 0.05. A population of alleles must meet all the following rules in order to be considered “in equilibrium”: (i) no gene mutations, hence no change in alleles; (ii) no migration of individuals either in or out of the population; (iii) random mating must occur, individuals mate by chance; (iv) no genetic drift must occur, a chance change in allele frequency may occur; (v) no natural selection, a change in allele frequency due to environment may occur. A deviation from the HWE results when p < 0.05 and this indicates evolution of species. Deviations of genotype frequencies from HWE can affect the validity of tests of association using allele-based contrasts (Schaid & Jacobsen, 1999). Testing of HWE is therefore used as a quality control step in the statistical analysis of genetic data. 2.12.1 Hardy-Weinberg Equation There are two equations necessary to solve a HWE question: (a) p + q = 1, and (b) p2 + 2pq +q2 = 1, where p is the frequency of the dominant allele, q is the frequency of the recessive University of Ghana http://ugspace.ug.edu.gh 30 allele, p2 is the frequency of individuals with the homozygous dominant genotype, 2qp is the frequency of individuals with the heterozygous genotype and q2 is the frequency of individuals with the homozygous recessive genotype. For instance: a population containing the genotypes A/A, aa, and Aa, the frequency of A/A will always be p2, aa, will be q2, and Aa will be 2pq at equilibrium, where p is the frequency of A and q is the frequency of a. University of Ghana http://ugspace.ug.edu.gh 31 CHAPTER THREE 3.0 METHODS 3.1 Study Design This cross sectional study involved adult patients on either high or low stable warfarin maintenance dose. The patients were classified into two groups after their demographic data and clinical histories were recorded. Blood samples were taken from all participating patients for INR measurement and genotyping. Ethical clearance for the study was obtained from the Protocol and Ethical Review Committee of the University of Ghana Medical School with reference number MS-Et/M.6-P.4.5/2011- 2012. 3.2 Study site and study population This study was conducted at the Korle-Bu Teaching Hospital (KBTH). KBTH is a referral hospital with over 1800 beds for in-patients and has several specialist clinics, wards, pharmacies, laboratories and a reference laboratory. Patients were recruited from the Cardiothoracic Center and the Anticoagulation clinic of Haematology department. A stable warfarin patient was defined as one whose warfarin dose requirement had remained constant for at least the 3 previous clinic visits over a minimum period of 3 months, and with an International Normalized Ratio (INR) of the prothrombin time within the target range of 2.0 to 3.0 or 2.5 to 3.5 for heart valve replacement patients. A total of 143 individuals were recruited for this study. Eighty five (85) of these individuals were patients on low daily warfarin maintenance dose and 58 of these individuals were University of Ghana http://ugspace.ug.edu.gh 32 patients on high daily warfarin maintenance dose. In this study, high daily warfarin dose was defined as > 5 mg/daily and low daily warfarin dose was defined as ≤ 5mg/daily based on personal interaction with some senior medical officers who administer the drug in Korle-Bu Teaching Hospital to reflect common practice already available in the hospital. 3.3 Inclusion Criteria Patients of both genders were included in the study. Patients who required warfarin for at least 3 months and were between 18 to 77 years with any of the indications listed below: atrial fibrillation/flutter (AF), deep vein thrombosis (DVT), pulmonary embolism (PE), and mitral valve replacement (MVR) were enrolled for the study. 3.4 Exclusion Criteria Patients with the following medical conditions were excluded from the study: history of GI bleeding or peptic ulcer disease, significant liver disease (active hepatitis or chronic HBV/HCV infection), uncontrolled hypertension, chronic diarrhoea or malabsorption syndrome, viral or bacterial infection prior to enrolment, active or previous infective endocarditis, hospital stay > 30 days as a result of septicaemia, mediastinitis or pneumonia, cardiac cachexia, and morbid obesity. 3.5 Procedures Demographic data and clinical history of all patients were taken. Patients who satisfied the inclusion criteria were enrolled into the study after they have given their consent to be part of the study. Relevant study data was extracted from their folders onto a study data sheet (Appendix III). Patient height and weight were recorded to determine the Body Mass Index University of Ghana http://ugspace.ug.edu.gh 33 (BMI). A whole blood sample (5mL) was collected from all patients. Aliquots of this sample (3.2 ml) were contained in EDTA specimen tubes for DNA extraction and genotyping of CYP2C9, VKORC1 and CYP4F2 variants. The remaining volume (1.8 mls) of the blood sample was collected into citrate tubes and used for INR measurement. 3.5.1 INR Measurement The HumaClot Duo plus device was used to measure the INR for all the samples. The device is a 2 channel photo-optical instrument which offers clotting, chromogenic and immuneturbidimetric testing capabilities. The result (in seconds) for a prothrombin time (PT) performed on a normal individual may vary according to the type of analytical system employed. This may be due to the variations between different batches of manufacturer's tissue factor used in the reagent to perform the test. The INR was devised to standardize the results. Each International Sensitivity Index (ISI) value assigned by each manufacturer. For any tissue factor the manufacturer indicates how a particular batch of tissue factor compares to an international reference tissue factor. The ISI is usually between 1.0 and 2.0. The INR is therefore the ratio of a patient's prothrombin time (PTtest) to a control sample (PTnormal) raised to the power of the ISI value for the analytical system used and is calculated by the following formula: University of Ghana http://ugspace.ug.edu.gh 34 3.5.2 Genomic DNA Extraction Genomic DNA was isolated from whole blood samples using a QIAamp DNA blood Maxi Kit (QIAGEN, USA) following the manufacturer’s protocol. Briefly, 500 µL of Qiagen protease was added to 3ml of whole blood and made up to 5ml with 1x PBS in a 50ml tube and mixed well. Lysis buffer AL (6ml) was added to the sample and vortexed for 1 minute. The sample was then incubated at 70°C for 10 minutes, after which 5ml of ethanol (96-100%) was added and the content vortexed. The solution was then transferred into the QIAamp Maxi column placed into a 50ml centrifuge tube and centrifuged at 3000 rpm for 3 min. The QIAamp maxi column was removed, the filtrate discarded and the column was placed back into the 50ml centrifuge tube. Buffer AW1 (5ml) was added to the QIAamp maxi column and the contents centrifuged at 5000 rpm for 1 min after which Buffer AW2 (5ml) was added to the column and the contents centrifuged at 5000rpm for 15 min. The QIAamp maxi column was then placed in a clean 50ml centrifuge tube and the collection tube containing the filtrate was discarded. Buffer AE (600µl) equilibrated to room temperature (250C) was then added to the QIAamp maxi column, incubated at room temperature for 5 min and then centrifuged at 5000rpm for 2 min. To get a maximum concentration of DNA, the eluate (600µl) containing the DNA was reloaded onto the membrane of the QIAamp maxi column, incubated at room temperature for 5 min and finally centrifuged at 5000rpm for 5 min. Less than 600µl was eluted from the column. 3.5.3 Genotyping Genotyping of CYP2C9 alleles was performed by Polymerase Chain Reaction – Restriction Fragment Length Polymorphism (PCR-RFLP) as previously described (Burian et al., 2002) University of Ghana http://ugspace.ug.edu.gh 35 with some modifications. PCR-RFLP also known as Cleaved Amplified Polymorphic Sequence (CAPS) is a popular technique for genetic analysis. It is applied for the detection of intraspecies as well as interspecies variation. The first step in a PCR-RFLP analysis is the amplification of a fragment containing the variation of interest. This is followed by treatment of the amplified fragment with an appropriate restriction enzyme. Since the presence or absence of the restriction enzyme recognition site results in the formation of restriction fragments of different sizes, allele identification can be done by electrophoretic resolution of the fragments in a gel matrix. 3.5.4 PCR for Genes under study In each reaction, genomic DNA was amplified using gene specific primers for each of the genes under study. Sequences of primers used for each gene are shown in Appendix I. Each PCR reaction was performed in a 25µl mixture made up of 10X PCR buffer containing Mg2+, 10mM dNTP mix, 20µM specific forward and reverse primers for each gene, 1U of Taq polymerase and 10µl of genomic DNA. Details of each PCR mix / thermal cycling conditions for CYP4F2, VKORC1 and CYP2C9 amplifications are contained in Tables 3.1, 3.1.1, 3.2, 3.2.1, 3.3, 3.3.1, 3.4, and 3.4.1 respectively. A blank reaction tube containing all other reagents except DNA was included as negative control in each run. Preparation of reagents is contained in Appendix VI. 3.5.5 Gel Electrophoresis of PCR Products Two percent (2% w/v) agarose gels were used to separate DNA fragments after PCR. Five microliters (5µl) aliquots of the PCR products already containing a loading dye were loaded University of Ghana http://ugspace.ug.edu.gh 36 onto the gel and electrophoresed to confirm PCR amplification before proceeding with RFLP analysis. A 100 bp DNA molecular weight marker was run on each gel to allow for fragment size determination. 3.5.6 PCR protocol for CYP4F2 rs2108622 The CYP4F2 gene was amplified using the following reaction compositions and thermal cycling conditions. The primer sequences used are contained in Appendix I. Table 3.1: Reaction composition / mix for CYP4F2 Reagents 1xµl 11xµl DNA Sample 10 - 10x PCR Buffer +15mM Mg2+ 5.0 55 10µM dNTPs dTTP 0.5 5.5 dATP 0.5 5.5 dCTP 0.5 5.5 dGTP 0.5 5.5 Primer 1 (F) 0.25 2.75 Primer 2 (R) 0.25 2.75 Taq Polymerase 0.125 1.375 Nuclease free water 7.375 81.125 Total Reaction Volume 25µ Table 3.1.1: Thermal Cycling conditions for CYP4F2 Initial Denaturation 950C for 5 mins 1 Cycle Denaturation 940C for 30 secs 35 Cycles Annealing 500C for 30secs Extension 720C for 1 min Final Extension 720C for 7 mins 1 Cycle University of Ghana http://ugspace.ug.edu.gh 37 3.5.7 PCR protocol for VKORC1 _1639G ˃ A The VKORC1 gene was amplified using the following reaction compositions and thermal cycling conditions. The primer sequences used are contained in Appendix I. Table 3.2: Reaction composition / mix for VKORC1 Reagents 1xµl 11xµl DNA Sample 10 - 10x PCR Buffer +15mM Mg2+ 5.0 55 10µM dNTPs dTTP 0.5 5.5 dATP 0.5 5.5 dCTP 0.5 5.5 dGTP 0.5 5.5 Primer 1 (F) 0.25 2.75 Primer 2 (R) 0.25 2.75 Taq Polymerase 0.125 1.375 Nuclease free water 7.375 81.125 Total Reaction Volume 25µl Table 3.2.1: Thermal Cycling conditions for VKORC1 Initial Denaturation 950C for 5 mins 1 Cycle Denaturation 950C for 60 secs 35 Cycles Annealing 510C for 30 secs Extension 720C for 2 mins Final Extension 720C for 10 mins 1 Cycle University of Ghana http://ugspace.ug.edu.gh 38 3.5.8 PCR protocol for CYP2C9*2 The CYP2C9*2 gene variant was amplified using the following reaction compositions and thermal cycling conditions. The primer sequences used are contained in Appendix I. Table 3.3: Reaction composition / mix for CYP2C9*2 Reagents 1xµl 11xµl DNA Sample 10 - 10x PCR Buffer +15mM Mg2+ 5.0 55 10µM dNTPs dTTP 0.5 5.5 dATP 0.5 5.5 dCTP 0.5 5.5 dGTP 0.5 5.5 Primer 1 (F) 0.25 2.75 Primer 2 (R) 0.25 2.75 Taq Polymerase 0.125 1.375 Nuclease free water 7.375 81.125 Total Reaction Volume 25µl Table 3.3.1: Thermal Cycling conditions for CYP2C9*2 Initial Denaturation 950C for 10 mins 1 Cycle Denaturation 950C for 5 secs 35 Cycles Annealing 530C for 10 secs Extension 720C for 15 secs Final Extension 720C for 5 mins 1 Cycle University of Ghana http://ugspace.ug.edu.gh 39 3.5.9 PCR protocol for CYP2C9*3 The CYP2C9*3 gene variant was amplified using the following reaction compositions and thermal cycling conditions. The primer sequences used are contained in Appendix I. Table 3.4: Reaction composition / mix for CYP2C9*3 Reagents 1xµl 11xµl DNA Sample 10 - 10x PCR Buffer +15mM Mg2+ 5.0 55 10µM dNTPs dTTP 0.5 5.5 dATP 0.5 5.5 dCTP 0.5 5.5 dGTP 0.5 5.5 Primer 1 (F) 0.25 2.75 Primer 2 (R) 0.25 2.75 Taq Polymerase 0.125 1.375 Nuclease free water 7.375 81.125 Total Reaction Volume 25µl Table 3.4.1: Thermal Cycling conditions for CYP2C9*3 Initial Denaturation 940C for 5 mins 1 Cycle Denaturation 940C for 45 secs 35 Cycles Annealing 530C for 45 secs Extension 720C for 1 min Final Extension 720C for 5 mins 1 Cycle University of Ghana http://ugspace.ug.edu.gh 40 3.5.10 Restriction Fragment Length Polymorphism (RFLP) For Genes under Study Aliquots of each PCR product (10µl) were digested with appropriate restriction enzymes obtained from Biolabs (AvaII for CYP2C9*2, KpnI for CYP2C9*3, NciI for VKORC1 and PvuII for CYP4F2) at 370C for 2hrs each except KpnI digestion of CYP2C9*3 which was carried out for 1hr to avoid star activity. Each reaction was performed in 20µl mixture containing 7µl of nuclease free water, 2µl of 10X NEBuffer, and 1µl restriction enzyme. The DNA fragments were electrophoresed on 2% agarose gel cast with Ethidium bromide (EtBr). Bands were detected (see Fig. 4.1, 4.2, 4.3, and 4.4), using Gel Logic 200 Imaging System from KODAK company, USA. 3.6 Statistical Analysis Data was initially entered into Microsoft ExcelTM 2010 table and then imported into StataTM version 10 (StataCorp, College Station, Texas, United States). All statistical analyses were done using StataTM version 10. Logistic regression was used to explore the association if any between categorical predictor / independent variables and categorical outcome variables. The data was summarized as frequencies and proportions. Chi square tests were performed to test for association between categorical variables. Observed genotype frequencies were compared with those expected under Hardy-Weimberg equilibrium using the χ2 test. Warfarin dosages were summarized as means with accompanying standard deviations, and compared between patients of different genotypes using t-tests and analysis of variance (ANOVA). All reported p-values were two-sided and considered statistically significant at a level of p <0.05. University of Ghana http://ugspace.ug.edu.gh 41 CHAPTER FOUR 4.0 RESULTS 4.1 Demographic and Clinical Data Influence of various patient-specific factors on daily warfarin maintenance dose (DD) was determined. A population of 143 subjects (55.9% females and 44.1% males) was recruited for the study. The most common indications for warfarin use were valve replacement (n = 63, 44%), deep vein thrombosis (n = 52, 36.4%), pulmonary embolism (n = 18, 12.6%), and atrial fibrillation (n = 10, 7.0%) (Table 4.1). Mean daily warfarin dose was negatively correlated with patient age but not statistically significant (r = -0.024, 95% CI (-0.052-0.004), p = 0.090) (Table 4.2). Warfarin dose was positively correlated with patient height but not statistically significant (r = 0.010, 95% CI (-0.031-0.052), p = 0.630) (Table 4.2). Body Mass Index (BMI) has no influence on mean daily warfarin dose; (OR = 0.571, 95% CI (0.107-3.051), p = 0.513) (Table 4.2). Females were found to be taking a higher mean daily warfarin dose 5.75mg (95% CI, 5.174-6.326) than males 5.46mg (95% CI, 4.907-6.022), p = 0.479) although this was not statistically significant as (Table 4.3). University of Ghana http://ugspace.ug.edu.gh 42 Table 4.1: Comparison of High and Low Warfarin dose Patient Populations Table 4.2: Relationship between some patient-specific factors and daily warfarin dose Factor Statistics 95% CI p Age -0.024* -0.052-0.004 0.090 Height 0.010* -0.031-0.052 0.95 BMI 0.571+ 0.107-3.051 0.513 *…… linear regression coefficient + ………Odds ratio P ≤ 0.05 denotes significance Characteristics Dosage High (>5mg) N=58, % Low (≤5mg) N=85, % Total (143) p Median Age, IQR, 46.5, (33-58) 48 (36.59) (100) 0.170, 0.650 Gender Female 32 (55.2) 48 (56.5) 80 (55.9) 0.88076 Male 26 (44.8) 37 (43.5) 63 (44.1) Diagnosis AF 2 (3.4) 8 (9.4) 10 (7.0) 0.17068 DVT PE MVR 23 (39.7) 8 (13.8) 25 (43.1) 29 (34.1) 10 (11.8) 38(44.7) 52 (36.4) 18 (12.6) 63 (44) 0.4965 0.71884 0.8493 BMI status Obese 23 (39.65) 27 (31.76) 50 (34.96) 0.20408 Overweight Underweight Normal 11 (18.97) 2 (3.45) 22 (37.93) 26 (30.58) 5 (5.88) 27 (31.76) 37 (25.87) 7 (4.90) 49 (34.27) 0.69654 0.64552 0.5485 N values indicate number of responses obtained in each category, BMI, body mass index, p ≤ 0.05 denotes significance, IQR, interquartile range, DVT, deep vein thrombosis, PE, pulmonary embolism, MVR, mitral valve replacement, AF, atrial fibrillation. University of Ghana http://ugspace.ug.edu.gh 43 Table 4.3: Gender versus Mean daily warfarin dose (mg) Mean dose 95% CI p Male 5.46 4.907-6.022 0.479 Female 5.75 5.174-6.326 4.2 PCR-RFLP Gel Electrophoreses Results L 1 2 3 4 5 6 7 8 9 10 11 L 1Kbp 500bp 400bp 100bp Fig.4.1: CYP4F2 PCR - RFLP Gel Electrophoregram A 2% agarose gel electrophoregram showing RFLP results for CYP4F2 using PvuII restriction enzyme. Lane L – 100 bp DNA ladder; lanes 1 and 10, samples homozygous to the wild-type allele (C/C). Lanes 3, 5, 7, 8, 9 and 11, heterozygous samples (C/T). Lanes 2 and 4, samples homozygous to the mutant allele (T/T). Lane 6, the uncut PCR product. University of Ghana http://ugspace.ug.edu.gh 44 L 1 2 3 4 5 6 7 8 9 10 11 12 1Kbp 600bp 500bp 100bp Fig. 4.2: VKORC1 PCR - RFLP Gel Electrophoregram A 2% agarose gel electrophoregram showing RFLP results for VKORC1 using NciI restriction enzyme. L- 100 bp DNA ladder. Lanes 5 and 8, the heterozygous samples (G/A). Lane 6, the uncut PCR product. Lanes 1, 2, 3,7,9,10,11 and 12, samples homozygous to the wild-type allele (G/G). No homozygous mutant (A/A) was detected in this study. L 1 2 3 4 5 300bp 100bp Fig. 4.3: CYP2C9*2 PCR - RFLP Gel Electrophoregram A 2% agarose gel electrophoregram showing RFLP results for CYP2C9*2 using AvaII restriction enzyme. Lane L- 100 bp DNA ladder. Lanes 1, 2, 3 and 4, samples with either the wild-type (CYP2C9*1) or the mutant (CYP2C9*3) alleles. Lane 5, the uncut PCR product. There was no sample with the mutant variant CYP2C9*2 allele. 1Kb 500bp University of Ghana http://ugspace.ug.edu.gh 45 L 1 2 3 4 5 6 7 8 9 10 11 12 1Kbp 500bp 100bp Fig. 4.4: CYP2C9*3 PCR - RFLP Gel Electrophoregram A 2% agarose gel electrophoregram showing RFLP results for CYP2C9*3 using KpnI restriction enzyme. Lane L-100 bp DNA ladder. Lanes 2, 5 and 7, samples with the variant CYP2C9*3 allele. Lane 6, the uncut PCR product. Lanes 3, 4, 8, 9, 10 and 12, samples with the wild-type (CYP2C9*1) allele. 4.3 Allele and Genotype Frequencies for CYP2C9 4.3.1 CYP2C9*3 The Hardy-Weinberg Equilibrium (HWE) was calculated using the formula in sections 2.12 and 2.12.1. The observed allele frequencies of CYP2C9*3 for the studied population and the low warfarin dose category both deviated significantly from the HWE (p < 0.05). The observed allele frequencies for high warfarin dose category were however in HWE (p > 0.05). University of Ghana http://ugspace.ug.edu.gh 46 Table 4.4: Allele and Genotype frequencies of CYP2C9*3 N = number of genotypes, n = number of alleles, SNP = single nucleotide polymorphism. † predicted Hardy-Weinberg frequencies. 4.3.2 CYP2C9*2 The CYP2C9*2 allele frequencies as well as genotype frequencies and their further categorization into low dose and high dose are summarized in Table 4.5 In the current study, all individuals (100%) had the common (C) allele and none carried the minor (T) allele for CYP2C9*2. The same observation was made in subjects on either low or high daily warfarin dose. SNP n Allele Freq N Genotype Observed (Expected†) frequencies (%) CYP2C9*3 142 *1 0.77 60 *1/*1 65.22 (59.56) 42 *3 0.23 22 *1/*3 23.91 (35.23) 10 *3/*3 10.87 (5.21) CYP2C9*3 83 *1 0.80 37 *1/*1 71.15 (63.69) (Low Dose) 21 *3 0.20 9 *1/*3 17.31 (32.23) 6 *3/*3 11.54 (4.08) CYP2C9*3 59 *1 0.74 23 *1/*1 57.50 (54.39) (High Dose) 21 *3 0.26 13 *1/*3 32.50 (38.72) 4 *3/*3 10.0 (6.89) University of Ghana http://ugspace.ug.edu.gh 47 Table 4.5: Allele and Genotype frequencies of CYP2C9*2 N = number of genotypes, n = number of alleles, SNP = single nucleotide polymorphism, C = Common allele, T = Minor Allele. 4.4 Allele and Genotype Frequencies for VKORC1 The VKORC1 allele frequencies as well as genotype frequencies and their further categorization into low dose and high dose groups within the Ghanaian population are summarized in Table 4.6 The observed allele frequencies of VKORC1 for the studied population were in HWE (p > 0.05), likewise the observed allele frequencies of both the low dose and high dose patient categories. SNP n Allele Freq N Genotype Freq CYP2C9*2 174 C 1.00 87 C/C 1.00 0 T 0.00 0 C/T 0.00 0 T/T 0.00 CYP2C9*2 92 C 1.00 46 C/C 1.00 (Low Dose) 0 T 0.00 0 C/T 0.00 0 T/T 0.00 CYP2C9*2 82 C 1.00 41 C/C 1.00 (High Dose) 0 T 0.00 0 C/T 0.00 0 T/T 0.00 University of Ghana http://ugspace.ug.edu.gh 48 Table 4.6 Allele and Genotype frequencies of VKORC1 N = number of genotypes, n = number of alleles, SNP = single nucleotide polymorphism. † predicted Hardy-Weinberg frequencies. 4.4 Allele and Genotype Frequencies for CYP4F2 The CYP4F2 (V433M: rs2108622: C>T) allele frequencies as well as genotype frequencies and their further categorization into low dose and high dose groups within the Ghanaian population are summarized in Table 4.7 The observed allele frequencies of CYP4F2 significantly deviated from HWE (p < 0.05), likewise the allele frequencies observed for both the low dose and the high dose groups. SNP n Allele Freq N Genotype Observed (Expected†) Frequencies (%) VKORC1- 1639G>A 182 G 0.94 85 G/G 87.63 (88.01) 12 A 0.06 0 G/A 12.37 (11.61) 12 A/A 0.00 (0.38) VKORC1- 1639G>A 105 G 0.91 47 G/G 81.03 (81.93) (Low Dose) 11 A 0.09 0 G/A 18.97 (17.17) 11 A/A 0.00 (0.90) VKORC1- 1639G>A 77 G 0.99 38 G/G 97.44 (97.45) (High Dose) 1 A 0.01 0 G/A 2.56 (2.53) 1 A/A 0.00 (0.02) University of Ghana http://ugspace.ug.edu.gh 49 Table 4.7: Allele and Genotype frequencies of CYP4F2 N = number of genotypes, n = number of alleles, SNP = single nucleotide polymorphism. † predicted Hardy-Weinberg frequencies. 4.5 Prevalence of CYP2C9, VKORC1 and CYP4F2 genotypes and Mean Daily Warfarin Dosage According to the CYP2C9 genotypes, the highest daily warfarin dosages were administered to carriers of the heterozygous (*1/*3) genotype, while carriers of the wild-type CYP2C9*1/*1 genotype were treated with lower daily warfarin dosages of (6.82 ± 0.56 mg/day and 5.84 ±0.25 mg/day) respectively. Carriers of the homozygous mutant (*3/*3) were given intermediate daily warfarin dosages of (6.50 ±0.67 mg/day). The carriers of the homozygous mutant (T/T) genotype for CYP4F2 were treated with higher daily warfarin dosages (6.88 ±0.41 mg/day) compared to the heterozygous (C/T) genotype (6.13 ±0.22 mg/day). Patients with the homozygous wild-type (C/C) were given intermediate daily warfarin dosages of (6.16 ±0.55 mg/day). The carriers of the homozygous wild-type (G/G) genotype for VKORC1, were given higher daily warfarin dosages (6.14 ±0.22 mg/day), than carriers of the heterozygous (G/A) genotype SNP n Allele Freq N Genotype Observed (Expected†) Frequencies (%) CYP4F2 137 C 0.59 28 C/C 23.93 (34.28) 97 T 0.41 81 C/T 69.23 (48.54) 8 T/T 6.84 (17.18) CYP4F2 80 C 0.63 18 C/C 28.13 (39.06) (Low Dose) 48 T 0.37 44 C/T 68.75 (46.88) 2 T/T 3.13 (14.06) CYP4F2 57 C 0.54 10 C/C 18.87 (28.92) (High Dose) 49 T 0.46 37 C/T 69.81 (49.72) 6 T/T 11.32 (21.37) University of Ghana http://ugspace.ug.edu.gh 50 (4.97 ±0.55 mg/day) (Table 4.8). There were no carriers of the homozygous mutant genotype (A/A) in this study. Table 4.8: The prevalence of CYP2C9, VKORC1 and CYP4F2 Genotypes and Mean Daily Warfarin Dosage Genotype Prevalence n (%) Daily Warfarin Dosage mean(SD), mg p CYP2C9*2 0 (0.00)% - - CYP2C9*3 *1/*1 60(65.2%) 5.84(0.25) 0.169 *1/*3 22(23.9%) 6.82(0.56) *3/*3 10(10.9%) 6.50(0.67) CYP4F2 C/C 28(23.9%) 6.16(0.55) 0.651 C/T 81(69.2%) 6.13(0.22) T/T 8(6.8%) 6.88(0.41) VKORC1 G/G 85(87.6%) 6.14(0.22) G/A 12(12.4%) 4.97(0.55) 0.065 A/A - - CYP2C9*3: *1/*1 = homozygous wild-type genotype, *1/*3 = heterozygous genotype, *3/*3 = homozygous mutant genotype, CYP4F2: C/C = wild-type genotype, C/T = heterozygous genotype, T/T = homozygous mutant genotype, VKORC1: G/A = heterozygous genotype, G/G = homozygous wild-type, and A/A = homozygous mutant genotype. 4.6 The Mean Daily Warfarin Dosage According to Combined CY2C9, VKORC1 and CYP4F2 Gene Variants According to the combined CYP2C9, VKORC1 and CYP4F2 genotypes, patients having the wild-type (*1/*1) genotype of CYP2C9 in combination with the homozygous mutant (T/T) genotype of CYP4F2 and the wild-type (G/G) genotype of VKORC1 required the highest mean daily warfarin dosage of 7.50mg/day (95% CI 7.50-7.50), p = 0.096). It was also University of Ghana http://ugspace.ug.edu.gh 51 observed that patients with a combination of CYP2C9 wild-type (*1/*1), CYP4F2 wild-type (C/C) and VKORC1 wild-type (G/G) genotypes were treated with the lowest mean daily warfarin dosage of 4.79mg/day (95% CI 3.02-6.55), p = 0.096). The findings also revealed that carriers of CYP2C9 wild-type (*1/*1), who are heterozygous (C/T) for CYP4F2 and also carry VKORC1 wild-type (G/G) genotypes required an intermediate mean daily warfarin dosage of 5.78mg/day (95% CI 5.10-6.45), p = 0.096). Furthermore, carriers of the homozygous mutant (*3/*3) for CYP2C9, heterozygous (C/T) for CYP4F2 and the wild-type (G/G) genotype for VKORC1 were administered 6.67mg/day (95% CI 5.00-8.33). Also, carriers of the heterozygous (*1/*3) genotype for CYP2C9, heterozygous (C/T) genotype for CYP4F2 and the wild-type (G/G) genotype for VKORC1 were given 6.50mg/day (95% CI 5.40-7.60), p = 0.027). Table 4.9: The Mean Daily Warfarin Dosage According to Combined CYP2C9, VKORC1 and CYP4F2 Gene Variants CYP2C9*3 CYP4F2 VKORC1 freq(%) mean(95%CI) dose class p* *1/*1 C/C G/A 1(1.45) 5(-) Low dose 0.096 *1/*1 C/C G/G 7(10.14) 4.79(3.02-6.55) Low dose *1/*1 C/T G/A 1(1.45) 5(-) Low dose *1/*1 C/T G/G 27(39.13) 5.78(5.10-6.45) High dose *1/*1 T/T G/A 1(1.45) 5(-) Low dose *1/*1 T/T G/G 5(7.25) 7.50(7.50-7.50) High dose *1/*3 C/C G/G 1(1.72) 15(-) High dose 0.027 *1/*3 C/T G/A 1(1.45) 5(-) Low dose *1/*3 C/T G/G 15(21.74) 6.50(5.40-7.60) High dose *1/*3 T/T G/G 0 - - *3/*3 C/T G/G 9(13.04) 6.67(5.00-8.33) High dose - *3/*3 T/T G/A 0 - - 68(100%) CYP2C9*3: *1/*1 = homozygous wild-type, *1/*3 = heterozygous genotype, *3/*3 = homozygous mutant genotype, CYP4F2: C/C = wild-type genotype, C/T = heterozygous genotype, T/T = homozygous mutant, VKORC1: G/A = heterozygous genotype, and G/G = homozygous wild-type. *Analysis of variance (ANOVA). University of Ghana http://ugspace.ug.edu.gh 52 Table 4.10: Frequency distribution for CYP2C9 alleles in Ghanaian and other previously studied populations. Ethnicity N *1 *2 *3 References African Ghanaian 184 0.77 0.0 0.23 This study Ghanaian 195 0.98 0.0 0.0 (Kudzi et al., 2009) Beninese 107 0.955 0.0 0.0 (Allabi et al., 2003) Ethiopian 150 0.977 0.043 0.023 (Scordo et al., 2001) African-American 107 0.914 0.033 0.023 (Dreisbach et al., 2005) Caucasians Belgian 121 0.822 0.10 0.074 (Allabi et al., 2003) Canadian 325 0.78 0.15 0.07 (Gaedigk et al., 2001) Swedish 430 0.82 0.107 0.074 (Yasar et al., 1999) Russian 290 0.82 0.11 0.07 (Gaikovitch et al., 2003) Asians Chinese 102 0.95 0.0 0.05 (Gaedigk et al., 2001) Japanese 218 0.98 0.0 0.02 (Nasu et al., 1997) Korean 574 0.99 0.0 0.01 (Yoon et al., 2001) N = number of Alleles University of Ghana http://ugspace.ug.edu.gh 53 CHAPTER FIVE 5.0 DISCUSSION AND CONCLUSIONS 5.1 DISCUSSION This study was designed to determine the frequencies of CYP2C9*1, *2, *3 allele variants, VKORC1_1639G>A and CYP4F2 _1347C>T gene polymorphisms in Ghanaian patients on either low or high warfarin maintenance therapy to ascertain the genetic basis of dose variation. The effects of patient specific factors such as age, sex, height, and body mass index on daily warfarin dosage were also assessed. The most prevalent indications for warfarin use were valve replacement (n = 63, 44%), deep vein thrombosis (n = 52, 36.4%), pulmonary embolism (n = 18, 12.6%), and atrial fibrillation (n = 10, 7.0%) (Table 4.1) and these differed from 10.8% (valve replacement), 24.5% (deep vein thrombosis), 12.2% (pulmonary embolism), and 49.6% (atrial fibrillation) reported by Whitley (Whitley et al., 2007) in an African-American population. Warfarin dose was negatively correlated with patient age but statistically not significant (r = -0.024) 95% CI (- 0.052-0.004), p = 0.090). This observation compares with what was reported for an African- American population where it was observed that total weekly warfarin dosage was 2.4 mg less for each additional decade of patient age (Whitley et al., 2007). In this study, women were found to be taking a higher mean daily warfarin dose of 5.75mg (95% CI (5.174-6.326) compared to men who were administered 5.460mg (95% CI (4.907-6.022), p = 0.479), although this was not statistically significant. This observation was however different from what was reported in an African-American population where women were found to require 2.55mg lower total weekly warfarin dosage compared to men, though not statistically significant (Whitley et al., 2007). Previous studies also reported that women require an University of Ghana http://ugspace.ug.edu.gh 54 average of 4.5mg less of warfarin per week (Ansell et al., 2004; Garcia et al., 2005). Warfarin dose was positively correlated with patient height but statistically not significant (r = 0.010, (95% CI (-0.031-0.052), p = 0.630) and this differed from what was reported in Lithuanian patients where higher daily warfarin dosages were prescribed for heavier and taller patients (Tatarunas et al., 2011). In this study, BMI has no influence on mean daily warfarin dose (OR = 0.571, p = 0.513) and this was consistent with findings from previous studies which also reported no relationship between BMI or body weight and warfarin dose (Blann et al., 1999; Gurwitz et al., 1992; Oates et al., 1998). This observation was however in contrast with what was reported in an African-American population where a weak correlation was found between BMI and Total Weekly warfarin Dose (TWD) (r = 0.08) though not statistically significant (Whitley et al., 2007). Other studies have also indicated that height has greater predictive value of warfarin dose than does body weight or BMI (Sconce et al 2005). However, Singla and Morrill reported that BMI influences TWD as equal as gender (r2 = 5.3, p = 0.001) (Singla & Morrill, 2005). Warfarin, the most commonly prescribed anti-clotting drug is a drug of choice for testing the hypothesis that pharmacogenetics can predict and reduce the incidence of adverse drug reactions. Warfarin has a narrow therapeutic/toxic ratio and is affected by common genetic polymorphisms. Use of clinical and patient-specific factors such as age, body size, race, concurrent diseases, and medications) explain some of the variability in warfarin dose but genetic factors influencing warfarin response explain a significantly higher proportion of the variability in dose (Wadelius & Pirmohamed, 2007b). The combination of the two CYP2C9 variants (*2 and *3) with the VKORC1 promoter mutation is estimated to account for 40% – University of Ghana http://ugspace.ug.edu.gh 55 63% of the variability in therapeutic warfarin dose (Rieder et al., 2005; Sconce et al., 2005). Recent genome wide association studies have not only confirmed these observations but also identified a novel association between reduced hepatic CYP4F2, higher levels of hepatic vitamin K, and higher warfarin dose requirements (Singh et al., 2011). In the present study, allele frequencies for CYP2C9*3 were observed at (23%) and this observation differed from an earlier report in a Ghanaian population by (Kudzi et al., 2009) where no CYP2C9*3 variant alleles were detected. The allele frequency observed for CYP2C9*3 in this study was high compared to frequencies obtained within the African- American and Ethiopian populations which were both 2.3% (Dreisbach et al., 2005; Scordo et al., 2001). This variant was prevalent at 1% in Korean, 2% in Japanese and 5% in Chinese populations (Gaedigk et al., 2001; Yoon et al., 2001) (Table 4.10). Genotype frequencies for CYP2C9*3 were observed at (10.87%). This was higher than that reported in the Egyptian (0.40%) population (Hamdy et al., 2002). This finding was also different from those reported in Moroccan (2%) and Libyan (3.3%) populations (Nakai et al., 2005). The CYP2C9*2 genotype and variant alleles were not detected in this study and this was consistent with an earlier report in a Ghanaian population (Kudzi et al., 2009). This finding agrees with those reported in Moroccan and Libyan populations (Nakai et al., 2005) as well as in a Beninese population (Allabi et al., 2003) (Table 4.10). This observation was however different from that reported in the Egyptian (2.43%) population (Hamdy et al., 2002) as well as in an African-American population and Ethiopian populations. The CYP2C9*2 variant University of Ghana http://ugspace.ug.edu.gh 56 allele was reported at 3.3% in an African American population (Dreisbach et al., 2005) and 4.3% in an Ethiopian population (Scordo et al., 2001). The CYP2C9*2 variant allele has been reported at 10-15% among the Caucasian populations (Allabi et al., 2003) but was absent from Asian populations (Table 4.10). Allele frequencies for VKORC1_1639A were observed at (6%). This observation is similar to that reported for African-Americans (10.8%) (Scott et al., 2009) but lower than that reported for Asians (66.7%), Caucasians (40.6%), Hispanics (43.6%) (Scott et al., 2010) and Ashkenazi Jewish (46.7%) populations (Scott et al., 2008). The VKORC1_1639A genotype (A/A) was not detected in this study and this is consistent with a previous study which reported that this genotype is very rare (1%) in Africans (Huang et al., 2009). This observation however differed from that reported in other ethnic populations; African-American (2.0%), Asians (55.9%), Caucasians (17.9%), Hispanics (17.8%) and Ashkenazi Jewish (22.7%) populations (Scott et al., 2008; Scott et al., 2009). Allele frequencies for CYP4F2 rs2108622 (T) was observed at (41%). This observation is higher than that reported in African-Americans (11.7%), Asians (30.5%), Caucasians (34.2%), Hispanics (23.3%) and Ashkenazi Jewish (32.8%) populations (Scott et al., 2010). Genotype frequencies for CYP4F2 rs2108622 (T/T) was observed at (6.84%). This observation was lower than that reported for Caucasians (11%), Ashkenazi Jewish (9%) and Asians (9%) populations (Scott et al., 2010) but was higher than that reported in African- Americans (1.3%), and Hispanics (5.3%) populations (Scott et al., 2010). University of Ghana http://ugspace.ug.edu.gh 57 From the CYP2C9 genotypes, the highest mean daily warfarin dosages in this study were administered to carriers of the heterozygous (*1/*3) genotype, while carriers of the wild-type CYP2C9*1/*1 genotype were treated with lower daily warfarin dosages (6.82 ± 0.56 mg/day) and 5.84 ± 0.25 mg/day respectively (p = 0.169). Carriers of the homozygous mutant (*3/*3) genotype were given intermediate daily warfarin dosages of 6.50 ± 0.67 mg/day. These findings were in contrast with those reported in the Lithuanian population where the highest daily warfarin dosages were given to carriers of CYP2C9 wild-type (*1/*1) genotype, while carriers of the CYP2C9 heterozygous (*1/*3) were treated with lower daily warfarin dosages 5.84 ± 2.84 mg/day versus 4.28 ± 1.92 mg/day (Tatarunas et al., 2011). The carriers of the homozygous minor (T/T) genotype for CYP4F2, were treated with higher daily warfarin dosages (6.88 ± 0.41 mg/day) than carriers of the heterozygous (C/T) genotype 6.13 ± 0.22 mg/day (p = 0.651). Patients with the homozygous wild-type (C/C) genotype were given intermediate daily warfarin dosages of 6.16 ± 0.55 mg/day. This observation was slightly different from that reported in Asian adult patients where carriers of the heterozygous (C/T) and carriers of the homozygous minor (T/T) genotypes of CYP4F2 required a 25% higher warfarin dosage than carriers of the wild-type (C/C) genotype (Singh et al., 2011). In this study, the carriers of the homozygous wild-type (G/G) genotype for VKORC1, were given higher daily warfarin dosages (6.14 ± 0.22 mg/day), than carriers of the heterozygous (G/A) genotype (4.97 ± 0.55 mg/day) (p = 0.065). There were no carriers of the homozygous mutant (A/A) genotype in this population. These findings were similar to those reported for the Lithuanian population where higher daily warfarin dosages were administered to carriers of the VKORC1 wild-type (G/G) genotype as compared to carriers of the heterozygous (G/A) University of Ghana http://ugspace.ug.edu.gh 58 (6.20 ± 2.78 mg/day and 5.60 ± 2.77 mg/day (p = 0.04) respectively. Carriers of the homozygous mutant (A/A) genotype were treated with significantly lower daily warfarin dosages (3.75 ± 1.40 mg/day (p = 0.04) than those carrying the wild-type (G/G) genotype (Tatarunas et al., 2011). Using the combined effect of the CYP2C9, VKORC1 and CYP4F2 genotypes, patients having the wild-type (*1/*1) genotype of CYP2C9 in combination with the homozygous mutant (T/T) genotype of CYP4F2 and the wild-type (GG) genotype of VKORC1 required the highest mean daily warfarin dosage of 7.50 mg/day to achieve the required therapeutic effect. This observation is consistent with previous reports which indicated that carriers of CYP2C9*1/*1 and VKORC1 (G/G) genotypes exhibit low sensitivity to warfarin (Scibona et al., 2012) while carriers of the homozygous mutant (T/T) genotype of CYP4F2 require higher daily warfarin dosages (Singh et al., 2011). This suggests that the standard administration of 5 mg of warfarin to initiate treatment in such patients could lead to hyper-coagulation which may result in thrombotic complications. It was also observed that patients with a combination of CYP2C9 wild-type (*1/*1), CYP4F2 wild-type (C/C) and VKORC1 wild-type (GG) genotypes were treated with the lowest mean daily warfarin dosage of 4.79mg/day. This also confirms what was reported in other studies that carriers of the wild-type (C/C) genotype of CYP4F2 require 25% lower warfarin dosages than those with either the heterozygous (C/T) or the homozygous mutant (T/T) genotypes (Singh et al., 2011). This suggests that the standard administration of 5 mg of warfarin to initiate treatment in such patients could lead to hypo-coagulation which may cause bleeding complications. The findings further revealed that carriers of CYP2C9 wild-type (*1/*1), who University of Ghana http://ugspace.ug.edu.gh 59 are heterozygous (C/T) for CYP4F2 and also carry VKORC1 wild-type (G/G) genotypes required an intermediate mean daily warfarin dosage of 5.78mg/day. 5.2 LIMITATIONS The sample size of 143 may not be large enough to extrapolate findings from this study to cover warfarin dose / response for the entire Ghanaian population. This limitation was as a result of lack of relevant resources and the limited time frame within which this thesis has to be submitted for examination. 5.3 CONCLUSIONS The current study has led to the determination of allelic variants of CYP2C9, VKORC1 and CYP4F2 in a Ghanaian population. With the exception of CYP2C9 which has already been reported in a Ghanaian population by a previous study, VKORC1 and CYP4F2 variant alleles to our knowledge are being reported for the first time among the indigenous Ghanaian population. This study has also established for the first time, the combined effect of genotypes of CYP2C9, VKORC1 and CYP4F2 genes on mean daily warfarin dosage where carriers of the wild-type genotypes of CYP2C9 (*1/*1) and VKORC1 (G/G) together with the homozygous mutant (T/T) genotype for CYP4F2 required the highest mean daily warfarin dosages of 7.50 mg/day at 95% CI (7.50-7.50), p = 0.096, compared to those with the wild-type genotypes of all three genes who required 4.79 mg/day at 95% CI (3.02-6.55), p = 0.096. Patients who had the heterozygous (C/T) genotype for CYP4F2 in addition to the wild-type genotypes of University of Ghana http://ugspace.ug.edu.gh 60 CYP2C9 and VKORC1 were given an intermediate daily warfarin dosage of 5.78 mg/day at 95% CI (5.10-6.45), p = 0.096. Also, carriers of the heterozygous genotypes of CYP2C9 (*1/*3), and CYP4F2 (C/T) and the wild-type (G/G) genotype of VKORC1 were given 6.50 mg/day at 95% CI (5.40-7.60), p = 0.027. Subjects with a combination of CYP2C9*3/*3, (C/T) for CYP4F2, and (G/G) for VKORC1 genotypes were given 6.67 mg/day at 95% CI (5.00-8.33). 5.4 RECOMMENDATIONS It is recommended that this study be carried out with a larger sample size so that the correlations established can reflect that of the larger Ghanaian population. It is possible that there may be other mutations in the genes genotyped in this study which may have some effect on warfarin dose / response in the Ghanaian population. It is therefore recommended that further investigation be carried out to ascertain this. These results provide additional information on polymorphisms of CYP2C9, CYP4F2, and VKORC1 subfamily of enzymes in an indigenous African population which is scarce in published literature and can be added to Pharmacogenetics for Every Nation Initiative (PGENI) database. PGENI has been set-up with the main objective of integrating pharmacogenetics into public health care for all global populations and aims to determine the baseline frequencies of known DNA variants present in 154 genes which are involved with the action of 206 drugs. University of Ghana http://ugspace.ug.edu.gh 61 REFERENCES Allabi, A. C., Gala, J. L., Desager, J. P., Heusterspreute, M., & Horsmans, Y. (2003). Genetic polymorphisms of CYP2C9 and CYP2C19 in the Beninese and Belgian populations. [Research Support, Non-U.S. Gov't]. Br J Clin Pharmacol, 56(6), 653-657. Alving, A. S., Carson, P. E., Flanagan, C. L., & Ickes, C. E. (1956). Enzymatic deficiency in primaquine-sensitive erythrocytes. Science, 124(3220), 484-485. Ameyaw, M. M., Regateiro, F., Li, T., Liu, X., Tariq, M., Mobarek, A., . . . McLeod, H. L. (2001). MDR1 pharmacogenetics: frequency of the C3435T mutation in exon 26 is significantly influenced by ethnicity. Pharmacogenet. 11(3), 217-221. Ansell, J., Hirsh, J., Poller, L., Bussey, H., Jacobson, A., & Hylek, E. (2004). The pharmacology and management of the vitamin K antagonists: the Seventh ACCP Conference on Antithrombotic and Thrombolytic Therapy. [Guideline Practice Guideline]. Chest, 126(3 Suppl), 204S-233S. doi: 10.1378/chest.126.3_suppl.204S. Aomori, T., Yamamoto, K., Oguchi-Katayama, A., Kawai, Y., Ishidao, T., Mitani, Y., . . . Horiuchi, R. (2009). Rapid single-nucleotide polymorphism detection of cytochrome P450 (CYP2C9) and vitamin K epoxide reductase (VKORC1) genes for the warfarin dose adjustment by the SMart-amplification process version 2. [Research Support, Non-U.S. Gov't]. Clin Chem, 55(4), 804-812. doi: 10.1373/clinchem.2008.115295. Arledge, E., Cort, J., Krulwich, R., Lander, E. S., Clear Blue Sky, P., Wgbh, & Video, W. (2001). Cracking the code of life. Au, N., & Rettie, A. E. (2008). Pharmacogenomics of 4-hydroxycoumarin anticoagulants. [Research Support, N.I.H., Extramural Review]. Drug Metab Rev. 40(2), 355-375. doi: 10.1080/03602530801952187. University of Ghana http://ugspace.ug.edu.gh 62 Blann, A., Hewitt, J., Siddiqui, F., & Bareford, D. (1999). Racial background is a determinant of average warfarin dose required to maintain the INR between 2.0 and 3.0. Br J Haematol. 107(1), 207-209. Booth, S. L., Charnley, J. M., Sadowski, J. A., Saltzman, E., Bovill, E. G., & Cushman, M. (1997). Dietary vitamin K1 and stability of oral anticoagulation: proposal of a diet with constant vitamin K1 content. [Research Support, U.S. Gov't, Non-P.H.S. Review]. Thromb Haemost. 77(3), 504-509. Borgiani, P., Ciccacci, C., Forte, V., Sirianni, E., Novelli, L., Bramanti, P., & Novelli, G. (2009). CYP4F2 genetic variant (rs2108622) significantly contributes to warfarin dosing variability in the Italian population. Pharmacogenom. 10(2), 261-266. doi: 10.2217/14622416.10.2.261. Bozina, N. (2010). The Pharmacogenetics of Warfarin in Clinical Practice. Biochemia Medica, 20(1), 33-34. http://dx.doi.org/10.11613/BM.2010.005. Breckenridge, A., Orme, M., Wesseling, H., Lewis, R. J., & Gibbons, R. (1974). Pharmacokinetics and pharmacodynamics of the enantiomers of warfarin in man. Clin Pharmacol Ther. 15(4), 424-430. Buckley, N. A., & Dawson, A. H. (1992). Drug interactions with warfarin. [Review]. Med J Aust. 157(7), 479-483. Burian, M., Grosch, S., Tegeder, I., & Geisslinger, G. (2002). Validation of a new fluorogenic real-time PCR assay for detection of CYP2C9 allelic variants and CYP2C9 allelic distribution in a German population. [Research Support, Non-U.S. Gov't Validation Studies]. Br J Clin Pharmacol. 54(5), 518-521. University of Ghana http://ugspace.ug.edu.gh 63 Caldwell, M. D., Berg, R. L., Zhang, K. Q., Glurich, I., Schmelzer, J. R., Yale, S. H., . . . Burmester, J. K. (2007). Evaluation of genetic factors for warfarin dose prediction. Clin Med Res. 5(1), 8-16. Cavallari, L. H., Langaee, T. Y., Momary, K. M., Shapiro, N. L., Nutescu, E. A., Coty, W. A., . . . Johnson, J. A. (2010). Genetic and clinical predictors of warfarin dose requirements in African Americans. Clin pharmacol ther. 87(4), 459-464. Crespi, C. L., & Miller, V. P. (1997). The R144C change in the CYP2C9*2 allele alters interaction of the cytochrome P450 with NADPH:cytochrome P450 oxidoreductase. Pharmacogenet. 7(3), 203-210. D'Andrea, G., D'Ambrosio, R. L., Di Perna, P., Chetta, M., Santacroce, R., Brancaccio, V., . . . Margaglione, M. (2005). A polymorphism in the VKORC1 gene is associated with an interindividual variability in the dose-anticoagulant effect of warfarin. Blood, 105(2), 645-649. Daly, A. K., & King, B. P. (2003). Pharmacogenetics of oral anticoagulants. Pharmacogenet. 13(5), 247-252. De Morais, S. M., Wilkinson, G. R., Blaisdell, J., Meyer, U. A., Nakamura, K., & Goldstein, J. A. (1994). Identification of a new genetic defect responsible for the polymorphism of (S)-mephenytoin metabolism in Japanese. Mol pharmacol. 46(4), 594-598. Demirkan, K., Stephens, M. A., Newman, K. P., & Self, T. H. (2000). Response to warfarin and other oral anticoagulants: effects of disease states. [Review]. South Med J, 93(5), 448-454; quiz 455. Dorak, M. T. ( 2005). Basic population genetics. http://dorakmt.tripod.com/genetics/popgen.html. 08/03/2014. University of Ghana http://ugspace.ug.edu.gh 64 Dreisbach, A. W., Japa, S., Sigel, A., Parenti, M. B., Hess, A. E., Srinouanprachanh, S. L., . . . Lertora, J. J. (2005). The Prevalence of CYP2C8, 2C9, 2J2, and soluble epoxide hydrolase polymorphisms in African Americans with hypertension. [Comparative Study Research Support, N.I.H., Extramural Research Support, U.S. Gov't, P.H.S.]. Am J Hypertens. 18(10), 1276-1281. doi: 10.1016/j.amjhyper.2005.04.019. Evans, W. E., & Relling, M. V. (1999). Pharmacogenomics: translating functional genomics into rational therapeutics. [Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, P.H.S. Review]. Science, 286(5439), 487-491. Falany, C. N. (1997). Sulfation and Sulfotransferases 3: Enzymology of human cytosolic sulfotransferases. FASEB J, 11(4), 206-216. Gaedigk, A., Casley, W. L., Tyndale, R. F., Sellers, E. M., Jurima-Romet, M., & Leeder, J. S. (2001). Cytochrome P4502C9 (CYP2C9) allele frequencies in Canadian Native Indian and Inuit populations. [Research Support, U.S. Gov't, P.H.S.]. Can J Physiol Pharmacol. 79(10), 841-847. Gage, B. F., & Lesko, L. J. (2008). Pharmacogenetics of warfarin: regulatory, scientific, and clinical issues. [Research Support, N.I.H., Extramural Review]. J Thromb Thrombolysis. 25(1), 45-51. doi: 10.1007/s11239-007-0104-y. Gaikovitch, E. A., Cascorbi, I., Mrozikiewicz, P. M., Brockmoller, J., Frotschl, R., Kopke, K., . . . Roots, I. (2003). Polymorphisms of drug-metabolizing enzymes CYP2C9, CYP2C19, CYP2D6, CYP1A1, NAT2 and of P-glycoprotein in a Russian population. Eur J Clin Pharmacol. 59(4), 303-312. doi: 10.1007/s00228-003-0606-2. University of Ghana http://ugspace.ug.edu.gh 65 Ganeval, D., Fischer, A. M., Barre, J., Pertuiset, N., Dautzenberg, M. D., Jungers, P., & Houin, G. (1986). Pharmacokinetics of warfarin in the nephrotic syndrome and effect on vitamin K-dependent clotting factors. Clin Nephrol. 25(2), 75-80. Garcia, D., Regan, S., Crowther, M., Hughes, R. A., & Hylek, E. M. (2005). Warfarin maintenance dosing patterns in clinical practice: implications for safer anticoagulation in the elderly population. [Comparative Study Research Support, Non-U.S. Gov't]. Chest, 127(6), 2049-2056. doi: 10.1378/chest.127.6.2049. Gedge, J., Orme, S., Hampton, K. K., Channer, K. S., & Hendra, T. J. (2000). A comparison of a low-dose warfarin induction regimen with the modified Fennerty regimen in elderly inpatients. Age Ageing, 29(1), 31-34. Gerbal-Chaloin, S., Pascussi, J. M., Pichard-Garcia, L., Daujat, M., Waechter, F., Fabre, J. M., . . . Maurel, P. (2001). Induction of CYP2C genes in human hepatocytes in primary culture. Drug metabol dispos: biol fate chem. 29(3), 242-251. Goldstein, J. A. (2001). Clinical relevance of genetic polymorphisms in the human CYP2C subfamily. Br j clin pharmacol. 52(4), 349-355. Grasmäder, K., Verwohlt, P. L., Rietschel, M., Dragicevic, A., Müller, M., Hiemke, C., . . . Rao, M. L. (2004). Impact of polymorphisms of cytochrome-P450 isoenzymes 2C9, 2C19 and 2D6 on plasma concentrations and clinical effects of antidepressants in a naturalistic clinical setting. Eur j clin pharmacol. 60(5), 329-336. Gray, I. C., Nobile, C., Muresu, R., Ford, S., & Spurr, N. K. (1995). A 2.4-megabase physical map spanning the CYP2C gene cluster on chromosome 10q24. [Research Support, Non-U.S. Gov't]. Genom. 28(2), 328-332. doi: 10.1006/geno.1995.1149. University of Ghana http://ugspace.ug.edu.gh 66 Guengerich, F. P. (2008). Cytochrome p450 and chemical toxicology. [Research Support, N.I.H., Extramural Review]. Chem Res Toxicol. 21(1), 70-83. doi: 10.1021/tx700079z Gurwitz, J. H., Avorn, J., Ross-Degnan, D., Choodnovskiy, I., & Ansell, J. (1992). Aging and the anticoagulant response to warfarin therapy. [Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, P.H.S.]. Ann Intern Med. 116(11), 901-904. Haining, R. L., Hunter, A. P., Veronese, M. E., Trager, W. F., & Rettie, A. E. (1996). Allelic variants of human cytochrome P450 2C9: baculovirus-mediated expression, purification, structural characterization, substrate stereoselectivity, and prochiral selectivity of the wild-type and I359L mutant forms. Arch Biochem Biophys. 333(2), 447-458. Hamdy, S. I., Hiratsuka, M., Narahara, K., El-Enany, M., Moursi, N., Ahmed, M. S., & Mizugaki, M. (2002). Allele and genotype frequencies of polymorphic cytochromes P450 (CYP2C9, CYP2C19, CYP2E1) and dihydropyrimidine dehydrogenase (DPYD) in the Egyptian population. [Comparative Study]. Br J Clin Pharmacol. 53(6), 596- 603. Higashi, M. K., Veenstra, D. L., Kondo, L. M., Wittkowsky, A. K., Srinouanprachanh, S. L., Farin, F. M., & Rettie, A. E. (2002). Association between CYP2C9 genetic variants and anticoagulation-related outcomes during warfarin therapy. [Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, P.H.S.]. JAMA, 287(13), 1690-1698. Hirsh, J., Dalen, J., Anderson, D. R., Poller, L., Bussey, H., Ansell, J., & Deykin, D. (2001). Oral anticoagulants: mechanism of action, clinical effectiveness, and optimal therapeutic range. [Review]. Chest, 119(1 Suppl), 8S-21S. University of Ghana http://ugspace.ug.edu.gh 67 Holbrook, A. M., Pereira, J. A., Labiris, R., McDonald, H., Douketis, J. D., Crowther, M., & Wells, P. S. (2005). Systematic overview of warfarin and its drug and food interactions. [Review]. Arch Intern Med. 165(10), 1095-1106. doi: 10.1001/archinte.165.10.1095. Huang, S. W., Chen, H. S., Wang, X. Q., Huang, L., Xu, D. L., Hu, X. J., . . . Xu, X. M. (2009). Validation of VKORC1 and CYP2C9 genotypes on interindividual warfarin maintenance dose: a prospective study in Chinese patients. [Randomized Controlled Trial Research Support, Non-U.S. Gov't]. Pharmacogenet Genom. 19(3), 226-234. doi: 10.1097/FPC.0b013e328326e0c7. Iafrate, A. J., Feuk, L., Rivera, M. N., Listewnik, M. L., Donahoe, P. K., Qi, Y., . . . Lee, C. (2004). Detection of large-scale variation in the human genome. Nature Genet. 36(9), 949-951. Jaffer, A., & Bragg, L. (2003). Practical tips for warfarin dosing and monitoring. [Research Support, Non-U.S. Gov't Review]. Cleve Clin J Med. 70(4), 361-371. Johnson, J. A., Gong, L., Whirl-Carrillo, M., Gage, B. F., Scott, S. A., Stein, C. M., . . . Altman, R. B. (2011). Clinical Pharmacogenetics Implementation Consortium Guidelines for CYP2C9 and VKORC1 genotypes and warfarin dosing. [Practice Guideline Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't Review]. Clin Pharmacol Ther. 90(4), 625-629. doi: 10.1038/clpt.2011.185. Jonas, D. E., & McLeod, H. L. (2009). Genetic and clinical factors relating to warfarin dosing. Trends Pharmacol. Sci. 30(7), 375-386. University of Ghana http://ugspace.ug.edu.gh 68 Kalow, W. (2002). Pharmacogenetics and personalised medicine. Fund clin pharmacol. 16(5), 337-342. Kamali, F., Khan, T. I., King, B. P., Frearson, R., Kesteven, P., Wood, P., . . . Wynne, H. (2004). Contribution of age, body size, and CYP2C9 genotype to anticoagulant response to warfarin. [Comparative Study Research Support, Non-U.S. Gov't]. Clin Pharmacol Ther. 75(3), 204-212. doi: 10.1016/j.clpt.2003.10.001. Kaminsky, L. S., & Zhang, Z. Y. (1997). Human P450 metabolism of warfarin. Pharmacol ther. 73(1), 67-74. Kittles, R. A., & Weiss, K. M. (2003). Race, ancestry, and genes: implications for defining disease risk. [Review]. Annu Rev Genomics Hum Genet. 4, 33-67. doi: 10.1146/annurev.genom.4.070802.110356. Klein, T. E., Altman, R. B., Eriksson, N., Gage, B. F., Kimmel, S. E., Lee, M. T., . . . Johnson, J. A. (2009). Estimation of the warfarin dose with clinical and pharmacogenetic data. [Validation Studies]. N Engl J Med. 360(8), 753-764. doi: 10.1056/NEJMoa0809329. Klotz, U. (2007). The role of pharmacogenetics in the metabolism of antiepileptic drugs: pharmacokinetic and therapeutic implications. [Research Support, Non-U.S. Gov't Review]. Clin Pharmacokinet. 46(4), 271-279. doi: 10.2165/00003088-200746040- 00001. Kudzi, W., Dodoo, A. N., & Mills, J. J. (2009). Characterisation of CYP2C8, CYP2C9 and CYP2C19 polymorphisms in a Ghanaian population. [Research Support, Non-U.S. Gov't]. BMC Med Genet. 10, 124. doi: 10.1186/1471-2350-10-124. University of Ghana http://ugspace.ug.edu.gh 69 Landow, L. (1998). Monitoring Adverse Drug Events: The Food and Drug Administration MedWatch Reporting System. Reg anesth. 23(2), 190. Lee, S. C., Ng, S. S., Oldenburg, J., Chong, P. Y., Rost, S., Guo, J. Y., . . . Goh, B. C. (2006). Interethnic variability of warfarin maintenance requirement is explained by VKORC1 genotype in an Asian population. Clin Pharmacol Ther. 79(3), 197-205. Li, T., Chang, C. Y., Jin, D. Y., Lin, P. J., Khvorova, A., & Stafford, D. W. (2004). Identification of the gene for vitamin K epoxide reductase. Nature -London-(6974), 541-543. Lindh, J. D., Lundgren, S., Holm, L., Alfredsson, L., & Rane, A. (2005). Several-fold increase in risk of overanticoagulation by CYP2C9 mutations. [Research Support, Non-U.S. Gov't]. Clin Pharmacol Ther. 78(5), 540-550. doi: 10.1016/j.clpt.2005.08.006. Marwick, C. (1997). MedGuide: at last a long-sought opportunity for patient education about prescription drugs. JAMA, 277(12), 949-950. McClean, P. (1997). Population and evolutionary genetics. http://www.cc.ndsu.nodak.edu/instruct/mcclean/plsc431/popgen/popgen1.htm 06/03/2014. McDonald, M. G., Rieder, M. J., Nakano, M., Hsia, C. K., & Rettie, A. E. (2009). CYP4F2 is a vitamin K1 oxidase: An explanation for altered warfarin dose in carriers of the V433M variant. [In Vitro Research Support, N.I.H., Extramural]. Mol Pharmacol. 75(6), 1337-1346. doi: 10.1124/mol.109.054833. Meyer, U. A. (2004). Pharmacogenetics - five decades of therapeutic lessons from genetic diversity. Nature rev. Genet. 5(9), 669-676. University of Ghana http://ugspace.ug.edu.gh 70 Miners, J. O., & Birkett, D. J. (1998). Cytochrome P4502C9: an enzyme of major importance in human drug metabolism. Br j clin pharmacol. 45(6), 525-538. Mitchell, C., Gregersen, N., & Krause, A. (2011). Novel CYP2C9 and VKORC1 gene variants associated with warfarin dosage variability in the South African black population. Pharmacogenom. 12(7), 953-963. doi: 10.2217/pgs.11.36. Nakai, K., Habano, W., Fukushima, N., Suwabe, A., Moriya, S., Osano, K., & Gurwitz, D. (2005). Ethnic differences in CYP2C9*2 (Arg144Cys) and CYP2C9*3 (Ile359Leu) genotypes in Japanese and Israeli populations. [Research Support, Non-U.S. Gov't]. Life Sci. 78(1), 107-111. doi: 10.1016/j.lfs.2005.04.049. Nasu, K., Kubota, T., & Ishizaki, T. (1997). Genetic analysis of CYP2C9 polymorphism in a Japanese population. Pharmacogenet. 7(5), 405-409. Nebert, D. W. (1999). Pharmacogenetics and pharmacogenomics: why is this relevant to the clinical geneticist? Clin genet. 56(4), 247-258. Nebert, D. W., & Menon, A. G. (2001). Pharmacogenomics, ethnicity, and susceptibility genes. Pharmacogenom. 1(1), 19-22. Nelson, D. R., Koymans, L., Kamataki, T., Stegeman, J. J., Feyereisen, R., Waxman, D. J., . . . Nebert, D. W. (1996). P450 superfamily: update on new sequences, gene mapping, accession numbers and nomenclature. Pharmacogenet. 6(1), 1-42. O'Reilly, R. A. (1969). Interaction of the anticoagulant drug warfarin and its metabolites with human plasma albumin. J Clin Invest, 48(1), 193-202. doi: 10.1172/JCI105968 Oates, A., Jackson, P. R., Austin, C. A., & Channer, K. S. (1998). A new regimen for starting warfarin therapy in out-patients. [Clinical Trial Comparative Study]. Br J Clin Pharmacol. 46(2), 157-161. University of Ghana http://ugspace.ug.edu.gh 71 Osinbowale, O., Al Malki, M., Schade, A., & Bartholomew, J. R. (2009). An algorithm for managing warfarin resistance. [Review]. Cleve Clin J Med. 76(12), 724-730. doi: 10.3949/ccjm.76a.09062. Pautas, E., Moreau, C., Gouin-Thibault, I., Golmard, J. L., Mahe, I., Legendre, C., . . . Siguret, V. (2010). Genetic factors (VKORC1, CYP2C9, EPHX1, and CYP4F2) are predictor variables for warfarin response in very elderly, frail inpatients. [Comparative Study]. Clin Pharmacol Ther. 87(1), 57-64. doi: 10.1038/clpt.2009.178. Pirmohamed, M., & Park, B. K. (2003). Cytochrome P450 enzyme polymorphisms and adverse drug reactions. Toxicol. 192(1), 23-32. Rettie, A. E., & Tai, G. (2006). The pharmocogenomics of warfarin: closing in on personalized medicine. Mol Interv. 6(4), 223-227. doi: 6/4/223 [pii] 10.1124/mi.6.4.8. Rieder, M. J., Reiner, A. P., Gage, B. F., Nickerson, D. A., Eby, C. S., McLeod, H. L., . . . Rettie, A. E. (2005). Effect of VKORC1 haplotypes on transcriptional regulation and warfarin dose. [Research Support, N.I.H., Extramural Research Support, U.S. Gov't, P.H.S.]. N Engl J Med. 352(22), 2285-2293. doi: 10.1056/NEJMoa044503. Roth, J., Boudreau, D., Fujii, M., Farin, F., Rettie, A., Thummel, K., & Veenstra, D. (2013). PS3-4: Genetic Risk Factors for Major Bleeding in Warfarin Patients in a Community Setting. Clin Med Res. 11(3), 148. Schaid, D. J., & Jacobsen, S. J. (1999). Biased tests of association: comparisons of allele frequencies when departing from Hardy-Weinberg proportions. [Research Support, U.S. Gov't, P.H.S.]. Am J Epidemiol. 149(8), 706-711. Schwarz, U. I. (2003). Clinical relevance of genetic polymorphisms in the human CYP2C9 gene. Eur J Clin Invest. 33, 23-30. University of Ghana http://ugspace.ug.edu.gh 72 Schwarz, U. I., Ritchie, M. D., Bradford, Y., Li, C., Dudek, S. M., Frye-Anderson, A., . . . Stein, C. M. (2008). Genetic determinants of response to warfarin during initial anticoagulation. [Research Support, N.I.H., Extramural]. N Engl J Med. 358(10), 999- 1008. doi: 10.1056/NEJMoa0708078. Scibona, P., Redal, M. A., Garfi, L. G., Arbelbide, J., Argibay, P. F., & Belloso, W. H. (2012). Prevalence of CYP2C9 and VKORC1 alleles in the Argentine population and implications for prescribing dosages of anticoagulants. Genet Mol Res. 11(1), 70-76. doi: 10.4238/2012.January.9.8. Sconce, E. A., Khan, T. I., Wynne, H. A., Avery, P., Monkhouse, L., King, B. P., . . . Kamali, F. (2005). The impact of CYP2C9 and VKORC1 genetic polymorphism and patient characteristics upon warfarin dose requirements: proposal for a new dosing regimen. Blood, 106(7), 2329-2333. Scordo, M. G., Aklillu, E., Yasar, U., Dahl, M. L., Spina, E., & Ingelman-Sundberg, M. (2001). Genetic polymorphism of cytochrome P450 2C9 in a Caucasian and a black African population. [Comparative Study Research Support, Non-U.S. Gov't]. Br J Clin Pharmacol. 52(4), 447-450. Scott, S. A., Edelmann, L., Kornreich, R., & Desnick, R. J. (2008). Warfarin pharmacogenetics: CYP2C9 and VKORC1 genotypes predict different sensitivity and resistance frequencies in the Ashkenazi and Sephardi Jewish populations. [Comparative Study Research Support, N.I.H., Extramural Research Support, Non- U.S. Gov't]. Am J Hum Genet. 82(2), 495-500. doi: 10.1016/j.ajhg.2007.10.002. Scott, S. A., Jaremko, M., Lubitz, S. A., Kornreich, R., Halperin, J. L., & Desnick, R. J. (2009). CYP2C9*8 is prevalent among African-Americans: implications for University of Ghana http://ugspace.ug.edu.gh 73 pharmacogenetic dosing. [Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't]. Pharmacogenom. 10(8), 1243-1255. doi: 10.2217/pgs.09.71. Scott, S. A., Khasawneh, R., Peter, I., Kornreich, R., & Desnick, R. J. (2010). Combined CYP2C9, VKORC1 and CYP4F2 frequencies among racial and ethnic groups. Pharmacogenom. 11(6), 781-791. Sebat, J. (2004). Large-Scale Copy Number Polymorphism in the Human Genome. Science Science, 305(5683), 525-528. Seng, K. C., Gin, G. G., Sangkar, V. J., & Phipps, E. M. (2003). Frequency of Cytochrome P450 2C9 (CYP2C9) Alleles in Three Ethnic Groups in Malaysia. AsPac J. Mol. Biol. Biotechnol. 11(2), 83-91. Shah, S. H., & Voora, D. (2013). Warfarin Dosing and VKORC1/CYP2C9. Medscape. Singh, O., Sandanaraj, E., Subramanian, K., Lee, L. H., & Chowbay, B. (2011). Influence of CYP4F2 rs2108622 (V433M) on warfarin dose requirement in Asian patients. [Research Support, Non-U.S. Gov't]. Drug Metab Pharmacokinet. 26(2), 130-136. Singla, D. L., & Morrill, G. B. (2005). Warfarin maintenance dosages in the very elderly. Am J Health Syst Pharm. 62(10), 1062-1066. Sullivan-Klose, T. H., Ghanayem, B. I., Bell, D. A., Zhang, Z. Y., Kaminsky, L. S., Shenfield, G. M., . . . Goldstein, J. A. (1996). The role of the CYP2C9-Leu359 allelic variant in the tolbutamide polymorphism. Pharmacogenet. 6(4), 341-349. Takahashi, H., & Echizen, H. (2003). Pharmacogenetics of CYP2C9 and interindividual variability in anticoagulant response to warfarin. Pharmacogenom J, 3(4), 202-214. doi: 10.1038/sj.tpj.65001826500182 [pii]. University of Ghana http://ugspace.ug.edu.gh 74 Takahashi, H., Wilkinson, G. R., Nutescu, E. A., Morita, T., Ritchie, M. D., Scordo, M. G., . . . Echizen, H. (2006a). Different contributions of polymorphisms in VKORC1 and CYP2C9 to intra- and inter-population differences in maintenance dose of warfarin in Japanese, Caucasians and African-Americans. Pharmacogenet Genom. 16(2), 101- 110. Takahashi, H., Wilkinson, G. R., Nutescu, E. A., Morita, T., Ritchie, M. D., Scordo, M. G., . . . Echizen, H. (2006b). Different contributions of polymorphisms in VKORC1 and CYP2C9 to intra- and inter-population differences in maintenance dose of warfarin in Japanese, Caucasians and African-Americans. Pharmacogenet genom. 16(2), 101-110. Takeuchi, F., McGinnis, R., Bourgeois, S., Barnes, C., Soranzo, N., Whittaker, P., . . . Wadelius, M. (2009). A genome-wide association study confirms VKORC1, CYP2C9, and CYP4F2 as principal genetic determinants of warfarin dose. PLoS Genet. 5(3). Tatarunas, V., Lesauskaite, V., Veikutiene, A., Jakuska, P., & Benetis, R. (2011). The influence of CYP2C9 and VKORC1 gene polymorphisms on optimal warfarin doses after heart valve replacement. Medicina (Kaunas), 47(1), 25-30. Tate, S. K., & Goldstein, D. B. (2004). Will tomorrow's medicines work for everyone? Nature Genet. 36(11), S34-S42. Taylor, A. L. (2004). Combination of Isosorbide Dinitrate and Hydralazine in Blacks with Heart Failure. N Engl J Med. 351(20), 2049-2057. Thompson, M. W., Roderick R. McInnes, & Willard., H. F. (1991). Thompson & Thompson genetics in medicine., 5th ed. Philadelphia: W. B. Saunders. University of Ghana http://ugspace.ug.edu.gh 75 Tishkoff, S. A., Reed, F. A., Ranciaro, A., Hirbo, J. B., Awomoyi, A. A., Mortensen, H., . . . Williams, S. M. (2009). The genetic structure and history of Africans and African Americans. Science, 324(5930), 1035-1044. Vargens, D. D., Suarez-Kurtz, G., Damasceno, A., & Petzl-Erler, M. L. (2011). Combined CYP2C9, VKORC1 and CYP4F2 frequencies among Amerindians, Mozambicans and Brazilians. Pharmacogenom. 12(6), 769-772. Vesell, E. S. (1989). Pharmacogenetic perspectives gained from twin and family studies. Pharmacol Ther. 41(3), 535-552. Voora, D., McLeod, H. L., Eby, C., & Gage, B. F. (2005). The pharmacogenetics of coumarin therapy. Pharmacogenom. 6(5), 503-513. Vormfelde, S. V., Brockmoller, J., Bauer, S., Herchenhein, P., Kuon, J., Meineke, I., . . . Kirchheiner, J. (2009). Relative impact of genotype and enzyme induction on the metabolic capacity of CYP2C9 in healthy volunteers. [Comparative Study]. Clin Pharmacol Ther. 86(1), 54-61. doi: 10.1038/clpt.2009.40. Wadelius, M., Chen, L. Y., Downes, K., Ghori, J., Hunt, S., Eriksson, N., . . . Deloukas, P. (2005). Common VKORC1 and GGCX polymorphisms associated with warfarin dose. [Research Support, Non-U.S. Gov't]. Pharmacogenom. 5(4), 262-270. doi: 10.1038/sj.tpj.6500313. Wadelius, M., Chen, L. Y., Eriksson, N., Bumpstead, S., Ghori, J., Wadelius, C., . . . Deloukas, P. (2007). Association of warfarin dose with genes involved in its action and metabolism. Hum genet. 121(1), 23-34. Wadelius, M., Chen, L. Y., Lindh, J. D., Eriksson, N., Ghori, M. J., Bumpstead, S., . . . Deloukas, P. (2009). The largest prospective warfarin-treated cohort supports genetic University of Ghana http://ugspace.ug.edu.gh 76 forecasting. Blood, 113(4), 784-792. doi: blood-2008-04-149070 [pii]10.1182/blood- 2008-04-149070. Wadelius, M., & Pirmohamed, M. (2007a). Pharmacogenetics of warfarin: current status and future challenges. Pharmacogenom. 7(2), 99-111. Wadelius, M., & Pirmohamed, M. (2007b). Pharmacogenetics of warfarin: current status and future challenges. Pharmacogenom. 7(2), 99-111. Weinshilboum, R. (2003). Inheritance and drug response. N Engl J Med. 348(6), 529-537. Whitley, H. P., Fermo, J. D., Chumney, E. C., & Brzezinski, W. A. (2007). Effect of patient- specific factors on weekly warfarin dose. Ther Clin Risk Manag. 3(3), 499-504. Wilson, J. F., Weale, M. E., Smith, A. C., Gratrix, F., Fletcher, B., Thomas, M. G., . . . Goldstein, D. B. (2001). Articles - Population genetic structure of variable drug response. Nature genet. 29(3), 265. Xie, H. G., Kim, R. B., Wood, A. J., & Stein, C. M. (2001). Molecular basis of ethnic differences in drug disposition and response. Ann Rev Pharmacol Toxicol. 41, 815- 850. Xie, H. G., Prasad, H. C., Kim, R. B., & Stein, C. M. (2002). CYP2C9 allelic variants: ethnic distribution and functional significance. Adv Drug Deliv Rev. 54(10), 1257-1270. Yasar, U., Eliasson, E., Dahl, M. L., Johansson, I., Ingelman-Sundberg, M., & Sjöqvist, F. (1999). Validation of methods for CYP2C9 genotyping: frequencies of mutant alleles in a Swedish population. Biochem Biophys Res Commun. 254(3), 628-631. University of Ghana http://ugspace.ug.edu.gh 77 Yoon, Y. R., Shon, J. H., Kim, M. K., Lim, Y. C., Lee, H. R., Park, J. Y., . . . Shin, J. G. (2001). Frequency of cytochrome P450 2C9 mutant alleles in a Korean population. [Research Support, Non-U.S. Gov't]. Br J Clin Pharmacol. 51(3), 277-280. University of Ghana http://ugspace.ug.edu.gh 78 APPENDIX I PRIMER SEQUENCES, AMPLICON SIZES AND RESTRICTION ENZYMES USED CYP2C9 specific primer sequences Primers Sequence 5’-3’ Detection of allelic variant Amplicon size Restriction Enzyme Fa CACTGGCTGAAAGAGCTAACAGAG CYP2C9*2 375 bp Ava II Ra GTGATATGGAGTAGGGTCACCCAC Fb TGCACGAGGTCCAGAGGTAC CYP2C9*3 105 bp Kpn I Rb ACAAACTTACCTTGGGAATGAGA CYP4F2 specific primer sequences Primers Sequence 5’-3’ Detection of allelic variant Amplicon size Restriction Enzyme Fa CGGAACTTGGACCATCTACA CYP4F2rs2108622 439bp PvuII Ra CCTACTCTCCCACAGGCATTA VKORC1 specific primer sequences Primers Sequence 5’-3’ Detection of allelic variant Amplicon size Restriction Enzyme Fa ATCCCTCTGGGAAGTCAAGC VKORC1_1639G>A 636bp Nci I Ra CACCTTCAACCTCTCCATCC University of Ghana http://ugspace.ug.edu.gh 79 APPENDIX II COMMON POTENTIAL DRUG-DRUG INTERACTIONS WITH WARFARIN The following drugs may increase INR (i.e. a lower warfarin dose may be necessary): Amiodarone Certain Antibiotics (TMP‐SMZ/Bactrim, Metronidazole) Antifungals (fluconazole, miconazole, voriconazole) Antiretrovirals (delaviradine,efavirenz) Cimetidine Corticosteroids Fibrates Griseofulvin Isoniazid Leflunomide (Arava) Mifepristone Orlistat (Alli, Xenical) PPIs (e.g. omeprazole) Statins (e.g. simvastatin) Tamoxifen University of Ghana http://ugspace.ug.edu.gh 80 Thyroid replacement Tramadol (Ultram) The following drugs may decrease INR (i.e. a higher warfarin dose may be required): Antacids Certain Antibiotics (dicloxacillin, nafcillin) Anticonvulsants (eg phenytoin) Barbiturates Bile acid resins Cyclosporine Rifampin Con-commitant use of the following drugs may increase bleeding risk on warfarin: Anti-depressants (e.g. SSRIs) Antiinflammatories (note: celecoxib may still cause bleeding but may be an option instead of other NSAIDs) Antiplatelet agents (e.g. aspirin/salicylates, clopidogrel (Plavix), prasugrel (Effient), aspirin/e xtended‐release dipyridamole (Aggrenox) Other anticoagulants (e.g. heparin, LMWH, fondaparinux). University of Ghana http://ugspace.ug.edu.gh 81 APPENDIX III CONSENT FORM CYP2C9, VKORC1 AND CYP4F2 VARIANT FREQUENCIES IN PATIENTS ON EITHER LOW OR HIGH STABLE WARFARIN MAINTENANCE THERAPY IN GHANAIAN POPULATION. Warfarin is an anti-clotting drug for reducing thromboembolic events such as stroke, deep vein thrombosis, pulmonary embolism and other serious coronary malfunctions. Warfarin has been used for more than 50 years, with varied degree of anticoagulation activity. An appropriate warfarin dose in one patient can induce a bleeding event in another. As a result of this variation, some patients are put on a low warfarin dose while others are on a high warfarin dose. Variation in warfarin dose in patients has been associated with genetic variations of patients among Caucasians and other ethnic populations. Little information exists on indigenous Africans populations and no data is available on Ghanaian populations. This study will take a small amount of blood (5ml) from you as a patient on warfarin by inserting a needle in your forearm. The risk involved in this procedure is negligible and it will cause only minimal pain and bruising. The sample will be used to determine the genetic variations of CYP2C9, VKORC1, and CYP4F2 genes and the International Normalized Ratio (INR), which gives an indication of the time it takes for your blood to clot. No other tests will be conducted on your blood sample. Results of this study may help Clinicians treat Patients on warfarin in Ghana better. All information gathered will be treated in strict confidentiality. It will be appreciated if you agree to take part in this study. You may choose not to take part in the study however; this will not affect your medical care in this Clinic. University of Ghana http://ugspace.ug.edu.gh 82 If you have any problems or further questions, please contact: Dr. William Kudzi of the University of Ghana Medical School. Mobile: 0246703400 Consent: I………………………………………………………………..of …………….......................... ……………………………………………give my consent to the research procedures above, the nature, purpose and possible consequences of which have been described to me By……………………………………………………………………………………………… Patient’s signature………………………………………….Date…………………………….. Doctor’s signature……………………………………………………………………………… University of Ghana http://ugspace.ug.edu.gh 83 APPENDIX IV DATA COLLECTION SHEET This form should be filled by a Clinician on duty or the MPhil Student for each patient enrolled in the warfarin study. A. DEMOGRAPHY OF PATIENT Participant ID: [ ] [ ] [ ] Date: [ ] [ ] / [ ] [ ] / [ ] [ ] [ ] [ ] 1) Please indicate the current age of patient (Yrs)……………………………………… 2) Please indicate the sex of the patient ….. ……………................................Male Female 3) Please describe the patient’s ethnic group: Akan Ga/Dangbe Ewe Mole Dagbani Guan Hausa Gruma Grussi Other (specify)……………………………………………… CLINICAL DATA OF PATIENT 4) Please record the Main Diagnosis of the patient ……………………………………… ……………………………………………………………………………………………… (a) Please indicate whether the patient takes any other medications aside warfarin? Yes….………………………………. University of Ghana http://ugspace.ug.edu.gh 84 No………………………………….. (b) If yes, please name the drug (s) and indicate their duration of use …………………… ………………………………………………………………………………………………. 5) Please indicate how long the patient has been on warfarin medication. ……………… 6) Please record the patient’s daily warfarin dosage ……………………………………… 7) (a) Please indicate if the patient has ever experienced any adverse effects after taken his/her warfarin medication? Yes…………..………………………. No ………………………………….. (b) If yes, what adverse effects did he/she experienced?……………………………….. 8) (a) Please indicate if the patient eats a lot of Vegetables (such as kontonmire, garden eggs, cabbage, lettuce, etc)? Yes….………………………………… No……….…………………………… (b) If yes, how often does the patient eat these vegetables? Daily Weekly Monthly (a) Please indicate if the patient takes fruit juice (such as orange juice etc)? Yes…………………………………….. No……………………………………… University of Ghana http://ugspace.ug.edu.gh 85 (b) If yes, how often does the patient drink these fruit juices? Daily Weekly Monthly 9) Folder Study Height (Cm) BMI: Weight (Kg) INR INR University of Ghana http://ugspace.ug.edu.gh 86 APPENDIX V REAGENTS AND MATERIALS USED Reagents: 1. Agarose 2. PCR tubes (0.2ml) 3. Eppendorf tubes (2.5ml) 4. Microcentrifuge tube (0.5ml) 5. Ethidium bromide 6. dNTPs (deoxynucleoside triphosphates) 7. Taq Polymerase 8. 10X PCR Buffer with 15mM MgCl2 9. TAE Buffer (50X) 10. Loading Dye 11. DNA ladder (100bp) 12. Nuclease free water 13. Distilled Water 14. 500g Tris base {Tris (hydroxymethyl)-aminomethan. Aminomethylidintrimethanol C4H11NO3 15. Glacial acetic acid 16. 0.5M EDTA pH 8.0 17. ddH2O 18. NaOH 19. EDTA powder University of Ghana http://ugspace.ug.edu.gh 87 Equipments: 1. Micro Pipettes (0.5-10µl, 10-100µl, 100-200µl, 200-1000µl) 2. Microwave Oven 3. Electrophoretic tray & tanks 4. Autoclave 5. Analytical Balance 6. KODAK Gel Logic 200 Imaging Systems 7. pH Meter 8. Glass stirrer 9. Spatula University of Ghana http://ugspace.ug.edu.gh 88 APPENDIX VI PREPARATION OF REAGENTS Primer stock solutions CYP2C9*2 Amount of substance, n (CYP2C9-Fa) = 153.4 nMoles Converting to µMoles gives 153.4 x 1 = 0.1534 µMoles 1000 To prepare a 100µM stock primer solution, volume of water required V (L) = n / C = 0.1534 / 100 = 0.001534L or 1534µl. Thus, 1534 µl of nuclease free water was added to the lyophilized primer content to make a 100 µM stock primer solution. Amount of substance, n (CYP2C9-Ra) = 151.9 nMoles Converting to µMoles gives 151.9 x 1 = 0.1519 µMoles 1000 To prepare a 100µM stock primer solution, volume of water required V (L) = n / C =0.1519 / 100 = 0.001519L or 1519µl. Thus, 1519 µl of nuclease free water was added to the lyophilized primer content to make a 100 µM stock primer solution. CYP2C9*3 Amount of substance, n (CYP2C9-Fb) = 163.1 nMoles Converting to µMoles gives 163.1 x 1 = 0.1631 µMoles 1000 University of Ghana http://ugspace.ug.edu.gh 89 To prepare a 100µM stock primer solution, volume of water required V (L) = n / C = 0.1631 / 100 = 0.001631L or 1631µl. Thus, 1631 µl of nuclease free water was added to the lyophilized primer content to make a 100 µM stock primer solution. Amount of substance, n (CYP2C9-Rb) = 164.1 nMoles Converting to µMoles gives 164.1 x 1 = 0.1641 µMoles 1000 To prepare a 100µM stock primer solution, volume of water required V (L) = n / C = 0.1641 / 100 = 0.001641L or 1641µl. Thus, 1641 µl of nuclease free water was added to the lyophilized primer content to make a 100 µM stock primer solution. CYP4F2 Amount of substance, n (CYP4F2-Fa) = 168.1 nMoles Converting to µMoles gives 168.1 x 1 = 0.1681 µMoles 1000 To prepare a 100µM stock primer solution, volume of water required V (L) = n / C = 0.1681 / 100 = 0.001681L or 1681µl. Thus, 1681 µl of nuclease free water was added to the lyophilized primer content to make a 100 µM stock primer solution. Amount of substance, n (CYP4F2-Ra) = 196.9 nMoles Converting to µMoles gives 196.9 x 1 = 0.1969 µMoles 1000 University of Ghana http://ugspace.ug.edu.gh 90 To prepare a 100µM stock primer solution, volume of water required V (L) = n / C = 0.1969 / 100 = 0.001969L or 1969 µl. Thus, 1969 µl of nuclease free water was added to the lyophilized primer content to make a 100 µM stock primer solution. VKORC1 Amount of substance, n (VKORC1-Fa) = 151.5 nMoles Converting to µMoles gives 151.5 x 1 = 0.1515 µMoles 1000 To prepare a 100µM stock primer solution, volume of water required V (L) = n / C = 0.1515 /100 = 0.001515L or 1515 µl. Thus, 1515 µl of nuclease free water was added to the lyophilized primer content to make a 100 µM stock primer solution. Amount of substance, n (VKORC1-Ra) = 193.3 nMoles Converting to µMoles gives 193.3 x 1 = 0.1933 µMoles 1000 To prepare a 100µM stock primer solution, volume of water required V (L) = n / C = 0.1933 / 100 = 0.001933L or 1933 µl. Thus, 1933 µl of nuclease free water was added to the lyophilized primer content to make a 100 µM stock primer solution. NB: All the stock solutions prepared were stored at -200C for future use. Working Primer solutions To prepare 20µM working primer solution from the 100µM stock primer solution in a final volume of 200µl for each of the genes listed above, the dilutions formula below was used. University of Ghana http://ugspace.ug.edu.gh 91 Stock concentration (C1) x Volume of stock concentration required to prepare working concentration (V1) = Working concentration (C2) x Volume of working concentration needed (V2). Thus, C1V1 = C2V2 C1 = 100 µM, V1 =? C2 = 20 µM, V2 = 200µl; V1 = C2V2 / C1 V1 = 20 µM x 200 µl / 100 µM = 40 µl Therefore, 160 µl of nuclease free water was added to an empty 2ml eppendorf tube and 40 µl of primer stock was added to make a 20 µM primer working solution. Preparation of dNTP Set To prepare 10mM dNTP set from 100mM dNTP stock solution in a final volume of 200µl, the dilutions formula C1V1 = C2V2 was used. C1 = 100mM, C2 = 10mM, V2 = 200µl V1 = C2V2 / C1 Hence V1 = 10mM x 200 µl / 100mM = 20µl. Therefore 20 µl of each dNTP (dATP, dCTP, dGTP, dTTP) was added to separate empty eppendorf tubes and 180µl of nuclease free water was added to make a 10mM dNTP set in a final volume of 200µl. Preparation of 0.5M Ethylenediaminetetra acetic acid (EDTA) The analytical balance was used to weigh 29.23g of the EDTA powder (FW = 292.25) into a clean glass bottle and 200 ml of distilled water was added to dissolve content. The pH of this solution was adjusted to 8.0 using concentrated NaOH solution. Preparation of 50X Tris-acetate-EDTA (TAE) Buffer Stock The analytical balance was used to weigh 242g of Tris base into a clean glass bottle and 800 ml of ddH2O was added and dissolved by stirring. Then 57.1 ml of glacial acetic acid and 100 University of Ghana http://ugspace.ug.edu.gh 92 ml of 0.5M EDTA was added and mixed. This was followed by the addition of 800 ml ddH2O to a final volume of 1 L. Finally, the stock buffer was sterilized by autoclaving. Preparation of 1X TAE Buffer from 50X TAE Buffer Stock Twenty milliliters of the stock buffer was measured in a 100ml measuring cylinder and poured into a 1 L volumetric flask and 980 ml of double distilled water was used to make it up to the 1 L mark. The flask was then stoppered and inverted several times to mix after which the buffer is stored away in a clean glass bottle at room temperature for future use. Two Percent (2%) Agarose Gel Preparation and Casting The analytical balance was used to weigh 2g of agarose powder into a heat resistant bottle and 100 ml of 1X TAE buffer was added and mixed. The solution was then heated in a microwave oven to melt the agarose and then allowed to cool down to just above room temperature. Two microliters of ethidium bromide was added and mixed and the resultant solution was poured into a gel casting tray with combs inserted to create wells. University of Ghana http://ugspace.ug.edu.gh