EVALUATION OF CYP2D6 PHENOTYPE IN A YORUBA NIGERIAN …

i

EVALUATION OF CYP2D6 PHENOTYPE IN A YORUBA

NIGERIAN POPULATION

A DISSERTATION SUBMITTED TO THE NATIONAL POSTGRADUATE

MEDICALCOLLEGE OF NIGERIA (NPMCN) IN PARTIAL FULFILMENT OF THE

REQUIREMENTS FOR THE AWARD OF FELLOWSHIP IN CLINICAL

PHARMACOLOGY & THERAPEUTICS (CPT) OF THE FACULTY OF

INTERNAL MEDICINE.

BY

DR. WAHEED ADEOLA ADEDEJI

MBBS (Ogbomoso) 2004, MSc Pharmacology& Therapeutics (Ibadan) 2014

AF/009/11/001/812

DEPARTMENT OF CLINICAL PHARMACOLOGY,

UNIVERSITY COLLEGE HOSPITAL, IBADAN, NIGERIA

NOVEMBER 2016

ii

DECLARATION

I hereby declare that this dissertation is the result of my research findings and has not been

presented elsewhere for the award of any degree or diploma.

………………………………………… …………………………………

Dr. Waheed Adeola Adedeji Date

iii

CERTIFICATION BY SUPERVISOR

I certify that this work was carried out by Dr. Waheed Adeola Adedeji in the Department of

Clinical Pharmacology, University College Hospital, Ibadan, under my supervision.

……………………………………………………….

Supervisor

Professor F. A. Fehintola

MBBS (Ib), M.Sc. (Pharmacology &Therapeutics), FMCP (Clinical Pharmacology)

Department of Clinical Pharmacology, University College Hospital,

Ibadan Nigeria

iv

CERTIFICATION BY THE HEAD OF DEPARTMENT

I certify that Dr. Waheed Adeola Adedeji of the Department of Clinical Pharmacology,

University College Hospital, Ibadan undertook the dissertation work under the guidance of the

above supervisor.

………………………………………… ………………………………

Professor Catherine O. Falade Date

MBBS, MSc, FMCP, FWACP

Head,

Department of Clinical Pharmacology,

University College Hospital, Ibadan, Nigeria.

v

DEDICATION

This work is dedicated to all my teachers, and my mother, Chief (Mrs.) Silifat Nike Aleem

Adedeji for her sacrifice towards my education.

vi

ACKNOWLEDGEMENT

All praises and adorations belong to Almighty Allah. May His peace and blessing be upon the

noble soul of the Prophet Muhammad (SAW).

The CMD, Prof. T.O. Alonge and the management of the University College Hospital, Ibadan is

appreciated for the enabling environment provided for my training.

I wish to express my profound gratitude to my supervisor and mentor, Prof. F.A. Fehintola for

his mentorship. I equally appreciate the Head of Department, Prof. Catherine O. Falade for her

encouragement and support. I appreciate my other trainers in the Department, Prof. A. Sowumi,

and Dr. Aduragbenro D. Adedapo. Also, to my teachers, Prof. Adekunle O. George, Prof. Bola

Ogunbiyi, Prof. Adesola Ogunniyi, Prof B.L. Salako, Dr. Arinola Esan, Dr. A.M. Adeoye, Dr.

Yemi R. Raji and all other Consultants in the Department of Medicine for the opportunity to

learn under your tutelage.

Dr. Titi Fakeye of the Department of Clinical Pharmacy and Dr. Ibrahim Oladosu of the

Department of Chemistry, University of Ibadan are appreciated for their immense contribution

towards the completion of my research work. I sincerely appreciate Dr. Sharon Igbinoba of the

Department of Clinical Pharmacy, Obafemi Awolowo University (OAU), Ile-Ife, for her support

and contribution that ensured the completion of my research work.

The Director, Prof. C.A. Obafemi, Mr. M. Adegoke, Mr. Akinola, and other staff of the Central

Science Laboratory, OAU, Ile-Ife are appreciated for providing me with enabling environment

that led to the eventual analysis of my work.

I am grateful to Prof. Jan Juřica, Clinical Pharmacology Department, Faculty of Medicine, Brno,

Czech Republic for the detailed methods of Zinova et. al and her own, despite the former was

written in Czech. This information was a turning point in my work.

I appreciate Mr and Mrs. Olomu of Haematology and Medicine laboratory Departments for their

assistance in the haematological and biochemical analysis of the samples.

Mr. Rotimi Olatunde, Department of Pharmacology and Therapeutics, University of Ibadan

contributed immensely in samples handling. My appreciation also goes to Mr. Nathaniel K.

vii

Afolabi, Department of Paediatrics for supporting the sample storage. Staff of Clinical

Pharmacology Department UCH, represented by Mr. M. Lateef, Mrs. J. Ekwesianya, Mrs. Tawa

Adediran and Mrs. Alake are appreciated for their support during the enrolment stage. I

appreciate Mr. Isa Muideen for his assistance during the enrolment stage and for data entry.

I must acknowledge Mrs. Korede and other staff of Multidisciplinary Central Research

Laboratory, University of Ibadan for introducing me to the HPLC. Drs Ismail and Bolarinwa are

appreciated for their hospitality during my stay in Ile-Ife.

I want to thank Dr. Tunde Adedokun and Dr. Bidemi Yusuf of the Epidemiology and Medical

Statistics Department, University of Ibadan for their assistance in the statistical analysis of this

work. Drs Nurain Azeez and Abdullah Akinniran are appreciated for their prayer and support.

My participants are appreciated for their contribution because without them I would not have had

the opportunity of completing this research work.

Prof. Ambrose Isa is appreciated for his fatherly care especially for the trainee in the Clinical

Pharmacology and Therapeutics subspecialty.

My special appreciation goes to my parents, Chief (Mrs.) Silifat Nike Aleem-Adedeji and Mr.

Moyosade Aleem Adedeji for their care and love. I equally thank my siblings, Mrs. D.O. Sulola,

Mr. Ismail Aleem, Miss Rukayat Ajebola Aleem and Mrs. Awawu Opeyemi Seidu for their

support and prayer.

I wish to thank Alhaja Saudat Fehintola for words of encouragement and support. To my

brothers, AbdulBasit and Rafiq, I appreciate you all.

I sincerely appreciate my love and soulmate, Princess Bilikisu Oluwakemi Adedeji (nee

Oladunmoye) for her care, love, sacrifice and support. To our children, Abdul Rahman Adeoye,

Khadijah Adebukola, Taofeekah Adeola, Maryam Aderinsola and Hafsah Igbayilola, I appreciate

your sacrifice and support.

Waheed Adeola Adedeji

January 2016

viii

TABLE OF CONTENTS

CONTENT PAGE

Title Page…………………………………………………………………………………..........i

Declaration……………………………………………………………………………………...ii

Certification by Supervisor…………………………………………………………..................iii

Certification by Head of Department…….…………………………………………..................iv

Dedication………….. ……………………………………………………………………….......v

Acknowledgement……………………………………………………………….........................vi

Table of Contents………………………………………………………………………….........viii

List of Tables…………………………………………………………………............................xii

List of Figures…………………………………………………………………...........................xiv

List of Appendices………………………………………………………………………………xvi

List of

Abbreviations………………………………………………………………....................xvii

Abstract………………………………………………………………………………………......xx

CHAPTER ONE: INTRODUCTION ……………………………………………………………1

1.1 Statement of problem……………………………………………………………..3

1.2 Rationale………………………………………………………………………….4

1.3 Aims and Objectives……………………………………………………………...5

CHAPTER TWO: LITERATURE REVIEW…………………………………………………….6

2.1 Background………………………………………………………………………..6

2.2 Racial/individual variation in drug

handling……………………………………..11

ix

2.3 Pharmacogenomics, Pharmacovigilance and Pharmacoepidemiology…………..12

2.4 Clinical Application of Pharmacogenetics……………………………………….15

2.5 Challenges…………………………………………………………………….18

2.6 Drug Metabolism……………………………………………………………..20

2.6.1. Enzymes involved in Drug Metabolism………………………………………24

2.6.2. Phase 1 Metabolism…………………..………………………………………..27

2.6.2.1. Oxidation Reactions involving Cytochrome P450 Enzyme System…..27

2.6.2.2. Oxidation Reactions not catalyzed by Cytochrome P450 Enzyme

System…………………………………………………………………..28

2.6.2.3. Reductive Metabolism………………………………………………….28

2.6.2.4. Hydrolytic Reaction…………………………………………………….28

2.6.3. Phase II Metabolism…………………………………………………………….31

2.6.4. Cytochrome P-450 Super families……………………………………………...34

2.6.4.1. CYP-Drug-Disease Interactions………………………………………...38

2.6.4.2. Pharmacogenetics testing of CYPs……………………………………...41

2.6.4.2.1 Genotyping……………………………………………………………...41

2.6.4.2.2 Phenotyping……………………………………………………………..43

2.6.4.3. Cytochrome P-450 2D6 (CYP2D6)…………………………………….47

2.6.4.3.1. CYP2D6 probe drugs……………………………………………………50

2.6.4.3.2. Dextromethorphan as CYP2D6 probe drug……………………………..50

2.6.4.3.3. Metabolic Ratio (MR) in biological matrices……………………………55

2.6.4.3.4. CYP2D6 Phenotyping with Dextromethorphan using urinary

Assay……57

2.6.4.3.5. CYP2D6 Phenotyping with Dextromethorphan using

plasma/serum…….58

x

2.6.4.3.6. Analytical methods for Dextromethorphan and

Dextrorphan…………….59

CHAPTER THTREE: METHODOLOGY………………………………………………………61

3.1. Setting…………………………………………………………………………....61

3.2. Location of the study……………………………………………………………61

3.3. Ethical approval…………………………………………………………………62

3.4. Design and Study population……………………………………………………62

3.5. Sample size determination………………………………………………………63

3.6. Eligibility/Inclusion Criteria…………………………………………………….64

3.7. Exclusion criteria………………………………………………………………..64

3.8.1. Chemicals and drugs…………………………………………………………….64

3.8.2. Equipment……..…………………………………………………………………64

3.9. Conduct of the study……………………………………………………………..67

3.9.1. Analytical methods for dextromethorphan and Dextrorphan……………………68

3.9.2. Preparation of Standard solution and solvent system……………………………68

3.9.3. Calibration curve for dextromethorphan and Dextrorphan in urine and plasma...69

3.9.4. Chromatographic

condition………………………………………………………70

3.9.5. Precision studies for dextromethorphan and

dextrorphan………………………..70

3.9.6. Recovery studies for dextromethorphan and dextrorphan from plasma…………71

3.9.7. Determination of dextromethorphan and dextrorphan in the plasma and urine....71

3.9.8. Data analysis……………………………………………………………………..72

CHAPTER FOUR: RESULTS…………………………………………………………………..74

xi

4.1. Socio-demographic Characteristics of the

participants…………………………...74

4.2. Haematological parameter of the

participants……………………………………78

4.3. Biochemical parameters of the participants………………………………..…….80

4.4. Analysis of dextromethorphan and

Dextrorphan…………………………………82 4.5. Dextromethorphan, dextrorphan and

MR urine…………………………………..93

4.6. Dextromethorphan, dextrorphan and MR

plasma………………………………...97

4.7. Comparison of the plasma and urinary metabolic ratio

dextromethorphan/dextrorphan............................................................................100

4.8. The sociodemographic characteristics of Poor and Extensive

metabolizers……102

CHAPTER FIVE: DISCUSSION………………………………………………………………104

5.1. Discussion……………………………………………………………………....104

5.2. Limitations……………………………………………………………………...108

CHAPTER SIX: CONCLUSION AND RECOMMENDATIONS…………………………….109

6.1. Conclusion……………………………………………………………………...109

6.2. Recommendation……………………………………………………………….110

REFERENCES………………………………………………………………………………....111

APPENDICES……………………………………………………………………………….…136

xiii

LIST OF TABLES

Table 2.1: Examples of altered drug response…………………………………………………….9

Table 2.2: History/Evolution of

pharmacogenetics/pharmacogenomics…………………………10

Table 2.3: Reaction classed as phase I and phase II reactions

……………………………………22

Table 2.4: Differences between phase I and Phase II

reactions……………………………………23

Table 2.5: Examples of selected phase I reactions by microsomal mixed oxidase

system………30

Table 2.6: Examples of established probe drugs for selected CYPs……………………………..46

Table 2.7: Prevalence of CYP2D6 phenotype among races of the

world………………………..49

Table 2.8: Drug substrates for CYP2D6 phenotyping and their metabolic

ratios…..……………56

Table 3.1: The Chemicals, sources and quality………………………………………………….65

Table 3.2: The equipment and their sources……………………………………………………..66

Table 4.1: Frequency distribution of socio-demographic characteristics of 89

participants……..75

Table 4.2: The gender differences in age (years), weight (Kg), Height (meter) and BMI (kg/m2)

of the 89 participants…………………………………………………………………77

Table 4.3: Haematological parameters of the 89

participants…………………………………….79

Table 4.4: Biochemical parameters of the 89 participants……………………………………….81

xiv

Table 4.5: Results of Precision for Dextromethorphan and dextrorphan

………………………....90

Table 4.6: Results of accuracy and recovery for dextromethorphan and Dextrorphan in

plasma…91

Table 4.7: Limit of detection (LOD) and Limit of quantitation (LOQ) for dextromethorphan

and Dextrorphan………………………………………………………………………92

Table 4.8: Plasma and urine concentrations of dextromethorphan and dextrorphan in 89

Yoruba Nigerian participants………………………………………………………...94

Table 4.9: Correlation of the 8-hour urinary MR, 3-hour plasma MRs, age

and body mass index……………………………………………………………….101

Table 4.10: Some Socio-demographics of the identified PMs and

EMs………………………..103

xv

LIST OF FIGURES

Figure 2.1: Phase I and phase II metabolism of a lipophilic

xenobiotics…………………………21

Figure 2.2: Pie chart showing the distribution of human phase I enzymes of drug

metabolism….25

Figure 2.3: Human phase II enzymes of drug

metabolism………………………………………26

Figure 2.4: Examples of phase I reactions……………………………………………………….29

Figure 2.5: Examples of phase II reactions………………………………………………………33

Figure .2.6: Structure of Cytochrome P450 enzyme reaction………………………...………….37

Figure 2.7 a: The metabolic pathway of

dextromethorphan………………………...…………….53

Figure 2.7b: The metabolic pathway of dextromethorphan……………………………………...54

Figure 4.1: Pie chart showing the frequency distribution of the state of origin

of the 89 participants………………………………………………………………...76

Figure 4.2: Chromatogram of plasma sample of one participant showing Dextrorphan,

xvi

Internal standard and

dextromethorphan…………………………………………….83

Figure 4.3: Neat calibration curve of

Dextrorphan……………………………………………….84

Figure 4.4: Neat calibration curve of

dextromethorphan…………………………………………85

Figure 4.5: Calibration curve of dextromethorphan in

plasma……………………………………86

Figure 4.6: Calibration curve of dextrorphan in

plasma……………………………………..……87

Figure 4.7: Calibration curve of dextromethorphan in

urine……………………………………..88

Figure 4.8: Calibration curve of dextrorphan in

urine…………………………………………….89

Figure 4.9. Histogram showing the frequency distribution of the log MR in 8-hour

urine……….95

Figure 4.10: Probit plot representation of metabolic ratio (n=89) in 8-hour urine

samples……….96

Figure 4.11. Histogram showing the frequency distribution of the log MR in 3-hour

plasma……98

Figure 4.12. Probit plot representation of metabolic ratio (n=89) in 3-hour plasma

samples……..99

xvii

LIST OF APPENDICES

Appendix 1. UI/UCH Ethical

Approval………………………………………………136

Appendix 2. Registration of title of

Dissertation……………………………………...137

Appendix 3. Informed Consent……………………………………………………….138

Appendix 4. Chromatogram of blank plasma………………………………………...142

Appendix 5. Chromatogram of plasma spiked with 3µg/ml of

Dextrorphan………….143

Appendix 6. Chromatogram of plasma spiked with standard solution of 1µg/ml of

Levallorphan…………………………………………………………...144

Appendix 7. Chromatogram of plasma spiked with standard solution of 3µg/ml

of dextromethorphan……………………………………………………145

Appendix 8. Chromatogram of plasma spiked with standard solution of 3µg/ml of

Dextrorphan, and dextromethorphan, and 1 µg/ml of

levallorphan…….146

Appendix 9. Questionnaire…………………………………………………………..147

xviii

LIST OF ABBREVIATIONS

3-MOM 3-Methoxymorphinan

3-OHM 3-Hydroxylmorphinan

ACE Angiotensin Converting Enzyme

ADH Alcohol dehydrogenase

ADRs Adverse Drug Reactions

AFLPD Amplified Fragment Length Polymorphism Detection

ALDH Aldehyde dehydrogenase

ALT Alanine Amino Transferase

AST Aspartate Amino Transferases

ASO Allele Specific Oligonucleotide

BRCA Breast Cancer Susceptibility gene

CNV Copy Number Variations

COMT Catechol-O-Methyltransferase

CPIC Clinical Pharmacogenetics Implementation Consortium (CPIC)

CSL Central Science Laboratory

CYP2D6 Cytochrome P450 2D6

CYPs Cytochrome P450

DEX Dextromethorphan

DNA Deoxyribonucleic Acid

DOR Dextrorphan

DPD Dihydropyridine dehydrogenase

xix

DPWG Dutch Pharmacogenetics Working Group

EGFR Epidermal Growth Factor Receptor

EMs Extensive Metabolizers

FAD Flavin Adenine Dinucleotide

FDA Food and Drug Administration

FMN Flavin Mononucleotide

G6PD Glucose-6-Phosphate Dehydrogenase

GSH Glutathione

GST Glutathione-S-Transferase

HER2 Human Epidermal Growth Factor Receptor 2

Hb Haemoglobin

HLA Human Leucocyte Antigen

HMT Histamine methyltransferase

HPLC High Performance Liquid Chromatography

IMs Intermediate Metabolizers

LC-MS/MS Liquid Chromatography-Mass Spectrometry/Mass Spectrometry

LOD Limit of Detection

LOQ Limit of Quantitation

MR Metabolic Ratio

NADPH Nicotinamide Adenine Dinucleotide Phosphate

NMDA N-methyl-D-Aspartate

PCV Packed Cell Volume

PCR Polymerase Chain Reaction

RELPI Restriction Fragment Length Polymorphism Identification

SJS-TENS Steven-Johnson Syndrome and Toxic Epidermal Necrolysis

xx

ROC Receiver Operating Characteristics

SNPs Single Nucleotide Polymorphism

ST Sulfotransferase

TMPT Thiopurine-S-Methyltransferase

UDPGT Uridine Diphosphate Glucuronosyltransferase

UGT Uridine-Glucuronosyl-S-Transferase

UMs Ultra rapid Metabolizers

UV-VIS Ultraviolet Visible Spectrophotometry

xxi

ABSTRACT

Background: Twenty five percent of all clinically used drugs are metabolized by CYP2D6.

CY2D6 is highly polymorphic and more than 140 alleles have been identified. It is responsible

for marked inter-individual and interethnic variation in drug response. The consequences range

from adverse drug reactions in poor metabolizers to therapeutic failure in ultra rapid

metabolizers. Only scanty information exist about the many Nigerian and Africa ethnic

nationalities including the Yoruba Nigerian. The use of dextromethorphan as a probe drug and 8-

hour urine collection has become popular in the recent times. Single 3-hour plasma sample has

been shown to be adequate in the determination of CYP2D6 phenotype. The objective of this

study was to determine the CYP2D6 phenotype of Yoruba Nigerian using dextromethorphan as

probe in both urine and plasma matrices.

Methodology: Unrelated healthy Nigerians of Yoruba descent were invited to participate in the

study and history, complete physical examination and laboratory investigation were done. Each

participant received 30 mg of Dextromethorphan hydrobromide orally after an overnight fast and

were observed for more than eight hours. Peripheral venous blood sample collected 3 hour post

dose, immediately separated and plasma stored at -20oC. Prior to administration of the

dextromethorphan, participants completely emptied their bladder, subsequently all the urine were

collected for 8 hours and an aliquot stored at -20oC. Both plasma and urine samples were later

moved to -80oC freezer until analysis. Assay of Dextromethorphan (DEX) and Dextrorphan

(DOR) were done at the Central Science Laboratory, OAU, Ile-Ife using reversed phase HPLC

with UV detector. Sample separation was achieved on C18 column (100 x 4.6 mm, 3.5 µm

particle size) using a mobile phase of 30% Acetonitrile: 20% Methanol: 0.06% Triethylamine:

49.94% KH2PO4 (0.01 mol/litre), PH 3.2, flow rate: 1.5ml/min and then measured with UV

detection at 230 nm wavelength. Log of DEX/DOR(metabolic ratio) at 3 hour for plasma and at

8 hour for urine plotted on probit and antimode obtained that separates poor (PMs) and extensive

metabolizers (EMs).

Results: Fifty-eight (65.3%) male and 31(34.8%) female participated, with mean age of 36.1±9.5

years. The log MR that separated PMs from EMs was 0.28 (anti-mode 1.91) for urine and 0.75

(anti-mode 5.6) for plasma. Two male participants, aged 25 and 27 years, exhibited poor

metabolizer phenotypes, with mean MR of 17±13.4 in plasma and 3.2±1.4 in urine, which were

xxii

significantly higher than that of EMs, 2.5± 0.7 and 0.7± 0.4, respectively, (p<0.0001). The two

PMs were identified with 3-hour plasma and 8-hour urine MRs. There was strong positive

correlation between 8-hour urine and 3-hour plasma metabolic ratios {r2 =0.8, p<0.0001, 95% CI

(0.2, 0.9)}.

Conclusion: Two (2.3%) of the participants studied were found to be poor metabolizers. Both 8-

hour urine and 3-hour post dose plasma metabolic ratios of dextromethorphan/dextrorphan

differentiated poor and extensive metabolizers, and there was strong positive correlation between

urine and plasma metabolic ratios.

xxiii

CHAPTER ONE

1.0 INTRODUCTION

The human Cytochrome P450 enzymes are the predominant phase 1 metabolizing enzymes

involved in the biotransformation of 70-80% of clinically used drugs.(1) It has three main

families and several isoforms. Many isoforms of this group of enzymes have been identified

including CYP2D6 which is known to be responsible for the metabolism of about 25% of all

currently available clinically used drugs.(2) Notable among such drugs are antidepressants

(amitriptyline, imipramine, and paroxetine), beta adrenergic receptor blockers (metoprolol,

timolol, and propranolol), antipsychotics (risperidone, haloperidol), antiarrhythmic (flecainide,

encainide, propafenone) and miscellaneous drugs including: codeine, debrisoquine,

dextromethorphan, phenformin, tramadol, tamoxifen, which are also useful in the management

of many diseases.(3, 4)

CYP2D6 is highly polymorphic and more than 140 variants of its alleles have been

identified.The gene is located on chromosome 22q13. CYP2D6 genotype of an individual is

based on inheritance of wild or mutant alleles. Extensive metabolizers (EMs) inherit one or two

normal (or wild) alleles, e.g. CYP2D6*1, CYP2D6*2, whereas poor metabolizers (PMs) are

homozygous for two recessive null alleles e.g.CYP2D6*3, CYP2D6*4. Individuals that inherit

one wild and one null alleles are intermediate metabolizers (IMs), while those that possess

duplicated wild or normal genes (≥ 2 copies) are ultra rapid metabolizers (UMs).(4, 5) The

frequencies and distributions of the alleles in various populations vary widely throughout the

world, and among different races and ethnic groups.

Phenotypic expression of the combinations of the CYP2D6 alleles have been broadly divided

into four distinct groups by evaluating the capacity of individuals to metabolize such probe drugs

xxiv

as sparteine, debrisoquine, dextromethorphan and metoprolol. Thus, ultra-rapid metabolizers

(UMs) possess an increased activity; extensive metabolizers (EMs) possess normal activity;

intermediate metabolizers (IMs) and poor metabolizers (PMs) have reduced to negligible

capacity to metabolise the CYP2D6 substrates. (6-9) Studies among Caucasians indicate an

aggregate prevalence of 7-10% for PMs, 10-15% for IMs, 70-80% for EMs and 3-5% for UMs.

(10)The prevalence of PM in Asians is 1- 2%. (7, 11) The frequency distribution of PMs is

between 1 and 4%, in Africans. (12-16) Prevalence rate of up to 29% of ultra-rapid metabolisers

have been documented among blacks in Ethopia. (11, 17) In Nigeria, only few studies are

available, and the prevalence of CYP2D6 PMs phenotypes was reported as between 1 and 3.5%.

(8, 18, 19)

The clinical consequence of CYP2D6 polymorphism may include dose-related adverse events

due to poor drug clearance, or therapeutic failure in case the drug requires activation as in the

conversion of Codeine to Morphine in PMs. (17) Also, there may be absence of response

expected from the medications in UMs because of low and thus ineffective plasma

concentrations as could be inferred from non-response to an antidepressant(nortriptyline), (20-

22) or adverse drug reactions because of excessive formation of active metabolite (morphine) in

UM treated with codeine.(23)

Pharmacogenetics provides a veritable tool for the individualization of therapy with respect to

the choice and dose of the specific drug aiming at improving the efficacy of drugs and preventing

adverse drug reactions. Genotyping provides direct tools in the identification of specific

isoenzymes and therefore understanding of enzyme polymorphism, whereas phenotyping

evaluates the attendant biochemical effect taking into consideration, the influence of

environmental factors on the activity of the target enzymes. Phenotyping is necessary to obtain a

xxv

precise picture of an individual actual enzymatic activity via administration of appropriate probe

drug followed by measurement of its concentration and those of the specific CYP dependent

metabolites in the body fluid .(24)

Nigeria is the largest country in Africa comprising many ethnic nationalities. The 2006 census

conducted by the Nigerian National Population Commission put the country’s population at more

than 154 million. (25) Of the over 154 million people counted in 2006, Yoruba, a major ethnic

nationality, had a population of over 32 million, that is, 21%. (www.mapsofworld.com/Nigerian)

The Yoruba Nigerians are indigenous to the Southwestern Nigeria and are believed to share a

common ancestry. This study aimed at evaluating CYP2D6 phenotype among this group of

people using dextromethorphan as probe drug.

1.1 Statement of problem

Adverse drug reactions was the 4th to 6th leading cause of death in USA. (26) In PMs, the

benefits a drug offers may be denied by adverse drug reactions. Therapeutic failure results in

avoidable physical economic burden. There is high morbidity and mortality from therapeutic

failure and adverse drug reactions which is understood to be partly due to inappropriate dosage

and dosing as currently practiced. There is scanty information on the CYP2D6 status of Nigeria

ethnic nationalities despite their disparate ancestry.

xxvi

1.2 Rationale

Evidence of elevated plasma levels have been demonstrated and established in poor metabolizers

for risperidone (antipsychotics), amitriptylline (antidepressant), propafenone (antiarrhythmic

agent) and metoprolol (β-blocker).(4, 27-30) Low plasma levels and rapid clearance of

amitriptylline (antidepressants) and metoprolol (β-blockers) have also been demonstrated in

ultra-rapid metabolizers.(31-33)

Available literatures have shown that CYP2D6 polymorphisms are, at least, partly responsible

for this variability and have been well researched among the Caucasians, African-Americans and

Oriental populations. However, only paltry information exists about the many Nigeria and

Africa ethnic nationalities including the Yoruba Nigerians. (34, 35)There is need for concerted

efforts to bridge the information gap, especially considering recent advances in the area of

personalized medicine.

Validation criteria have shown that dextromethorphan and debrisoquine are the best CYP2D6

probes.(4, 36) The preference for dextromethorphan as a CYP2D6 probe is because of the

potential of the latter for causing clinically significant hypotension; particularly in poor

metabolizers.

Few attempts have so far been made at determining metabolic ratio (MR) in plasma samples. In

Nigeria, CYP2D6 phenotyping with dextromethorphan as probe drug was evaluated with

DEX/DOR ratio in urine. (8) Also, there is a need to assess the appropriateness or otherwise of

using plasma MR by comparing with the urine MR. There is total lack or, at least, scanty

information on the foregoing among the many Nigerian nationalities.

xxviii

1.3 Aims and Objectives

Broad Objectives

To determine the CYP2D6 phenotype of healthy volunteers in a Yoruba Nigerian population of

ethnic origin using dextromethorphan

Specific Objectives

1. To assess the metabolic ratio (MR) of dextromethorphan/dextrorphan in the urine.

2. To assess the metabolic ratio (MR) of dextromethorphan/dextrorphan in the plasma.

3. To compare the plasma and urinary metabolic ratios of dextromethorphan/dextrorphan in

the determination of CYP2D6 phenotype among healthy volunteers.

xxix

CHAPTER TWO

LITERATURE REVIEW

2.1 Background

Drugs have revolutionized modern medicine and this has led to the significant reduction in

morbidity and mortality associated with both communicable and non-communicable

diseases.(37) The effect of drugs varies from normal response, adverse drug reactions, which

may be life threatening to therapeutic failure. Variations in drug response occur within and

between individuals. Factors known to be responsible for the variations in responses to drugs

include genetics, age, sex, nutrition, other drugs co-administered and underlying diseases

especially liver and kidney diseases. Of these, genetics is an important factor responsible for

most of the variations in drug response. (38)

Pharmacogenetics is the study of the variability in drug response due to heredity. (39) It provides

explanation for the inter-individual differences in responses to pharmaceutical agents.(40)

Pharmacogenomics is the study of the human genome, and its structure as relates to genes

involved in drug absorption, action and elimination. (41) It was introduced in the late 1990s and

it studies how genetic inheritance of individual affects the body response to drugs. Unlike in

pharmacogenetics, where investigations in specific genes are related to individual differences in

drug response, pharmacogenomics use information from the entire genome of an individual to

study the variability in drug response.(42)The two terms are often used interchangeably but the

latter became more popular after the completion of the Human Genome project in 2003, in which

development of novel drugs from the newly discovered genes are given priority.(43)

Contextually, both terms enunciate personalized medicine. On the contrary, Ecogenetics or

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‘environmental genetics’, represents the entire field of gene-environment interactions, for

example, ionizing radiation, heavy metals, herbicides, foods, drugs, and alcohol. (44)

Genetic variations can be divided broadly into somatic mutations as occur in tumour tissue and

germ-line genetic variations.(45) The different somatic mutations in cancer on the other hand

have allowed the development of new anti-cancer agents aimed at treating patients whose cancer

cells carry the target mutation (target therapies). The germ-line genetic variants are heritable and

include variations in gene encoding drug metabolizing enzymes, drug transporters, drug targets

and human leucocyte antigen (HLA).(45, 46) Genetic variations may result from genomic

insertions, deletions, genetic copy number variations (CNVs) or single nucleotide

polymorphisms (SNPs). However, single nucleotide polymorphisms (SNPs) are the most

frequent sequence variations that affect drug metabolism, as they constitute approximately 90%

of all human genome variations and occurring in every 100 to 300 base pairs.(47)

Allele is one of two or more alternative forms of a gene that arise by mutation and are found at

the same place on a chromosome, and it results in genetic variations. The resultant genetic

variations are known as sequence variants if the alleles are present in less than one percent of

heterozygous individuals in a given population and polymorphism if the alleles are present in

more than one percent of heterozygous individuals in a given population. However, most of the

genetic variations that affect pharmacokinetics and pharmacodynamics are due to genetic

polymorphism. (38)

Genetic variations in drug metabolism influence pharmacokinetics-absorption, distribution,

metabolism and excretion; and pharmacodynamics-receptors interactions, ion channel

interactions, enzyme interactions, signaling pathway interactions and immune system

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interactions. Examples of altered drug response and the implicated genes are shown in table 2.1.

However, of all the altered drug responses due to genetic variations, cytochrome P450 enzyme

system is the most important one affecting drug metabolism.

The landmark discoveries in the field of pharmacogenomics are summarized in table 2.2. The

genomic evaluation, more importantly, after the human genomic project in 2003(48) has given

scientists the opportunity of having access to large quantities of genomic data that can be used in

the development of novel drugs/pharmaceuticals. (43) This revolution promises to provide many

potent and effective drugs for treatment of diseases and for the individualization of therapy

(personalized medicine).

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Table 2.1: Examples of altered drug response

Enzyme/Disease Gene

Glucose-6-Phosphate Dehydrogenase (G6PD) deficiency

N-Acetylation and tuberculosis

Cytochrome P450 Enzyme (drug metabolism)

Warfarin and coagulation

Thiopurine-S-Methyltransferase and cancer

Angiotensin Converting Enzyme (ACE) Inhibitors and

antidepressants, diabetes, asthma

G6PD

NAT2

CYP2D6

CYP2C9 and VKORC1

TMPT

ACE

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Table 2.2: History/Evolution of pharmacogenetics/pharmacogenomics

Year Discoveries

510BC

1932

1950s

1959

1977

1979

1990

2003

Pythagoras (Croton, Italy) observed haemolysis following the consumption of fava

beans. He was the first to recognize the danger of some food in those who are G6PD

deficient. Haemolytic anaemia following consumption of fava beans(49)

Snyder’s first observed that some people can taste phenyl-thio-carbamide while some

others could not. He described the ‘phenylthiourea non-taster’ phenotype inherited as

autosomal recessive trait(50)

Series of discoveries- Watson and Crick described DNA’s double helix. (51)Carson

et al. observed enzymatic deficiency in primaquine sensitive erythrocytes. (52)

Hughes described the metabolism of isoniazid in man as related to the occurrence of

peripheral neuritis. He linked the occurrence of peripheral neuritis to slow isoniazid

acetylation. (53)Kalow described the method for detection of an atypical form of

serum cholinesterases. He termed those with atypical form as having

butyrylcholinesterase deficiency and thereby demonstrated the influence of genetics

over drug response.

(54) Motulsky proposed the ideal of genetic components of drug effects.(55)

Friedrich Vogel first introduced the term “pharmacogenetics”(56, 57)

Observation of greater response to debrisoquine in a subgroup of population known

as “slow hydroxylator”(58)

Observation of greater response to sparteine in a subgroup of population known as

“slow hydroxylator”(59)

Human Genome Project started(60)

Human Genome Project completed(48)

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2.2. Racial/Individual Variation in drug handling

As widely known, factors affecting response to drugs are genetic constitution, age, sex, co-

morbidities, environmental factors including diet and lifestyle (e.g. smoking and alcohol intake)

and drug related factors including drug interactions. Genetic variation is the most important as it

can lead to more than 1000 fold change in plasma drug level in response to the same medication

among individuals of the same sex, weight and same drug dosage. (61)Responses to medications

are often compared among populations that are divided according to the traditional racial

divisions.(62) The opinion of some of the biomedical scientists about race differs as some

described it as “biologically meaningless”(63) or not “based on scientific evidence”(64).

However, some supported the uses of race “in designing research studies and taking medical

decisions”.(65-67) Scientists that see race as biologically meaningless claims there is more

genetic variation within the group as compared to between them. And that there is more subtle

and complex description of an individual genetic make-up in ancestry than the race. (68)

Evolutionary studies have divided humans into three main groups, Europeans, Asians and Africa.

The evolutionary relationship shows that the overall genetic distance between Europeans and

Asians is significantly lower than that between Europeans and Africans, and that between Asians

and Africans. Such observations appear to support the notion that Asians and Europeans have a

common descent from Africans.(69, 70) Studies have shown that an approximately 85-90% of

genetic variation are found in a collection of individuals from a single continent and only an

additional 10-15% of variation are found in the collection of Europeans, Asians and

Africans.(62, 71, 72) Barbujani et al. then concluded that “the differences among continents

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represents roughly 1-10% of human molecular diversity and does not suggest that the racial

subdivision of our species reflects any major discontinuity in our genome”. (72)

However, race may provide some useful information as other factors affecting variation in drug

response because individuals living together, or constituting a particular race, share some of the

other environmental conditions including culture, religion, climate and tradition. This affects

attitude to treatment and response to drug. Obviously, it is not all the inter-ethnic differences to

drug response that are genetic. Starvation, malnutrition and protein deficiency may all cause

differences in the way the response to drug. Climate is a chief determinant of food production

and therefore determines the racial characteristics of nutrition.

2.3. Pharmacogenomics, pharmacovigilance and Pharmacoepidemiology

The availability of many drugs means increased exposure to the potential risks associated with

their use. A meta-analysis of 39 prospective studies among hospitalized patients in the US

showed that the overall incidence of serious adverse drug reactions (ADRs) was 6.7% and that of

fatal ADRs was 0.32% of all hospitalized patients, making these ADRs to be fourth to sixth

leading cause of deaths.(26) In England, the reported prevalence of ADRs related to hospital

admission was 6.5%, increased hospital stay and overall fatality was 0.15%.(73) In US, there

was an increase in the serious adverse drug events reported to FDA between 1998 and 2007.(74)

Drugs are only approved for human consumption after requisite investigations through clinical

trials. These clinical trials are limited by strict selection criteria of few thousand individuals

relative to the number of people and populations that will eventually take the drug after approval.

It highlights the importance of post-marketing surveillance since some of these ADRs will only

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be detected after full approval. Therefore there is need for early detection and or prevention of

ADRs.

Pharmacoepidemiology is the application of epidemiological methods to the clinical use and

effects of drugs in a large population of people. It is primarily concerned with post- marketing

studies of drug safety, often based on large health care utilization databases using non

experimental study of intended and unintended drug effects outside of randomized controlled

trials. In addition to identifying adverse events, one of the goals of pharmacoepidemiology is to

identify reasons that may explain the adverse events. (75)

Pharmacovigilance is the science and activities relating to the detection, assessment,

understanding and prevention of adverse effects or any other possible drug-related problems.

(76) Many drugs have been withdrawn from the market following reporting of suspected ADRs

through pharmacovigilance. For about 33 years, between 1969 and 2002, more than 75

drugs/drug products were removed from the market due to safety problems and 11 drugs have

special requirements for prescriptions or have restricted distribution programmes by FDA. (77)

This highlight the importance of pharmacovigilance as the primary surveillance database used

for the identification of safety problems of marketed drugs. Apart from the problem of

underdeveloped pharmacovigilance system in developing nations, other limitations include

underreporting, (78-80) differential reporting, and uneven quality of reporting. In addition,

causality assessment is difficult and therefore, the underlying mechanism of the reported ADRs

are not known in most cases. Besides the key mechanism of the ADRs, it is difficult to

extrapolate the detected signals to other countries or geographical region in a faster and accurate

manner. (81) There is need for better design in pharmacovigilance in which the ADRs, drug

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resistance and treatment failure can be detected early with the possible mechanism of ADRs, and

with the potential of extrapolation to other populations or geographical region.

One of the most challenging areas of research in pharmacoepidemiology is to understand why

individuals respond differently to drug therapy, both in terms of beneficial and adverse effects.

Pharmacogenetics focuses on the question to what extent variability in genetic make-up is

responsible for these observed differences.(82) The pharmacogenomics and pharmacovigilance

aim is to understand heterogeneity and population substructure in the distribution of drug

efficacy and safety signals, and Sardas have proposed a term, pharmacogenovigilance, as a

convergence of the two. He defined “pharmacogenovigilance as pharmacovigilance activities

informed and guided by accompanying pharmacogenomics analysis”.(82) And studies have

shown the beneficial effect of this convergence including extrapolation of early signals on drug

related events from one population to another using pharmacogenomics biomarkers and

understanding of pharmacokinetics and pharmacodynamics performance of drugs in poor and

ultra rapid metabolizers.(83-86) Pharmacogenomics analysis can assist in the determination of

mechanisms of ADRs and contribute to causality assessment. This improves the reporting

standard by making it more scientific and mechanism oriented, and the pharmacovigilance can

then be generalized to other population.

This synergistic relationship can also be applied right from the early phase of the clinical trial.

For example, if the early clinical trial phase pharmacogenomics analysis suggests toxicity in

rapid acetylators, then the post-marketing surveillance will focus on rapid acetylators. This

should also assist in approval process of drug by the regulatory agencies. In addition, patients

can be selected for genotyping based on spontaneous ADRs reports, and this form of genomic

analysis have been found useful. (84, 87)

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The synergistic interaction between pharmacoepidemiology and pharmacogenomics will provide

opportunities including the application of molecular biology and pharmacogenetics (molecular

pharmacoepidemiology) to population studies and well-designed large scale clinical trials in less

contrived settings. This will eventually leads to more efficient drug development and a better

post-marketing surveillance. (88)

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2.4. Clinical Application of Pharmacogenetics

The overall goal and the main driving force for pharmacogenetics research is the optimization of

pharmacotherapy. Fully developed pharmacogenomics system will permit the identification of

“at risk” individuals thus avoiding or, at least, reduce drug-associated morbidity and mortality.

(89) The following are some of the specific clinical applications of pharmacogenomics.

1. Development of novel drugs: The pharmaceutical companies will be able to develop

drugs based on the proteins, enzymes and RNA molecules associated with gene and

diseases. That is drug discovery and therapy are targeted for specific diseases. This will

reduce the damaging effects of the drugs on healthy tissue and cells. For examples,

trastuzumab (Herceptin) used in the treatment of breast cancer targets HER2

receptor;(90) imatinib (Gleevec) used in the treatment of Chronic myeloid leukaemia,

targets tyrosine kinase receptor (91) and cetuximab (Erbitux) targets epidermal growth

factor receptor (EGFR) and is used to treat metastatic colorectal cancer.(92)

2. Better and safer drugs: The clinician uses the genetic profile of the patients to prescribe

the best available drug from the beginning instead of traditional trial and error methods of

matching. This will speeds recovery time and increase safety.

3. Optimization of dosages and dosing regimens: The dose of drugs will be based on the

individual genetic make-up rather than currently practiced generalization. It maximises

therapeutic value and reduces the likelihood of over dosage.(93)

4. Screening for diseases: With the completion of the Human genomic project and by

knowing the genetic code of an individual, it is possible to screen for diseases early and

ensure adequate life style and environmental modification. This will reduce the

occurrence and or the severity of genetic disease. In addition, it allows for the careful

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monitoring and introduction of treatment at the appropriate stage. (94) The following are

examples of diseases in which genetic screening are found useful.

a. Hypersensitivity reaction to Abacavir: Abacavir is nucleoside reverse

transciptase inhibitor and an effective antiretroviral drug. An important

limiting factor to its use is the hypersensitivity reaction. The immunologically

mediated hypersensivity reaction affects 5-8% of patients on abacavir and

occurs during the first 6 weeks of treatment. (95, 96)This hypersensitivity

reaction is strongly associated with the presence of HLA-B*5701.

Pharmacogenetic screening for HLA-B*5701 are been used to prevent the

toxic effect of the drug.(97, 98)

b. Tamoxifen and breast cancer: Tamoxifen is a selective oestrogen receptor

modulator and effective in the treatment of oetrogen positive early and

advanced breast cancer. Women with mutation of BRCA1 and BRCA2 have a

higher risk of developing breast cancer and of contralateral breast cancer after

the initial diagnosis of breast cancer. (99) Tamoxifen use decreases the risk of

development of contralateral breast cancer in women with mutation of

BRCA1 and BRCA2. (99)The reduction is more among premopausal or

women who had undergone natural menopause. (100).

In addition, tamoxifen is metabolized by CYP2D6 and individual who are

poor and intermediate metabolizers may not have the full benefit because of

slow metabolism of tamoxifen prodrug to its active metabolites, 4-

hydroxytamoxifen. (101, 102) Guideline for CYP2D6 pharmacogenetics

testing before using tamoxifen have been provided. (103)

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c. Carbamazepine-induced toxic effects: Carbamazepine is an anticonvulsant

and effective in treatment of seizure disorders. An important factor that may

limit its use is the carbamazepine induced Steven-Johnson syndrome and toxic

epidermal necrolysis (SJS-TENs). Carbamazepine induced SJS-TENs are

strongly associated with HLA-B*1502 allele. Screening of HLA-B*1502 and

avoidance of carbamazepine therapy is associated with reduction in

carbamazepine induced SJS-TENs. (104)

d. Warfarin induced bleeding: CYP2C9 and VKORC are enzymes that

metabolize warfarin, an important anticoagulant with narrow therapeutic

index. Individual who are poor metabolizers like CYP2C9*2 or CYP2C9*3 or

VKORC1 (g-1639G>A) are warfarin sensitive and therefore require a lower

dose to achieve optimal anticoagulation.(105) Genetic testing for CYP2C9*2

or CYP2C9*3 or VKORC1 (g-1639G>A) may allow for selection of patients

that will benefit from dose reduction and prevent the occurrence of fatal

adverse drug reaction. (106, 107)

5. Pharmacogenomics into DNA/RNA vaccines: Vaccination involves the introduction of

an infectious agents or component of an infectious agent to stimulate the immune system

to produce antibodies that neutralizes the organism anytime it invade the host. Traditional

vaccination are effected either by introducing a specific antigen or live attenuated

infectious agent. Pharmacogenomics recently allow introduction of appropriate tissues of

plasmid containing the DNA sequence encoding the antigen(s) against which an

immunity is achieved and relies on in situ production of the target antigen. Besides RNA

or complexes of nucleic acid molecules can be used.

xlii

(www.who.int/biologicals/ares/vaccines/dna/en). The advantage of the vaccines include

the ability to activate the immune system in the absence of infectious agents, provision of

both humoral and cell mediated immunity, and improved stability. Besides, the vaccines

are cheaper, easy to store, capable of being engineered to carry several strains of

pathogen at once and retain the traditional benefits of vaccine without risk. (108)

Examples include hepatitis B and West Nile virus vaccines.

6. Drug discovery: The pharmaceutical companies will be able to discover potential

therapies more easily and quickly using genomic targets. It may be possible to revisit

previously failed drug candidates and matching them with the niche population they

serve. The clinical trial will target specific genetic population and therefore increases the

degree of success. This will facilitate the drug approval process, reduces the cost and risk

of clinical trials.(93)

7. Reduction in the cost of healthcare: In addition to the ill health, adverse drug reactions

(ADRS) is associated with high cost of treatment. (73) Pharmacogenomics provides an

avenue to ensure reduction in number of ADRs, drug resistance and therapeutic failures.

And may also reduce the number of failed drug trials, the time it takes to obtain drug

approval, the duration of medication for effective therapy and increase in the range of

possible drug targets. All these will ultimately reduce cost of health care.(93)

2.5. Challenges

Pharmacogenomics is a rapidly growing specialty but is faced with some challenges

including the following:

http://www.who.int/biologicals/ares/vaccines/dna/en

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1. Gene variations: SPNs are DNA sequence variations and occur every 100 to 300

bases along the 3-billion base human genome. Thus, millions of SNPs must be

identified and analyzed to determine their involvement (if any) in drug response.

Besides, the process of obtaining the impact of gene variations that affect each drug

response is time-consuming and complicated since many genes may influence

response.(93)

2. Drug alternatives: Genetic screening may exclude some patients from taking certain

drugs because of possibility of life-threatening adverse drug reactions or therapeutic

failure. However, in such a situation, the patient may be left without alternative

treatment if there is only one or two available approved drugs for the treatment of the

condition.

3. Education: The traditional method of prescribing is simple. To implement

personalized medicine, there is need for the training of the prescriber since the

introduction of multiple pharmacogenomics to treat similar conditions for different

population subsets may complicate the process of prescribing and dispensing drugs.

4. Limited facilities: There is limited facilities and expertise for pharmacogenomics,

especially in developing countries.

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2.6. Drug Metabolism

Metabolism is the biochemical modification of pharmaceutical substances (or xenobiotics) by

living organism usually through an enzymatic products. It often leads to the conversion of

lipophilic chemical substances into readily excreted water soluble products by the kidney. The

aim of drug metabolism is to make drugs more water soluble, and more easily excreted from the

body.

The major site of drug metabolism is the liver in which the hepatic microsomal enzyme system

play an important role. Other sites of drug metabolism include the kidney, lung, intestinal

mucosa, plasma and nervous tissue. The routes of metabolism varies and determines the ultimate

pharmacological or toxicological activity of the drug. The routes include oxidation, reduction,

hydrolysis, hydration, conjugation and condensation.

Drug metabolism is divided into two major phases namely, phase I (or functionalization reaction)

and phase II (or conjugative reactions). Phase I prepare the drug for phase II by producing or

uncovering the chemically reactive functional group while phase II detoxify the drug, produce

inactive product that are excreted by the kidney and other organ of excretion. Figure 2.1 shows

the schematic representation of the phases of drug metabolism while table 2.3 shows the various

routes of metabolism under the 2 major phases of drug metabolism. The major differences

between phase I and Phase II reactions are shown in table 2.4.

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Figure 2.1: Phase I and phase II metabolism of a lipophilic xenobiotics

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Table 2.3: Reaction classed as phase I and phase II reactions (109)

Phase I reactions Phase II reactions

Oxidation

Reduction

Hydrolysis

Dethioacetylation

Isomerization

Glucuronidation/glycosidation

Sulfation

Methylation

Acetylation

Amino acid conjugation

Glutathione conjugation

Fatty acid conjugation

Condensation

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Table 2.4: Differences between phase I and Phase II reactions

Phase I Reaction Phase II Reaction

1. Degradative reaction

2. Introduction of functional group.

3. Mainly microsomal

4. Metabolites formed may be smaller,

polar/non-polar Active/Inactive

1. Synthetic reaction

2. Conjugates phase I metabolites with

glucuronic acid, sulphate, acetyl,

methyl group

3. Microsomal, mitochondrial and

Cytoplasmic

4. Metabolites formed are usually

larger, polar, water soluble and

inactive

xlviii

2.6.1. Enzymes involved in drug metabolism

The enzymes involved in drug metabolism are classified as either phase I (functionalisation) or

phase II (conjugative). They complement each other because phase II metabolizing enzymes act

on the products of phase I reactions. The various phase I and II human metabolizing enzymes are

shown in figure 2.2 and 2.3 below.

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Figure 2.2: Pie chart showing distribution of the human phase I enzymes of drug metabolism

(110)

l

Figure 2.3: Human phase II enzymes of drug metabolism (110)

li

2.6.2. Phase I (or functionalization) reaction

This is a non-synthetic reaction and it involves a change in the drug molecule by introduction of

reactive and polar groups into their substrate. The reactions include oxidation, reduction,

hydrolysis and hydration. This may results in activation, change or inactivation of the drug.

Figure 2.4 shows an example of type I reaction.

Phase I reactions can be sub-classified into the following reactions. (109)

1. Oxidation reactions involving cytochrome P450 enzyme system

2. Oxidation reactions involving other enzyme systems

3. Reduction reactions

4. Hydrolysis reactions

5. Isomerization reactions

6. Miscellaneous reactions

2.6.2.1. Oxidation reactions involving Cytochrome P450 enzyme system (the

microsomal mixed- function oxidases)

These enzymes system are found in the endoplasmic reticulum of many cells most

importantly the liver, but also in the kidney, lung and intestine. They are the most

important phase I metabolizing enzyme as they are involved in the metabolism of 70-

80% of clinically used drugs. (1) All the reactions require the presence of molecular

oxygen, NADPH and complete mixed function oxidase system. The reactions involve the

initial insertion of a single oxygen atom into the drug molecule, followed by

rearrangement and /or decomposition of this product and leading to the formation of the

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final product. Table 2.4 shows examples of reaction perform by microsomal mixed

oxidase system. (109)

2.6.2.2. Oxidation reactions not catalyze by cytochrome P450

These are phase I oxidation reactions not catalyze by cytochrome P450 mixed oxidase

system. Examples of the enzymes (substrate) involved are alcohol dehydrogenase

(ethanol), aldehyde dehydrogenase (aldehyde), xanthine oxidase (caffeine, theophylline,

and purine), amine oxidase (dietary tyramine, endogenous catecholamine, histamine, and

imipramine) and alkyl-hydrazine oxidase (carbidopa)

2.6.2.3. Reductive metabolism

The reduction reactions take place in the liver catalyzed by hepatic microsomal enzymes.

They require NADPH but are inhibited by oxygen. Examples of compounds that undergo

reduction include azo compounds (sulfanilamide/sulphonamide), nitro-compounds

(chloramphenicol), epoxides, heterocyclic ring compounds and halogenated hydrocarbon.

2.6.2.4. Hydrolytic reaction

This involve ester hydrolysis and occur in different part of the body. Examples include

plasma pseudocholinesterases (e.g. procaine) and liver specific esterases (e.g. pethidine,

meperidine).

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Figure 2.4: Example of phase I reaction

liv

Table 2.5: Examples of selected phase I reactions by microsomal mixed oxidase system

Reactions Substrate

Aromatic hydroxylation

Aliphatic hydroxylation

Epoxidation

N-Dealkylation

S-Dealkylation

O-Dealkylation

Oxidative deamination

N-oxidation

S-oxidation

Phosphothionate oxidation

Dehalogenation

Alcohol oxidation

Lignocaine

Pentabarbitone

Benzopyrine

Diazepam

6-methylthiopurine

Codeine

Amphetamine

3-methylpyridine

2-Acetylaminofluorene

Chlorpromazine

Parathion

Halothane

Ethanol

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2.6.3. Phase II metabolism (Synthetic reactions)

The conjugation or synthetic reactions involves chemical combination (covalent linkage)

of a parent compound or phase I metabolite with a molecule provided by the body

(usually a carbohydrate, amino acids or compound derived from them).The end products

of phase II reaction are highly water soluble and can be excreted in the bile or urine.

Figure 2.2 shows an examples of phase II reaction. The end products are usually inactive,

exception is morphine-6-glucuronide. The major phase II reactions are glucuronidation,

sulphation, acetylation, and conjugation with glutathione or amino acids. (111)

1. Glucuronidation: This is the most frequently occurring conjugation for drugs and

endogenous compounds. It involves the conjugation of glucuronide by UDP-glucuronic

acid in the hepatocytes. The enzyme for the reaction is UDP-glucuronosyl transferase,

and the glucuronic acid for the conjugation results from the breakdown of glycogen. The

glucuronide are highly polar and are easily secreted in urine and bile.

2. Sulphation: This involves conjugation with sulphate groups from phosphate-adenosyl-1-

phosphosulphate by sulphokinase to aliphatic or aromatic hydroxyl-containing

compounds and amines. Examples of compounds that are metabolizes by sulphation are

isoprenaline, chloramphenicol and serotonin.

3. Acetylation: This is a reaction of amino groups, and it involves the transfer of acetyl-

coenzyme A (acetyl CoA) to an aromatic primary or aliphatic amine, amino acid,

hydrazine, or sulphonamide group. Acetyl-coenzyme A is obtained from the glycolysis

pathway, catabolism of fatty acids or amino acids, or through direct interaction of acetate

and coenzyme A. The major site of acetylation is the liver. Other extrahepatic sites

include spleen, lung and gut. The enzyme involved in the acetylation is the acetyl

lvi

transferases, and genetic polymorphism affecting the reactions of these enzymes has

important consequences in drug therapy and tumorigenicity of certain xenobiotics. (111).

Examples of drugs that utilizes acetylation are isoniazid and hydralazine.

4. Glutathione (GSH) Conjugation: This involves the formation of thioether link between

the glutathione and electrophilic compounds. It results in detoxication of the electrophilic

compounds by preventing their reaction with nucleophilic centres in macromolecules

such as proteins and nucleic acids. The glutathione (GSH) is an endogenous compound

known to be protective by removing potentially toxic electrophilic compounds. The

highest concentration of GSH are found in the liver but are also found in the cortex,

medulla, cytosol, mitochondrial, nucleus and blood. The conjugates may be excreted in

the urine or bile but more commonly undergo further metabolism.(111)

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Figure 2.5: Examples of phase II reactions

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2.6.4. The Cytochrome P-450 Super Families (the CYPs)

The Cytochrome P450 is a large super family of haem-thiolate proteins involved in the

metabolism of a wide variety of both exogenous and endogenous compounds. (112) The

cytochrome P450 enzymes in families 1-3 are generally polymorphic and responsible for

70-80% of all phase I-dependent metabolism of clinically used drugs.(1) CYPs are

located in the smooth endoplasmic reticulum of cells throughout the body but the highest

concentrations are found in the liver. They were first discovered in 1955 in rat liver

microsomes, and are characterized by an intense absorption of light at wavelength of 450

nm in the presence of Carbon monoxide. (113) CYPs contain three domains, namely:

NADH or NADPH – dependent Flavin Adenine Dinucleotide (FAD) containing

reductase (FAD domain); an iron-sulfur protein or Flavin Mononucleotide (FMN) –

binding domain; and P 450 domain (haem domain).The haem is non-covalently bound to

the polypeptide chain. The haem contains one atom of iron in a hydrocarbon cage that

functions to bind oxygen in the CYP active site as part of the catalytic cycle of the

enzyme. CYPs use oxygen and hydrogen ion derived from the co-factor nicotinamide

adenine dinucleotide phosphate (NADPH) to carry out the oxidation of substrates. The

structure of Cytochrome P450 enzyme reaction is shown in figure 2.6.

Genomic sequencing has revealed the existence of 57 putatively functional genes and 58

pseudogenes in humans. At least 12 CYP gene families have been identified in humans,

although 3 families are involved in the majority of the drug biotransformation. These are

1, 2 and 3 (or CYP1, CYP2 and CYP3). These genes are grouped based on amino acid

sequence similarity into a super family composed of families and subfamilies with

increasing similarity. An enzyme belongs to a family when the amino acid sequence

lix

possesses more than 40% homology while enzymes with more than 55% homology form

a super family. (114) Genes encoding CYP enzymes, and the enzymes themselves, are

designated with the abbreviation CYP, followed by a number indicating the gene family,

a capital letter indicating the subfamily, and another numeral for the individual gene. For

example, CYP2D6 belongs to family 2, sub-family D and gene number 6. (3) In humans,

12 CYPs (CYP1A1, 1A2, 1B1, 2A6, 2B6, 2C8, 2C9, 2C19, 2D6, 2E1, 3A4 and 3A5) are

known to be important for the metabolism of xenobiotics. The most active CYPs for drug

metabolism are those in the CYP2C, CYP2D and CYP3A subfamilies. CYP3A is the

most abundant and it is involved in the metabolism of over 50% of clinically used drugs.

The CYP1A, CYP1B, CYP2A and CYP2E subfamilies are not significantly involved in

the metabolism of therapeutic drugs but catalyze the metabolic activation of many

protoxins and procarcinogens to their ultimate reactive metabolites .(3)

The CYPs that catalyze steroid and bile acid synthesis have specific substrate

preferences. However, the CYPs that catalyze xenobiotics metabolism have the capacity

to metabolize diverse chemicals. There is an extensive overlapping of substrate

specificity among CYPs, and they can therefore metabolize multiple substrates. These

features of CYPs may explain the prolonged half-lives, and the predominant drug-drug

interactions of their substrates. (3)

The expression of the different CYPs can differ markedly as a result of diet;

environmental exposure to inducers or inhibitors; inter-individual changes resulting from

heritable polymorphic differences in gene structure (genetic polymorphism); disease; and

age. Infants do not develop a mature enzyme system until more than 2 weeks after birth

lx

while elderly people have age related decreases in liver mass, hepatic enzyme activity,

hepatic blood flow, and therefore the overall metabolic capacity of the liver is decreased.

Genetic polymorphism can be defined as the presence within a population of at least two

groups with distinctly different abilities to metabolize drugs and xenobiotics. Individual

can be categorized as extensive (rapid), poor (slow), or ultra-rapid metabolizers. Thus,

individual who are PM may have adverse drug reactions whereas there may be lack of

effect in UM with normal dose of medication respectively. Genetic polymorphism and

differences in gene regulation are responsible for the largest inter-individual variability in

CYPs expression. Several human CYP genes exhibit polymorphisms including CYP2A6,

CYP2C9, CYP2C19 and CYP2D6. Low frequencies allelic variants are found in the

CYP1B1 and CYP3A4 but have little role in inter-individual variability in their

expression. (3)

lxi

Figure 2.6: Structure of Cytochrome P450 enzyme reaction

(https://en:wikipedia.org/wiki/cytochrome_P450)

lxii

2.6.4.1. CYP-Drug-Disease interactions: particular reference to CYP2D6–influenced

drugs

The ultimate goal of pharmacogenetics is individualization of therapy to reduce drug-associated

morbidity and mortality. However, as simple as it appears, only few drugs have simple or single

pathway of elimination process. In addition, metabolic pathways and mechanism of action of

substantial numbers of clinically used drugs are yet to be fully elucidated further increasing the

challenges to achieving individualized therapy. The fact that some drugs have active metabolites

or enantiomers with different activities and pathway of elimination poses a great problem. There

will be need for changing the dosage only if genotype or phenotype predictably affects the active

moieties at site of action of the drug. In addition, the therapeutic index of the drug and the

benefits of the prospective tests need when compared with the cost implication must be assessed

before recommending any pharmacogenetics tests/guidelines. (38)

It has been established that pharmacogenetics testing in relation to drug metabolizing enzymes

for certain drugs will enhance case management. Dosing regimens have also been provided for

such drugs.

1. Selective Serotonin Reuptake inhibitors (e.g. paroxetine, fluvoxamine): The Clinical

Pharmacogenetics Implementation Consortium (CPIC) dosing guideline for paroxetine

recommends an alternative drug not predominantly metabolized by CYP2D6 for CYP2D6

ultra rapid metabolizers and for CYP2D6 poor metabolizers. For CYP2D6 poor

metabolizers, if paroxetine use is warranted, consider a 50% reduction of recommended

starting dose and titrate to response.(115) For fluvoxamine, the CPIC recommends a 25-

lxiii

50% reduction of recommended starting dose and titrate to response or use an alternative

drug not metabolized by CYP2D6 for CYP2D6 poor metabolizers.(115)

2. Tricyclic antidepressants (e.g. amitriptyline, nortriptyline, clomipramine, imipramine,

trimipramine, doxepin, and desipramine): For amitriptyline and nortriptyline, the CPIC

guidelines recommends an alternative drug for CYP2D6 or CYP2C19 ultra rapid

metabolizers and for CYP2D6 poor metabolizers. Also, to consider a 50% dose reduction

for CYP2C19 poor metabolizers and a 25% dose reduction for CYP2D6 intermediate

metabolizers. In addition, it was suggested that the same dosing guideline be applied to

other tricyclic antidepressants since they have comparable pharmacokinetic

properties.(116)

3. Atypical antipsychotics (e.g. risperidone): The Dutch pharmacogenetics Working Group

(DPWG) guidelines recommends selecting an alternative drug or be extra alert to adverse

drug events for patients who are CYP2D6 poor metabolizers, intermediate metabolizers,

or ultra-rapid metabolizers with risperidone. Also to adjust risperidone dose to clinical

response.(103)

4. Codeine: Poor metabolism impedes the conversion of codeine to active morphine and

hence no or reduced analgesic activity. Also there is rapid formation and accumulation of

active metabolites in ultra-rapid metabolizers with the possibility of adverse drug

reactions. The Clinical Pharmacogenetics Implementation Consortium (CPIC)

recommends an alternative analgesics for CYP2D6 ultra-rapid and poor metabolizers.

And a label recommended age-or weight specific codeine dose is warranted for CYP2D6

extensive and intermediate metabolizers.(47, 117)

lxiv

5. Tramadol: For CYP2D6 poor metabolizers, the Dutch Pharmacogenetics Working Group

DPWG recommends selection of an alternative to tramadol (not oxycodone or codeine)

and be alert for symptoms of insufficient pain relief. For CYP2D6 intermediate

metabolizers, the prescriber should be alert for symptoms of insufficient pain relief, and

consider dose increase or select an alternative to tramadol (not oxycodone or codeine).

For CYP2D6 ultra rapid metabolizers, use a 30% decreased dose and be alert for adverse

drug events, or use an alternative to tramadol (not oxycodone or codeine).(103)

6. Tamoxifen: For CYP2D6 poor and intermediate metabolizers, the DPWG recommends

using an aromatase inhibitors for postmenopausal women due to increased risk for

relapse of breast cancer with tamoxifen. And to avoid concomitant use of CYP2D6

inhibitors in intermediate metabolizer.(103)

7. Metoprolol: To select another drug or reduce the dose of metoprolol for CYP2D6 poor

and intermediate metabolizers’ patients. And to use a dose titration of metoprolol for

CYP2D6 ultra rapid metabolizers or select an alternative drug.(103)

lxv

2.6.4.2. Pharmacogenetics testing of CYPs

Generally, two approaches are employed in the determination of variations in enzymatic

activities or allelic variants; genotyping and phenotyping. It may help in predicting the right dose

for the patients, and anticipating toxicities or therapeutic inefficacies.

2.6.4.2.1. Genotyping

Genotyping involves the determination of an individual’s DNA sequence and analysis of

functional genetic mutations coding for specific enzymes. It is possible to predict the phenotype

based on the alleles identified. It reveals the specific alleles that an individual has inherited

which may in turn affect the activity of drug metabolizing enzymes. Genotyping begins with

DNA extraction from (nucleated) cells of blood, oral mucosa and other easily accessible tissues

and organs of an individual using various standardized methods such as phenol-chloroform

method (118) or commercially available DNA isolation kits. The specific alleles are then

identified from the extracted DNA using genotyping methods such as restriction fragment length

polymorphism identification (RFLPI) of genomic DNA, random amplified polymorphic

detection (RAPD) of genomic DNA, amplified fragment length polymorphism detection

(AFLPD), polymerase chain reaction (PCR), DNA sequencing, allele specific oligonucleotide

(ASO) probes and hybridization to DNA microarrays or beads. Although it provides direct tools

in the identification of specific isozymes and therefore understanding of enzyme polymorphism,

it does not take the influence of environmental factors on the activity of the target enzymes into

consideration. Other advantages and disadvantages of genotyping are discussed below.

lxvi

Advantages of Genotyping

1. Intra-individual variability is not significant. This is because the genetic composition of

an individual is relatively constant and the same results is expected if the genotyping is

repeated severally. Therefore there is no need to repeat the genotype of an individual

once it is done.

2. The current genotyping methodologies are simple PCR-based assay and requires small

amount of whole blood and the techniques are easily adaptable in any molecular

laboratory.

3. Easier to use than biochemical measurements in a clinical setting. This is because it

requires only a single sample e.g. finger prick or buccal swab unlike in phenotyping

where you need venous blood, biopsies or saliva as the case may be.

4. Rapid bedside test. Genotyping can be done at the bedside of patients as there exist some

rapid diagnostic kits that can be used.

5. Sample can be obtained at the screening visit and results obtained before the washout

period is over.

6. Genotype is very useful in the early part of clinical trial for proper selections of

participants.

7. Retrospectively, post-marketing issues can be addressed by post-marketing collection of

DNA samples and subsequent pharmacogenomics analysis.

Disadvantages of Genotyping

1. Genotyping is not yet available for all CYPs.

lxvii

2. The presence or absence of a particular alleles may not absolutely determine the

phenotype. This is because some alleles may not be expressed.

3. It cannot measure the influence of the environmental factors such as drug-drug

interactions on the activities of the enzyme.

4. The facilities and expertise are not readily available especially in the developing

countries.

5. It is challenging for drugs with narrow therapeutic indices as intermediate metabolizer

cannot be readily identified.

6. Specific drug-drug interactions can convert extensive metabolizers to poor metabolizers

7. Ethical issues surrounding genotyping including fear of invasion of privacy, fear of

employer/insurance companies getting access to the genotype data

2.6.4.2.2. Phenotyping

Phenotyping consists of the administration of a probe drug metabolized by an individual specific

enzyme. It affords direct assessment of a person’s actual enzymatic activity by consecutive

measurement of their metabolites in body fluids. The commonly used body fluids include urine

and blood. Example of documented probe drugs for some CYPs are found on table 2.6.

There are two in vivo methods usually employed for identifying phenotypes, namely, the

selective (CYP-specific) and mixed (or cocktail) methods. The selective method of phenotyping

involves administering one probe drug. (119) The mixed or cocktail method involves the

simultaneous administration of multiple probe drugs specific for individual cytochrome P450.

The latter offers an economic advantage because many enzymes are evaluated at the same

time.(120, 121) Usually the metabolic ratio (MR) of the parent compound and its CYP-mediated

lxviii

metabolite is calculated after quantification by adequate analytical methods such as high

performance liquid chromatography (HPLC) or liquid chromatography mass spectrometry/mass

spectrometry (LCMS/MS) assays. The concentration of specific substrate and its identified major

metabolite in the body fluids (a ratio of molar concentrations; metabolic ratio) serves as a

measure of the individual’s CYP activity. Histograms of log-transformed metabolic ratios may

show cut-off values of MR which distinguish EMs from PMs, UMs or IMs. Phenotyping is

necessary because environmental factors may have influence on enzymatic activity. Other

advantages and disadvantages of phenotyping are discussed below.

Advantages of phenotyping

1. The influence of environmental factors can be evaluated.

2. It is possible to determine the activities of several enzymes (e.g. CYP) in a single test.

3. It provides information on the real-time (in-vivo) activity of the enzymes and may

therefore provide the most clinically relevant information as it reflects a combination

of genetic, environment and endogenous factors.

4. It may be helpful in drug-drug interactions studies of novel therapeutics because of

inherent interpatient variability in safety or efficacy

Disadvantages of phenotyping

1. Intra individual variability may be significant. Susceptibility to environmental

changes, unlike genotyping which is not.

2. The length of time it takes to determine metabolic states delays administration of

the test drug.

lxix

3. The involvement of other CYP isoform in the metabolism of the probe drug may

confound the interpretation of results.(122)

4. In patients on maintenance therapy, withholding treatment to permit phenotyping

would not be practical.(122)

5. Careful drug screening must be used as there may be significant drug-drug

interaction with inhibitors or inducers that may leads to inaccurate metabolic

measurements. For example, patients taking drugs that inhibit CYPs may have

reduced metabolite formation and misclassified as poor metabolizer.(122)

6. Rate of metabolism of the probe drug may not be a reflection of that of the test

drug.

7. Occurrence of side effects and pharmacokinetics-pharmacodynamics interactions

between the probes when therapeutic doses of probes are used.

8. Limited information is available about phenotyping in special groups including

children, elderly and patients with impaired function of the liver and kidney.(122)

9. Tedious sample collection, in terms of multiple sample (blood, urine etc.) and time

that patients have to wait for phenotyping.

The present lack of comprehensive knowledge of genotype-phenotype correlations represents a

limitation of the application of genotyping for pharmacogenomics decision making. The

phenotype is what is important to the physicians and unfortunately, present DNA-based tests can

fail to reflect the full range of phenotypic variation. As a result, a major challenge for companies

designing DNA-based tests is to develop dependable, economical, high-throughput genotyping

platforms, and a major challenge for pharmacogenomics science is to determine comprehensive,

clinically useful genotype-phenotype correlation .(123)

lxx

Table 2.6: Examples of established probe drugs for selected CYPs

CYPs Probe drug(s)

CYP2D6

CYP2C19

CYP1A2

CYP2A6

CYP3A

CYP2C9

CYP2B6

Debrisoquine, Sparteine, dextromethorphan, metoprolol

Omeprazole

Caffeine

Nicotine

Erythromycin, dapsone, endogenous cortisol, midazolam

Warfarin, tolbutamide, losartan, flurbiprofen

Bupropion

lxxi

2.6.4.3. Cytochrome P450 2D6 (CYP2D6)

CYP2D6 gene is located on chromosome 22q13.The enzyme is largely non-inducible and

represents about 1-5% of the total cytochrome P450 in the liver. (124, 125)The enzymatic action

of CYP2D6 is genetically determined and has a polymorphic distribution in most populations.

This can result in 30-40 fold differences in substrate drug clearance resulting in concentration

outside both sides of the therapeutic range in a fraction of treated patients.(23, 32) Human inherit

two alleles for CYP2D6 gene, one from each parent. Each allele may be normal or wild

(designated ‘wt’) or variant type (designated ‘vt’). Hence, genotypically, an individual may be

homozygous wild type (wt/wt), heterozygous (wt/vt), or homozygous variants (vt/vt). (126)The

following are examples of the alleles with different activities based on inheritance. (127)

1. CYP2D6 with non-functional or null alleles (vt/vt): CYP2D6*3, CYP2D6*4, CYP2D6*5,

CYP2D6*6, CYP2D6*7, CYP2D6*8, CYP2D6*11, CYP2D6*12, CYP2D6*13, CYP2D6*14,

CYP2D6*15, CYP2D6*16, CYP2D6*18, CYP2D6*19, CYP2D6*20, CYP2D6*21,


CYP2D6*47, CYP2D6*51, CYP2D6*56, CYP2D6*62

2. CYP2D6 with increased or normal alleles (wt/wt): CYP2D6*1, CYP2D6*2, CYP2D6*27,


3. CYP2D6 with alleles with reduced activity (wt/vt): The individuals possess one wild and one

null alleles (wt/vt) e.g. CYP2D6*10, CYP2D6*17, CYP2D6*29, CYP 2D6*41, CYP2D6*49,

CYP2D6*50, CYP2D6*54, CYP2D6*55, CYP2D6*59, CYP2D6*72

4. CYP2D6 with functionally undetermined alleles: CYP2D6*22 to *26, CYP2D6*28,


lxxii



Depending on the combination of CYP2D6 alleles present, an individual may be classified as

poor metabolizers (PMs), intermediate metabolizers (IMs), extensive metabolizers (EMs) and

ultra-rapid metabolizers (UMs). In UMs there is duplication of the wild alleles (≥ 2 wt) and it is

autosomally inherited.

The CYP2D6 genotype and phenotype vary greatly among populations of different racial origin

in the world. The most common alleles among the different races are Caucasians (CYP2D6*2,

CYP2D6*3, CYP2D6*4, CYP2D6*5, CYP2D6*6, CYP2D6*10, CYP2D6*41) (128), Asians

(CYP2D6*10, CYP2D6*36) (128, 129) and African (CYP2D6*17, CYP2D6*2) (128, 130, 131).

The prevalence of the CYP2D6 phenotypes among races are shown in table 2.7.

To assess the CYP2D6 phenotype of an individual, the clearance of a substance exclusively

metabolized by the CYP2D6 would be the most appropriate. However, this may not be feasible

all the time because of environmental factors and renal excretion. Therefore, to accurately assess

its enzymatic activity, it will be necessary to determine the partial clearance of a compound

which it metabolizes to its dependent metabolite. The metabolic ratios of some CYP2D6 probe

drugs have been established e.g. debrisoquine, dextromethorphan, metoprolol, sparteine and

tramadol. (132-135)

lxxiii

Table 2.7: Prevalence of CYP2D6 phenotype among races of the world

Race Prevalence of CYP2D6 phenotype

Caucasian

Asians

Africans

Nigerian

EMs (70-80%), PMs (7-10%), IMs (10-15%), UMs (3-5%)(10, 136, 137)

PMs (1-2%), IMs (50-70%), UMs (1-2%)(138)UMs Saudi Arabia

(29%)*(139, 140)

PMs (1-4%), IMs (18-34%), UMs Ethiopians (29%)*(13, 15, 130, 141,

142)

PMs (0-3.5%), IMs (18%)(8, 18)

lxxiv

2.6.4.3.1. CYP2D6 Probe Drugs

The commonly used suitable probe drugs for CYP2D6 phenotyping are debrisoquine, sparteine,

tramadol, metoprolol and dextromethorphan. (143, 144)

Both debrisoquine and sparteine are considered appropriate probe drugs but concern about

safety, as they cause clinically significant hypotension, and availability make them inferior

compared with other worldwide available and approved probe drugs such as

dextromethorphan.(121, 135, 145)Besides, there is little correlation between the metabolic ratios

of debrisoquine, sparteine and dextromethorphan with that of metoprolol for some non-

Caucasian populations.(6) Fux et al showed that in addition to hypotension caused by metoprolol

in some cases, there was no association between CYP2D6 genotype derived phenotype and

adverse effects during a 6-week course of treatment with metoprolol .(10)Tramadol use as probe

drug is limited because of its poor tolerability. It may cause nausea, vomiting, tiredness or

drowsiness. In addition, large doses are needed for a reliable assay. (146)

2.6.4.3.2. Dextromethorphan (D-3-methoxy-N-methyl morphinan) as CYP2D6 probe

Dextromethorphan is a synthetic analog of codeine. It is normally used in the treatment of cough

as an antitussive by elevating the threshold of cough reflex. (3) It has no analgesic or addiction

proneness and does not act through the opioid receptor. Its potency is nearly equal to that of

codeine but produces fewer subjective and gastrointestinal side effects. It is well established as a

probe drug.(6) It fulfills the criteria for the validation of phenotyping probe drugs and assay used

for cytochrome P450 2D6. Some of the criteria include, wide safety margin and availability, it is

predominantly metabolized by CYP2D6 and can be safely administered to human. (119, 121) It

is well absorbed from the gastrointestinal tract after oral administration. The maximum serum

lxxv

concentration level of the dextromethorphan occurs at about 2.5 hours (147) while that of its

major metabolite (dextrorphan) occur at about 1.6 to 1.7 hours. (148) Other metabolites of

dextromethorphan are 3-hydroxymorphinan and 3-methoxymorphinan. The onset of action is

rapid, often beginning between 15 to 30 minutes after administration. It is widely distributed and

does not bind to plasma protein. It has a half-life of between 2 and 4 hours in individuals with

normal metabolism (EMs) and between 21.1 and 37.9 hours in PMs. The dextromethorphan

metabolic pathway (figure 2.7a&b) is mediated by θ-demethylation to dextrorphan (DOR), its

major active metabolite, by CYP2D6, and N-demethylation to 3-methoxy-morphinan (3-MEM)

via CYP3A4/5. (149, 150) 3-Methoxymorphinan (3-MEM) is further metabolized to 3-

hydroxymorphinan (3-OHM) by CYP2D6. Dextrorphan and 3-hydroxymorphinan may undergo

glucuronidation by uridine diphosphate glucuronosyltransferase (UDP-glucuronosyltransferase,

UDPGT) enzyme and are then eliminated via the kidneys. (151) Less than 0.1% is excreted

through the faeces.

It mediates its action through multiple mechanisms including the opioid sigma 1 and sigma 2

receptors agonist, the serotonin reuptake pump inhibitor (non-selective serotonin reuptake

inhibitor), α3/β4 nicotinic receptor blockers and N-methyl-D-aspartate (NMDA) glutaminergic

receptor antagonist(non-competitive channel blocker) in the central nervous system.(152) It is

contraindicated in patients taking selective serotonin reuptake inhibitors (e.g. fluoxetine,

paroxetine), monoamine oxidase inhibitors; atopic children; people with persistent or chronic

cough (e.g. smoking, emphysema, asthma) or when cough is accompanied by excessive

secretion; and history of hypersensitivity reaction to the drug. It is avoided in individuals taking

alcohol and other central nervous system depressants, because it increases the central nervous

system side effects, including dizziness, drowsiness, difficulty concentration, impairment in

lxxvi

thinking and judgement. Adverse effects are very uncommon at therapeutic doses. However,

dizziness, drowsiness, central nervous depression, nausea, vomiting and abdominal pain may be

precipitated at extremely high doses. (3)

In addition to the CYP34 that is involved in the metabolic pathway of dextromethorphan as

shown in figure 2.6, another enzyme that metabolizes the drug is CYP2C9, although it only

contributes to the formation of dextrorphan (DOR) at increasing dextromethorphan (DEX)

concentration, above the recommended dose for CYP2D6 phenotyping.CYP3A contributes only

minimally to individual variability of the metabolic ratios,(153) and several isoenzymes of

cytochrome P450 including CYP3A/4, CYP3A5, CYP3A7, CYP2C9, and CYP2C19 catalyze the

alternative pathway of dextromethorphan (DEX) metabolism to 3-methoxymorphinan.(154-156)

The specificity of the metabolic step DEX/DOR was evaluated as high enough and reliable for

measuring the activity of CYP2D6 in humans.(148, 157-159) Dextromethorphan has been

validated as the best probe drug using the proposed validation criteria and it remains the most

widely used probe for CYP2D6 metabolic activity assessment in vivo. It supersedes other probe

drugs because of its worldwide availability, good tolerability and well characterized metabolic

profiles. (143, 145, 160, 161) It can be used for detecting CYP2D6 activity in a variety of body

fluids including urine, blood and saliva.

lxxvii

a.

Figure 2.7a: The chemical structure and metabolic pathway of dextromethorphan (150) the

apparent Km for the major contributor to each reaction estimated in the present study is shown

lxxviii

Figure 2.7b: The chemical structure and metabolic pathway of dextromethorphan (162)

lxxix

2.6.4.3.3. Metabolic Ratio (MR) in biological matrices

Metabolic ratio is the differences in the metabolic ability of enzymes, and can be obtained

indirectly by relating the ratio of the molar concentration of the unchanged drug to that of its

dependent metabolite collected in the biological fluid (drug/metabolite). It has been employed in

CYP2D6 phenotyping with different probes including debrisoquine (debrisoquine/4-

hydroxydebrisoquine), (13, 58, 163) sparteine (sparteine/2- +5-dehyrosparteine), (18, 59)

metoprolol (metoprolol/α-hydroxymetoprolol) (18, 164) and dextromethorphan (DEX/DOR).

(165-167)

In determining the CYP2D6 phenotyping, 8-hour urine collection is known to match the 24-hour

collection hitherto 8-hour urinary metabolic ratios of the probe drugs are employed for

debrisoquine, sparteine, metoprolol and dextromethorphan. And inter-individual variability in

CYP2D6 activity are obtained by finding the appropriate cut off points (antimode) in the

logarithm transformed metabolic ratio (log MR). This cut off point can be used to separate

individuals into extensive, intermediate, poor and ultra rapid metabolizers depending on the

sensitivity of the analytical methods employed. Although the antimode may differ from one race

to another and differences in the laboratory methods/techniques, certain antimode have been

validated for the different probe drugs in differentiating poor from extensive metabolizers. For

example studies have categorized PMs as individual with an MR greater than 12.6, (165)20,

(166, 167) 1.10(164) and 0.3(168) for debrisoquine, sparteine, metoprolol and dextromethorphan

respectively (table 2.8).

The methods that are employed in determining the appropriate cut off metabolic ratio for

separating different phenotypes, in addition to values from literature, are receiver operating

characteristics (ROC),(169) histogram and probit plots.(170)

lxxx

Table 2.8: Drug substrates for CYP2D6 phenotyping and their metabolic ratios

Test drug and products Phenotypes References

Debrisoquin→4-

hydroxydebrisoquin

PM=MR≥12.6

UM=MR<0.5

(165)

Dextromethorphan→dextrorphan PM=MR≥0.3 (168)

Metoprolol→α-

hydroxymetoprolol

PM>1.1 (164)

Sparteine→2- and 5-

dehydrosparteine

PM≥20 (166, 167)

lxxxi

2.6.4.3.4. CYP2D6 Phenotyping with Dextromethorphan using Urinary Assay

The urinary metabolic ratio of DEX/DOR is widely used to assess CYP2D6 because of

its non-invasiveness. Study has shown that the metabolic ratios obtained with 24 hours

urine were highly correlated with those in either the 8hour (r=0.967, p<0.0001) or 4 hours

urines (r=0.946, p=0.0001).(171) Advantages of urinary matrix include its non-

invasiveness, convenience, reliability and has been widely validated for CYP2D6

phenotyping. However, it may not be possible in children, psychiatric patients and even

some non-psychiatric adults may not completely empty their bladder. Normally, urine

samples are de-conjugated with B-glucuronidase before measurement in order to include

the entire amount of unbound DOR and 3-hydroxymorphinan (3-OHM). Study has shown

a significant inverse relationship between physiologic urinary PH and sequential

DEX/DOR metabolic ratio, and may lead to a 20 fold variation in urinary DEX/DOR

metabolic ratio.(172) Lower recoveries of dextrorphan were found in patients with

impaired renal function.(173) However, this lower recovery may be corrected by

increasing the collection period.(174) Most phenotyping studies are carried out with the

urinary DEX/DOR metabolic ratio of the 0- to 8 hour collection interval. The correlation

between the metabolic ratios of the different urine collection intervals for CYP2D6

phenotyping were investigated and found to be suitable for the 4-hour, 6-hour, 8-hour and

12-hour but not for 2-hour interval.(175) Chladek et al also found good correlation

between the urinary DEX/DOR metabolic ratio of the 4-h and 8-h samples with 24-h

interval.(171)In addition, Anna Wojkczak et al found 10-hour urine collection interval

suitable for CYP2D6 phenotyping following administration of 40 mg dextromethorphan

lxxxii

among healthy volunteers of Polish origin.(176) Studies in Africa also found good

correlation with 8 hours urine collection using 30 mg of dextromethorphan.(8, 177)

Urinary MRs of DEX/DOR of the 0-8 hour sample can be regarded as an appropriate

metric with its advantage being shorter collection time compared with the MRs of the 12-

and 24-h collection intervals. However, the discomfort of having to stay for longer period

of time for urinary collection, effect of urinary PH and renal impairment necessitated the

need for the validation of other body fluids for phenotyping with DEX.

2.6.4.3.5. CYP2D6 Phenotyping with Dextromethorphan using plasma/ serum

This is one of the alternative procedures developed because of the highly demanding

nature of the 8-h sampling urine, effect of urinary pH and renal impairment. It is more

representative, requires only one sample collection and not time consuming. However,

limitations are mainly due to the low analyte concentrations, thus sensitive analytical

methods are needed for the purpose of phenotyping using plasma/serum.

Kӧhler et al showed that the 1-hour sample was able to differentiate between EM and PM

and suggested a value of 0.126 using the 1-h post-dose metabolic ratio of

DEX/DOR.(178)Shiran et al. suggested a value of 0.1 for differentiating between EM and

PM using 3-hour post-dose MR of DEX/DOR (179) whereas Jurica et al. in a recent

study conducted among Caucasians indicated a cut-off (determined by receiver operating

characteristics (ROC)) of 0.215- 0.742 discriminating IM from PM and the cut-off value

for discriminating PM from IM +EM was 0.21-0.742 3-hour post-dose MR of

DEX/DOR.(169) This finding corroborate the need to determine the antimode of MR for

separating phenotypes in different races unless it has been validated. Jurica et al. also

lxxxiii

demonstrated a good correlation between serum and urinary metabolic ratio of

DEX/DOR. (169) The MRs of the 3-, 4-, 6- and 8-h serum samples were compared with

oral clearance of dextromethorphan and its AUC for 10 subjects. The correlation were

r=0.60-0.74, p<0.003 between serum MRs and oral clearance, and r=0.79-0.88 between

the MRs and the AUC of DEX respectively.(180) It was concluded from the above study

that samples at 2, 3, 4, 5 and 8 h after drug administration serves well for phenotyping

purposes.(181)

2.6.4.3.6. Analytical Methods for Dextromethorphan and Dextrorphan in Biological

Matrices

The various analytical methods that have been employed for the determination of

dextromethorphan and Dextrorphan in the biological fluids include direct fluorescence

spectrometry,(182) radioimmunoassay,(183) gas-liquid chromatography,(168) high-performance

liquid chromatography (HPLC)(153, 184-186) and Liquid Chromatography–Mass

Spectrometry/Mass Spectrometry (LC-MS/MS). (151, 187, 188) LC-MS/MS is considered as the

most preferred method because of its high sensitivity but cost and availability limit its usage.

High performance liquid chromatography (HPLC) with fluorescence detector is the most

commonly employed analytical technique for dextromethorphan and its metabolites in biological

matrices.

Reversed phase HPLC is the most commonly used, and though it makes use of column with

similar size with normal phase, the silica-based column is modified to non-polar, “reversed”, by

attaching long hydrocarbon chains to its surface (either 8 or 18 carbon atoms). Also a polar

lxxxiv

solvent is used e.g. water and methanol, and this allow for faster movement of polar molecules

through the non-polar stationary phase.

In separating dextromethorphan and its metabolites, reversed phase HPLC is commonly used and

different types of column have been used, though with different sensitivities and recoveries.

Example of such column include phenyl column, (153, 169, 189-191) cyano column (192) and

C18 column. (186, 193, 194). However, phenyl column is preferred as it produces adequate

separation. (195)

Of all the established detectors used in HPLC, Ultraviolet Visible spectrophotometry (UV-VIS),

photo diode Array, fluorescence, mass spectroscopy, electrochemical detector, refractive index

and light scattering detector, the most commonly used detectors for dextromethorphan and

Dextrorphan are UV-VIS detector and fluorescence detector.(153, 171, 184) In the assay of DEX

and DOR, fluorescence detector offers greater sensitivity over UV-VIS detector. (191)

lxxxv

CHAPTER THREE

MATERIALS AND METHODS

3.1. Setting

According to the 2006 population census, Nigeria has a population of over 154 million, (25)

across the 36 states, and the Federal capital territory. Nigeria is divided into six geopolitical

zones namely; South-west, South-east, South-south, North-east, North-west and North-central

zones. There are about 371 ethnic groups in the Country, and Yoruba ethnic group is one of the

major ones. Together with the two other major ethnic groups, Hausa and Ibo represent about

68% of Nigerian population (24, 25). The Yoruba Nigerians inhabit the Southwestern and some

part of the North central Nigeria. Historically, the Yoruba people were said to have migrated

from Mecca, Saudi Arabia under the leadership of Oduduwa, and have settled in the present day

Ile-Ife, Osun State, Southwest Nigeria at about 600 BCE. Yorubas are also found in the Republic

of Benin and Togo, West Africa. (196) They constitute about 21% of the total population of

Nigeria, that is about 32.34 million.

3.2. Location of the Study

The study was coordinated at the University College Hospital (UCH), Ibadan located in Oyo

State, Southwestern Nigeria (Longitude 3.916667°E, Latitude 7.396389°N). Ibadan is the capital

of Oyo State. It has accommodated the central of administration of regional and subsequently

State government since the pre-independence era. The population of Ibadan is 2,338,659

lxxxvi

according to 2006 census. The University College hospital (UCH) was established by an act of

parliament in November, 1952 in response to the need for the training of medical personnel and

other healthcare professionals for the country and the West African Sub-Region. It serves as an

apex referral center for patients from every part of Nigeria and neighbouring West African

countries. The hospital provides health services at all levels, from primary to tertiary particularly

for residents of Ibadan and its environs. It is an 850- bed space hospital. It provides services in

all subspecialties of Internal Medicine, Surgery, Obstetrics & Gynecology, Pediatrics,

Otorhinolaryngology, Ophthalmology, Anesthesia, Laboratory Medicine, Psychiatry,

Community Medicine, General Medical Practice, Radiology, Radiotherapy and Dentistry.

Medical patients in all subspecialties, including Cardiology, Clinical Pharmacology,

Dermatology, neurology, Nephrology, Gastroenterology, Endocrinology, Respiratory and

Infectious diseases.

3.3.Ethical approval

Ethical approval was obtained from University of Ibadan/University College Hospital (UI/UCH)

Ethical Review Committee (Appendix 1).

Each participant gave a written informed consent (Appendix 3) following the explanation of the

nature and procedure involved in the study. They were also informed about the voluntary nature

of the study, and the obligations of the investigators including the observance of strict

confidentiality.

3.4.Design and Study Population

There was no formal advertisement but adult Nigerians of Yoruba ethnic group were informally

invited to participate in the study by visiting social functions, community meetings where the

lxxxvii

study was introduced. Individuals of Yoruba descent were thereafter requested to come to the

Clinical Pharmacology ward at the University College Hospital. They were instructed to abstain

from taking any natural remedy or over-the-counter drugs two weeks before the test. The

participants were enrolled in batches of between 10 and 12 on each of the recruiting days

between 2 September and 30 September, 2014. Full cognizance was taken of the convenience of

the participants in determining their schedule for enrolment.

The study design was quasi-experimental involving healthy participants. It was ensured that no

two participants were blood relations. The minimum sample size was calculated using the

prevalence of poor metabolisers obtained in a similar study conducted at Ile-Ife.

The assay of dextromethorphan and dextrorphan took place at the Central Science Laboratory

(CSL) of the Obafemi Awolowo University (OAU), Ile-Ife with High Performance Liquid

Chromatography (HPLC) with UV detector.

3.5.Sample Size Determination

Minimal sample size was determined using Fisher’s statistical formula.

n=Zα2 x p (1-p)

d2 Where n = sample size

Z = 1.96, that is standard normal deviate at 95% confidence interval

P = expected prevalence or proportion of the outcome of interest =0.035(the expected

proportion of poor metabolizers in Nigeria is 3.5% in recent study conducted in Ile-Ife (8)

d = precision (if 5%, d = 0.05)

lxxxviii

n=1.962X 0.035(1-0.035) =52

0.052

The minimum sample size, n=52

3.6.Eligibility/ Inclusion Criteria

Male or female Yoruba-Nigerians aged 18 - 50 years

Informed consent of the participant

Non-smoking

Not on any medication at enrolment or the two weeks preceding enrolment

3.7.Exclusion criteria

Persons with any chronic illness, for example, hypertension, chronic kidney disease,

diabetes mellitus

Chronic use of alcohol or any other recreational drugs

Oral contraceptives

Pregnancy

Lactation

Allergy to dextromethorphan and related drugs

3.8.1.Chemicals and drugs

The chemicals and drugs used are shown in table 3.1

3.8.2. Equipment

lxxxix

The equipment and their source are shown in table 3.2

Table 3.1: The chemicals, source and quality

Chemicals Source Quality

Dextrorphan tartrate Toronto Research Chemical HPLC grade

Dextromethorphan hydro

bromide Sigma-Aldrich chemical company,

Steinheim, Germany HPLC grade

Levallorphan tartrate Sigma-Aldrich chemical company,

Steinheim, Germany

HPLC grade

Acetonitrile Sigma-Aldrich chemical company,

Steinheim, Germany

HPLC grade

Methanol Sigma-Aldrich chemical company,


β-glucuronidase (Helix

Pomata) Sigma-Aldrich chemical company,


Anhydrous sodium carbonate BDH Chemical limited, England Analytical grade

Anhydrous sodium acetate BDH Chemical limited, England Analytical grade

Orthophosphoric acid BDH Chemical limited, England Analytical grade

Potassium dihydrogen

orthophosphate (KH2PO4

BDH Chemical limited, England Analytical grade

Hydrochloric acid BDH Chemical limited, England Analytical grade

Ascorbic acid BDH Chemical limited, England Analytical grade

Hexane and n-Butanol Scharlau SL Gato Parez, Spain Analytical grade

Triethylamine Burgoyne reagents, India Analytical grade

Dextromethorphan

hydrobromide syrup

(Tussipect), Belgien

1.5mg/mL

Benjamin Michael Pharmacy, Lagos

Table 3.2: The Equipment and their sources

xc

Equipment Sources

Agilent 1260 series HPLC system Agilent Technologies, Germany

Quaternary pump VL (model G1311C) Agilent Technologies, Germany

A gradient mixer with a system purge Agilent Technologies, Germany

The injector (manual injector valve with a 20 µl sample

loop)

Rheodyne, USA

Online vacuum degasser Agilent, Japan

Sample detector with a variable wavelength (VWD)

(190-600nm) standard version (model G1311B)

Agilent Technologies, Germany

LC3D Chemstation software and window 2007 Agilent Technologies, Germany

Eclipse plus C-18 reverse phase HPLC column (3.5 µm

particle size and 100 x 4.6 mm, i.d.)

Agilent, USA.

xci

3.9. Conduct of the Study

Subsequently the participants were interviewed with respect to their medical history and were

physically examined including blood pressure, height and weight. Thereafter samples were

collected for laboratory investigations such as full blood count, liver function tests, serum

electrolyte, urea and creatinine, and urinalysis for purpose of determining vital organs functions.

The participants were instructed to fast overnight. Similarly, prior to the administration of

dextromethorphan, participants were instructed to completely empty their bladder. Thereafter, 30

mg of dextromethorphan hydrobromide syrup was given orally followed by about 200 mls of

water intake. Three hours following the administration of dextromethorphan, another 5 mls of

blood was collected, immediately centrifuged for 10 minutes (4000 rpm) and plasma were

transferred to separate sterile plasma tubes. Participants’ urine were collected for an 8 hour

period. Each container for the urine collection contained 2 g of ascorbic acid to acidify the urine.

The total urine volume collected was recorded for each participant and 15 mls aliquots were

taken into containers containing 20 mg ascorbic acid. The plasma and urine samples were stored

at -20oC initially for four weeks and later transferred to -80oC freezer until analysis. Samples

were moved into liquid nitrogen for transportation and final storage prior to analyses at the

Central Science Laboratory (CSL) of the Obafemi Awolowo University, Ile-Ife.

The participants were observed for between 15 and 30 minutes after the urine collection to

observe for occurrence of adverse drug reaction before been allowed to go home.

xcii

3.9.1. Analytical methods (Determination of Dextromethorphan/Dextrorphan in

plasma and urine)

Concentrations of dextromethorphan and dextrorphan were determined in the plasma and urine

by a reversed-phase Agilent HPLC with UV detection with some modification of the method of

Zimova et al. (184) Briefly, 1 ml urine with addition of 0.4 ml sodium acetate (0.2 mol per liter)

and 600-1000 units/sample β-glucuronidase incubated in water bath at 37 oC for 18 hours. 1 ml

of the mixture was subjected to extraction: 0.4 ml Na2CO3 (0.5 mol/liter) was added, 0.1 ml of

internal standard (betaxolol). And 4 ml of mixture hexane: n-butanol, 9:1 v/v), 15 minutes

vortex, centrifugation 2200 rpm for 15 minutes. Then, sample were frozen at -20oC, organic

layer was transferred into conical shaped glass tube and water phase extracted once again. Both

organic phases were subjected to re-extraction: 0.3 ml KHSO4 (0.01 mol/liter) was added, 15

minutes vortex, centrifugation 2200 rpm for 15 minutes. Then, samples were frozen at -20oC,

organic layer was discarded. Water phase was used for HPLC analysis (50 ul). Mobile phase

Acetonitrile: KH2PO4 (0.01 mol/liter), 3:2(v/v), trimethylamine (350 µl/l), PH 3.6 (adjusted by

H3PO4 0.1 mol/liter). Flow rate 0.7 ml/min, column temperature 30 oC, column Tessek phenyl

(150x 3mm, 5 µm), detection: fluorescence detector lambda ex 280, lambda em. 310nm.

Standard curves were analyzed in the concentration range of 0.2 to 5µg/ml for dextromethorphan

and dextrorphan. The internal standard (levallorphan tartrate, LP) in a final concentration of

1µg/ml was added before incubation with β-glucuronidase.

3.9.2. Preparation of Standard Solutions and Solvent System

1. Standard solution of dextromethorphan (1000µg/ml)

1.3mg of dextromethorphan hydrobromide powder (1 mg of dextromethorphan base) was

accurately weighed in an Eppendorf tube on an analytical balance and dissolved in

xciii

1 ml of distilled water.

2. Stock solution of Dextrorphan (1000µg/ml)

1.6 mg of Dextrorphan tartrate powder (1 mg Dextrorphan base) was accurately weighed

in an Eppendorf tube on an analytical balance and dissolved in 1 ml of distilled water.

3. Stock solution of Levallorphan (1000 µg/ml):

1.53 mg of Levallorphan tartrate powder (1mg levallorphan base) was accurately

weighed in an Eppendorf tube and dissolved in 1ml distilled water.

4. Another set of stock solutions of 500 µg/ml, 400µg/ml, 200µg/ml, 100 µg/ml, 50µg/ml and

20µg/ml were prepared from the stocks of dextromethorphan and Dextrorphan. A stock of

25µg/ml solution was prepared from the stock solution (1000 ug/ml) of levallorphan.

3.9.3. Calibration Curve for dextromethorphan and Dextrorphan in urine and plasma

Blank urine (1 ml) sample was each placed in six different extraction tubes and varying amount

of the stock solutions of dextromethorphan ad dextrorphan were added to give concentrations of

0.2µg/ml, 0.5µg/ml, 1.0µg/ml, 2.0µg/ml, 4.0µg/ml and 5.0µg/ml for both dextromethorphan and

Dextrorphan.One ml each of the mixture was pipetted into a 10-ml screw-capped, tapered glass

tube to which were added 0.4 ml Na2CO3 (0.5 mol/litre), 20µL of 25µg/ml levallorphan and 4

ml of mixture, hexane: n-butanol, 9:1(v/v). The mixture was vortexed for 5 minutes and

centrifuged at 4000 rpm for 10 minutes. Then, the organic layer was transferred into another 10

ml screw capped extraction tube and re-extracted by addition of 0.3 mls 0.1M HCL, vortexed for

5 minutes and centrifuged at 4000 rpm for 10 minutes. Then, samples were frozen at -20°C,

organic layer was discarded. The water phase was used for HPLC analysis by injection of 20 µl.

For the plasma, the samples were handled in exactly the same way as urine. The peak area ratio

xciv

was plotted against the concentration of each of the compounds injected. The regression analysis

was done with Microsoft Excel Version 2013.

3.9.4. Chromatographic conditions

The composition of the gradient mobile phase was 30% Acetonitrile: 20% Methanol: 0.06%

Triethylamine: 49.94% KH2PO4 (0.01 mol/litre), vol/vol/vol/vol, adjusted to PH of 3.2 by

orthophosphoric acid (0.1 mol/litre). The flow rate was set 1.5ml/min at the ambient

temperature.The wavelength of the Ultraviolet Visible spectrophotometry (UV-VIS) detector

used was 230nm.

3.9.5. Precision studies for Dextromethorphan and dextrophan in plasma

Intra-day run precision: Three sets, each set consisting of six centrifuge tubes, were used. Each

tube in the first set contained 1 ml of plasma sample spiked with the stock solution of the

dextromethorphan and dextrorphan to give concentration of 0.5µg/ml. The second set contained

1 ml of plasma spiked with stock solution of dextromethorphan and dextrorphan to give a

concentration of 2 µg/ml each, while the third set contained 1 ml of plasma spiked with stock

solution of the dextromethorphan and dextrorphan to give a concentration of 5µg/ml. All the

samples were spiked with 20µL of the 25 µg/ml levallorphan. The extraction was done as

described above and 20µL was injected into HPLC. The coefficient of variation of each set was

computed.

Inter-day run precision: This followed as above for intra-day but a sample for each set was

analyzed daily for 3 days.

xcv

3.9.6. Recovery studies for dextromethorphan and dextrorphan from plasma

Three sets, each set consisting of six centrifuge tubes were used. Each tube in the first set

contained 1 ml of blank plasma spiked with the stock solution of dextromethorphan and

dextrorphan to give a concentration of 0.5µg/ml. The second and third contained the same

amount of blank plasma spiked with the stock solution of dextromethorphan and dextrorphan to

give a concentration of 2µg/ml and 5 µg/ml. All the samples were spiked with 20µl of 25 µg/ml

levallophan and then extracted as described above.

In another sets of centrifuge tubes, the stock solutions were diluted in such a way as to obtain

concentration of 0.5µg/ml, 2µg/ml and 5µg/ml for dextromethorphan and dexrorphan. The three

tubes were spiked with 20 µl of the internal standard solution.

In order to determine the recovery, the peak area ratio of the extraction method and direct

injection method were compared.

3.9.7. Determination of dextromethorphan and Dextrorphan in the plasma and urine

Analysis of test urine samples: To 1 ml of urine sample in an extraction tube, 20 µl of the stock

solution (25 µg/ml) of the internal standard was added. Then 0.4 ml sodium acetate (0.2 mol.l-1)

and 0.4 ml of β-glucuronidase (4000 IU) in 0.14 M sodium acetate buffer (PH=5) was added.

The mixture was incubated in a thermostatic box at 37°C for 18 hours. After the incubation, the

mixture was extracted as above and 20 µl was injected onto the HPLC. The same procedure was

repeated for the plasma including the addition of β-glucuronidase.

xcvi

The metabolic ratio (MR) was calculated as the molar concentration of the dextromethorphan

and dextrorphan in a 0-8-hour urine collection, and 3-hour post dose plasma sample. The

metabolic ratios were used to estimate the activity of CYP2D6.

3.9.8. Data Analysis

The statistical analysis was performed using IBM SPSS Statistics for Windows, version 22 and

Microsoft Excel 2013. Data were double entered and cleaned.The socio-demographic variables

were summarized using descriptive statistics (frequency and percentage). The age, height, weight

and Body Mass Index (BMI) were summarized with mean ± standard deviation. The molar

concentration of dextromethorphan and dextrorphan in the plasma and urine samples were

measured and summarized with mean, median, range and standard deviation. The metabolic ratio

of dextromethorphan/dextrorphan (MRDEX/DOR) was calculated by dividing the molar

concentration of dextromethorphan (µg/ml) by the molar concentration of dextrorphan (µg/ml).

The log MRDEX/DOR at 3 hour for plasma and 8-hour for urine were calculated and used as the

index of CYP2D6 activity.

A probit plot of log MR was constructed for plasma and urine, and the anti-mode (cut-off points)

that separated the phenotypes (poor and extensive metabolizers) were obtained from the graph.

The probit plot was constructed with Microsoft excel 2013, with log MR on the X-axis and

probability % on Y-axis on semi-logarithm graph. The probability % was calculated for each

sample (plasma and urine) using the equation: (197)

Probability %, P=100(i-0.5)

T

Where i= rank of the participant log MR (from 1-89) and T=total number of participants (i.e. 89)

Trend lines were added to the probit plot to get the best line of fit. Based on the best line of fit, a

polynomial equation of regression was obtained and intercept at X-axis was considered as the

xcvii

anti-mode. Individuals with log MR greater than the anti-mode were classified as poor

metabolizers (PMs) while those with the log MR that is lower than the anti-mode were classified

as extensive metabolizers (EMs).

Pearson’s correlation was used to compare the quantitative variables (plasma and urinary

metabolic ratios, age, body mass index) while the independent t test was used to compare mean

values in two groups such as male and female, PMs and EMs. The P value was set at <0.05 for

statistical significance.

xcviii

CHAPTER FOUR

RESULTS

4.1. Socio-demographic Characteristics of the 89 participants

One hundred and four (104) accepted the invitation but after preliminary screening including

ancestry, blood relationship and presence of proteinuria, a total of 93 individuals met the

inclusion criteria and were enrolled. Missing samples (3) and/or incomplete urine sample

collection (1) accounted for non-inclusion of the remaining four participants. Of 89 participants

for whom complete data were obtained, 58(65.2%) were males and 31(34.8%) were females. The

mean age of these participants was 36.1±9.5years. The mean weight, height and Body Mass

Index (BMI) were 64±13.4 kg, 1.69±0.1m and 22.4±4.2 kg/m2 respectively. The gender

differences in age, weight, height and BMI are shown in table 4.2. Other socio-demographic

characteristics of the participants are shown in table 4.1. and fiqure 4.1. One participant reported

mild drowsiness one hour post dose but resolved spontaneously without any intervention. It

could not be ascertained if this was due to dextromethorphan or the “unusual environment and

restriction”

xcix

Table 4.1: Frequency distribution of socio-demographic characteristics of 89 participants

Variables Frequency %

Gender

Male

Female

58

31

65.2

34.8

Age (years)

<30

30-39

40+

Mean age = 36.1 years

SD = 9.5

27

29

33

30.3

32.6

37.1

Level of education

None

Primary

Secondary

Tertiary

3

10

20

56

3.3

11.2

22.5

62.9

Marital status

Single

Married

Divorced

Widowed

24

62

1

2

27.0

69.7

1.1

2.2

Occupation

Self employed

Civil servant

Private employment

Artisan

Students

37

14

20

4

14

41.6

15.7

22.5

4.5

15.7

Income

<10000

10000 – 50000

50000 – 100000

100000 – 200000

12

69

7

1

13.5

77.5

7.9

1.1

c

Figure 4.1: Pie chart showing the frequency distribution of the state of origin of the participants

Frequency

Oyo Osun Ogun Kwara Lagos Ondo

ci

Table 4.2: The gender differences in age (years), weight (Kg), Height (meter) and BMI (kg/m2)

of the 89 participants

Variable(mean±SD) Male Female t P

Age 34.8±10 38.5±8.2 -1.8 0.078

Weight 63.9±13.2 64.1±14 -0.1 0.949

Height 1.72±0.1 1.64±0.1 6 <0.0001

BMI 21.6±3.7 23.8±4.7 -2.5 0.014

cii

4.2.Haematological parameter of the 89 participants

Generally, all the haematological parameters of the participants were within normal limits. The

mean packed cell volume (PCV), haemoglobin concentration, total white blood cell count counts

are shown in table 4.3.There was a significant mean difference in the PCV, Hb concentration

and total white blood cell count between male and female( p<0.05).

ciii

Table 4.3: Haematological parameters of the 89 participants

Haematological

parameter

Mean±SD Male(mean±SD) Female(mean±SD t p-value

Packed Cell Volume

(%)

42.1 ±4.2 43.3±3.9 39.8±3.8 4 <0.0001*

Hb(g/dl) 12.7±1.3 13.2±1.1 11.8±1 6.2 <0.0001*

Total White blood

Cell count(x109/L)

4.8±1.3 5.1±1.3 4.3±1.3 3.0 0.004*

Platelet Count

(x109/L)

223 ±63 218±63 231±62 -0.9 0.4

civ

4.3. Biochemical parameters of the 89 participants

The results of plasma urea, creatinine, AST, ALT, total protein and albumin were within normal

limits as shown in Table 4.4.There was significant gender difference in mean value of plasma

urea and creatinine(p<0.05).

cv

Table 4.4: Biochemical parameters of the 89 participants

*statistically significant

Biochemical

parameters

Mean±SD Male(mean±SD) Female(mean±SD) T p-value

Urea(mg/dl) 20.1±10 22.3±11.4 17.5±6.8 2.1 0.04*

Creatinine(mg/dl) 1±0.3 1±0.4 0.9±0.2 2.5 0.016*

ALT(iu/L) 12±5.3 12±5.7 12.2±4.7 -0.24 0.815

AST(iu/L) 20.4±7.5 21±7 19.5±8.5 0.84 0.403

Total

Protein(mg/dl)

7.4±1.3 7.3±1.4 7.5±0.9 -0.73 0.465

Albumin(mg/dl) 3.5±0.6 3.5±0.7 3.6±0.5 -0.37 0.714

cvi

4.4. Analysis of dextromethorphan and Dextrorphan

The typical chromatograms of the blank plasma, plasma spiked with standard solutions of

3µg/ml of dextrorphan, 1µg/ml levallorphan (internal standard), 3µg/ml of dextromethorphan

and the three combined are shown in appendices 4-8. There were no interference from the

endogenous components of the biological fluid. Dextrorphan, levallorphan and

dextromethorphan were distinctly resolved eluting after a retention time of 1.3 minutes, 1.7

minutes and 3.5 minutes respectively. Figure 4.2 shows an example of a chromatogram of a

participant’s plasma sample displaying dextrorphan, internal standard and dextromethorphan.

Figure 4.3 to 4.8 show the calibration curve of the neat, plasma and urine obtained by plotting

the Peak Area Ratio (PAR) of dextromethorphan and levallorphan versus dextromethorphan

concentration, and the PAR of dextrorphan and levallorphan versus dextrorphan concentration.

Linear curves were obtained over a range of 0.2µg/ml to 5µg/ml for the neat, plasma and urine

calibration curves. The correlation coefficient (r) values were over 0.995 for each of the six

standard curves. Data obtained from the validation studies of two different concentrations

(0.5µg/ml and 2µg/ml) are shown in Table 4.5. The coefficient of variation obtained for both the

intra- and inter day runs were less than 6% indicating a good precision of the analytical method.

Table 4.6 shows the results of accuracy and recovery for dextromethorphan and dextrorphan in

the plasma while table 4.7 shows the limit of detection (LOD) and limit of quantitation for

dextromethorphan and dextrorphan.

cvii

Figure 4.2: Chromatogram of plasma sample of one participant showing dextrorphan (1), Internal

standard (2) and dextromethorphan (3)

cviii

Figure 4.3: Neat calibration curve of Dextrorphan

PAR Met=Peak Area Ratio Metabolite (Dextrorphan)

cix

Figure 4.4: Neat calibration curve of dextromethorphan

cx

Figure 4.5: Calibration curve of dextromethorphan in plasma

cxi

Figure 4.6: Calibration curve of dextrorphan in plasma

cxii

Figure 4.7: Calibration curve of dextromethorphan in urine

y = 2.0928x + 1.0222R² = 0.9964

0

2

4

6

8

10

12

14

0 1 2 3 4 5 6

PA

R(D

EXTR

OM

ETH

OR

PH

AN

)

CONC UG/ML

PAR(DEXTROMETHORPHAN)

cxiii

Figure 4.8: Calibration curve of dextrorphan in urine

y = 2.6119x + 0.4355R² = 0.995

0

2

4

6

8

10

12

14

16

0 1 2 3 4 5 6

PA

R(D

EXTR

OR

PH

AN

)

CONC UG/ML

PAR DEXTRORPHAN

cxiv

Table 4.5: Results of Precision for Dextromethorphan and dextrorphan

Sample (N=6) Concentration

(µg/ml)

Coefficient of

variation (%)

Intraday run

Dextromethorphan 0.5 1.3

2 2.5

Dextrorphan 0.5 2.2

2 3.4

Interday run


2 1.7

Dextrorphan 0.5 5.3

2 2.6

cxv

Table 4.6: Results of accuracy and recovery for dextromethorphan and Dextrorphan in plasma

Sample Concentration(µg/ml) % Accuracy± SD %Recovery± SD

Dextromethorphan

0.5 78.2±0.6 78.2±0.4

2 65.7±1.5 65.7± 5

Dextrorphan

0.5 118±1.2 118±0.9

2 84.7±1.0 88.6±7

cxvi

Table 4.7: Limit of detection (LOD) and Limit of quantitation (LOQ) for dextromethorphan and

Dextrorphan

Matrix Drug Limit of

Detection(LOD)

µg/ml

Limit of

Quantitation(LOQ)

µg/ml

Plasma


Dextrorphan 0.20 0.67

Urine


Dextrorphan 0.32 0.98

cxvii

4.5. Dextromethorphan, dextrorphan and MR in urine of 89 participants

The retention time for dextrorphan, levallorphan (internal standard) and dextromethorphan were

1.3, 1.7 and 3.7 minutes respectively. The mean concentration of the dextromethorphan and

dextrorphan in the 8-hour urine were0.75±0.54µg/ml and 1.01±0.51µg/ml respectively. Other

details about the urine concentration of dextromethorphan and dextrorphan are shown in table

4.8.

The median (range) metabolic ratio and logMR in the 8-hour urine were 0.74(0-4.2) and -0.13(-

2.9- 0.6) respectively. There was no statistically significant gender differences in the mean MR

urine (t=1.8, p=0.072). Figure 4.9. shows the histogram of the frequency distribution of the

metabolic ratio of the participants in the 8-hour urine.

The probit plot with best fit trend line of the log MR for 8-hour urine samples (figure 4.10)

intercepts the X axis at 0.28, setting the cut-off between the extensive metabolizers (EM) and

the poor metabolizers (PM) at log 0.28 (anti-mode of 1.91). Two (2.3%) participants with MR

greater than the cut-off were classified as poor metabolizers.

cxviii

Table 4.8: Plasma and urine concentrations of dextromethorphan and dextrorphan in 89

Yoruba Nigerian participants

Variable(ug/ml) Mean±SD Median(range)

8-hour urine dextromethorphan 0.75±0.54 0.74(0.01-2.56)

8- hour urine dextrorphan 1.01±0.51 0.95(0.36-3.9)

3-hour plasma dextromethorphan 3.14±1.78 2.5(0.51-9.0)

3-hour plasma Dextrorphan 1.33±0.79 1.03(0.06-4.22)

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Figure 4.9. Histogram showing the frequency distribution of the log MR in 8-hour urine

cxx

Figure 4.10: Probit plot representation of metabolic ratio (n=89) in 8-hour urine samples

The probit graph plotted using semi log graph of probability percent (probability %) against the

logMR. The trend line best fit line plotted and the log MR when the line crosses the x axis was

chosen as the anti-mode by converting back to MR i.e. the antilog of log MR. The cut-off was

0.28 with anti-mode of 1.91.

y = -28.08x2 - 100.04x + 31.61R² = 0.8376

0.1

1

10

100

1000

-3.5 -3 -2.5 -2 -1.5 -1 -0.5 0 0.5 1

PR

OB

AB

ILIT

Y %

LOG MR URINE

Urine probit plot on semi logarithm graph

cxxi

4.6. Dextromethorphan, dextrorphan and MR in plasma of 89 participants

The mean concentration of dextromethorphan in the 3-hour plasma was 3.4±1.78µg/ml while

that of the dextrorphan was 1.33±0.79µg/ml. Other details about the obtained plasma

concentration of dextromethorphan and dextrorphan are found in table 4.8.

The median (range) of the metabolic ratio of the participants in the 3-hour plasma was 2.36 (1.4-

26.5) while the median log MR was 0.37(0.1-1.4). MR plasma was not significantly different

between genders (p=0.072). Figure 4.11. shows the histogram of the frequency distribution of

the log MR of the 3-hour plasma samples. As shown in probit plot in figure 4.12, the log MR that

separated the extensive metabolizers from poor metabolizers was 0.75 and the anti-mode was

5.6. Two participants (2.3%) whose MR were greater than the anti-mode were classified as poor

metabolizers.

cxxii

Figure 4.11.Histogram showing the frequency distribution of the log MR in 3-hour plasma.

cxxiii

Figure 4.11: Probit plot representation of metabolic ratio (n=89) in 3-hour urine samples

The probit graph plotted using semi log graph of probability percent (probability %) against the

logMR. The trend line best fit line plotted and the log MR when the line crosses the x axis was

chosen as the anti-mode by converting back to MR i.e. the antilog of log MR. As shown above,

the cut-off was 0.75corresponding to MR of 5.6.

y = -139.55x + 104.21R² = 0.7002

0.10

1.00

10.00

100.00

0.00 0.20 0.40 0.60 0.80 1.00 1.20 1.40 1.60

PR

OB

AB

ILIT

Y %

LOG MR PLASMA

Plasma probit plot on semilogarithm graph

cxxiv

4.7. Comparison of the plasma and urine metabolic ratio of dextromethorphan/dextrorphan

in the determination of CYP2D6 phenotype

Two participants (2.3%) were classified as poor metabolizers by both the 8-hour urine (0.28) and

3-hour plasma (0.75) metabolic ratio of dextromethorphan and dextrorphan. The metabolic ratio

of one of the PMs was 26.11 in the plasma. The two PMs identified were male, but there was no

statistically significant relationship between gender and phenotype (p=0.541). There was strong

positive correlation between 8-hour urinary and 3-hour plasma metabolic ratios [r=0.772,

p<0.01, CI (0.22, 0.891)] but no significant correlation between age, body mass index and

metabolic ratios as shown in table 4.9

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Table 4.9: Correlation of the 8-hour urine MR, 3-hour plasma MRs, age and body mass index

Variable Age(years)

BMI(kg/m2)

Urine MR Plasma MR

Urine MR r(p-value)

0.14(0.188)

-0.09(0.43) 1 0.772(<0.0001)*

Plasma MR r(p-value)

0.09(0.359)

-0.04(0.622)

0.772(<0.0001)* 1

*Statistical significant

cxxvi

4.8.The sociodemographic characteristics of identified PMs and EMs

The two identified PMs were both males and from Osun State (Ila-Orangun and Iree). The

median (range) plasma MR for the PMs was 17(7.5-26.5) while the median (range) plasma MR

for the EMs was 2.4(1.4-4.9). There was statistically significant mean difference between the

plasma MR of PMs and EMs (t = -12.6, p<0.0001). The median (range) urine MR for the PMs

was 3.2(2.2-4.2) while that of the EMs was 0.7(0-1.8). There was statistically significant mean

difference between the urine MR of PMs and EMs (t = -8.9 p<0.0001). Other socio-

demographics of the identified PMs and EMs are shown in table 4.10.

cxxvii

Table 4.10: Some Socio-demographics of the identified PMs and EMs

Variable PMs EMs T P-value 95%

Confidence

Interval

Age(years)

(mean ± SD)

27±2.8 36.3±9.5 1.374 0.173 (-4.15, 22.75)

BMI(Kg/m2)

(mean ± SD)

19.6±1.4 22.4±4.2 0.949 0.345 (-3.1, 8.8)

MR Plasma

(mean ± SD)

17±13.4 2.5±0.7 -12.631 <0.0001* (-12.3, -16.9)

MR Urine

(mean ± SD)

3.2±1.4 0.7±0.4 -8.868 <0.0001* (-19.2, -3.04)

cxxviii

CHAPTER FIVE

DISCUSSION

5.1. Discussion

In this study, dextromethorphan O-demethylation polymorphism was studied among unrelated

89 healthy volunteers of Yoruba ethnic origin in Nigeria using both 8-hour urinary and 3-hour

post dosing plasma samples. The study only enrolled individuals whose grandparents were of

Yoruba extraction, an attempt to ensure that all the participants were of the same ancestry. (189)

Studies based on specific ethnic nationalities in Nigeria are rare but few studies on CYP2D6

phenotype, particularly using urine MR have been reported. (8)

The study involved mostly young adult males and females in line with standard practice and in

recognition of potential influence of age on the rate and extent metabolism. Within the age range

of the participants there was a lack of correlation between age and the metabolic ratios of the

participants. This is not unexpected because of the exclusion of the elderly individuals. It is also

noteworthy that the two poor metabolizers that were identified were aged 25 and 27 years. The

age range in this study was similar to previous studies aiming at determining the CYP2D6

phenotype. (8, 18, 186, 198).

Relevant cutoff(s) may be obtained by subjecting data to a probit analysis or Receiver Operating

Characteristics (ROC) or other similar statistical analysis. (169, 170, 194) On the other hand

extrapolations from similar studies may inform the cutoff. (160, 176, 199, 200) The former

option was chosen in this case for, at least, two reasons: 1.There is no immediate record of an

identical study, that is, determination of CYP2D6 phenotype in the Yoruba Nigerians. Secondly,

use of plasma for the purpose is evolving and has not been previously investigated in Nigeria

cxxix

before now. Further, some researchers have argued against the use a “universal” cutoff as it may

be misleading.(169, 201) It is also noteworthy that very few studies have used DEX in Nigerians

in the past.(8) A close look at the histogram reveals the bimodal distribution and same was

reinforced by the probit plot similar to Gogtay et al. in India (194) and Othman et al in

Yemen.(201) There is no doubting the fact that large sample size would enhance deductions of

histogram and probit plots.

The choice of DEX has gained ground recently for a number reasons including good safety

profile. Only one patient indicated mild transient drowsiness which reinforces the foregoing.

Previous studies in Nigeria and abroad have recorded similar good tolerance.(8, 153, 169, 194)

The use of saliva as an alternative to plasma/serum, requires higher dose of dextromethorphan,

which may increase the likelihood of adverse drug reactions, is needed for phenotyping using

saliva. (200, 202)

There were some challenges with the assay of DEX and DOR, particularly for resource-poor

countries where sophisticated analytic facilities may be lacking. Indeed, most well-resourced

facilities use the LC-MS/MS or HPLC with fluorescent detection as the HPLC with UV

detection is not well suited for dextromethorphan and dextrorphan. However, the method

described by Zimova et al with modification (184) was found to be adequate at present time. The

lower limit of quantitation and detection would not have been perfectly representative in this

study, however, it is thought that both the parent drug and the major metabolite, dextrorphan,

would be equally affected, thus the same relative concentrations may be maintained. Further

studies would be necessary to address this, perhaps, same samples should be subjected to the

various analytical techniques.

cxxx

Hitherto, a 24-hour urine collection was required for the determination of MR. However, recent

studies that used 8-hour urinary assay have been established as an effective option. (169, 171) In

addition, a single 3 hour plasma sample have equally been found useful alternative. This study

employed both options and found a clear correlation. Both the plasma and the urinary

DEM/DOR identified two (2.3%) individuals with poor metabolic phenotype. Should these

findings be replicated in similar and larger studies it may be possible to avoid keeping patients

for long hours for a prolonged urine collections which is fraught with some challenges including

incomplete sample collection and inconvenience to subjects. The inference of 2.3% PMs from

this study is similar to the reported prevalence of PM phenotype among black Africans (8, 15,

141, 142)

For emphasis, plasma matrix for phenotyping with dextromethorphan have been found to be

accurate, convenient and more rapid than the standard urine approach. Besides, varying

glucuronidation, preferential accumulation of metabolites due to impaired renal function and

variability in metabolic ratio due to urinary PH are prevented in 3-hour post dose plasma

sample,(203) and it has been found to correlate well with the much validated urinary metabolic

ratio.(169, 200)

CYP2D6 poor metabolizers in this study is similar to previous studies in Nigeria and other

African countries. Iyun et al obtained a prevalence of less than one percent among heterogeneous

population using debrisoquine and metoprolol urinary metabolic ratio.(204) A prevalence of

3.5% poor metabolizers with urinary dextromethorphan/dextrorphan metabolic ratio among

heterogeneous Nigerians was obtained by Ebeshi et al.(8) Other studies in African also showed a

poor metabolizers prevalence of 1.2% in South Africa, (198) 1-4% in other African countries,

(14-16, 141) and 1-4% in Asian countries.(7, 11, 194) However, poor metabolizers’ phenotype in

cxxxi

this study is lower than that of African American (ranges between 5.3% and 7.7%)(128, 205,

206) and Caucasians (7-10%). (10, 169) Also, there is strong positive correlation between the

urine and plasma metabolic ratios at determining the CYP2D6 phenotypes, similar to findings

from other studies. (169, 178, 181)

The clinical implications of poor metabolisers include slow drug metabolism with potential for

drug-drug interactions and adverse drug reactions. Besides, there may be slower conversion of

pro drug to active metabolites with potential lower efficacy.(207, 208) As a result, dose

adjustment or alternate drugs have been recommended for poor metabolisers by Clinical

Pharmacogenetics Implementation Consortium (CPIC) dosing guidelines and Dutch

Pharmacogenetics Working Group (DPWG) for drugs like paroxetine, amitriptyline, risperidone,

codeine, tramadol and tamoxifen.(47, 103, 115, 117, 209) Consequently, the use of these

commonly prescribed drugs among Yoruba, Nigerian can be guided by CYP2D6 phenotyping

with dextromethorphan using 3-hour post dose plasma sample, which can be done routinely in

the hospital.

cxxxii

5.2 Limitations

1. The use of Ultraviolet detector and C-18 column as against the fluorescence detector and

phenyl column or LC/MS –MS with higher sensitivity and analyte recovery.

2. A larger sample size might also allow for the identification of phenotypes that are present

in the population but rare.

3. The study was conducted among healthy individuals and the applications in the general

population may be limited because of the concomitant drugs and disease states that may

contraindicate or have interaction with dextromethorphan.

4. The samples were stored in optimum temperature but for long period before the analysis.

This might have affected the recoveries of the dextromethorphan and Dextrorphan.

cxxxiii

CHAPTER SIX

CONCLUSION AND RECOMMENDATIONS

6.1. Conclusion

The study recorded a poor metabolizer phenotype of 2.3% among the 89 Yoruba ethnic

Nigerians studied. The 8-hour urinary and 3-hour post dose plasma metabolic ratio of

dextromethorphan/dextrorphan were able to differentiate between poor and extensive

metabolizers, and there was strong positive correlation between urine and plasma metabolic

ratio.

cxxxiv

6.2.Recommendations

1. There is need for further studies with larger sample populations with more sensitive

analytical methods.

2. Independent validation of the plasma metabolic ratio should be determined before its

wide use.

3. Suggests clinical trial randomizing patients to prescribing using CYP2D6 phenotyping

and traditional methods of prescribing.

4. Needs for CYP2D6 genotyping for phenotyping-genotyping matching.

5. Despite the above some patients will benefits from CYP2D6 phenotyping especially for

substrate of CYP2D6 with narrow therapeutic index.

cxxxv

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APPENDICES

Appendix 1: UI/UCH Ethical approval for the study

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Appendix 2: National Postgraduate Medical College of Nigeria registration of title of

dissertation

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Appendix 3: INFORMED CONSENT

Title of the research: Evaluation of CYP2D6 Phenotypes in a Nigerian Population.

Name(s) and affiliation(s) of researcher(s): This study is being conducted by Dr. W.A. Adedeji

of Clinical Pharmacology Department, University College Hospital, Ibadan.

Purpose of Research: This study is being carried out to determine how a particular enzyme; the

CYP2D6 enzymes in your body break down dextromethorphan. This will allow us to know its

effectiveness in breaking down drugs that it normally acts on in your body. It is going to involve

only healthy participants. All our participants will be unrelated Yoruba from Nigerian. It is

hoped that findings from this study will help in knowing CYP2D6 phenotype and its

effectiveness in breaking down drugs. This will help us in reducing the drugs of those whose

enzyme function is low and to increase the dose of the drugs in those whose enzyme are working

too fast. This will reduce the occurrence of adverse drug reactions and improve good response

following treatment. .

Procedure of Research: If you agree to take part in this study, you will be asked to fast

overnight (that is stop eating from 10 pm the night before the test) and come to the UCH in the

morning by 7:30 am. You will be examined, and your weight will be measured, thereafter you

will be asked to pass all the urine in your bladder as much as you can and about 10 mls of blood

will be collected from your arm for CYP2D6 genotyping and laboratory tests .You will then be

given 30 mg of dextromethorphan orally. We will be collecting your urine inside a container for

8 hours. And about 5 mls of blood will be collected from your arm 3 hours after taking the drug

and you will be allowed to eat after 2 hours. You will not be allowed to go out for about 8 hours.

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Expected Duration of Research and of Participant(s)’ involvement: The study is expected to

be conducted over a period of 3 months; however you will only be requested to partake once and

it will take you about 8 hours during which time you will not be allowed to go out.

Risk(s): About 10 to 15 mls of blood will be collected from forearm with needle and syringe by

expert under a clean environment and conditions. It will cause little pain from needle pricking.

To ensure bleeding and infection from the site, we will ensure that the sample are collected by

expert and avoidance of multiple pricking as much as possible, and make sure that bleeding stop

before pressure is removed from pricking site. Also cleaning of the site with methylated spirit

before pricking will also prevent infection transmission. Besides, we will avoid reusing of needle

and syringe and no two participants will use the same needle and syringe.

Urine collection will not cause any pain apart from the discomfort of passing the urine inside a

container for 8 hours.

To ensure that you are comfortable, we will not use our general wards and the venue will be

conducive and your privacy is guaranty.

The drug (dextromethorphan hydrobromide syrup) that you will be given has been validated to

be a good and safe drug for the study. Also the dose is small and is not likely to lead to adverse

drug reaction.

However, dizziness, lightheadedness, drowsiness, nervousness, restlessness, nausea, vomiting

and stomach pain can occur. To prevent this, if you have reacted to the drug before, you will not

be allowed to participate in the study. And for any reaction that occur during the study, the

participants will be treated properly by experts.

Benefit(s): This will assist doctors in selecting appropriate dose of drugs that will be effective in

treating patients while avoiding adverse drug reactions and failure of the medication. This will

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lead to individualization of drug therapy and reduction in morbidity and mortality associated

with hypertension and other non-communicable diseases.

This will provide a valuable pharmacogenetics data for Nigerian, and a good data base for

Africa and the world as a whole.

Confidentiality: All the information collected from this study will be coded. This cannot be

linked to you in any way and your name or identifier will not be in any publication or reports

from this study. As part of our responsibility to conduct this research properly, officials from

UI/UCH IRC on ethics may have access to these records. However, data obtained from this study

may be used for publication in local or international journals as well as presentations at

conferences.

Consequences of participants’ decision to withdraw from research and procedure for

orderly termination of participation: You can also choose to withdraw from the research at

any time. Please note that some of the information that has been obtained about you before you

chose to withdraw may have been modified or used in reports and publications. These cannot be

removed anymore. However, the researcher promises to make good faith and effort to comply

with your wishes as much as practicable.

Statement of person obtaining informed consent:

I have fully explained this research to-----------------------------------------------------------------------

--------------and have given sufficient information, including about risks and benefits, to make an

informed decision.

DATE: _________________________ SIGNATURE_____________________

NAME: __________________________________________________________

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Statement of person giving consent:

I have read the description of the research or have had it translated into language I understand. I

have also talked it over with the doctor to my satisfaction. I understand that my participation is

voluntary. I know enough about the purpose, methods, risks and benefits of the research study to

judge that I want to take part in it. I understand that I may freely stop being part of this study at

any time. I have received a copy of this consent form and additional information sheet to keep

for myself.

DATE: _________________________ SIGNATURE: _______________________________

NAME: __________________________________________________________

WITNESS’ SIGNATURE (if applicable): ______________________________________

WITNESS’ NAME (if applicable): _______________________________________________

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Appendix 4: Chromatogram of blank plasma

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Appendix 5: Chromatogram of plasma spiked with 3µg/ml of Dextrorphan

1. Peak present in blank plasma 2: Dextrorphan

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Appendix 6: Chromatogram of plasma spiked with standard solution of 1µg/ml of Levallorphan

(internal standard), retention time 1.7 min

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Appendix 7: Chromatogram of plasma spiked with standard solution of 3µg/ml of

dextromethorphan (1)

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Appendix 8: Chromatogram of plasma spiked with standard solution of 3µg/ml of Dextrorphan,

and dextromethorphan, and 1 µg/ml of levallorphan

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Appendix 9: QUESTIONNAIRE

EVALUATION OF CYP2D6 PHENOTYPE WITH DEXTROMETHORPHAN IN

A YORUBA NIGERIAN POPULATION

Serial Number.............. Initials................ Phone No....................................

Date of Recruitment……………………………. IRB number: ……………..

SECTION A

(1) Age ..................(last birthday) Date of Birth ---------------------------------

(2) Gender (1) Male (2) Female

(3) Place of Birth ......................................................................

(4) Local Government Area..............................................................

(5) State of Origin........................................................................

(6) Nationality...............................................................................

(7) Ethnicity (1) Hausa (2) Igbo (3) Yoruba (4) Others (Specify)...................

(8) What is the home town of your father? ...................................................

(9) What is the name of your mother home town? ----------------------------------------------

(10) Marital Status (1) Single( 2) married(3)Divorced (4) Widow (5) Separated

(11) Level of educational (1) Nil (2) Some primary (3)Primary(4) Some secondary

(5) Completed secondary (5) Tertiary or Post-secondary

(12) Occupation (specify) ---------------------------------------------

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SECTION B

MEDICAL HISTORY

(13) Are you currently being treated for any ailment? (1)Yes (2) No

(14) If yes, specify -----------------------------------------------------------------

DRUG HISTORY

(15) Are you on any routine medication? (1) Yes (2) No

(16) If yes, please specify _______________________________List the drugs you are

taking. .................................................................... ..

(17) Do you take herbal medications? (1) Yes (2) No

(18) If yes, please provide details

________________________________________________________________________

_________________________________________________________

(19) Have you ever adversely reacted to any drug in the past? (1) Yes (2) No

(20) If yes, please, provide details --------------------------------------------------

SOCIAL HISTORY

(21) Do you take alcohol? (1) Yes (2) No

(22) If yes, give details ____________________________

(a) What type (1) Beer (2) Liquor (3) Local brew (4) All of the above

(b) Duration of alcohol intake ---------------------------------------------------------

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(23) Ever smoked cigarette? (1)Yes (2) No

If yes, quantify and provide duration ---------------------------------------------------------------

(a) Duration of Smoking -------------------------------------------------

(b) Number of sticks per day --------------------------------------------

(24) History of substance abuse (1) Heroine (2) Cocaine (3) Marijuana (4)

others (specify) --------------------------------------------------------------------------------

SECTION 1 C

CLINICAL PARAMETERS

PHYSICAL FINDINGS

1) Weight (Kg) --------------------------------

2) Height (m) ----------------------------------

a. BMI (Kg/m2) -------------------------

3) Temperature (O C) --------------------------

4) Purse Rate -----------------------------------

5) Blood Pressure: -----------------------------

INVESTIGATIONS

(1)Urine Dipsticks:

(a) Proteinuria:

(1) Positive (2) Negative

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(b) Urine PH ---------------------------

(c) Glycosuria --------------------------------

(d)Others (specify) -----------------------------------------

(3) Electrolyte, urea and Creatinine

(a) Creatinine (mg/dl) ------------------ (b) Urea (mg/dl) -----------------

(c)Sodium ------------------ (d) Potassium--------------- (e) Chloride ---------

-- (f) Bicarbonate -----------------------------

(5) Liver Function Test (a) AST ---------------------- (b) ALT -----------------------------

(c) ALP-------------------------- (d) Total Protein ------------------- (i)

Albumin------------------------- (ii) Globulin

(e) Total bilirubin -------------------------- (i) Conjugated -----------------

(6) Full blood Count (a) Packed Cell Volume ------------------------------------

(b) Total White Blood Cell Count -----------------------------------

(c)Platelet Count ----------------------------------------------------

(7) ECG findings ----------------------------------------------------------------------------

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SECTION D

RESEARCH FINDINGS

Phenotype:

Drug(Urine) 0 hour 8 hours

Dextromethorphan

Dextrorphan

Dextromethorphan/Dextrorphan

Drug(plasma) 0 hour 3 hours

Dextromethorphan

Dextrorphan

Dextromethorphan/Dextrophan

EVALUATION OF CYP2D6 PHENOTYPE IN A YORUBA NIGERIAN …

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