Preface

The inspiration for this volume emerged from a combination of the completion of the Human Genome Project and advances in cellular and molecular medicine. Together these disciplines have established the basis for a new wave of translational research where the aim is for advances in basic science to impact directly on improved clinical outcomes. Although medical pathology has historically been divided into subsets dependent on the organ system involved and disease aetiologies, it is becoming increasingly evident that diagnoses and treatment of disease, whether acquired or heritable, should additionally be based on the detailed knowledge of epidemiology and genetics, lifestyle, molecular and cellular pathology. The objective of the book is to provide an exciting insight into advances in key areas of molecular and cellular aspects of applied medical research. Based on a series of authoritative chapters that provide opinion and data across a broad field of medicine, the aim is to enable the reader to acquire a usable platform of knowledge sufficient, for example, to gain access to the specialist literature.

The first two chapters address molecular aspects of pharmacogenetics and biomarkers.

The opening chapter from Imtiaz Shah and colleagues describes some of the potential practical outputs of the Human Genome Project. Person to person variability in response to drugs has long been recognized and the authors summarize the recent research finding on genotype testing in relationship to variability in drug response with reference to the CYP genes. Continuing with the theme of molecular analysis in relation to physiological states, Debmalya Barh and colleagues reviews the field of biomarkers. These substances which can indicate disease states and treatment outcomes are of increasing importance in medicine. The chapter provides an introductory review of biomarkers in general whilst focusing on cancer related molecular markers, their classification, detection approaches and applications. Chapters 3 and 4 review aspects of cancer therapy. In Chapter 3, Noor Al-Dasooqi and colleagues focus on HER2 targeted therapy and the role of HER2 in cancer. The central theme addresses the gastrointestinal toxicities associated with commonly used HER2 targeted therapy drugs and the possible underlying mechanisms. Although drugs that target HER2 and other EGF receptors have proved to be effective in managing a range of cancers, toxic side effects remain a significant problem. In Chapter 4, Mahendra Deonarain and colleagues sustain the theme of cancer therapy with a review of photodynamic therapy (PDT). The complexity of PDT targeting, lack of potency and side effects have limited the technology and restricted its general usage by oncologists. The problem of targeting disease cells is addressed and the translational research harnessing monoclonal antibodies and antibody fragments is described.

In Chapter 3 Kazuhiro Ito and Nicolas Mercado review the free-radical theory of ageing in relation to inflammatory disease. The most ageing-associated disease is recognized as chronic inflammatory disease where oxidative stress is likely to contribute to the inflammation. The authors describe the analysis of oxidative stress reduced anti-ageing molecules such as those that are involved in epigenetic control of pro-inflammatory gene expression and control of protein function.

The next two chapters are focused on RNAi, which is widely acknowledged as a potential basis for powerful new therapies. Sunit Singh and Praveensingh Hajeri (Chapter 6) provide a sterling review of the topic. Whilst the techniques have proven potential for providing therapeutic solutions, the authors do not shy from highlighting the hurdles to be overcome in designing strategies for knocking down specific gene expression. In Chapter 7 Hermann Lage and colleagues review the development and potential applications for Transkingdom RNAi (TkRNAi). The tkRNAi approach described represents a new strategy for delivery of RNAi effectors, in particular for the treatment of bowel disease.

There follow two chapters on key areas of current medical research, stem cells and gene therapy. In Chapter 8 Ian Phillips and colleagues comprehensively review the history of stem cell biology and the current advances. The chapter addresses the key questions that need to be answered before new human stem cell therapies can be used routinely, including the choice of stem cells, the ease of preparing, storage and delivery of stem cells, and the effectiveness of the therapies. In Chapter 9 Thomas Ritter and Matthew Griffin tackle gene therapy. Whilst gene therapy technologies have been successfully applied in many preclinical models for the treatment of various diseases – including the prevention of allogeneic organ graft rejection – mainly for safety reasons the translation into the clinic has lagged behind. The authors examine the role that gene therapy and gene transfer technologies may play in the successful application of new strategies to improve the success rates and long-term, immunosuppression-free survival of organ allografts.

In Chapters 10 and 11 advances in the two most common neurodegenerative diseases are presented. Neurodegenerative disease, in particular Alzheimer's disease, is an area where the burden of disease cost is set to increase significantly over the next 50 years. First Michael Rafii discusses promising new treatments for Alzheimer's disease, the most common form of progressive dementia in older people. The major therapeutic strategies are reviewed as are the complexities of dealing with such a heterogeneous condition. In Chapter 11 Tiago Outeiro and colleagues review current and new therapeutic approaches to Parkinson's disease, the second most common neurodegenerative disease that is estimated to affect some 2% of the world population aged over 65.

A vital facet of twentyfirst century medicine is the control of infectious diseases. The last two chapters deal with approaches to bacterial infection and vaccine development. In Chapter 12 Joanne Fothergill and Craig Winstanley address the challenges for the development of new drugs in the face of increasing incidence of antibacterial resistance. In addition to traditional strategies to drug discovery, approaches based on genomic information are addressed. The authors provide a snapshot of some of the approaches being taken to the identification of new therapeutic targets that might enable development of new and better strategies to combat infections in a post-antibiotic era. Niall McMullan (Chapter 13) reviews advances in vaccine development. The last 30 years has seen promising developments in vaccinology. The integration of reverse genetics approaches and reverse vaccinology offer the prospect of rapid methods for developing new vaccines. Recent successes with these new strategies in human clinical trials and the licensing of new animal vaccines offer real hope for major breakthroughs in the control of infectious diseases.

There can be no doubt that therapeutic and diagnostic strategies and approaches that have emerged since the completion of the Human Genome Project have been both wide ranging and highly focused. The notion of ‘bench to bedside’ which is underpinned by the outputs of translational research has gathered momentum and credibility as evidenced by the contents of the chapters presented.

David Whitehouse and Ralph Rapley

1

Cytochrome P450 pharmacogenetics: from bench to bedside

Imtiaz M. Shah, Catherine J. Breslin and Simon P. Mackay

1.1 Introduction

With the elucidation of the human genome sequence over the past decade, pharmacogenetics has evolved into an important area of translational medicine research (International Human Genome Sequencing Consortium, 2004; Grant and Hakonarson, 2007; Shurin and Nabel, 2008). Most patient populations display interindividual variability to drug response and efficacy, with genetic factors accounting for up to 30% in these differences (Evans and McLeod, 2003). Mutations within the genetic DNA sequence (genetic polymorphism) can alter the transcribed mRNA structure and subsequent protein function. This altered genotype expression can result in variability in drug activity (O’Shaughnessy, 2006). Pharmacogenetics is the study of such genetic factors and its effects on drug response. The most common genetic polymorphism is a single nucleotide polymorphism (SNP). This results in a single nucleotide substitution within the DNA structure and accounts for 90% of human genetic variation (Eichler et al., 2007; McCarroll et al., 2006). SNPs are associated with variability in drug response between different patient populations and are an important basis for pharmacogenomics research (Twyman, 2004). This variability in patient genetic profiles can lead to potential risks of drug toxicity or treatment failure (Hoffman, 2007). Current pharmacogenetics research is focusing on patient genotype testing and utilizing this genetic information to provide more ‘personalized’ drug therapy in clinical practice (Feero, Guttmacher and Collins, 2010; Hoffman, 2007).

1.1.1 The Human Genome Project

The Human Genome Project (HGP) has made a crucial contribution to research advances in the rapidly evolving areas of pharmacogenetics and translational medicine. This major international scientific collaboration, which was completed in 2003, has elucidated the complete DNA sequence of the human genome (International Human Genome Sequencing Consortium, 2004). The results of this project have started to provide important genotype–phenotype correlations from genome wide association studies (GWAS), and will potentially lead to major advances in drug development and translational research (The Wellcome Trust Case Control Consortium, 2007; Chung et al., 2010). The HGP is being followed on by the larger 1000 Genomes Project, which will allow more detailed genetic analysis of different ethnic populations (Gamazon et al., 2009).

The HGP analysis commenced in 1995 with the aim of sequencing three billion base pairs (bps) of DNA. The sequencing strategy involved subcloning the human genome into bacterial artificial chromosomes, which were then sequenced (shotgun method) and correctly aligned (Lander et al., 2001). Once the initial sequence was determined, advanced computational algorithms were used to generate a final sequence map. The genome was sequenced five times to minimize any errors. The main findings from the HGP have shown that humans have between 20 000 and 25 000 genes (International Human Genome Sequencing Consortium, 2004). The average human gene spans between 27 000 and 29 000 bases of DNA and consists of four to six exons. The main coding sequence is approximately 1340 bps. Genes are not evenly distributed throughout the genome, with some chromosomes containing more genetic information (chromosomes 1, 2, 11) than others (chromosomes 13, 18, 21).

The relatively small number of genes is not indicative of a similarly small number of proteins. Genes can undergo alternative splicing, thereby increasing the number of different protein products (Barash et al., 2010; Tress et al., 2007). RNA studies have shown that there may be an average of three different transcripts from one gene. The HGP has also identified approximately two million SNPs, which has allowed genetic linkage studies and location of specific diseases to their chromosome loci (Sachidanandam et al., 2001). GWAS and SNP analysis have now started to elucidate genetic associations with common clinical diseases (The Wellcome Trust Case Control Consortium, 2007; Chung et al., 2010). These genomic studies will potentially lead to the identification of new protein targets for drug discovery and play an important role in translational medicine research (Hopkins and Groom, 2002; Schilsky, 2010).

1.2 Cytochrome P450 pharmacogenetics

Genetic polymorphisms and variation in protein structure expression can result in altered drug–protein interactions and affect subsequent drug response. There are three main pharmacogenetic mechanisms that can influence drug activity. These molecular changes can result in genetic polymorphisms affecting the drug metabolizing enzymes (DMEs), drug transporter proteins and the drug receptors. This can result in altered pharmacokinetic properties (metabolism and transport) or pharmacodynamic properties (action) of the drug.

The most widely studied group of proteins displaying pharmacogenetic variability are the DMEs and specifically the cytochrome P450 enzymes (CYP) (Sim and Ingelman-Sundberg, 2010). These enzymes are involved in phase I biotransformation reactions, which mainly result in drug substrate oxidation. Genetic polymorphism affecting the CYP enzymes can result in altered drug metabolism and efficacy (Ingelman-Sundberg and Sim, 2010; Tomalik-Scharte et al., 2008). Cytochrome P450 2D6 (CYP2D6), CYP2C9 and CYP2C19 have been the most extensively studied metabolic enzymes (Zhou, Liu and Chowbay, 2009). The following sections will discuss these CYP enzymes in more detail and provide clinical examples of commonly used drugs displaying pharmacogenetic variability.

1.2.1 CYP2D6 pharmacogenetics

CYP2D6 functions as a mono-oxygenase enzyme and is predominantly found within the liver. It metabolizes up to 30% of commonly used medications and important drug classes include antidepressants, beta-blockers and analgesics. The drug substrates are mainly lipophilic bases with a protonable nitrogen atom and an aromatic ring (Costache et al., 2007). The approval of CYP2D6 genotype testing by the FDA in 2005 has put this enzyme at the forefront of research into personalized medicine (Frueh et al., 2008; Sun and Scott, 2010).

The CYP2D6 enzyme is a 497 amino acid protein (55.8 kDa) and contains a haem group (Protein Data Bank ID: 2F9Q) (Rowland et al., 2006). The gene encoding CYP2D6 is located on chromosome 22. CYP2D6 has a well-defined active site structure, which is located above the haem group. The amino acid residues that have been implicated in substrate recognition and binding are Asp301, Glu216, Phe483 and Phe120 (Rowland et al., 2006). The main enzyme action is drug substrate oxidation, via electron transfer and substrate interaction with a dioxygen–ferrous complex. The catalysis involves the insertion of one oxygen atom into the substrate molecule and the second oxygen atom is converted into water. There are also alternative CYP enzyme mechanisms which result in substrate N- and O-demethylation reactions.

CYP2D6 displays extensive genetic polymorphism that influences enzyme expression and function. More than 100 allelic variants of the CYP2D6 gene have now been identified (www.cypalleles.ki.se/cyp2d6.htm). The enzyme genetic polymorphism and metabolic activity also shows ethnogeographic variation, with differences between Caucasian, Oriental and Afro-Caribbean populations (Ingelman-Sundberg, 2005). The three major allelic variants, which are found in the Caucasian population are CYP2D6*3, CYP2D6*4 and CYP2D6*5 (Table 1.1). All three variants are associated with poor metabolizer (PM) phenotypes, with CYP2D6*4 being the most frequent allele (∼20%) (Lee et al., 2006; Mizutani, 2003). The CYP2D6*10 allele is the most commonly found allelic variant in the Oriental population and this enzyme displays an intermediate metabolizer (IM) phenotype (Lee et al., 2006). This allele results in the production of an unstable enzyme caused by a double amino acid substitution (P34S, S486T) (Shen et al., 2007). The most commonly found allele in the African population is CYP2D6*17 (Dandara et al., 2001). It is also associated with an IM phenotype, resulting in reduced catalytic activity caused by a triple amino acid substitution (T107I, R296C, S486T) (Shen et al., 2007). The ultra-rapid metabolizer (UM) phenotype is associated with CYP2D6 gene multiplication and enzyme over-expression. This has been most commonly associated with the Ethiopian and Middle Eastern populations, with 15–30% allelic frequency (Aklillu et al., 1996; McLellan et al., 1997). Due to this extensive genetic polymorphism displayed by CYP2D6, the role of genotype and phenotype testing for this enzyme has become an important area of research into personalized medicine and pharmacogenomics (de Leon, Armstrong and Cozza, 2006).

Table 1.1 Common allelic variants of CYP2D6#

In 2005, the FDA approved one of the first CYP2D6 genotype tests (AmpliChipCYP450) for clinical use (de Leon et al., 2009). The introduction of this genotype test has been a major step towards introducing personalized medicine into the clinical setting. The CYP AmpliChip test involves the identification of a defined genetic mutation in the CYP2D6 and CYP2C19 gene, which is associated with a specific drug metabolism phenotype. The test screens for susceptible patient genotypes and will potentially allow tailoring of drug therapy in an attempt to reduce adverse drug reactions (ADRs) or avoid treatment failure (de Leon, Armstrong and Cozza, 2006). An example in the use of this test has been to optimize drug therapy in patients taking antidepressant and antipsychotic medication (de Leon et al., 2009). The AmpliChip CYP450 test is based on microarray technology. These DNA microarrays, also known as DNA chips, allow multiple gene expression analysis. This consists of DNA oligonucleotides embedded onto tiny glass chips, which allow detection and analysis of the different gene variants. Patient DNA can be extracted from blood or saliva samples, which is analysed via polymerase chain reaction (PCR) amplification. The PCR products are then applied to the microarray chip, which allows binding of complementary base pairs between the patient DNA sample and the microarray (hybridization). A laser scanner is then used to read the result, providing the physician with information on the patient's CYP2D6 genotype status. The AmpliChip test has been validated against in vivo studies using CYP2D6 probe drugs and it shows good correlation in detecting the different enzyme phenotypes (Heller et al., 2006). Newer PCR and microarray technologies are continuing to be developed for CYP genotyping (Deeken, 2009).

Clinical studies have demonstrated a potential increased risk of ADRs or treatment failure associated with different CYP2D6 allelic variants (Ingelman-Sundberg, 2005; Zhou, 2009). Most clinical studies have investigated the effect of CYP2D6 genetic polymorphism in psychiatric patients taking antidepressant and antipsychotic medication (de Leon, Armstrong and Cozza, 2006). Larger pharmacogenetic clinical studies are ongoing, into evaluating the role of genotype testing in psychiatric patients (Kirchheiner and Rodriguez-Antona, 2009; Uher et al., 2009). Recent interest in CYP2D6 pharmacogenetic variability has been focusing on analgesic agents and the breast cancer drug, tamoxifen.

Figure 1.1 Tramadol metabolism and CYP2D6. Tramadol is metabolized by CYP2D6 via O-demethy-lation into the more active metabolite O-desmethyltramadol. UMs have shown to have increased opioid-related ADRs (Kirchheiner et al., 2008; Stamer et al., 2008).

Tramadol and codeine are commonly used analgesic agents, which are both metabolized by CYP2D6. Tramadol undergoes O-demethylation by CYP2D6 into the more active metabolite O-desmethyltramadol (Figure 1.1). A poor analgesic effect has been demonstrated in PM phenotypes treated with tramadol (Halling, Weihe and Brosen, 2008; Stamer et al., 2007). On the other hand, UM phenotype patients taking tramadol have displayed an increased incidence of ADRs, for example respiratory depression (Kirchheiner et al., 2008; Stamer et al., 2008). Codeine is a prodrug and is metabolized into its active metabolite, morphine. Clinical studies have shown PM phenotypes achieve a poor analgesic effect, caused by the decreased production of morphine (Caraco, Sheller and Wood, 1996). These patient phenotypes also have a degree of protection from codeine overdose. On the other hand, UM phenotypes have been shown to be very sensitive to codeine treatment due to its rapid conversion to morphine (Kirchheiner et al., 2007; Madadi et al., 2009). This increases the risk of developing toxic opioid side effects: drowsiness, respiratory depression and hypotension. CYP2D6 genotype testing could, therefore, potentially help in the prevention of ADRs or treatment failure associated with codeine and tramadol use (Foster, Mobley and Wang, 2007).

Tamoxifen is an important drug in the treatment of breast cancer. This drug targets oestrogen receptor positive breast cancer cells and has been shown to improve long-term survival in these patients (Early Breast Cancer Trialists’ Collaborative Group, 2005). Tamoxifen is metabolized by CYP2D6 and pharmacogenetic variability of this enzyme has been associated with altered treatment response and patient prognosis (Kiyotani et al., 2008; Schroth et al., 2007). Tamoxifen is metabolized into the more active metabolites (Figure 1.2), 4 hydroxy-N-desmethyltamoxifen (endoxifen) and 4-hydroxytamoxifen (Ingle, 2007). The major metabolite of tamoxifen is N-desmethyltamoxifen, which is produced via the CYP3A4/5 enzymes. This is then metabolized via CYP2D6 to endoxifen (Desta et al., 2004). CYP2D6 also directly metabolizes tamoxifen into 4-hydroxytamoxifen, which is then metabolized into endoxifen via CYP3A4/5. Both 4-hydroxytamoxifen and endoxifen have higher affinity for the oestrogen receptor (Lim et al., 2005). CYP2D6 PMs have been shown to respond less well to tamoxifen treatment due to reduced production of these more active metabolites (Goetz et al., 2007; Lim et al., 2007; Xu et al., 2008). This has also been associated with increased breast cancer recurrence rates and patient mortality in CYP2D6 PM phenotypes (Goetz et al., 2007; Kiyotani et al., 2008). There has therefore been increasing interest in the role CYP2D6 genotype testing for drug treatment selection in breast cancer patients (Hartman and Helft, 2007; Punglia et al., 2008; Ross et al., 2008). However, some negative association studies have also been reported and more rigorous clinical pharmacogenetic studies are required before CYP2D6 genotyping is more widely used in drug treatment selection for breast cancer patients (Limdi and Veenstra, 2010; Wegman et al., 2007).

Figure 1.2 Tamoxifen metabolism and CYP2D6. Tamoxifen is metabolized into the more active metabolites, 4-hydroxytamoxifen and endoxifen, via the CYP2D6 and CYP3A4/5 enzymes.

1.2.2 CYP2C9 pharmacogenetics

Cytochrome P450 2C9 (CYP2C9) is a 490 amino acid protein (55.6 kDa) and the gene encoding this enzyme is located on chromosome 10 (Solus et al., 2004; Wang et al., 2009). CYP2C9 is one of the most abundant hepatic CYP enzymes and metabolizes approximately 15% of commonly used drugs (Rettie and Jones, 2005). Some of the important drugs metabolized by CYP2C9 are the non-steroidal anti-inflammatory drugs (NSAIDs; diclofenac, ibuprofen), angiotensin receptor blockers (ARBs; irbesartan) and anticoagulants. The main function of CYP2C9 is drug substrate oxidation, via interaction with the haem–oxygen complex (PDB ID: 10G5) (Williams et al., 2003). Important amino acid residues implicated in active site interactions are Arg97, Arg108, Phe114 and Asp293 (Dickmann et al., 2004; Flanagan et al., 2003; Mosher et al., 2008; Ridderstrom et al., 2000). CYP2C9 displays genetic polymorphism between different patient populations, which can result in altered enzyme activity and different drug pharmacokinetic profiles (Wang et al., 2009). Over 30 allelic variants have now been identified (www.cypalleles.ki.se/cyp2c9.htm). The two common allelic variants of CYP2C9 are CYP2C9*2 and CYP2C9*3, which result from SNPs occurring within the CYP2C9 gene (Table 2.2). This leads to amino acid substitutions within the CYP2C9*2 (R144C) and CYP2C9*3 (I359L) enzyme structures. Both mutant enzymes result in PM phenotypes and the protein structural changes could explain the altered metabolic activity between the enzyme variants (Takanashi et al., 2000). Both CYP2C9*2 and CYP2C9*3 alleles are more commonly found in the Caucasian population (Table 1.2) (Wang et al., 2009).

Table 1.2 Common allelic variants of CYP2C9#

Recently, there has been considerable interest in the role of CYP2C9 pharmacogenetics in warfarin metabolism and its therapeutic effect (Schelleman, Limdi and Kimmel, 2008; Wadelius and Pirmohamed, 2007). Warfarin is a commonly used anticoagulant agent and is metabolized by CYP2C9 (PDB ID: 10G2) into its major inactive metabolite, 7-hydroxywarfarin (Figure 1.3) (Kaminsky and Zhang, 1997). Warfarin is used in the treatment of venous thrombosis, for example pulmonary embolism and deep venous thrombosis (DVT). It is also used to reduce thrombo-embolic risk associated with the cardiac arrhythmia, atrial fibrillation (AF) and in patients with prosthetic heart valves (Singer et al., 2008). Warfarin has a narrow therapeutic window and requires careful coagulation blood test monitoring, using the International Normalized Ratio (INR). However, one of the serious complications of this treatment is overcoagulation and the associated risk of bleeding, which can sometimes be fatal (Fanikos et al., 2005; Linkins, Choi and Douketis, 2003). CYP2C9 enzyme inhibition and induction by co-administered drugs, for example antibiotics, is an important cause of altered warfarin therapeutic effect and ADRs in the clinical setting (Lin and Lu, 1998). Warfarin related adverse effects have been recognized as one of the most common ADRs among patients and has major financial implications for the health service (Davies et al., 2009; Pirmohamed et al., 2004).

Figure 1.3 Warfarin metabolism and CYP2C9. Warfarin is metabolized by CYP2C9 via hydroxylation into the inactive metabolite 7-hydroxywarfarin. PMs have an enhanced anticoagulation effect (Aithal et al., 1999; Higashi et al., 2002).

The effects of CYP2C9 pharmacogenetic variability can also alter the time to reach the therapeutic target and increase the risk of ADRs (Caraco, Blotnick and Muszkat, 2008; Schwarz et al., 2008). GWAS have identified genetic polymorphisms of CYP2C9 and the therapeutic target, Vitamin K epoxide reductase complex 1 (VKORC1), as important determinants of warfarin activity (Cooper et al., 2008). Poor metabolism of warfarin by CYP2C9 variants can increase the risk of over-coagulation and bleeding. The two common allelic variants, CYP2C9*2 and CYP2C9*3 have been associated with an increased risk of bleeding in patients taking warfarin (Aithal et al., 1999; Higashi et al., 2002). The genetic mutations result in amino acid changes within the protein structure (Table 2.2), which affect warfarin-CYP2C9 metabolism (Lee, Goldstein and Pieper, 2002). CYP2C9 genotype testing has therefore been developed to allow more effective targeting of warfarin therapy, with the aim of reducing the risk of ADRs. The FDA approved warfarin genotype-testing in 2007 and has recently updated its label for warfarin pharmacogenetic testing (www.pharmgkb.org/clinical/warfarin.jsp). Various PCR-based CYP2C9 genotyping methods are available and some have been approved by the FDA (King et al., 2008; Langley et al., 2009).

Recent clinical studies have shown that genotype-guided warfarin dosing is more accurate in determining the initial dosing, especially in patients requiring low or high dose warfarin treatment (The International Warfarin Pharmacogenetics Consortium, 2009; Anderson et al., 2007). Genotype-guided dosing has also been shown to achieve better anticoagulation control and less risk of ADRs (Caraco, Blotnick and Muszkat, 2008). The effects of VKORC1 genetic variants also play an important role in determining warfarin activity (Limdi et al., 2008). Various warfarin dosing algorithms have been proposed, based on CYP2C9 and VKORC1 genotypes (Langley et al., 2009). However, further clinical evidence in the benefits of genotype-guided warfarin dosing is required before more widespread use of this test in clinical practice (Gage and Lesko, 2008). Larger prospective warfarin clinical pharmacogenetic studies are ongoing (van Schie et al., 2009).

Another important area of CYP2C9 pharmacogenetics is in the treatment of diabetes. Sulphonylurea drugs are commonly used in the treatment of type 2 diabetes (Krentz and Bailey, 2005). These oral hypoglycaemic agents bind to the ATP-dependent potassium channels on the pancreatic beta cells, which leads to the opening of the calcium channels. This results in calcium influx into the beta cell and subsequent release of insulin. Sulphonylureas are metabolized by CYP2C9 into inactive metabolites and clinical studies have demonstrated pharmacogenetic variability in drug response. Patients with the CYP2C9*2 and CYP2C9*3 genotypes have been shown to have a better treatment response to sulphonylureas (Zhou et al., 2010). The reduced drug metabolism in these diabetic genotypes was also shown to lead to better glycaemic control. However, the risk of hypoglycaemia has also been shown to increase in PM genotypes, due to the enhanced effect of sulphonylureas (Ragia et al., 2009b). These drugs are also playing an important role in the treatment of some types of monogenic diabetes (single gene defects). Mutations of the beta cell potassium channels (subunits Kir6.2 and Sur1) have been associated with defective closing of these channels and subsequent development of neonatal diabetes (Sperling, 2006). The sulphonylurea drugs can effectively bind to these mutated channels, resulting in insulin release and therefore avoiding the need for insulin injections in these young diabetic patients (Flechtner et al., 2007). Both CYP2C9 pharmacogenetics and genotyping for monogenic diabetes are becoming exciting new areas in diabetes research and personalized medicine.

1.2.3 CYP2C19 pharmacogenetics

CYP2C19 metabolizes many clinically important drug classes, for example proton pump inhibitors, antidepressants and anticonvulsants (de Leon, Armstrong and Cozza, 2006). The CYP2C19 gene is located on chromosome 10 and to date there is no crystal structure available for this enzyme. Like the other CYPs, this also displays genetic polymorphism, with over 20 genetic variants of CYP2C19 having now been identified (www.cypalleles.ki.se/cyp2c19.htm). CYP2C19*2 and CYP2C19*3 are the most common allelic variants (Table 1.3). CYP2C19*2 is characterized by a SNP which leads to a splicing defect and subsequently encodes a non-functional enzyme (de Morais et al., 1994b). This is the main inactive allelic variant found in the Caucasian population (∼15%) (Desta et al., 2002). The CYP2C19*3 allelic variant is also associated with a PM phenotype and this is most commonly found in the Asian population (de Morais et al., 1994a). These two CYP2C19 PM phenotypes have been associated with reduced clearance of some drug substrates and related to ADRs (Desta et al., 2002; Jin et al., 2010). CYP2C19*17 is a newly identified allelic variant, which is associated with a specific promoter polymorphism and more commonly found in the Caucasian and African populations (Sim et al., 2006). The CYP2C19*17 enzyme is associated with increased metabolic activity and related to altered drug efficacy (Rudberg et al., 2008; Sim et al., 2006). Due to the rapid metabolism associated with this allelic variant, patients taking antidepressant drugs have been shown to have reduced plasma drug concentrations (Rudberg et al., 2008). The AmpliChip CYP450 test can be used to detect the PM phenotypes but newer PCR methods are used for the recently identified CYP2C19*17 allele (de Leon, Armstrong and Cozza, 2006; Rudberg et al., 2008). Further analysis of these CYP2C19 genetic polymorphisms and their pharmacogenetic effects are ongoing (Ragia et al., 2009a).

Table 1.3 Common allelic variants of CYP2C19#

Figure 1.4 Clopidogrel metabolism and CYP2C19. Clopidogrel is a prodrug and metabolized by CYP2C19 into the active metabolites, which inhibits the P2Y12 platelet receptor. PMs have a reduced anti-platelet effect, whereas UMs have a higher risk of bleeding (Mega et al., 2009; Sibbing et al., 2010).

Currently, there is a lot of interest in the effect of CYP2C19 pharmacogenetics on the antiplatelet activity of clopidogrel (Mega et al., 2009). Clopidogrel belongs to the thienopyridine drug class. It has been increasingly used in the treatment of acute coronary syndromes and secondary stroke prevention therapy. One of its important treatment indications is in reducing the risk of coronary artery stent thrombosis, post-percutaneous coronary intervention (PCI). Clopidogrel irreversibly inhibits the P2Y12 receptor on the platelet surface, which then blocks the activation of the GpIIb/IIIa pathway that is associated with the cross-linking of platelets via fibrin (Parikh and Beckman, 2007). Clopidogrel is a prodrug and metabolized by the CYP2C19 enzyme into the active metabolites, which produce the antiplatelet effects (Figure 1.4). Drugs which inhibit CYP2C19 enzyme function have been shown to reduce clopidogrel activation. One of the commonly used proton pump inhibitors, omeprazole, has been associated with reduced clopidogrel efficacy (Cuisset et al., 2009).

CYP2C19 genetic polymorphism has also been shown to affect clopidogrel activity. CYP2C19 PMs were found to have higher plasma clopidogrel concentrations and lower antiplatelet effect compared to EMs (Kim et al., 2008). Patients with low CYP2C19 activity have also been shown to have increased risk of cardiovascular events and coronary stent thrombosis post-PCI (Mega et al., 2009; Shuldiner et al., 2009). On the other hand, increased activation of clopidogrel in patients with the CYP2C19*17 genotype have shown an increased risk of bleeding (Sibbing et al., 2010). The FDA has recently updated its label for clopidogrel pharmacogenetic testing (www.pharmgkb.org/clinical/clopidogrel.jsp). Further evaluation is ongoing into how best to implement these findings for clopidogrel use in clinical practice, and the role of newer P2Y12 inhibitors (Wallentin, 2009).

1.3 Conclusion

Cytochrome P450 pharmacogenomics represents an important area of translational medicine research. This covers the entire spectrum, from the medicinal chemistry of CYPs to genotype testing and application to clinical practice. CYP pharmacogenetics has become an important part of the drug discovery process and in lead drug candidate optimization (Katz et al., 2008; Roses, 2008). The approval of CYP genotype testing has been a major advance in personalized medicine. Recent clinical studies have shown a potential role of CYP2D6 genotyping in drug treatment selection for breast cancer patients. CYP genotyping may also have an important role to play in determining optimal therapeutic efficacy and reducing ADRs in patients taking the antithrombotic agents, warfarin and clopidogrel. However, larger prospective clinical pharmacogenetic studies are required to provide a more rigorous evidence-base for pharmacotyping together with well-developed genomic services, before genotype testing is more widely used in clinical practice (Limdi and Veenstra, 2010; Ormond et al., 2010; Vizirianakis, 2007).

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