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Review Article |
Department of Medicine, Christchurch School of Medicine and Health Sciences, Christchurch, New Zealand
Abstract
Abstract I. Introduction/Perspective A. Background on Pharmacogenetics B. Pathways with Genetic Variation That May Be Important Clinically II. Cytochrome P450 A. CYP2D6 1. Tricyclic Antidepressants. a. Amitriptyline (tertiary)/nortriptyline (secondary). b. Imipramine (tertiary)/desipramine (secondary). c. Clomipramine (tertiary)/desmethylclomipramine (secondary). d. Doxepin (tertiary)/desmethyldoxepin (secondary). 2. Selective Serotonin Reuptake Inhibitors. a. Fluoxetine. b. Paroxetine. c. Other selective serotonin reuptake inhibitors. 3. Other Antidepressants. a. Maprotiline. b. Mianserin. c. Venlafaxine. 4. Antidepressants (in General) and Clinical Outcomes. 5. Antipsychotics. a. Chlorpromazine. b. Haloperidol. c. Perphenazine. d. Thioridazine. e. Zuclopenthixol. f. Atypical antipsychotics. g. Antipsychotics (in general) and clinical outcomes. 6. Antiarrhythmics. a. Propafenone. b. Flecainide. c. Mexiletine. 7. beta-Blockers. a. Carvedilol. b. Metoprolol. c. Propranolol. d. Timolol. 8. Opioid Analgesics. a. Codeine. b. Dihydrocodeine. c. Tramadol. d. Other opioids. 9. Antiemetics. 10. Antihistamines. 11. Other Drugs. a. Atomoxetine. b. Perhexiline. c. Phenformin. d. Tolterodine. 12. Summary of CYP2D6. B. CYP2C9 1. Coumarin Anticoagulants. a. Warfarin. b. Acenocoumarol. c. Phenprocoumon. 2. Sulfonylurea Drugs. a. Tolbutamide. b. Glyburide. c. Glimepiride. d. Glipizide and gliclazide. 3. Angiotensin II Blockers. a. Losartan. b. Candesartan. c. Irbesartan. 4. Nonsteroidal Anti-inflammatory Drugs. a. Diclofenac. b. Ibuprofen. c. Oxicams. d. Celecoxib. e. Other selective cyclooxygenase-2 inhibitors. f. Nonsteroidal anti-inflammatory drugs (in general) and clinical outcomes. 5. Phenytoin. 6. Other Drugs. 7. Summary of CYP2C9. C. CYP2C19 1. Proton Pump Inhibitors. 2. Benzodiazepines. 3. Tricyclic Antidepressants. 4. Selective Serotonin Reuptake Inhibitors. 5. Barbiturates. 6. Proguanil. 7. Phenytoin. 8. Moclobemide. 9. Other Drugs. 10. Summary of CYP2C19. D. Other Cytochromes P450 1. CYP2B6. a. Bupropion. b. Efavirenz. 2. CYP2C8. a. Paclitaxel. b. Ibuprofen. c. Repaglinide. d. Thiazolidinediones. e. Cerivastatin. f. Summary. 3. CYP3A5. a. Midazolam. b. Calcineurin inhibitors. c. 3-Hydroxy-3-methylglutaryl-CoA reductase inhibitors. d. Protease inhibitors. e. Summary. III. Other Important or Potentially Important Enzymes A. Acetyltransferase 1. Isoniazid. 2. Hydralazine. 3. Procainamide. 4. Sulfonamide Antibiotics. 5. Sulfasalazine. 6. Dapsone. 7. Phenelzine. 8. Summary. B. Butyrylcholinesterase 1. Suxamethonium and Mivacurium. 2. Procaine. 3. Cocaine. 4. Bambuterol. 5. Summary. C. Thiopurine Methyltransferase 1. Azathioprine and 6-Mercaptopurine. 2. Summary. D. Dihydropyrimidine Dehydrogenase 1. 5-Fluorouracil. 2. Summary. E. Uridine Diphosphate Glucuronosyltransferase 1A1 IV. Overall Summary and Conclusions V. Future Directions
The application of pharmacogenetics holds great promise for individualized therapy. However, it has little clinical reality at present, despite many claims. The main problem is that the evidence base supporting genetic testing before therapy is weak. The pharmacology of the drugs subject to inherited variability in metabolism is often complex. Few have simple or single pathways of elimination. Some have active metabolites or enantiomers with different activities and pathways of elimination. Drug dosing is likely to be influenced only if the aggregate molar activity of all active moieties at the site of action is predictably affected by genotype or phenotype. Variation in drug concentration must be significant enough to provide "signal" over and above normal variation, and there must be a genuine concentration-effect relationship. The therapeutic index of the drug will also influence test utility. After considering all of these factors, the benefits of prospective testing need to be weighed against the costs and against other endpoints of effect. It is not surprising that few drugs satisfy these requirements. Drugs (and enzymes) for which there is a reasonable evidence base supporting genotyping or phenotyping include suxamethonium/mivacurium (butyrylcholinesterase), and azathioprine/6-mercaptopurine (thiopurine methyltransferase). Drugs for which there is a potential case for prospective testing include warfarin (CYP2C9), perhexiline (CYP2D6), and perhaps the proton pump inhibitors (CYP2C19). No other drugs have an evidence base that is sufficient to justify prospective testing at present, although some warrant further evaluation. In this review we summarize the current evidence base for pharmacogenetics in relation to drug-metabolizing enzymes.
Modern pharmacogenetics has its origins in the 1950s with a series of discoveries—primaquine sensitivity, slow isoniazid acetylation, and butyrylcholinesterase deficiency—that demonstrated the influence of genetics over drug response (Hughes et al., 1954
; Alving et al., 1956; Kalow, 1956). However, it was decades later that research in molecular biology (Gonzalez et al., 1988) and the Human Genome Project greatly accelerated interest in the area. This led to some authors enthusiastically claiming that "... genotype testing has the potential to optimize drug therapy" (Meyer, 2000) and that there is sufficient evidence to warrant instigation of "... population pharmacogenetic testing" (Wolf et al., 2000). More recently, other authors have tempered the hope for pharmacogenetics and stated that "the promise of pharmacogenetics has largely remained unfulfilled" (Tucker, 2004). It therefore seems useful to take a hard look at the evidence behind such claims and counterclaims.
The main aim of this article is to critically review the literature to ascertain which pharmacogenetic tests for drug-metabolizing enzymes should be undertaken clinically and in relation to what drugs. A second aim is to propose a list of drugs for which the case for pharmacogenetically based dose individualization is strongest. As few clinicians actually assess genotype or phenotype prospectively to individualize dose (Gardiner and Begg, 2005), it seems likely that some claims of clinical relevance are excessive or premature.
A. Background on Pharmacogenetics
The term "pharmacogenetics" has historically been used to describe the field, but the term "pharmacogenomics" has been a recent addition. Whereas there are subtle differences, with pharmacogenomics having a wider brief, it is not clear that our understanding has been increased by having two such similar terms. We, therefore, will use the term pharmacogenetics in this article, referring to any influence that genetics may have on drug therapy.
A second point of confusion is related to the use of the term "function". There have been many articles on the functional effects of genetic polymorphisms, which to a molecular biologist may refer to changes in protein expression, but to a clinician might refer to effects that are important in the clinic. Furthermore, the term "clinical importance" may, to some, relate to effects that have been proven in practice, whereas to others it may also include the potential for clinical relevance.
"Polymorphism" also has different meanings within pharmacogenetics. We accept the broad definition of polymorphism as the presence of two or more variants (e.g., alleles and phenotypes) in a population that occur at a significant frequency. What constitutes a "significant frequency" is not particularly clear, although most authors seem to accept 1% as the cutoff. Thus, thiopurine methyltransferase is polymorphic genotypically and phenotypically, with the most common genetic variant (TPMT*3A) having an allele frequency of 
4% in German Caucasians, whereas absolute and partial enzyme deficiency affect 0.6 and 10% of the population, respectively (Schaeffeler et al., 2004).
Many review articles describe genetic variations related to many mechanisms that may be relevant to drug therapy (Meyer, 2000; Wolf et al., 2000; Weinshilboum, 2003). Effects may be on genes that code for metabolizing enzymes, transporters, receptors, and/or ion channels. The effects can be described as pharmacokinetic (affecting drug concentrations) and pharmacodynamic (affecting drug action). In this article our discussion is limited to genetic variations affecting pharmacokinetics via effects on metabolism. Other aspects of pharmacokinetics (e.g., absorption) are also potentially affected by genetic variation, but those that affect clearance (drug elimination) and hence steady-state concentrations are most important for chronic dosing.
The major routes of drug elimination are renal excretion and metabolic biotransformation. The latter can be subdivided into cytochrome P450 (P4501)-mediated reactions, conjugations (especially glucuronidation) and "others" (Table 1). There are many sources of variation in enzyme activity, including age, enzyme induction or inhibition, and diseases (especially of the liver). Variation in the DNA sequence of genes encoding enzymes can abolish, reduce, or increase the expression and activity of an enzyme. Individuals with two alleles coding for "normal" enzyme function are termed homozygous extensive metabolizers (homozygous EM or "wild-type") whereas those with two variant alleles resulting in inactive or absent enzyme are "poor metabolizers" (PM). There may also be an intermediate metabolizer (IM) phenotype with reduced function, which usually results from the presence of one variant and one normal allele (heterozygous EM). Intermediate and extensive metabolizers are often collectively referred to as "extensive metabolizers", especially in studies in which metabolizer status is assigned using phenotype. Gene duplication or multiplication has only been identified for CYP2D6 and can lead to ultrarapid metabolism (UM).
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To assess the clinical relevance of pharmacogenetics, a perspective is necessary. Simplistically, standard drug doses will achieve normal concentrations and effect in homozygous EMs (which usually comprise the largest proportion of the population), but might be toxic in PMs (and maybe in heterozygous EM or IMs) and ineffective in UMs. For polymorphisms to be important clinically, the signal of their effect must be greater than the noise from all the other sources of variance. Similarly, the therapeutic index (the size of the window between efficacy and toxicity) of each drug must be considered. If a drug is safe over the wide range of concentrations that encompasses the variation caused by genetics (i.e., high therapeutic index), then it is not important to consider polymorphisms in the therapeutic context. By contrast, if a drug has a low therapeutic index (e.g., warfarin), minor variations in concentrations, such as from polymorphisms, may be important.
There are other effects that may neutralize or abolish the clinical significance of a genetic polymorphism. If the product of an enzymatic reaction has activity similar to that of the parent molecule, an altered ratio of parent to metabolite (through polymorphism) may have little clinical effect. Similarly, if a drug is metabolized or eliminated by multiple pathways, total ablation of one pathway (as in a PM) may result in minimal alteration of overall drug concentrations and hence minimal effect. The presence of stereoselective metabolism complicates things further, as sometimes the enantiomers have different pharmacological activity and pathways of elimination. It is the aggregate area under the concentrationtime curve (AUC) of molar activity at the site of action that is important in overall drug effect. There is also the phenomenon of "phenocopying", which describes the conversion of a patient from a phenotypic normal metabolizer to a slow metabolizer as a result of inhibition of the enzyme by another drug or by itself ("autophenocopying"). If all patients taking a drug are ultimately poor metabolizers either by their genetics or by phenocopying, then the genetics are essentially irrelevant. Phenocopying sometimes explains why differences between PMs and EMs is less at steady state than after single doses.
The net effect of the above is that many (if not most) single-pathway genetic polymorphisms are unlikely to have major clinical importance unless the following attributes apply:
Further, assessment of drugs in relation to polymorphisms is difficult unless the following apply:
It is often stated that in addition to the above, prospective studies should be undertaken to confirm clinical benefits (e.g., of genotype-directed dose regimens). It is unlikely that such studies will be performed for the vast majority of drugs. However, it would certainly assist the evidence base if some key drug-gene pairings were examined prospectively so that the paradigm of prospective testing was put on a firm foundation. Thereafter, clinical uptake is likely to follow the practice of clinicians who have ready access to a particular test that they perceive to have clinical merit. Clearly, from a population health funding perspective, other factors such as supportive pharmacoeconomic analyses are also helpful.
All of these factors need to be considered in the assessment of the evidence base supporting testing for pharmacogenetic effects of drugs. To do this in a semi-objective manner, an algorithm was developed (Table 2), based on the Naranjo algorithm for assessing adverse effect likelihood (Naranjo et al., 1981). We are not necessarily advocating the use of this algorithm, as it has not been validated formally, but it was helpful in a general sense to formalize the assessment of the current evidence base and comparison between drugs.
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The best pharmacokinetic endpoint for the assessment of pharmacogenetic effects is the AUC, usually of serum, plasma, or blood. For the purposes of this review, known polymorphisms will be examined with respect to the magnitude of change in AUC, the therapeutic index of the drug, the presence of other pathways of elimination that may "dilute" the primary effect, other potential pharmacokinetic effects, and evidence of actual differences in clinical endpoints (efficacy and adverse effects). The applicability of pharmacogenetics in current therapeutics will also be examined, along with suggestions about how this area might be improved.
B. Pathways with Genetic Variation That May Be Important Clinically
All of the pathways involved in drug metabolism (Table 1) have the potential to be affected by genetic variation. The activities of many of these enzymes (e.g., CYP2D6, thiopurine methyltransferase) meet our general description of polymorphism in terms of the expressed phenotypes and will be discussed in turn. The enzyme family most important for overall drug metabolism (CYP3A) has activity that is unimodally distributed and can largely be disregarded for the purpose of this review (the subfamily CYP3A5 may be an exception and is discussed in section II.D.). Although genetic variations in metabolism are recognized as influencing nicotine and alcohol disposition and effect, these will not be discussed here.
The first evidence of polymorphisms in drug-metabolizing enzymes having clinical effect was the observation of slow acetylation in relation to isoniazid (Price Evans et al., 1960). The first evidence supporting genetic polymorphism related to P450 enzymes came almost two decades later with the almost simultaneous observations of a greater response to sparteine and debrisoquine occurring in a subgroup of the population known as "slow hydroxylators" (Mahgoub et al., 1977; Eichelbaum et al., 1979). The first evidence that genetic polymorphisms were taken seriously in the clinic relates to butyrylcholinesterase deficiency in anesthetics (section III.).
P450 enzymes are a group of heme proteins found largely in hepatocytes, but also in the small intestine, lungs, kidneys, and brain. The major families responsible for the oxidative metabolism of drugs and environmental chemicals are CYP1, CYP2, and CYP3. These enzymes also metabolize a diverse range of endogenous substances (e.g., steroids). The physiological consequences of polymorphism in P450 enzymes in the absence of drug therapy will not be discussed in this review.
In the excellent review of Weinshilboum (2003), a small number of drugs with "proven" clinical effect from P450 polymorphisms were listed. These included debrisoquine, sparteine, nortriptyline, and codeine for CYP2D6, warfarin and phenytoin for CYP2C9, and omeprazole for CYP2C19. The implication was that these drugs may be the tip of the iceberg and that many of the other drugs metabolized by these pathways are also likely to be affected to a clinically important extent. For reasons noted above we believe this is unlikely. We will now review the evidence, as we have found it, to determine which drugs are affected or are likely to be affected to a clinically important extent because of a significant change in AUC of the active moiety.
Approximately 7 to 10% of European Caucasians and 1% of Chinese, Japanese, and Koreans are PMs of CYP2D6 (Nakamura et al., 1985; Alvan et al., 1990; Sohn et al., 1991; Bertilsson et al., 1992). Many variant alleles are associated with the PM phenotype, although most of these occur infrequently (http://www.cypalleles.ki.se). In Caucasians, CYP2D6*3, *4, and *5 produce inactive enzyme or no protein product and are the variants most commonly implicated in the PM phenotype. CYP2D6*4 is the most common variant allele in Caucasians (allele frequency 21%) (Sachse et al., 1997; Cascorbi, 2003), but it is virtually absent in Chinese. However, overall CYP2D6 activity is lower in Chinese than in Caucasians (Bertilsson et al., 1992) as a result of the high allele frequency of CYP2D6*10 (50%) which is largely absent in Caucasians. This variant produces an unstable enzyme with reduced (but not absent) ability to metabolize substrate drugs. At the other end of the spectrum, gene duplication/multiplication occurs in 1% of Swedish Caucasians (Dahl et al., 1995), 7% of white Spaniards (Agundez et al., 1995), and 29% of black Ethiopians (Aklillu et al., 1996) and is predictive of an UM phenotype. Genotyping for the more common variant alleles in a population can predict phenotype (PM versus EM) with high accuracy (99%) in a population of defined ethnicity (Sachse et al., 1997) and avoids the logistic problems with drug administration for phenotyping. However, some problems remain. For example, rare mutations may not be identified with "routine" genotyping methods, and many individuals with the UM phenotype may not have gene duplication/multiplication (Dahl et al., 1995).
CYP2D6 is the most widely studied enzyme in relation to polymorphisms and is involved in the elimination of 25% of drugs. Substrates are largely lipophilic bases and include some 
-blockers, antidepressants, neuroleptics, antiarrhythmics, and opioids (Table 3). As noted earlier, however, just because a drug is a substrate for CYP2D6, clinical effects related to polymorphism cannot be assumed.
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1. Tricyclic Antidepressants. These drugs have a moderate therapeutic index, as they produce significant adverse effects at therapeutic concentrations and are dangerous in overdose. Tricyclic antidepressants (TCAs) are high-clearance, lipid-soluble drugs that are metabolized via multiple pathways involving both phase I (P450) and phase II (glucuronidation) processes. They exist as tertiary or secondary amines, and the tertiary forms are metabolized to secondary amines. Both tertiary and secondary amines are active, as are some of the subsequent hydroxylated metabolites. The tertiary amines are metabolized by many P450s, whereas the secondary amines are largely metabolized by CYP2D6. In addition, there may be differential metabolism of enantiomers. As these drugs have complex pharmacology, it is always going to be difficult to establish clear associations with genetic variations. The lesser complexity of the secondary TCAs (when administered as such, rather than as metabolites of the tertiary forms) and a more convincing involvement of these with CYP2D6 suggest a greater chance of establishing associations.
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). CYP2D6 mediates the conversions to E-10-hydroxyamitriptyline and E-10-hydroxynortriptyline (Mellstrom et al., 1981; Breyer-Pfaff et al., 1992; Olesen and Linnet, 1997), whereas demethylation of amitriptyline to nortriptyline and of E-10-hydroxyamitriptyline to E-10-hydroxynortriptyline is by multiple P450s but especially CYP2C19 (Olesen and Linnet, 1997; Venkatakrishnan et al., 1998; Yan et al., 1998). Subsequent metabolism of hydroxy derivatives is generally via glucuronidation. Both amitriptyline and nortriptyline inhibit CYP2D6 but not enough to phenocopy (Baumann et al., 1992; Solai et al., 2002).
As the pharmacology is complex, it is not surprising that demonstrating clear effects for amitriptyline has been difficult. A significant correlation between amitriptyline clearance and the debrisoquine metabolic ratio has been observed in nonsmokers (Mellstrom et al., 1983, 1986) supporting some CYP2D6 dependence. In a recent study, patients with one dysfunctional CYP2D6 allele had a greater risk of side effects with amitriptyline 150 mg daily than those with two functional alleles (77 versus 12%), and this risk was associated with higher nortriptyline concentrations (Steimer et al., 2005).
The metabolism of nortriptyline, when administered as such, is simpler and is mediated mainly (>80% in EMs) by CYP2D6 (Bertilsson et al., 1980; Mellstrom et al., 1981; Nordin et al., 1985; Olesen and Linnet, 1997; Venkatakrishnan et al., 1999). After giving a 25-mg dose to Caucasians, the mean nortriptyline AUCs in genotypic PMs, IMs, and UMs were 3.3-, 2.8-, and 0.7-fold that observed in EMs, with reciprocal changes in 10-hydroxynortriptyline concentrations (Dalen et al., 1998). Changes in AUC have also been seen with reduced activity alleles (e.g., CYP2D6*10) in Asian subjects (Yue et al., 1998; Morita et al., 2000). The major metabolite produced by CYP2D6, E-10-hydroxynortriptyline, has approximately half the potency of the parent in inhibiting noradrenaline reuptake and greatly reduced anti-cholinergic activity (Nordin and Bertilsson, 1995). It is often present at comparable (or higher) concentrations to the parent drug and may contribute to the antidepressant effects (Nordin and Bertilsson, 1995). In one study, the sole PM among 21 Caucasians receiving nortriptyline 100 mg (n = 1, a heterozygous EM) or 150 mg (n = 20) daily achieved nortriptyline plus 10-hydroxynortriptyline concentrations that were only slightly above the mean observed in heterozygous and homozygous EMs (10.9, 7.0, and 7.8 nM/mg, respectively) (Dahl et al., 1996).
Evidence of variation in clinical effect in relation to nortriptyline and metabolizer status is sparse. A number of case reports have documented toxicity (e.g., dizziness and sedation) with elevated nortriptyline concentrations in PMs and individuals receiving CYP2D6 inhibitors (Bertilsson et al., 1981; van der Kuy et al., 2002). Cases of treatment failures in UMs are also documented (Bertilsson et al., 1985). However, clinical endpoints (salivation, accommodation, sedation, blood pressure, and pulse rate) did not vary between genotypes in a single-dose study in healthy subjects (Dalen et al., 1998). In another study of patients with depression, CYP2D6 did not influence the rate of adverse reactions to nortriptyline (Roberts et al., 2004). As the main metabolite is active, altered parent/metabolite ratios may be the reason that altered effect has been hard to demonstrate; i.e., there is minimal change in overall molar activity. It is notable that the major metabolite does not seem to have been measured in most of the assessments and is not considered clinically during therapeutic drug monitoring.
b. Imipramine (tertiary)/desipramine (secondary).
Imipramine is metabolized to desipramine via CYP2C19, 1A2, and 3A4 (Lemoine et al., 1993; Skjelbo et al., 1993; Madsen et al., 1995; Spina et al., 1997a), and both compounds are metabolized to their hydroxy derivatives, which are also active (Nordin and Bertilsson, 1995), largely via CYP2D6 (Brosen et al., 1986a; Brosen and Gram, 1989; Madsen et al., 1995). Data regarding enantiomers are lacking. The clearance of imipramine in PMs is approximately half that of EMs after a single dose, although steady-state concentrations may remain within the range of EMs, perhaps due to saturable kinetics in EMs (Brosen et al., 1986a,b). Desipramine concentrations at steady-state are 7-fold higher in PMs, with the sum of imipramine plus desipramine concentrations being 5-fold higher in PMs than in EMs (Brosen et al., 1986a). Although not well established, the sum of imipramine plus desipramine concentrations may be used to monitor treatment with imipramine, and PMs generally require lower doses to attain the target concentrations. For example, PMs required 20 to 25 mg/day, whereas EMs required 50 to 350 mg/day to produce summed concentrations of 300 to 500 nM in the treatment of diabetic neuropathy (Sindrup et al., 1990a). Data supporting increased adverse effects in PMs is again lacking for imipramine (Meyer et al., 1988).
After a single desipramine dose, the mean AUCs of desipramine were 4- to 8-fold higher in PMs and 1.8-fold higher in IMs than in EMs (Brosen et al., 1986b; Spina et al., 1987; Steiner and Spina, 1987). Mean steady-state concentrations were 3-fold higher in PMs (Spina et al., 1997b). Similar effects have been seen in Japanese (Shimoda et al., 2000b). In one study, two PMs received a greatly reduced dose compared with that given to EMs (50 mg versus 200 mg daily) and still attained desipramine concentrations at the upper end of the range observed in EMs (860 and 880 versus 130 to 910 nM) (Sindrup et al., 1990b). Evidence for increased toxicity in PMs is harder to find. In one study of 2 PMs and 29 EMs receiving desipramine 100 mg daily, three patients (including both PMs) required a dose decrease because of sedation or postural hypotension. Efficacy at 3 weeks did not correlate with dextromethorphan metabolic ratio or desipramine plasma concentrations (Spina et al., 1997b). In the absence of a clear concentration-effect relationship for desipramine, these findings are collectively hard to interpret.
c. Clomipramine (tertiary)/desmethylclomipramine (secondary).
Demethylation of clomipramine to desmethylclomipramine (active) is via CYP2C19, 1A2, and 3A4, and each compound is metabolized to respective hydroxy derivatives via CYP2D6 (Kramer Nielsen et al., 1992, 1994, 1996; Nielsen et al., 1996; Gram et al., 1999). The clomipramine AUC was 1.8-fold higher in PMs than in EMs after a single dose (Kramer Nielsen et al., 1994). During twice daily treatment, one PM had trough concentrations of clomipramine, desmethylclomipramine and clomipramine plus desmethylclomipramine that were 3-fold higher than the median of the respective compound(s) in EMs (n = 36). The clomipramine concentration was within the EM range (570 in the PMs versus 70-730 nM in the EMs), whereas desmethylclomipramine and summed concentrations were 20 to 40% above the upper concentration in EMs (Kramer Nielsen et al., 1992). In another study, the summed concentrations were higher in two PMs (590 and 750 nM) than in EMs (70-510 nM) despite receiving a lower dose (50 versus 75 mg/day) (Sindrup et al., 1990b). There is little evidence for altered effect in relation to CYP2D6 metabolizer status.
d. Doxepin (tertiary)/desmethyldoxepin (secondary).
Doxepin is given as a 15:85 mixture of Z-(cis)-/E-(trans)-isomers which differ in activity, with Z-doxepin suggested to have greater antidepressive effect (Pinder et al., 1977). Desmethyldoxepin (active) is produced by several enzymes (e.g., CYP2C19), whereas CYP2D6 stereospecifically hydroxylates the E-isomers of doxepin and desmethyldoxepin (Haritos et al., 2000; Hartter et al., 2002; Kirchheiner et al., 2002d). The AUC of the active moieties after a single dose was 3-fold higher in PMs than in EMs, whereas IMs behaved similarly to EMs (Kirchheiner et al., 2002d). There seems to be no data that quantify modified clinical outcomes with CYP2D6 status.
2. Selective Serotonin Reuptake Inhibitors. The selective serotonin reuptake inhibitors (SSRIs) are generally thought to have a higher therapeutic index than TCAs. However, they have a wide range of adverse effects at clinical concentrations and are associated with the serotonin syndrome, which may be fatal. Like the TCAs, they are very lipid-soluble, high-clearance drugs subject to multiple metabolic pathways, and renal elimination is not relevant to the active moieties.
a. Fluoxetine.
R- and S-fluoxetine are metabolized (in part) to R- and S-norfluoxetine. These compounds share similar serotonin reuptake inhibition, although R-norfluoxetine is 20 times less potent (Fuller et al., 1992). CYP2D6 is the main enzyme producing S-norfluoxetine at low concentrations, with other enzymes (e.g., CYP3A4) filling in when this enzyme becomes saturated. CYP2C9 and CYP2D6 are largely responsible for R-norfluoxetine production (Margolis et al., 2000; Ring et al., 2001). Saturable metabolism and some autophenocopying occurs with chronic dosing (Alfaro et al., 2000; Amchin et al., 2001).
After a 20-mg dose, the AUC of fluoxetine was 3.9-fold higher and that of norfluoxetine was 0.5-fold lower in PMs than in EMs, whereas the sum of these moieties was 1.3-fold higher in PMs (Hamelin et al., 1996). After a higher 60-mg dose, the median AUCs of S- and R-fluoxetine were 11.5- and 2.4-fold higher in PMs, respectively, whereas S- and R-norfluoxetine were decreased marginally (0.8- and 0.6-fold, respectively) (Fjordside et al., 1999). After 23 days of fluoxetine 20 mg daily the sum of racemic parent plus norfluoxetine trough concentrations was comparable between PMs and EMs. Enantiomers were also examined, with no significant difference seen in the concentrations of R-fluoxetine and R-norfluoxetine, whereas S-fluoxetine was 2.2-fold higher and S-norfluoxetine was 3.4-fold lower in PMs than in EMs (Eap et al., 2001). In small studies a relationship between CYP2D6 status and adverse reactions with fluoxetine has not been identified (Clark et al., 2000; Stedman et al., 2002; Roberts et al., 2004). This finding is not unexpected given that the activity of the two S-moieties is similar (although residence time would also be a factor).
b. Paroxetine.
Paroxetine is inactivated by CYP2D6 and at least one other enzyme (Bloomer et al., 1992). The median paroxetine AUC was 7-fold higher in PMs after a 30-mg dose but diminished to 1.7-fold with chronic dosing (Sindrup et al., 1992c). Another steady-state study reported 3.3-fold higher 12-h concentrations in PMs than in EMs (Sindrup et al., 1992b). The difference observed with single versus repeated dosing is due to saturable metabolism (Sindrup et al., 1992b; Laine et al., 2001), which results in autophenocopying (Lam et al., 2002; Solai et al., 2002). Heterozygous EMs had nonsignificant 2-fold higher median steady-state trough concentrations than homozygous EMs (Ozdemir et al., 1999), although considerable overlap existed. Some have reported that UMs may have very low or undetectable concentrations of paroxetine with usual doses (Lam et al., 2002; Charlier et al., 2003). Data on the clinical implications are lacking, although one study (without pharmacokinetic assessment) suggested that sexual dysfunction was more frequent in those who were genotypically EMs, but who were phenotyped as PMs during treatment (17 of 24 patients or 71%) compared with those who were phenotyped as EMs (2 of 6 or 33%) (p = 0.015) (Zourkova and Hadasova, 2002). However, it seems unlikely that knowledge of the CYP2D6 genotype will assist with dosing given the unpredictable phenocopying that occurs. In addition, paroxetine concentrations do not seem to correlate with effect (as is the case with SSRIs as a class) (Lam et al., 2002).
c. Other selective serotonin reuptake inhibitors.
Fluvoxamine is metabolized in part by CYP2D6 and to a lesser extent by CYP1A2 (Spigset et al., 2001). Data are conflicting regarding the effect of CYP2D6 on fluvoxamine concentrations, with a single-dose study reporting a 1.3-fold higher AUC in PMs (Spigset et al., 2001), whereas in another no difference was observed (Christensen et al., 2002). Similar disparities were observed at steady state (Spigset et al., 1998; Christensen et al., 2002). Overall, the effect of the CYP2D6 genotype seems to be minor.
CYP2D6 status has little relevance for sertraline, which is metabolized by many P450s, including CYP2C19 (discussed later) (Hamelin et al., 1996; Kobayashi et al., 1999b; Xu et al., 1999). Likewise, citalopram is metabolized to a less active metabolite (desmethylcitalopram) mainly by CYP2C19 and 3A4 (35% each in EMs) and thence to didesmethylcitalopram (less active again) by CYP2D6 (Sindrup et al., 1993; Kobayashi et al., 1997; von Moltke et al., 1999, 2001; Herrlin et al., 2003). The AUC of racemic or S-citalopram (active enantiomer) does not vary appreciably with CYP2D6 status (Sindrup et al., 1993; Herrlin et al., 2003).
3. Other Antidepressants.
a. Maprotiline.
Maprotiline is metabolized to desmethylmaprotiline (active) mainly (80% in EMs) by CYP2D6 (Brachtendorf et al., 2003). Other metabolites (e.g., hydroxy derivatives) (Breyer-Pfaff et al., 1985) may also be active. The AUC of maprotiline (metabolites not measured) was 3.5-fold higher in PMs than in EMs after 50 mg twice daily for 8 days, and the half-life was proportionately longer. Prolonged histamine-induced bronchoconstriction has been seen in PMs (Firkusny and Gleiter, 1994).
b. Mianserin.
Production of desmethylmianserin (active) is largely by CYP1A2 (>50%), with CYP2D6 being involved in other pathways, including hydroxylation (8-hydroxymianserin is active) and further metabolism of desmethylmianserin (Pinder and van Delft, 1983; Dahl et al., 1994; Koyama et al., 1996a; Eap et al., 1998, 1999; Stormer et al., 2000). Consistent with this result, the mean AUCs of mianserin and desmethylmianserin were 1.8- and 1.5-fold higher, respectively, in PMs than in EMs (Dahl et al., 1994). A PM for both debrisoquine and mephenytoin had the highest summed concentrations among 18 patients with diabetic neuropathy (Sindrup et al., 1992d), and three of six patients with high mianserin concentrations were phenotypic PMs in another study (Tacke et al., 1992). In contrast, only one of seven patients with slow mianserin elimination was a PM, which does not support an important role for CYP2D6 (Begg et al., 1989).
S-Mianserin is more reliant on CYP2D6 (Dahl et al., 1994; Yasui et al., 1997; Eap et al., 1998) and may have a greater antidepressant effect than R-mianserin (Pinder and van Delft, 1983). Higher mean S-mianserin plasma concentrations and a slightly greater response were seen in Japanese patients with the CYP2D6*1/*10 versus those with the *1/*1 genotype (15 versus 8 mg/l at 12-h postdose) after 30 mg daily for 3 weeks (Mihara et al., 1997). Thioridazine inhibited CYP2D6 and increased S-mianserin, S-desmethylmianserin, and R-desmethylmianserin concentrations by 1.9-, 2.1- and 2.7-fold, respectively, whereas no effect on R-mianserin was observed (Yasui et al., 1997).
c. Venlafaxine.
There are multiple metabolic pathways and stereoisomerism, with the major route of metabolism to the equiactive O-desmethylvenlafaxime being partially mediated by CYP2D6 (Holliday and Benfield, 1995; Otton et al., 1996; Lessard et al., 1999). The ratio of parent to metabolite is significantly greater in PMs than in EMs, but the sum of parent and active metabolite seems similar (Fukuda et al., 1999, 2000; Veefkind et al., 2000), suggesting that polymorphism has minor clinical importance. CYP2D6 preferentially metabolizes R-venlafaxine (Eap et al., 2003), which has greater inhibitory effects on noradrenaline reuptake than the S-enantiomer but comparable serotonin reuptake inhibition (Holliday and Benfield, 1995). This finding could suggest that PMs may have greater serotonergic effects, although the activities of the metabolite enantiomers are not known. Some have suggested that PMs may be at risk of cardiac toxicity with this drug, although this theory is based on a small series of four subjects (Lessard et al., 1999), and there is no other supporting evidence.
4. Antidepressants (in General) and Clinical Outcomes.
As described above, there are case reports of toxicity in PMs (Bertilsson et al., 1981; Bluhm et al., 1993) and lack of effect in UMs (Bertilsson et al., 1985, 1993). In addition, there is some evidence to suggest that more problems with antidepressants (duration of hospital stay and frequency of adverse effects) occur at the extremes of CYP2D6 activity (Chou et al., 2000). A recent retrospective study reported that 29% of individuals with adverse reactions to antidepressants (most commonly TCAs) were genotypic PMs, whereas 19% (3 of 16) of nonresponders were genotypic UMs (4- and 5-fold higher than expected, respectively) (Rau et al., 2004). Consistent with this finding, a higher rate of CYP2D6 gene duplication was seen in patients in whom treatment with antidepressants metabolized by CYP2D6 failed (10 versus 1% expected) (Kawanishi et al., 2004). These initial studies suggest that prospective genotyping for CYP2D6 may identify individuals at increased risk of adverse reactions or treatment failure with antidepressants. However, although it is clear that toxicity and treatment failures are major issues in psychiatry, most adverse reactions and treatment failures occur in individuals who are EMs rather than PMs or UMs. This is not surprising since EMs are more frequent. Furthermore, although recommendations for antidepressant dose adjustment based on genotype have been proposed (Kirchheiner et al., 2001, 2004c) the effectiveness of this approach has not been validated. Large prospective studies (perhaps testing these dose recommendations) should be undertaken.
5. Antipsychotics. This is a structurally diverse group of drugs with a moderate to high therapeutic index [except maybe thioridazine, use of which has been decreasing because of its unfavorable benefit to risk (arrhythmia) profile]. They are generally very lipid-soluble, subject to high clearance and eliminated by metabolic rather than renal mechanisms. Some, but not all, are dependent on CYP2D6. A strong concentration-effect relationship has not been established for this group.
a. Chlorpromazine.
Chlorpromazine has many metabolites, at least one of which, 7-hydroxychlorpromazine, is active (Bunney and Aghajanian, 1974; Levy et al., 2000). This metabolite is partly (50%) produced by CYP2D6 (Muralidharan et al., 1996; Yoshii et al., 2000). In Korean volunteers, nonsignificant 1.3- and 1.7-fold higher chlorpromazine AUCs were seen in heterozygotes and homozygotes for CYP2D6*10 (Sunwoo et al., 2004). These differences are minor, and intersubject variation is substantial. Consequently, the CYP2D6 genotype is unlikely to be helpful for chlorpromazine.
b. Haloperidol.
This drug has complex metabolism, with CYP2D6 involvement appearing to be minor. Cytosolic carbonyl reductase produces reduced haloperidol, which has 10 to 20% of the activity of the parent and is metabolized further by CYP3A4 and glucuronosyltransferases. Reduced haloperidol is also back-oxidized to haloperidol primarily by CYP3A4 (Pan et al., 1998; Kudo and Ishizaki, 1999; Tateishi et al., 2000). Other metabolic pathways include N-dealkylation by CYP3A4 and others, and direct glucuronidation (Kudo and Ishizaki, 1999; Tateishi et al., 2000). Although it seems that CYP3A4 is the most important enzyme for the overall disposition of haloperidol, CYP2D6 may also play a minor role (Llerena et al., 1992a). A single-dose study showed 2-fold greater haloperidol clearance in EMs than in PMs, and mean reduced haloperidol concentrations were 2- to 4-fold higher in PMs from 10 to 72 h postdose (Llerena et al., 1992a,b). This result is difficult to understand but may suggest CYP2D6 involvement in the metabolism of reduced haloperidol. In Caucasian and Japanese subjects, steady-state haloperidol concentrations tend to be a little higher in those with variant alleles, or sometimes there is no appreciable difference (especially with the CYP2D6*10 variant). Reduced haloperidol concentrations are more consistently elevated in those with variant alleles, suggesting greater reliance on CYP2D6 (Suzuki et al., 1997; Mihara et al., 1999; Pan et al., 1999; Shimoda et al., 2000a; Ohnuma et al., 2003). However, these differences often fail to reach statistical significance, and clinical relevance is limited by the overlap in concentrations between genotypes.
There is little evidence for clinical relevance of genotype, with a Chinese study (n = 18) reporting no relationship between CYP2D6 and antipsychotic symptoms with haloperidol 10 mg daily (Lane et al., 1997). In contrast, a study of eight Caucasian patients treated with depot haloperidol for schizophrenia reported that the highest haloperidol concentrations and dopamine-2 receptor occupancy (determined by positron emission tomography) were in the sole PM (Nyberg et al., 1995b). In a Korean study, 60% of individuals with the CYP2D6*1/*10 or *10/*10 genotypes (n = 93) required benztropine compared with 35% of EMs (n = 23) (Roh et al., 2001a). The complexity of haloperidol pharmacokinetics indicates that knowledge of CYP2D6 genotype is unlikely to be helpful clinically.
c. Perphenazine.
Perphenazine is primarily metabolized to N-dealkylperphenazine, perphenazine sulfoxide, and 7-hydroxyperphenazine, with the activity of the latter metabolite comparable with that of the parent in vitro (the activity of the other metabolites is not clear) (Hals et al., 1986). CYP2D6 metabolizes perphenazine in vitro (Olesen and Linnet, 2000), and an in vivo study showed a 4-fold higher perphenazine AUC in PMs after a single dose (Dahl-Puustinen et al., 1989). Similarly, steady-state studies demonstrated a 2-fold higher median AUC (Linnet and Wiborg, 1996b) and a 3-fold decrease in clearance (Jerling et al., 1996) in PMs. The strong CYP2D6 inhibitor, paroxetine, increased the AUC 7-fold in EMs and was associated with a significant increase in central nervous system symptoms (sedation, extrapyramidal symptoms, and psychomotor performance) (Ozdemir et al., 1997). In elderly patients with dementia, perphenazine 0.05 to 0.1 mg/kg/day led to improved psychotic symptoms overall without any difference between EMs (n = 40) and PMs (n = 5). However, PMs had significantly more side effects (primarily extrapyramidal and sedative) early in treatment that became similar in both phenotypes by day 17 of dosing (Pollock et al., 1995). Overall, the intergroup differences in perphenazine AUC suggests possible clinical relevance, although the failure to measure the active metabolites in vivo dilutes this somewhat. However, considerable overlap in concentrations exists between CYP2D6 groups, which is likely to decrease the value of prospective genotyping or phenotyping.
d. Thioridazine.
The production of mesoridazine, the first metabolite (also known as thioridazine 2-sulfoxide), correlates weakly with the debrisoquine metabolic ratio (Llerena et al., 2000, 2002; Berecz et al., 2003), whereas the subsequent metabolite sulforidazine (thioridazine 2-sulfone) does not seem to be reliant on CYP2D6 (von Bahr et al., 1991; Eap et al., 1996). The metabolites seem to have activity equal to (sulforidazine) or greater (mesoridazine) than that of the parent (Kilts et al., 1984), whereas a further ring sulfoxide (thioridazine 5-sulfoxide) produced from thioridazine may be less active as an antipsychotic, but more arrhythmogenic (Hale and Poklis, 1986). After a single dose, the sum of active moieties (thioridazine + mesoridazine + sulforidazine) was 1.4-fold higher in PMs, largely due to a 4.5-fold increase in thioridazine itself (von Bahr et al., 1991). Consistent with this, the dose-corrected median steady-state plasma thioridazine concentrations were 3.8- and 1.8-fold higher in the presence of no or one active CYP2D6 alleles, respectively, compared with two active alleles. Median concentrations of mesoridazine and sulforidazine were not statistically different (Berecz et al., 2003).
There are limited data on CYP2D6 and adverse effects. A case report described marked oversedation with high thioridazine concentrations in a PM (Meyer et al., 1990). One study reported a weak correlation between QTc interval and thioridazine plasma concentrations, debrisoquine metabolic ratio, and thioridazine/mesoridazine concentrations (r = 0.3 for each comparison) (Llerena et al., 2002). However, contradictory findings were found in another study in which QTc interval correlated with plasma concentrations of thioridazine, mesoridazine, and sulforidazine, but no relationship with CYP2D6 genotype was seen (Thanacoody et al., 2003). Dahl (2002) concluded that CYP2D6 is of importance, based on the study of von Bahr et al. (1991). However, the evidence for this conclusion seems poor, and the likelihood of clinical relevance low, given the multiple metabolic pathways, interindividual variability in pharmacokinetics, and the phenocopying in up to 80% of patients (Llerena et al., 2001; Berecz et al., 2003). Further confusing the picture is the presence of R- and S-enantiomers of thioridazine (and the metabolites), which have differing pharmacological activities (Eap et al., 1996).
e. Zuclopenthixol.
The metabolic profile of zuclopenthixol is unclear, although CYP2D6 is involved (Dahl et al., 1991; Jerling et al., 1996; Jaanson et al., 2002). After depot administration, median plasma concentrations were 1.6- and 1.4-fold higher in PMs and heterozygous EMs, respectively, than homozygous EMs (Jaanson et al., 2002). No increase in tardive dyskinesia was seen in this study (n = 52). Clearance was 2.2- and 1.5-fold higher in homozygous and heterozygous EMs, respectively, than in PMs at steady-state (Jerling et al., 1996), whereas a 1.9-fold higher AUC was seen in PMs after a single-dose (Dahl et al., 1991). Overall, the data suggests a gene-concentration effect but nothing convincing for clinical effects.
f. Atypical antipsychotics.
Of this class, risperidone is the most well studied with respect to CYP2D6 which, together with other P450s, e.g., CYP3A (Odou et al., 2000; Yasui-Furukori et al., 2001), produces a metabolite with comparable activity, 9-hydroxyrisperidone (Mannens et al., 1993; van Beijsterveldt et al., 1994). 9-Hydroxyrisperidone is further metabolized by N-dealkylation, possibly by CYP3A (Spina et al., 2000). The ratio of risperidone to 9-hydroxyrisperidone concentrations is <1 in EMs, and >1 in PMs, but the sum of active moieties is similar (Mannens et al., 1993; Nyberg et al., 1995a; Olesen et al., 1998; Scordo et al., 1999; Roh et al., 2001b; Bondolfi et al., 2002). UMs have very low ratios of risperidone to 9-hydroxyrisperidone (Guzey et al., 2000). Limited data associate PM status with increased risperidone adverse effects. In particular, a large (n = 500) cross-sectional study reported a 3-fold increased risk of moderate-to-severe adverse effects in PMs. However, PMs comprised only a small proportion (16%) of all individuals with adverse effects and only 9% of those who stopped risperidone because of toxicity were PMs. Thus, genotyping is only likely to be helpful in identifying individuals who might be at elevated risk of side effects and could benefit from closer monitoring (Rau et al., 2004). Overall, studies strongly support a gene-concentration effect, but similar activity between the parent and primary active metabolite may negate the effect of the altered ratio.
None of the more established atypical antipsychotics (clozapine, olanzapine, or quetiapine) are extensively metabolized by CYP2D6, with other enzymes such as CYP1A2 and CYP3A playing more important roles (Ring et al., 1996; Olesen and Linnet, 2001; Li et al., 2005). For example, the CYP2D6 phenotype did not correlate with the olanzapine AUC after a single dose (Hagg et al., 2001) or plasma concentrations at steady state (Carillo et al., 2003). CYP2D6 polymorphism is unlikely to be important for these compounds.
g. Antipsychotics (in general) and clinical outcomes.
Results of the studies investigating a relationship between CYP2D6 and parkinsonism or tardive dyskinesia with traditional antipsychotics have been conflicting (Andreassen et al., 1997; Armstrong et al., 1997; Kapitany et al., 1998; Ohmori et al., 1998; Hamelin et al., 1999; Vandel et al., 1999; Schillevoort et al., 2001; Mihara et al., 2002). This may be due to methodological issues such as small sample size, inclusion of antipsychotics with variable CYP2D6 metabolism, and phenocopying due to the antipsychotic or concurrent drug therapy. A recent meta-analysis showed a small, but significant, 1.4-fold (95% CI 1.06, 1.93) increased risk of tardive dyskinesia in PMs (Patsopoulos et al., 2005). This is perhaps the most significant and problematic side effect of this class, although the small increased risk in PMs does not seem to support routine prospective genotyping. A pilot study of 100 psychiatric inpatients showed a trend for increasing adverse reactions with CYP2D6 drugs (haloperidol, perphenazine, risperidone, and TCAs) from the UM to
