Variability in Cytochrome P450-Mediated Metabolism ...

Review Received: July 4, 2003 Accepted after revision: November 24, 2003 Published online: February 20, 2004

Heart Drug 2004;4:55–79 DOI: 10.1159/000076934

Variability in Cytochrome P450-Mediated Metabolism of Cardiovascular Drugs: Clinical Implications and Practical Attempts to Avoid Potential Problems Espen Molden Department of Pharmacology, School of Pharmacy, University of Oslo, Oslo, Norway

Key Words Cardiovascular drugs W Cytochrome P450 W CYP W Drug interactions W Genetic polymorphism

Abstract Cytochrome P450 (CYP) enzymes play an important role in the turnover of more than 50 cardiovascular drugs (CVDs). Variable CYP activities due to genetic polymorphism or drug interactions are important sources of variability in systemic exposure of many of these drugs. The therapeutic implications are in most cases an increased response (effect/side effects) in patients with genetically determined decreased/deficient metabolic activity or during concurrent use of CYP inhibitors. Special attention with regard to safety should be paid to several coumarin-type anticoagulants, antiarrhythmics, ß-receptor antagonists and HMG-CoA reductase inhibitors (statins). Prevention of potential clinical problems associated with CYP variability is easily achieved using equally effective therapeutic alternatives that are not dependent on CYP metabolism. However, if ‘CYP sensitive’ CVDs are either the preferred or only therapeutic alternatives, restrictive use of inhibitors is advisable, whereas patient genotyping prior to treatment might be a helpful tool to apply rational (individual) doses for certain agents. Copyright © 2004 S. Karger AG, Basel

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Introduction

Most cardiovascular drugs (CVDs) are aimed at preventing future events, which implies lifelong treatment. Thus, a major challenge is to obtain both optimal effect on surrogate end points and good tolerability. The purpose of recommended drug-dosing schedules is for the patients to achieve these goals. It is well known, however, that patients, despite similar drug-dosing schedules, may differ substantially in the therapeutic response to CVDs, either due to patient characteristics or susceptible drug combinations. The impact of this variability might be drug-induced morbidity expressed as unpleasant or harmful side effects, or on the other hand lack of drug-prevented morbidity due to insufficient effect. In any circumstance, the net result is unsatisfactory for the patient and it might also be negative for economic reasons (hospital admissions due to adverse drug events or payment for ineffective treatment). The recent withdrawals of the HMG-CoA reductase inhibitor cerivastatin and the calcium channel blocker mibefradil, motivated by many reports of severe drug toxicity and even deaths in certain drug combinations [1, 2], illustrate the gravity of these issues and that they also may imply big economical losses for the pharmaceutical companies. Individual variability in drug response reflects patient differences in terms of pharmacokinetics (drug exposure)

Espen Molden Department of Pharmacology, School of Pharmacy, University of Oslo NO–0316 Oslo (Norway) Tel. +47 22857578, Fax +47 22854402 E-Mail [email protected]

Fig. 1. Cellular localization of CYP en-

zymes.

and/or pharmacodynamics (drug sensitivity). Whereas newly discovered genetic polymorphisms of several drug target proteins (e.g. ß1-receptor [3]) seem to be important in explaining occurrences of nonresponse, pharmacokinetic differences are most frequently the basis for excessive or toxic drug effects. Since metabolism is a crucial process in both restricting systemic availability (bioavailability) and facilitating systemic elimination (clearance) of many drugs, individual variability in drug-metabolizing capacity is a major source of differences in drug exposure. Enzymes of the cytochrome P450 (CYP) superfamily are quantitatively the most important drug-metabolizing enzymes, and it has been estimated that more than 50% of all drugs are CYP substrates [4]. CYP enzymes are highly expressed in the endoplasmatic reticulum of cells in the liver and intestine. Here, they play a protective function by turning potentially toxic compounds (xenobiotics) into more hydrophilic, usually less active metabolites (fig. 1). The CYP enzymes are divided into families and subfamilies across different species according to genetic sequence homology. Homology greater than approximately 40% congregates enzymes into families (indicated by the first Arabic numeral after ‘CYP’, e.g. CYP3), whereas homology exceeding approximately 60% assembles enzymes into subfamilies (indicated by the capital letter, e.g. CYP3A). The final Arabic numeral (e.g. CYP3A4) denominates the individual enzyme, called isoform, isoenzyme or isozyme. Mammalian species differences are often seen at this final level; for example, rats and humans express CYP3A2 and CYP3A4, respectively, as their major CYP3A isforms. When describing the CYP gene, all letters and numerals are written in italic (e.g. CYP3A4 encodes the CYP3A4 protein), while an added asterisk (*)-number combination indicates a certain allelic variant.

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In humans, almost 60 different CYP enzymes have been described [5], but only a few are important in drug metabolism. The enzymes CYP1A2, CYP2C8, CYP2C19, CYP2C9, CYP2D6 and CYP3A4 are all important, and a common feature is their ability to metabolize a wide range of structurally different compounds. This makes the enzymes effective as protectors against xenobiotics. However, variability in their activities (phenotypes) will have a great impact on the systemic exposure of many drugs. Variable CYP activity could be determined by genetic or environmental factors, the latter including enzymatic interference of coadministered drugs (drug interactions). The majority of the CYP variability caused by genetic polymorphism leads to decreased or deficient activity, but increased activity has also been described. Similarly, most CYP interactions are inhibitory in nature, leading to decreased metabolism of the affected drug by the inhibitor. However, some drugs act as inductors of CYP enzymes and may speed up the metabolism of coadministered agents. The specific CYP enzymes mentioned in the previous paragraph are collectively involved in the metabolism of more than 50 CVDs, when including antidiabetics in this group (table 1). For most of these drugs, their major effect is mediated through the parent compound (administered form), such as the calcium channel blocker felodipine (fig. 2A). Then, decreased or deficient activity of the CYP of relevance will result in an increased pharmacological response, and vice versa if the activity is increased. By having the status of a ‘prodrug’, the angiotensin II receptor antagonist losartan is an example of the opposite type (fig. 2B). The HMG-CoA reductase inhibitor atorvastatin is an example of a more complex situation, where both the parent drug and a metabolite mediate relevant activity (discussed later). Sometimes, toxic metabolites are produced by CYP enzymes, as for dihydralazine through a

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Table 1. Overview of CVDs in relation to CYP enzymes involved in their metabolism

CYP1A2

CYP2C8

CYP2C9

CYP2C19

CYP2D6

CYP3A4

Acenocoumarol Dihydralazine1 [6] Mexiletine Propranolol Warfarin

Repaglinide Rosiglitazone [9] Tolbutamide [10] Troglitazone [12] Verapamil [15]

Acenocoumarol Candesartan Carvedilol [11] Fluvastatin Gliclazide [16] Glimepiride Glipizide Glyburide Irbesartan [20] Losartan2 Nateglinide Phenprocoumon [24] Pioglitazone1 [14] Tolbutamide Torasemide [27] Warfarin

Ticlopidine1 [7]

Alprenolol [8] Carvedilol Diltiazem3 Encainide2 Flecainide Gliclazide [16] Indoramin Metoprolol Mexiletine Procainamide1 [22] Propafenone Propranolol Tamsulosin [19] Timolol

Amlodipine Amiodarone Atorvastatin Bisoprolol [13] Bosentan Clopidogrel2 [17] Disopyramide [18] Diltiazem Dorzolamide [21] Eplerenone [23] Felodipine Isradipine [25] Lidocaine [26] Lovastatin Nicardipine Nifedipine Nimodipine Nisoldipine Nitrendipine Pioglitazone [14] Quinidine Repaglinide Simvastatin Tamsulosin [19] Troglitazone1 [12] Verapamil Vesnarinone

References have only been included if no pharmacogenetic and/or interaction studies implying involvement of the enzyme are presented in this article. 1 A metabolite that mediates drug toxicity is produced by the indicated enzyme. 2 A metabolite that mediates the principal pharmacological response is produced by the indicated enzyme. 3 The indicated enzyme is important in subsequent metabolism of pharmacologically active metabolites, but not the parent drug.

CYP1A2-mediated metabolite that triggers an immune response when bound to the CYP enzyme [6]. To what extent variable CYP activity will predict the exposure of a certain CVD depends on the relative importance of the affected CYP enzyme for the overall turnover. Thus, multiple routes of elimination (metabolic or nonmetabolic) will generally reduce the pharmacokinetic sensitivity to variability of a certain CYP activity. However, the therapeutic importance of variable CYP activity is not solely dependent on the pharmacokinetic sensitivity, but certainly also the clinical/pharmacodynamic sensitivity (i.e. the drug’s therapeutic index). Warfarin is an example of a clinically sensitive drug, where small changes in exposure could still be of importance. HMGCoA reductase inhibitors are examples of CVDs with con-

siderably lower clinical sensitivity, and more extensive changes are required to be of importance. Undoubtedly, variability in CYP activities contributes to individual differences in the response of many CVDs. The purpose of this review article is to give a comprehensive but compact presentation of the reported CYP-determined variability in exposure of CVDs with the main focus on genetics and inhibitory interactions. Based on this material, clinical implications of the variability are discussed. In the final part, practical attempts to prevent potential CYP-related problems are outlined.

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57

A

Cl

B N

Cl

CH3

Cl N

H5C2OOC

COOCH3 OH

H3C

Felodipine (active)

HN

N H

N

Losartan (inactive)

N

CYP2C9

CYP3A4

Cl

N

Cl

Fig. 2. Structures of felodipine (A), a dihy-

dropyridine calcium channel blocker, and losartan (B), an angiotensin II receptor antagonist, and their main metabolites (principal active forms and enzymes involved in turnover are indicated).

H3C

All tabulated information regarding CYP variability and influence on exposure of CVDs is derived from pharmacokinetic results published in human clinical studies available on PubMed. When searching for genetic studies in relation to CYP2C8, CYP2C9, CYP2C19 and CYP2D6 activity, substrates of the respective enzymes (table 1) were matched with each of the following words: ‘genotyping’, ‘genotype’ and ‘enzyme name’ (e.g. CYP2D6). In addition, the words ‘debrisoquine’, ‘sparteine’, ‘dextromethorphan’, ‘phenotype’ and ‘phenotyping’ were applied for CYP2D6. Pharmacokinetic interaction studies between substrates and inhibitors of CYP enzymes were found by matching substrates (table 1) and inhibitors of the respective enzymes. All searches in PubMed were restricted to Title/Abstract and English language. Only studies with peroral administration of drugs were used to extract pharmacokinetic data. The values of relative systemic exposure (‘relative systemic dose’, presented

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N

COOH

-3174 E-3174 (active)

Dehydrofelodipine (inactive)

Literature Search and Pharmacokinetic Data Extraction

58

COOCH3

CH3 N

Cl H5C2OOC

N

HN N N

N

as ratios) are calculated from mean or median data for the dose-adjusted area under the plasma concentration-versus-time curve (AUC), steady-state plasma concentration (Css) or peroral clearance (Cl/F). If multiple studies on similar issues were found, results are presented as ranges of the reported mean or median values. Neither drug doses, time intervals of treatment, size nor type of population (sex, age, healthy/patient etc.) have been indicated in the tables, but these factors could affect the outcomes.

Influence of CYP Genetics on CVDs

Basic Considerations regarding CYP Genetics The first CYP enzymes discovered to express phenotypic differences due to genetic polymorphism were CYP2D6 and CYP2C19 in the 1970s [28]. Later, genetic polymorphism with a major influence on enzyme activity was disclosed for CYP2C9 [29], and recently, mutations coding for altered activity of CYP2C8 were reported [30– 33]. No important activity-determining mutations have so far been described for CYP3A4 [34]. Regarding

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Table 2. Overview of mutated CYP alleles that code for reduced or deficient enzyme activity and their estimated allele frequencies in different populations

Enzyme

Allele

Activity

Estimated population allele frequencies, % Afr

Afr-Am

Cau

Jap

18.0 2.0

0 11.3 7.5

0 0 0

Spa/Por

Tur

10.6 10.0

CYP2C8

2C8*2 2C8*3 2C8*4

decreased decreased decreased

CYP2C9

2C9*2 2C9*3

decreased decreased

4.3 2.3

1.0 0.5

11.3 6.7

0 2.1

14.31 16.21

CYP2C19

2C19*2 2C19*3

deficient deficient

16.6 1.0

28.6 0

19.2 0.1

27.5 12.6

13.02

CYP2D6

2D6*3 2D6*4 2D6*5 2D6*6 2D6*9 2D6*10 2D6*17

deficient deficient deficient deficient decreased decreased decreased

0 3.1 2.8 0 0 4.9 21.0

0.4 7.5 6.4 0.4 0.3 5.0 21.6

1.6 19.4 4.1 1.0 2.2 2.4 0.1

0.5 5.4

2.41 11.61 1.61 1.71

38.8

0 11.3 1.5 0.7 0.6 6.1 0.1

Data for CYP2C8 are drawn from original articles [30–33], whereas information about CYP2C9, CYP2C19 and CYP2D6 is based on review articles [29, 36, 37]. Note that the number of individuals in which the allelic frequency estimates are calculated was highly variable and that the frequencies may show relevant differences within the classified populations. Afr = Africans; Afr-Am = African-Americans; Cau = Caucasians; Spa = Spanish1; Por = Portuguese2; Tur = Turkish.

CYP1A2, inducibility has mainly been linked to genetic polymorphism [35]. Apart from the inducibility of CYP1A2 and a functional allele of CYP2D6 (i.e. 2D6*2n) with multiplying abilities (basis for the ultrarapid CYP2D6 phenotype), all CYP mutations have been reported to encode decreased or deficient enzyme activities [29–33, 36, 37]. These are presented for CYP2C8, CYP2C9, CYP2C19 and CYP2D6 in table 2, but it should be noticed that there is uncertainty about the influence of some mutations on the in vivo phenotypes of the two former enzymes (CYP2C8 and CYP2C9). Interestingly, there are substantial interethnic differences in the frequencies of the mutated alleles (table 2). Variable interethnic phenotypes could therefore be expected, implying that the mean exposure after similar dosing of certain drugs may differ between different populations. To illustrate how the distributions of different genotypes could be estimated from allele frequencies, CYP2D6 polymorphism in Caucasians is used as an example. From table 2, it can be concluded that the total frequency of deficient alleles in Caucasians is approximately 26% (0.26). According to the Hardy-Weinberg principle for

diploid inheritance, the proportion with homozygous CYP2D6 allele deficiency is 0.262 (0.068, 6.8%), which corresponds to the fraction of CYP2D6 poor metabolizers (PMs) among Caucasians. Those with homozygous CYP2D6 wild-type (wt) genotypes [denominated extensive metabolizers (EMs)] are approximately 55% (0.742) of Caucasians. The fraction carrying one deficient and one functional CYP2D6 allele is 2 ! 0.26 ! 0.74 = 0.38 (38%; based on the Hardy-Weinberg principle), and these make up the subpopulation of heterozygous EMs. In the literature search, no studies investigating the role of CYP2C19 genetics on variability in exposure of CVDs (i.e. ticlopidine) were found. However, a number of studies on the disposition of CVDs in relation to genetic polymorphism of CYP2D6 and CYP2C9 have been published, as well as a single study in relation to CYP2C8 (repaglinide). These are presented and discussed in the following two subsections. For CYP2D6, some studies have used genotyping to separate populations into different subgroups, whereas others have used phenotyping (with probe compounds, i.e. dextromethorphan and others). These approaches are considered equivalent in separating CYP2D6 PMs and EMs, because there is a well-

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Table 3. Relative systemic exposure (‘relative systemic dose’) re-

ported for CVDs in CYP2D6 PMs or IMs compared to EMs Drug

PMs (*3–6/*3–6)

Carvedilol1

2.2 (R/S) 1.4 (S) [38] 65 [39] ^0.2 [40–43] 1.2–3.0 [44–48] 16.9 [49] 3.1–7.8 (R/S) [50–54] 1.4–2.1 [56–59] 1.9–7.9 (R/S) [59–64] 1.0 (R/S) [68, 69] 1.8–2.1 (S) [72, 73]

Diltiazem2 Encainide3 Flecainide Indoramin Metoprolol1 Mexiletine Propafenone1 Propranolol1 Timolol1

IMs (*10/*10)

2.8–4.4 (R/S) [54, 55] 1.7–2.1 (R/S) [65–67] 2.3 (R/S) [70, 71]

Data are derived from dose-adjusted mean or median values for AUC, Css or Cl/F. Ranges are lowest to highest ratios calculated from mean/median values in different studies. 1 ß-Receptor antagonism is mediated by S-enantiomers. 2 Data represent desacetylated metabolites (active together with diltiazem). 3 Data represent O-demethylencainide (principal active form of encainide treatment).

established, close association between genotype and phenotype for CYP2D6. However, phenotyping is not ideal for separating CYP2D6 homo- and heterozygous EMs, and many studies using phenotyping do therefore have a mixture of homo- and heterozygous EMs collectively denominated ‘EMs’. For CYP2C9, the association between genotype and phenotype is poorer than for CYP2D6, and all genetic CYP2C9 studies found were based on genotyping. Hence, the data for exposure variability of CVDs in relation to CYP2C9 (and CYP2C8) activity are presented for hetero- and/or homozygous mutated genotypes compared to homozygous wt individuals. CYP2D6 Genetics and Variability in Exposure of CVDs Studies investigating the variability in exposure in relation to CYP2D6 genetic polymorphism were found for 10 different CVDs (table 3). For metoprolol, a frequently used selective ß1-receptor antagonist, PMs do have about 3- to 8-fold higher dose-adjusted systemic exposure compared to EMs [50–54]. In Orientals, the exposure of metoprolol has been reported to be approximately 3–4 times higher in individuals with homozygous 2D6*10 genotype (intermediate metabolizers; IMs) [54, 55], who comprise approximately 15–20% of Orientals

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(table 2). Metoprolol is used clinically as a racemate (50/ 50 mixture of R- and S-enantiomers; R/S), but only the S-enantiomer is active. It has been shown that the exposure of the S-enantiomer is dependent on CYP2D6 activity to the same extent as the sum of the enantiomers (R/S) [51, 55]. Moreover, the therapeutic response of metoprolol has been clearly associated with the patient’s CYP2D6 activity. In a recent investigation, Wuttke et al. [74] found that the risk for adverse effects of metoprolol was 5 times higher in Caucasian (German) CYP2D6 PMs than EMs, indicating that doses in practice are not properly individualized based on patient (clinical) monitoring. Individual CYP2D6 activity does not affect the systemic exposure of other ß-receptor antagonists to similar extents as metoprolol. Carvedilol has mixed pharmacological effects by being both a ß1/2-receptor (S-mediated) and ·1-receptor (R/S-mediated) antagonist. Whereas the exposure of the S-enantiomer was increased by about 40%, the sum of the enantiomers was approximately 2 times higher in CYP2D6 PMs in a single study [38]. The clinical implications for patients of these findings have not been outlined, but an approximately 50–100% difference in exposure (‘dose’) must empirically be considered as relevant. For propranolol (ß1/2-receptor antagonist), it is surprising that the exposure was reported to be unaffected by CYP2D6 activity in Caucasians (PMs versus EMs) [68, 69], whereas a 2-fold higher level was observed in Chinese IMs [70, 71]. This might indicate that another eliminating pathway(s) than CYP2D6 (e.g. CYP1A2) is relatively more important in propranolol metabolism in Caucasians than in Orientals. The cardiovascular use of timolol is probably sparse. Nevertheless, both timolol’s exposure and ß-blockade has been shown to be dependent on individual CYP2D6 activity [72, 73]. The antiarrhythmic agent propafenone exhibits both ß-receptor antagonism (S-enantiomer) and sodium channel blocking activity (both enantiomers). The sum of propafenone enantiomers has been reported to be elevated approximately 2- to 8-fold and 2-fold in CYP2D6 PMs and IMs (table 3), respectively, and this clearly affects the response of propafenone [59–67]. Mexiletine and flecainide exposure is to a lesser extent dependent on CYP2D6 activity (table 3), but more pronounced effects/side effects per dose-equivalent might still be expected for these antiarrhythmics as well. For encainide, the situation is opposite, as this compound is metabolized to its principal active form (O-desmethylencainide) via CYP2D6. A single study reported that the systemic exposure of the ·1-receptor antagonist indoramin was approximately 17 times higher in CYP2D6 PMs [49]. In this study,

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Table 4. Relative systemic exposure (‘relative systemic dose’) reported for CVDs in individuals with different CYP2C9 mutated genotypes compared to individuals with homozygous wt genotypes

Drug

wt/*2

*2/*2

Acenocoumarol1

Candesartan Fluvastatin Glimepiride Glipizide Glyburide Losartan3 Tolbutamide Warfarin1

1.0 [81] 1.1 [82]

1.2 [81]

1.0–1.1 [82, 84] 1.0–1.3 [85, 86] 1.1 [88] 1.1 (R/S) 1.0 (R) 1.0–1.7 (S) [90–92]

1.3 [84] 0.9 [85] 1.3 [88] 0.9–1.0 (R) 0.6–3.1 (S) [91–93]

wt/*3 2.7 (R/S) 2.0 (R) 16.3 (S) [79] 2.5 [80] 1.5 [81] 2.72 [82] 1.4–2.82 [82, 84] 0.6–1.2 [85–87] 1.7–1.9 [88, 89] 1.6 (R/S) 1.1–1.2 (R) 1.0–2.7 (S) [90–93]

*2/*3

*3/*3

2.3 [81]

4.2 [81]

1.7 [84] 0.5 [85] 2.2 [88]

5.5 [83] 2.3 [84] ! 0.1 [85] 6.5 [88]

1.1 (R) 3.5–4.3 (S) [91, 92]

1.5 (R) 9.3–10.8 (S) [91, 92]

Data are derived from dose-adjusted mean or median values for AUC, Css or Cl/F. Ranges are lowest to highest ratios calculated from mean/median values in different studies. 1 S-Enantiomers are more potent than R-enantiomers. 2 The ratios are calculated from a combined group of wt/*3 and *2/*3 genotypes. 3 Data represent E-3174 (principal active form of losartan treatment).

where only a single indoramin dose (50 mg) was administered to healthy subjects, a tendency of a higher incidence of side effects (e.g. sedation) was observed among PMs. Diltiazem is an unselective calcium channel blocker, with both the parent drug and metabolites being active. Interestingly, the levels of deacetylated diltiazem metabolites are strongly related to CYP2D6 activity (increased 65fold in PMs), whereas the parent compound is unaffected [39]. When weighing the total exposure of diltiazem and its metabolites against their reported activities, it could be estimated that CYP2D6 PMs might have approximately 50–100% higher vasodilating activity compared to EMs. None of the HMG-CoA reductase inhibitors (statins) have been shown to be substrates for CYP2D6. However, two studies have investigated the clinical effect of simvastatin on cholesterol reduction in relation to CYP2D6 phenotype/genotype [75, 76]. In both studies, an increased lipid-lowering effect was observed with declining CYP2D6 activity. Since in vitro studies have indicated that simvastatin is not metabolized by CYP2D6 [77], authors of the phenotype/genotype studies suggested that active metabolites of simvastatin could be CYP2D6 substrates, in a fashion similar to that outlined for diltiazem and its metabolites. However, others have claimed that CYP2D6 activity does not predict the lipid-lowering

response of simvastatin [78], but this statement is based on unpublished results. Nevertheless, this dispute makes it of great importance to clarify if the therapeutic response of one of the world’s most frequently used drugs is related to CYP2D6 genetics or not. This should be performed in a study where pharmacokinetics (parent drug and metabolites), CYP2D6 phenotype/genotype and clinical outcomes are measured concurrently.

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CYP2C9 Genetics and Variability in Exposure of CVDs Of the 15 CVDs indicated in table 1 as substrates for CYP2C9, the systemic exposure of 8 had been investigated in relation to genetics of this enzyme (table 4). All coumarin-type antiocoagulants (coumarins) are CYP2C9 substrates and of particular interest due to their high clinical sensitivity (narrow therapeutic index). Variability in systemic exposure related to CYP2C9 genotype has been reported for both acenocoumarol and warfarin, but no studies were found for phenprocoumon. Coumarins are used as racemates, and the S-enantiomers are more active as inhibitors of the target enzyme, vitamin K epoxide reductase. However, the R-enatiomers are also active and of importance, due to generally higher exposure than the S-forms.

61

From the studies that have investigated the influence of CYP2C9 polymorphism on the pharmacokinetics of warfarin [90–93], it can be concluded that individuals with the 2C9*3 mutant have elevated dose-adjusted Swarfarin exposure. Regarding the influence of the 2C9*2 mutation, it is difficult to make a conclusion, since one study actually reported faster metabolism of S-warfarin in homozygous 2C9*2 subjects [92]. However, all results evaluated together indicate that 2C9*2 is of importance for S-warfarin exposure, but far less than 2C9*3 (table 4). For acenocoumarol, a 2- and 16-fold higher exposure of the R- and S-form, respectively, was reported in a heterozygous 2C9*3 individual compared to a homozygous wt individual (only one person of each genotype) [79]. The ratio between the R-form and S-form was approximately 15 in the homozygous wt individual and approximately 2 in the heterozygous 2C9*3 individual. Acenocoumarol data were not found in relation to the 2C9*2 mutant. Several studies have tried to link CYP2C9 genotypes to the individual dose requirements of different coumarins to achieve target INR, as well as the incidence of adverse events. For warfarin, a clear relationship between individual dose requirement and CYP2C9 genotype has been established (2C9*3 1 2C9*2, but both relevant) [94]. However, it is important to notice that a great variability in dose requirements is observed within each genotype, indicating a significant role of environmental factors as well. The relationship between CYP2C9 genotype and dose requirements of acencoumarol and phenprocoumon have been studied to a lesser extent, but both drugs show trends similar to warfarin [95, 96]. Since the anticoagulant effect is closely monitored and doses are adjusted in accordance with the therapeutic response, it is difficult to measure the genotypic influence on the incidence of adverse events. However, elevated initial-dose INR, longer time to achieve stable dosing and more bleeding events have been registered among patients carrying mutated CYP2C9 alleles [94]. Empirically, it is also reasonable to believe that intake of higher coumarin doses than prescribed (noncompliance etc.) is more risky in individuals with mutated CYP2C9 alleles (especially 2C9*3), because these patients would have a steeper dose-exposure relationship than homozygous wt patients. Fluvastatin is the only HMG-CoA reductase inhibitor subjected to relevant metabolism by CYP2C9. Recently, it was shown that fluvastatin exposure was approximately 1.5 and 4 times higher in individuals with heterozygous and homozygous 2C9*3 genotypes, respectively [81]. The safety profile of fluvastatin could therefore be related to the presence of the 2C9*3 allele. For fluvastatin, 2C9*2

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was apparently not an important source of variability in its exposure. Genetic CYP2C9 polymorphism is clearly of relevance for the sulfonylurea antidiabetic drugs [82–84, 88, 89]. However, it seems evident that only the 2C9*3 mutation is a predictor for their pharmacokinetic variability. Roughly a doubling or more in the systemic exposure of glimepiride, glipizide, glyburide (INN, glibenclamide) and tolbutamide could be expected in patients carrying 2C9*3 (table 4), which corresponds to approximately 4– 5% of African or Japanese, 10–15% of Caucasian, 15– 20% of Turkish and 25–30% of Spanish patients (table 2). All studies with the sulfonylureas have been performed in a limited number of healthy subjects, and the data are therefore not optimal to evaluate the influence of 2C9*3 on glucose and/or insulin levels. However, in the study with glyburide, statistically higher insulin levels were observed in 2C9*3 carriers [84]. This could indicate an elevated risk for hypoglycemia among individuals with 2C9*3. The angiotensin II receptor antagonist losartan is metabolized through CYP2C9 to a metabolite (E-3174) with more than 10 times the activity of the parent drug. E-3174 has a longer elimination half-life than losartan, and their mean exposure is of the same magnitude. Thus, E-3174 is the principal mediator of the pharmacological effect(s) of losartan treatment. Yasar et al. [85] studied the exposure of E-3174 in different CYP2C9 genotypes after administration of a single losartan dose (50 mg), and in common with fluvastatin and the sulfonylureas (table 4), it was clearly observed that metabolism was affected by 2C9*3, but not 2C9*2. In heterozygous 2C9*3 subjects, the E3174 level was only about one half that of homozygous wt subjects [85]. Only one individual with the homozygous 2C9*3 genotype was included in the study, but this subject had less than one tenth the E-3174 exposure of homozygous wt values. Based on these results, a poor response of losartan could be expected in 2C9*3 carriers. This might be particularly problematic in patients with heart failure and diabetic nephropathy who are treated with losartan, as clinical monitoring of the effect is more complicated for these conditions than the blood pressure response. However, whether heterozygous 2C9*3 carriers actually would experience relevantly lower levels of E3174 has been questioned by two recent studies [86, 87]. In these latter studies, the active metabolite was 20% lower [87] and 20% higher [86], respectively, in individuals with 2C9wt/*3 genotypes compared to homozygous wt genotypes. The studies with losartan were carried out in subjects from three different geographical areas (Sweden,

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USA and Japan). The diverging data could therefore indicate that in some instances, environmental factors might overrule the importance of the CYP2C9 genotype for its phenotype. Candesartan (hydrolyzed, active form of candesartan cilexetil) and irbesartan are further angiotensin II receptor antagonists that are subjected to metabolism via CYP2C9. Neither of these agents are metabolized to products with relevant activity via CYP2C9, and reduced activity of this enzyme may therefore imply an increased response. It has been suggested that CYP2C9 is of limited importance for the overall metabolism of candesartan, but it was recently reported that a patient (89 years old) genotyped as heterozygous 2C9*3 experienced 2.5-fold higher exposure of candesartan, and an excessive blood pressure response, compared to homozygous 2C9wt elderly controls [80]. These findings are interesting, but larger studies should be performed to confirm the importance of CYP2C9 activity for the pharmacokinetics and response of candesartan. Pharmacokinetic studies in relation to CYP2C9 genotypes have not been performed with irbesartan. However, a study was recently published where the aim was to investigate the association of the blood pressure response to irbesartan and CYP2C9 genotype in patients with essential hypertension. Surprisingly, a greater blood pressure reduction was observed in patients with wt/*2 genotypes compared to homozygous wt patients, and the differences were statistically significant for diastolic blood pressure (–14.4 versus –7.5%, p = 0.036) [97]. The number of patients with 2C9*3-containing genotypes was too small to evaluate. Nevertheless, these results are clinically interesting and might indicate that exposure of irbesartan, in contrast to many other CVDs (table 4), is predicted by the 2C9*2 allele. Thus, pharmacokinetic studies with irbesartan should be performed to clarify this issue.

ide did not include homozygous mutated genotypes, additional studies are required before conclusions could be drawn about the influence of CYP2C8 mutations on phenotype.

Influence of Coadministered CYP Inhibitors on CVDs

CYP2C8 Genetics and Variability in Exposure of CVDs Mutations with possible importance for the CYP2C8 phenotype were recently discovered, and the only CVD substrate (and possibly also the only drug so far) that has been investigated in relation to CYP2C8 genotypes is repaglinide. In individuals with 2C8wt/*3 genotypes, it was actually reported that the exposure of repaglinide was about 40% lower than in homozygous wt individuals [98]. This might indicate that 2C8*3 encodes increased activity, which disagrees with in vitro data showing that the metabolism of paclitaxel was substantially reduced by the 2C8*3 variant [30]. However, as the study with repaglin-

Basic Considerations regarding CYP Inhibition Agents that within their therapeutic concentrations have the ability to reduce a certain substrate’s metabolism via a specific enzyme to a ‘relevant extent’ are classified as inhibitors. This does not necessarily mean that they will affect all drugs metabolized by the enzyme, but the potential is present. Drugs that are described as inhibitors of CYP enzymes are presented in table 5, but it is important to note that their inhibitory potencies per dose administered are variable. Some of these could also affect the disposition of concurrently used drugs through mechanisms other than enzyme inhibition (e.g. transport proteins in intestine and kidneys). Reversible inhibitory action on metabolic activity is due to occupation of the catalytic site (enzyme displacement; competitive inhibition) or inactivation through conformational alteration (noncompetitive inhibition) of the enzymes. As competitive CYP inhibitors are themselves substrates for the CYP, they may be sensitive to/inhibited by other inhibitors, and the term ‘inhibitor’ may therefore appear confusing. However, from a clinical point of view, it is important to be alert with drugs classified as CYP inhibitors, regardless of the inhibitory nature. Through the fascinating discovery that grapefruit juice contained CYP3A4 inhibitors, it became clear that dietary compounds could have an extensive influence on the metabolism of drugs. In 1989, Bailey et al. [131] reported an unexpected observation from an interaction study between the dihydropyridine calcium channel blocker felodipine and ethanol. In this study, grapefruit juice was used to mask the taste of the ethanol. During analyses of the serum samples, the authors registered that concentrations of felodipine were far beyond that of historical controls, both with and without ethanol. They suspected the vehicle (grapefruit juice) to be responsible for the increased bioavailability of felodipine, and this was confirmed in a study published in 1991 [132]. Later, the influence of grapefruit juice on many CYP3A4 substrate drugs has been extensively investigated. The results of these studies leave us thinking: What about potential dietary CYP inhibitors that we do not know about?

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63

Table 5. Drugs described as inhibitors of CYP enzymes CYP1A2

CYP2C8

CYP2C9

CYP2C19

CYP2D6

CYP3A4

Amiodarone [99] Cimetidine [103] Ciprofloxacin [106] Fluvoxamine [101] Mexiletine [112] Propafenone [112]

Gemfibrozil [100] Retinoic acid [9] Rosiglitazone [107] Sulfamethoxazole [109] Troglitazone [107] Trimethoprim [109]

Amiodarone Benzbromarone Fluconazole Fluvoxamine Phenytoin Sulfamethoxazole [109] Sulfaphenazole [115] Trimethoprim [109] Troglitazone [107] Valproate [119]

Fluoxetine [101] Fluvoxamine [101] Omeprazole [108] Ticlopidine [110]

Bupropion [102] Celecoxib [104] Diphenhydramine Fluoxetine [111] Hydroxychloroquine Metoclopramide [113] Paroxetine Propafenone Quinidine [118] Ritonavir [117] Terbinafine [121] Thioridazine [123] Ticlopidine [124]

Amiodarone [99] Amprenavir [105] Clarithromycin Diltiazem Erythromycin Fluconazole [114] Imatinib [116] Indinavir [117] Itraconazole Ketoconazole [120] Nefazodone [122] Nelfinavir Nicardipine [125] Ritonavir Roxithromycin [126] Saquinavir Telithromycin [127] Verapamil

References have not been included if inhibiton of CVDs considered as enzyme indicators/probes (i.e. simvastatin/CYP3A4, atorvastatin/CYP3A4, metoprolol/CYP2D6, losartan/CYP2C9, tolbutamide/CYP2C9, S-warfarin/CYP2C9) [128–130] is presented in the article.

Table 6. Relative systemic exposure (‘relative systemic dose’) of CVDs reported when coadministered with CYP3A4 inhibitors Substrates

Inhibitors Clarithro

Amlodipine Amiodarone Atorvastatin Bosentan Diltiazem Felodipine Lovastatin Nicardipine Nifedipine Nimodipine Nisoldipine Nitrendipine Quinidine Repaglinide Simvastatin Verapamil Vesnarinone

Diltiaz

Erythro

Gfj

Itracon

1.31 [138]

1.1–1.2 [134, 135] 1.5 [136] 2.52 [139]

2.5–3.33 [140, 141]

1.6 [133] 1.81 [137]

Ketocon

Nelfin

Rito/Saq

1.71 [142]

3.93 [143]

Verapam

2.3 [144] 2.5 [147] 3.62 [162] 1.5 [168]

1.5 [175] 1.4 [179] 4.84 [181]

3.93 [182]

1.1–1.2 [145, 146] 1.4–3.3 [132, 147–160] 6.3 [161] 1.6–5.03 [163, 164] 8.6–22.13 [165, 166] 1.6 [167] 1.4–2.0 [132, 169, 170] 1.5 [171] 3.1–4.1 [172, 173] 2.3 [174] 1.1 [176] 2.4 [177] 1.4 [180] 4.5–6.83 [183, 184] 18.64 [185] 1.1–1.4 [186–188]

1.3 [168]

1.5 [178] 6.11 [142]

32.23 [143] 2.83 [182]

1.5 [189]

Data are derived from dose-adjusted mean or median values for AUC, Css or Cl/F. Ranges are lowest to highest ratios calculated from mean/median values in different studies. Clarithro = Clarithromycin; Diltiaz = diltiazem; Gfj = grapefruit juice; Itracon = itraconazole; Ketocon = ketoconazole; Nelfin = nelfinavir; Rito/Saq = ritonavir/saquinavir (combination); Verapam = verapamil. 1 Based on serum HMG-CoA reductase inhibitory activity. 2 Based on total serum concentrations of acidic (active) and lactonic (inactive) forms. 3 Based on serum concentration of acidic form (active). 4 Based on serum concentration of lactonic form (inactive).

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When matching the substrates in table 1 with the inhibitors in table 5 (plus grapefruit juice), studies on potentially interacting combinations were found for the enzymes CYP3A4, CYP2D6, CYP2C9, CYP1A2 and CYP2C8 (only one single study). These are presented for each enzyme in the following subsections, including a discussion of therapeutic implications for the affected CVDs (selected examples of particular interest for CYP3A4). Relative Exposure of CVDs with CYP3A4 Inhibitors In total, 17 CVDs that are CYP3A4 substrates had been investigated in interaction studies with CYP3A4 inhibitors (table 6). It is interesting that 14 of these were coadministered with grapefruit juice and extensive increases in exposure were reported for many CVDs, but the influence is certainly variable. Between different substrates, the effect of grapefruit juice varied from a marginal influence on amlodipine, diltiazem, quinidine and verapamil to several-fold increases in exposure of felodipine, lovastatin, nisoldipine and simvastatin (table 6). This might reflect several factors, such as different amounts of juice ingested, different types of juices or batches of the same type (content of inhibitors) and variable dependency of CYP3A4 in the overall turnover of the CVDs. Nevertheless, regular drinking of grapefruit juice by patients treated with many of the CVDs indicated in table 6 can definitely be troublesome (elevated response). With respect to both clinical actuality and degree of influence by concurrent CYP3A4 inhibitors, the dihydropyridine calcium channel blockers (dihydropyridines) and the HMG-CoA reductase inhibitors (statins) are of special interest. All dihydropyridines are sensitive to CYP3A4 inhibitors (table 6), but amlodipine, felodipine and nifedipine are probably most frequently used in clinical practice. Based on the interaction studies performed between dihydropyridines and CYP3A4 inhibitors, felodipine seems to be the most susceptible agent (table 6). The fact that the concurrent use of diltiazem increased the exposure of amlodipine and nifedipine to a similar extent [133, 168] suggests that these agents may be considered equally sensitive. If a CYP3A4 inhibitor is added to an established dihydropyridine treatment, this could result in an excessive blood pressure response with the risk of unpleasant and potentially harmful side effects (e.g. flushing, elevated heart rate and forced heart contractions). Statins are generally considered to be well tolerated, though not harmless, and especially their potential muscle toxicity has been a concern. Muscle-related side effects of statins range from unpleasant muscle fatigue and myalgia to harmful myopathy, which might proceed to the poten-

CYP Variability and Cardiovascular Drugs

tially fatal condition rhabdomyolysis. The exact mechanism(s) behind the muscle-related side effects of statins is not known, but the risk is clearly related to their systemic exposure [190, 191]. As the enzyme HMG-CoA reductase mediates production of mevalonic acid, a precursor for crucial compounds in cell proliferation and coenzyme Q10 (important for aerobic energy synthesis), the toxicity may reflect the direct inhibitory action of statins on HMGCoA reductase in skeletal muscle cells [190–193]. Atorvastatin, lovastatin and simvastatin are all extensively metabolized by CYP3A4. A number of interaction studies with CYP3A4 inhibitors have been performed with these statins, and the increases in exposure are in most cases substantial (table 6). Evaluation of these studies is complicated by the fact that different types of measurements have been applied. This is partly because statins in vivo are in equilibrium between acid (lipid-lowering) and lactone (non-lipid-lowering) forms. The lactone form is generally more abundant in serum than the acid, regardless of lactone administration (lovastatin and simvastatin) or acid administration (atorvastatin). It is the lactone forms that are the primary CYP3A4 substrates, but due to the equilibrium with the acids, increased exposure of lactones will simultaneously result in higher acid levels when coadministered with CYP3A4 inhibitors. It is not obvious which measurement is the most relevant regarding the risk of myotoxicity, but the acid form of the statins has been preferred in table 6 whenever reported. However, in some studies, only the pharmacokinetics of the lactone form or the sum of the acid and lactone forms has been recorded. In three studies with atorvastatin (table 6), the relative change in ‘serum HMG-CoA reductase inhibitory activity’ was applied as the only measurement. This is because an equally potent HMG-CoA reductase-inhibiting metabolite (2-hydroxylated derivate) is formed via CYP3A4 (fig. 3). Thus, the relative change in serum HMG-CoA reductase inhibitory activity (serum extracts tested on an HMG-CoA reductase bioassay) reflects the net change of atorvastatin and the 2-hydroxylated metabolite in serum. The serum HMG-CoA reductase inhibitory activity is surely a relevant end point for the lipid-lowering response of treatment with atorvastatin and other statins, but is it relevant for muscle toxicity? If reflecting toxicity, one would expect atorvastatin to be safely combined with CYP3A4 inhibitors, because the mean 1.3–1.8 increases in serum HMG-CoA reductase inhibitory activity reported during concurrent use of such agents (table 6) is far from alarming for this kind of drug.

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65

O

Tissue penetrability

OH OH

O NH

C

N

O

O

COO-

NH

N

C

OH

Tissue penetrability

In vivo

F

F Atorvastatin lactone (inactive)

Atorvastatin acid (the admistered drug, active)

CYP3A4

O

Tissue penetrability

OH OH

O NH

C

N

OH

O

O

COO-

NH

In vivo

N

C

Tissue penetrability

OH

F 2-Hydroxyatorvastatin acid (active, ~1/1 compared to atorvastatin)

OH

2-Hydroxyatorvastatin lactone (inactive)

F

Fig. 3. Interconversion between atorvastatin and atorvastatin lactone, and their CYP3A4-mediated counterparts

(activities and estimated relative tissue-penetrating abilities are indicated).

The fact that CYP3A4 inhibitors were concomitantly used in more than 50% of all atorvastatin-associated cases of rhabdomyolysis reported to the FDA during November 1997 to March 2000 (total number 105) [194] indicates that serum HMG-CoA reductase inhibitory activity does not reflect the actual increased risk of muscle-related side effects in combination therapy with CYP3A4 inhibitors. In one of the interaction studies between atorvastatin and the azole antimycotic drug itraconazole [140], the reported relative exposure increases of atorvastatin (acid), atorvastatin lactone and serum HMG-CoA reductase inhibitory activity were 3.3-, 4.4- and 1.6-fold, respectively. This shows that the increase in unmetabolized atorvastatin is much more pronounced than the serum HMG-CoA reductase inhibitory activity. Thus, as the tissue-penetrating abilities (lipophilicity) of the parent form are higher than those of the metabolite produced through CYP3A4 (fig. 3), it might be that the change in exposure of unmetabolized atorvastatin better reflects the elevated risk for myotoxicity than serum HMG-CoA reductase inhibitory activity. It is no doubt that concomitant use of CYP3A4 inhibitors elevates the risk of muscle-related side effects of all

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three ‘CYP3A4-sensitive’ statins [194], which was one of the reasons for withdrawing mibefradil (CYP3A4 and CYP2D6 inhibitor) shortly after it entered the market [2]. Regarding the trend towards more aggressive lipid-lowering treatment (higher statin exposure at ‘baseline’), interactions associated with CYP3A4 inhibition may be an even greater concern in the future. The reported high frequency of rhabdomyolysis in patients concomitantly treated with cerivastatin and the fibrate gemfibrozil was a major reason to withdraw cerivastatin from the market [1], but the interacting mechanism was probably not CYP3A4 inhibition, as cerivastatin has been shown to be insensitive towards several wellknown CYP3A4 inhibitors [141, 195, 196]. Interaction studies have been performed between most statins (not atorvastatin) and gemfibrozil, and except for fluvastatin, gemfibrozil increases the acid level of all statins studied (table 7). However, the observed mean increase was highest for cerivastatin. In addition, a peculiar elevation of the lactone form was reported for cerivastatin when combined with gemfibrozil (3- to 4-fold) [197], which implies the possible relevance of the lactone levels as toxicity markers of statins. Although not as frequent as with ceri-

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Table 7. Relative systemic exposure (‘relative systemic dose’) re-

ported for statins when coadministered with gemfibrozil Statin

Acid

Lactone

Cerivastatin1 [197] Fluvastatin1 [198] Lovastatin2 [199] Pravastatin1 [200] Rosuvastatin1 [201] Simvastatin2 [202]

4.4 1.0 2.8 2.0 2.0 2.9

3.5 n.m. 1.0 n.m. n.m. 1.4

Data are derived from dose-adjusted mean values for AUC. No studies were found for atorvastatin. n.m. = Not measured. 1 Admistered in acid form. 2 Admistered in lactone form.

results showing that atorvastatin lactone inhibited conversion of clopidogrel to its active metabolite [17]. However, retrospective analyses of the Clopidogrel for the Reduction of Events During Observation [209] and Maximal Individual Therapy of Acute Myocardial Infarction PLUS [210] trials could not show any significant effect of atorvastatin on the therapeutic outcomes (hard end points) of clopidogrel treatment. The reason(s) for the lack of concordance between the influence of the surrogate end point (ex vivo platelet aggregation) and clinical end points is uncertain. As atorvastatin mediated a dose-dependent effect on the surrogate end point [207], it might be that atorvastatin (or simvastatin) doses influence whether a potential clinical interaction with clopidogrel will occur. Nevertheless, to what degree ‘CYP3A4 statins’ generally could affect (inhibit) the metabolism of other drugs metabolized by this enzyme should be further investigated.

vastatin [1], many cases of rhabdomyolysis have also been reported for lovastatin, pravastatin and simvastatin in combination with gemfibrozil [194]. The mechanism(s) behind the increase in systemic exposure of many statins when coadministered with gemfibrozil has not been fully outlined, but in vitro studies suggest that inhibition of CYP2C8 (important for cerivastatin) and/or conjugating enzymes of the UDP-glucuronosyl transferase superfamily might be central [100, 203]. Special care should be paid when combining gemfibrozil and pharmacokinetically sensitive statins, but since both statins and fibrates might exhibit muscle toxicity in monotherapy, attention is recommended whenever combining these types of drugs. The same advice applies if statins are combined with cyclosporine (INN ciclosporine; immunosuppressant drug), which has also been shown to increase statin levels through mechanisms other than inhibition of CYP3A4 [204]. According to the product monograph for rosuvastatin, the newly approved statin (not subjected to relevant metabolism via CYP3A4 [205] or CYP2C9 [206]), the acid form is elevated 7-fold in combination with cyclosporine, and concurrent use of rosuvastatin and cyclosporine is actually contraindicated [201]. Overall, fluvastatin appears to be the safest statin in combination with either gemfibrozil or cyclosporine. No studies were found on the possible interaction between CYP3A4 inhibitors and the thrombocyte inhibitor clopidogrel, which is converted to its active form via this enzyme (table 1). However, it has actually been reported that the ability of clopidogrel to inhibit platelet aggregation is reduced in combination with atorvastatin or simvastatin (not pravastatin, which is a poor CYP3A4 substrate) [207, 208]. This is in agreement with in vitro

Relative Exposure of CVDs with CYP2D6 Inhibitors Altogether, studies for 7 CVDs that are CYP2D6 substrates in combination with inhibitors of this enzyme were found (table 8). The values in table 8 are drawn from studies performed in CYP2D6 EMs, and when CYP2D6 inhibitors are administered to EMs, their phenotype will approach or even become equal to the PM phenotype. Metoprolol has been studied in combination with four different CYP2D6 inhibitors (table 8). The highest increase in metoprolol exposure was observed during concurrent use of the antidepressant drug paroxetine, a selective serotonin reuptake inhibitor (SSRI). The mean 5-fold increase in exposure of S-metoprolol was accompanied by a pronounced bradycardia after a single dose of metoprolol (100 mg), which was not experienced in the control phase (metoprolol alone) [214]. When considering that the relative ‘dose’ of metoprolol with paroxetine was 5 times higher (i.e. 500 mg, linearly scaled), this is not surprising. Compared to paroxetine, diphenhydramine (H1-antihistamine), hydroxychloroquine (antimalaria/antirheumatic) and propafenone produced more moderate increases (mean 50–70%) in metoprolol exposure [53, 213, 215], but an altered therapeutic response of metoprolol is not unlikely with these agents as well. In patients with reduced cardiac function, fluoxetine (SSRI) increased the levels of S-carvedilol by approximately 40% [211]. This did not result in any statistical change in therapeutic end points of carvedilol, which is less dependent on CYP2D6 than metoprolol (table 3), probably due to relevant metabolism via CYP2C9 as well [11]. For propranolol, the relative increase of the sum of the enantiomers was reported to be elevated 2- to 3-fold

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Table 8. Relative systemic exposure (‘relative systemic dose’) reported for CVDs when coadministered with CYP2D6 inhibitors

Substrates

Inhibitors Diphen

Carvedilol1 Encainide2 Flecainide Metoprolol1 Mexiletine Propafenone1 Propranolol1

Fluox

Hychlo

Parox

Propaf

Quinid

1.6 (R/S) 1.4 (S) [211] 0.1–1.7 [42, 43] 1.1–1.3 [47, 212] 1.6 (R/S) [53]

1.5 (R/S) [213]

6.2 (R/S) 5.1 (S) [214]

1.7 (R/S) [215] 1.53 [59]

1.5 (R/S) [217] 2.1 (R/S) [218]

1.3–1.5 [56, 216] 2.7 (R/S) [61] 2.3–2.8 (R/S) [219, 220]

Data are derived from dose-adjusted mean or median values for AUC, Css or Cl/F. Ranges are lowest to highest ratios calculated from mean/median values in different studies. Diphen = Diphenhydramine; Fluox = fluoxetine; Hychlo = hydroxychloroquine; Parox = paroxetine; Propaf = propafenone; Quinid = quinidine. 1 ß-Receptor antagonism is mediated by S-enantiomers. 2 Data represent O-desmethylencainide (principal active form of encainide treatment). 3 Interaction is shown to be solely due to CYP2D6 inhibition and not through the CYP1A2-inhibitory properties of propafenone.

by propafenone and quinidine (antiarrhythmic) administration [218–220]. Therapeutic end points were not registered, but it is reasonable to believe that coadministration of CYP2D6 inhibitors could affect the response of propranolol. The fact that propranolol was shown to be sensitive towards CYP2D6 inhibitors (propafenone and quinidine; studies in Caucasians) is in disagreement with the two genetic studies that reported no influence of CYP2D6 activity on the exposure of propranolol in Caucasians (table 3) [68, 69]. Propafenone is additionally an inhibitor of CYP1A2 (table 5), an enzyme also involved in the metabolism of propranolol, and the influence of this inhibitor could be explained by changed CYP1A2 metabolism. However, quinidine is considered a specific CYP2D6 inhibitor, and the results of the genetic and interaction studies with propranolol therefore remain paradoxical. All the antiarrhythmic drugs that are CYP2D6 substrates have been studied in combination with quinidine (table 8). For flecainide and mexiletine, only marginal increases in exposure were reported, but the studies had both limited numbers of individuals and limited serum concentration measurements [47, 56, 212, 216]. Due to their clinical sensitivity and apparent dependency on CYP2D6 in the metabolism (table 3), care should be paid with respect to coadministration of CYP2D6 inhibitors. The same applies for propafenone, where an almost 3-fold increase in exposure was reported during concurrent use

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of quinidine [61]. Regarding encainide, whose principal activity is mediated through the metabolite produced by CYP2D6, two studies with quinidine had contradictory results (table 8). One study resulted in an expected substantial reduction in the level of the active metabolite [43], whereas another actually showed increased exposure [42]. However, there should be little doubt that the therapeutic response of encainide will generally be reduced if coadministered with CYP2D6 inhibitors. As mentioned in the beginning of this subsection, all studies were performed in CYP2D6 EMs. The subpopulation of PMs will of course not experience increased exposure of CYP2D6 substrates (or reduced levels of active metabolites) if inhibitors are concurrently used, because they already have deficient activity. For the same reason, though, the risk of overdosing (or nonresponse) is already present in monotherapy for PMs, as outlined in the genetic section. Relative Exposure of CVDs with CYP2C9 Inhibitors Altogether, interaction studies with CYP2C9 inhibitors were found for 7 CVDs that are substrates for this enzyme (table 9). Genotypes of CYP2C9 were not determined in any of the studies. Coadministration of CYP2C9 inhibitors is expected to affect the exposure of the coumarin S-enantiomers. Studies were only found for warfarin, which had been investigated in combination with three different CYP2C9 inhib-

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Table 9. Relative systemic exposure

(‘relative systemic dose’) reported for CVDs when coadministered with CYP2C9 inhibitors

Substrates

Inhibitors Amiod

Fluvastatin Glimepiride Irbesartan Losartan1 Nateglinide Tolbutamide Warfarin2

1.8–2.2 (R/S) 2.1 (S) 1.6 (R) [229–231]

Benzbr

Flucon

Fluvox

1.5 (R/S) 2.0 (S) 1.2 (R) [232, 233]

1.8 [221] 2.4 [222] 1.3 [222] 1.6 [223] 0.5–0.6 [224, 225] 1.5 [227] 1.5 [228] 2.4 (R/S) 2.8 (S) 2.1 (R) [234]

Pheny

0.4 [226]

Data are derived from dose-adjusted mean or median values for AUC, Css or Cl/F. Ranges are lowest to highest ratios calculated from mean/median values in different studies. Amiod = Amiodarone; Benzbr = benzbromarone; Flucon = fluconazole; Fluvox = fluvoxamine; Pheny = phenytoin. 1 Data represent E-3174 (principal active form of losartan treatment). 2 S-Enantiomers are more potent than R-enantiomers.

itors (table 9). Amiodarone (antiarrhythmic), benzbromarone (uricosuric) and fluconazole (azole antimycotic) were all reported to increase the exposure of S-warfarin 62-fold [229–233], and the potential clinical relevance of this is obvious. The clinical influence of amiodarone and fluconazole on warfarin is probably worsened by their marked elevations of the R-enantiomer too (table 9). The mean exposure of fluvastatin has been shown to increase almost 2-fold when combined with fluconazole [221]. This is far from the increases observed for the ‘CYP3A4 statins’ during inhibition (table 6), but a possible increased risk of muscle-associated side effects of fluvastatin should not be ruled out if coadministered with CYP2C9 inhibitors. The relevance of CYP2C9 activity for the exposure of irbesartan was confirmed in a study with fluconazole [223]. A mean increase of 60% in irbesartan level during fluconazole coadministration (table 9) might intensify the response if combined with CYP2C9 inhibitors. For losartan, CYP2C9 inhibitors will have the opposite clinical influence, since CYP2C9 is responsible for production of its principal active form (E-3174). Both fluconazole and phenytoin were reported to lower the level of E-3174 to approximately one half compared to monotherapy [224– 226]. Exposure of glimepiride, nateglinide and tolbutamide seems to be increased to a similar extent as other CYP2C9 substrates when coadministered with inhibitors (table 9). Thus, a higher risk for hypoglycemia is present with these

Relative Exposure of CVDs with CYP1A2 Inhibitors Interaction studies with CYP1A2 inhibitors were found for 4 CVDs that are substrates of this enzyme (table 10). Although the coumarin R-enantiomers are less active than the S-forms, inhibitory action against the Rforms might be clinically relevant as well. Cimetidine (H2antihistamine) has been shown to significantly increase exposure of both acenocoumarol and warfarin [235, 242– 244], and case reports of potentiated anticoagulation have been published for the cimetidine-warfarin combination [247–249]. This also applies for patients receiving warfarin together with ciprofloxacin (fluoroquiniolone antibiotic) [250], which has been shown to elevate R-warfarin levels by about 20% [245]. An approximately 40% increase in the sum of the warfarin enantiomers has been shown in combination with propafenone [246]. This

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drugs, and possibly also glipizide, if CYP2C9 inhibitors are added to the drug regimen. Fluconazole has been shown to increase the levels of many CYP2C9 substrates, but it should be pointed out that the potential clinical problems associated with fluconazole interactions are probably not present for single-dose treatment with this antimycotic drug (warfarin may be an exception). The influence and importance of interindividual variability in terms of sensitivity to CYP2C9 inhibitors in relation to genetics are based on similar reasoning as sketched for CYP2D6 interactions in the former subsection.

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Table 10. Relative systemic exposure (‘relative systemic dose’) reported for CVDs when coadministered with CYP1A2 inhibitors

Substrates

Inhibitors Cimet

Acenocoumarol Mexiletine Propranolol1 Warfarin2

1.4 (R/S) [235] 0.7–1.1 [236, 237] 1.9–2.0 (R/S) [239–241] 1.2–1.4 (R/S) 1.3 (R) 1.0 (S) [242–244]

Cipro

1.1 (R/S) 1.2 (R) 1.0 (S) [245]

Fluvox

Prapaf

1.6 [238]

1.53 [59] 1.4 (R/S) [246]

Data are derived from dose-adjusted mean or median values for AUC, Css or Cl/F. Ranges are lowest to highest ratios calculated from mean/median values in different studies. Cimet = Cimetidine; Cipro = ciprofloxacin; Fluvox = fluvoxamine; Propaf = propafenone. 1 ß-Receptor antagonism is mediated by the S-enantiomer. 2 S-Enantiomers are more potent than R-enantiomers. 3 Interaction is shown to be solely due to CYP2D6 inhibition and not through the CYP1A2 inhibitory properties of propafenone.

probably reflects the CYP1A2 inhibitory properties of propafenone and that an enhanced anticoagulant response of warfarin could be expected if the drugs are coadministered. By being an inhibitor of three different CYP enzymes (table 5), the SSRI fluvoxamine is a particularly troublesome drug in combination therapy. The CYP1A2-inhibitory action of fluvoxamine is reflected by its ability to increase the mean exposure of mexiletine by more than 50% [238], which might imply serious clinical consequences if the drugs are concomitantly used. No interaction study was found between fluvoxamine and warfarin, but excessive anticoagulation has been reported in patients receiving both drugs [251, 252]. Cimetidine exhibits pronounced inhibition of CYP1A2, and increased exposure during coadministration of cimetidine was reported for all substrates indicated in table 10, except for mexiletine. The apparent lack of interaction between cimetidine and mexiletine was shown to be the net result of two different mechanisms, i.e. reduced absorption (probably due to elevated gastric pH) and inhibited metabolism [236, 237]. Thus, it is unlikely that cimetidine will affect the mexiletine response to a clinically relevant extent. Relative Exposure of CVDs with CYP2C8 Inhibitors The only CVD metabolized by CYP2C8 that had been investigated in combination with CYP2C8 inhibitors was repaglinide. This antidiabetic drug is a substrate for both CYP2C8 and CYP3A4 (table 1). The mean exposure of repaglinide increased 8.1-fold when combined with gem-

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fibrozil (CYP2C8 inhibitor) [180], which indicates that CYP2C8 is most important in the overall metabolism. In comparison, coadministration of CYP3A4 inhibitors (clarithromycin and itraconazole) resulted in a mean repaglinide elevation of 40% (table 6). Interestingly, concurrent use of both gemfibrozil and itraconazole resulted in a mean 19.2-fold increase in repaglinide exposure [180]. It is important to be aware that the combination repaglinidegemfibrozil has recently been contraindicated.

Influence of Coadministered CYP Inductors on CVDs

Basic Considerations regarding CYP Induction Induction of drug-metabolizing enzymes is mediated through binding of inductors to nuclear receptors, which stimulate transcription of selected enzymes. The result is higher enzyme levels and faster metabolism of affected drugs. Since binding to different nuclear receptors stimulates transcription in an unselective manner, activities of several enzymes are often speeded up simultaneously. Usually, stimulation involves both phase I metabolism (e.g. CYP enzymes) and phase II metabolism (e.g. UDPglucuronosyl transferase enzymes). This means that CVDs metabolized by enzymes other than CYP enzymes will be affected by induction as well, which was the main argument for focusing less on induction than inhibition in this article. Moreover, inhibition is more common in combination therapy than induction, because inhibitors are considerably more abundant than inductors.

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However, in cases where enzyme inductors are included in a drug regimen, this might have major consequences for a large proportion of the drugs used by the patient, due to the unselective nature of induction. In most cases, addition of an inductor will reduce the therapeutic response of the affected drugs, as a result of faster turnover and lower drug exposure. This often also applies for so-called prodrugs of inducible CYP enzymes, because the subsequent metabolism of the active metabolite is usually also speeded up. Bosentan (endothelin receptor antagonist), carbamazepine (antiepileptic, also used in other neurological disorders), dexamethasone (steroid hormone), rifampicin (antibiotic) and troglitazone (antidiabetic) are all typical enzyme inductors. Commonly, these drugs speed up the activities of CYP3A4 and CYP2C9, which implies that metabolism of all substrates of CYP3A4 and CYP2C9 is likely to be faster in combination therapy. It is important to be aware that herbal medicines may contain compounds with marked abilities to induce drug-metabolizing enzymes as well. The remedy used against mild depressions, St. John’s wort (Hypericum perforatum), is an excellent example with its potential to induce CYP3A4 and CYP2C9 activities. Moreover, cigarette smoking is well known as an inductor of CYP1A2 activity. For patients who are exposed to inductors, higher doses of affected drugs are generally required to achieve sufficient effect. This leads to more expensive treatment, but is not a clinical problem as long as the drug regimen is adjusted and stabilized. However, the situation may be problematic if the inductor exposure is ended. Then, the metabolic activities are gradually reduced, and if doses of the affected drugs are not adequately reduced according to the decline in metabolic capacity, the risk of overdosing/toxic reactions is present. In the following section, some examples will be presented to illustrate the effect of inductors on the exposure of selected CVDs.

ratio 0.05) after inductor pretreatment [253]. This reflects the fact that the former (least sensitive) individual had 90% of the ‘simvastatin dose’ left after St. John’s wort, whereas the latter (most sensitive) individual retained only 5%. Cigarette smoking has been reported to increase the in vivo metabolism of mexiletine (CYP1A2 substrate) [255]. In individuals smoking about 15 cigarettes per day, the relative exposure of mexiletine was decreased to an extent reflecting a mean 30% higher dose requirement among smokers to achieve similar serum levels as nonsmokers. It is of course very important for patients using CVDs to stop smoking, but one should be aware that this might lead to increased exposure/response of certain drugs (especially CYP1A2 substrates), due to a decline in metabolic activity. Reduced doses might therefore be needed to avoid potential side effects.

Practical Approaches to Prevent Potential Problems Associated with CYP Variability

Examples of the Influence of CYP Inductors on Exposure of CVDs The pharmacokinetics of simvastatin has been studied in combination with both St. John’s wort and bosentan [253, 254]. The mean exposure of simvastatin in its active form (acid) was reduced by 40 and 60% after pretreatment with bosentan and St. John’s wort, respectively [253, 254]. The degree of induction displays extensive interindividual variability. In the study with St. John’s wort, for example, the relative exposure of simvastatin acid ranged from –10% (AUC ratio 0.9) to –95% (AUC

The easiest way to prevent potential clinical problems related to CYP variability is to use therapeutically equivalent alternatives that are not metabolized by CYP enzymes to a relevant extent. Within groups of drugs sharing a similar mode of action, there are often agents for which CYP metabolism is not relevant. Examples are pravastatin and rosuvastatin among the statins, eprosartan, telmisartan and valsartan among the angiotensin II receptor antagonists, and atenolol among the ß-receptor antagonists. However, CVDs within similar groups may be used at doses with variable clinical effects on surrogate end points, which could favor some agents over others. In addition, one common mode of action does not necessarily mean that the rest of the pharmacological profile is equal (selectivity, distribution etc.). Hence, when drugs within each group have different effect documentation, especially on so-called hard end points, it might, from an evidence-based point of view, be difficult to defend a random use of CVDs with similar modes of action. So, how should potential CYP-related problems be prevented when the preferred drug is sensitive to CYP variability or insensitive alternatives are absent? Regarding drug interactions, the clue is to be particularly careful with the use of drugs that are described as inhibitors of the enzyme involved in the sensitive drug’s metabolism (table 5). Instead of adjusting the dose of the sensitive substrate during coadministration, which is often recommended,

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Table 11. Concurrent prescription of CYP-sensitive CVDs and

inhibitors of the enzymes involved in their metabolism during a 6month period in three Norwegian primary pharmacies CVDs

Number of patients

Concurrent CYP inhibitors

Statins (CYP3A4) Atorvastatin Lovastatin Simvastatin Dihydropyridines (CYP3A4) Amlodipine Felodipine Nifedipine ß-Receptor antagonists (CYP2D6) Carvedilol Metoprolol Propranolol

1,918 762 39 1,117 1,248 897 283 68 1,837 170 1,497 170

39 (2.0%) 13 (1.7%) 2 (5.1%) 26 (2.3%) 30 (2.4%) 23 (2.6%) 3 (1.1%) 4 (5.9%) 48 (2.6%) 2 (1.2%) 38 (2.5%) 8 (4.7%)

The data are drawn from a master thesis in pharmacy at the University of Tromsø [256].

but difficult because of interindividual variability with regard to interaction degree (and time-consuming, i.e. due to follow-up), use of a therapeutic alternative to the inhibitor without inhibitory action eliminates the potential problem. The macrolides clarithromycin/erythromycin and the SSRIs fluoxetine/paroxetine are frequently used in combination therapy and are especially troublesome if combined with CVDs that are substrates for CYP3A4 (28 agents in table 1) and CYP2D6 (14 agents in table 1), respectively. For CYP3A4, statins and dihydropyridines are clinically important CVDs, whereas ß-receptor antagonists are central among CYP2D6 substrates. In a recent study in Norwegian primary pharmacies, it was observed that on approximately 2–3% of the occasions where CYPsensitive drugs of these three CVD groups were used, potent inhibitors of the enzymes involved in their metabolism were concurrently prescribed (table 11, pooled data) [256]. Among statins and dihydropyridines, clarithromycin and erythromycin were the concurrent inhibitors in 190% of the cases, whereas fluoxetine and paroxetine made up 170% of the CYP2D6 inhibitors prescribed with ß-receptor antagonists. Relevant information for the macrolide-statin combinations is that a normal treatment period for the antibiotic (1–2 weeks) is enough to provoke rhabdomyolysis in susceptible patients. Regarding combinations of ß-receptor antagonists and SSRIs, it is interest-

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ing that treatment with the former drugs has been associated with the development of depression. When considering the great number of patients who use CVDs every day, about 2–3% concurrency of inhibitors is serious. Although some combinations might be under control, by far the most are probably not. For the safety and welfare of the patients, it is important that these risky drug combinations are kept to an absolute minimum, which could be achieved through a restrictive use of potent CYP inhibitors in combination with sensitive CVDs. Therapeutic alternatives with more ‘CYPinert’ profiles are available for the most frequently used CYP inhibitors, including clarithromycin/erythromycin (macrolide alternatives: rovamycin or azithromycin) and fluoxetine/paroxetine (SSRI alternatives: citalopram or sertraline). With respect to genetically determined variability of CYP activities, it is important to acknowledge that the optimal dose may be highly variable among patients with different genotypes. For CVDs where the systemic exposure is known to be predicted by the patient’s genotype of the CYP involved, a general piece of advice would be to monitor both the effect(s) and potential side effects closely after initiation of the treatment and perform dose adjustments if necessary. An attractive approach would of course be to determine the patient’s genotype prior to treatment and adjust the dose according to the genotype. CYP genotyping is increasingly available as a clinical tool and is not particularly expensive. For some drugs, such as warfarin and metoprolol, it might be a good investment to determine the genotype prior to treatment. In patients with genotypes corresponding to decreased metabolic activity, the doses could be inversely downregulated according to the increased exposure observed in pharmacogenetic studies (tables 3, 4). In patients with heterozygous 2C9*3 genotypes, it could, for example, be advisable to start with a warfarin dose 1/3–1/4 of that normally used as a starting dose. Similarly, in patients with homozygous deficient CYP2D6 genotypes, i.e. 2D6*3–6/*3–6 (PMs), it could be wise to start with a metoprolol dose that is approximately 1/5 of the recommended initial dose. When drugs are converted to their active forms via a polymorphic enzyme (e.g. losartan and encaidine), dose increases among individuals with low/deficient activity are not a proper option and other therapeutic alternatives should be used instead. Today, genotyping requires special competence and is therefore mainly performed in hospitals. However, the genotyping technology will probably be simplified in the near future, making it appropriate even in general prac-

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tice. If this is accompanied by genotype-specific dose recommendations of drugs in their product monographs, CYP genotyping could be a major step towards achieving a safer and more rational pharmacotherapy.

Concluding Remarks

More than 50 CVDs are substrates for CYP enzymes, and the systemic exposure (‘available dose’) of approximately two thirds has been reported to be predicted by the in vivo activity of the enzymes involved in their metabo-

lism. Thus, there is no doubt that variability in CYP activity is an important contributor to individual differences in drug response. To reduce the unpredictability caused by variable CYP activity, application of ‘CYPinsensitive’ drugs is an obvious alternative. However, if a ‘CYP-sensitive’ CVD has to be used, restrictive concomitant use of inhibitors is advisory. Finally, for CVDs that are substrates for enzymes where genetic polymorphism is important for the phenotype (e.g. CYP2D6 and CYP2C9), the patient response should be closely monitored, and genotyping prior to treatment may be performed to optimize doses in each patient.

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