CHAPTER 2 DIGOXIN 33

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1 CHAPTER 2 DIGOXIN 33

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3 CHAPTER 2.1 Role of ABCB1 genotypes and haplotypes in digoxin steady state pharmacokinetics in geriatric patients S.V. Frankfort, R.J. Keizer, A.D.R. Huitema, V.D. Doodeman, C.R. Tulner, J.P.C.M. van Campen, P.H.M. Smits, J.H.M. Schellens, J.H. Beijnen Abstract Objectives: To evaluate the influence of ABCB1 polymorphism on digoxin steady state pharmacokinetics in geriatric patients using digoxin for the indications atrial fibrillation or congestive heart failure. Methods: ABCB1 genotype was determined by sequencing at positions C1236T (exon 21), G2677T/A (exon 21) and C3435T (exon 26) and haplotypes were subsequently inferred. Non-linear mixed effect modelling (NONMEM) was used to model the steady-state pharmacokinetics of digoxin in geriatric patients. In co-variate analyses the influence of ABCB1 genotypes and haplotypes on the clearance of digoxin after oral ingestion was investigated. Results: 140 patients were included with a median age of 84.8 years and a median daily digoxin dose of 125 µg. A subpopulation of 40 prospectively recruited patients was genotyped for polymorphisms of ABCB1. A typical value for the apparent digoxin clearance of 5.68 L/h was found. Identified ABCB1 genotypes and haplotypes were not significant covariates for digoxin clearance. Conclusion: Digoxin steady state pharmacokinetics were not significantly influenced by the identified ABCB1 polymorphism or haplotypes of these polymorphisms in a population of geriatric patients. Submitted 35

4 Chapter 2.1 Introduction Digoxin is used in the treatment of atrial fibrillation and congestive heart failure in the elderly 1,2. Both inotropic and arrhythmogenic effects of digoxin are related to its effects on the sodium-potassium pump 3. Sodium-calcium exchange is promoted and thereby the intracellular calcium concentration is increased and eventually results in increased force of cardiac contraction 3,4. The pharmacokinetics of digoxin are characterised by a bioavailability exceeding 90%, a volume of distribution between 4 and 7 L/kg and a long elimination half-life between 30 and 40 hours 4. Earlier research investigated age, serum creatinine level, co-administration of spironolactone, gender and presence of congestive heart failure as variables that may influence digoxin pharmacokinetics. Female gender, higher age, higher level of serum creatinine, and use of spironolactone resulted in significantly lower oral digoxin clearances 5-7. Digoxin is a substrate for the drug transporter P-glycoprotein (P-gp), a 170 kda membrane bound efflux pump. This efflux pump is located amongst others in the epithelial layer of the intestine, renal tubules, placenta and blood-brain-barrier. It enhances transport from blood into the gut lumen via the intestinal epithelium and from the renal tubules into urine 8,9. The Multi Drug Resistance gene (ABCB1) encodes for P-gp. It is known that the ABCB1 gene is highly polymorphic 10. The three most frequently occurring Single Nucleotide Polymorphisms (SNPs) are C1236T in exon 12, G2677T/A in exon 21 and C3435T in exon A common haplotype containing these three SNPs simultaneously was found by Kim et al. 12 The synonymous SNP C3435T was the first variant to be associated with altered protein function. As a linkage disequilibrium exists between this SNP and the nonsynonymous G2677T/A it has been suggested that functional differences associated with the C3435T polymorphism may be the result of the associated SNP at G2677T/A 10. Studies investigating single SNPs resulted in conflicting results; both increases, no significant differences or decreases in maximal plasma concentrations and area under the plasma concentration versus time curve (AUC) of digoxin were reported in heterozygous and homozygous mutants at positions G2677T/A and C3435T ABCB1 haplotypes composed of different SNPs may better represent changes in P-gp function, as found in digoxin and ciclosporin pharmacokinetic studies 10,14,15. Digoxin has been used as a probe drug in studies regarding the functional relevance of P- gp 16,17. Clinical studies regarding the functional relevance of ABCB1 SNPs were mostly performed in young healthy volunteers as either a single-dose study or a multiple dose study during a short period 13-15, This study aims to investigate the correlation between ABCB1 SNPs and their haplotypes and the steady state pharmacokinetics of digoxin in a cohort of geriatric patients that use digoxin as part of a regular therapeutic regimen for atrial fibrillation and/or congestive heart failure. 36

5 Role of ABCB1 genotypes in digoxin pharmacokinetics Methods Patients This study consisted of two parts. First, a retrospective part was performed in patients who were admitted to the geriatric diagnostic day-clinic of the Slotervaart Hospital, Amsterdam, The Netherlands between May 2000 and May In these patients digoxin plasma concentrations were determined. Second, a prospective study was carried out at the department of Geriatric Medicine of the Slotervaart Hospital between January 2004 and May In this prospective study, digoxin plasma concentrations were determined in patients treated with digoxin and patients were genotyped at positions C1236T in exon 12, G2677T/A in exon 21, and C3435T in exon 26 of ABCB1. All patients used digoxin for the indications atrial fibrillation or congestive heart failure and plasma digoxin concentrations were regularly measured within the therapeutic drug monitoring service of the Department of Pharmacy & Pharmacology. Patients were only included if digoxin was used at the current dose for a minimum of two weeks to assure that pharmacokinetics were measured at steady state levels. The study protocol was approved by the Institutional Review Board of the Slotervaart Hospital, Amsterdam, The Netherlands. Written informed consent was obtained from each participant for ABCB1 genotyping in this study. Sampling, bioanalysis and pharmacogenetic analysis From all patients, a 5 ml EDTA blood sample was obtained by venous puncture. We considered untimed samples as steady state levels due to the very long elimination half-life of digoxin. In the prospective part of this study, 2 ml whole blood was stored at -20 C pending genotype analysis. After isolation of plasma by centrifuging, the samples were stored at 20 C until drug analysis. Digoxin concentrations were assayed with the TDx digoxin assay kit (Abbott Laboratories Ltd) for fluorescence polarisation immunoassay (FPIA) technology. The lower limit of quantification was 0.2 ng/ml. The precision and accuracy of this assay were within 8% (as mentioned in the manufacturer manual) 22. Genomic DNA was extracted from EDTA whole blood using the Qiagen QIAamp DNA Mini Kit (Qiagen, Leusden, The Netherlands) according to the manufacturer protocol. ABCB1 genotypes at positions C1236T, G2677T/A and C3435T were analysed as previously described 23. Haplotypes were inferred with the software package HPlus65v2.1.1 ( using the Expectation-Maximisation (EM) algorithm. 37

6 Chapter 2.1 Pharmacokinetic analysis The nonlinear mixed effect modelling program (NONMEM) Version V (double precision, level 1.1, GloboMax LLC, Hanover MD, USA) 24 was used to perform the analysis. The first-order conditional estimation procedure (FOCE) with interaction was used throughout. The adequacy of the tested models was evaluated using statistical and graphical methods. The minimal value of the objective function (OFV, equal to minus twice the log likelihood) provided by NONMEM was used as a goodness of fit characteristic to discriminate between hierarchical models using the log likelihood ratio test 24. A p-value of 0.001, representing a decrease in OFV of 10.8 points (degrees of freedom (df)= 1) or 13.8 points (df= 2) was considered statistically significant. Standard errors for all parameters were calculated with the COVARIANCE option in NONMEM, individual Bayesian pharmacokinetic parameter estimates were obtained using the POSTHOC option 24. The program PDx-POP (version 1.1, release 4, Globomax LLC, Hanover MD, USA) was used as a tool for expediting population pharmacokinetic analysis with NONMEM and for graphical model diagnostics. Pharmacokinetic model and co-variate analysis The data were fitted to the following one-compartment steady state deterministic model: C ss,i = D i /(CL i /F*τ i ) (equation 1) where C ss, i is the serum steady state concentration of digoxin (µg/l) measured in the i th patient, D i is the dose of digoxin (µg), CL i /F is the oral clearance of the i th individual (L/h) and τ i is the interval between daily doses for the i th individual. Variability was modelled according to the following equation: C i =Ĉ i +ε i (equation 2) where C i is the observed digoxin concentration of individual i, Ĉ i is the corresponding predicted concentration by the model and ε i is the difference between observed and predicted concentrations and consists of the interindividual variability and residual variability since only one digoxin concentration was available per patient. To identify possible relationships between the clearance and patient characteristics, the following co-variates were collected: age (years), gender, creatinine level in serum, use of spironolactone, use of diuretics and presence of congestive heart failure. Genotypic data were not available of the retrospectively included patients. Therefore, in the analyses investigating genotypes as possible co-variates, separate typical values of CL/F were estimated for the retrospectively included patient population and for prospectively included 38

7 Role of ABCB1 genotypes in digoxin pharmacokinetics patients including the influence of genotypes. Genotypic data were investigated at the positions C1236T (exon 12), G2677T/A (exon 21) and C3435T (exon 26) as three groups: homozygous wild-type, heterozygous mutants and homozygous mutants. The three investigated genotypes were separately introduced as co-variates according to the following equations: CL/F= θ 1 (equation 3) heterozygous homozygous CL/F= θ 2 * θ 3 * θ 4 (equation 4) where θ 1 represents the apparent clearance in the retrospectively included patients, θ 2 represents the apparent clearance in the prospectively included wild-type patients, θ 3 is the fractional change in heterozygous mutants and θ 4 is the fractional change in homozygous mutants. Haplotypes were investigated as inferred haplotypes at positions in exon 12, exon 21 and exon 26. Haplotype data were divided into dichotomous variables: presence or absence of the TTT haplotype and presence or absence of the CGC haplotype. Inferred haplotypes at position C1236T, G2677T/A and C3435T were introduced in the model as described in the following equations: CL/F = θ 1 (equation 5) HAPLOTYPE CL/F = θ 2 * θ 3 (equation 6) where θ 1 represents the apparent clearance in retrospectively included patients, θ 2 represents the apparent clearance in prospectively included patients and θ 3 is 1 for carriers of the TTT haplotype and 0 for non-carriers of the TTT haplotype and in a separate analysis 1 for carriers of the CGC haplotype and 0 for non-carriers of the CGC haplotype. A covariate was considered statistically significant when the inclusion was associated with a decrease in minimal value of the OFV associated with a p-value of <0.001 (log-likelihood ratio test). Results Patients A total of 140 patients were included in this study of whom 40 were prospectively included and who gave informed consent for ABCB1 genotyping. Demographic characteristics were not significantly different between prospectively and retrospectively included patients (results not shown). The total population had a median age of 84.8 years, 64% were females and they used a median daily digoxin dose of 125 µg (table 1). Plasma concentrations of 39

8 Chapter 2.1 digoxin are shown in figure 1. In table 1 the frequencies of the genotypes at positions C1236T, G2677T/A and C3435T and the frequencies of the inferred haplotypes at those three positions are listed. 28 (70.0) 31 (77.5) Table 1. Baseline characteristics of digoxin users. Baseline characteristic Digoxin users (n=140)* Age (years), median (range) 84.8 ( ) Gender, male / female (%) 12/ 21 (36 / 64) Dose (µg), median (range) 125 ( ) Prospectively included patients, n 40 C1236 T (Exon 12), n (% of prospective patients) CC 12 (30.0) CT 21 (52.5) TT 7 (17.5) G2677T/A (Exon 21), n (% of prospective patients) GG 11 (27.5) GT 23 (57.5) TT 6 (15.0) C3435T (Exon 26), n (% of prospective patients) CC 8 (20.0) CT 24 (60.0) TT 8 (20.0) Haplotype, n (% of (prospective patients*2 )) CGC 38 (47.5) CGT 6 (7.5) CTT 1 (1.3) TGC 1 (1.3) TTC 1 (1.3) TTT 33 (41.3) Presence of minimal 1 TTT haplotype, n (% of prospective patients) Presence of minimal 1 CGC haplotype, n (% of prospective patients) Serum creatinine (µmol/l), median (range) 93 (54-482) Use of spironolactone, n (%) 29 (20.7) Use of diuretics, n (%) 89 (83.6) Presence of congestive heart failure, n (%) 51 (36.4) * total included patients: n=140 (retrospective study: n=100; prospective study, including ABCB1 genotyping: n=40), each patient carriers two haplotype alleles, haplotype C1236T-G2677T-C3435T 40

9 Role of ABCB1 genotypes in digoxin pharmacokinetics Figure 1. Steady state plasma concentration (µg/l) versus daily digoxin dose (µg). Concentration digoxin (µg/l) Daily digoxin dose (µg) Population pharmacokinetics and co-variate analyses The basic pharmacokinetic model based upon equation 1 and modelled as a onecompartment model resulted in a population clearance of 5.68 L/h with a relative standard error (RSE) of 5.76%. Age, gender, serum creatinine level, use of spironolactone and presence of congestive heart failure were not identified as significant co-variates for the steady-state clearance of digoxin, as introduction of these co-variates resulted in decreases in OFV of less than 10.8 points. Table 2. Results of analyses investigating genotypes as possible co-variates for digoxin steady-state pharmacokinetics. SNP Typical value CL/F (% RSE) Retrospectively included patients Prospectively included wild types Fractional change in Cl/F in heterozygous mutants (% RSE) Fractional change in Cl/F in homozygous mutants (% RSE) p-value C1236T 5.61 (6.52) 4.75 (14.4) 1.32 (23.6) 1.41 (21.6) >0.05 G2677T/A 5.61 (6.52) 4.38 (13.2) 1.44 (22.0) 1.63 (21.8) >0.05 C3435T 5.61 (6.52) 4.77 (13.3) 1.28 (21.6) 1.37 (24.7) >0.05 SNP = Single Nucleotide Polymorphism, CL/F= apparent digoxin clearance (L/h), RSE= Relative standard error, Retrospectively included patients: CL/F= θ CL/F, Prospectively included patients: CL/F=θ CL/F, WILD TYPES * θ HETEROZYGOUS * θ HOMOZYGOUS 41

10 Chapter 2.1 An increase in CL/F was shown in both heterozygous and homozygous mutants. However, all relations between CL/F and genotypes of ABCB1 were non-significant. The results of the analyses investigating ABCB1 genotypes as covariates are summarised in table 2. Presence of the TTT or CGC haplotype was not revealed as a significant co-variate for CL/F as the decreases in OFV were smaller then 10.8 points (table 3). Table 3. Results of analyses investigating haplotypes as possible co-variates for digoxin steady-state pharmacokinetics. Haplotype Typical value CL/F (% RSE) Retrospectively included patients Prospectively included patients Fractional change in CL/F in patients carrying the haplotype (% RSE) p- value TTT 5.61 (6.52) 4.75 (14.4) 1.34 (20.7) >0.05 CGC 5.61 (6.52) 6.69 (15.7) (21.9) >0.05 Haplotype of C1236T-G2677T-C3435T. CL/F= apparent digoxin clearance (L/h), RSE= Relative standard error. Prospectively included patients: CL/F= θ CL/F * θ TTT, where TTT=0 for non-carriers and TTT=1 for carriers or CL/F= θ CL/F * θ CGC, where CGC=0 for non-carriers and CGC=1 for carriers Discussion Our basic pharmacokinetic model revealed a typical value of 5.68 L/h for CL/F. Yukawa et al. 5 gave an overview of estimated digoxin clearances in various studies and these ranged between 1.56 L/h when calculated for a creatinine clearance of 5 ml/min to 10.3 L/h as calculated for a creatinine clearance of 100 ml/min. The population clearance from our results is comparable to the range in the described population clearances. In our population we did not find age, gender, serum creatinine, presence of congestive heart failure and use of spironolactone as significant co-variates in an intermediate model. The frequencies of ABCB1 genotypes in our population are comparable to those earlier described in a geriatric population 25 and in younger populations 12,23,26. Haplotype frequencies were also comparable to those earlier described by us in another geriatric population 25. No significant correlations were found between individual genotypes at positions C1236T, G2677T/A and C3435T and digoxin clearance. We did, however, show a non-significant increase in the apparent clearance of digoxin in patients bearing mutant alleles compared to wild-types. This was most pronounced for the homozygous mutants and for heterozygous mutants intermediate values were found. An increase in the apparent clearance of digoxin results in lower steady state concentrations and lower AUC values. We performed analyses in geriatric patients that use digoxin for medical conditions. Thus far, only investigations into the role of ABCB1 polymorphisms into digoxin pharmacokinetics were performed in 42

11 Role of ABCB1 genotypes in digoxin pharmacokinetics healthy volunteers. These volunteers are often of a younger age 14,18,19 or receive only a single oral dose of digoxin 18,19. Our results for C3435T in exon 26 are comparable to those of Sakaeda et al. 20 In that study a lower maximum plasma concentration and lower AUC 0-4h of digoxin were found in heterozygous and homozygous mutants. On the other hand, our results are in contradiction to the results of Johne et al. 14 who found the highest AUC 0-24h in homozygous mutants at position C3435T (not statistically significant) and steady-state plasma concentrations were significantly higher in homozygous mutants compared to wildtypes. Our results for G2677T/A in exon 21 are comparable to the results of Kim et al. 12 who showed non-significantly higher fexofenadine, also a P-gp substrate, AUC 0-4h in homozygous wild-type subjects compared to homozygous mutants. In the study by Verstuyft et al. 18 no significant differences in digoxin AUC 0-24h were found between different genotypes at position G2677T/A in exon 21. As earlier suggested 12,13-15, correlations between ABCB1 genotypes and pharmacokinetics show conflicting results. This study adds to those conflicting results. A possible explanation for the conflicting results may be that the function and/or expression of P-gp is not solely influenced by a single ABCB1 genotype, but instead by different SNPs at other loci in the ABCB1 gene 13. In addition, it could be possible that different SNPs that are currently unknown, but may be important functional SNPs, are in a strong linkage disequilibrium with C3435T. This may result in the linkage of the mutant T allele at position 3435 to different SNPs, resulting in differences in function of P-gp 27. Haplotype analysis may thus be superior to genotype analysis. In our geriatric population the TTT and CGC haplotypes inferred at positions C1236T, G2677T/A and C3435T were most frequent among the different haplotypes that were present. We investigated whether presence of at least one TTT haplotype or the presence of at least one CGC haplotype was significantly related to the apparent clearance in our population, but did not show significant results. In the study by Johne et al. 14 carriers of the TT haplotype (position G2677T linked to C3435T) showed significantly higher digoxin trough concentrations compared to non-carriers. Those results are contradictory to our results as we showed a (non-significantly) higher apparent clearance, corresponding to lower digoxin plasma concentrations. Johne et al. 14 also demonstrated that individuals with at least one haplotype GT (position G2677T linked to C3435T) had significant higher digoxin plasma levels. In our population of geriatric patients we included 6 patients with at least 1 haplotype CGT (position C1236T linked to G12677T and C3435T) and haplotypes consisting of TGT were not found in the population. The presence of at least one haplotype CGT resulted in not significantly reduced apparent clearance, corresponding to higher digoxin plasma concentrations (results not shown). The study by Kim et al. 12 investigated fexofenadine concentrations in patients with different ABCB1 haplotypes. Patients homozygous for CGC showed higher AUC values compared to patients with one TTT haplotype and one CGC 43

12 Chapter 2.1 haplotype. In our population we did not find such significant differences in clearance between those latter two groups (results not shown). Our results did not show that haplotype analysis is superior to genotype analysis in the correlation between SNPs and steady state digoxin pharmacokinetics and are thus not in agreement with the results of Johne et al. 14 and Kim et al. 12. We do not have clear explanations for these differences. We have included a relatively low number of participants of whom we obtained genotypic data, however, numbers of included patients were also small in those studies 12,14. In general, to obtain additional knowledge into the functional relevance of ABCB1 haplotypes, future studies should include larger number of patients and if possible haplotypes consisting of more genotypes. These studies may reveal new insights into haplotypes that are less frequent and into haplotypes composed of different genotypes. In healthy volunteer studies, complete pharmacokinetic curves were sampled in participants. In the study by Kurata et al. 15 heterozygous and homozygous mutants had significantly lower apparent tubular secretary clearances and they suggested that both reductions in intestinal secretion of digoxin and renal secretion into the urine occur in subjects. The study by Johne et al. 14 suggested that the terminal elimination does not proceed more slowly in homozygous mutants compared to wild-types. This study showed increased absorption and higher levels of steady state exposure in homozygous mutants at position C3435T compared to wild-types and suggest the absorption phase is particularly affected by ABCB1 polymorphism. Our study only investigated effect of genotypes and haplotypes on steady state concentrations. In the long-term steady-state pharmacokinetics the trough concentration is probably less influenced by effects of genotype or haplotype on absorption as compared to the single dose studies or short-term multiple dose studies. The non-significant influences of genotypes and haplotypes on clearance in our study may be explained by these differences. Earlier described studies investigating the relation between ABCB1 genotypes and digoxin pharmacokinetics in healthy volunteers and our study differ in design and this may also explain different results between studies. Those studies intended to investigate the functional relevance of ABCB1 SNPs by using digoxin as a probe drug. Our study was designed to investigate the role of these SNPs in the steady state pharmacokinetics of digoxin in geriatric patients. We did not exclude patients if they used co-medication that may influence P-gp function, which is contrary to the healthy volunteer studies. In addition, our study was performed in routine clinical practice and possible medication non-adherence may have influenced our results. In conclusion, digoxin steady state pharmacokinetics were not significantly influenced by ABCB1 polymorphism or haplotypes of these polymorphisms in a population of geriatric patients using digoxin as part of their therapeutic drug regimens for the indications atrial fibrillation or congestive heart failure. 44

13 Role of ABCB1 genotypes in digoxin pharmacokinetics Acknowledgements Dieuwke Meier, Eric Calla, Remko Harms, Jan Nelis and Kees de Goey are kindly acknowledged for their technical assistance in digoxin measurements. References 1. Cheap G, Girard K, Vincent JP. Atrial fibrillation in the elderly. Facts and management. Drugs Aging 2002;19: Dec GW. Digoxin remains useful in the management of chronic heart failure. Med Clin N Am 2003;87: Eichhorn EJ, Gheorghiade M. Digoxin. Prog Card Dis 2002;44: Hanratty CG. McLinchey P, Johnston GD, Passmore AP. Differential pharmacokinetics of digoxin in elderly patients. Drugs Aging 2000;17: Yukawa E, Honda T, Ohdo S, Higuchi S, Aoyama T. Population-based investigation of relative clearance of digoxin in Japanese patients by multiple through screen analysis: an update. J Clin Pharmacol 1997;37: Yukawa E, Suematu F, Yukawa M, et al. Population pharmacokinetics of digoxin in Japanese patients. A 2- compartment pharmacokinetic model. Clin Pharmacokinet 2001;40: Yukawa E, Mine H, Higuchi S, Aoyama T. Digoxin population pharmacokinetics from routine clinical data: role of patient characteristics for estimating dosing regimens. J Pharm Pharmacol 1992;44: Schinkel AH and Jonker JW. Mammalian drug efflux transporters of the ATP binding cassette (ABC) family: an overview. Adv Drug Del Rev 2003;55: Borst P, Oude Elferink R. Mammalian ABC transporters in health and disease. Ann Rev Biochem 2002;71: Marzolini C, Paus E, Buclin T, Kim RB. Polymorphisms in human MDR1 (P-glycoprotein): Recent advances and clinical relevance. Clin Pharmacol Ther 2004;75: Bosch TM, Meijerman I, Beijnen JH, Schellens JHM. Genetic polymorphisms of drug-metabolising enzymes and drug transporters in the chemotherapeutic treatment of cancer. Clin Pharmacokinet 2006;45: Kim RB, Leake BF, Choo EF, et al. Identification of functionally variant MDR1 alleles among European Americans and African Americans. Clin Pharmacol Ther 2001; 70: Chowbay B, Li Huihua, David M, et al. Meta-analysis of the influence of MDR1 C3435T polymorphism on digoxin pharmacokinetics and MDR1 gene expression. Br J Clin Pharmacol 2005;60: Johne A, Kopke K, Gerloff T, et al. Modulation of steady state kinetics of digoxin by haplotypes of the P- glycoprotein MDR1 gene. Clin Pharmacol Ther 2002;72: Kurata Y, Ieiri I, Kimura M, et al. Role of human MDR1 gene polymorphism in bioavailability and interaction of digoxin, a substrate of P-glycoprotein. Clin Pharmacol Ther 2002;72: Mayer U, Wagenaar E, Beijnen JH, et al. Substantial excretion of digoxin via the intestinal mucosa and prevention of long-term digoxin accumulation in the brain by the mdr 1a P-glycoprotein. Br J Pharmacol 1996;119: Schinkel AH, Wagenaar E, van Deemter L, et al. Absence of the mdr1a P-glycoprotein in mice affects tissue distribution and pharmacokinetics of dexamethasone, digoxin and cyclosporin A. J Clin Invest 1995;96: Verstuyft C, Schwab M, Schaeffeler E, et al. Digoxin pharmacokinetics and MDR1 genetic polymorphisms. Eur J Clin Pharmacol 2003;58: Gerloff T, Schaefer, Johne A, et al. MDR1 genotypes do not influence the absorption of a single oral dose of 1 mg digoxin in healthy white males. Br J Clin Pharmacol 2002;54:

14 Chapter Sakaeda T, Nakamura T, Horinouchi M, et al. MDR1 genotype related pharmacokinetics of digoxin after single oral administration in healthy Japanese subjects. Pharm Res 2001;18: Horinouchi M, Sakaeda T, Nakamura T, et al. Significant linkage of MDR1 polymorphisms at positions 3435 and 2677: functional relevance to pharmacokinetics of digoxin. Pharm Res 2002;19: Abbott Laboratories. Digoxin TDx (No 9511). August Bosch TM, Doodeman VD, Smits PHM, Meijerman I, Schellens JHM, Beijnen JH. Pharmacogenetic screening for polymorphisms in drug-metabolizing enzymes and drug transporters in a Dutch population. Mol Diagn Ther 2006; 10: Beal SL, Sheiner LB. NONMEM User s guides. NONMEM Project Group, University of California at San Francisco, Frankfort SV, Doodeman VD, Bakker R, et al. ABCB1 genotypes and haplotypes in patients with dementia and age-matched non-demented control patients. Mol Neurodegener 2006;1: Kroetz DL, Pauli-Magnus C, Hodges LM, et al. Pharmacogenetics of membrane transporters investigators: Sequence diversity and haplotype structure in the human ABCB1 (MDR1, multi drug resistance transporter) gene. Pharmacogenetics 2003;13: Tang K, Ngoi S, Gwee P, et al. Distict haplotype profiles and strong linkage disequilibrium at the MDR1 multidrug transporter gene locus in three ethnic Asian populations. Pharmacogenetics 2002;12: