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Genetic Variation in CYP3A43 Explains Racial Difference in Olanzapine Clearance

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Genetic Variation in CYP3A43 Explains Racial Difference in Olanzapine Clearance Molecular Psychiatry (2011) 16, 620–625 & 2011 Macmillan Publishers Limited All rights reserved 1359-4184/11 www.nature.com/mp IMMEDIATE COMMUNICATION Genetic variation in CYP3A43 explains racial difference in olanzapine clearance KL Bigos1, RR Bies2, BG Pollock3,4, JJ Lowy1, F Zhang1 and DR Weinberger1,5 1Genes, Cognition, and Psychosis Program, National Institute of Mental Health, NIH, Bethesda, MD, USA; 2Division of Clinical Pharmacology, Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA; 3Rotman Research Institute, University of Toronto, Toronto, ON, Canada; 4Centre for Addiction and Mental Health, University of Toronto, Toronto, ON, Canada and 5Clinical Brain Disorders Branch, National Institute of Mental Health, NIH, Bethesda, MD, USA The antipsychotic drug, olanzapine, one of the most widely used drugs in clinical medicine, has a high rate of discontinuation due to inefficacy and/or adverse effects. We identified a single nucleotide polymorphism in the drug metabolizing enzyme, cytochrome P450 3A43 (CYP3A43; rs472660), that highly significantly predicted olanzapine clearance in the Clinical Antipsychotic Trials of Intervention Effectiveness trial (P = 5.9eÀ7). Moreover, at standard antipsychotic doses, 50% of individuals with the high clearance genotype (AA) have trough blood levels below the therapeutic range. Interestingly, a much higher proportion of African Americans carry the A allele compared with Caucasians (allele frequency 67 vs 14%). After accounting for CYP3A43 genotype, race is no longer a significant predictor of olanzapine clearance. Olanzapine clearance was associated with measures of clinical response. Patients with greater clearance had higher symptom ratings and were more likely to discontinue treatment due to an inadequate response. Our data identify a genetic mechanism for variation in olanzapine response and demonstrate that blood level monitoring of olanzapine treatment is advisable. Molecular Psychiatry (2011) 16, 620–625; doi:10.1038/mp.2011.38; published online 26 April 2011 Keywords: CYP450; CYP3A43; genetics; olanzapine; pharmacogenetics; pharmacokinetics Introduction therapeutic response. This study aimed to identify genetic predictors of olanzapine clearance and The Clinical Antipsychotic Trials of Intervention ultimately response. Effectiveness (CATIE) were a systematic evaluation of the clinical response to antipsychotics in the treatment of Alzheimer’s disease and schizophrenia. Patients and methods In the schizophrenia trial (CATIE-SZ), olanzapine was The study design details for the CATIE-SZ study have the most effective antipsychotic studied; with the been published.3 The study was approved by an lowest rate of discontinuation for any cause (64% 1 institutional review board at each site, and written discontinued treatment before 18 months). There informed consent was obtained from each patient or was a wide variability in response to olanzapine and his or her legal guardian. Patients with schizophrenia the other antipsychotics in the trial and although the were recruited from multiple US sites and patients in response to olanzapine was overall more positive, this analysis were randomized to receive olanzapine treatment with olanzapine was also associated with (7.5–30 mg per day taken as a single dose or split into greater weight gain and alterations in glucose and 1 two doses). Demographic information was collected at lipid metabolism. One reason for the high rates of study visits and race was self-reported. A subset of discontinuation may relate to the wide variability in patients provided a sample to be used for genetic the pharmacokinetics of these drugs, which often analysis (CATIE genetics distribution 7, n = 235). The results in differences in the pharmacodynamics, patients in this subset who had all available data both in the response to a drug and the incidence of pertinent to this study did not differ demographically adverse effects. Sex, smoking and race have pre- from all subjects randomized to olanzapine in phase 1 viously been shown to impact clearance of olanza- 2 of the CATIE trials (n = 336, 33% female, 60% pine, which likely contributes to the variable Caucasian, 36% African American). Likewise, base- line Positive and Negative Syndrome Scale (PANSS) Correspondence: Dr DR Weinberger, GCAP/DIRP/NIMH/NIH, 10 scores did not differ between this group and the entire Center Drive, MSC 1379, Bethesda, MD 20892, USA. sample (74.84±19.45 vs 76.13±18.18, P = 0.48). E-mail: [email protected] Received 14 February 2011; accepted 15 February 2011; Plasma samples were collected during the study published online 26 April 2011 visits and each patient provided between 1 and 6 CYP3A43 and olanzapine metabolism KL Bigos et al 621 samples for determination of olanzapine concentra- which pharmacokinetic data, genetic data and any tions. Data were excluded for missing or incorrect clinical response data were available. Four patients dose, time of dose, sample or time of sample. Plasma were excluded after blood level analysis indicated the levels of olanzapine were determined using liquid use of an antipsychotic drug outside of the study. chromatography tandem mass spectrometry, as pre- The likelihood ratio test was used to determine the viously described.2,4 effect of each SNP on the model. The likelihood ratio Genotyping methods have been previously pub- test is based on the property that the ratio of the lished.5 We used a candidate gene approach and NONMEM objective function values (À2 log-like- selected single nucleotide polymorphisms (SNPs) lihood) is asymptotically w2 distributed. The objec- that are in or near known olanzapine metabolizing tive function value is the sum of squared deviations enzymes (CYP1A2, CYP2D6 and FMO3)6 as well as between the predictions and the observations. An CYP3A, which is involved in metabolism of approxi- objective function decrease of 3.84 units was con- mately half of all drugs and has been reported to be sidered significant (w2, d.f. = 1, P = 0.05). That is to say altered during olanzapine treatment.7 All of the that the SNP had a significant impact on olanzapine available SNPs in these genes on the Affymetrix clearance if the objective function value decreased at 500 K chip that was used for genotyping of these least 3.84 points. patients were tested. A total of 26 SNPs were tested in Post-processing of NONMEM outputs and all plots or near CYP1A2 (rs2472300, rs2069522, rs2069526, were generated using GraphPad Prism 5 (version 5.02, rs4646425 and rs11631682), CYP2D6 (rs6002616 and GraphPad Software, San Diego, CA, USA). Linear rs9306356), FMO3 (rs2213712, rs2859228, rs2859229, regression was performed to determine the magnitude rs1492899, rs929087 and rs10458360) and CYP3A4, of contribution to the variability of clearance for the 3A5, 3A7 or 3A43 (rs2527894, rs2527887, rs4215, significant covariates (sex and smoking status) as well rs2525557, rs6960542, rs4729562, rs651430, rs12535293, as genotype effects. In order to correct for multiple rs472660, rs17161981, rs17161983, rs2572023 and comparisons for the 26 SNPs tested, we set an a priori rs2527927). threshold based on the conservative Bonferroni Nonlinear mixed-effects modeling was used to correction of P = 0.002 for the effect of genotype on determine the effects of genotype on olanzapine olanzapine clearance. Data are reported as mean±s.d. clearance using NONMEM (version 5, level 1.1; Data in the plots were estimated using the final GloboMax, Ellicott City, MD, USA) and the first order model, which included the covariates (sex and conditional estimation method with interaction. The smoking status) and genotype. baseline population pharmacokinetic model has been To address the possibility of population stratifica- previously published.2 A one-compartment pharma- tion, which could result in finding false positive cokinetic model with additive error best describes the associations in this subset of patients, we completed a data. In a previous analysis of these data, we multidimensional scaling (MDS) analysis. We per- identified sex, race and smoking status as indepen- formed the MDS analysis based on identify by state of dent significant contributors to olanzapine clearance;2 the genome-wide SNP genotypes within each racial therefore, the model used to test each genetic variant group and the first two MDS components were included sex, race and smoking status as covariates. extracted to be used as covariates in drug clearance Details on the pharmacokinetic modeling have been analysis. The identify by state and MDS analyses were previously published.2 Smoking status was given by completed using PLINK8 and R package (http:// patient self-report as either active smoker or non- www.r-project.org/). smoker (including past smokers). Concomitant med- ications that had an incidence of approximately 1% Results or greater were individually tested as discrete covari- ates in the original characterization of the population Patient demographics are listed in Table 1. There was pharmacokinetics of olanzapine, and none had a a ninefold difference in clearance across the popula- significant effect.2 Each SNP was tested separately as tion (range 6.941–60.09 litre per hour) with a mean a categorical covariate to determine its effect on the clearance of 25.83±9.920 litre per hour. Similar to the olanzapine population clearance. original pharmacokinetic analysis,2 men had 25% To determine the effect of olanzapine concentra- higher clearance than women (27.31±9.975 vs tions on
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