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Physiogenomic Comparison of Weight Profiles of Olanzapine

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Physiogenomic Comparison of Weight Profiles of Olanzapine Molecular Psychiatry (2007) 12, 474–482 & 2007 Nature Publishing Group All rights reserved 1359-4184/07 $30.00 www.nature.com/mp ORIGINAL ARTICLE Physiogenomic comparison of weight profiles of olanzapine- and risperidone-treated patients G Ruan˜o1, JW Goethe2, C Caley2, S Woolley2, TR Holford3, M Kocherla1, A Windemuth1 and J de Leon4 1Genomas, Inc., Hartford, CT, USA; 2Institute of Living, Hartford Hospital, Hartford, CT, USA; 3Department of Epidemiology and Public Health, Yale University School of Medicine, New Haven, CT, USA and 4Department of Psychiatry, College of Medicine, Eastern State Hospital, Mental Health Research Center, University of Kentucky, Lexington, KY, USA Atypical antipsychotics induce pre-diabetic symptoms in some but not all patients, characterized most notably by elevated weight. The side effect profiles of the various drugs in the class differ, however, raising the possibility of drug-specific mechanisms for similar side effects. We used physiogenomic analysis, an approach previously employed to study the genetics of drug and diet response, to discover and compare genetic associations with weight profiles observed in patients treated with olanzapine and risperidone as an approach to unraveling contrasting mechanistic features of both drugs. A total of 29 single nucleotide polymorphisms (SNPs) were selected from 13 candidate genes relevant to two potential pharmacological axes of psychotropic-related weight profiles, appetite peptides and peripheral lipid homeostasis. We applied physiogenomic analysis to a cross-section of 67 and 101 patients being treated with olanzapine and risperidone, respectively, and assessed genetic associations with the weight profiles. Weight profiles in patients treated with olanzapine were significantly associated with SNPs in the genes for apolipoprotein E, apolipoprotein A4 and scavenger receptor class B, member 1. Weight profiles in patients treated with risperidone were significantly associated with SNPs in the genes for leptin receptor, neuropeptide Y receptor Y5 and paraoxonase 1. These results are consistent with contrasting mechanisms for the weight profile of patients treated with these drugs. Genes associated with olanzapine weight profiles may be related to peripheral lipid homeostatic axes, whereas those associated with risperidone’s may be related to brain appetite peptide regulation. Future physiogenomic studies will include neurotransmitter receptor SNPs and validation in independent samples. Molecular Psychiatry (2007) 12, 474–482. doi:10.1038/sj.mp.4001944; published online 2 January 2007 Keywords: obesity; antipsychotic agents; pharmacogenetics; appetite; lipid metabolism Introduction case–control studies have shown that olanzapine is an independent risk factor for diabetes mellitus in Atypical antipsychotics (AAPs) are associated with patients with schizophrenia.7,8 Olanzapine is a thie- weight gain, although excess weight does not develop nobenzodiazepine with high affinities for the D ,D, in all patients.1–3 Hypertriglyceridemia ( > 600 mg/dl) 1 2 D , 5HT , 5HT , 5HT ,H, alpha and M receptors. may develop in as little as 3 months after initial expo- 4 2A 2C 3 1 1 1 It is a substrate for the cytochrome P450 1A2 (CYP sure to these drugs.4 The AAPs are much more 1A2) and for the UDP-glucuronosyltransferase 1A4 frequently associated with diabetes than are the (UGT 1A4)9 and has no active metabolites.10,11 ‘typical’ antipsychotics. In a study of more than Risperidone, another drug in this class, has a 38 000 patients, those on AAPs were 9% more likely different side effect profile. Weight gain is less pro- to have diabetes than those treated with ‘typical’ nounced than with olanzapine,12 but it is much more antipsychotics.5 In September 2003, the Food and likely to increase prolactin. Risperidone is a benzi- Drug Administration required re-labeling of all AAPs soxazole with high affinities for the D , 5HT , 5HT , to inform physicians about these risks. 2 2A 2C a and a receptors. It is a substrate for the cytochrome Olanzapine and clozapine carry the highest risk for 1 2 P450 2D6 and 3A (CYP 2D6 and CYP 3A)13 and has these side effects.6 Several population-based nested an active metabolite, 9-hydroxyrisperidone, with a comparable receptor affinity profile.10,11 Correspondence: Dr J de Leon, Department of Psychiatry, Study of the AAP pharmacological feature, which College of Medicine, Eastern State Hospital, Mental Health is responsible for the development of pre-diabetic Research Center, University of Kentucky, 627 West Fourth Street, complications in vulnerable populations, has princi- Lexington, KY 40508, USA. pally centered around weight gain caused by these E-mail: [email protected] Received 13 July 2006; revised 2 October 2006; accepted 2 medications. Histamine 1 (H1) and serotonin 2C November 2006; published online 2 January 2007 (5HT2C) receptor antagonism were among the most Physiogenomics weight olanzapine risperidone G Ruan˜o et al 475 important pharmacologic mechanisms discussed.14 of gene variation are analyzed to discover statistical 26 Antagonism of H1 and 5HT2C receptors is believed to associations with physiological characteristics. stimulate appetite and prevent satiety, respectively.15 The phenotypes are measured in populations of Other mechanisms that may lead to weight gain are individuals either at baseline or after they have been drug-induced elevations in serum leptin, neuro- similarly exposed to environmental challenges or peptide Y (NPY) or ghrelin.16,17 Patients taking AAPs interventions, including drugs and diet. The physio- are also known to be at risk for elevations in serum genomic approach affords testing broad hypotheses triglycerides and glucose.4,18 The mechanism behind about mechanistic features of drug effects. By relating hypertriglyceridemia is not known. In one case the physiological response to natural gene variation, report, olanzapine-induced hyperlipidemia resolved we gain valuable mechanistic insight. We also gain a when olanzapine levels disappeared, whereas weight practical way of predicting the response when the persisted.19 Genetically tractable metabolic differ- gene variation is known. In this report, we have ences could account for the variability in drug- extended physiogenomics to a comparison of two induced weight gain.1,2,18,20–23 AAP medications, olanzapine and risperidone. The availability of comprehensive genomic data- bases and massively parallel SNP genotyping techno- logy cannot be adequately handled by traditional Materials and methods statistical methods; it requires the development of Subjects and study design new statistical methods. This report is the first use in Patients were recruited as part of ongoing pharmaco- psychiatry of one of these new methods, which we genetic studies at the Institute of Living (Hartford, have called physiogenomics.24–26 Physiogenomics is a CT, USA) and at three Kentucky state hospitals medical application of sensitivity analysis and sys- (Lexington, KY, USA). These hospitals treat patients tems engineering, which we had previously applied with severe and persisting mental illness. From this to the study of drug and diet responses.24,25 Sensiti- study, 67 patients taking olanzapine and 101 patients vity analysis is the study of the relationship bet- taking risperidone who were willing to provide ween input and output as determined by each system a blood sample were selected for genotyping. The component.27 Physiogenomics utilizes genes as the demographic characteristics of the patient population components of the system. Gene variability, measured are presented in Table 1. To be eligible, patients had to by single nucleotide polymorphisms (SNPs), is have a current prescription of olanzapine or risper- correlated with physiological characteristics in a idone. All patients had an examination during which population, the output. With the advent of nanotech- their weight was determined. nology-based gene arrays, parallel processing of gene variability is practically possible at the level of Candidate gene selection physiological systems. Although single-gene muta- We selected eight genes related to peripheral lipid tions are the basis of most inborn errors of meta- homeostasis and five related to central appetite bolism, partial penetrance of genes interlinked in regulation, as summarized in Table 2. From the networks is more relevant to phenotypes common in lipid homeostasis axis, we selected representative clinical neuroscience. In physiogenomics, markers low-density lipoprotein (LDL) and high-density Table 1 Demographic characteristics of the olanzapine- and risperidone-treated patients in this study Variable Value Olanzapine Risperidone Subjects Mean weight (kg) Subjects Mean weight (kg) All All 67 82.9 101 78.4 Gender Female 19 82.4 38 73.4 Gender Male 48 83.1 63 81.5 Age (years) < 20 1 65.0 3 97.7 Age (years) 20–30 20 87.1 20 77.8 Age (years) 30–40 22 83.2 26 78.0 Age (years) 40–50 20 79.3 41 77.8 Age (years) 50–60 3 95.7 10 76.5 Age (years) 60–70 0 1 87.6 Age (years) 70–80 1 44.4 0 Heritage African-American 14 87.4 10 80.5 Heritage Caucasian 50 82.0 91 78.2 Heritage Hispanic 1 110.9 0 Heritage Other 2 60.5 0 Site Connecticut 14 84.2 0 Site Kentucky 53 82.6 101 78.4 Molecular Psychiatry Physiogenomics weight olanzapine risperidone G Ruan˜o et al 476 Table 2 Genes and SNPs analyzed for associations with weight profiles for olanzapine- and risperidone-treated groups Area Pathway Gene Symbol SNP Type Lipid metabolism LDL Apolipoprotein E APOE rs405509 B200 bp upstream
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