Pharmacogenetics of adverse events in schizophrenia treatment: Comparison study of ziprasidone, olanzapine and perazine

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Pharmacogenetics of adverse events in schizophrenia treatment: Comparison study of ziprasidone, olanzapine and perazine Piotr Tybura, Beata Trześniowska-Drukała, Przemyslaw Bienkowski, Aleksander Beszlej, Dorota Frydecka, Pawel Mierzejewski, Agnieszka Samochowiec, Anna Grzywacz, Jerzy Samochowiec www.elsevier.com/locate/psychres

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S0165-1781(14)00436-3 http://dx.doi.org/10.1016/j.psychres.2014.05.039 PSY8309

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Cite this article as: Piotr Tybura, Beata Trześniowska-Drukała, Przemyslaw Bienkowski, Aleksander Beszlej, Dorota Frydecka, Pawel Mierzejewski, Agnieszka Samochowiec, Anna Grzywacz, Jerzy Samochowiec, Pharmacogenetics of adverse events in schizophrenia treatment: Comparison study of ziprasidone, olanzapine and perazine, Psychiatry Research, http://dx.doi.org/10.1016/j.psychres.2014.05.039 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting galley proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Pharmacogenetics of adverse events in schizophrenia treatment: comparison study of ziprasidone, olanzapine and perazine

Piotr Tybura MD1, Beata Trześniowska-Drukała MD1, Przemyslaw Bienkowski MD2, Aleksander Beszlej MD3, Dorota Frydecka MD3, Pawel Mierzejewski MD2, Agnieszka Samochowiec MA4, Anna Grzywacz MA1,Jerzy Samochowiec MD, PhD1 x

1 2

Department of Psychiatry, Pomeranian Medical University, Szczecin, Poland

Department of Pharmacology, Institute of Psychiatry and Neurology, Warsaw, Poland 3 4

x

Department of Psychiatry, Wroclaw Medical University, Wroclaw, Poland

Institute of Psychology, Department of Clinical Psychology, Szczecin, Poland

Correspondence and reprint requests: Jerzy Samochowiec, MD, PhD, Department of Psychiatry,

Pomeranian Medical University, ul. Broniewskiego 26, 71-460 Szczecin, Poland; tel.: 0048-914541507; fax: 0048-91-4540733; email: [email protected]

Running title: Pharmacogenetics of adverse events in schizophrenia treatment

Pharmacogenetics of adverse events in schizophrenia treatment: comparison study of ziprasidone, olanzapine and perazine

Piotr Tybura MD1, Beata Trześniowska-Drukała MD1, Przemyslaw Bienkowski MD2, Aleksander Beszlej MD3, Dorota Frydecka MD3, Pawel Mierzejewski MD2, Agnieszka Samochowiec MA4, Anna Grzywacz MA1,Jerzy Samochowiec MD, PhD1 x

1 2

Department of Psychiatry, Pomeranian Medical University, Szczecin, Poland

Department of Pharmacology, Institute of Psychiatry and Neurology, Warsaw, Poland 3 4

x

Department of Psychiatry, Wroclaw Medical University, Wroclaw, Poland

Institute of Psychology, Department of Clinical Psychology, Szczecin, Poland

Correspondence and reprint requests: Jerzy Samochowiec, MD, PhD, Department of Psychiatry,

Pomeranian Medical University, ul. Broniewskiego 26, 71-460 Szczecin, Poland; tel.: 0048-914541507; fax: 0048-91-4540733; email: [email protected]

Running title: Pharmacogenetics of adverse events in schizophrenia treatment

Abstract: The primary aim of the present study was to assess the possible associations between dopaminergic, serotonergic, and glutamatergic system-related genes and adverse events after antipsychotic treatment in paranoid schizophrenia patients. The second aim of the study was to compare the intensity of these symptoms between atypical (ziprasidone and olanzapine) and typical (perazine) antipsychotic drugs. Methods: One hundred ninety-one Polish patients suffering from paranoid schizophrenia were genotyped for polymorphisms of DRD2, DAT1, COMT, MAOA, SERT, 5HT2A, and GRIK3. The patients were randomized to treatment with perazine, olanzapine or ziprasidone monotherapy for 3 months. The intensity of side effects (changes in body weights and extrapyramidal symptoms) was measured at baseline and after 12 weeks of antipsychotic treatment. Results: After 3 months of therapy, the weight increase was the greatest in the group treated with olanzapine and the least in the group treated with ziprasidone. None of the examined gene polymorphisms was associated with the body weight changes. Perazine treatment was associated with the significantly highest intensity of extrapyramidal symptoms. None of the examined polymorphisms was associated with the changes in extrapyramidal adverse events after antipsychotic treatment. Conclusion: The selected polymorphisms are not primarily involved in changes in body weights and extrapyramidal symptoms related to antipsychotic treatment in paranoid schizophrenia patients. Key words: schizophrenia, antipsychotics, gene polymorphisms, side effects, weight gain, extrapyramidal symptoms

1. Introduction

Schizophrenia is a psychiatric disease that affects nearly 1% of the world’s population (Gottesman, 1991; Jablensky, 2000). This disorder is typically chronic with relapses, and it causes severe cognitive, emotional, and functional abnormalities in affected individuals (Mak et al., 2013a,b). Because of the widespread nature of this disorder and its destructive course, many comprehensive research studies have been performed over the years aimed at elucidating its causes, determining its prognosis, and identifying the optimal treatment. Despite the fact that the susceptibility of the general population is similar, some families have been found to develop schizophrenia more frequently (10% or more among the first-degree relatives and co-morbidity among monozygotic twins of up to 40-50%) (McGuffin et al., 1994; Cannon et al., 1998; Cardno and Gottesman, 2000; Jablensky, 2000). However, twin fathers and adoption studies excluded a simple Mendelian inheritance (Tienari, 1991; Kidd, 1997; Tienari et al., 1997). Pharmacotherapy is the primary modality of treatment for the psychotic symptoms of schizophrenia. It is widely accepted that most patients suffering from schizophrenia benefit from antipsychotic treatment. However, the benefits of antipsychotic therapy are inconsistent and difficult to predict in individual patients (Gasquet et al., 2005; Kahn et al., 2008; Stahl, 2008). Pharmacogenetics refers to the efforts to dissect the genetic contributions to individual variations in drug responses (Kirchheiner et al., 2004; Arranz and Kapur, 2008; Tybura et al., 2012). Interindividual differences in the therapeutic benefits and the adverse effects of antipsychotic drugs are thought to depend, at least partially, on inherited factors. However, the current understanding of the pharmacogenetics of the antipsychotic drug response to acute exacerbation of schizophrenia is based on relatively few studies (Arranz and de Leon, 2007; Arranz and Kapur, 2008). In contrast to the few patients who experience full remission of schizophrenia, many patients experience significant symptoms. Additionally, adverse effects of therapy, including

movement disorders, cardiovascular events, and metabolic disturbances, require careful analysis by every clinician. A multicenter study found that more than 70% of patients suffering from chronic schizophrenia discontinued their psychopharmacotherapy. This situation is caused by poor effectiveness or tolerability of the antipsychotic drugs (Kane and Freeman, 1994). Traditionally, antipsychotic drugs used for schizophrenia therapy are categorized into two groups. Historically, the first group consists of typical or classical neuroleptics that display strong affinity for the dopaminergic system, especially D2 receptors, and the second group of new atypical antipsychotics displays affinity for different receptors in the dopaminergic and serotonergic systems (Miyamoto et al., 2005). The effectiveness of classical antipsychotics to treat the positive symptoms of schizophrenia, such as hallucinations and delusions, is associated with a high risk of adverse events. The most common adverse events associated with long-term therapy include extrapyramidal symptoms, parkinsonism, akathisia, acute dystonic reactions and tardive dyskinesia (Malhotra et al., 1993; Kane, 2006). Second-generation neuroleptics are similarly effective for the positive symptoms but demonstrate potential for the treatment of negative symptoms of schizophrenia. Additionally, patients administering atypical antipsychotic drugs are less exposed to the risk of extrapyramidal symptoms but are likely exposed to a higher risk of weight gain and metabolic disturbances (Kahn et al., 2008; Stahl, 2008; Houston et al., 2012; Brandl et al., 2013; Potkin et al., 2013). The primary aim of the present study was to assess the possible associations between dopaminergic, serotonergic, and glutamatergic system-related genes and adverse events after antipsychotic treatment in paranoid schizophrenia patients. The second aim of the study was to compare the intensity of these symptoms between atypical (ziprasidone and olanzapine) and typical (perazine) antipsychotic drugs. The efficacy of olanzapine, ziprasidone, and perazine was compared and described in a separate paper (Tybura et al., 2012).

2. Methods

2.1. Patients A total of 191 Caucasian patients of Polish descent [age (mean+SD): 36.1+12.4 yrs.] suffering from paranoid schizophrenia were recruited to the study at 2 university tertiary care centers (Pomeranian Medical University, n=141 patients; Wroclaw Medical University, n=50 patients) between June 2006 and May 2010. The Polish version of the Composite International Diagnostic Interview (CIDI) and the ICD-10 criteria were used to confirm the diagnosis of paranoid schizophrenia (Robins et al., 1988; Welbel et al., 2013). The exclusion criteria included serious neurological and/or somatic disorders (e.g., stroke, hepatic insufficiency or diabetes) (Kalinowska et al., 2013). Informed consent was obtained from each participant via both written materials and verbal communication. The study was performed in accordance with the Declaration of Helsinki, and the study protocol was approved by the Ethics Committee of the Pomeranian Medical University. The study group consisted of 89 men [age (mean+SD): 32.7±10.4 yrs.] and 102 women (38.9±13.2 yrs.). The mean age of the first psychotic episode for the entire group was 26.2±7.4 yrs. As expected, the first episode tended to appear earlier in the male (24.1±5.9 yrs.) than in the female patients (28.1±8.1 yrs.) (Kahn et al., 2008). Prior to admission, the subjects remained free of antipsychotic medications for 3-7 days. The patients were admitted because of exacerbation of paranoid schizophrenia and randomly assigned to the treatment groups of perazine, olanzapine, or ziprasidone monotherapy for 3 months (olanzapine, n=72; ziprasidone, n=59; perazine, n=60) according to the simple randomization method (Everitt and Vessely, 2008). A computer program allowed for random (with a probability of 33.3%) allocation of each qualified patient to one of the three treatment groups. The processes of initial enrollment and randomization were separated. The senior

investigators at each center were asked to perform a random allocation by the physicians willing to enroll the patients in the study. Each patient was registered in the study database and allocated to one of the study groups. The senior investigator was responsible for maintaining the database records and performing the randomization. Thus, the physician who determined whether the patient qualified for the study could not predict to which group the patient would be allocated. The allocation was performed by the senior investigator and was final. The entire system was equivalent between the two 'randomization centers'. The ranges of doses of ziprasidone (120-160 mg = equivalent to 200-300 mg/day of chlorpromazine), olanzapine (10-20 mg = equivalent to 200-400 mg/day of chlorpromazine), and perazine (300-600 mg = equivalent to 300-600 mg/day of chlorpromazine) used in the present study were in accordance with the Polish standards of schizophrenia treatment and followed the manufacturers’ recommendations (Jarema et al., 2006; Woods, 2003). All of the patients were previously treated with antipsychotic drugs, but none of the patients were treated with olanzapine, perazine or ziprasidone prior to inclusion in the present study. Perazine is a phenothiazine derivative widely used in some European countries, including Germany and Poland, and it is thought to exert potent antipsychotic and sedative effects, as well as a relatively low risk of extrapyramidal side effects (Leucht and Hartung, 2014; Adamowski and Kiejna, 2012). Interestingly, recent naturalistic studies have demonstrated that the effectiveness of some typical and atypical antipsychotics did not differ in clinical settings (Lieberman, 2006; Lewis and Lieberman, 2008; Stahl, 2008; Leucht et al., 2009; Naber and Lambert, 2009). At the time of study conception, perazine and olanzapine were the two most widely used antipsychotic drugs at both recruiting centers and ziprasidone had just been introduced to the Polish market.

The patients were assessed using the Positive and Negative Syndrome Scale (PANSS) at admission (T0) and after 2 (T1) and 12 weeks (T2) of monotherapy with olanzapine, perazine, or ziprasidone. The percentage change in the PANSS total score from T0 (baseline) to T1 and from T0 to T2 was a measure of the efficacy of the antipsychotic treatment. Patients who required a change in antipsychotic medication or dropped out of the study were treated as treatment failures, and their final PANSS score was carried forward (LOCF method). The overall measure of effectiveness in this study was all-cause discontinuation. A higher retention rate (i.e. a lower discontinuation rate) was treated as better effectiveness (Kahn et al., 2008; Naber and Lambert, 2009, Kay et al., 1987). The efficacy of the investigated drugs was described in more detail by Tybura et al. (2012). The intensity of the neurological adverse events was assessed using the Barnes Akathisia Scale (BAS) and the Simpson–Angus Extrapyramidal Rating Scale (SAS) (Rummel-Kluge et al., 2012). The weight of the patients was measured at the beginning of the study and after 12 weeks or when the patient dropped out.

2.2. Genetic analysis Genomic DNA was extracted from leukocytes using Miller’s desalting method (Miller et al., 1988). Polymerase chain reaction (PCR) was performed to amplification of the genetic material. The next step was a restriction fragments length polymorphism (RFLP) or variable number tandem repeat (VNTR) reaction. The polymorphisms of the dopamine receptor D2 (DRD2) (Arinami et al., 1997; Jönsson et al., 1999; Samochowiec et al., 2000), 5HT2A, GRIK3, and COMT genes (Lotta et al., 1995; Lachman et al., 1996) were analyzed via PCR-RFLP. The polymorphisms of the DAT1, SERT, and MAOA gene, were analyzed via PCR-VNTR (Vandenbergh et al., 1992; Sabol et al., 1998; Michelhaugh et al., 2001; Tybura et al., 2012).

2.3. Statistical analysis Hardy-Weinberg equilibrium was assessed using the SAS software. In the present study, there were no deviations from the Hardy-Weinberg principle. The χ2 test was performed to analyze the quantitative variables (i.e. retention rate or percentage of female patients). One-way analysis of variance (ANOVA) was performed to search for possible differences between the treatment groups in the baseline PANSS scores and the age. Two-way ANOVA (drug × time) was performed to compare the percentage changes in total PANSS scores between the treatment groups. One-way ANOVA was used to compare the changes in body weights, between the treatment groups and between genotypes, from the beginning of the study (T0) to the 3-month follow-up (T2). The Newman-Keuls test was used for further between-group comparisons. To compare changes in the extrapyramidal symptoms between the treatment groups and between genotypes, we performed the Kruskal–Wallis test. The Mann-Whitney U test was used for further betweengroup comparisons. P values less than 0.05 were considered to be significant. No correction for multiple comparisons was applied. The statistical analyses were performed using Statistica 5.0 software (StatSoft, Tulsa, Oklahoma, USA).

3. Results

To properly assess the intensity of the adverse events, the treatment efficacy data is presented in Table 1 (adapted from Tybura et al., 2012). At admission, the total PANSS score did not differ between the patients assigned to olanzapine (97.5 ± 16.7), perazine (99.8 ± 15.8), or ziprasidone treatment (102.2 ± 18.2) [ANOVA: F(2,188) = 1.25, p = 0.20] (Table 1). The treatment groups did not differ in the mean age (ziprasidone: 36.8 ± 11.4 yrs.; olanzapine: 34.7 ± 12.8 yrs.; perazine: 36.0 ± 12.5 yrs.) or the percentage of female patients (ziprasidone: 55.9%; olanzapine: 52.7%; perazine: 56.6%) (the one-way ANOVA and χ2 test, p > 0.05). Two-way ANOVA revealed a significant reduction in the PANSS score over time in the entire study group [time effect: F(1,188) = 56.19, p < 0.0001]. However, no difference was detected in the percentage reduction of the PANSS score between the patients treated with the different antipsychotics [drug effect: F(2,188) = 0.74, p = 0.48; drug × time interaction: F(2,188) = 0.75, p = 0.47] (Table 1). No differences were detected in the body weight between the study groups at T0. After 3 months of therapy, the weight increase was the greatest in the group treated with olanzapine (3.92 kg) and the lowest in the group treated with ziprasidone (-0.51 kg). Significant differences (p < 0.05) were found between the perazine and olanzapine treatment groups and between the ziprasidone and olanzapine treatment groups (see Table 2 for other details). The examined polymorphisms of key genes were not significantly associated with changes in body weights after 12 weeks of the antipsychotic drug treatment (see Table 3 for details). For the extrapyramidal symptoms, no differences were detected between the study groups at the beginning of the study. Significant changes in BAS and SAS scores were noted after 12 weeks of antipsychotic treatment. Significant differences (p < 0.05) were found between the perazine and ziprasidone treatment groups and between the perazine and olanzapine treatment groups. The patients treated with perazine exhibited the significantly highest intensity of extrapyramidal symptoms (Table 4).

The examined polymorphisms of key genes were not significantly associated with changes in extrapyramidal symptoms after 12 weeks of the antipsychotic drug treatment (see Table 5 for details).

4. Discussion

The field of pharmacogenetics was proposed by Vogel in the 1950s to define the inherited variability of responses to drug treatment (Gonzalez et al., 1988). Since this time, investigators have explored the associations between genetic factors and therapies in most fields in medicine, such as psychiatry, in which pharmacotherapy is very often insufficient. Likely, the response to a therapy depends on a combination of factors, including genotypes, the environment, patient behaviors, the clinical form of schizophrenia etc. (Weber, 1997; Rietschel et al., 1999; Kirchheiner et al., 2004; Kirchheiner et al., 2005). Clinical improvement in the treatment of chronic psychosis using currently available antipsychotic drugs is achieved in approximately 50% of cases (Lieberman et al., 2005), which agrees with our result that the retention rate after only 3 months of therapy was approximately 70%. Treatment failure has wide far-reaching consequences for the patient, his or her family and social environment, and the burden on the entire health care system (Drake et al., 2000; Knapp et al., 2005). These important implications drive the search for factors which facilitate the prediction of clinical outcomes. Many investigators are hopeful that pharmacogenetics can be used to identify strong associations between hereditary factors and responses to schizophrenia treatment and the intensity of adverse events, which is very often linked to the success of therapy (Arranz and de Leon, 2007). In our study, we selected a few genetic factors that, at least theoretically, can influence the efficacy and safety of commonly used antipsychotic drugs. The patients were genotyped for

ins/del -141C polymorphisms in the promoter region of the DRD2 gene (rs1799732). The functional effect this polymorphism manifests is a 21–43% decrease in gene expression in cell cultures and in individuals carrying the -141C Del allele. Possibly, this polymorphism also influences the density of D2 receptors, as investigations based on positron emission tomography (PET) found a higher density of these receptors in the striatum of individuals carrying the -141C allele (Samochowiec et al., 2000). Another investigated polymorphism is in exon 8 of DRD2 (rs 71653615). This polymorphism influences the expression of the gene (Finckh et al., 1997). The DRD2/ANKK1 Taq 1A polymorphism (rs 1800497) is characterized by a decreased density of D2 receptors in the striatum of individuals carrying the A1 allele and can also modulate the utilization of glucose in those parts of the brain in which the concentration of D2 receptors is higher (Thompson et al., 1997; Suchanecka et al., 2011). The polymorphism in DAT1 (a 40-bp VNTR polymorphism) that was investigated likely influences the expression of the gene (Sano et al. 1993). Serotonin transporters are responsible for serotonin reuptake. In the present study, the functional effect of polymorphism (the insertion–deletion type) of that gene was analyzed. This polymorphism was found to influence its transcriptional expression level. The genetic variation examined in this study is functionally responsible for the decrease in serotonin reuptake among individuals carrying the shortened variant (Ramamoorthy et al., 1993; Heils et al., 1997; Greenberg et al., 1999). The function of the serotonergic 5HT2A receptor is the activation of phospholipase C by a G protein, which leads to increased levels of inositol triphosphate and calcium (Hsieh et al., 1990; Sanders-Busch and Canton, 1995). The 5HT2A gene has many polymorphisms, but the best understood one thus far is the variation in codon 102, which results in the occurrence of alleles T and C (Warren et al., 1993). The functional consequences of the described polymorphism have yet to be established.

Glutamatergic kainate receptors are protein complexes situated in the cell membrane that enable ionic transmission after stimulation. They consist of five subunits: three low-affinitysubunits (GRIK1, GRIK2, and GRIK3) and two high affinity subunits (GRIK4 and GRIK5) (Begni et al., 2002). One polymorphism that caught our interest was a change in the protein sequence at position 928 from thymine to guanine in the GRIK3 gene (T928G) (Nutt et al., 1994; Schiffer et al., 2000; Begni et al., 2002). It is likely that the T allele has undergone suppression of expression much more frequently than the G allele, which may be the reason for the formation of two different protein subunits: one less stable subunit containing serine at position 310 and one more stable subunit containing alanine at the same site. We lastly examined the Val158Met (rs 4680) polymorphism of COMT, which results in a 3–4fold decrease in the enzyme activity level among homozygous Met/Met carriers (Bertocci et al., 1991; Grossman et al., 1992; Lundstrom et al., 1995; Pełka-Wysiecka et al., 2013), and a polymorphism (30-bp VNTR in the promoter region) of the MAOA gene, in which the activity of the enzyme expressing the 3–repeat allele is decreased compared to that of the 4- and 5-repeat alleles (Chen et al., 1992 Tybura et al., 2011; Tylec et al. 2013). Notably, only polymorphisms reported to have a functional significance and likely to be involved in a range of psychiatric disorders were selected for the present study. The most frequent or serious side effects of antipsychotic drugs are extrapyramidal symptoms, tardive dyskinesia and weight gain with metabolic syndrome. Their occurrence can interrupt therapy and force the psychiatrist to design a new treatment plan. Therefore, pharmacogenetic studies are aimed to identify predictive gene factors, which could allow psychiatrists to establish a “personalized” treatment for each patient. However, at the moment it remains unknown how epigenetic changes could be assessed in clinical practice. Extrapyramidal symptoms (EPS) and tardive dyskinesia (TD) have been extensively investigated. There are at least 20 SNPs in the DRD2, DRD3, COMT, HTR2A and HTR2C genes that have been analyzed. A few large reviews

summarizing the studies have been published (Malhotra et al., 2004; Weiner et al., 2004; Davies et al., 2005; Arranz and de Leon, 2007). Some demographic and clinical factors are known to increase the risk of EPS and TD, including older age, female gender, African American descent, higher antipsychotic dosage, and early EPS (Tenback et al., 2009; Plesničar, 2010). Hypersensitivity of dopamine receptors, other neurotransmitter system changes, and disturbances in the antioxidant response have also been proposed as possible pathophysiological mechanisms (Arranz and de Leon, 2007). Dopaminergic antagonism by antipsychotic drugs results in up-regulation of D2 receptors post-synaptically, which contributes to nigrostriatal dopaminergic hyperactivity. Therefore, variants of dopamine and other neurotransmitter receptor genes may play a key role. The DRD2 gene is the primary site of action of typical antipsychotic drugs and was a clear candidate for pharmacogenetic studies; however, genetic variations in DRD2 have yielded predominantly negative results in studies investigating their association with EPS and TD. However, there are reports that the A2 allele and the A2/A2 genotype display significantly increased risk of TD; a cumulative sample of 1256 patients (507 with TD and 749 without TD) from 6 cohorts demonstrated an odds ratio of 1.30 for the risk of TD in the A2 allele (Tenback et al., 2009). Another meta-analysis of 764 patients (297 with TD and 467 without TD) from 4 studies confirmed these findings (Zai et al., 2007). In a study of the Japanese population by Mihara et al., no difference was detected in the severity of EPS between bromperidol and nemonapride treatment. Other SNPs of DRD2, including −141C Ins/Del and Ser311Cys, have not been found to affect the risk of EPS or TD development. Our results confirmed these previous negative results. Despite the theoretical background, the polymorphisms investigated in this study are not likely involved in EPS. Importantly, the DRD2 gene is large relative to the other dopamine receptor genes, and thus, it is difficult to examine all of the SNPs distributed throughout the more than 250-kb length of this gene.

Second-generation antipsychotics display high affinities for serotonin receptors. It has been hypothesized that the serotonergic inhibition of dopamine function contributes to the development of extrapyramidal side effects. Some studies have demonstrated associations between the 5-HT2A and 5-HT2C receptor variants and EPS or TD, although other studies, including our study, could not confirm these results (Chong et al., 2000; Segman et al., 2000 and 2001; Tan et al., 2001; Herken et al., 2003; Deshpande et al., 2005). Some SNPs of the COMT, BDNF, MAOA, MAOB, and other genes have also been investigated, but no SNP displayed a clear association with drug-induced EPS (Arranz and de Leon, 2007). Weight gain is a major problem for patients treated with antipsychotics for long periods of time and can lead to treatment noncompliance and medical problems, including hypertension, type II diabetes, cardiovascular disease and respiratory difficulties. Body weight gain and the associated metabolic dysfunction are common side effects of antipsychotic drugs, especially second generation antipsychotics such as olanzapine and clozapine. Although many antipsychotics are known to be associated with an increased risk of obesity and diabetes, in clinical practice, there is little possibility to predict which patients treated with antipsychotics will develop obesity and diabetes and which will not. In our study, the patients treated with olanzapine demonstrated the highest increase in body weight, which was typical for this drug and in accordance with other studies (Lencz et al., 2013). Monozygotic twin and sibling studies have also suggested that a genetic factor contributes to this side effect (Wehmeier et al., 2005). The serotonin and histamine receptors play important roles in regulating eating behavior, which is why those genes have been investigated in several studies. The most significant results linked the 759 T/C polymorphism in the promoter region of the HTR2C gene (rs3813929) with druginduced weight gain. This SNP has been correlated to late-onset diabetes among patients and obesity among the general population. At least 17 studies have reported an association between the 759 T/C SNP of the HTR2C gene and weight gain among patients treated with

antipsychotics. Of those studies, 10 reported that the C allele was significantly associated with greater weight gain than the T allele after antipsychotic drug treatment. This effect was detected especially among subjects treated with clozapine and olanzapine, both of which display a high affinity to 5-HT2C. A meta-analysis of 8 studies containing 588 patients revealed that the T allele was significantly protective against antipsychotic drug-induced weight gain. The C allele was associated with a more than doubled increase in the risk for clinically significant weight gain, i.e., an increase of 7-10% or more of the body weight during treatment (Wehmeier et al., 2005).Another SNP which has been associated with weight gain is the 2548 A/G variant of the leptin gene. This polymorphism was associated with long-term but not short-term weight gain (weight gain developed after 9 months of antipsychotic treatment) (Theisen et al., 2005; De Luca et al., 2007). A significant relationship between the alleles of leptin and the leptin receptor, the olanzapine plasma concentration, and the body mass index was reported. Patients carrying at least one allele at each locus exhibited a 3-fold increase in the body mass index and a high concentration of olanzapine (Ellingrod et al., 2007). However, the mechanism of this polymorphism has yet to be determined. Other multiple genes of various neurotransmitter systems and many polymorphisms that have been examined (e.g., ADRA2A, SNAP-25, GNB3, and PAH) for their association with weight gain have revealed unclear results. In our study, polymorphisms of genes representing different neurotransmitter systems were investigated. However, we did not detect an association between weight gain and any particular genetic variation. In a study performed on 117 Han Chinese patients, no association was detected between the treatment-induced weight gain and the response to a variety of antipsychotics among first-episode patients (Arranz and de Leon, 2007). The Taq1 polymorphism of the DRD2 gene was also analyzed. Similarly, no association was detected during clozapine treatment between weight gain and the polymorphisms of the 5-HT2A and 5-HTT genes. This problem requires

further investigation aimed at identifying more genes engaged in antipsychotic-induced weight gain.

5. Conclusions

Pharmacogenetic studies of antipsychotic drugs can play an important role, particularly with respect to the treatment response and drug-induced adverse events among patients diagnosed with schizophrenia. Clinical implementation of pharmacogenetics can have a clear impact by improving treatment adherence and efficacy. Investigators have succeeded in the identification of several gene polymorphisms which can influence treatment responses. However, their genetic contribution is relatively small and is additionally complicated by environmental, clinical, ethnic, and demographic factors, which require further investigation. Moreover, pharmacogenetic studies could help to improve our understanding of the mechanism of action of antipsychotics and ultimately facilitate the discovery of new classes of neuroleptics. The interpretation of our negative findings is not simple because there are so few reports on this subject. The existing reports are limited, and in most cases, they were performed on small populations. However, in the future, further pharmacogenetic studies will likely facilitate the identification and verification of genetic factors that influence safety of antipsychotic treatment.

Acknowledgment

This study was supported by a Pfizer Independent Research Grant (grant no. 2005-0039).

Conflicts of Interest

All authors declare that they have no conflicts of interest.

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Tab. 1. The percentage reduction (±SD) in the PANSS total score, from T0 (baseline) to T1 (14 days) and from T0 to T2 (84 days), and the retention rate in patients treated with perazine, ziprasidone or olanzapine [adapted from Tybura et al. (2012)] Drug / T1 (14 days) T2 (12 weeks) PANSS total at T0 Retention Retention Percentage Percentage rate rate reduction in reduction in PANSS score PANSS score Perazine 99.8±15.8 17.2±16.7% 52/60 (87%) 24.0±21.7% 41/60 (68%) Olanzapine 97.5±16.7 19.1±15.1% 58/72 (81%) 29.2±20.6% 55/72 (76%) Ziprasidone 102.2±18.2 17.9±12.4% 44/59 (75%) 26.1±22.3% 40/59 (68%)

Tab. 2. Changes in body weights (BW) after 12 weeks of therapy Drug N BW (kg) BW (kg) Average SD T0 T2 change Ziprasidone 59 77.22 76.70 -0.51 2.35 Olanzapine 82 71.96 75.89 3.92 3.81 Perazine 60 72.07 73.50 1.43 2.69

Statistics F(2,198)=35.9, p<0.001

Tab. 3. Influence of genetic factors on changes in body weights after 12 weeks of antipsychotic treatment Statistics Polymorphism F(2,198) P COMT 0.09 0.91 MAOA 0.22 0.80 GRIK3 0.55 0.58 5HT2A 1.17 0.31 DAT 0.07 0.93 SERT 1.06 0.35 DRD2 ins/del 0.79 0.46 DRD2 Taq1A 0.55 0.58 DRD2 exon 8 0.11 0.89

Tab. 4. Changes in extrapyramidal symptoms (EPS) after 12 weeks of antipsychotic treatment Drug

N

Ziprasidone Olanzapine Perazine

59 82 60

Simpson-Angus Scale Barnes Akathisia Scale Average change SD Average change SD -0.051 2.674 0.898 2.503 0.476 3.601 0.744 2.053 5.300 6.603 2.617 3.320 Statistics H(2)=47.6, P<0.0001 H(2)=18.9, P<0.001

Tab. 5. Influence of genetic factors on changes in extrapyramidal symptoms after 12 weeks of antipsychotic treatment Simpson-Angus Scale

Barnes Akathisia Scale

Statistics

Statistics

Polymorphism COMT MAOA GRIK3 5HT2A DAT SERT DRD2 ins/del DRD2 Taq1A DRD2 exon 8

H(2) 2.70 0.77 2.93 3.71 3.86 0.02 0.37 0.41 1.41

P 0.25 0.68 0.23 0.15 0.14 0.99 0.83 0.81 0.49

H(2) 0.46 1.62 1.00 0.57 1.73 0.50 1.34 1.39 0.94

P 0.80 0.45 0.60 0.75 0.42 0.78 0.51 0.52 0.63