Pharmacogenomics can improve antipsychotic treatment in schizophrenia

Abstract

Schizophrenia is a widespread mental disease with a prevalence of about 1% in the world population, and heritability of up to 80%. Drug therapy is an important approach to treating the disease. However, the curative effect of antipsychotic is far from satisfactory in terms of tolerability and side effects. Many studies have indicated that about 30% of the patients exhibit little or no improvements associated with antipsychotics. The response of individual patients who are given the same dose of the same drug varies considerably. In addition, antipsychotic drugs are often accompanied by adverse drug reactions (ADRs), which can cause considerable financial loss in addition to the obvious societal harm. So, it is strongly recommended that personalized medicine should be implemented both to improve drug efficacy and to minimize adverse events and toxicity. There is therefore a need for pharmacogenomic studies into the factors affecting response of schizophrenia patients to antipsychotic drugs to provide informed guidance for clinicians. Individual differences in drug response is due to a combination of many complex factors including ADEM (absorption, distribution, metabolism, excretion) process, transporting, binding with receptor and intracellular signal transduction. Pharmacogenetic and pharmacogenomic studies have successfully identified genetic variants that contribute to this interindividual variability in antipsychotics response. In addition, epigenetic factors such as methylation of DNA and regulation by miRNA have also been reported to play an important role in the complex interactions between the multiple genes and environmental factors which influence individual drug response phenotypes in patients. In this review, we will focus on the latest research on polymorphisms of candidate genes that code for drug metabolic enzymes (CYP2D6, CYP1A2, CYP3A4, etc.), drug transporters (mainly ABCB1) and neurotransmitter receptors (dopamine receptors and serotonin receptors, etc.). We also discuss the genome-wide pharmacogenomic study of schizophrenia and review the current state of knowledge on epigenetics and potential clinical applications.

Keywords

pharmacogenomics / epigenetics / schizophrenia / antipsychotics

Introduction

Schizophrenia is a multi-factorial/polygenic complex disorder, which is often described in terms of positive and negative (or deficit) symptoms [1]. The positive symptoms include delusions, disordered thoughts and speech, and tactile, auditory, visual, olfactory and gustatory hallucinations, typically regarded as manifestations of psychosis [2]. The negative symptoms mainly include flat or blunted emotions, poverty of speech (alogia), inability to experience pleasure (anhedonia), lack of desire to form relationships (asociality), and lack of motivation (avolition) [3,4]. Schizophrenia onset typically occurs between late adolescence and young adulthood and its course is commonly chronic and severely disabling, causing significant public health and economic burdens. As a growing number of people become subject to this disorder, we have gradually entered the “schizophrenia era.”

As a complex disorder, the pathogenesis of schizophrenia is influenced by the comprehensive effect of manifold causes including genetic and environmental factors. Scientists have for some time been exploring the mechanism of the pathogenesis of schizophrenia in order to seek effective ways to cure it. Drug therapy is an important approach in schizophrenia treatment. The vast majority of antipsychotic drugs in current use can be classified into two categories: first-generation antipsychotic medications (FGAs) and second-generation antipsychotic medications (SGAs), also called typical antipsychotics and atypical antipsychotics, respectively. The FGAs have been effective in treating the positive symptoms of schizophrenia. The mechanism is that FGAs mainly tend to block the receptors in the brain’s dopamine pathways (mainly D2 receptors). The SGAs have been effective in treating the negative as well as the positive symptoms and are believed to act against a number of targets such as dopamine and serotonin receptors in the brain. The relative attributes of FGAs and SGAs are shown in Table1.

There is, however, the clinical problem that patients display significant differences in drug response after treatment with same dose of the same drug. Some patients are in remission after antipsychotic treatment, whereas others show no curative effects or even suffer from adverse drug reactions (ADRs) [5], including weight gain, extrapyramidal symptoms, tardive dyskinesia and agranulocytosis, etc. [6]. There is wide variability in patient response and toleration across the whole spectrum of antipsychotic medication.

At present, schizophrenic are generally treated on a “trial and error” basis with medication being constantly adjusted, rather than on scientific data or empirical evidence. This approach often leads to delays in treatment and increases the medical burden and can even lead to serious adverse reactions. The compliance of treatment is often bad, therefore it is very important to find appropriate antipsychotics earlier. Pharmacogenetic and pharmacogenomic studies have been successful in associating interindividual variability in antipsychotics response with genetic differences. Pharmacogenomics is the study of genetic variations that influence individual response to drugs. Pharmacogenomics is the broader application of genomic technologies to new drug discovery and further characterization of older drugs, while pharmacogenetics is generally regarded as the study or clinical testing of an individual’s genetic make-up in order to predict responses to a drug and guide prescription. The pharmacogenomic approach to schizophrenia is therefore of considerable significance. Its aim is to achieve personalized medicine—“mapping the right dose of the right drug to the right patient” [7] to both improve drug efficacy and minimize adverse events and toxicity.

The implementation of the Human Genome Project and genetic mechanism studies of schizophrenia have provided theoretical and technical support for research into the genetic aspect of variable drug efficacy as well as promoting the rapid development of pharmacogenomics. A recent genome-wide association study (GWAS) of the Han Chinese population identified common single nucleotide polymorphisms (SNPs) associated with schizophrenia of genome-wide significance on 8p12 [8]. Another two-stage GWAS of schizophrenia in the Han Chinese population identified two susceptibility loci for schizophrenia at 6p21-p22.1 and 11p11.2 [9]. These findings have provided a theoretical foundation for a pharmacogenomic approach to schizophrenia in the Chinese population.

Pharmacogenomic studies in schizophrenia

A range of complex influences can affect variability in drug response, including environmental (smoking and eating habits, etc.), clinical and demographic factors. However, evidence suggests that genetic factors play an important role in predicting individual drug response. Pharmacogenomic research on genetic factors involved in response to antipschotics has mainly focused on gene polymorphisms of drug metabolic enzymes, drug transporters and neurotransmitter receptors and recent pharmacogenomic and pharmacoepigenomic genome-wide association studies have made significant advances in this area which we will review.

Drug metabolic enzymes: the cytochrome P450 (CYP450) enzyme family

CYPs are the major enzymes involved in drug metabolism and bioactivation, accounting for about 75% of the total number of different metabolic reactions [17]. Antipsychotics are also metabolized by the CYP450 enzyme family. Phase I reactions (also called nonsynthetic reactions) may occur by oxidation, reduction, hydrolysis, cyclization, decyclization, addition of oxygen or removal of hydrogen, and are most mediated by the CYP450 enzyme family. Approximately 40% of antipsychotics are major substrates of CYP2D6 enzymes, 23% are major substrates of CYP3A4, and 18% are major substrates of CYP1A2 [18]. In this section, we will therefore focus on the latest research into gene polymorphisms of CYP2D6, CYP3A4 and CYP1A2 in schizophrenia.

CYP2D6

CYP2D6 is known to be involved in the main metabolic pathway of a number of antipsychotics, including most typical antipsychotics, some atypical antipsychotics, tricyclic antidepressants and some selective serotonin reuptake inhibitors. More than 90 allelic variants of the CYP2D6 gene have been identified [19]. These gene polymorphisms have been found to exhibit high individual variability in catalytic activity in response to drug dosage, and therefore affect clinical drug efficacy [20]. The presence of defective, one, two or multiple CYP2D6 gene copies results in patients being poor metabolizers (PMs), intermediate metabolizers (IMs), extensive metabolizers (EMs) and ultra rapid metabolizers (UMs). Of all the CYP2D6 phenotypes, PMs are of the highest significance for clinicians because this group is at risk of adverse reactions to medication and may reach toxic levels of medications at relatively low clinical doses. Several studies on different populations have confirmed that the CYP2D6 genotype strongly affects plasma levels of risperidone and the metabolic ratio in Italian, Japanese and Korean schizophrenic patients [21-23]. A recent study on drug-naive patients with first-episode schizophrenia treated with risperidone indicated that the CYP2D6 genotype had a significant influence on the steady-state dose-corrected levels of risperidone, 9-OH risperidone and on the active moiety [24]. The clinically significant groups of CYP2D6 PMs were characterized as having significantly higher levels of dose-corrected risperidone and active moiety, and lower levels of dose-corrected 9-OH risperidone [24]. Accumulating evidence has indicated that the metabolic ratio of antipsychotics substrate for CYP2D6 can be affected by these genetic variants. Wang et al. have studied the relationship between CYP2D6 genotypes and the metabolism of risperidone in Chinese schizophrenic patients. The study was performed on 108 Chinese schizophrenia patients (40 males, 78 females, aged 15–60 years) treated with risperidone. The results was in accordance with a previous studies [23,25-27] that the incidence of allele *10 is likely to contribute to the decreased CYP2D6 activity found in oriental populations. Although, the Wang’s study has demonstrated that there is no correlation within the genotypes of CYP2D6 with respect to clinical response [28], it warrants further validation in large-size samples.

CYP3A4

The commonly used antipsychotic drugs such as clozapine and haloperidol are metabolized by CYP3A4. Moreover, the CYP3A4 genes are located on 7q21.1 which is in close vicinity to schizophrenia susceptibility locus 7q22. Du et al. found that the two-marker haplotypes covering components CYP3A4*1G and CYP3A5*3 were significantly associated with schizophrenia (corrected global P = 0.0009) in the Chinese population, which suggests that CYP3A4 might play a role in genetic susceptibility to the disease [29]. Studies have suggested that CYP3A4 contributes significantly to the metabolism of risperidone [30,31]. Numerous variants of the CYP3A4 gene have been identified. Among these, CYP3A4*17 has been found to exhibit functional variability with a decreased activity, while CYP3A4*18 exhibits increased activity [32]. Du et al. [33]conducted a genetic association study of the CYP3A4 gene with clinical risperidone response in Chinese patients. This report found that CYP3A4*1G haplotype was associated with schizophrenic symptoms, but the association was not significant on adjusting for multiple testing. This study indicated that the effect of CYP3A4 gene variants on the therapeutic efficacy of risperidone might be weak [33]. Another study revealed that there is no significant association between CYP3A4*1B and the occurrence of tardive dyskinesia [34]. At present, the functional significance of the CYP3A4 polymorphism for drug efficiency needs further investigation.

CYP1A2

The CYP1A2 is the main metabolic pathway of the antipsychotics clozapine and olanzapine [35,36]. CYP1A2 presents a high interindividual variability in its activity and also in its inducibility by smoking. Cigarette smoking may be a factor influencing the plasma levels of antipsychotics that metabolize through CYP1A2. Interestingly, smokers have significantly higher molar ratio of caffeine metabolites in the urine (P<0.001) and saliva (P = 0.001) than nonsmokers, suggesting a higher activity of CYP1A2 caused by smoking [37]. In particular, CYP1A2*1C and *1D have a significantly increased metabolic rate in smokers [38]. It has been reported that CYP1A2*1C, CYP1A2*1K and CYP1A2*11 show decreased metabolic activity [39,40]. However, another study on a group of schizophrenia patients indicated that CYP1A2 polymorphisms *1F and *1D did not significantly influence clozapine metabolic capacity [41]. Further studies on larger groups are needed to confirm these results.

As stated, although many studies have found the polymorphism of CYP450 genotypes can affect the metabolism of antipsychotics, none of the studies have found associations between genetic variations in CYP450 enzymes and antipsychotic efficacy. However, since the sample size seems to be small, further studies on large sample size are required.

The drug transporters

Permeability glycoprotein (P-gp or Pgp), also known as multidrug resistance protein 1 (MDR1) or ATP binding cassette sub-family B member 1 (ABCB1), is a glycoprotein that in humans is encoded by the ABCB1 gene. ABCB1 is expressed in excretory organs (kidneys and liver), in intestine mucosa and on the blood-brain barrier. P-gp is a transport protein involved in drug absorption, distribution, and elimination. It functions as an efflux transporter in different cells, and also plays a major role in absorption, distribution and elimination of various xenobiotics. Because of the particular distribution of the protein, the activity of ABCB1 may significantly affect drug pharmacokinetics during absorption and distribution. In particular, ABCB1 may influence both blood and brain drug concentrations. Recently, a number of functional SNPs in the ABCB1 gene have been reported [42,43]. There is increasing evidence that genetic polymorphisms of the ABCB1 gene could contribute to the pharmacokinetics or pharmacodynamics of many chemotherapy drugs [44]. In recent years, many studies have reported possible association between ABCB1 polymorphisms and drug response in schizophrenia patients (Table 2). These reports suggest that genetic variation in the ABCB1 gene may influence the individual response to risperidone and ABCB1 genotyping should be considered as a novel strategy that should improve drug efficacy. But at the moment, we cannot draw the conclusion whether the patients who have a certain genotype of ABCB1 should be given higher/lower dose of antipsychotic. It needs further investigation.

Neurotransmitter receptors

Neurotransmitter systems are altered in the brain of schizophrenia patients. For example, the dopamine hypothesis of schizophrenia is based on the notion that excess dopaminergic activity leads to psychotic symptoms. Therefore, neurotransmitter systems have been used as targets for antipsychotic therapy. Most antipsychotics display a wide range of affinities for neurotransmitter receptors: mainly the dopamine receptor (DR) and the serotonin receptor (5-HT). The pharmacogenomic study of antipsychotics has revealed the association of genetic polymorphism of DR and 5-HT with treatment response.

Dopamine receptor can be classified into five subtypes: D1, D2, D3, D4 and D5. Among these, D2 and D3 are the most strongly targeted by antipsychotic drugs. Many reports have demonstrated the association of D2 and D3 genetic variants with response to antipsychotic drugs.

The D2 receptor is the main target of classical antipsychotic drugs chlorpromazine and haloperidol. Genetic polymorphisms on the D2 receptor gene region include -241A/G, -141Ins/Del in the functional promoter region, missense mutations 196Val/Ala, 311Ser/Cys and 310Pro/Ser in the coding region. Zhang et al. has reported that regulatory D2 polymorphisms can modify mRNA expression and splicing and working memory pathways [52]. Another study suggested that the SNPs in D2 may influence the treatment response to risperidone in schizophrenia patients [53]. A recent study reported that patients with the Cys311 allele had a significantly worse treatment response and presented with more prominent negative symptoms, and patients with the wild-type -141C Ins allele tended to have less pronounced or milder symptoms of schizophrenia compared with patients with the variant -141C Del allele [54]. Another study suggests that genotyping D2 -241A/G may help to predict the efficacy of risperidone treatment, because they found that patients with the A allele showed greater improvement than those with the G allele on the overall BPRS (the Brief Psychiatric Rating Scale) (χ² = 7.19, P = 0.007, P = 0.031), while other polymorphisms, including -141C Ins/Del, TaqIB, rs1076562, T939C and TaqIA, did not show any association with the response to risperidone [55].

Dopamine receptor D3 is expressed in phylogenetically older regions of the brain, suggesting that this receptor plays a role in cognitive and emotional functions. Therefore it is considered to be relevant to the pathology of schizophrenia and is an important candidate gene for the disease. One report has shown that the missense mutation of D3 9Ser/Gly is relevant to antipsychotic response. In vitro studies indicate that the 9Ser/Gly variants are associated with higher dopamine binding affinity [56]. Several recent studies focused on the 9Ser/Gly polymorphism of the D3 gene, but the results were inconclusive. Lane et al. performed a study on 123 Han Chinese patients suggesting that those with either 9Ser/Ser or 9Ser/Gly had a better performance on negative symptoms than patients with the 9Gly/Gly genotype after risperidone treatment (P = 0.0002 and 0.0092, respectively) [57]. However, our group performed a study in 130 schizophrenic patients from the mainland of China and no significant correlation was found between any variations and general symptom improvement, nor was a trend toward an excess of Ser9 variant observed in patients with better response [58]. Further study is needed.

The serotonin receptors, also known as 5-hydroxytryptamine receptors (5-HT receptors/5-HTR), influence various biological and neurological processes such as aggression, anxiety, appetite, cognition, learning, memory, etc. The serotonin receptors are the targets of a variety of pharmaceutical drugs, including many antidepressants and antipsychotics. Of the many subtypes of serotonin 5-HT receptors, the 5-HT 2A and 5-HT 2C subtypes have been the most extensively studied. Statistics indicate that the high occupancy of 5-HT 2 receptors by atypical antipsychotics is associated with improvements of negative symptoms and cognition [59]. Several studies have shown that the -1438A/G polymorphism of the 5-HT 2A gene is associated with clinical response to clozapine and other SGAs [60,61]. Interestingly, Benmessaoud et al. found that no allele of the -1438A/G polymorphism of the 5-HT 2A gene was excessively transmitted over a whole sample of schizophrenia patients (P = 0.90). By contrast, a significant excess of transmission of the G allele was observed (P= 0.02) in the subgroup of patients with good treatment response [62]. Based on previous research, it can be concluded that the G allele tags a subgroup of schizophrenic patients with greater chance of improvement with antipsychotics of either type. Several reports have suggested that 5-HT 2C and 5-HT 2A gene polymorphisms are associated with the occurrence of metabolic abnormalities in patients treated with olanzapine or clozapine [63]. Popp et al. performed a study on 102 Caucasian psychiatric in-patients, which suggested that the D4 receptor 48 bp variable number of tandem repeat but not the 5-HT 2C 23Cys/Ser receptor polymorphism is related to antipsychotic-induced weight gain [64]. Hill et al. identified 5-HT 2C -759C/T as a functional polymorphism and suggested disruption of DNA-protein interactions as a mechanism by which HTR 2C expression is perturbed leading to an influence on antipsychotic-induced weight gain [65].

Functional in vitro studies have demonstrated how nonsynonymous nucleotide substitutions in the coding region of the 5-HT 2A gene can alter the receptor’s binding affinity and the cellular functional effects of quetiapine [66]. 5-HT 2A would therefore appear to be an increasingly firm candidate antipsychotic pharmacogene. Also, a study performed on 130 schizophrenia patients has reported that the -1019 C/G polymorphism of 5-HT 1A was associated with negative symptom response to treatment. Patients with the CC genotype showed substantial improvement as regards negative symptom response (F = 4.177, df= 2, P = 0.019), compared with the patients with the CG and GG genotypes [67]. It suggests that the -1019 C/G polymorphism (rs6295) in the 5-HT 1A gene may be a useful predictor of reduction in negative symptoms in schizophrenic patients treated with risperidone. The polymorphism of 5-HT 3A is also reported to be a potential useful predictor of therapeutic response to risperidone treatment in schizophrenic patients [68]. Another study which aimed to identify the association of serotonin receptor 7 gene (HTR 7) and risperidone response in schizophrenia patients has not detected any significant correlation of HTR 7 with antipsychotic efficacy [69], which suggests that variations in the HTR 7 gene may not be good genetic markers for predicting the therapeutic efficacy of risperidone.

What is more, some studies show that the genetic polymorphism has an association with adverse drug reaction, such as tardive dyskinesia, weight gain, extrapyramidal symptoms, etc. A study found that the A allele of D2 receptor rs2440390 (A/G) was associated with greater weight gain in the entire study sample who were newly exposed to olanzapine (P = 0.0473) [70]. Kuzman et al. observed significant association of -759T 5-HT 2C genetic variant and greater increase in waist circumference (P = 0.03), fasting glucose level (P = 0.046) and triglyceride level (P = 0.045) in blood after a 3-month period. The 2677T and 3435T ABCB1 genetic variants were significantly associated with the greater increase in fasting glucose level in blood when patients were using olanzapine (P<0.001 and P = 0.028, respectively) [71]. Association of the SNP rs3943552 T allele in the GLI2 gene with tardive dyskinesia was observed in a subsample of Ashkenazi Jewish patients (N = 96, P = 0.018; P = 6.2 × 10^-5 in the Clinical Antipsychotic Trials of Intervention Effectiveness sample). Preliminary results indicated that dopamine D2 receptors C957T was associated with tardive dyskinesia in African-American sample (P = 0.047) [72]. These studies indicate that the genetic polymorphism could be a predictor for treatment outcomes in a subgroup of patients with schizophrenia.

Genome-wide pharmacogenomic analysis

Rather than studying the putative association of a few of candidate mutations, the genome-wide pharmacogenomic analysis of schizophrenia may provide effective guidance for predicting drug efficacy and side effects. McClay et al. performed a GWAS in 738 subjects from the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) study to detect genetic variation underlying individual differences in response to antipsychotic treatment [73]. They produced several interesting findings. The most significant association was with rs12860002 at 5-HT 2A, which mediates the effects of quetiapine on negative symptoms. Several markers close to the FMO5 locus showed association for mediating the effects of quetiapine on emotional distress symptoms. Another study used a genome-wide approach to search for genetic variations affecting susceptibility to antipsychotic-induced metabolic side effects. The principal finding was that rs1568679 in MEIS2 reached genome-wide significance in mediating the effect of risperidone on both hip and waist circumference and in showing secondary associations with body mass index, and diastolic and systolic blood pressure. There was also some evidence showing that this SNP mediates the effect of olanzapine effect on glucose [74]. These studies demonstrate the potential of GWAS to uncover novel genes that potentially mediate the effects of antipsychotics and to discover genes and pathways that mediate adverse effects of antipsychotic medication, which could eventually help to tailor treatment for individual schizophrenic patients.

Pharmacoepigenomic studies of drug efficacy in schizophrenia

Environmental factors can influence drug metabolism and drug response. Although the variability of drug response in individuals is usually attributed to genetic polymorphisms, many of the mechanisms cannot be attributed simply to diversity of DNA sequences. Therefore there is a need to recognize the role of pharmacoepigenomics in elucidating the complex interactions between the many genes and environmental factors which go to make up a distinct phenotype. Epigenetics refers to functionally relevant modifications to the genome (including DNA methylation, histone modification and regulation by miRNA) that do not involve a change in the nucleotide sequence. Many genes encoding drug metabolizing enzymes, drug transporters, nuclear receptors and drug targets are regulated by DNA methylation. These epigenetic changes will influence drug response [75]. It has been suggested that chemotherapeutic drugs can actively induce epigenetic changes within the MDR1 promoter, and enhance the MDR1 phenotype thus influencing the drug effect [76]. A study has indicated that CpG methylation may be involved in controlling the expression of CYP1A2, whereby hypermethylation reduces expression, which can influence the rate of drug metabolism [77]. Another study found a significant inverse association between the expression levels of miR-27b and CYP1B1 protein [78]. miRNAs can regulate not only essential genes for physiological events but also drug-metabolizing enzymes. Thus, it can be seen that epigenetic changes can lead to changes in gene function. Exposure to different environmental factors may result in individuals’ phenotype diversity with regard to disease susceptibility. Environmental factors include not only chemical substances and drugs but also social behavior which can end up with changes in the epigenome.

The application of pharmacogenomics in schizophrenia—personalized medicine

At present, the therapic effect of antipsychotics is far from satisfactory, with up to one-third of patients continuing to experience clinical relapse or unacceptable medication-related side-effects in spite of efforts to identify optimal treatment regimes with one or more drugs. The ultimate goal of pharmacogenetic studies is to achieve personalized medicine—mapping the right dose of the right drug to the individual patient to maximize the therapeutic effect and minimize drug-induced side effects. The application of pharmacogenomics in schizophrenia can assist in rational antipsychotic medication at the clinical level.

Phenotypic diversity among individual patients results in different tolerability to the same dose of the same drug. As mentioned above, metabolic enzymes such as CYP2D6, CYP3A4 and CYP1A2 can affects plasma levels of antipsychotic drugs. For example, poor metabolizers of CYP2D6 have a lower tolerance for drug doses, thus this group is at risk of adverse reactions and may reach toxic levels of medication at relatively low clinical doses. Such genotype patients could be given a lower dosage of a drug. Similarly, patients with a particular genotype might need higher doses to achieve the same plasma concentration (Table 2). Based on such information, optimal dosages could be calculated to avoid toxic metabolite accumulation. The implementation of pharmacogenomics can thus provide substantial advances in schizophrenia treatment.

Side effects associated with antipsychotic treatment are even more important than antipsychotic efficacy in considering which drug to choose. The patients who have severe or lasting side effects associated with antipsychotic treatment often manifest poor compliance. Therefore adverse drug reaction greatly contributes to treatment failure. There are many adverse drug reactions caused by antipsychotic drugs, but the most severe and troublesome ones include tardive dyskinesia (mainly caused by second-generation antipsychotics), agranulocytosis, extrapyramidal symptoms, and weight gain (commonly associated with second-generation antipsychotics, especially clozapine, olanzapine, and quetiapine). A number of studies have reported the association of antipsychotic-induced side effect with genetic variants [6]. Although there are contradictory findings, several genetic variants have gained consistent support. For tardive dyskinesia, the Taq1A in D2 receptor, the Ser9Gly in D3 receptor, the T102C SNP in 5-HT 2A, and the loss of functional variants in CYP2D6 may warrant further research. For weight gain, the only promising variant for which substantial data has been accumulated is the C759T SNP in 5-HT 2C [5]. Pharmacogenetics provides a promising tool to prevent side effects in the clinical management of schizophrenia patients.

Challenges and prospects

From the perspective of pharmacogenetics, drug processes involve drug metabolism, drug transporting and drug targeting which involves multi-gene interactions and cumulative effects. The effect of single genetic variants may be weak, while the combination and cumulative effect of many variants will lead to wide differences of drug response in individual patients. At present, many studies of pharmacogenomics in schizophrenia have been reported. However, most of them have studied only a few polymorphisms. As the metabolism of antipsychotics is complex, in order to provide comprehensive information with sufficient sensitivity and specificity for clinical guidance, a systematic analysis of polymorphisms across multiple loci, including genes encoding metabolic enzyme, drug transporters, drug targets and epigenetics, etc., will be required. Large sample size and reliable clinical data are also needed.

Although the pharmacogenomic studies of schizophrenia have identified a number of genetic markers that can be used to predict drug response and side effects, a credible model to guide efficient medication has not yet been created. Personalized medicine remains a challenge because of the complexity and multifactorial character of drug response. The implementation of personalized medicine needs to consider genetic, environmental and personal variables. To fulfill the promise of personalized medicine, large pharmacogenetic clinical trials are needed. In summary, the pharmacogenomics contribution to schizophrenia treatment is both promising and challenging. The development of GWAS and second-generation sequencing technology can promote this contribution.

References

[1] Schultze-Lutter F. Subjective symptoms of schizophrenia in research and the clinic: the basic symptom concept. Schizophr Bull2009; 35(1): 5-8

[2] Fletcher PC, Frith CD. Perceiving is believing: a Bayesian approach to explaining the positive symptoms of schizophrenia. Nat Rev Neurosci2009; 10(1): 48-58

[3] Phan SV, Kreys TJ. Adjunct mirtazapine for negative symptoms of schizophrenia. Pharmacotherapy2011; 31(10): 1017-1030

[4] Hovington CL, Lepage M. Neurocognition and neuroimaging of persistent negative symptoms of schizophrenia. Expert Rev Neurother2012; 12(1): 53-69

[5] Zhang JP, Malhotra AK. Pharmacogenetics and antipsychotics: therapeutic efficacy and side effects prediction. Expert Opin Drug Metab Toxicol2011; 7(1): 9-37

[6] Arranz MJ, de Leon J. Pharmacogenetics and pharmacogenomics of schizophrenia: a review of last decade of research. Mol Psychiatry2007; 12(8): 707-747

[7] Hamburg MA, Collins FS. The path to personalized medicine. N Engl J Med2010; 363(4): 301-304

[8] Shi Y, Li Z, Xu Q, Wang T, Li T, Shen J, Zhang F, Chen J, Zhou G, Ji W, Li B, Xu Y, Liu D, Wang P, Yang P, Liu B, Sun W, Wan C, Qin S, He G, Steinberg S, Cichon S, Werge T, Sigurdsson E, Tosato S, Palotie A, Nöthen MM, Rietschel M, Ophoff RA, Collier DA, Rujescu D, Clair DS, Stefansson H, Stefansson K, Ji J, Wang Q, Li W, Zheng L, Zhang H, Feng G, He L. Common variants on 8p12 and 1q24.2 confer risk of schizophrenia. Nat Genet2011; 43(12): 1224-1227

[9] Yue WH, Wang HF, Sun LD, Tang FL, Liu ZH, Zhang HX, Li WQ, Zhang YL, Zhang Y, Ma CC, Du B, Wang LF, Ren YQ, Yang YF, Hu XF, Wang Y, Deng W, Tan LW, Tan YL, Chen Q, Xu GM, Yang GG, Zuo XB, Yan H, Ruan YY, Lu TL, Han X, Ma XH, Wang Y, Cai LW, Jin C, Zhang HY, Yan J, Mi WF, Yin XY, Ma WB, Liu Q, Kang L, Sun W, Pan CY, Shuang M, Yang FD, Wang CY, Yang JL, Li KQ, Ma X, Li LJ, Yu X, Li QZ, Huang X, Lv LX, Li T, Zhao GP, Huang W, Zhang XJ, Zhang D. Genome-wide association study identifies a susceptibility locus for schizophrenia in Han Chinese at 11p11.2. Nat Genet2011; 43(12): 1228-1231

[10] Leucht S, Heres S, Kissling W, Davis JM. Evidence-based pharmacotherapy of schizophrenia. Int J Neuropsychopharmacol2011; 14(2): 269-284

[11] Foussias G, Remington G. Antipsychotics and schizophrenia: from efficacy and effectiveness to clinical decision-making. Can J Psychiatry2010; 55(3): 117-125

[12] Hill SK, Bishop JR, Palumbo D, Sweeney JA. Effect of second-generation antipsychotics on cognition: current issues and future challenges. Expert Rev Neurother2010; 10(1): 43-57

[13] Guo X, Fang M, Zhai J, Wang B, Wang C, Hu B, Sun X, Lv L, Lu Z, Ma C, Guo T, Xie S, Twamley EW, Jin H, Zhao J. Effectiveness of maintenance treatments with atypical and typical antipsychotics in stable schizophrenia with early stage: 1-year naturalistic study. Psychopharmacology (Berl)2011; 216(4): 475-484

[14] Citrome L. A systematic review of meta-analyses of the efficacy of oral atypical antipsychotics for the treatment of adult patients with schizophrenia. Expert Opin Pharmacother2012; 13(11): 1545-1573

[15] Crossley NA, Constante M, McGuire P, Power P. Efficacy of atypical v. typical antipsychotics in the treatment of early psychosis: meta-analysis. Br J Psychiatry2010; 196(6): 434-439

[16] De Hert M, Schreurs V, Sweers K, Van Eyck D, Hanssens L, Sinko S, Wampers M, Scheen A, Peuskens J, van Winkel R. Typical and atypical antipsychotics differentially affect long-term incidence rates of the metabolic syndrome in first-episode patients with schizophrenia: a retrospective chart review. Schizophr Res2008; 101(1-3): 295-303

[17] Guengerich FP. Cytochrome p450 and chemical toxicology. Chem Res Toxicol2008; 21(1): 70-83

[18] Cacabelos R, Hashimoto R, Takeda M. Pharmacogenomics of antipsychotics efficacy for schizophrenia. Psychiatry Clin Neurosci2011; 65(1): 3-19

[19] Kirchheiner J, Nickchen K, Bauer M, Wong ML, Licinio J, Roots I, Brockmöller J. Pharmacogenetics of antidepressants and antipsychotics: the contribution of allelic variations to the phenotype of drug response. Mol Psychiatry2004; 9(5): 442-473

[20] Teh LK, Bertilsson L. Pharmacogenomics of CYP2D6: molecular genetics, interethnic differences and clinical importance. Drug Metab Pharmacokinet2012; 27(1): 55-67

[21] Yasui-Furukori N, Mihara K, Takahata T, Suzuki A, Nakagami T, De Vries R, Tateishi T, Kondo T, Kaneko S. Effects of various factors on steady-state plasma concentrations of risperidone and 9-hydroxyrisperidone: lack of impact of MDR-1 genotypes. Br J Clin Pharmacol2004; 57(5): 569-575

[22] Gunes A, Spina E, Dahl ML, Scordo MG. ABCB1 polymorphisms influence steady-state plasma levels of 9-hydroxyrisperidone and risperidone active moiety. Ther Drug Monit2008; 30(5): 628-633

[23] Roh HK, Kim CE, Chung WG, Park CS, Svensson JO, Bertilsson L. Risperidone metabolism in relation to CYP2D6*10 allele in Korean schizophrenic patients. Eur J Clin Pharmacol2001; 57(9): 671-675

[24] Jovanović N, Božina N, Lovrić M, Medved V, Jakovljević M, Peleš AM. The role of CYP2D6 and ABCB1 pharmacogenetics in drug-naïve patients with first-episode schizophrenia treated with risperidone. Eur J Clin Pharmacol2010; 66(11): 1109-1117

[25] Scordo MG, Spina E, Facciolà G, Avenoso A, Johansson I, Dahl ML. Cytochrome P450 2D6 genotype and steady state plasma levels of risperidone and 9-hydroxyrisperidone. Psychopharmacology (Berl)1999; 147(3): 300-305

[26] Mihara K, Kondo T, Yasui-Furukori N, Suzuki A, Ishida M, Ono S, Kubota T, Iga T, Takarada Y, de Vries R, Kaneko S. Effects of various CYP2D6 genotypes on the steady-state plasma concentrations of risperidone and its active metabolite, 9-hydroxyrisperidone, in Japanese patients with schizophrenia. Ther Drug Monit2003; 25(3): 287-293

[27] Yasui-Furukori N, Mihara K, Kondo T, Kubota T, Iga T, Takarada Y, De Vries R, Kaneko S, Tateishi T. Effects of CYP2D6 genotypes on plasma concentrations of risperidone and enantiomers of 9-hydroxyrisperidone in Japanese patients with schizophrenia. J Clin Pharmacol2003; 43(2): 122-127

[28] Wang L, Yu L, Zhang AP, Fang C, Du J, Gu NF, Qin SY, Feng GY, Li XW, Xing QH, He L. Serum prolactin levels, plasma risperidone levels, polymorphism of cytochrome P450 2D6 and clinical response in patients with schizophrenia. J Psychopharmacol2007; 21(8): 837-842

[29] Du J, Xu Y, Duan S, Zhang A, Xuan J, Wang L, Yu L, Wang H, Li X, Feng G, He L, Xing Q. A case-control association study between the CYP3A4 and CYP3A5 genes and schizophrenia in the Chinese Han population. Prog Neuropsychopharmacol Biol Psychiatry2009; 33(7): 1200-1204

[30] Mahatthanatrakul W, Nontaput T, Ridtitid W, Wongnawa M, Sunbhanich M. Rifampin, a cytochrome P450 3A inducer, decreases plasma concentrations of antipsychotic risperidone in healthy volunteers. J Clin Pharm Ther2007; 32(2): 161-167

[31] Mahatthanatrakul W, Sriwiriyajan S, Ridtitid W, Boonleang J, Wongnawa M, Rujimamahasan N, Pipatrattanaseree W. Effect of cytochrome P450 3A4 inhibitor ketoconazole on risperidone pharmacokinetics in healthy volunteers. J Clin Pharm Ther2012; 37(2): 221-225

[32] Dai D, Tang J, Rose R, Hodgson E, Bienstock RJ, Mohrenweiser HW, Goldstein JA. Identification of variants of CYP3A4 and characterization of their abilities to metabolize testosterone and chlorpyrifos. J Pharmacol Exp Ther2001; 299(3): 825-831

[33] Du J, Zhang A, Wang L, Xuan J, Yu L, Che R, Li X, Gu N, Lin Z, Feng G, Xing Q, He L. Relationship between response to risperidone, plasma concentrations of risperidone and CYP3A4 polymorphisms in schizophrenia patients. J Psychopharmacol2010; 24(7): 1115-1120

[34] Tiwari AK, Deshpande SN, Rao AR, Bhatia T, Lerer B, Nimgaonkar VL, Thelma BK. Genetic susceptibility to tardive dyskinesia in chronic schizophrenia subjects: III. Lack of association of CYP3A4 and CYP2D6 gene polymorphisms. Schizophr Res2005; 75(1): 21-26

[35] Eiermann B, Engel G, Johansson I, Zanger UM, Bertilsson L. The involvement of CYP1A2 and CYP3A4 in the metabolism of clozapine. Br J Clin Pharmacol1997; 44(5): 439-446

[36] Ring BJ, Catlow J, Lindsay TJ, Gillespie T, Roskos LK, Cerimele BJ, Swanson SP, Hamman MA, Wrighton SA. Identification of the human cytochromes P450 responsible for the in vitro formation of the major oxidative metabolites of the antipsychotic agent olanzapine. J Pharmacol Exp Ther1996; 276(2): 658-666

[37] Bozikas VP, Papakosta M, Niopas I, Karavatos A, Mirtsou-Fidani V. Smoking impact on CYP1A2 activity in a group of patients with schizophrenia. Eur Neuropsychopharmacol2004; 14(1): 39-44

[38] Pavanello S, Pulliero A, Lupi S, Gregorio P, Clonfero E. Influence of the genetic polymorphism in the 5′-noncoding region of the CYP1A2 gene on CYP1A2 phenotype and urinary mutagenicity in smokers. Mutat Res2005; 587(1-2): 59-66

[39] Murayama N, Soyama A, Saito Y, Nakajima Y, Komamura K, Ueno K, Kamakura S, Kitakaze M, Kimura H, Goto Y, Saitoh O, Katoh M, Ohnuma T, Kawai M, Sugai K, Ohtsuki T, Suzuki C, Minami N, Ozawa S, Sawada J. Six novel nonsynonymous CYP1A2 gene polymorphisms: catalytic activities of the naturally occurring variant enzymes. J Pharmacol Exp Ther2004; 308(1): 300-306

[40] Sachse C, Brockmöller J, Bauer S, Roots I. Functional significance of a C—>A polymorphism in intron 1 of the cytochrome P450 CYP1A2 gene tested with caffeine. Br J Clin Pharmacol1999; 47(4): 445-449

[41] Kootstra-Ros JE, Smallegoor W, van der Weide J. The cytochrome P450 CYP1A2 genetic polymorphisms *1F and *1D do not affect clozapine clearance in a group of schizophrenic patients. Ann Clin Biochem2005; 42(Pt 3): 216-219

[42] Hoffmeyer S, Burk O, von Richter O, Arnold HP, Brockmöller J, Johne A, Cascorbi I, Gerloff T, Roots I, Eichelbaum M, Brinkmann U. Functional polymorphisms of the human multidrug-resistance gene: multiple sequence variations and correlation of one allele with P-glycoprotein expression and activity in vivo. Proc Natl Acad Sci USA2000; 97(7): 3473-3478

[43] Kerb R, Hoffmeyer S, Brinkmann U. ABC drug transporters: hereditary polymorphisms and pharmacological impact in MDR1, MRP1 and MRP2. Pharmacogenomics2001; 2(1): 51-64

[44] Marzolini C, Paus E, Buclin T, Kim RB. Polymorphisms in human MDR1 (P-glycoprotein): recent advances and clinical relevance. Clin Pharmacol Ther2004; 75(1): 13-33

[45] Xing Q, Gao R, Li H, Feng G, Xu M, Duan S, Meng J, Zhang A, Qin S, He L. Polymorphisms of the ABCB1 gene are associated with the therapeutic response to risperidone in Chinese schizophrenia patients. Pharmacogenomics2006; 7(7): 987-993

[46] Alenius M, Wadelius M, Dahl ML, Hartvig P, Lindström L, Hammarlund-Udenaes M. Gene polymorphism influencing treatment response in psychotic patients in a naturalistic setting. J Psychiatr Res2008; 42(11): 884-893

[47] Consoli G, Lastella M, Ciapparelli A, Catena Dell’Osso M, Ciofi L, Guidotti E, Danesi R, Dell’Osso L, Del Tacca M, Di Paolo A. ABCB1 polymorphisms are associated with clozapine plasma levels in psychotic patients. Pharmacogenomics2009; 10(8): 1267-1276

[48] Skogh E, Sjödin I, Josefsson M, Dahl ML. High correlation between serum and cerebrospinal fluid olanzapine concentrations in patients with schizophrenia or schizoaffective disorder medicating with oral olanzapine as the only antipsychotic drug. J Clin Psychopharmacol2011; 31(1): 4-9

[49] Kuzman MR, Medved V, Bozina N, Grubišin J, Jovanovic N, Sertic J. Association study of MDR1 and 5-HT2C genetic polymorphisms and antipsychotic-induced metabolic disturbances in female patients with schizophrenia. Pharmacogenomics J2011; 11(1): 35-44

[50] Xiang Q, Zhao X, Zhou Y, Duan JL, Cui YM. Effect of CYP2D6, CYP3A5, and MDR1 genetic polymorphisms on the pharmacokinetics of risperidone and its active moiety. J Clin Pharmacol2010; 50(6): 659-666

[51] Ghotbi R, Mannheimer B, Aklillu E, Suda A, Bertilsson L, Eliasson E, Osby U. Carriers of the UGT1A4 142T>G gene variant are predisposed to reduced olanzapine exposure—an impact similar to male gender or smoking in schizophrenic patients. Eur J Clin Pharmacol2010; 66(5): 465-474

[52] Zhang Y, Bertolino A, Fazio L, Blasi G, Rampino A, Romano R, Lee MLT, Xiao T, Papp A, Wang DX, Sadée W. Polymorphisms in human dopamine D2 receptor gene affect gene expression, splicing, and neuronal activity during working memory. Proc Natl Acad Sci USA2007; 104(51): 20552-20557

[53] Ikeda M, Yamanouchi Y, Kinoshita Y, Kitajima T, Yoshimura R, Hashimoto S, O’Donovan MC, Nakamura J, Ozaki N, Iwata N. Variants of dopamine and serotonin candidate genes as predictors of response to risperidone treatment in first-episode schizophrenia. Pharmacogenomics2008; 9(10): 1437-1443

[54] Zahari Z, Teh LK, Ismail R, Razali SM. Influence of DRD2 polymorphisms on the clinical outcomes of patients with schizophrenia. Psychiatr Genet2011; 21(4): 183-189

[55] Xing Q, Qian X, Li H, Wong S, Wu S, Feng G, Duan S, Xu M, Gao R, Qin W, Gao J, Meng J, He L. The relationship between the therapeutic response to risperidone and the dopamine D2 receptor polymorphism in Chinese schizophrenia patients. Int J Neuropsychopharmacol2007; 10(5): 631-637

[56] Lundstrom K, Turpin MP. Proposed schizophrenia-related gene polymorphism: expression of the Ser9Gly mutant human dopamine D3 receptor with the Semliki Forest virus system. Biochem Biophys Res Commun1996; 225(3): 1068-1072

[57] Lane HY, Hsu SK, Liu YC, Chang YC, Huang CH, Chang WH. Dopamine D3 receptor Ser9Gly polymorphism and risperidone response. J Clin Psychopharmacol2005; 25(1): 6-11

[58] Xuan JK, Zhao XZ, He G, Yu L, Wang L, Tang W, Li XW, Gu NF, Feng GY, Xing QH, He L. Effects of the dopamine D3 receptor (DRD3) gene polymorphisms on risperidone response: a pharmacogenetic study. Neuropsychopharmacology2008; 33(2): 305-311

[59] Travis MJ, Busatto GF, Pilowsky LS, Mulligan R, Acton PD, Gacinovic S, Mertens J, Terrière D, Costa DC, Ell PJ, Kerwin RW. 5-HT2A receptor blockade in patients with schizophrenia treated with risperidone or clozapine. A SPET study using the novel 5-HT2A ligand 123I-5-I-R-91150. Br J Psychiatry1998; 173(3): 236-241

[60] Parsons MJ, D’Souza UM, Arranz MJ, Kerwin RW, Makoff AJ. The-1438A/G polymorphism in the 5-hydroxytryptamine type 2A receptor gene affects promoter activity. Biol Psychiatry2004; 56(6): 406-410

[61] Myers RL, Airey DC, Manier DH, Shelton RC, Sanders-Bush E. Polymorphisms in the regulatory region of the human serotonin 5-HT2A receptor gene (HTR2A) influence gene expression. Biol Psychiatry2007; 61(2): 167-173

[62] Benmessaoud D, Hamdani N, Boni C, Ramoz N, Hamon M, Kacha F, Gorwood P. Excess of transmission of the G allele of the‐1438A/G polymorphism of the 5‐HT(2A) receptor gene in patients with schizophrenia responsive to antipsychotics. BMC Psychiatry. 2008 May 30; 8:40

[63] Gunes A, Melkersson KI, Scordo MG, Dahl ML. Association between HTR2C and HTR2A polymorphisms and metabolic abnormalities in patients treated with olanzapine or clozapine. J Clin Psychopharmacol2009; 29(1): 65-68

[64] Popp J, Leucht S, Heres S, Steimer W. DRD4 48 bp VNTR but not 5-HT 2C Cys23Ser receptor polymorphism is related to antipsychotic-induced weight gain. Pharmacogenomics J2009; 9(1): 71-77

[65] Hill MJ, Reynolds GP. Functional consequences of two HTR2C polymorphisms associated with antipsychotic-induced weight gain. Pharmacogenomics2011; 12(5): 727-734

[66] Davies MA, Setola V, Strachan RT, Sheffler DJ, Salay E, Hufeisen SJ, Roth BL. Pharmacologic analysis of non-synonymous coding h5-HT2A SNPs reveals alterations in atypical antipsychotic and agonist efficacies. Pharmacogenomics J2006; 6(1): 42-51

[67] Wang L, Fang C, Zhang A, Du J, Yu L, Ma J, Feng G, Xing Q, He L. The -1019 C/G polymorphism of the 5-HT(1)A receptor gene is associated with negative symptom response to risperidone treatment in schizophrenia patients. J Psychopharmacol2008; 22(8): 904-909

[68] Gu B, Wang L, Zhang AP, Ma G, Zhao XZ, Li HF, Feng GY, He L, Xing QH. Association between a polymorphism of the HTR3A gene and therapeutic response to risperidone treatment in drug-naive Chinese schizophrenia patients. Pharmacogenet Genomics2008; 18(8): 721-727

[69] Wei Z, Wang L, Xuan J, Che R, Du J, Qin S, Xing Y, Gu B, Yang L, Li H, Li J, Feng G, He L, Xing Q. Association analysis of serotonin receptor 7 gene (HTR7) and risperidone response in Chinese schizophrenia patients. Prog Neuropsychopharmacol Biol Psychiatry2009; 33(3): 547-551

[70] Houston JP, Kohler J, Bishop JR, Ellingrod VL, Ostbye KM, Zhao F, Conley RR, Poole Hoffmann V, Fijal BA. Pharmacogenomic associations with weight gain in olanzapine treatment of patients without schizophrenia. J Clin Psychiatry2012; 73(8): 1077-1086

[71] Kuzman MR, Medved V, Bozina N, Grubišin J, Jovanovic N, Sertic J. Association study of MDR1 and 5-HT2C genetic polymorphisms and antipsychotic-induced metabolic disturbances in female patients with schizophrenia. Pharmacogenomics J2011; 11(1): 35-44

[72] Zai CC, Hwang RW, De Luca V, Müller DJ, King N, Zai GC, Remington G, Meltzer HY, Lieberman JA, Potkin SG, Kennedy JL. Association study of tardive dyskinesia and twelve DRD2 polymorphisms in schizophrenia patients. Int J Neuropsychopharmacol2007; 10(5): 639-651

[73] McClay JL, Adkins DE, Aberg K, Stroup S, Perkins DO, Vladimirov VI, Lieberman JA, Sullivan PF, van den Oord EJ. Genome-wide pharmacogenomic analysis of response to treatment with antipsychotics. Mol Psychiatry2011; 16(1): 76-85

[74] Adkins DE, Aberg K, McClay JL, Bukszár J, Zhao Z, Jia P, Stroup TS, Perkins D, McEvoy JP, Lieberman JA, Sullivan PF, van den Oord EJ. Genomewide pharmacogenomic study of metabolic side effects to antipsychotic drugs. Mol Psychiatry2011; 16(3): 321-332

[75] Ingelman-Sundberg M, Gomez A. The past, present and future of pharmacoepigenomics. Pharmacogenomics2010; 11(5): 625-627

[76] Baker EK, Johnstone RW, Zalcberg JR, El-Osta A. Epigenetic changes to the MDR1 locus in response to chemotherapeutic drugs. Oncogene2005; 24(54): 8061-8075

[77] Hammons GJ, Yan-Sanders Y, Jin B, Blann E, Kadlubar FF, Lyn-Cook BD. Specific site methylation in the 5′-flanking region of CYP1A2 interindividual differences in human livers. Life Sci2001; 69(7): 839-845

[78] Tsuchiya Y, Nakajima M, Takagi S, Taniya T, Yokoi T. MicroRNA regulates the expression of human cytochrome P450 1B1. Cancer Res2006; 66(18): 9090-9098

RIGHTS & PERMISSIONS

Higher Education Press and Springer-Verlag Berlin Heidelberg