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Pharmacogenomics: a path to predictive medicine for schizophrenia Simone Gupta1, Sanjeev Jain2, Samir K Brahmachari1 & Ritushree Kukreti1† †Author

for correspondence of Genomics and Integrative Biology (CSIR), Delhi University Campus, Delhi 110007, India Tel.: +91 11 2766 2202; E-mail: ritushree@ hotmail.com 2National Institute of Mental Health and Neuro Sciences, Department of Psychiatry, Hosur Road, Bangalore – 560029, India 1Institute

A significant variability is observed among patients in response to antipsychotics, and is caused by a variety of factors. This review summarizes the available knowledge of associations between pharmacogenetics and drug response in schizophrenia. The multifactorial etiology of schizophrenia makes it a complex interaction of symptoms. Adopting a pharmacogenomics approach represents a unique opportunity for the prediction of response to antipsychotic drugs by investigating genes implicated with specific symptoms and side effects. A network model of the interaction/crosstalk between the neurotransmitter signaling systems is presented to emphasize the importance of the genes associated with the molecular mechanisms of the disease and drug response. These genes may serve as potential susceptibility genes and drug targets for schizophrenia. The crucial point for the identification of a significant biologic marker(s) will include not only the experimental validation of the genes involved in the neurotransmitter signaling systems, but also the availability of large exactly comparable phenotyped patients samples. Coupling our knowledge of genetic polymorphisms with clinical response data promises a bright future for rapid advances in personalized medicine.

Schizophrenia is a complex psychiatric syndrome characterized by clusters of specific clinical symptoms, with extensive variation between individuals [1]. Several meta-analyses of large schizophrenic populations have demonstrated the clustering of symptoms into: • Positive symptoms, including hallucinations, delusions, thought disorder, and paranoia • Negative symptoms with anhedonia, social withdrawal and poverty of thought

Keywords: drug-metabolizing enzymes, drug targets, neurotransmitter signaling pathways, pharmacogenetics, pharmacogenomics, schizophrenia, single nucleotide polymorphism

Cognitive dysfunction is also observed in most cases involving deficits, particularly in attention, working memory and executive function. Patients also often experience depression and anxiety, express aggression and become demoralized [1]. Variability is observed among patients as these symptoms may co-occur or occur independent of each other, and often even change over time. The susceptibility to schizophrenia is strongly heritable and is transmitted in a complex non-Mendelian manner [2]. Many studies, including twin, family, and adoption studies, suggest that schizophrenia has a multifactorial genetic component involving multiple genes interacting in a complex manner with influential epigenetic and environmental factors [3]. The lifetime prevalence of schizophrenia has been reported to be 1% of the world population [3]. In a population of nearly one billion there are estimated to be 4 million people with schizophrenia

10.2217/14622416.7.1.31 © 2006 Future Medicine Ltd ISSN 1462-2416

in India alone [201]. The vast costs associated with schizophrenia are estimated to account for approximately 2% of the annual total healthcare expenditure in most countries [3]. Schizophrenia has become one of the most important public health problems confronted by society, with 90% of untreated schizophrenics residing in the poorest countries [201]. In the pharmacotherapy of schizophrenia, the classical typical and the more recent atypical antipsychotics can be differentiated. Typical antipsychotics, for example, haloperidol and chlorpromazine, are primarily dopamine antagonists, effective in alleviating positive symptoms, and may not be fully curative for negative symptoms of schizophrenia, while at the same time they possess the ability to cause extrapyramidal side effects such as tardive dyskinesia [4]. The disadvantages caused by this class of antipsychotics led to the introduction of the atypical antipsychotics such as clozapine, risperidone and olanzapine, which alleviate both positive and negative symptoms and target multiple central receptor sites [4,5], notably serotonin along with dopamine. In 1989, Meltzer proposed the serotonin–dopamine hypothesis, where the 5-hydroxytryptamine 2A (5-HT2A) receptor antagonism, in association with the relatively weak D2 receptor antagonism, could differentiate most atypical antipsychotics from typical antipsychotics [6,7]. This model is useful for the development of new Pharmacogenomics (2006) 7(1), 31–47

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REVIEW – Gupta, Jain, Brahmachari & Kukreti

drugs to achieve a significant antipsychotic effect with a lower incidence of extrapyramidal side effects compared with first-generation antipsychotics [8]. This model is in contrast to the ‘fast-off dopamine’ theory by Kapur and Seeman, which states that an atypical antipsychotic agent occupies D2 receptors to a similar extent as typical antipsychotics, but rapidly dissociate from receptors, to produce antipsychotic effect without extrapyramidal side effects and compounds with a relatively low risk of tardive dyskinesia [9]. However, response to both classes of antipsychotic drugs remains heterogeneous and variable. These observed interindividual variations may be caused by a variety of factors among which genetic components presumably play a major role. Pharmacogenetics is defined as the science of pharmacologic response and its modification by hereditary influence that can be divided into two categories: • The genetic background of pharmacokinetics – the absorption, distribution, tissue localization, biotransformation and excretion of drugs • Pharmacodynamics – the biochemical and physiologic consequences of a drug and its mechanism of action [10] The focus of pharmacogenetics is to determine the genetic polymorphisms in drug-metabolizing enzymes (DMEs) and drug targets that influence inherited patient variation in drug response. Single nucleotide polymorphisms (SNPs), observed between individuals in a population, are present throughout the human genome with a frequency of approximately 1 per 1000 base pairs, and 10.1 million human reference SNPs have been deposited into the public database dbSNP [11]. Understanding of human genetic variations promises to have a great impact on the ability to uncover the cause of individual variation in response to therapeutics [12]. Individual polymorphisms alone may be unable to explain variability to treatment, and a combination of polymorphisms in multiple genes may provide a better predictive value of response. As a result, targeting and investigating multiple genes and adopting a pharmacogenomics approach to identifying genes that together govern an individual’s response to drug therapy has recently been introduced in the pharmacogenomics of antipsychotics [10]. The new field of pharmacogenomics now promises to help in the prescription of individual specific drugs that are both safer and more effective for each patient, and also leads to the development of new targets. 32

As most of the drug effects are a consequence of the interplay of several gene products that govern the pharmacokinetics and pharmacodynamics of medications, improved understanding of related brain networks will aid in the understanding and prediction of the phenotypic effects of genes at the clinical level (Figure 1). This review presents the need for data extraction from various sources, including genetic, expression, clinical and pharmacogenetic studies, to provide insights into the functions of the genes involved in the interaction between neurotransmitter signaling mechanisms that may mediate the pathologic processes in schizophrenia. In this review, knowledge of the effect of DMEs and receptor/transporter polymorphisms associated with antipsychotic response is presented. A model for the interaction/crosstalk between the neurotransmitter signaling systems is also outlined, and the importance of the genes in the molecular mechanisms of the disease is emphasized. These genes may serve as potential candidates for disease susceptibility or drug targets for schizophrenia. Adopting a pharmacogenomics approach will provide a unique opportunity for the prediction of response to antipsychotic drugs by investigation of the genes related to specific symptoms and side effects. Genetic variation at the pharmacokinetic level: DMEs Most DMEs exhibit clinically relevant genetic polymorphisms. DMEs include oxidative drug metabolizing enzymes such as cytochrome P450s (CYPs), flavin-containing monooxygenases (FMOs), aldehyde and alcohol dehydrogenases and esterases responsible for the modification of functional groups (Phase I reactions). DMEs also include the conjugative enzyme families such as uridine diphosphateglycosyltransferases (UGTs), glutathione transferases (GSTs), catechol O-methyltransferase, sulfotransferases (SULTs), and N-acetyltransferases (NATs) involved in conjugation with endogenous substituents (Phase II reactions) [5]. The CYP enzymes represent a large family of DMEs, catalyzing the metabolism of more medications than any other family of enzymes. Among these enzymes, CYP2C9, CYP2C19, CYP1A2, CYP3A4, and CYP2D6 are related to the metabolism of drugs used in psychiatry [13]. Currently, six forms of the FMO gene are known. However, FMO3 is the major form in the adult human liver and is likely to be responsible for the majority of FMO-mediated metabolism. Pharmacogenomics (2006) 7(1)

Pharmacogenomics: a path to predictive medicine for schizophrenia – REVIEW

Figure 1. Crosstalk between the common neurotransmitter signaling pathways involving the genes implicated in schizophrenia. COMT

G72

GABA Glutamate

PRODH

GAD

DAAO Dopamine Proline Ach R

Glial cell

D-serine racemase

L-Serine

D-Serine

EAAT2

Serine hydroxy methyltransferase

Glutamate

Glycine

Yotiao

D1

Glutamate

Depolarization

NMDA

AMPA

GABA

Spinophilin

Gs/olf PKA ATP

GRM

AC

D2 cAMP

Gi

Ca2+

DARPP-32

RGS4 NF κB dependent

Ca2+

BDNF PP-1 DTNBP1 Tryptophan hydroxylase

PP2B Postsynaptic density proteins

Synaptic proteins (synaptophysin)

Trafficking NMDA and exocytosis of glutamate

NRG

Serotonin

Inhibition

Serotonin receptor

A simplified scenario of the presumed functions of genes important in the etiology of schizophrenia have been highlighted in this crosstalk pathway between glutamatergic, dopaminergic, serotonergic and cholinergic neurotransmitter receptors. AC: Adenylate cyclase; Ach R: Acetylcholine receptor; AMPA: α-amino-3-hydroxy-5-methyl-4-isoxazole propionate receptor; ATP: Adenosine triphosphate; BDNF: Brain-derived neurotrophic factor; Ca2+: Calcium ions; cAMP: Cyclic adenosine monophosphate; COMT: Catechol-O-methyltransferase; D1: Dopamine receptor 1; D2: Dopamine receptor 2; DAAO: D-amino-acid oxidase; DARPP32: Dopamine and cAMP-regulated neuronal phosphoprotein 32; DTNBP1: Dystrobrevin binding protein 1 or dysbindin; EAAT2: Excitatory amino acid transporter 2; G72: D-amino acid oxidase activator; GABA: γ-aminobutyric acid; GAD: Glutamate decarboxylase; Gi: Adenylate cyclase-inhibitory G protein; GRM: Glutamate receptor, metabotropic; Gs/olf: Adenylate cyclase-stimulatory G protein; NF κB: Nuclear factor-κB; NMDA: N-methyl-D-aspartate receptor; NRG: Neuregulin; PKA: Protein kinase A; PP-1: Protein phosphatase 1; PP2B: Protein phosphatase 2B or calcineurin; PRODH: Proline dehydrogenase (oxidase) 1; RGS4: Regulation of G-protein signaling. www.futuremedicine.com

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However, unlike human CYP, mammalian FMO3 does not appear to be inducible. The human FMO3 participates in the oxygenation of antipsychotics such as clozapine [14]. Therefore, interindividual variation in the FMO3-dependent metabolism of drugs is more likely to be due to genetic, as oppose to environmental, effects [15]. Many antipsychotics, including perphenazine, zuclopenthixol, thioridazine, haloperidol, and risperidone, are metabolized to a significant extent by the polymorphic CYP2D6, which shows a large interindividual variation in activity [16]. Polymorphisms in CYP2C9, CYP2C19 and CYP2D6, and gene amplification of CYP2D6, enable the categorization of individuals within a given population into at least three groups – poor metabolizers (PMs), extensive metabolizers (EMs) and ultrarapid metabolizers (UMs) of certain drugs [5]. Individuals with a PM phenotype have higher plasma concentrations and more adverse effects from antipsychotics [17], while UM individuals may suffer from treatment-refractoriness to antipsychotics. For haloperidol, differences in drug metabolism necessitate a dose reduction for PMs [16,18]. A higher risk for extrapyramidal side effects in PMs was observed, most probably due to higher levels of reduced haloperidol. Patients with the UM genotype have the poorest clinical status as measured by the positive and negative symptoms scale [16]. Consequently, particularly at the beginning of antipsychotic treatment, knowledge regarding the metabolizer status might help to reduce adverse events by initiation of therapy with lower doses in a subgroup of the population. Clozapine is a substrate of several CYP isoenzymes, namely CYP1A2, CYP3A4 and CYP2D6, influencing the large interindividual variations in bioavailability, steady-state plasma concentrations and clearance [16]. In a study by Arranz and colleagues, CYP2D6 was not found to be a major enzyme responsible for metabolizing clozapine [19]. In contrast, in another study it was suggested that a CYP1A2 gene polymorphism might be associated with clozapine response [20]. Adverse effects have been observed due to the impaired metabolic capacity of CYP2D6 resulting in extrapyramidal side effects [17]. Liou and colleagues reported that allele (*)10 of the C188T polymorphism of this gene is associated with susceptibility to tardive dyskinesia with typical antipsychotics [17]. Brockmoller and colleagues demonstrated that treatment with haloperidol should be avoided in extremely slow and extremely rapid metabolizers of CYP2D6 34

substrates, and observed that CYP2D6 polymorphisms are good predictors for adverse events [21]. These observations emphasize the significant role of CYP2D6 in adverse drug reactions. Aitchison and colleagues have reported CYP1A2 as a major determinant of clozapine clearance and investigated the in vivo contribution of CYP1A2 to clozapine pharmacokinetics and pharmacodynamics using the CYP1A2-null mouse. They inferred that CYP1A2 PMs might be more susceptible than EMs to dose-related adverse effects of clozapine, such as sedation, myoclonus and seizures [20]. There are only a few reports regarding metabolic pathways of other atypical antipsychotics such as risperidone, olanzapine and quetiapine. Further research in this field of pharmacokinetics is needed to clarify the relationship between polymorphisms of metabolic enzymes and response to antipsychotic drugs. Genetic differences between ethnic groups may also result in the preferential development of drugs that may benefit one group more than another. For CYP2D6, approximately 7–10% of Caucasians are poor, 40% are intermediate (heterozygous carriers), and 50% are extensive metabolizers [22]. The prevalence of poor metabolizers in the black populations has been estimated to be from 0 to 19%, in Asians 0–2% [1,22], and 3% in North Indians [23]. Therefore, physicians should take race/ethnicity into account when prescribing, dosing and monitoring antipsychotics agents [24]. Polymorphisms in metabolizing enzymes cannot fully account for the heterogeneity observed in pharmacokinetics. Gene dose has an effect on drug metabolism, and studies have quantified the influence of the number of functional CYP2D6 genes on the metabolic clearance and plasma concentration of drugs metabolized by this enzyme [25]. The overall pharmacologic effects of medications are typically not attributed to monogenetic traits; they are instead determined by the interplay of several genes encoding proteins involved in multiple pathways of drug effects and disposition, in addition to metabolism. As pharmacokinetic factors explain only a small part of the variability in therapeutic response, efforts should concentrate on variations within target molecules in the brain. Genetic variation at the pharmacodynamics level: drug targets With respect to schizophrenia, the genetic variation of drug targets expressed in the CNS is of specific interest. Receptor and transporter genes Pharmacogenomics (2006) 7(1)


for neurotransmitters such as dopamine, serotonin, glutamate, and γ-aminobutyric acid (GABA), for example, have mainly been studied in patients as predictors of the response to psychotropic drug therapy. Among the large number of potential candidate genes, the dopamine and serotonin (5-HT) receptors have been extensively studied for the presence of genetic variation for binding profiles of antipsychotics. It is noteworthy that interindividual and intergroup variations render all findings inconclusive until they are validated using larger and more diverse sample sets, or until a direct biologic correlation can be confirmed.

acid repeat in exon 3, associated with response to risperidone in an Israeli adolescent population. An association with response to other antipsychotics such as clozapine [34,35] has been observed between the ‘short’ variant of DRD4 and tardive dyskinesia [36], though contradictory results exist [5]. The D1 and D5 receptor genes have been systematically screened and several polymorphisms have been detected [37–39]. However, none of the variants in the dopamine D1 and D5 receptor genes have been confirmed to be associated with an antipsychotic drug response [40]. Serotonin receptors

Dopamine receptors

Dopamine receptors are characterized into five subtypes belonging to the dopamine D1-like (D1 and D5 receptors) and D2-like (D2, D3 and D4 receptors) families. Since almost all the antipsychotics are dopamine receptor antagonists, numerous polymorphisms in all five receptors have been studied for association with antipsychotics [5]. However, the impact of these polymorphisms remains medically controversial. The Ser311Cys, Pro310Ser and Val96Ala polymorphisms in the DRD2 receptor have been reported to be functionally relevant [26,27], however clinical data are inconsistent [5]. The Val96Ala polymorphism was indicated to reduce dopamine, chlorpromazine and clozapine binding affinities, and increase inhibition of cyclic adenosine monophosphate (cAMP) synthesis, whereas both the Pro310Ser and Ser311Cys polymorphisms have been shown to decrease inhibition of cAMP synthesis [26,27]. Promoter polymorphisms in this receptor include -241A>G and -141 deletion, and no positive results have been reported for association between these polymorphisms and clinical response to clozapine and other typical antipsychotics [28,29]. Inconsistent associations have been observed between the Ser9Gly polymorphism in the D3 receptor gene and response to antipsychotics [30,31]. The Ser9Gly polymorphism has been reported to alter the function of the D3 receptor and is implicated with the pathogenesis of tardive dyskinesia, a side effect of long-term usage of neuroleptics [32]. However, Lane and colleagues have reported that the D3 receptor Ser9Gly polymorphism may influence response to risperidone in negative symptoms and social functioning, but not positive symptoms [33]. The D4 receptor gene has a characteristic array of genetic polymorphisms that includes a 16 amino www.futuremedicine.com

5-HT receptors are targets for various antipsychotics, particularly atypical ones, and numerous variants of the 5-HT2A, 5-HT2C, 5-HT5A and 5-HT6A receptor genes have been reported in pharmacogenetic studies as predictors of the therapeutic response to clozapine. The indications for an association between clozapine response and the 102T/C polymorphism in 5HT2A remains a subject of discussion [41]. The other variant in 5HT2A is His45Tyr, which has presented homogenous data for association with responder status to clozapine. The 5HT2C polymorphism, Cys23Ser, causes a structural change in the receptor and an association was found with clozapine response by Sodhi and colleagues [42]; however, the association has not been replicated in studies by other investigators. Clozapine has affinity for 5HT6 [43], which contains the C267T polymorphism [44]. This polymorphism is reported to affect translation, but its association with response to clozapine remains controversial [45]. Polymorphisms in the dopamine and serotonin receptors/transporters have also been investigated for their association with tardive dyskinesia and weight gain, which are major side effects seen with antipsychotic therapy. Few polymorphisms, such as the 9Gly variant of the Ser9Gly polymorphism of the D3 receptor [32,46] and the 102C-variant of the T102C polymorphism in the 5HT2A receptor, predispose carriers to a higher risk of tardive dyskinesia [41]. Adverse effects of antipsychotics have been related to the serotonin transporter (SERT) polymorphisms, especially with tardive dyskinesia. However, the results failed to be statistically significant [5]. To date, a significant association has been found only with the (-759)C allele of the C(-759)T polymorphism of the 5HT2C receptor in Han Chinese patients [5]. 35


There is considerable variability among individuals with respect to the ability of clozapine to induce weight gain [47]. In a pathway-based approach, obesity-related pathways were reviewed by Basile and colleagues to identify candidate molecules involved in clozapineinduced weight gain [48]. Although in its infancy, the aim of such an approach in psychiatric pharmacogenetics is to aid clinical practice in the prediction of response and side effects, in order to minimize the current ‘trial and error’ approach in prescribing treatment. Promising efforts have been made to test for the best predictive value of combinations of polymorphisms in the context of genetic prediction of response to a drug, such as clozapine, as exemplified by Arranz and colleagues [12]. The study supports the rationale that individual polymorphisms on their own may be unable to explain variability to treatment, and a combination of polymorphisms in multiple genes may provide a better predictive value of response. Thus, a multiple candidate gene approach has recently been adopted in the pharmacogenomics of antipsychotics [10]. Insights about gene function at the level of cells, brain networks and interactions may help to understand and predict the effects of genes and lead to improvements in prevention and pharmacologic treatment of disease. Converging on susceptibility genes for schizophrenia: plausible pathophysiologic mechanisms & pharmacologic targets The interaction between two genes may have profound effects on an individual’s pharmacogenetic profile, and multiple interactions may be the norm in a given individual with standard genetic variation, indicating the need for multiple typing. An integrative approach to elucidate the network of the genes is presented, which enables the visualization of the cause and effects of the genes and their interactions from a disease and treatment perspective. Though the dopaminergic and serotonergic theories dominate drug research and development, there is the continued need to understand the role of the neurotransmitter systems, especially the glutamatergic pathway that plays a crucial role in the control of cognition, memory, mood and motor function, disturbed in schizophrenia [49]. Interaction between dopaminergic and glutamatergic signaling is complex and may be modulated by many other neurotransmitters and their signaling pathways [50]. 36

Dopamine, acting through the D1 receptor, activates the adenylyl cyclase-stimulatory G protein Gs/Golf, to activate adenylyl cyclase for the formation of cAMP and activation of protein kinase A (PKA), causing PKA-mediated phosphorylation of dopamine- and cAMP-regulated phosphoprotein (DARPP)32. By contrast, acting through the D2 receptor and adenylate-inhibitory Gi protein, there is the inhibition of D1 receptorinduced increase in cAMP formation, resulting in the dephosphorylation of DARPP32. The D2 receptor activation synergistically raises intracellular calcium (Ca2+) levels, which activates Ca2+-dependent protein phosphatase 2B, calcineurin (PP2B), that dephosphorylates DARPP32 [51]. Glutamate binds to the ionotropic subclass of glutamate receptors [52], α-amino-3hydroxy-5-methyl-4-isoxazole-propionic acid (AMPA) and N-methyl-D-aspartic acid (NMDA). The AMPA and NMDA receptors increase intracellular Ca2+ levels and enhance the activity of PP2B, causing dephosphorylation of DARPP32. In addition, DARPP32, in its phosphorylated form, is a potent inhibitor of protein phosphatase 1 (PP1) [51,53], which has very broad substrate specificity and controls the state of phosphorylation and activity of numerous neurotransmitter receptors, voltage-gated ion channels, ion pumps, and transcription factors [53]. The sensitivity to glutamate is enhanced upon the phosphorylation of the NMDA and AMPA receptors by cAMP-dependent PKA [52,53]. PP1, which is capable of antagonizing actions of PKA, dephosphorylates the AMPA and NMDA receptors, inactivating these receptors to glutamate [50,53] in the presence of cytoskeleton scaffolding protein, spinophilin and yotiao, respectively [53,55]. Multiple phosphorylation sites on DARPP32 through multiple protein phosphatases control distinct and opposing functions of DARPP32. Some of the actions include dephosphorylation of DARPP32 at a single threonine residue at position 34 (Thr34), which stimulates the activity of PP1, while dephosphorylation at Thr75 increases PKA activity. Consequently, DRD1 receptor activation increases AMPA channel activity by phosphorylation of the Ser845 of AMPA subunit 1 due to inhibition of PP1 by phosphorylated DARPP32 at Thr34. The DRD2 receptor activation conversely causes the dephosphorylation of DARPP32 at Thr34 [50]. These actions, mediated by regulating the effects of DARPP32, may contribute to explaining the fact that dopamine and glutamate can have either opposing or synergistic action [55]. Pharmacogenomics (2006) 7(1)


Although the serotonin (5-HT) and glutamate receptors are separately implicated in schizophrenia, alterations in the expression of the serotonin receptors may be partly due to changes in glutamate activity [56]. Furthermore, AMPA and NMDA modestly increase extracellular serotonin levels [57,58] in the serotonergic system by increasing brain-derived neurotrophic factor (BDNF) expression through an NF-κBdependent pathway [59]. Animal model results suggest that BDNF augments 5-HT synthesis [60], probably by affecting the tryptophan hydroxylase levels [61]. This highlights the influence of the glutamate pathway on serotonin and the serotonergic receptor signaling, which is implicated in depression [62], a symptom observed in schizophrenia patients. Other genes that converge onto the glutamate receptor signaling include G72 and D-amino acid oxidase (DAAO) that have the most direct impact on the NMDA receptors, since DAAO metabolizes D-serine, an endogenous modulator of the receptor [63], and G72 is probably an activator of DAAO [64]. Data are consistent with overactivity of DAAO in schizophrenia and, correspondingly, lower levels of D-serine [65]. D-serine or glycine binds to a second site on the NMDA receptor, specifically on the NR1 subunit [66], which must be occupied in order to gate the NMDA ion channel [65]. One source of glycine is from L-serine converted via a reversible enzyme, serine hydroxymethyltransferase [65] while L-serine is transformed into D-serine and vice versa by D-serine racemase. Reports suggest that glycine–serine metabolism is perturbed in schizophrenia, and this decrease in plasma glycine levels and glycine:serine ratios support the evidence for efforts to improve negative symptoms by augmentation of antipsychotic drugs with agonists at the glycine site of the NMDA receptor [65]. A pool of glutamate is maintained in the synapse by glial and neurons through numerous glutamate transporters such as excitatory amino acid transporter (EAAT)1 and EAAT2 (glia) and EAAT3 and EAAT4 (neurons), that critically modulate glutamate levels by its removal from the synaptic cleft [65]. Proline dehydrogenase (PRODH) influences glutamate metabolism [68] and release [69] by regulating proline levels, also affecting the glutamatergic synapse [70]. Finally catechol-O-methyltransferase (COMT), a methylation enzyme, metabolizes released dopamine [71]; thereby acting directly on the dopaminergic neurotransmission, and most probably will affect www.futuremedicine.com

the glutamatergic one. Neuregulin present in glutamatergic synapse binds to ErbB4 that colocalizes with the NMDA receptor within the postsynaptic density [72], which is an important structure that scaffolds ion channels and signaling molecules at sites of synaptic transmission [73]. Therefore, neuregulin may play a role in modulating NMDA receptor-dependent maintenance and/or the regulation of synaptic structure and synaptic plasticity [74]. In addition, dysbindin is located in the postsynaptic density [75] to facilitate trafficking and tethering of receptors, including the NMDA receptor and signal transduction proteins [76], and also influence exocytotic glutamate release via upregulation of the molecules in presynaptic machinery [77]. The neurotransmitter glutamate also binds to the metabotropic receptors [78], which consist of eight subtypes localized to specific regions of the brain, playing a crucial role not only in the release of glutamate but also in modulating serotonin and dopamine transmission [79]. Metabotropic receptor 3 and metabotropic receptor 5 can critically and differentially modulate the expression of glutamate transporters such as EAAT2 and may represent interesting pharmacologic targets to regulate the extracellular levels of glutamate in pathologic conditions [65,80]. Regulator of G protein signaling 4 (RGS4) is a negative regulator of G protein-coupled receptors, including the metabotropic glutamate receptors, and may have a neurodevelopmental role [81]. Certain subtypes of the metabotropic glutamate receptor are found to affect the phosphorylation state of DARPP32 [82]. The relationship of the glutamate system with other neurotransmitter signaling systems needs further elucidation. There is evidence that both the nicotinic and cholinergic acetylcholine receptors modulate glutamatergic [83,84] signaling, and the various acetylcholine receptor subtypes are associated with schizophrenia [85–87]. The nicotinic receptor may be responsible for the heavy smoking among schizophrenic patients [88]. GABA is one of the most important inhibitory neurotransmitters in the vertebrate brain [89]. The GABA-ergic neurons are widely distributed throughout the CNS, and dysfunction in this system has been implicated in schizophrenia and mood disorders, which is reflected by decreased levels of glutamic acid decarboxylase (GAD) and reelin [90]. GAD is the rate-limiting enzyme responsible for the conversion of glutamate to GABA, maintaining the levels of these neurotransmitters in the mammalian 37


brain. Reelin is an extracellular matrix protein that helps in normal lamination of the embryonic brain and subserves synaptic plasticity in the adult brain [90]. The interplay between glutamate, via the NMDA receptor, and GABA via GABAA receptors, have been reported to affect the BDNF mRNA levels [91]. The mechanism of GABA–glutamate interaction could be explained by a GABA modulation of the membrane depolarization stage. It is known that the activation of NMDA receptors requires membrane depolarization to remove magnesium (Mg2+) blockage and allow Ca2+ permeability [52]. GABA-induced hyperpolarization [92] might explain inhibition of NMDA receptor activity, thus decreasing Ca2+ concentration and downregulation of BDNF [93]. The presumed functions of all of these genes are important in the etiology of schizophrenia, as they are implicated in the glutamatergic, dopaminergic, serotonergic, and cholinergic neurotransmitter signaling pathways and their crosstalk. These individual signaling pathways and their crosstalk are expected to be highly complex and complicated. However, a simplified scenario of the interacting genes and proteins is shown in Figure 1, along with the polymorphisms in these genes in Table 1, highlighting the importance of the genes in the molecular mechanism of the disease etiology. The central glutamatergic receptor is associated with synaptic plasticity, such as learning and memory, participating in the etiology and pathology of different neuropsychiatric disorders [148]. Antipsychotics elicit a complex influence upon the glutamatergic pathways, including the NMDA receptors [65], either directly by affecting the glutamate [65] and glycine [65] concentrations or indirectly via phosphorylation by PKA, possibly mediated by dopamine receptor signaling pathway [149]. Studies from DARPP32 mutant mice demonstrated a decreased sensitivity of these mice to drugs of abuse and antipsychotic agents, supporting the involvement of DARPP32 in mediating the pharmacologic effects of both of these classes of compounds [150]. Adjuvant treatment with D-serine or glycine, endogenous full agonists of the glycine site of NMDA receptor, or D-cycloserine, a partial agonist, has shown to improve the symptoms of schizophrenia [151,152]. In view of the potential role of the α7 group for CNS-related actions, it has been looked upon as containing potentially new pharmacologic targets for cognition in schizophrenia. A new drug 38

has been discovered by Tatsumi and colleagues known as compound 25 ([R]-3’-[5-chlorothiophen-2-yl]spiro-1-azabicyclo[2.2.2]octane3,5’-[1’,3’]oxazolidin-2’-one [25]) with good selectivity for its receptor, and pharmacokinetic evaluation reveals that this drug has good oral bioavailability and brain permeability [153]. The selection of all these potentially important targets for the disease might not prove to be of immediate success due to several reasons, including the side affects caused by the target. This is well elucidated by a classic example of DAAO which, with its interaction with G72, was considered to have therapeutic potential. However, studies with DAAO mutant mice revealed that agents that target DAAO activity potentially produce hyperalgia as a side effect [154]. This network of genes enables relationships between receptors, transporters and other proteins, and their impact on cellular processes, to be revealed, and vastly improves the understanding of disease mechanisms and their treatment. Furthermore, this network will also help in the identification of amenable targets for therapeutic intervention. It is important to note that these targets for intervention may not necessarily ameliorate the disease, but rather only reduce certain symptoms of schizophrenia. Significant role of phenotyping Even if we have plausible candidate genes available, the confirmation of their involvement in schizophrenia and drug response remains a complex and challenging task. This may not only be due to the phenotypic heterogeneity of schizophrenia and the lack of an objective definition of the disorder, but also due to the fact that assessment of response and symptoms varies from study to study and has often not been performed prospectively. Several approaches have been proposed to reduce this phenotypic heterogeneity. Among these are patients’ characteristics such as age, gender and ethnicity, and the assessment of response, for example instruments to be applied, initiation and duration of the study, dose, and comedication of schizophrenic patients, have attracted increasing interest [155]. In addition, the majority of gene effects in response to medication might be individually small and statistical error may affect results. Thus, a collection of patient samples with possibly uniform phenotypes, large enough to exclude statistical errors, is required for pharmacogenomic studies. Pharmacogenomics (2006) 7(1)


Table 1. Genes and their polymorphisms associated with schizophrenia and related symptoms . Gene

Locus

Genetic variation

Functional consequence

DRD1

5q35.1

DeI polymorphism in the 5' UTR : -48 (A-48G)

The G/G genotype shows worse results in all domains of The Wisconsin Card Sorting Test, which is used as a standard test to assess various aspects of working memory and executive functions in schizophrenia

[94]

Report of a male-limited association between the DRD1 gene polymorphism and sensation-seeking score in alcohol-dependent subjects

[95]

A significant genotype and allele association with bipolar I disorder in the Sardinian population

[96]

-94G–A

A significant association with panic disorder

[97]

His313

A significant genotype association with schizophrenia in the South Indian population

[98]

Taq1A

Susceptibility to polydipsia (drinking behaviour) in schizophrenia

[99]

DRD2

11q23

-141C Ins/Del

Association with antipsychotic medication response

[100]

Significant association was found between the A1 allele and severe substance dependence in both Caucasian and non-Caucasian groups

[101]

Significant association with smoking cue-induced cigarette craving in African–American smokers

[102]

Increased risk of extrapyramidal adverse effects in schizophrenic patients

[103]

The number of perseverative errors, reflecting an inability to change the reaction or/and ignorance of relevant information, was higher in female schizophrenic patients with -141 ins/del DRD2 genotype than with ins/ins genotype

Ser311Cys

COMT

22q11.21

val108/158met

Ala72Ser

Ref.

[94]

Association of antipsychotic medication response

[100]

Significant associated with alcoholism in Mexican–Americans

[104]

Del allele worsens the positive symptoms

[105]

Patients with no Del allele show significant improvement to treatment with chlorpromazine than those with Del allele

[106]

Determines risperidone efficacy for positive, negative and cognitive symptoms

[107]

The Ser/Cys patients exhibited significantly lower positive and negative symptom scores than Ser/Ser patients

[105]

Predicts working memory improvement following administration of antipsychotic medication to patients with schizophrenia

[108]

Associations with cognitive and motor impairment

[109]

Associated with the severity of aggression in Korean male schizophrenic patients

[110]

Impact on the therapeutic profile of olanzapine

[111]

Homozygous Met allele carriers have a lower frontal P300 amplitude which is a clinically significant marker of neurocognitive function

[112]

Correlated with reduced COMT enzyme activity and is implicated in schizophrenia in the Korean population

[113]

5-HT: 5-hydroxytryptamine; BDNF: Brain-derived neurotrophic factor; CHRNA7: Cholinergic receptor, nicotinic, α polypeptide 7; COMT: Catechol-O-methyltransferase; DAAO: D-amino acid oxidase; DARPP: Dopamine- and cAMP-regulated phosphoprotein; DR: Dopamine receptor; EAAT: Excitatory amino acid transporter; GABA: γ-aminobutyric acid; GAD1: Glutamate decarboxylase 1; GRIN1: Glutamate receptor, ionotropic, N-methyl-D-aspartate 1; GRM3: Glutamate receptor, metabotropic 3; NMDA: N-methyl-D-aspartic acid; NRG1: Neuregulin 1; PP2B: Protein phosphatase 2B; PRODH: Proline dehydrogenase (oxidase) 1; RGS4: Regulation of G-protein signaling 4; SNP: Single nucleotide polymorphism.

www.futuremedicine.com

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Table 1. Genes and their polymorphisms associated with schizophrenia and related symptoms (cont.). Gene

Locus

Genetic variation


NMDA receptor subtypes

GRIN1 - 9q34.3

G1001C in the GRIN1 gene and the T4197C and T5988C polymorphisms in the GRIN2B gene

Combined effects of the polymorphisms in the GRIN1 and GRIN2B genes might be involved in the etiology of schizophrenia

Ref. [114]

GRIN2A - 16p13.2

GRIN2A promoter (GT)n

Association with schizophrenia in the Japanese population

[115]

GRIN2B 12p12

GRIN2B C2664T

Significant association to clozapine treatment

[116]

G allele of the 366C/G polymorphism of GRIN2B

Significant association with schizophrenia in Japanese population

[117]

-1438A/G

Association was related to negative symptoms (following treatment) much more than to treatment response

[118]

HTR1A

13q14-q21

T-102C

Increased risk of schizophrenia for carriers of the T-102 allele

[119]

5-HT2c

Xq24

5-HT2C receptor -759C/T

Associated with weight gain: via leptin and reduced expression of HTR2C mRNA

[120]

Calcineurin (PP2B)

8p21.3

CCS3 in PPP3CC

Significant association with schizophrenia

[121]

CC21 in PPP3CC


[121]

Neuregulin (NRG1)

8p21–p12

rs3924999

The functional polymorphism in exon 2 (Arg38Gln) is associated with variations in schizotypal personality in nonclinical populations

[122]

SNP8NRG221533 (C/T)

TT genotype is overrepresented in the nonresponders group compared with the responders

[123]

Dysbindin

RGS4

6p22.3

1q23.3

Susceptibility to schizophrenia in Han Chinese population

[124]

rs760761


[125]

rs3213207, rs1011313, rs2005976, rs760761, rs1018381

5-marker haplotype A-C-A-T-T showed a significant association with schizophrenia

[126]

SNP7 located upstream of RGS4

Significant association with schizophrenia in Han Chinese and Scottish populations

[127]

SNP1 and SNP4 located upstream of RGS4

Haplotype constructed from both the SNPs show association with schizophrenia

[128]

SNP18 located in RGS4 intron 1

Association with schizophrenia

[128]

G72

13q34

rs3916966,rs3916971,rs 778293,rs3918342

Significant association with schizophrenia in the Ashkenazi population

[129]

DAAO

12q24

rs3741775

Highly significant association with schizophrenia in Han Chinese

[130]

Intronic SNPs MDAAO-4, MDAAO-5, MDAAO-6, and MDAAO-7

Association with schizophrenia in French Canadian

[131]

Val66Met polymorphism

Significant association to schizophrenia and good response to clozapine

[132]

C(270)T

Association with schizophrenia

[133]

Dinucleotide repeat polymorphism in the putative promoter region

Highly significant association with schizophrenia in Scottish population

[134]

BDNF

11p13

5-HT: 5-hydroxytryptamine; BDNF: Brain-derived neurotrophic factor; CHRNA7: Cholinergic receptor, nicotinic, α polypeptide 7; COMT: Catechol-O-methyltransferase; DAAO: D-amino acid oxidase; DARPP: Dopamine- and cAMP-regulated phosphoprotein; DR: Dopamine receptor; EAAT: Excitatory amino acid transporter; GABA: γ-aminobutyric acid; GAD1: Glutamate decarboxylase 1; GRIN1: Glutamate receptor, ionotropic, N-methyl-D-aspartate 1; GRM3: Glutamate receptor, metabotropic 3; NMDA: N-methyl-D-aspartic acid; NRG1: Neuregulin 1; PP2B: Protein phosphatase 2B; PRODH: Proline dehydrogenase (oxidase) 1; RGS4: Regulation of G-protein signaling 4; SNP: Single nucleotide polymorphism.

40

Pharmacogenomics (2006) 7(1)


Table 1. Genes and their polymorphisms associated with schizophrenia and related symptoms (cont.). Gene

Locus

Genetic variation


GABA receptor

GABBR1 - 6p21.31

γ-aminobutyric acid type B receptor 1 (GABBR1) A-7265G


Ref. [135]

GABRG2 - 5q31.1q33.1

GABA(A) receptor γ2 subunit gene (GABRG2) 315C>T and 1128+99C>A

Haplotype association with methamphetamine (METH) abuse disorder

[136]

GABA(A) receptor γ2 subunit gene (GABRG2) B2I7G1584T, rs1816071, rs194072, rs252944 and rs187269


[137]

EAAT2

11p13-p12

(-)

Decreased EAAT2 mRNA in schizophrenia patients

[138]

GRM3

7q21.1q21.2

SNP1 (rs274622), located in a potential promoter region

Significant association with improvement in negative symptoms in patients with schizophrenia treated with olanzapine

[139]

rs2299225

Significant association with schizophrenia in the Han Chinese

[140]

(SNP) 4 (hCV11245618) in intron 2

AA homozygotes of (SNP) 4 (hCV11245618) in intron 2 of the GRM3 gene have shown lower mRNA levels of the glial glutamate transporter EAAT2

[141]

haplotype consisting of PRODH*1945T>C and PRODH*1852G>A in the maps to the 3' region of the gene

Significant association with schizophrenia in the Chinese population

[142]

Three missense mutations V427M, L441P, and R453C

Association with schizophrenia and severe reduction of proline oxidase activity and hyperprolinemia

[143]

Missense mutations – L441P and L289M

Associated with schizophrenia and an increase in plasma proline levels

[144]

D15S1360 marker present in intron 2 on the gene

Significantly associated with smoking in patients with schizophrenia

[145]

(-)

Reduction in DARPP32 levels in schizophrenic subjects

[146]

(-)

GAD activity or gene expression was abnormal in schizophrenics

[147]

PRODH

Acetylcholine receptor α7 (CHRNA7)

22q11.21

15q14

DARPP32 Glutamic acid decarboxylase (GAD1)

2q31

5-HT: 5-hydroxytryptamine; DAAO: D-amino acid oxidase; BDNF: Brain-derived neurotrophic factor; CHRNA7: Cholinergic receptor, nicotinic, α polypeptide 7; COMT: Catechol-O-methyltransferase; DARPP: Dopamine- and cAMP-regulated phosphoprotein; DR: Dopamine receptor; EAAT: Excitatory amino acid transporter; GABA: γ-aminobutyric acid; GAD1: Glutamate decarboxylase 1; GRIN1: Glutamate receptor, ionotropic, N-methyl-D-aspartate 1; GRM3: Glutamate receptor, metabotropic 3; NMDA: N-methyl-D-aspartic acid; NRG1: Neuregulin 1; PP2B: Protein phosphatase 2B; PRODH: Proline dehydrogenase (oxidase) 1; RGS4: Regulation of G-protein signaling 4; SNP: Single nucleotide polymorphism.

Rigorous and quantitative definition of phenotype for schizophrenia is difficult, since the disease has neither visible traits nor significant laboratory data. To describe the different aspects of response, specific symptoms such as positive/negative symptoms, disorganization, altered affect, specific hallucinations, and delusions should be followed over the course of investigation. In addition, other measures of response can be assessed, for example, www.futuremedicine.com

neurocognitive functioning, psychophysiologic measures, motor behavior, hormone levels, and quality of life. All these considerations for phenotype will accelerate the pharmacogenomic studies in schizophrenia. In this review, the importance of clearly characterized patient samples for association studies involving multiple candidate genes, and their combinations of polymorphisms that may represent susceptibility to disease and to drug 41


Highlights • Cytochrome P450 (CYP)2C9, CYP2C19, CYP1A2, CYP3A4, CYP2D6 and flavin-containing monooxygenase (FMO)3 are related to pharmacokinetic implications. The polymorphisms in these genes have been investigated in numerous studies for association with drug response in addition to side effects. • Dopamine receptors belonging to the dopamine D1-like (D1 and D5 receptors) and D2-like (D2, D3 and D4 receptors) families, serotonin receptors such as 5-hydroxytryptamine (5-HT)2A, 5-HT2C, 5-HT5A and 5-HT6A and serotonin transporters such as SERT are the targets for antipsychotics drugs. The polymorphisms in these pharmacodynamic genes have been investigated in numerous studies for association with disease etiology, drug response and side effects. • A hypothetical network model of the interaction/crosstalk between the neurotransmitter signaling systems is presented to emphasize the importance of genes in the molecular mechanisms of the disease and drug response. • The effects of the associated single nucleotide polymorphisms on expression and function of the gene products involved in the interplay of genes such as neuregulin, dysbindin, catechol-O-methyltransferase, D-amino acid oxidase, Regulation of G-protein signaling 4, proline dehydrogenase (oxidase) 1, brain-derived neurotrophic factor, and calcineurin need to be investigated in phenotypically-characterized patient samples. • Patients’ characteristics, such as age, gender and ethnicity, and assessment of response along with significant sample size, are important parameters for identification of genes determining disease and drug response. • Large-scale identification of genetic variations in multiple genes in addition to cost effective, high-throughput genotyping systems using Sequenom® and DNA chip technology will certainly play a part in building a pharmacogenomics platform, and a path toward predictive medicine.

response, is highlighted. The susceptibility can then be determined by logistic regression analysis to the symptoms and/or drug response as the dependent variable and the polymorphisms studied as the independent variable [12]. Recently, preliminary guidelines in the field of pharmacogenetics have been proposed by the ‘Consensus Group for Outcome Measures in Psychosis for Pharmacogenetic Studies’ [156]. It is essential to understand that several discrete clinical features and variations exist between individuals with schizophrenia. As a consequence it becomes important to understand that different genetic susceptibility loci exist, which may lead to different disease phenotypes and help to resolve the genotype–phenotype correlation. Expert commentary The benefits of developing safe and effective drugs based on genetic information has long been realized by the biotechnology industry, and has made pharmacogenetics one of the fastest growing areas in this field. The pharmacologic effects of antipsychotics are complex in nature 42

and are likely to be determined by a combination of protein variants acting at the metabolic and the drug target level. Making a prediction of drug response at the level of the individual patient requires parallel observations of a larger number of genetic variants that are determinants of drug effects. The genomic era has by now altered the course of schizophrenia research. Advances in proteomics and genomics will provide more powerful approaches to identifying the gene products involved in schizophrenia pathogenesis. As the evidence for a particular gene grows, the effects of the associated SNPs on expression and function of the gene products will require further investigation. It is noteworthy that a number of genes, such as neuregulin, dysbindin, COMT, DAAO, RGS4, PRODH, BDNF and calcineurin and their variants are implicated in numerous studies in the etiology of schizophrenia. However, aspects of study design, sample size, and adequate symptom assessment of the samples are crucial in validating the association of genes individually or in combination with the disease susceptibility or drug response. It is also necessary to mention that various genetic factors such as gene dose and epigenetic factors may play a significant role in the disease etiology and drug response. The advantage of a multiple gene, pathway-based approach is that various combination of genes and their effects can be visualized, and the role of additional genes, such as cyclin-dependent kinase 5 (CDK-5), which causes phosphorylation of DARPP32 at Thr-75 [157], in the above mentioned pathway can be understood and analyzed for association. More than 1.4 million SNPs were identified in the initial sequencing of the human genome, with over 60,000 of them present in the coding region of genes [158]. The next technical barrier will be the development of inexpensive highthroughput methods for genotyping large numbers of SNPs from hundreds of patients. Considerable efforts are now underway within the biotechnology community to establish low-cost, high-throughput, accurate SNP scoring technologies. Prospective genotyping of schizophrenic patients for the many genes at the level of the drug target, drug metabolism and disease pathways will contribute to the interpatient variability in drug response. The real challenges will then be to demonstrate convincing links between genetic variation and drug responses and to translate that information into useful pharmacogenomic tests. Pharmacogenomics (2006) 7(1)


Outlook A number of challenges exist today in realizing the value of a high-density map of SNPs for pharmacogenomics. Polygenic determinants of drug effects have become increasingly important in pharmacogenomics. Schizophrenia is not a single disease but a complex interaction of symptoms. Despite large effects attributed to single gene polymorphisms, multigenic links and gene–environment interactions need to be considered. A large-scale identification of genetic variations in multiple genes, in addition to cost-effective, high-throughput genotyping systems such as Sequenom® and DNA chip technology, is essential to develop genetic-based diagnostics and therapeutic tests. Several recent studies focused on susceptibility genes for schizophrenia, which have shared effects on synapses, such as glutaminergic, GABA-ergic, cholinergic, and monoaminergic synapses. Polymorphisms in these genes, including neuregulin, dysbindin, COMT, DAAO, RGS4, PRODH, BDNF and calcineurin, may be candidates for prediction of therapeutic response and disease susceptibility, and should certainly be addressed in future studies. This concept of prediction of response and recommendations is almost Bibliography Papers of special note have been highlighted as either of interest (•) or of considerable interest (••) to readers. 1. Sawa A, Snyder S: Schizophrenia: diverse approaches to a complex disease. Science 296, 692–695 (2002). 2. Owen MJ, O’Donovan MC, Gottesman II: Schizophrenia. In: Psychiatric genetics and genomics. McGuffin P, Owen MJ, Gottesman II (Eds), Oxford University Press, New York, USA, 247–266 (2005). 3. Cloninger CR: The discovery of susceptibility genes for mental disorders. Proc. Natl Acad. Sci. USA 99, 13365–13367 (2002). 4. Freedman R: Schizophrenia. N. Engl. J. Med. 349, 1738–1749 (2003). 5. Kawanishi Y, Tachikawa H, Suzuki T: Pharmacogenomics and schizophrenia. Eur. J. Pharmacol. 410, 227–241 (2000). 6. Meltzer HY: Clinical studies on the mechanism of action of clozapine: the dopamine-serotonin hypothesis of schizophrenia. Psychopharmacology (Berl) 99(Suppl.), S18–S27 (1989). 7. Meltzer HY, Matsubara S, Lee JC: The ratios of serotonin 2 and dopamine 2 affinities differentiate atypical and typical


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