Pharmacogenetics in schizophrenia: a review of clozapine studies

Abstract

Objectives:

Clozapine is quite effective to treat schizophrenia, but its use is complicated by several factors. Although many patients respond to antipsychotic therapy, about 50% of them exhibit inadequate response, and ineffective medication trials may entail weeks of unremitted illness, potential adverse drug reactions, and treatment nonadherence. This review of the literature sought to describe the main pharmacogenetic studies of clozapine and the genes that potentially influence response to treatment with this medication in schizophrenics.

Methods:

We searched the PubMed database for studies published in English in the last 20 years using keywords related to the topic.

Results and Conclusions:

Our search yielded 145 studies that met the search and selection criteria. Of these, 21 review articles were excluded. The 124 studies included for analysis showed controversial results. Therefore, efforts to identify key gene mechanisms that will be useful in predicting clozapine response and side effects have not been fully successful. Further studies with new analysis approaches and larger sample sizes are still required.

Schizophrenia; clozapine; polymorphisms; pharmacogenetics; adverse effects

Introduction

Schizophrenia is an oft-devastating neuropsychiatric illness with a lifetime prevalence of 0.8%.¹ Its clinical manifestations usually arise in late adolescence and early adulthood. Schizophrenia is a complex and highly heritable disorder with a significant impact on public health. In Brazil, patients with schizophrenia occupy 30% of psychiatric hospital beds, or about 100,000 beds/day. In addition, 14% of first outpatient psychiatric visits are provided for schizophrenic patients, and schizophrenia is the fifth most common illness leading people to apply for social security disability benefits.²

Clozapine is an antipsychotic drug widely used in the treatment of schizophrenia. It is more effective than traditional antipsychotics for patients with poor response or resistance to treatment.³ The antipsychotic effect of clozapine has been attributed in part to its ability to block stimulation of the serotonin 2A receptor (5-HT2A), particularly when associated with weak dopamine D2 receptor blockade (DRD2).⁴ The action of this agent is not limited to 5-HT2 receptors (in particular 5-HT2A and 5-HT2C) and, to a lesser extent, to D2 receptors; it also acts on other dopaminergic (D1, D3, D4), histaminergic, adrenergic and cholinergic receptors.⁵

The variability of response to clozapine treatment in schizophrenia patients has a marked impact on clinical practice. Approximately 50% of patients who do not respond to typical antipsychotics benefit from clozapine.⁶ Additionally, clozapine is associated with side effects, including sedation, drowsiness, dizziness, hypersalivation, headache, constipation, generalized seizures, anticholinergic effects, orthostatic hypotension, weight gain, and agranulocytosis.⁷

The effect of psychopharmacological treatment depends on many factors that influence response. The heterogeneity of response is partly attributable to physiological and environmental factors affecting individuals, including age, sex, ethnicity, liver and kidney function, diet, co-medication, severity and type of illness, and alcohol and tobacco use.⁸ In some cases, however, response heterogeneity cannot be explained only by these factors, and genetic aspects should be considered as a potential source of variability.

In a study of monozygotic twins, Vojvoda et al.⁹ showed the importance of genetic factors in predicting the response to clozapine. Symptom improvement following clozapine treatment showed strong concordance in monozygotic twin pairs. Similarly, the contribution of genetics to antipsychotic-induced weight gain was addressed in studies of monozygotic twins and sib pairs, ^10-12 suggesting a genetic contribution of 60-80%. Two case reports of agranulocytosis induced by clozapine in monozygotic twins with schizophrenia provided evidence for a genetic basis of this adverse event.¹³,¹⁴

Pharmacogenetics is the study of the influence of genetic variants on response to medications and adverse effects, as well as the consequent understanding of how genes interact to determine individual variability in this response. The goal of pharmacogenetics is to find polymorphisms in genes encoding proteins and enzymes involved in the transport, metabolism, and action of drugs, enabling knowledge of the applicability of a particular drug and increasing its effectiveness.¹⁵ Pharmacogenomic studies consider the genome as a whole and do not rely on prior knowledge of candidate genes or specific hypotheses.¹⁶

The detection of individual genetic differences in the response to clozapine may provide new strategies for the treatment of major psychoses such as schizophrenia. The application of pharmacogenetic data has been analyzed in several studies investigating the impact of genetic polymorphisms on adverse effects and response to treatment with clozapine. The objective of the present literature review was to discuss the main results of these studies.

Methods

We searched the PubMed database for scientific articles published in English in the last 20 years about the use of clozapine to treat schizophrenia. The last search was performed on October 11, 2012. The following keywords were used in the search: antipsychotic or clozapine combined with polymorphism or genetics. Combinations of these keywords with schizophrenia, pharmacogenetic, pharmacogenomic, side effects, adverse effects, genotype, and allele were also used. Further searches were conducted based on the list of references of the selected articles and included in this review when relevant.

The articles were selected according to the following criteria: studies evaluating the impact of genetic polymorphisms on 1) treatment response and/or side effects, and 2) clozapine-treated patients or treatment with no more than three antipsychotics, when clozapine was the main prescribed drug (since findings from studies exploring mixed antipsychotics provided unclear and often contradictory results). Studies containing no information about the type of antipsychotics were not included.

Results

One hundred and forty-five articles met the search and selection criteria. Of these, 21 review articles were excluded. To supplement the data of the 124 remaining studies, six meta-analyses were also assessed.

The articles were divided according to their focus: studies investigating the effect of genetic and pharmacokinetic variation and studies investigating the effect of pharmacodynamic and genetic variability on treatment response and adverse effects. Table 1 summarizes significant results regarding response to treatment. Table 2 shows findings related to adverse effects. Nevertheless, these results are uncertain and should be considered cautiously, since several studies did not report the same associations.

Table 1
Reported associations between genetic polymorphisms and clozapine response^*

Gene/Polymorphism†	Ethnicity	Sample size	p-value
ABCB1
3435C>T17	Caucasian	75	0.04
3435C>T/2677G>T18‡	Caucasian	60	0.028
rs7787082, rs1024842019	Korean	96	< 0.001
COMT
Val158Met20	Caucasian and African American	84	< 0.01
CYP1A2
-163C>A21	Caucasian	33	0.01
DRD1
rs26597622	African American	49	0.033
-48A>G23	Caucasian	13	0.05
DRD2
-141C Ins/Del24	Caucasian and African American	72	< 0.05
Taq1A/Taq1B/rs1125394c25	African American	49	< 0.02
Taq1B/rs112539426‡	African American	31	< 0.02
DRD3
Ser9Gly27	Caucasian	133	0.04
Ser9Gly28	Pakistani	32	0.033
DRD4
VNTR 48 pb29	Chinese	81	0.05
VNTR 48 pb30	Caucasian	183	0.002
120bp indel30	African American	49	0.004
Intron 1 (G)(n)30	African American	49	0.014
DTNBP1
Several31‡	Caucasian and African American	88	0.007
GFRA2
rs1128397/rs13250096/rs456702832‡	mostly Caucasian	140	< 0.04
GNB3
825C>T33	Caucasian	145	0.01
825C>T34	Brazilian	121	0.02
HTR2A
102T>C35	Caucasian	149	0.001
102T>C36	Chinese	99	0.003
His452Tyr37	Caucasian and African American	184	0.01
His452Tyr38	Caucasian	153	0.008
-1438G>A39	Caucasian	274	0.0006
HTR2C
Cys23Ser40	Caucasian	162	0.005
HTR3A
rs10622613, rs227630241	Indian	101	0.02
rs106261342	Caucasian	140	0.04
HTR6
267T>C43	Chinese	99	0.04
NRXN1
rs104588144	Caucasian	302	0.03
OXT
Several45	Caucasian and African American	140	0.04
SLC6A3
rs2652511/rs2975226/rs296323846‡	Chinese	320	0.01
SLC6A4
HTTLPR47	Caucasian	200	0.04
HTTLPR48	Brazilian	116	0.01
TNFA
-308G>A49	Caucasian and African American	190	0.015

• ^*
  Including only significant association studies. See text for supplementary information about other nonsignificant studies concerning these genes.
• ^†
  See text for abbreviations.
• ^‡
  Haplotype: polymorphisms analyzed as a unique block.

Table 2
Reported associations between genetic polymorphisms and clozapine side effects^*

Gene/Polymorphism†	Ethnicity	Sample size	p-value
Weight gain
ADIPOQ
Several50
ADRA2A	Caucasian	160	< 0.045
-1291C>G51	Taiwanese	394	< 0.05
-1291C>G52	Korean	62	0.013
BDNF
rs6265/rs11030101/rs229118653	Taiwanese	481	0.047
DRD2
rs443657854	Taiwanese	479	0.001
957C>T, rs1079598, rs180049755	Caucasian and African American	192	< 0.05
GNB3
825C>T56	Chinese	134	0.002
HTR2A
102T>C/His452Tyr/-1438A>G57‡	Caucasian	46	0.034
HTR2C
-759C>T58	Chinese	32	< 0.02
-759C>T59	most Caucasian	35	0.003
-759C>T/-697G>C/Cys23Ser57‡	Caucasian	46	0.029
rs49820760	Caucasian	128	0.019
INSIG2
rs17587100, rs10490624, rs1704776461	Caucasian	160	< 0.05
LEP
-2548G>A62	Chinese	102	0.039
MC4R
rs808752263	Caucasian	69	0.027
rs48969364	Caucasian	73	0.0001
PRKAA2
rs1078903865	Caucasian	208	0.023
PRKAB2
rs376652265	Caucasian	208	0.022
PRKAG2
rs17714947, rs780006950	Caucasian	160	< 0.02
ROBO1
rs145583266	Caucasian	164	0.025
TNF
-308G>A67	Chinese	55	0.008
Metabolic syndrome
HTR2C
Several68	Caucasian	112	0.01-0.05
rs141433469	Caucasian	164	< 0.05
rs141433470	Caucasian	164	0.015
rs521018/rs49817771‡	Chinese	456	0.0108
MTHFR
1298A>C72,73	Caucasian	104,518	0.009, 0.018
Lipid levels
APOA5
1131T>C/S19W74‡	Caucasian, Hispanic and Black	95	0.049
APOC3
1100C>T/323874‡	Caucasian, Hispanic and Black	95	0.048
PRKAR2B
rs1322468275	Caucasian	175	< 0.0001
Agranulocytosis
HLA
Several76	Ashkenazi Jewish and non-Jewish	75	< 0.03
HSP-70 9.0-Ac77	Ashkenazi Jewish and non-Jewish	75	0.04
DBQ1*020178	Jewish	18	0.036
B3879	Israeli	11	0.001
DBQ*050280	Caucasian	103	0.006
6672G>C81	N/A	33	< 0.05
NQO2
1536C>T, 1541G>A, Phe372Leu, 202G>A82	Israeli	98	< 0.05
TNF
TNFb, TNFd83§	Ashkenazi Jewish and non-Jewish	33	0.0005
Seizures
GNB3
825C>T34	Brazilian	108	0.007
General ADRs∥
CYP1A2
Low activity84	Caucasian	34	0.019

• ADR = adverse drug reaction; N/A = not available.
• ^*
  Including only significant association results. See text for complementary information about other nonsignificant studies concerning these genes.
• ^†
  See text for abbreviations.
• ^‡
  Haplotype: polymorphisms analyzed as a unique block.
• ^§
  Microsatellites: short tandem repeat polymorphism.
• ^II
  Neurological, cardiovascular, gastrointestinal, hematological, behavioral, and musculoskeletal adverse reactions.

Genetic variants in metabolizing enzymes and response to treatment

Most drugs used in clinical practice that act on the central nervous system (CNS) are extensively metabolized in the liver by enzymes of the cytochrome P450 (CYP) system.¹⁶,⁸⁵,⁸⁶ Pharmacogenetic studies report that phenotypes generated by the activity of cytochrome P450 isoenzymes strongly influence the sensitivity or response to medication because of different elimination, concentration, and biotransformation rates.⁸⁵ These phenotypes are genetically determined and show great variation between different individuals. Variations in genes coding for CYP enzymes can result in absent, deficient, or increased activity.⁸⁷

Eap et al.,²¹ evaluating cytochrome P450, family 1, subfamily A, polypeptide 2 (CYP1A2) and plasma levels of clozapine, found that treatment non-responders had low levels of the drug and the *1F/*1F genotype, suggesting that this variation is associated with resistance to treatment. However, van der Weide et al.⁸⁸ observed that mean clozapine ratios and daily doses did not vary significantly between patients with different CYP1A2 genotypes, neither among smokers nor nonsmokers.

The cytochrome P450, family 2, subfamily D, polypeptide 6 gene (CYP2D6) is highly polymorphic, and more than 90 allelic variants and subvariants have been described.⁸⁷ Three studies (one conducted in Brazil) evaluating polymorphisms in CYP2D6 were unable to find a significant association between CYP2D6 alleles and response to clozapine.¹⁷,⁸⁹,⁹⁰ Dahl et al.⁹¹ evaluated the importance of genetic factors for the metabolism of clozapine and did not find significant differences in the plasma concentrations or any of the pharmacokinetic parameters of clozapine between poor and extensive metabolizers of debrisoquine. Since clozapine is metabolized minimally by this enzyme,⁹² more studies on clozapine metabolism would be helpful.

However, variations in metabolizing enzymes cannot be fully responsible for the heterogeneity observed in the response of an individual to treatment. The pharmacological effects of the medication are not typically monogenic traits; moreover, they are determined by the interposition of several genes encoding proteins involved in multiple pathways that determine the disposition and effects of drugs in addition to their metabolism.⁸⁵

Genetic variants in drug target proteins and response to treatment

Since clozapine is a high-affinity antagonist of dopamine receptors, initial studies focused on the relationship between the dopamine D4 receptor gene (DRD4) and the response to clozapine. Zhao et al.²⁹ and Hwang et al.³⁰ found significant associations between polymorphisms in DRD4 and response to clozapine. However, most studies were unable to detect this significant association. ^93-98

The dopamine D3 receptor gene (DRD3) is important because antipsychotics show high affinity for this receptor, especially in the mesolimbic system.⁹⁹ Two studies analyzed the Ser9Gly polymorphism in DRD3, and the Ser/Ser genotype was found to be more frequent among non-responders to clozapine,²⁷,²⁸ but other studies failed to replicate these findings. ^100-106 The importance of Ser9Gly was confirmed in a meta-analysis, where significant differences were found when the DRD3 Ser9 allele or the Ser/Ser genotype were compared between responders and non-responders to clozapine in a sample of 233 schizophrenia patients.¹⁰⁷ However, a more recent meta-analysis with a much larger sample size (n=758) reported a negative but consistent trend for the DRD3 Ser9 allele and poor clozapine response.¹⁰⁸

Another obvious candidate for pharmacogenetic studies is DRD2, because clozapine has an affinity for this receptor.¹⁰⁹ Studies with DRD2 polymorphisms produced contradictory results. Positive results were found by Malhotra et al.²⁴ and Hwang et al.,²⁵,²⁶ not corroborated by Arranz et al.,¹¹⁰ Reynolds et al.,¹¹¹ and Hwang et al.¹⁰⁶ In a meta-analysis including 889 individuals, Zhang et al.¹¹² concluded that single-nucleotide polymorphisms (SNPs) in the DRD2 promoter region, such as -141C Ins/Del, may be particularly important in predicting clinical response to various antipsychotic drugs.

Recently, Xu et al.⁴⁶ found a haplotype combination of genetic variants in the dopamine transporter gene (DAT or SLC6A3) significantly associated with response to clozapine, but in a previous study this association was not observed.¹¹³ Two studies analyzed DRD1 and found a significant association with clozapine response in African Americans²² and Caucasians,²³ but another study was unable to replicate this association.¹⁰⁶ Hwang et al.³⁰ evaluated the importance of DRD5 and found no significant association with clozapine response.

Of the seven subtypes of serotonin receptors (5-HT1-7), 5-HT2 subtypes are the strongest targets of atypical antipsychotic drugs.¹¹⁴ The 102T>C polymorphism in HTR2A was studied by Arranz et al.³⁵ They found a significant association between the 102C allele and failure to respond to clozapine in schizophrenic patients treated with the drug. These results were subsequently replicated by Yu et al.,³⁶ but several other studies did not achieve similarly significant results.³⁷,) Another less common polymorphism is HTR2A (His452Tyr), which seems to produce functional effects in vitro, providing both positive³⁷,³⁸ and negative results.¹¹⁶,¹¹⁷,¹¹⁸ The -1438A>G polymorphism was significantly associated with clozapine response in one study,³⁹ whereas another study failed to detect this association.¹²⁰ A meta-analysis of association studies on the 102T>C and His452Tyr polymorphisms in 733 clozapine-treated patients found an association between these two polymorphisms and poor response to medication.¹²¹

The HTR2C Cys23Ser polymorphism was associated with response to clozapine by Sodhi et al.,⁴⁰ but other studies did not replicate these results.³⁷,¹²²,¹²³ The serotonin receptor type 6 gene (HTR6) was analyzed in two studies; the first study observed a significant association between the HTR6 and the 267T>C polymorphism,⁴³ whereas the second study was unable to replicate this result.¹²⁴ Individual studies evaluated the influence of HTR5A¹²⁵ and HTR3B,¹²⁶ and no significant results were found. Unclear results were observed for HTR3A.⁴¹,⁴²,¹²⁶

The serotonin transporter gene (HTT or SLC6A4) has also been studied. Arranz et al.⁴⁷ observed an association between response to clozapine and the HTTLPR (HTT repeat promoter length) polymorphism in the promoter region of the gene. They found that individuals homozygous for the short allele tended to show a poor response to treatment with clozapine. Kohlrausch et al.⁴⁸ observed a significant association between the presence of short allele and failure to respond to clozapine in Brazilian schizophrenia patients. Two previous studies did not find a significant relationship.¹²⁷,¹²⁸

Arranz et al.,¹⁰² analyzing different polymorphisms, found a combination of six polymorphisms in neurotransmitter receptor-related genes predicting clozapine response (HTR2A 102T>C and His452Tyr, HTR2C -330-GT/244-CT repeat and Cys23Ser, 5HTTLPR, HRH2 -1018G>A). This finding constituted a great potential for pharmacogenetic studies as a key for future improvement and individualization of clinical treatment of patients with schizophrenia. However, these results have not been replicated with the same approach so far, and the pharmacogenetic test designed for use in clinical practice is no longer available on the market.⁶

Genetic variants in other classes of proteins and response to treatment

Since catecholamine receptors are G-protein-coupled (GPCRs) and antipsychotics exert their effects by competitive antagonism of postsynaptic GPCRs, this protein may have an important influence on the function of dopaminergic and serotoninergic systems. Müller et al.³³ found the 825C>T polymorphism in the gene encoding the small Beta-subunit 3 of G proteins (GNB3) to be associated with response to clozapine in patients with schizophrenia. This result was corroborated by the study conducted by Kohlrausch et al.³⁴ in Brazilians, where homozygosity for the 825T allele was more frequent among non-responders to treatment with clozapine.

Studies involving other genes with significant associations include variants in the following genes: ATP-binding cassette sub-family B member 1 (ABCB1), ^17-19 catechol-O-methyltransferase (COMT),²⁰ dystrobrevin binding protein 1 (DTNBP1),³¹ GDNF family receptor alpha 2 (GFRA2),³² neurexin 1 (NRXN1),⁴⁴ and oxytocin prepropeptide (OXT).⁴⁵ In contrast, the adrenoreceptor alpha 2A (ADRA2A),¹²⁹,¹³⁰ brain-derived neurotrophic factor (BDNF),¹³¹ human glutathione peroxidase (GPX1),¹³² glutamate receptor ionotropic N-methyl D-aspartate 1 (GRIN1),¹⁰⁶ 2A (GRIN2A)¹⁰⁶ and 2B (GRIN2B),¹⁰⁶,¹³³ histamine receptor H1 (HRH1),¹³⁴ histamine receptor H2 (HRH2),¹³⁴ and superoxide dismutase 2 mitochondrial (MNSOD)¹³² were investigated and no significant associations were observed. The tumor necrosis factor gene (TNF) showed significant⁴⁹ and nonsignificant¹³⁵ results. As these studies are mostly unique, confirmation of the results is necessary.

Studies assessing the adverse effects of clozapine

There is strong evidence that the serotonergic (5-HT) system plays a role in the regulation of feeding behavior; thus, clozapine-induced weight gain could be explained by dysfunction of this neurotransmitter.¹⁶ Several studies linking HTR2C (Cys23Ser and -759C>T) polymorphisms to weight gain have been conducted, with significant ^57-60 and nonsignificant ^136-140 results. A recent meta-analysis of 522 schizophrenia individuals suggested that the -759C allele is associated with weight gain.¹⁴¹ However, this study detected a relevant publication bias, suggesting preferential publication of significant findings over nonsignificant observations. A previous meta-analysis of 588 subjects reporting data on -759C>T supported the existence of an association between this individual marker and the side effect only under a fixed model.¹⁴² Both analyses included studies with mixed antipsychotics. Recently, Hill & Reynolds¹⁴³ established -759C>T as a functional polymorphism and suggested disruption of DNA-protein interactions as a mechanism whereby HTR2C expression is perturbed, leading to an influence on antipsychotic-induced weight gain.

A moderate association between the GNB3 825C>T polymorphism and weight gain⁵⁶ was not observed in a previous study.¹⁴⁴ Other genes with significant associations include ADRA2A,⁵¹,⁵² BDNF,⁵³ DRD2,⁵⁴,⁵⁵ adiponectin, C1Q and collagen domain containing (ADIPOQ),⁵⁰ melanocortin 4 receptor (MC4R),⁶³ protein kinase beta 2 non-catalytic subunit (PRKAB2),⁶⁵ protein kinase gamma 2 non-catalytic subunit (PRKAG2),⁵⁰ and roundabout axon guidance receptor homolog 1 (ROBO1).⁶⁶ Controversial results were observed for HTR2A ⁵⁷,¹³⁶ (positive and negative results, respectively), insulin induced gene 2 (INSIG2)⁶⁰,⁶¹,¹⁴⁵ (positive results only in the second study), leptin (LEP)⁶⁰,⁶² (negative and positive results, respectively), protein kinase alpha 2 catalytic subunit (PRKAA2)⁵⁰,⁶⁵ (negative and positive results, respectively), and TNF⁶⁷,¹³⁷,¹⁴⁶ (positive results only in the second study). No correlation was observed for adrenoreceptor beta 3 (ADRB3),¹⁴⁴ cholecystokinin (CCK),¹⁴⁷ cannabinoid receptor 1 (CNR1),¹⁴⁸ fatty acid binding protein 3 (FABP3),⁵⁰ fat mass and obesity associated (FTO),⁵⁰ peroxisome proliferator-activated receptor gamma (PPARG),¹⁴⁹ protein kinase alpha 1 catalytic subunit (PRKAA1),⁵⁰ protein kinase gamma 1 non-catalytic subunit (PRKAG1),⁵⁰ protein kinase gamma 3 non-catalytic subunit (PRKAG3),⁵⁰ DRD1,⁵⁵ DRD3,⁵⁵ DRD4,⁵⁵,¹⁵⁰ DRD5,⁵⁵ HRH1,¹⁵¹ HTR6,¹³⁶ and SLC6A4.¹³⁶ Confirmation of these results by other studies is also needed.

Additionally, polymorphisms in the HTR2C ^68-71 and methylenetetrahydrofolate reductase (MTHFR) genes⁷²,⁷³ were associated with risk of metabolic syndrome induced by clozapine or risperidone/olanzapine. No significant association was found for ADRA2A.¹⁵² Polymorphisms in the apolipoprotein A-V (APOA5) and C-III (APOC3) genes, but not in LEP, showed an influence on triglyceride and cholesterol levels in patients treated with clozapine or olanzapine.⁷⁴

Agranulocytosis is a serious adverse effect associated with clozapine. Some studies showed strong associations between polymorphisms in genes of the major histocompatibility complex (HLA) and the occurrence of this adverse effect. ^76-81 Significant associations were also found with the NAD(P)H dehydrogenase quinone 2 (NQO2)⁸² and TNF genes.⁸³ In other studies, no associations were observed with the cytochrome b-245 alpha polypeptide (CYBA),¹⁵³ P450 family 2 subfamily D polypeptide 6 (CYP2D6),¹⁵⁴ and myeloperoxidase (MPO).¹⁵³,¹⁵⁴

A study conducted with a Brazilian population sample evaluated the influence of GNB3 polymorphisms and the occurrence of tonic-clonic seizures due to clozapine treatment.³⁴ The 825T allele of the 825C>T polymorphism was significantly associated with an increased risk of developing seizures.

Ferrari et al.⁸⁴ studied the influence of CYP1A2 polymorphisms and clozapine-induced adverse effects (neurological, cardiovascular, gastroenterological, hematological, behavioral, and musculoskeletal adverse drug reactions, ADRs) and observed that the LA (low activity) phenotype was significantly more frequent in subjects with clozapine-induced ADRs than in those without ADRs.

From candidate genes to genome-wide association studies

Genome-wide association studies (GWASs), a powerful method for the large-scale analysis of genotype-phenotype relationships, are currently the method of choice for dissecting the genetic basis of complex traits.¹⁵⁵ In GWASs, genetic variations associated with response to treatment are detected randomly throughout the genome. Few studies of antipsychotic response and adverse effects have been published, partly due to the need for large samples to achieve truly significant results.¹⁵⁶ Although the few published studies have little statistical power because of insufficient sample size, they may identify new genes for investigation and assist in the elucidation of new metabolic pathways possibly related to efficacy and adverse effects of clozapine.¹⁶

A few GWASs have been conducted using samples from the CATIE study (Clinical Antipsychotic Trials of Intervention Effectiveness, n=750),¹⁵⁷ where treatment of patients was based on several classes of antipsychotics. One of these studies⁷⁵ examined 12 indicators of metabolic side effects of antipsychotics and found a polymorphism in the protein kinase type II beta gene (PRKAR2B) mediating effects of clozapine on triglyceride levels.

Malhotra et al.⁶⁴ conducted the first GWAS of weight gain in patients undergoing initial exposure to second-generation antipsychotics (SGAs) and also assessing three independent replication cohorts (one treated only with clozapine) to confirm the results. The authors found one polymorphism (rs489693) located approximately 190kb downstream from MC4R (previously identified as a candidate for weight-related phenotypes), implicating MC4R in extreme SGA-induced weight gain and related metabolic disturbances, including in the clozapine-treated sample.

More intriguing is that most candidate genes that were previously found to be associated with individual response to treatment, or adverse effects of clozapine (Tables 1 and 2), did not show statistical significance in these studies. As GWASs are exploratory, they should be replicated in independent samples.

Discussion

The study of pharmacogenetics in schizophrenia had its milestone in the work of Arranz et al.,¹⁰² conducted 12 years ago. This study had a great impact at the time because of its multigene approach and the observation of a strong association between a specific set of six polymorphisms and response to clozapine in schizophrenic patients, with a positive predictive value of 76%. Since then, few studies have been carried out with this approach. Studies with individual candidate genes have been more frequent in recent years, and GWASs are the real promise.¹⁵⁵

Study limitations

Most of the reviewed articles were individual association studies. This approach has minimal practical value, since most antipsychotics have multiple targets, and it would be unlikely for only one of these targets to be responsible for all variability in treatment response.¹¹⁴

Association studies are the most appropriate strategy for pharmacogenetic research.¹⁵⁸ However, determining the practical relevance of pharmacogenetic variants is difficult, partly because of problems with the design and replication of such studies.¹⁵⁹ The results of many studies of response to antipsychotics were not replicated in clinically similar populations, and the implication of the few studies that have been replicated still needs to be established. In addition to type I and II statistical errors, the difficulty lies mainly in the standardization of clinical samples in relation to an appropriate number of individuals and detailed clinical information about symptom improvement and development of adverse effects. The complexity of genetic factors implicated in psychiatric illness and response to medication is also a complicating factor.¹⁵⁹ Polygenic involvement in the etiology of schizophrenia hinders the identification and characterization of many genes that would be relevant as therapeutic targets and how these components interact or combine in the process. Other difficulties include incomplete knowledge of the mechanisms of schizophrenia, the complexity of brain function, and the influence of nongenetic factors, including age, diet, environmental exposures and interactions, comorbidities, and drug interactions. The dynamics of epigenetic events can also be responsible for the variations observed in the clinical response to antipsychotics.¹⁶⁰,¹⁶¹

In most meta-analyses, the heterogeneity of the antipsychotic drugs used in the analyzed studies limits the possibility of examining the association of candidate genes with any specific drug. In the pharmacogenetics of schizophrenia, meta-analyses support the involvement of DRD2¹¹² and DRD3¹⁰⁷ in treatment response and HTR2C in weight gain¹⁴¹,¹⁴² but simultaneously indicate that the establishment of pharmacogenetics associations in clinical psychiatry requires much larger sample sizes.

Population stratification in case-control studies causes most false-positive associations,¹⁶² because genetic differences between ethnic groups often lead to differences in treatment response. Additionally, non-publication of negative findings also generates a problem in terms of replication of results.¹⁵⁹ For greater uniformity in studies, some characteristics should be assured, including: 1) large sample sizes, since most genes influencing response have little effect on the phenotype; 2) standardization of clinical data important for the outcome of the phenotype (such as dose, treatment duration, age at start of treatment)¹⁶³; 3) presence of co-medication; 4) standardization of response criteria; 5) disease severity; and 6) prospective studies.

Despite continuous advances toward revealing the genetic basis of many complex traits using GWASs, a major proportion of genetic variance remains unexplained. A large number of disorders have been studied by GWASs, contributing to the detection of many previously undetected loci. For example, Franke et al.¹⁶⁴ conducted a meta-analysis of six Crohn's disease GWASs and 30 new susceptibility loci were identified at genome-wide significance. Jia et al.¹⁶⁵ examined multiple GWAS datasets in schizophrenia through meta-analysis of the related SNPs and identified 205 module genes significantly associated with schizophrenia, including well-studied candidate genes, such as GRIN2B, disrupted in schizophrenia 1 (DISC1), G protein-coupled receptor 17 (GPR17), guanine nucleotide binding protein alpha 12 (GNA12) and alpha 13 (GNA13), and alpha inhibiting activity polypeptide 1 (GNAI1). However, most GWASs have achieved limited success in explaining a considerable proportion of genetic variance of complex traits.¹⁶⁶ The very large number of markers under investigation raises the issue of multiple testing, and the need for correction, which makes it even harder to detect a small association signal.¹⁶⁷ Most of the susceptibility loci that have been discovered so far by GWASs are of small predisposing risk. In addition, detecting such contributions is difficult when the predisposing allele is rare or the sample size is not sufficiently large.¹⁶⁸ Additionally, these studies do not take into account existing biological knowledge about the trait, which could help narrow down datasets and guide the process of extracting biologically meaningful results in a more effective manner.¹⁶⁹ In view of these limitations, new approaches to analyze complex traits would be helpful.

Clinical applications

The CATIE study¹⁵⁷ and a double-blind study investigating dose of antipsychotics,¹⁷⁰ controlled for confounding variables in clinical practice, indicated that variations in metabolizing enzymes play a small role in determining the clinical response to antipsychotics. However, combining assessment of these pharmacokinetic factors with analysis of pharmacodynamic markers, each conferring moderate effects, may be a more valid approach, possibly improving cost-effectiveness in clinical practice.

Substantial advances in knowledge of the gene-response connection have been made, and pharmacogenomics approaches have become increasingly popular. With advances in sequencing technologies and bioinformatics, new dimensions in the search for multiple genes and how their expression affects response to medication are being generated. However, clinical and pharmacogenomic knowledge has not advanced as rapidly as technology, and no application has been developed yet regarding the management of schizophrenia treatment and drug development.⁶

Conclusions

Despite several decades of research, no biological or clinical predictors of response to antipsychotic medication or development of side effects have been identified.⁶ To date, efforts to identify key genes that may be useful in predicting response and adverse effects to clozapine treatment have not been fully successful, and additional studies are required. Meta-analysis results have confirmed one of the greatest difficulties of association studies: sample sizes are not large enough to detect positive associations. Therefore, further studies with much larger sample sizes are still needed to detect real associations. Great hope lies in the introduction of GWASs, as the hypothesis that a combination of genes contribute to the effect of the drug is a more likely explanation for the interindividual variability in treatment response.¹¹⁴

Pharmacogenetic-driven prescription focused on genotypes might enable optimal selection of medications and their doses in the future. However, in the treatment of multifactorial diseases, pharmacogenetics is only one of several approaches that should be analyzed, such as expression analysis and proteomics. Thus, as noted by Pirmohamed, pharmacogenetics “is coming along, but not for everything.”¹⁷¹ Only time will tell whether prediction of drug efficacy will reduce suffering and improve patient quality of life.

Acknowledgement

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), Fundação Carlos Chagas Filho de Amparo è Pesquisa do Estado do Rio de Janeiro (FAPERJ), Pró-Reitoria de Pesquisa e Inovação/Universidade Federal Fluminense (PROPPI/UFF).

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Publication Dates

• Publication in this collection
  Jul-Sep 2013

History

• Received
  23 Aug 2012
• Accepted
  19 Dec 2012