Pharmacogenetics of Antipsychotic Drug Treatment: Update and Clinical Implications

Abstract

Numerous genetic variants have been shown to be associated with antipsychotic response and adverse effects of schizophrenia treatment. However, the clinical application of these findings is limited. The aim of this narrative review is to summarize the most recent publications and recommendations related to the genetics of antipsychotic treatment and shed light on the clinical utility of pharmacogenetics/pharmacogenomics (PGx). We reviewed the literature on PGx studies with antipsychotic drugs (i.e., antipsychotic response and adverse effects) and commonly used commercial PGx tools for clinical practice. Publications and reviews were included with emphasis on articles published between January 2015 and April 2018. We found 44 studies focusing on antipsychotic response and 45 studies on adverse effects (e.g., antipsychotic-induced weight gain, movement disorders, hormonal abnormality, and clozapine-induced agranulocytosis/granulocytopenia), albeit with mixed results. Overall, several gene variants related to antipsychotic response and adverse effects in the treatment of patients with schizophrenia have been reported, and several commercial pharmacogenomic tests have become available. However, further well-designed investigations and replication studies in large and well-characterized samples are needed to facilitate the application of PGx findings to clinical practice.

Introduction

Schizophrenia is a severe neurodevelopmental disorder with high heritability [1, 2]. Likewise, genetic factors have also been implicated in antipsychotic medication used in the treatment of schizophrenia [3, 4]. Antipsychotics are currently the main medication for treatment of schizophrenia; however, the clinical response and adverse effects vary substantially between individuals, which typically leads clinicians to “trial-and-error” procedures before optimal treatment medication is found [5].

Pharmacogenetics/pharmacogenomics (PGx) is the use of genomic data to understand drug metabolism and response, which may allow clinicians to select medications based on the genetic variability across patients [6]. Multiple studies have investigated PGx approaches in order to identify genotype-specific dosing and predict antipsychotic responses and/or adverse effects [6]. Over the past years, specific recommendations on how to apply such genetic information, including commercial tests, have been proposed for clinical practice.

This narrative review summarizes most recent publications and recommendations related to the genetics of antipsychotic treatment. Furthermore, this review aims to shed light on the clinical utility of PGx.

Methods

First, recently published articles were searched using PubMed. The following search terms were applied: (schizophreni* or schizoaffective or psychosis or psychoses or “severe mental illness”) and (antipsychotic* or neuroleptic*) and (pharmacogenetic* or genetic* or genomic* or gene or “single nucleotide polymorphism” or SNP or polymorphism). Studies were included if they (1) were peer-reviewed original articles or meta-analyses, (2) referred to PGx in the treatment of patients with schizophrenia or related psychoses (i.e., serum/plasma concentrations or dosages, treatment response, and major adverse effects including antipsychotic-induced weight gain [AIWG], movement disorders, hyperprolactinemia, and clozapine-associated neutropenia), and (3) were published in English between January 2015 and April 2018. Next, expert group recommendations and Food and Drug Administration (FDA) drug labeling were reviewed regarding PGx information for antipsychotics.

Results and Discussion

Articles Included in This Review

Ninety-two original articles and 6 systematic reviews and meta-analyses were included in this review. Among the original articles, 7 reported on serum/plasma concentrations or dosage (Table 1), 44 reported on responses to antipsychotics (Table 2), and 45 reported on antipsychotic-induced adverse effects (Table 3); some of the included articles reported on two or three topics (i.e., antipsychotic concentrations or dosage, response, and adverse effects).

Table 1.

Association between genetic polymorphisms and antipsychotic serum (plasma) concentrations or dosage

Study [Ref.] (year)	Gene(s)	Polymorphism(s)	Study design	Subjects, n	Ethnicity or nationality	Treatment duration	Treatment medication	Outcome	Main findings
Hettige et al. [14] (2016)	29 candidate genes	109 SNPs	Cross-sectional 263 SCZ		European	Not reported	Various antipsychotic drugs	Antipsychotic dosage	Significant association between GABRB1 (rs16860087 and rs4627835) and higher antipsychotic dosage
Hettige et al. [15] (2016)	Exploratory	Exploratory	GWAS	83 SCZ and SAD	Caucasian, African, Asian	Not reported	Various antipsychotic drugs	Antipsychotic dosage	Polygenic risk score revealed no significant association with antipsychotic dosage
Koga et al. [16] (2016)	Exploratory	Exploratory	GWAS	79 SCZ and SAD	Caucasian	Not reported	Mainly olanzapine, risperidone, clozapine	Antipsychotic dosage	No SNPs were associated with antipsychotic dosage at a genome-wide level
Piatkov et al. [13] (2017)	ABCB1 ABCC1	rs1045642 rs212090	Prospective	137 SCZ	Caucasian, Asian, Pacific Islander, others	12 months	Clozapine	Clozapine and norclozapine concentrations	No significant association; the combination of ABCB1 and ABCC1 homozygote SNPs was associated with increased clozapine and norclozapine serum levels
van der Weide and van der Weide [7] (2015)	CYP3A4 CYP2D6	CYP3A4*22 CYP2D6 polymorphisms	Retrospective	834 psychotic disorders	Mainly Caucasian	1,380 days on average	Aripiprazole, haloperidol, pimozide, risperidone	Antipsychotic concentration	CYP2D6 genotype affected dose-corrected concentrations of the antipsychotics
Czerwensky et al. [10] (2015)	CYP1A2 UGT1A4 POR	CYP1A2*1D, CYP1A2*1F UGT1A4*3 rs2302429	Naturalistic and retrospective	98 SCZ, schizotypal, paranoid disorder, mood disorders, affective disorder, and other disorders treated with SGAs	Caucasian except for 1 Asian	>4 weeks	Olanzapine (monotherapy or in combination with other antipsychotics)	Olanzapine concentration	Significant association between CYP1A2*1D and CYP1A2*1F polymorphisms and olanzapine serum concentration
Cabaleiro et al. [11] (2015)	Several candidate genes (detailed elsewhere [11])	Several candidate polymorphisms (detailed elsewhere [11])	Randomized cross-over	79 healthy	Caucasian, except for 2 (from Guatemala)	24 h	Quetiapine	Quetiapine concentration	Pharmacokinetics was affected by DRD3 and CYP1A2 polymorphisms, and pharmacodynamics was affected by CYP2C19 polymorphisms

GWAS, genome-wide association study; SAD, schizoaffective disorder; SGAs, second-generation antipsychotics; SNP, single nucleotide polymorphism; SCZ, schizophrenia.

Table 2.

Association between genetic polymorphisms and clinical response to antipsychotic medications

Study [Ref.] (year)	Gene(s)	Polymorphism(s)	Study design	Subjects, n	Ethnicity or nationality	Treatment duration	Treatment medication	Outcome	Main findings
McGregor et al. [54] (2018)	MMP9	Several SNPs	Prospective	103 FES	South African, Xhosa, Caucasian	12 months	Flupenthixol decanoate	PANSS	Several variants within MMP9 showed associations with treatment response
Sun et al. [41] (2018)	COMT	rs165599, rs4680	Prospective	96 SCZ	Han Chinese	8 weeks	Various antipsychotic drugs	PANSS	Significant association between COMT rs4680 and treatment response
Yu et al. [77] (2018)	Exploratory	Exploratory	GWAS	Discovery sample: 2,413 SCZ; Replication sample: 1,379 SCZ	Discovery sample: Han Chinese; Replication sample: Han Chinese	Sample A: 6 weeks; Sample B: 8 weeks	Discovery sample: aripiprazole, olanzapine, quetiapine, risperidone, ziprasidone, or one of the firstgeneration antipsychotics (haloperidol or perphenazine); Replication sample: olanzapine, risperidone, or aripiprazole	PANSS	Five novel loci (rs72790443 in MEGF10, rs1471786 in SLC1A1, rs9291547 in PCDH7, rs12711680 in CNTNAP5, and rs6444970 in TNIK) were significantly associated with treatment response; furthermore, three additional loci were associated with drug-specific treatment responses (rs2239063 in CANCA1C for olanzapine, rs16921385 in SLC1A1 for risperidone, and rs17022006 in CNTN4 for aripiprazole)
Calabrò et al. [42] (2018)	COMT, GSK3B, HTR2A, PLA2G4A, SIGMAR1	12 SNPs	Naturalistic	83 SCZ	Italian	10 days	Various antipsychotic drugs	PANSS	Suggested association between PLA2G4A rs1214459 and positive symptom response
CHRNA7, COMT, CREB1, GSK3B, HTR2A, MAPK1, PLA2G4A, S100B, SIGMAR1	49 SNPs	Naturalistic	176 SCZ	Korean	37.5±17.08 days	Olanzapine, quetiapine, risperidone	PANSS	Suggested associations between CHRNA7 (rs11071511), HTR2A (rs1328685), and PLA2G4A (rs10798069) and positive symptom response; suggested associations between CHRNA7 (rs2337980 and rs6494223), HTR2A (rs643627), and SIGMAR1 (rs10814130) and negative symptom response
Li et al. [78] (2018)	Exploratory	Exploratory	GWAS, Sample A: double-blind, randomized; Sample B: double-blind, randomized	Sample A: 171 SCZ; Sample B: 131 SCZ	Sample A: Caucasian; Sample B: African American	Sample A: 6 weeks; Sample B: 6 weeks	Lurasidone	PANSS	No significant findings after multiple testing correction; common genetic variants related to synaptic adhesion complexes, scaffolding, and the alternative splicing regulator may be associated with treatment response to lurasidone
Calabrò et al. [55] (2017)	BDNF, ESYT2, NCAPG2, PKDCC, VIPR2, WDR60	15 SNPs	Naturalistic	83 SCZ	Italian	10 days	Various antipsychotic drugs	PANSS	Suggested associations between ESYT2 rs2657375 and positive symptom response
ARC, BDNF, CHL1, ESYT2, 51 SNPs HOMER1, NCAPG2, TXNRD2, VIPR2, WDR60		Naturalistic	176 SCZ	Korean	37.5±17.08 days	Olanzapine, quetiapine, risperidone	PANSS	HOMER1 rs3822568 was nominally associated with antipsychotic response; suggested associations between TXNRD2 rs4646310 and positive symptom response; suggested association between ARC rs10110456 and HOMER1 rs6893883 and negative symptom response
Kang et al. [56] (2017)	SNAP25	rs8636, rs3746544	Observational	101 SCZ	Korean	6 weeks	Amisulpride	PANSS	Significant association between SNAP25 rs8636 and treatment response
Kaur et al. [21] (2017)	DRD2 HTR2A CYP2D6	rs1800497, rs1079597, rs180498, rs1801028 rs6313, rs6311, rs6305 rs3892097, rs106585	Prospective	SCZ	Indian	12 weeks	Risperidone	PANSS	Significant associations between DRD2 rs180498 and HTR2A rs6305 and treatment response; CYP2D6 rs3892097 was significantly associated with treatment response when dropouts were excluded from analysis
Papazis is et al. [24] (2018)	ABCB1 CYP2D6	rs2032582, rs1045642 common variants	Naturalistic	SCZ or other psychotic disorder	Caucasian	4 weeks	Various antipsychotic drugs	PANSS	No significant association; however, a combination of a loss-of-function CYP2D6 allele and the TT genotype of ABCB1 rs2032582 were associated with poor response to antipsychotic treatment
Shi et al. [43] (2017)	100 risperidone response-related genes	Exploratory	Prospective	288 SCZ	Chinese	4 weeks	Risperidone	PANSS	UGT1A3 rs6706232 and COMT rs4818 were significantly associated with treatment response in the meta-analysis
Kang et al. [69] (2017)	ANKS1B	rs7968606	Prospective	101 SCZ	Korean	6 weeks	Amisulpride	PANSS	Significant association between ANKS1B rs7968606 and treatment response
Taylor et al. [57] (2017)	SLC1A2 SLC6A9 GRIA1 GRM2 GAD1	rs4354668, rs4534557, rs2901534 rs12037805, rs1978195, rs16831558 rs2195450 rs4067, rs2518461 rs3749034	Prospective	163 SCZ and SAD	European	6 months	Clozapine	BPRS	No significant association
Ovenden et al. [79] (2017)	Exploratory	Exploratory	GWAS, prospective	103 FES	South African	12 months	Flupenthixol decanoate	PANSS	Suggested associations between MANBA, COL9A2, and NFKB1 and treatment response
Li et al. [80] (2017)	Exploratory	Exploratory	GWAS	1,390 SCZ from 12 trials	European	≥6 weeks	Paliperidone extended-release or paliperidone palmitate	PANSS	ADCK1 gene variants may be associated with paliperidone efficacy
Sacchetti et al. [68] (2017)	Exploratory	Exploratory	GWAS	Discovery sample: 86 SCZ; Replication sample: 97 SCZ, SAD	Sample A: Caucasian; Sample B: European	Sample A: 2 weeks; Sample B: 9 months	Risperidone	PANSS	Significant association between GRM7 rs2133450 and treatment response
Labad et al. [58] (2016)	ESR1 UGT1A8	rs9340799, rs2234693, rs1801132 rs1042597	Double-blind, randomized	65 SCZ (female, postmenopausal status)	Spanish	24 weeks	Raloxifene	PANSS	UGT1A8 rs1042597 and ESR1 rs2234693 were significantly associated with negative symptoms and general psychopathology, respectively
Brandl et al. [59] (2016)	ITIH3	rs2535629	Sample A: prospective; Sample B: prospective; Sample C: double-blind, randomized; Sample D: prospective	256 SCZ, SAD	European, African American	Sample A: up to 6 weeks; Sample B: up to 6 months; Sample C: up to 14 weeks; Sample D: up to 6 months	Sample A: various antipsychotic drugs; Sample B: clozapine; Sample C: various antipsychotic drugs; Sample D: clozapine	BPRS	Significant association of ITIH3 rs2535629 with improvement of negative symptoms in Europeans
Terzić et al. [29] (2016)	DRD1 DRD2 DRD3 COMT	rs4532, rs5326 rs1801028, rs1799732 rs6280 rs165815, rs4680	Case-control	138 SCZ, 94 healthy	Slovenian	Not reported	Various antipsychotic drugs	PANSS, BPRS, and GAF	No significant association between any of the genotypes and treatment response, and the occurrence of treatment-resistant schizophrenia
Porcelli et al. [60] (2016)	PDE7B NMBR EPM2A	rs975676, rs3734548 rs2717, rs6926279, rs6902780 rs1415744, rs702304, rs2235481	Case-control	573 SCZ, 560 healthy	Korean	20–40 days	Various antipsychotic drugs	PANSS	Significant association between EPM2A rs1415744 and treatment response in negative symptoms
Drögemöller et al. [83] (2016)	Exploratory	Exploratory	Whole-exome sequencing	Discovery sample: 103 FES; Replication sample: 87 FES	Discovery sample: South African Colored, Xhosa, European; Replication sample: African American, European	Discovery sample: 3 months; Replication sample: ≥3 months	Discovery sample: flupenthixol decanoate; Replication sample: various antipsychotic drugs	Discovery sample: PANSS; Replication sample: BPRS	Significant association between rs13025959 in MYO7B (E1647D) and rs10380 in MTRR (H622Y) and treatment response
Stevenson et al. [67] (2016)	Candidate genes involved with glutamate signaling and exploratory	Candidate SNPs and exploratory	GWAS, prospective (open-label)	Discovery sample: 86 first-episode patients (SCZ, SAD, psychotic bipolar disorder, or major depressive disorder with psychotic features); Replication sample: 240 patients from the CATIE study	Discovery sample: Caucasian, African American	Discovery sample: 6 weeks	Discovery sample: various antipsychotic drugs (mainly risperidone monotherapy); Replication sample: risperidone	BPRS	Significant association between GRM7 (rs2069062 and rs2014195) in candidate gene analysis and GRID2 (rs9307122 and rs1875705) in GWAS analysis and treatment response
Taylor et al. [61] (2016)	GRIN2B	rs3764030, rs7301328, rs12826365, rs1072388, rs2284411, rs1806201, rs1806191, rs890	Prospective	175 SCZ and SAD	European	6 months	Clozapine	BPRS	No significant association
Jajodia et al. [62] (2016)	Candidate genes of NRG1-ERBB signaling pathway, neuroactive ligand-receptor interaction, glutamate signaling	1,536 SNPs	Cross-sectional and naturalistic	742 SCZ and 786 healthy	Indian	3 months	Various antipsychotic drugs	CGI	CCL2 (rs4795893, rs4586) and GRIA4 (rs2513265) in the low severity group, and ADCY2 (rs1544938) and NRG1 (rs13250975 and rs17716295) in the high severity group were associated with treatment response
Chen et al. [44] (2016)	COMT	rs2075507, rs737865, rs933271, rs5993883, rs740603, rs4646312, rs4633, rs6267, rs4818, rs4680, rs165774, rs174697, rs165599, rs165728	Naturalistic	185 SCZ	Han Chinese	12 weeks	Amisulpride	PANSS	Significant association between COMT variants (rs4680, rs4633, and rs6267) and treatment response, particularly negative symptoms
Huang et al. [30] (2016)	DRD2	rs2514218	Prospective	208 SCZ	Caucasian, African American, and others	6 months	Clozapine	BPRS	Significant association between DRD2 rs2514218 and treatment response
Xu et al. [23] (2016)	25 candidate genes including CYP2D6, CYP2C19, COMT, ABCB1, DRD3, and HTR2C	77 SNPs	Prospective	995 SCZ	Han Chinese	2 weeks	Risperidone, clozapine, quetiapine, chlorpromazine	PANSS	Significant associations of several genes, including new candidate genes, with treatment response; however, most of the associations remained no longer after multiple corrections, except for COMT (rs6269, rs5993883, and rs4818); significant association of haplotype rs1544325-rs5993883-rs6269-rs4818 in COMT with treatment response; the combination of rs6269 in COMT and rs3813929 in HTR2C may be associated with treatment response
Takekita et al. [53] (2015)	HTR7	rs12412496, rs7916403, rs1935349	Randomized open-label	100 SCZ	Japanese	12 weeks	Aripiprazole or perospirone	PANSS	No significant association
Lee et al. [63] (2015)	ALDH2	ALDH2 polymorphisms	Double-blind, randomized	149 SCZ	Taiwanese	11 weeks	Risperidone + dextromethorphan or risperidone + placebo	PANSS, SANS	The ALDH2*2*2 genotype was significantly associated with negative symptoms in the risperidone + dextromethorphan group
Zhang et al. [31] (2015)	DRD2	rs2514218	Double-blind, randomized	198 FEP	Asian, African American, Hispanic, Caucasian, and others	12 weeks	Aripiprazole or risperidone	BPRS, SANS	Homozygotes for the rs2514218 risk allele (C) had a significantly greater reduction in positive symptoms than T-allele carriers
Le Clerc et al. [81] (2015)	Exploratory	Exploratory	GWAS, prospective	89 SCZ	Caucasian	6 weeks	Olanzapine or risperidone	BPRS, PANSS	Significant association between PPP1R18 rs3129996 and treatment response
Porcelli et al. [64] (2015)	CACNA1C	24 SNPs	Case-control	176 SCZ, 326 healthy	Korean	Not reported	Risperidone, olanzapine, quetiapine	PANSS	Five SNPs (rs723672, rs1034936, rs2283271, rs10848635, and rs1016388) were associated with an improvement in PANSS subscale scores
Takekita et al. [49] (2015)	HTR1A	rs6295, rs1364043, rs878567, rs10042486	Randomized open-label	100 SCZ	Japanese	12 weeks	Aripiprazole or perospirone	PANSS	HTR1A rs1364043 and the rs10042486-rs6295-rs1364043 haplotype may affect negative symptoms in PANSS
Terzić et al. [50] (2015)	5-HT1A SLC6A4	rs6295 5-HTTLPR	Case-control	138 SCZ (94 treatment responsive and 44 treatment resistant) and 94 healthy	Slovenian	Not reported	Various antipsychotic drugs including clozapine	PANSS, BPRS, CGI, GAF	Association between 5-HT1A rs6295 and GAF score; association between the three-allelic 5-HTTLPR polymorphism and GAF score and the negative subscale score of the PANSS
Pai et al. [25] (2015)	GRIN1 ABCB1 DRD4	rs11146020 rs1045642, rs2032582 rs1800955, rs4646984	Prospective	195 SCZ and 136 healthy	Indian	12 weeks	Mainly risperidone and olanzapine	CGI-S	No significant association
Wang et al. [82] (2015)	Exploratory	Exploratory	GWAS	Discovery sample: 684 SCZ; Replication sample: 2,856 SCZ	Detailed elsewhere [82]	Discovery sample: 6, 9, or 30 weeks; Replication sample: 2, 6, 13, or 53 weeks	Paliperidone	PANSS	ERBB4 rs6435681 was significantly associated with treatment response
Kang et al. [32] (2015)	DRD2	rs1079597, rs1800497	Prospective	125 SCZ	Korean	6 weeks	Amisulpride	PANSS	Significant association between DRD2 rs1079597 and treatment response
Porcelli et al. [65] (2015)	AHI1	rs11154801, rs7750586, Case-control rs9647635, rs9321501		426 SCZ and 345 healthy	Korean	Not reported	Not reported	PANSS	AHI1 rs7750586 and rs9647635 were associated with treatment response of negative symptoms
Blasi et al. [33] (2015)	DRD2 HTR2A	rs1076560 rs6314	Sample A: prospective; Sample B: double-blind, randomized	Sample A: 63 SCZ; Sample B: 54 SCZ, 620 healthy	Caucasian	Sample A: 8 weeks; Sample B: 4 weeks	Sample A: olanzapine; Sample B: various antipsychotic drugs	PANSS	DRD2 rs1076560 and HTR2A rs6314 together affected the treatment response
Bosia et al. [45] (2015)	COMT 5-HT1A-R	rs4680 rs6295	Prospective	107 SCZ	Italian	≥3 months	Clozapine	PANSS	Significant association between COMT and 5-HT1A-R and treatment response in negative symptom variation
Pouget et al. [66] (2015)	TSPO	rs739092, rs5759197, rs138911, rs1l3515, rs6971/rs6973, rs80411, rs138926	Sample A: naturalistic; Sample B: prospective; Sample C: double-blind, randomized; Sample D: prospective	161 SCZ and SAD	European	Up to 14 weeks	Clozapine, olanzapine, quetiapine, risperidone, others	BPRS	No significant association
Huo et al. [37] (2015)	DRD1	rs5326, rs4867798, rs4532, rs686	Prospective	185 SCZ	Han Chinese	4 weeks	Risperidone	PANSS	No significant association
Brand1 et al. [22] (2015)	CYP3A43	rs472660, rs680055	Prospective	152 SCZ or SAD (Sample A: 86; Sample B: 66)	European	Up to 6 months	Various antipsychotics including clozapine	BPRS	Significant association between CYP3A43 rs680055 and treatment response
Bishop et al. [34] (2015)	GRM3 DRD2/ANKK1 COMT	rs6465084, rs274622, rs1989796, rs1468412, rs2228595 rs1799732 (−141C Ins/Del), rs1800497 (TaqIA) rs4680 (Val158Met)	Prospective	61 untreated FES, SAD, schizophreniform disorder; 130 healthy	Caucasian, African American, Hispanic, and Asian	6 weeks	Mainly risperidone	BPRS	Negative symptom improvement was associated with rs6465084 in the GRM3 gene
Czerwensky et al. [10] (2015)	CYP1A2	CYP1A2*1D, CYP1A2*1F	Naturalistic, retrospective	209 SCZ, schizotypal, paranoid disorder, mood disorders, affective disorder, and other disorders treated with SGAs	Caucasian except for 1 Asian	≥4 weeks	Olanzapine or clozapine (monotherapy or in combination with other antipsychotics)	Paranoid Depressive Scale	Significant association between at least two factors promoting higher serum concentrations (no CYP1A2 inducer, *1D deltT allele, or *1F C allele) and abetter response

BPRS, Brief Psychiatric Rating Scale; CAT1E, Clinical Antipsychotic Trial of Intervention Effectiveness; CGI-S, Clinical Global Impression-Severity; FEP, first-episode psychosis; FES, first-episode schizophrenia; GAF, Global Assessment of Functioning; GWAS, genome-wide association study; PANSS, Positive and Negative Syndrome Scale; SGAs, second-generation antipsychotics; SAD, schizoaffective disorder; SANS, Scale for the Assessment of Negative Symptoms; SNP, single nucleotide polymorphism; SCZ, schizophrenia.

Table 3.

Association between genetic polymorphisms and antipsychotic adverse effects

Study [Ref.] (year)	Gene(s)	Polymorphism(s)	Study design	Subjects, n	Ethnicity or nationality	Treatment duration	Treatment medication	Outcome	Main findings
Antipsychotic-induced weight gain and metabolic syndrome
Mittal et al. [109] (2017)	mtDNA and 670 nuclear-encoded mitochondrial genes	mtDNA SNPs and nuclear-encoded mitochondrial genes	mtDNA sequencing and gene set analysis	74 SCZ and 168 SCZ	Caucasian	143±11.98 days	Risperidone, quetiapine, olanzapine	AIWG	Thirty nuclear-encoded mitochondrial genes were nominally significantly associated with AIWG; of these, the associations of three genes (CLPS, PAUL, and ACAD10) with AIWG were replicated
Piatkov et al. [13] (2017)	ABCB1 ABCC1	rs1045642 rs212090	Prospective	137 SCZ	Caucasian, Asian, Pacific Islander, others	12 months	Clozapine	AIWG	No significant association; ABCB1 rs1045642 and ABCC1 rs212090 were associated with AIWG in males after 3 months and 12 months of clozapine treatment, respectively
Li et al. [160] (2017)	23 genes	43 SNPs	Prospective	339 SCZ and SAD (86 first-episode patients)	Chinese	12 weeks	Olanzapine, risperidone, clozapine, quetiapine, aripiprazole, ziprasidone	AIWG	TOX rs11777927 and ADIPOQ rs182052 were associated with BMI; BDNF rs6265, BDAF rs11030104, and ADIPOQ rs822396 were significantly associated with a change in waist-to-hip ratio
Klemettilä et al. [161] (2017)	21 genes (NPY gene, NPY receptor genes, and genes encoding arcuate nucleus NPY neuron receptors)	215 SNPs	Cross-sectional	180 SCZ (F2 group accordingto ICD-10)	Finnish	≥3 months (some patients with no data)	Clozapine	AIWG	21 genes (NPY gene, NPY receptor genes, and genes encoding arcuate nucleus NPY neuron receptors)
Daray et al. [89] (2017)	HTR2C	rs3813939 (-759C>T)	Prospective	48 SCZ or related illness (female)	Caucasian	6 weeks	Risperidone, olanzapine, clozapine, quetiapine	AIWG	T allele at position −759 (TT or CT) was associated with less weight gain
Zhang et al. [162] (2017)	C3	3 tag SNPs and rs7951, rs2230199, rs2250656, rs1l672613	Cross-sectional	576 SCZ	Han Chinese	2 years	Clozapine monotherapy or combination therapy	MetS	Significant association between C3 rs2277984 and MetS
Koskinen et al. [105] (2016)	INSIG2	rs1559509, rs2161829, rs2161830, rs9308762, rs12151787, rs1049626, rs17047733	Cross-sectional	190 SCZ (F2 group accordingto ICD-10)	Finnish	≥3 months	Clozapine	AIWG	Significant association between INSIG2 SNPs (rs12151787, rs1049626, and rs17047733) and weight gain
Brandl et al. [110] (2016)	Exploratory	Exploratory	GWAS	CATIE sample: 189 SCZ; Toronto sample: 86 SCZ and SAD	CATIE sample: European or African American; Toronto sample: European	CATIE sample: up to 18 months; Toronto sample: up to 6 weeks (Sample A), 6 weeks (Sample B), or 14 weeks	CATIE sample: risperidone, quetiapine, olanzapine; Toronto sample: olanzapine, clozapine	AIWG	None of the SNPs were significantly associated with AIWG, although nominal associations were found for rs9346455 upstream of OGFRL1 and rs1059778 in IBA57
Zai et al. [94] (2016)	HTR3A HTR3B	21 SNPs	Sample A: naturalistic; Sample B: prospective; Sample C: double-blind, randomized	149 SCZ and SAD	European	Sample A: up to 6 weeks; Sample B: 6 weeks; Sample C: up to 14 weeks	Sample A: haloperidol olanzapine, risperidone, aripiprazole, quetiapine, amisulpride; Sample B: clozapine; Sample C: clozapine, olanzapine	AIWG	No significant association
Grädinaru et al. [90] (2016)	HTR2C	rs3813929 (-759C/T)	Prospective	81 SCZ and bipolar disorder	Romanian	Up to 18 months	Risperidone, aripiprazole, olanzapine	AIWG and hyperinsulinemia	No significant association between HTR2C rs3813929 and AIWG; however, a significant association between insulinemia and T-allele carriers was found
Tiwari et al. [163] (2016)	HRH1 HRH3	40 tag SNPs	Retrospective	193 SCZ and SAD	European American, African American, and others	Up to 14 weeks	Clozapine, haloperidol, olanzapine, risperidone, and others	AIWG	No significant associations between the SNPs in HRH1 and HRH3 and AIWG
Fang et al. [100] (2016)	BDNF	rs6265 (Val66Met)	Cross-sectional	308 chronic schizophrenia, 304 healthy	Han Chinese	≥12 months	Clozapine, risperidone, other typical antipsychotics	AIWG	Significant association between BDNF rs6265 and AIWG
Rico-Gomis et al. [93] (2016)	HTR2C	rs1414334	Cross-sectional, observational	166 SCZ, SAD, schizophreniform disorder, other psychotic disorders, bipolar disorder	Spanish	≥3 months	Various antipsychotics	MetS	No significant association between the C allele of the rs1414334 polymorphism in the HTR2C gene and MetS
Yang et al. [104] (2016)	SCAP SREBF1	5 SNPs 11SNPs	Cross-sectional	722 SCZ	Han Chinese	≥1 year	Clozapine, olanzapine, risperidone	MetS	Significant association between the rs11654081 T allele of the SREBF1 gene and an increased risk for MetS
Ryu et al. [164] (2016)	60 candidate genes	233 SNPs	Prospective	Sample A: 84 SCZ; Sample B: 46 SCZ	Korean	Sample A: up to 8 weeks; Sample B: ≥4 weeks (up to 48 weeks)	Sample A: risperidone, olanzapine, amisulpride, quetiapine, and others; Sample B: risperidone, olanzapine	AIWG and appetite change	No significant association between these SNPs and BMI or appetite change; GHRL rs696217 suggested evidence of an association with weight gain and appetite change
Yu et al. [111] (2016)	Exploratory	Exploratory	GWAS	Discovery sample: 534 SCZ; Replication sample: 547 SCZ	Han Chinese	Discovery sample: 8 weeks; Replication sample: 8 weeks	Various antipsychotics	AIWG	Significant association between rs10977144 and rs10977154 in PTPRD and rs12386481 in GFPT2 and AIWG
Tiwari et al. [165] (2016)	HCRTR1 HCRTR2	Tag SNPs (exploratory)	Sample A: naturalistic; Sample B: prospective; Sample C: double-blind, randomized	Discovery sample: 218 SCZ and SAD (Sample A: n = 88; Sample B: n = 74; Sample C: n = 56); Replication sample: 122 SCZ	Discovery sample: European American, African American, and others; Replication sample: European	Discovery sample: up to 6 weeks (Sample A), 6 weeks (Sample B), or 14 weeks (Sample C); Replication sample: up to 190 days	Discovery sample: clozapine, haloperidol, olanzapine, risperidone, and others (Sample A); clozapine (Sample B); clozapine, haloperidol, olanzapine, risperidone (Sample C); Replication sample: olanzapine, risperidone	AIWG	Genetic variation in HCRTR2 was associated with weight gain; none of the SNPs in HCRTR1 were associated with weight gain
Wang et al. [166] (2015)	85 candidate genes	768 SNPs	Prospective	216 SCZ	Han Chinese	4 weeks	Risperidone	AIWG	Significant association between four SNPs on SLC6A4 (rs3813034, rs1042173, rs4325622, and rs9303628) and AIWG
Chen et al. [167] (2015)	TMEM18 SH2B1 GNPDA2	rs6548238 rs7498665 rs10938397	Double-blind, randomized	55 SCZ, SAD (metformin treatment [n = 28] or placebo [n = 27])	Taiwanese	24 weeks	Clozapine	AIWG	Significant association in the TMEM18 and GNPDA2 minor-allele carrier groups; body weight reduction in the metformin group
Dong et al. [168] (2015)	A2BP1	rs10500331, rs4786847, rs8048076, rs1478697	Prospective	Discovery sample: 328 SCZ; Replication sample: 208 FES and drug-naïve SCZ	Han Chinese	Discovery sample: 8 weeks; Replication sample: 4 weeks	Olanzapine	AIWG	Significant association between A2BP1 rs1478697 and AIWG
Bonaccorso et al. [99] (2015)	BDNF	rs6265 (Val66Met)	Randomized trial, prospective	76 SCZ and SAD; 90 bipolar disorder	Caucasian, African American, others	12 months	Olanzapine, risperidone	AIWG, Metabolic parameters	Significant association between BDNF Met66 allele carriers and AIWG in all patients
Pouget et al. [66] (2015)	TSPO VDAC1 ANT1	rs739092, rs5759197, rs138911, rs1l3515, rs6971, rs6973, rs80411, rs138926 rs13169435, rs4279383, rs2288834 rs10024068, rs7660552	Discovery: Sample A, naturalistic; Sample B, prospective; Sample C, double-blind, randomized; RUPP: prospective; Munich: naturalistic	Discovery: 109 SCZ and others; RUPP: 119 autism spectrum disorder; Munich: not reported	Discovery: European; RUPP: European and Hispanic; Munich: European	Discovery: up to 14 weeks; RUPP: 8 weeks; Munich: ≥4 weeks	Discovery: clozapine, olanzapine, quetiapine, risperidone, and others; RUPP: risperidone; Munich: SGAs	AIWG	TSPO rs6971 was nominally associated with AIWG in the discovery for the clozapine/olanzapine subsample and the RUPP sample, and it interacted with ANT1 rs10024068 in the discovery and RUPP samples
Fonseka et al. [169] (2015)	IL-1β IL-2 IL-6 BDNF	rs4849127, rs13032029, rs16944, rs3136558, rs1143634, rs1143643 rs2069762, rs2069778, rs2069779, rs2069772, rs2069776 rs2069827, rs1800795, rs2069837, rs2066992, rs2069840, rs2069861, rs10242595 rs6265	Sample A: naturalistic; Sample B: prospective; Sample C; double-blind, randomized	188 SCZ, SAD	European, African, and others	Up to 14 weeks	Clozapine, haloperidol, olanzapine, risperidone, others	AIWG	SNPs across IL-1β and BDNF rs6265 may influence AIWG
Zai et al. [170] (2015)	GABRA2	rs16859227, rs279858, rs1442060, rs3849591, rs1442062, rs16859354, rs1l503014, rs6856130, rs1372472	Sample A; naturalistic; Sample B; prospective; Sample C; double-blind	160 SCZ, SAD	European	Up to 14 weeks	Various antipsychotics (mainly clozapine and olanzapine)	AIWG	Significant association between GABRA2 rs279858 and AIWG
Ono et al. [171] (2015)	GIPR	rs10423928	Prospective	32 SCZ	Japanese	4 weeks	Olanzapine	AIWG	Significant association between GIPR rs10423928 and AIWG
Klemettilä et al. [92] (2015)	LEP ADIPOQ HTR2C	rs7799039 (-2548A/G) rs1501299 rs1414334	Retrospective	190 SCZ (clinical diagnosis of F2 group according to ICD-10), 395 healthy	Finnish	≥3 months	Clozapine (monotherapy or combination therapy with other antipsychotics)	AIWG	No significant associations between LEP rs7799039, ADIPOQ rs1501299, and HTR2C rs1414334 and AIWG
Yang et al. [103] (2015)	SREBF2	rs4822063, rs17002737, rs2267439, rs5996080, rs5996078, rs1569451, rs2228314, rs1052717, rs2267443, rs17379759	Case-control	621 SCZ	Han Chinese	≥1 year	Clozapine	MetS	Significant associations between SREBF2 A allele of rs2267443 and rs1052717 and MetS
Czerwensky et al. [10] (2015)	CYP1A2	CYP1A2*1D, *1F	Naturalistic and retrospective	209 SCZ, schizotypal disorder, paranoid disorder, mood disorders, affective disorder, and other disorders treated with SGAs	Caucasian and 1 Asian	≥4 weeks	Olanzapine, clozapine (monotherapy or in combination with other antipsychotics)	AIWG	No significant association
Antipsychotic-induced movement disorders Kang et al. [113] (2018)	MAP2K5	rs1026732, rs11635424, rs12593813, rs4489954, rs3784709	Case-control	190 SCZ	Korean	Not reported	Various antipsychotics	RLS	No significant association; however, the G-G-G-G-T (rs1026732-rs11635424-rs12593813-rs4489954-rs3784709) haplotype was associated with RLS
Zai et al. [114] (2017)	NRG1 ERBB4	rs35753505, rs6994992 rs839523	Cross-sectional	153 SCZ and SAD	European	≥1 year	Typical or atypical antipsychotics	TD	Significant association between ERBB4 rs839523 and TD
Lanning et al. [115] (2017)	NRXN1	rs17041112, rs10490162, rs1400882, rs12467557, rs1045881	Cross-sectional	178 SCZ and SAD	European	≥12 months	Typical antipsychotics	TD	No significant association
Hui et al. [124] (2017)	DBH	DBH5′-Ins/Del polymorphism	Case-control	742 SCZ	Han Chinese	≥12 months	Clozapine, risperidone, perphenazine, sulpiride, chlorpromazine, haloperidol	TD	No significant association
Sychev et al. [116] (2016)	CYP2D6	1846G>A (CYP2D6*4)	Cross-sectional	79 SCZ (F2 group according to ICD-10)	Russian and Tatar	Not reported	Haloperidol, risperidone, paliperidone, quetiapine, others	EPS	Significant association of CYP2D6 heterozygous 1846GA genotype and 1846A allele frequency with EPS in patients treated with haloperidol
Mas et al. [117] (2016)	31 candidate genes (involved in dopamine, serotonin, and glutamate pathways)	202 SNPs	Naturalistic	113 FEP	Caucasian and others	Up to 12 months	Amisulpride, paliperidone, risperidone, ziprasidone	EPS	Significant associations between four SNPs (rs9567733 [HTR2A], rs363341 [SLC18A2], rs1334802 [GRIK3], and rs1124491 [DRD2]) and EPS
Ivanova et al. [118] (2016)	GRIN2A GRIN2B DRD3 HTR2C DRD4	43 tag single nucleotide polymorphisms	Cross-sectional	Sample A: 431 SCZ; Sample B: 168 SCZ, psychosis, affective disorders, and others	Caucasian (Sample A: Siberian; Sample B: Dutch)	Not reported	Not reported	TD	Only GRIN2A rs1345423 exhibited a significant association with TD in both groups
Ivanova et al. [119] (2016)	CYP1A2 CYP2D6	CYP1A2*1F CYP2D6*3, CYP2D6*4	Case-control	353 SCZ	Caucasian	Not reported	Various antipsychotics	TD	Significant associations of polymorphic variant CYP1A2*1F(-163C>A) of CYP1A2, polymorphic variant CYP2D6*4 (1846G>A), and genotype A/A of CYP2D6 with TD
Kang et al. [120] (2015)	MEIS1	rs2300478, rs6710341	Cross-sectional	190 SCZ	Korean	Not reported	Various antipsychotics	RLS	No significant association between MEIS1 (rs2300478 and rs6710341) and antipsychotic-induced RLS
Mas et al. [121] (2015)	Exploratory	Exploratory	Protein-protein interaction network construction and functional annotation analysis	12 antipsychotic-naïve patients with FEP	Caucasian	9 days (± 1 day) or as soon as any EPS appeared and prior to starting treatment with anti-parkinsonian drugs	Risperidone, paliperidone	EPS	Suggested association between the NF-κB pathway (inflammatory response) and mTOR pathway (lipid biosynthesis, insulin signaling, and autophagy) and EPS
Ivanova et al. [122] (2015)	CYP1A2	rs762551 (-163C<A)	Case-control	319 SCZ, schizotypal disorder; 117 healthy	Caucasian	Not reported	Various antipsychotics	TD	Significant association between the CYP1A2*1F (-163C>A) polymorphism and limb-truncal TD
Mas et al. [123] (2015)	TSC1 TSC2 mTOR AKT1 FCHSD1 PARK2 DISCI RPTOR DDIT4	rs7874234 rs13335638 rs2024627 rs1l30214 rs456998 rs1801582 rs3737597 rs7211818 rs1053639	Case-control	Sample A: 114 patients treated with risperidone; Sample B: 102 patients treated with antipsychotics (except for risperidone or clozapine); Sample C: 27 antipsychotic- naïve patients with FEP treated with risperidone, paliperidone, or amisulpride	Spanish	Not reported	Sample A: risperidone; Sample B: antipsychotics other than risperidone or clozapine; Sample C: risperidone, paliperidone, amisulpride	EPS	Significant association of a four-way interaction, including AKT1 rs1l30214, FCHSD1 rs456998, RPTOR rs7211818, and DDIT4 rs1053639, with EPS
Antipsychotic-induced prolactin increase
Ivanova et al. [139] (2017)	PRL	rs1341239 (-1149G/T)	Case-control	443 SCZ and 126 healthy	Russian	Not reported	Various antipsychotics	Hyperprolactinemia	Significant association between the polymorphic variant rs1341239 and hyperprolactinemia
Ivanova et al. [140] (2017)	HTR1A HTR1B HTR2A HTR2C HTR3A HTR3B HTR6	29 SNPs	Cross-sectional	446 SCZ	Caucasian	Not reported	Various antipsychotics	Hyperprolactinemia	Significant association between hyperprolactinemia and the HTR2C X-chromosome polymorphisms rs569959 and rs17326429
Chen et al. [44] (2016)	COMT	rs2075507, rs737865, rs933271, rs5993883, rs740603, rs4646312, rs4633, rs6267, rs4818, rs4680, rs165774, rs174697, rs165599, rs165728	Naturalistic	185 SCZ	Han Chinese	12 weeks	Amisulpride	Prolactin level	Significant association between COMT rs4680 and prolactin level
Clozapine-induced agranulocytosis/granulocytopenia
Legge et al. [145] (2017)	Exploratory	Exploratory	Combination of GWAS, HLA allele imputation, exome array, and copy number variation	Discovery sample: 5,649 SCZ (clozapine-associated neutropenia: n = 66; control: n = 5,583); Replication sample: up to 163 cases and 7,970 controls	Discovery sample: European; Replication: detailed elsewhere [82]	Not reported	Clozapine	Clozapine-associated neutropenia	Significant association between rs149104283, located between SLCO1B3 and SLCO1B7, and clozapine-associated neutropenia; the association of HLA-DQB1 6672G>C (rs113332494) with clozapine-associated agranulocytosis was replicated
Saito et al. [144] (2016)	Exploratory	Exploratory	GWAS	CIAG patients: n = 50; healthy controls: n = 2,905; clozapine-tolerant controls: n = 380	Japanese	CIAG patients: up to 180 days; clozapine-tolerant controls: >180 days	Clozapine	CIAG	Significant association between HLA-B*59:01 and CIAG

AIWG, antipsychotic-induced weight gain; CIAG, clozapine-induced agranulocytosis/clozapine-induced granulocytopenia; EPS, extrapyramidal symptom; FEP, first-episode psychosis; GWAS, genome-wide association study; HLA, human leukocyte antigen; ICD-10, International Statistical Classification of Diseases and Related Health Problems, 10th Revision; MetS, metabolic syndrome; mtDNA, mitochondrial DNA; RLS, restless legs syndrome; RUPP, Research Units on Pediatric Psychopharmacology; SAD, schizoaffective disorder; SGAs, second-generation antipsychotics; SNP, single nucleotide polymorphism; SCZ, schizophrenia; TD, tardive dyskinesia.

Antipsychotic Serum (Plasma) Concentrations and Dosage

Cytochrome P450 (CYP) enzymes mediate the metabolism of various drugs, and for certain CYPs, the genotype affects serum (plasma) drug levels [7]. Previous studies have explored the role of pharmacokinetic (PK) genes for antipsychotic serum/plasma concentrations, particularly of the CYP genotype [8]. Four classes of CYP metabolizer profiles have been established: poor (PM), intermediate, normal, and ultrarapid metabolizers [9]. These phenotypes are based on the multiallelic nature of the CYP enzyme's genetic construct, which reflects several polymorphisms such as single nucleotide polymorphisms (SNPs) [8]. Notably, the FDA has included warnings for higher side effects at standard dosages for CYP2D6 PM; the details are described later. Nonetheless, the relationship between antipsychotic serum/plasma concentrations and the CYP genotypes continues to be investigated.

Three studies in this review reported a potential in­fluence of polymorphisms of CYP genotypes (i.e., the CYP1A2, 2C19, 2D6, and 3A4 genes) on PK profiles (i.e., the antipsychotic serum/plasma concentration) [7, 10, 11]. One study reported a significant association between olanzapine serum concentrations and the CYP1A2*1D and *1F polymorphisms [10], while 2 other studies also reported that polymorphisms in CYP2D6, CYP1A2, and DRD3 affected antipsychotic concentrations to some extent [7, 11]. The membrane transport protein P-glycoprotein, which is encoded by the ATP-binding cassette subfamily B member 1 (ABCB1) gene, helps clear antipsychotic medications across the blood-brain barrier [12]. One study investigated the influence of the ABCB1 rs1045642 polymorphism and the ATP-binding cassette subfamily C member 1 (ABCC1) rs212090 polymorphism on clozapine and norclozapine serum levels [13]. The combination of ABCB1 and ABCC1 homozygotes was associated with increased clozapine and norclozapine serum levels, although there were no significant associations between the ABCB1 and ABCC1 SNPs and serum concentrations.

In addition, antipsychotic dosage is affected by PK and pharmacodynamic (PD) factors. Three studies that investigated the influence of genetics on antipsychotic dosage were included in the review [14, 15, 16]. Hettige et al. [14, 17] reported a significant association between higher antipsychotic dosage and the γ-aminobutyric acid type A receptor β1 subunit (GABRB1) gene polymorphisms rs16860087 and rs4627835, although the authors were unsuccessful in reproducing the results of their previous study. However, the other 2 studies [15, 16] (using a genome-wide association approach) reported negative findings. One of the 2 studies investigated the association between antipsychotic dosage and polygenic risk scores in schizophrenia derived from significant risk loci identified by the Psychiatric Genomics Consortium (PGC2) but found no association between them [15]. Given that antipsychotic dosage can be influenced by several factors such as symptom severity and duration of illness, further research on this topic will be needed.

Antipsychotic Response

Response to antipsychotics is a complex phenotype involving genetic and clinical factors such as symptom severity and adherence level. Despite this challenging issue, various genetic variants related to PK and PD have been investigated in association with the response to antipsychotics.

Most studies included in this review focused on genetic polymorphisms, associated with response to antipsychotics, and how these polymorphisms related to clinical symptom improvement in patients with schizophrenia (e.g., a reduction in scores in the Brief Psychiatric Rating Scale [18] or the Positive and Negative Syndrome Scale [PANSS] [19]).

PK CYP450 and ABCB1 Genes

Antipsychotic drugs are primarily metabolized by CYP2D6, CYP3A4, and CYP1A2, and approximately 40, 23, and 18% of antipsychotics comprise major substrates for CYP2D6, CYP3A4, and CYP1A2, respectively [20]. Numerous studies have investigated the association between CYP variants and response to antipsychotics [8]. However, most have resulted in negative findings [8]. In the current review, 2 studies reported significant associations between antipsychotic response and the CYP3A43 rs680055 and CYP2D6 rs3892097 polymorphisms [21, 22]. Although another study found that CYP2C19 rs4986893 and CYP2D6 rs1135840 were associated with antipsychotic response, the associations did not remain significant after correction for multiple testing [22, 23].

In addition to the CYP enzymes, common polymorphisms of the P-glycoprotein-coding gene (ABCB1) have been associated with antipsychotic response. Previous studies investigating the rs1045642 (C3435T), rs2032582 (G2677T/A), and rs1128503 (C1236T) polymorphisms and their association with antipsychotic response are summarized elsewhere; the findings in this area of research are still inconsistent [12]. The current review includes 3 studies that investigated the association between polymorphisms in ABCB1 and response to antipsychotics. Of these, 1 study reported positive findings for the rs2032582 polymorphism, although the association did not remain significant after correction for multiple testing [23]. The other studies reported negative findings regarding the rs1045642 and rs2032582 polymorphisms, although a combination of a loss-of-function CYP2D6 allele and the TT genotype of ABCB1 rs2032582 was associated with poor response to antipsychotic treatment in one of those 2 studies [24, 25]. The current review includes several studies suggesting that response to antipsychotics is influenced by CYP genetic variants and ABCB1. However, this conclusion is limited by several factors such as heterogeneous ethnicity, medication, and study duration. Therefore, the association between PK gene variants and antipsychotic responses remains controversial, and further investigation is required.

Dopaminergic System Genes

Several studies investigated PD-related genes and treatment responses, particularly dopamine receptor D2 (DRD2), which plays a critical role in antipsychotic treatment. DRD2 antagonism is a common mechanism of antipsychotic action and is considered necessary for antipsychotic efficacy [26]. Accordingly, both DRD2 and D2-like receptor genes, including DRD3 and DRD4, have been extensively investigated as candidate genes that influence antipsychotic responses [27, 28]. We identified 7 studies that investigated the association between polymorphisms of the DRD2 gene and response to antipsychotics [21, 29, 30, 31, 32, 33, 34], where three polymorphisms of DRD2 (rs180498, rs2514218, and rs1079597) were significantly associated with treatment response [21, 30, 31, 32]. In particular rs2514218, which is located 47-kb upstream of the DRD2 gene, was previously reported as one of the genome-wide significant SNPs associated with risk of schizophrenia [35]. Further, it was associated with response to antipsychotics such as clozapine and risperidone in independent samples [31].

In addition, Blasi et al. [33] reported that a combination of the DRD2 rs1076560 and serotonin 2A receptor gene (HTR2A) rs6314 polymorphisms affected the response to antipsychotic treatment. Although a previous meta-analysis reported an association of DRD2 rs1799732 (−141C Ins/Del) with antipsychotic treatment response, no statistically significant associations were found in 2 studies included in this review [29, 34]. The association of DRD3 rs6280 (Ser9Gly) with antipsychotic responses has been extensively investigated [36]. One study included in this review reported a significant association between DRD3 rs6280 (Ser9Gly) and response to quetiapine [23]. A previous meta-analysis showed a nonsignificant trend toward lower response in Ser allele carriers [27]. Although DRD3 may theoretically affect antipsychotic responses via a high affinity of antipsychotics for the D3 receptor, empirical research findings remain inconsistent [36]. In contrast, 3 studies included in this review reported no significant associations of DRD1 rs5326, rs4867798, rs4532, and rs686, DRD3 rs6280, and DRD4 rs1800955 and rs4646984 with response to antipsychotics [25, 29, 37]. Similarly, a recent meta-analysis also showed no significant association between the DRD1 rs4532 polymorphism and response to antipsychotics, including cloza­pine [38].

COMT Gene

In addition, catechol-O-methyltransferase (COMT), which is another dopamine pathway-related gene, has been investigated. The COMT gene is located within the 22q11 chromosomal locus, which is involved in schizophrenia susceptibility [39]. The COMT enzyme is involved in dopamine degradation [40], making the COMT gene a candidate gene for an association with antipsychotic response. In this review, 6 of 9 studies reported associations of polymorphisms of the COMT gene (including marker rs4680) with improvement in the response to treatment by antipsychotics, including clozapine [23, 41, 42, 43, 44, 45]. Furthermore, a recent meta-analysis also showed that the COMT Val158Met (rs4680) polymorphism was significantly associated with response to antipsychotics [46]. These findings suggest that COMT gene variants, particularly COMT Val158Met (rs4680), are associated with antipsychotic response. However, the role of Val158Met polymorphism in antipsychotic treatment regulation is yet to be entirely elucidated [47].

Serotonergic System Genes

Most second-generation antipsychotics display a high affinity for serotonin receptors, which is considered as contributing to antipsychotic response [48]. Accordingly, several serotonin pathway-associated genes have been studied. Three studies in this review reported that the serotonin 1A receptor (HTR1A) polymorphism rs6295 was significantly associated with improvement in clinical symptoms [45, 49, 50]. Takekita et al. [49] indicated that the HTR1A polymorphism rs1364043 and the rs10042486-rs6295-rs1364043 haplotype might influence negative symptoms on the PANSS. A recent meta-analysis by Takekita et al. [51] showed that the HTR1A rs6295 polymorphism might be associated with improvement of negative symptoms but not with overall or positive symptoms. However, given the relatively small number of studies included in the analysis (n = 10) and the heterogeneity of antipsychotics, further studies using larger sample populations and homogeneous treatments are required to confirm this effect. It is thought that HTR2A contributes to the pathophysiology of hallucinations, and the receptor has been a major target among many second-generation antipsychotics [52]. Two of the 3 studies identified in this review indicated the impact of the HTR2A polymorphism rs6314 on antipsychotic treatment response modulation [21, 33, 42].

Associations of the HTR2C polymorphisms rs1328685, rs643627, rs498177, rs3813929, and rs1414334 with response to antipsychotics were also found [23, 42]. In contrast, the serotonin 7 receptor (HTR7) polymorphisms rs12412496, rs7916403, and rs1935349 did not appear to improve antipsychotic treatments [53].

Other Genes

Several other candidate genes, including glutamate-related genes, are also identified in this review (Table 2) [10, 23, 25, 34, 43, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66]. For example, Stevenson et al. [67] examined the association between glutamate gene polymorphisms and treatment response to risperidone in patients with first-episode psychosis (n = 86). They found that several SNPs were associated with antipsychotic treatment response; of these, the type-7 metabotropic glutamate receptor (GRM7) polymorphism rs2069062 showed the most robust finding [67].

Similarly, GRM7 rs2133450 was significantly associated with Emsley's positive domain derived from the PANSS in a genome-wide association study (GWAS), using a sample of patients treated with risperidone [68]. As for other genes, synaptosomal-associated protein 25 kDa (SNAP25) rs8636 and ankyrin repeat and sterile alpha motif domain-containing protein 1B (ANKS1B) rs7968606 were significantly associated with response to amisulpride [56, 69]. The brain-derived neurotrophic factor (BDNF) Val66Met (rs6265) polymorphism was not associated with response to antipsychotics in a recent meta-analysis that included 9 studies with a total of 2,461 patients treated with antipsychotics [70].

Genome-Wide Association Studies

An alternative to the candidate gene approach is to use GWAS, which is characterized as a hypothesis-free approach [71]. To our knowledge, the first GWAS investigating antipsychotic response was performed in the context of a phase III clinical trial of iloperidone, published in 2009 [72]. Subsequently, several GWAS on antipsychotic response have been conducted [73, 74, 75, 76]. In the current review, we found 9 studies that used this approach [67, 68, 77, 78, 79, 80, 81, 82]. The following gene polymorphisms were significantly associated with treatment response: rs72790443 in multiple EGF-like domains 10 (MEGF10); rs1471786 in solute carrier family 1 member 1 (SLC1A1); rs9291547 in protocadherin 7 (PCDH7); rs12711680 in contactin-associated protein-like 5 (CNTNAP5); rs6444970 in TRAF2 and NCK-interacting kinase (TNIK); rs2133450, rs2069062, and rs2014195 in GRM7; rs9307122 and rs1875705 in glutamate ionotropic receptor delta type subunit 2 (GRID2); rs3129996 in protein phosphatase 1 regulatory subunit 18 (PPP1R18); and rs6435681 in erb-b2 receptor tyrosine kinase 4 (ERBB4) [67, 68, 77, 81, 82, 83]. Among these studies, the study by Yu et al. [77] has one of the largest sample sizes reported so far (n = 2,413 in the discovery cohort and n = 1,379 in the replication sample). They found five novel genome-wide significant loci associated with treatment response in samples of Han Chinese ancestry (i.e., rs72790443 in MEGF10, rs1471786 in SLC1A1, rs9291547 in PCDH7, rs12711680 in CNTNAP5, and rs6444970 in TNIK). Furthermore, three additional loci were associated with drug-specific treatment responses (rs2239063 in CANCA1C for olanzapine, rs16921385 in SLC1A1 for risperidone, and rs17022006 in CNTN4 for aripiprazole). Although several factors such as duration of illness, duration of treatment, and concomitant therapy should be considered as covariates and validation studies in other ethnic populations are needed, the genes identified are clinically relevant and the findings can provide novel insights into the underlying mechanisms of antipsychotic action [84].

In addition, Li et al. [78] reported that common genetic variants related to synaptic adhesion complexes, scaffolding, and the alternative splicing regulator were associated with treatment response to lurasidone, although their findings were not statistically significant after correction for multiple testing. Ovenden et al. [79] found tentative associations between response to treatment and the mannosidase beta (MANBA), collagen type IX alpha 2 chain (COL9A2), and nuclear factor kappa B subunit 1 (NFKB1) genes.

Whole-Exome Sequencing

Recently, the rapid progress of next-generation sequencing, also called massively parallel sequencing, has led to revolutionary changes in medical genomics, including the field of psychiatry [85]. This method enables the sequencing of the whole genomes or exomes [85]. In the first study using exome sequencing to examine the pharmacogenomics of antipsychotic response, Drögemöller et al. [86] sequenced 11 South African patients with first-episode schizophrenia to identify genetic traits related to antipsychotic response. In the current review, we found a whole-exome sequencing study by the same group [83]. They identified two novel variants that were significantly associated with antipsychotic treatment response in two independent first-episode schizophrenia cohorts: rs13025959 in myosin VIIB (MYO7B) and rs10380 in 5-methyltetrahydrofolate-homocysteine methyltransferase reductase (MTRR). Although these new findings provide valuable information regarding future pharmacogenomic antipsychotic studies, further research will be needed.

Adverse Effects of Antipsychotics

Four main categories of antipsychotic-induced adverse effects were identified: (1) metabolic dysregulation, such as AIWG and metabolic syndrome; (2) movement disorders, including extrapyramidal symptoms (EPS), tardive dyskinesia (TD), and restless legs syndrome; (3) hormonal abnormalities, such as hyperprolactinemia; and (4) clozapine-induced agranulocytosis/granulocytopenia (CIAG).

AIWG and Metabolic Syndrome

AIWG is a common side effect in patients treated with antipsychotics, coinciding with metabolic dysregulation and heritability [87]. Although the mechanisms of AIWG are not fully understood, various genes appear to contribute to symptom onset (e.g., genes related to antipsychotic metabolism, neurotransmitter systems, and neuroendocrine systems) [88].

Twenty-eight of the studies in this review investigated the association between genetic factors and AIWG and metabolic dysregulation (Table 3). Regarding genes related to antipsychotic metabolism, Czerwensky et al. [10] found no significant association between AIWG and CYP1A2*1D and *1F polymorphisms. The ABCB1 rs1045642 and ABCC1 rs212090 polymorphisms were associated with AIWG in male patients treated with clozapine, although no significant associations were found in the total sample [13].

As for neurotransmitter systems, serotonin receptors influence central pathways affecting satiety and hunger [88]. Of the serotonin receptor genes, HTR2C has been extensively studied in association with AIWG, and the −759C/T polymorphism of HTR2C has been targeted in previous studies. One study included in this review replicated an association of the −759C/T polymorphism of HTR2C with AIWG [89]. Although another study produced negative findings, the authors found a significant association between insulinemia and T allele carriers [90]. A recent meta-analysis that included papers up until the end of 2014 reported 13 SNPs from nine genes being significantly associated with AIWG, including the −759C/T polymorphism of HTR2C [91]. In contrast, the rs1414334 polymorphism of HTR2C and the studied polymorphisms of HTR3A and HTR3B were not associated with AIWG and metabolic dysregulation [92, 93, 94]. The dopamine system also appears to be associated with AIWG and metabolic dysregulation [88].

BDNF is a neurotrophic factor that plays an important role in neurogenesis, neuronal survival, and synaptic plasticity [95]. Evidence exists to indicate that BDNF contributes to food intake and body weight control [95]. Although researchers continue to examine the BDNF Val66Met (rs6265) polymorphism and its potential association with AIWG, the results are still inconsistent [96, 97, 98]. Two studies included in this review reported signi­ficant associations between AIWG and the BDNF Met66Met polymorphism [99, 100]. Furthermore, the recent meta-analysis mentioned above [91] also showed a significant association between the BDNF polymorphism and AIWG.

Leptin is an adipocyte hormone that acts on the hypothalamus to regulate appetite and energy expenditure, which makes it a natural candidate for genetic AIWG studies. In particular, the −2548A/G (rs7799039) polymorphism of the LEP gene has been investigated in several studies [92]. However, the association between the −2548A/G polymorphism and AIWG remains inconclusive. In the current review, 1 study reported no significant association [92].

Antipsychotic-induced lipid biosynthesis may explain the metabolic side effects of antipsychotics [101]. Le Hellard et al. [102] investigated the association between AIWG and five major genes involved in the sterol regulatory element-binding protein (SREBP) activation of fatty acids and cholesterol production (SREBF1, SREBF2, SREBP cleavage-activation protein [SCAP], insulin-induced gene 1 [INSIG1], and INSIG2). They found a significant association between three markers localized within or near INSIG2 (rs17587100, rs17047764, and rs10490624) and AIWG. In addition, nominally significant associations with AIWG were found in INSIG1 (rs13223383), SREBF2 (rs4822064), and SCAP (rs12490383). The following gene polymorphisms were significantly associated with AIWG or the metabolic syndrome in this review: rs11654081 in SREBF1; rs2267443 and rs1052717 in SREBF2; and rs12151787, rs1049626, and rs17047733 in INSIG2 [103, 104, 105]. Taken together, these genes might enhance the risk of antipsychotic- induced metabolic dysregulation, although these mixed findings warrant further investigation.

The mitochondria play a key role in energy metabolism, and mitochondrial dysfunction contributes to metabolic disorders [106]. Thus, the mitochondrial system has become an interesting target for AIWG studies, although there have not been many studies investigating mitochondrial genetic variance in AIWG; Gonçalves et al. [107] reported an association between the mitochondrial NADH dehydrogenase (ubiquinone) Fe-S protein 1 (NDUFS1) gene and AIWG. Translocator protein 18 kDa (TSPO) is also a mitochondrial gene that may regulate weight through its effects on mitochondrial metabolism [108]. One study included in this review reported a nominal association between AIWG and the TSPO rs6971 polymorphism in two independent samples [66]. More recently, Mittal et al. [109] examined associations of variants in nuclear-encoded mitochondrial genes and mitochondrial DNA with AIWG. They identified three nuclear-encoded mitochondrial genes conferring a risk for AIWG. These findings suggest that mitochondrial genes have a significant role in AIWG, although replication studies are needed with larger samples and/or other ethnic groups.

As for other genes, Brandl et al. [110] conducted a GWAS using the data set derived from the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) sample, selecting a well-characterized and homogeneous subsample of individuals of European ancestry. Although none of the SNPs were significantly associated with AIWG, there were nominal associations for rs9346455 upstream of opioid growth factor receptor-like 1 (OGFRL1) and rs1059778 in iron-sulfur cluster assembly (IBA57). Notably, rs9346455 showed a significant association with AIWG in an independent sample of Europeans patients (n = 86) [110]. Another GWAS of 534 Han Chinese patients with schizophrenia found significant associations with rs10977144 and rs10977154 in protein tyrosine phosphatase, receptor type D (PTPRD), and these results were further validated in an independent replication cohort (n = 547) [111]. Notably, a recent meta-analysis that included studies through the end of 2014 found that 13 SNPs from nine genes were significantly associated with AIWG, with the SNPs in adrenoreceptor alpha 2A (ADRA2A), DRD2, HTR2C, and melanocortin 4 receptor (MC4R) having the largest effect sizes [91]. Additional details are summarized in Table 2. The previous studies from 2010 to 2015, focusing on gene variants associated with AIWG, are summarized in a recent comprehensive review [87].

In summary, several genes and polymorphisms have been studied in relation to AIWG with some findings showing independent replications. Nevertheless, considering that AIWG is a polygenic phenotype interacting with clinical and demographic factors, further studies are required to elaborate an algorithm for clinical practice [91].

Antipsychotic-Induced Movement Disorders

Antipsychotic drugs are associated with various movement disorders. Among them, TD is a severe and often irreversible side effect, characterized by involuntary trunk, limb, and orofacial muscle movements. Several studies using genome-wide association and candidate gene approaches have been conducted to identify risk variants associated with TD development [112]. In the current review, 12 studies reported associations between variants of related genes and EPS, TD, and restless legs syndrome, with 6 of them reporting TD [113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124]. A large number of studies have examined an association between CYP genes, including CYP2D6, and EPS/TD, and produced mixed findings [87]. One meta-analysis from 2005 suggested that loss-of-function alleles in CYP2D6 increased the risk of developing TD [125], whereas a recent study reported that CYP2D6 ultrarapid metabolizers were associated with an increased risk of TD [126]. Two studies included in this review found associations of polymorphic 1846G>A CYP2D6*4 with EPS and limb-trunk TD [116, 119]. Combined with the existing knowledge, it appears that CYP2D6 is a potential gene associated with the onset of TD [112]. In addition, CYP1A2 is involved in the metabolism of several antipsychotics, such as cloza­pine, olanzapine, and some first-generation antipsychotics [8]. Two studies included in this review reported an association between the CYP1A2*F polymorphic variant and TD [119, 122]. However, further studies using larger samples are required to confirm the association between CYP enzyme genes and TD, and to evaluate the clinical utility of these genes.

Neurotransmitter genes, including those within the dopamine, serotonin, γ-aminobutyric acid, and glutamate systems, may be linked to antipsychotic-induced movement disorders including TD [112]. For example, the Taq1A (rs1800497) polymorphism of the DRD2 gene [127], Ser9Gly (rs6280) of the DRD3 gene [128], and T102C (rs6313) of the HTR2A gene [129] have previously been investigated as risk variants for TD. Furthermore, vesicular monoamine transporter 2, which is coded by the solute carrier family 18 member A2 (SLC18A2) gene, has been implicated in TD [130, 131]. Zai et al. [131] found that the polymorphisms rs2015586, rs363390, rs363224, and rs14240 were associated with TD. Remarkably, these findings are consistent with clinical evidence demonstrating that a novel selective vesicular monoamine transporter 2 inhibitor (valbenazine) improves TD in patients with schizophrenia [132, 133]. In the current review, 1 study examined the association of 43 tag SNPs in five neurotransmitter genes with TD [118]. As a result, only rs1345423 in the glutamate receptor, ionotropic, N-methyl D-aspartate 2A (GRIN2A) gene showed a significant association with TD. A recent study focused on the influence of the neuregulin-1 (NGR1) and ERBB4 genes on TD [114], which help regulate N-methyl-D-aspartate and dopaminergic activity [134, 135]. They found a significant association between ERBB4 rs839523 and TD, although additional replication studies are needed to replicate this preliminary finding.

One study included in this review investigated an association between EPS and 202 SNPs in 31 neurotransmitter genes [117]. Four SNPs (rs9567733 [HTR2A], rs363341 [SLC18A2], rs1334802 [glutamate ionotropic receptor kainate type subunit 3 (GRIK3)], and rs1124491 [DRD2]) were significantly associated with EPS. Mas et al. [123] reported that the mTOR pathway was important for developing EPS. Using protein-protein interaction network analysis in 12 antipsychotic-naïve patients with first-episode psychosis, the same group showed that the NF-κB pathway (inflammatory response) and the mTOR pathway (lipid biosynthesis, insulin signaling, and autophagy) played a key role in EPS [121].

In summary, a large number of genes are potentially involved in antipsychotic-induced movement disorders. In the light of clinical evidence, SLC18A2 is a promising marker of TD risk. Nevertheless, further research and genetic validation studies are required to predict the risk for antipsychotic-induced movement disorders, including TD [112].

Antipsychotic-Induced Prolactin Increase

With regard to hormonal abnormality, hyperprolactinemia has been reported as a common adverse effect of antipsychotics [136]. Prolactin synthesis and secretion are inhibited by dopamine in the anterior pituitary gland through DRD2 activation [137]. Thus, an association between the DRD2 gene and hyperprolactinemia has been investigated [138]. A recent meta-analysis that included studies up until May 2015 showed that DRD2 Taq1A A1 carriers had significantly higher prolactin levels than A1 noncarriers among patients with schizophrenia, although further investigation will be needed due to several limitations, including a small sample size and heterogeneity of antipsychotics (n = 475; Hedges' g 0.250; 95% CI: 0.068–0.433; p = 0.007) [138]. This review included 3 original studies that focused on the association between genetic variants and hyperprolactinemia (or an increase in prolactin levels). It appears that rs1341239 in the prolactin (PRL) gene, rs569959 and rs17326429 in the HTR2C gene, and rs4680 in the COMT gene are significantly associated with hyperprolactinemia [44, 139, 140]. Thus, investigating the effect of combinations of several gene variants will be required to predict the risk for hyperprolactinemia.

Clozapine-Induced Agranulocytosis/Granulocytopenia

Clozapine is the only drug with proven efficacy in treatment-resistant schizophrenia. However, it has a risk of hematological side effects such as CIAG [141]. The human leukocyte antigen (HLA) genes have been implicated in clozapine-induced agranulocytosis (CIA) [142]. The first GWAS in relation to CIA, which was conducted by the Clozapine-Induced Agranulocytosis Consortium (CIAC), demonstrated that the HLA-DQB1 126Q and HLA-B 158T alleles were significantly associated with CIAG [143]. The current review includes 2 studies that examined the genetic factor for CIAG [144, 145]. One study reported a significant association of HLA-B*59: 01 − which was not compatible with the HLA-B 158T allele detected in the previous study − with CIAG in a Japanese sample [144]. The other study, using a genome-wide association approach, HLA allele imputation, exome array, and copy number variation, reported that clozapine- associated neutropenia was associated with rs149104283 located between SLCO1B3 and SLCO1B7 (solute carrier organic anion transporter family, member 1B3 and member 1B7) through a meta-analysis using the CIAC samples [145]. HLA-DQB1 (126Q) and HLA-B (158T), implicated in a previous study [143], could not be imputed with sufficient quality and thus were investigated in the study, while no imputed classic HLA or amino acid polymorphism was associated with clozapine-induced neutropenia. As for another finding, the association of HLA-DBQ1 6672G>C (rs113332494), which had been shown to be associated with the risk for CIA in another previous study [146], was replicated in this study.

In 2007, a first commercial test kit for CIA, PGxPredict: CLOZAPINE (Clinical Data, Inc., New Haven, CT, USA), which included the 6672G/C polymorphism in HLA-DQB1 for the detection of high-risk patients carrying the C allele, was launched, with a high specificity of 98.4% but a low sensitivity of 21.5% [47]. However, this test was discontinued due to lack of general interest at that time [147]. Further research focusing on multiple genes and polymorphisms will be needed to predict CIAG.

Expert Consensus Recommendations and FDA Drug Labeling

Currently, the US FDA provides information on pharmacogenomic biomarkers in their drug labeling for nine antipsychotics (i.e., aripiprazole, aripiprazole lauroxil, brexpiprazole, clozapine, iloperidone, perphenazine, pimozide, risperidone, and thioridazine) [148]. Seven out of nine refer to the CYP2D6 PM status, where dose adjustment recommendations are provided for the following antipsychotics: aripiprazole, aripiprazole lauroxil, brexpiprazole, clozapine, iloperidone, pimozide, and thioridazine. Similarly, the Pharmacogenomics Knowledgebase (PharmGKB) website lists ten antipsychotics where caution is advised for patients who are poor CYP2D6 metabolizers [149]. Drug labels with PGx information are provided for the following ten antipsychotics: aripiprazole, aripiprazole lauroxil, brexpiprazole, clozapine, iloperidone, olanzapine, perphenazine, pimozide, risperidone, and thioridazine.

The Clinical Pharmacogenetics Implementation Consortium (CPIC) [150], which was established in 2009 as a shared project of PharmGKB and the Pharmacogenomics Research Network (PGRN) [151], also provides useful gene-drug information for clinicians. This is available on the PharmGKB website, which assigns CPIC levels to genes and drugs according to the extent to which genetic information affects drug prescription. PharmGKB also provides levels of evidence for gene-drug associations. However, recommendations for antipsychotic medications have not yet been published. In contrast, the Royal Dutch Association for the Advancement of Pharmacy − Dutch Pharmacogenetics Working Group has also provided PGx drug dosing guidelines based on CYP2D6 genotypes for six antipsychotics: aripiprazole, clozapine, haloperidol, olanzapine, risperidone, and zuclopenthixol [152]. The guidelines are available on the PharmGKB website. An overview of the current recommendations is provided in Table 4.

Table 4.

Overview of recommendations by various agencies and expert groups for actionable gene-antipsychotic pairs

	Drug labels with PGx information [148, 149]				PGx drug dosing guidelines (related biomarker) [152]	CPIC level [150]	PharmGKB level of evidence [149]
	FDA	EMA	HCSC	PMDA
Aripiprazole	Actionable PGx	Actionable PGx	Actionable PGx	N/A	DPWG (CYP2D6)	B	CYP2D6 3
Aripiprazole lauroxil	Actionable PGx	N/A	N/A	N/A	N/A	N/A	N/A
Brexpiprazole	Actionable PGx	N/A	N/A	N/A	N/A	B	CYP2D6 N/A
Clozapine	Actionable PGx	N/A	N/A	N/A	DPWG (CYP2D6)	C D	CYP2D6 No literature support found for PGx HTR2C 2B
Haloperidol	N/A	N/A	N/A	N/A	DPWG (CYP2D6)	C	CYP2D6 3
Iloperidone	Actionable PGx	N/A	N/A	N/A	N/A	B/C	CYP2D6 3
Olanzapine	N/A	Informative PGx	N/A	N/A	DPWG (CYP2D6)	C D	CYP2D6 3 HTR2C 2B
Perphenazine	Actionable PGx	N/A	N/A	Actionable PGx	N/A	B/C	CYP2D6 N/A
Pimozide	Testing required	N/A	N/A	N/A	N/A	B	CYP2D6 4
Risperidone	Informative PGx	N/A	Informative PGx	N/A	DPWG (CYP2D6)	B C D	CYP2D6 2A DRD2 2A HTR2C 2B
Thioridazine	Actionable PGx	N/A	N/A	N/A	N/A	C	CYP2D6 3
Zuclopenthixol	N/A	N/A	N/A	N/A	DPWG (CYP2D6)	C	CYP2D6 3

The definition of PGx level is outlined below: “testing required” = stating or implying that some sort of genetic testing should be conducted before using this drug; “actionable PGx” = not discussing genetic testing for gene variants, but containing information regarding changes in efficacy, dosage, or toxicity due to such variants; “informative PGx” = mentioning a gene involvement in the metabolism or pharmacodynamics of the drug, but there is no information to suggest that variation in these genes leads to a different response. The definition of CPIC level is outlined as below: A = genetic information should be used to change prescription of the affected drug; B = genetic information could be used to change prescription of the affected drug; C = no actions for prescription are recommended, because the alternatives are unclear or evidence is weak; D = there are few data. PharmGKB level of evidence: “level 1A” and “level 1B” refer to high evidence, “level 2A” and “level 2B” refer to moderate evidence, and “level 3” refers to low evidence regarding an association of a variant-drug combination. CPIC, Clinical Pharmacogenetics Implementation Consortium; DPWG, Royal Dutch Association for the Advancement of Pharmacy − Pharmacogenetics Working Group; EMA, European Medicines Agency; FDA, Food and Drug Administration; HCSC, Health Canada (Santé Canada); N/A, not applicable; PGx, pharmacogenetics/pharmacogenomics; PharmGKB, Pharmacogenomics Knowledgebase; PMDA, Pharmaceuticals and Medical Devices Agency, Japan.

In summary, recommendations exist on how to use PK variants (such as CYP2D6) for some antipsychotics; however, no PD variants for antipsychotics are available for clinical practice.

Since the FDA first approved a PGx testing platform in 2004 (i.e., that of Roche Molecular Systems Inc. and Affymetrix Inc. [Pleasanton, CA, USA] for CYP2D6 and CYP2C19), several pharmacogenomic tests have become commercially available [153]. Several randomized clinical trials have previously evaluated the effectiveness of PGx testing for antidepressants and compared it with that for standard treatments (i.e., treatment as usual), and promising results regarding the clinical utility of PGx testing have been observed [154, 155, 156]. However, the precise clinical validity and utility of PGx tests regarding antipsychotics remain to be validated in randomized clinical trials. Therefore, randomized clinical trials investigating the effectiveness of pharmacogenomic tests for antipsychotics in clinical practice are required.

Conclusion

In this study, we reviewed recent developments regarding PGx in the treatment of schizophrenia. Numerous new studies have been published in the past years on antipsychotic serum/plasma concentrations, response to treatment, and adverse effects. While some studies could replicate previous findings, others could not, but many new associations have been reported which warrant further validation. Overall, the strongest associations are being noted of CYP2D6 metabolizer status and outcome with antipsychotic medications. The influence of CYP2D6 on antipsychotic dosage and the occurrence of side effects has also been integrated in recommendations provided by various expert groups and agencies such as the FDA. Not surprisingly, genetic tests are now being commercially offered across the world and have recently been reviewed for their clinical use [153]. In addition, some promising studies have detected associations between “older” candidate genes such as COMT and treatment response.

However, newer findings need to be considered as preliminary until further replication studies will have been conducted. Importantly, there is still a large heterogeneity across studies, possibly explaining some of the inconsistent findings. Sriretnakumar et al. [141] proposed five factors in addressing mixed findings: (1) heterogeneity of the study design, (2) adherence to treatment, (3) individual study-wide limitations, (4) population stratification, and (5) additional mechanisms beyond polymorphic DNA sequence effects. Although these authors particularly focused on the field of clozapine pharmacogenetics in patients with schizophrenia, their suggestions may be valid for the overall field of PGx regarding the response to antipsychotics and adverse effects in patients with schizophrenia.

In addition to the traditional candidate gene approach, new methodologies including GWAS, whole-exome sequencing, and gene-gene interaction have been adopted in PGx research [157]. These studies have produced novel findings and keep the promise to develop PGx research, although further replication studies are needed in other ethnic populations. Moreover, collaborations with pooled samples using robust biostatistical strategies are strongly encouraged, similar to the efforts made by the PGC in the broader field of psychiatric genetics or by the Pharmacogenomics of Antipsychot ic-Induced Weight Gain Consortium [158] and the CRESTAR group for clozapine response [159] in psychiatric pharmacogenetics.

In conclusion, PGx has the potential for optimizing antipsychotic treatment through the prediction of clinical outcomes without the need for conventional “trial-and-error” approaches. However, further well-designed investigations (such as trials to create algorithms for use in clinical practice and replication studies in large, well-characterized samples) are needed.

Disclosure Statement

The authors declare no conflict of interest.

Author Contributions

K.Y. wrote the first draft of the manuscript, and both authors conducted the literature search and contributed to and approved the final manuscript.