This document discusses the genetic factors influencing the efficacy and side effects of antipsychotic medications in the treatment of schizophrenia and other psychotic disorders, highlighting the role of pharmacogenetics. It emphasizes that interindividual variability in drug responses necessitates predictive testing to personalize treatment, particularly focusing on various gene variants, including those related to drug metabolism enzymes like CYP2D6 and CYP2C19. Findings indicate significant connections between genetic polymorphisms and both therapeutic outcomes and adverse reactions, advocating for the integration of pharmacogenetic testing in clinical practice.

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Genetics of antipsychotic drug outcome and
implications for the clinician: into the limelight
Amtul H. Changasi, Tahireh A. Shams, Jennie G. Pouget & Daniel J. Müller
To cite this article: Amtul H. Changasi, Tahireh A. Shams, Jennie G. Pouget & Daniel J. Müller
(2014) Genetics of antipsychotic drug outcome and implications for the clinician: into the limelight,
Translational Developmental Psychiatry, 2:1, 24663, DOI: 10.3402/tdp.v2.24663
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2. REVIEW ARTICLE
Genetics of antipsychotic drug outcome and
implications for the clinician: into the limelight
Amtul H. Changasi$
, Tahireh A. Shams$
, Jennie G. Pouget and
Daniel J. Mu¨ ller*
Pharmacogenetics Research Clinic, Centre for Addiction and Mental Health, Toronto, ON,
Canada
Background and purpose: Antipsychotics (APs) are the primary method of treatment for schizophrenia and
other psychotic disorders. Unfortunately, lengthy trial-and-error approaches are typically required to find
the optimal medication and dosage due to a large interindividual variability with outcome to AP treatment.
The literature has shown abundant evidence for a genetic component in individuals’ responses to APs.
Pharmacogenetic studies analyze specific genetic markers and their association with symptom improvement
and occurrence of side effects with APs. This research aims to optimize AP drug treatment by usage of
predictive testing and to personalize medicine.
Recent findings: This review will highlight the most consistent findings in pharmacogenetics of APs and will
update the reader on the clinical implications. This will include how genetic variants modulate AP drug levels,
side effects, and therapeutic symptom improvement (i.e. response) to AP treatment.
Summary: Several promising findings were obtained implicating gene variants of the dopamine receptor genes
in addition to gene variants of serotonin receptors for response and common side effects. Notably, effect
sizes appear to be particularly high in the genetics of side effects compared to response. One example is
antipsychotic-induced weight gain where the leptin, HTR2C and in particular the melanocortin-4-receptor
(MC4R) genes have been implicated in weight gain in children and adolescents. Consistent findings were
also obtained for genes implicated in tardive dyskinesia and agranulocytosis. However, the most clinically
relevant findings pertain to genes involved in drug metabolism such as the CYP2D6 and CYP2C19 genes
which have been included in the first genetic test kits such as the Amplichip†
CYP450 Test and more recently
the DMETTM
Plus Panel, the GeneceptTM
Assay, the Genomas HILOmet PhyzioTypeTM
System, and the
GeneSight†
Test.
Keywords: pharmacogenetics; antipsychotics; response; side effects; CYP450
A Corrigendum has been published for this paper. Please see http://www.translationaldevelopmentalpsychiatry.net/
index.php/tdp/article/view/25715
Received: 15 April 2014; Revised: 9 June 2014; Accepted: 12 June 2014; Published: 18 July 2014
D
ue to a large interindividual variability with
response to psychotropic drugs, a lengthy trial-
and-error approach is typically required to find
the right medication and dosage. This variability results
from various factors such as age, gender, ethnicity, disease
symptoms, drugÁdrug interactions, and most importantly
genetics.
Friedrich Vogel coined the term pharmacogenetics in
1959, referring to interactions between the response to
drugs and genetics in an individual (1Á4). In particular,
pharmacogenetic research aims to identify specific genetic
markers and their association with treatment outcome
to drugs (5, 6). Pharmacogenetics bears the promise to
become a tool in psychiatry, used to tailor treatment to
an individual’s genetic make-up.
Several areas of research have now embraced pharma-
cogenetics as a way to improve treatment with medication.
There are many tests emerging in all fields of medicine
such as cardiology, pain management, cancer treatment,
and psychiatry (7, 8). Many efforts are currently being
$
These authors contributed equally to the work.
Translational
Developmental
Psychiatry
æ
Translational Developmental Psychiatry 2014. # 2014 Amtul H. Changasi et al. This is an Open Access article distributed under the terms of the Creative
Commons Attribution-Noncommercial 3.0 Unported License (http://creativecommons.org/licenses/by-nc/3.0/), permitting all non-commercial use, distribution,
and reproduction in any medium, provided the original work is properly cited.
1
Citation: Translational Developmental Psychiatry 2014, 2: 24663 - http://dx.doi.org/10.3402/tdp.v2.24663
(page number not for citation purpose)

3. made to integrate pharmacogenetic testing into the clinical
setting to improve patient care as well as work toward
personalized medicine.
Pharmacology usually differentiates between pharma-
cokinetics and pharmacodynamics. Pharmacokinetics
is the study of how drugs are metabolized (including
degradation and excretion) in various body compart-
ments. Pharmacokinetic effects include genetic variations
that lead to differences in the activity of drug-metabolizing
enzymes. This can influence the availability and plasma
concentrations of antipsychotic drugs in the brain,
and affect the synthesis of active metabolites (9). In
contrast, pharmacodynamics is the course of action a
drug exerts on various organs. This includes how gene
variants may affect the interindividual variability seen
in outcome to medications (9).
Antipsychotics (APs) are the most used class of
medications for schizophrenia and related psychotic dis-
orders. However, complete therapeutic benefit may not
always be achieved in patients. AP use can frequently
result in adverse reactions such as weight gain, leading
to metabolic syndrome. Such side effects increase dis-
continuation and relapse rates (1, 10). Response to APs
depends partially on demographic and clinical factors (1).
However, the literature has shown substantial evidence
for a genetic component in individuals’ outcomes to APs
which include variation in drug metabolism and side
effects (11).
A large number of genes are involved in AP treatment
outcome, and gene variants (or polymorphisms) can be
studied for their potential impact on this outcome. Most
genes will typically carry a variable amount of poly-
morphisms that can be investigated and analyzed for their
impact on drug treatment outcome. Such polymorphisms
may result in a lack of gene expression, altered levels and
functions of gene expression, which also have an impact
on drug metabolism in the organism (1).
This review will highlight the most important findings
in pharmacogenetics of APs and will also update the
reader on the clinical implications. This will include exam-
ples of how genetic variants modulate AP drug levels,
side effects, and therapeutic symptom improvement (i.e.
response) to AP treatment.
Methods
We reviewed published review articles and meta-analyses
on pharmacogenetic studies on APs published using Med-
line database (http://www.ncbi.nlm.nih.gov/pubmed/) and
OVID (psycINFO) from 2008 to 2013 with an emphasis
on studies published between 2012 and 2013. Selected key
words were ‘pharmacogenetics’, ‘pharmacogenetic test-
ing’, ‘response’, ‘side effects’, ‘pharmacokinetics’, ‘phar-
macodynamics’, ‘APs’, ‘CYP alleles’, ‘CYP450’, ‘weight
gain’, ‘tardive dyskinesia (TD)’, ‘agranulocytosis’, ‘sexual
dysfunction’. In addition, we included highly relevant
original articles recently published. We excluded letters to
the editor and editorials as well as conference abstracts. In
total, we reviewed 41 studies. Our review article empha-
sizes findings that have been consistently replicated in
independent samples, or were observed using larger and
well-characterized samples (e.g. CATIE sample), or were
found through GWAS or any combinations of the above.
Results
Pharmacokinetics
The liver cytochrome P450 (CYP450) enzymes are
involved in the metabolism of various psychotropic drugs
(12) and are involved in metabolic phase I oxidative
reactions (13). The enzymes which are most critically
involved in the metabolism of psychotropic medications
are CYP2D6 and CYP2C19 and to a lesser extent
CYP1A2, CYP2C9, CYP3A4, and CYP3A5 (13). Due
to their role in the metabolism of psychotropic medi-
cations, for which there are interindividual differences,
the CYP450 enzymes are extensively studied.
As for CYP2D6 and CYP2C19, individuals are
considered to be normal or extensive metabolizers (EM)
if they have two functional alleles. Those who carry one
normal and one non-functional allele are categorized
as intermediate metabolizers (IM); those with two non-
functional alleles are known as poor metabolizers (PM).
Finally, individuals with duplicate copies of alleles are
categorized as ultra-rapid metabolizers (UM) (11).
As for AP drugs metabolized by CYP2D6 and
CYP2C19 enzymes, individuals with the PM phenotype
may suffer from dose-dependent complications due to
increased, and potentially toxic, plasma concentration (1).
Those with IM phenotypes are also likely to have
increased plasma levels compared to the EMs. The UM
phenotypes can result in sub-therapeutic drug levels when
standard doses of medications are given, requiring in-
creased dosage in affected individuals (1).
Knowledge of an individual’s metabolizer status of
these genes may have potential benefits in order to
optimize drug treatment by reducing the likelihood of
side effects or therapeutic failure. By knowing the meta-
bolizer status, dose adjustments can be made or alternative
medications can be selected (11).
Of note, frequencies for PM, IM, EM, and UM vary
considerably between ethnic groups. For example, fre-
quencies for CYP2D6 UMs are much higher in Africans
(11, 14) (see Table 1).
Furthermore, both enzymes can be inhibited or
induced by drugs and diet and create phenocopies (11).
An example of a phenocopy would be the conversion of
a CYP2D6 EM to a CYP2D6 PM after exposure to a
potent CYP2D6 inhibitor such as paroxetine (19).
AP drugs such as aripiprazole, haloperidol, perphena-
zine, risperidone, thioridazine, and zuclopenthixol are
Amtul H. Changasi et al.
2(page number not for citation purpose)
Citation: Translational Developmental Psychiatry 2014, 2: 24663 - http://dx.doi.org/10.3402/tdp.v2.24663

4. metabolized to a various degree by CYP2D6. Other most
commonly prescribed APs such as olanzapine and clo-
zapine are metabolized by CYP1A2 (20). For additional
information on AP and antidepressant medications meta-
bolized by the CYP450 enzymes, please refer to the Phar-
macogenomics Knowledgebase (https://www.pharmgkb.
org/) and the CYP450 Drug Interaction Table by the
Indiana University Department of Clinical Pharmacology
(http://medicine.iupui.edu/clinpharm/ddis/main-table/).
More details on this topic can also be found in two reviews
published by Ravyn et al. (1) and Altar et al. (5).
CYP2D6
This is a highly polymorphic enzyme, with more than
100 described allelic variants (3, 15). Variation occurs
through single nucleotide polymorphisms (SNPs); a
single nucleotide variation in the DNA sequence varies
between person to person; for example, one individual
can have the ‘A’ nucleotide while another person can
have the ‘G’ nucleotide on the same locus (21), as well
as from copy number variations (CNVs; i.e. duplications
of the gene) (22). These variations can lead to loss-
of-function, decreased activity, or increased enzymatic
activity through gene duplications (3).
Genotyping and defining metabolizer status for
CYP2D6 can be challenging because of the vast amounts
of allelic variations and their interactions. A common
limitation is that rare and population-specific variations
are typically not tested which could impact the results of
published articles. Another limitation with respect to
gene duplication is that they are not usually determined
quantitatively but rather qualitatively (3).
There are a few examples which show how pharmaco-
genetic testing could have prevented critical situations: A
9-year-old boy, diagnosed with encephalopathy second-
ary to fetal alcohol syndrome, attention-deficit hyper-
activity disorder, and Tourette’s disorder, died due to
accidental toxic plasma levels of fluoxetine which also
likely resulted from his previously unknown CYP2D6
PM status. Adopted when he was 5 years old, he was
diagnosed with physical aggressiveness, negativity, and
impulsivity. He also had a history of absence seizures.
Clonidine 0.6 mg/day (in divided doses) was initially
started to treat his tics, and the dose was increased over a
year to 0.9 mg/day. At age 6, he was initially started on
treatment with fluoxetine at 5 mg/day, and the dose was
gradually increased to a high dose of 100 mg by the time
he was 8 years old. In addition, he was taking clonidine
0.9 mg/day and methylphenidate 60 mg/day concurrently.
This particular constellation of type and dose of drugs
and his PM status had likely exacerbated the fluoxetine
toxicity which was revealed at the autopsy where toxic
fluoxetine levels were noted. Fluoxetine and norfluox-
etine blood plasma levels were 21 mg/mL, substantially
higher concentrations than what is normally seen in
adults who are taking fluoxetine (with levels typically
below 5 mg/mL) (23).
An infant’s death was due to opioid toxicity from
morphine formation because his mother was taking the
prodrug codeine. CYP2D6 is responsible for the conver-
sion of codeine to morphine. The mother’s UM status
caused an increase in morphine formation leading to the
neonate’s death (24).
CYP2C19
Although CYP2C19 is not primarily involved in the
metabolism of APs, it is an important enzyme involved in
the metabolism of antidepressants and the antiplatelet
drug, clopidogrel (16, 25, 26). Given that it is included
in various commercially available genetic test kits, its
genetic architecture is briefly discussed. CYP2C19 is a
fairly polymorphic enzyme, with more than 30 known
allelic variants (www.cypalleles.ki.se/cyp2c19.htm). When
a drugs’ primary metabolism pathway is non-functional
(i.e. CYP2D6 PM), CYP2C19 plays a secondary role in
its metabolism (15). Similar to CYP2D6, phenotypes
of CYP2C19 can be categorized into the UM, IM, EM,
and PM criteria (25). UMs have been found to be non-
responders to standard doses of medication and PMs
endorse more side effects. IMs can be given a lower dose
of the CYP2C19 substrate medication (15).
CYP2C19*2 is the dominant defective allele (27).
The distribution of common variant alleles of CYP2C19
has been found to vary among different ethnic groups.
The PM phenotype is more prevalent in the Asian popu-
lation and less in Caucasian and African populations
(please see below) (17). The PM phenotype of CYP2C19 is
inherited as an autosomal recessive trait (28, 29) (Table 2).
CYP1A2
The CYP1A2 allele has 41 described variants (www.
cypalleles.ki.se/cyp1a2.htm) and this enzyme can be
induced by various other drugs and substances. This can
include smoking (the most common CYP1A2 inducer),
insulin, modafinil, nafcillin, omeprazole, cruciferous
vegetables (15), and oral contraceptives (32). The polycy-
clic aromatic hydrocarbons found in tobacco smoke
induces CYP1A2 activity (33Á36), which results in de-
creased plasma concentration of the drugs metabolized by
CYP1A2 (34). Individuals who quit smoking need to be
informed that their CYP1A2 activity decreases which then
increases the risk for potential side effects (34, 37).
Two well-studied CYP1A2 alleles are CYP1A2*1A and
CYP1A2*1F. The *1A allele is not easily induced whereas
the *1F allele is. With the absence of an inducer, both the
alleles are similar. When an inducer is present, the *1F
activity (and *1C activity in people of European ances-
try) increases. Individuals who begin to smoke and take a
CYP1A2 substrate medication while having the *1F/*1F
genotype are at an increased risk for a loss of efficacy of
that medication (15). There is a marked ethnic difference
Genetics of antipsychotic drug outcome and clinical implications
Citation: Translational Developmental Psychiatry 2014, 2: 24663 - http://dx.doi.org/10.3402/tdp.v2.24663 3(page number not for citation purpose)

5. in this CYP enzyme activity; Swedes had a 1.54-fold
higher CYP1A2 activity than Koreans (27, 38). When
compared to the Caucasian population, both Asian and
African populations have lower CYP1A2 activities (39).
Fourteen percent of Japanese people and 5% of Chinese
people were found to be PMs (17, 27).
Few studies have investigated the role of CYP1A2
and response. A study by Laika et al. found that
CYP1A2*1F/*1F genotype was associated with plasma
levels for olanzapine (40); however, an association with
therapeutic response has not yet been established (1).
Smoking status was considered in the study; out of a
total of 124 participants, 44 were smokers. For the
olanzapine serum cohort, there were 73 participants out
of whom 30 were smokers (40).
CYP2C9
CYP2C9 is also fairly polymorphic with more than 50
allelic variants (www.cypalleles.ki.se/cyp2c9.htm). CYP2C9
plays an important role in drug clearance if the primary
metabolic pathway is non-functional. It also has a role
to code an enzyme allowing for the oxidation of appro-
ximately 100 medications (15). It is estimated that
for drugs requiring phase I metabolism, CYP2C9 is
responsible for approximately 15Á20% of metabolic clear-
ance (41Á43). CYP2C9 only plays a minor role for APs
while it is involved in the metabolism of various anti-
depressants and S-warfarin. Genetic variants which cause
changes in metabolic activity can lead to pathogenesis
due to adverse drug reactions. This can be seen with
patients who have low enzyme activity for CYP2C9
substrates (41, 44). Reduced CYP2C9 activity is caused
by the CYP2C9*2 and CYP2C9*3 polymorphisms (45),
These allelic variations are not common in East Asian,
African-American, and Ethiopian populations (45, 46);
CYP2C9*2 is absent in the East Asian population and is
present in 3.2% of the African American and Ethiopian
populations. CYP2C9*2 is present in 8Á19% of the
Table 1. Variability in the distribution of genes (allele frequencies) in different ethnicities$
(15, 16)
Africans Asians European South American Indians
CYP2D6*1 (EM) 55% (Ethiopian)
52% (Sub-Saharan
African)
48% (Japanese) 37% (Northern
European)
73%
CYP2D6*3 (PM) B0.1% (Ethiopians)
B0.1% (Sub-Saharan
African)
B0.1%
(Japanese)
2% (Northern
European)
B0.1%
CYP2D6*4 (PM) 3% (Ethiopian)
2% (Sub-Saharan African)
B0.1% 19% (Northern
European)
3%
CYP2D6*10 (IM) 6% (African Americans;
Ethiopian)
4% (Sub-Saharan African)
39Á51% 1Á2% 1%
CYP2D6*17 (Altered affinity for
substrates of 2D6)
20Á35% (African
Americans)
B0.1%
(Japanese)
B0.1% (Northern
European)
B0.1%
CYP2D6*M X N$$
(Depending on the
allele, it represents an increased
function) (17)
1.0Á2.4% (African
Americans)
0.9Á16.0% (Black
Africans)
0.9Á1.3% (East
Asians)
0.7Á5.6%
(Caucasians)
Not determined (Native
Americans)
For determination of metabolizer status using *allele combinations, the reader is referred to comprehensive review articles such as that by
Mrazek (15).
$
The precise frequencies can differ in small communities due to their geographic locations (15, 18).
$$
XN refers to the number of gene copies; for example, CYP2D*1X2 refers to two copies of CYP2D6*1 (17).
Table 2. Distribution of common variant alleles of CYP2C19 (allele frequencies) (21, 30Á32)
Africans Asian Europeans (Caucasians) Native American
CYP2C19*2 (PM) 17% 18Á23% (Japanese) 2Á15% 12.0Á19.1
CYP2C19*3 (PM) 0.4% 5% 0.04% Not determined
Total PM status: 2Á5% Â25% 2Á5% 3.3Á11.65%
CYP2C19*17 (UM) 18% (Ethiopians) 1.3% (Japanese)
0.64% (Chinese)
18% (Swedes) Not determined
Amtul H. Changasi et al.
4(page number not for citation purpose)
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6. Caucasian population (46). The presence of CYP2C9*3
in East Asian populations (Koreans, Japanese, and
Chinese) range from 1.1 to 3.3%. In Africans, it is present
in 1.3% (for both African Americans and Ethiopians
combined). In contrast, CYP2C9*3 is present between 3.3
and 16.2% in the Caucasian population (46). Carrying two
non-functional CYP2C9 alleles can result in a risk
for serious side effects such as life threatening bleeding
episodes with warfarin and toxicity with phenytoin (47).
For those who are heterozygous for the CYP2C9*2
or CYP2C9*3 allele (i.e. *1/*2 or *1/*3), a 25% dose
reduction is suggested for the administration of phenytoin.
Those who are homozygous for the two alleles (i.e. *2/*2 or
*3/*3) require a 50% dose reduction for phenytoin (45, 48)
Likewise, a 50% reduction is also suggested for those who
have the *2/*3 allelic variation (48).
CYP3A4 and CYP3A5
CYP3A4 comprises more than 30% of hepatic enzymes
and for marketed drugs which rely on metabolic elimi-
nation, CYP3A4 is involved in the metabolism for over
half of them (49Á53). In people with reduced CYP1A2
activity, CYP3A4 is involved in clozapine metabolism
while CYP3A5 does not influence clozapine pharmaco-
kinetics (54). Based on in-vitro affinity constants, it has
been suggested that the role of CYP3A4 is relevant with
higher doses of clozapine (54, 55).
Structurally, CYP3A5 is similar to CYP3A4 but the
substrate selectivity of these proteins differ (51, 56Á58).
CYP3A5*1 is present in approximately 10Á20% of White-
European individuals (50) and is present in approxi-
mately 55% of African American individuals (51, 56, 59).
Apart from the liver, CYP3A5 is also distributed in
the intestine and kidneys (50, 60Á62). There are over
26 allelic variants (www.cypalleles.ki.se/cyp3a5.htm) for
CYP3A5. Protein expression and activity are affected by
genetic polymorphisms of CYP3A5 which may also affect
drug response (51, 56Á58). Those who are homozygous or
heterozygous for the CYP3A5*1 allele express CYP3A5
to normal levels while having the CYP3A5*3, *6, and *7
alleles result in diminished expression CYP3A5 (www.
cypalleles.ki.se/cyp3a5.htm.) (51, 56Á58, 63).
Linkage studies conducted in a Japanese population
demonstrated that three SNPs in CYP3A5 showed some
linkage with a SNP in CYP3A4 suggesting that CYP3A4
and CYP3A5 are within the same gene block (64).
CYP3A4 plays a major role in the metabolism of a
number of drugs, chemicals, and compounds. This is
mainly due to the relatively high abundance of CYP3A4
and the minor impact of genetic variants for this enzyme
(65).
Notably, for CYP3A43, a member of the same family
as CYP3A4, Bigos et al. found that marker rs472660
was associated with olanzapine clearance in African
Americans and where clearance was associated with
therapeutic response (66).
Pharmacodynamics
Response. There are some variants that have been shown
repeatedly to be associated with overall response to
treatment.
One of the most intensely studied genes is the DRD2
receptor gene due to its known role in the pathway
of many AP drugs, and in particular, for positive
symptoms (9). In addition, the dopamine D1, D3, D4,
and D5 receptor polymorphisms were also investigated.
Interesting findings were more recently reported for
the DRD1 rs4532 polymorphism, which showed an in-
creased risk for treatment resistance (67). As for the
DRD3 gene, a possible role was suggested for the Ser
allele of the Ser9Gly polymorphism (rs6280) to be
associated with poorer response to clozapine in a meta-
analysis by Hwang et al. (68). The DRD4 variants have
been found to have a minor contribution to clozapine
response using 18-item BPRS scale, while DRD5 showed
none (69). A study by Miura et al., investigated the
Taq1A polymorphism (rs1800497), in linkage disequili-
brium and related to the DRD2 receptor, in relation to
response to aripiprazole treatment, using the PANSS and
CGI scales. They found a non-significant trend that
carriers of the A1 allele responded better to aripiprazole
compared to non-carriers. They also found a significant
effect for response and genotype/response interaction
on the change of plasma levels of homovanillic acid
(pHVA) but not for the change of plasma levels of
3-methoxy-4hydroxyphenylglycol (pMHPG). This indi-
cates a possible, partial role for the Taq1A polymorphism
in response to aripiprazole (70). Two other previous
studies in 2008 both also had positive findings in rela-
tion to Taq1A and clinical response to aripiprazole using
the PANSS scale (71). In 2008, Ikeda et al. found that
two SNPs in DRD2 ((241A!G [rs1799978] and Taq1A
[rs1800497]) and two SNPs in AKT1 (AKT1-SNP1
[rs3803300] and AKT1-SNP5 [rs2494732]) were signifi-
cantly associated with response to risperidone, using the
PANSS scale (72).
The HTR2A gene is a target for atypical APs, making
it another candidate for pharmacogenetic testing (9).
Earlier studies have reported some interesting results
implicating serotonergic gene variants to AP response.
HTR2A gene polymorphisms have been shown to be
associated with hallucinations, overall treatment response
(73, 74) and in particular with negative symptom response
(75). Earlier studies also suggested the HTR2C receptor
was involved in response to AP treatment, given its role in
regulating the effect of the drug on cognitive functioning
(76). Consistent with this notion, a highly studied poly-
morphism of HTR2C, Cys23Ser (rs6318), has been found
to be associated with clozapine response, although most
Genetics of antipsychotic drug outcome and clinical implications
Citation: Translational Developmental Psychiatry 2014, 2: 24663 - http://dx.doi.org/10.3402/tdp.v2.24663 5(page number not for citation purpose)

7. studies were negative (77). In 2009, Wei et al. investigated
the HTR7 gene and response using the BPRS scale, but
found no significant association (78). Also in 2009,
Lavedan et al. reported results of a GWAS study showing
an association between iloperidone response (using the
PANSS scale) and the nudix (nucleoside diphosphate
linked moiety X)-type motif 9 pseudogene (NUDT9P1),
which is located approximately 200kb away from the
HTR7 gene. The NUDT9P1 gene could act as a remote
regulatory unit (79) on the HTR7 gene, where the
encoding receptor has shown high affinity for iloperidone
(80). Overall, dopamine and serotonin receptors are
strongly involved in AP mechanism of action and there
is moderate evidence that gene variants of these receptors
play a major role in response to APs.
More recent studies, including genome-wide ap-
proaches, have suggested other genes to be possibly
involved in therapeutic response to APs. The zinc finger
gene ZNF804A potentially plays a role in neurodevelop-
ment, similar to other zinc-finger domainÁcontaining
proteins, and has been suggested to be involved in sus-
ceptibility to schizophrenia and psychotic bipolar dis-
order, particularly the functional marker rs1344706
(81Á83). Furthermore, replication of this finding has
been successful (81, 84Á87). Zhang et al. reported that
Chinese T allele carriers showed significantly less symp-
tom improvement, using the PANSS scale, while being
treated with various SGAs (82). In contrast, Mo¨ssner
et al. reported that those individuals of European descent
who were homozygous for the A allele showed significantly
less symptom improvement in positive symptoms, based
on the PANSS scale (81).
Also of interest, the brain derived neurotrophic factor
gene (BDNF) has been reported to be associated with
treatment resistance in schizophrenic patients. Zai et al.
found that the rs11030104 marker and the Val66Met
marker (rs6265) were associated with AP response; fur-
thermore, the rs11030104 and Val66Met C-A haplotypes
were underrepresented in responders (assessed with the
BPRS scale) compared to non-responders (88). Further-
more, Zhang et al. found the rs11030104 marker and the
rs6265 marker along with the rs10501087 marker to be
significantly associated with treatment resistance (89).
Xu et al. reported that two haplotypes (230-bp/C-270/
rs6265G and 234-bp/C-270/rs6265A) were significantly
associated with response to risperidone based on BPRS
scores. Patients with the 230-bp allele of the (GT)n
polymorphism or the 230-bp/C-270/rs6265G haplotype
responded better to risperidone than those with other
alleles or haplotypes (90).
The ATP-Binding Cassette (ABCB1) gene has been
investigated in relation to response. ABCB1 functions as
an efflux transporter for some APs in the bloodÁbrain
barrier thus decreasing concentrations of APs in the
brain tissue (91). In their association study, Lee et al.
found that the markers rs7787082 and rs10248420 of
ABCB1 were significantly associated with response (using
the CGI scale) in a sample of Korean patients treated
with clozapine. Markers rs7787082 G and rs10248420
A alleles in ABCB1 were more frequently observed in
non-responders (92). A naturalistic study by Vijayan
et al. found that individuals with 3435CC (rs1045642)
and 1236CC (rs1128503) genotypes responded better to a
variety of APs, using the BPRS scale (93). Notably,
earlier monotherapy studies in other populations found
that individuals with the 3435TT genotype showed better
response to olanzapine (94), and those with the 1236TT
polymorphism showed better response to risperidone
(95). On the contrary, Crisafulli et al. did not observe
an association between ABCB1 and response in a Korean
population treated with a variety of APs using the PANSS
scale (96).
Souza et al. investigated several variants of the
neurexin 1 (NRXN1) gene with clozapine response.
They found a non-significant trend with the rs12467557
marker and association with clozapine response, using
the BPRS scale (97). In 2011, Lett et al. reported a
significant association between the rs1045881 marker of
NRXN1 and BPRS negative symptoms score (98).
Spellmann et al. found a significant association be-
tween a number of variants of the Homer homolog
1 gene (HOMER-1) and response to APs. The dendritic
HOMER-1 protein regulates group 1 metabotropic glu-
tamate receptor function and is therefore an excellent
candidate for pharmacogenetic studies. There were sev-
eral variants with a strong association, particularly with
the rs2290639 marker showing significant associations
between both PANSS baseline scores as well as at the
4 weeks of treatment mark (99).
Side effects. There are potentially serious adverse reac-
tions to treatment with APs. Typical side effects include
transient sedation, extrapyramidal symptoms, weight
gain, sexual side effects, and in rare cases agranulocytosis
depending on the type of AP drug (100).
Based on their side effect profile, APs were historically
classified into typical (or first generation) and atypical
(or second generation) APs. While all APs have antag-
onistic properties at the level of the dopamine D2 recep-
tor, typical APs are much more likely to induce motoric
side effects such as TD.
TD is a movement disorder which typically develops
after months or years of AP treatment which often persists
even after discontinuation of APs (101). Given the pro-
minent role of APs on dopaminergic receptors and the
role of the dopaminergic system in movement con-
trol, dopamine receptor genes have been extensively
investigated (102). Most promising findings include the
Taq1A polymorphism (rs6280) related to DRD2 and the
Ser9Gly polymorphism (rs1800497) of DRD3 (103).
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8. The Taq1A polymorphism (which was associated with
a lower density of D2 receptors in the brain in vitro)
(104, 105) is likely associated with TD as reported by three
different studies (106). The Gly variant of the Ser9Gly
polymorphism has been shown several times to be linked
to increased risk for TD (107). However, there have also
been negative findings in this area and thus more inves-
tigation is required.
There are numerous findings in regards to CYP2D6
metabolizer status and TD where the majority suggested
that increased or decreased CYP2D6 activity are asso-
ciated with the presence of TD (108Á111), although some
negative findings, most likely due to heterogeneous study
designs, were also reported (112).
Meta-analyses have found three other genes impli-
cated in TD: manganese superoxide dismutase (MnSOD),
cytochrome P450 1A2 (CYP1A2), and serotonin 2A
receptor (HTR2A) (113). It has also been proposed that
BDNF levels contribute to TD and that certain poly-
morphisms of BDNF may increase response to treat-
ment for TD using ginkgo biloba, a potent antioxidant
with neuroprotective effects mediated through enhanc-
ing BDNF levels (114). BDNF is a neuronal growth and
survival peptide that modulates a variety of processes in-
cluding regulation of the dopamine D3 receptor (DRD3)
and could thus be involved in TD through this mechanism
(75). The heparan sulfate proteoglycan 2 (HSPG2) gene
emerged as the top hit in a GWAS of TD screening by
Syu et al. (115) and was later replicated in a prospective
sample by Greenbaum et al. (116) but not in a study by
Bakker et al. (113).
Second-generation AP medications often induce a
large amount of weight gain (117). This increased weight
gain often leads to metabolic syndrome, which predis-
poses the patient to further conditions, such as diabetes
and cardiovascular disease.
Since atypical APs frequently act as antagonists at the
HTR2A receptor, this gene has been extensively investi-
gated for response and side effects (118). Ujike et al. reported
four gene variants to be associated with olanzapine-induced
weight gain, two of which were the 102T allele (rs6313) of
the HTR2A receptor, and the 23Cys allele (rs6318) of
the HTR2C receptor (119). However, there have also been
negative findings in this area. Mou et al., in 2005, reported
that the (1438G/A polymorphism (rs6311) of the HTR2A
gene was not associated with antipsychotic-induced weight
gain (AIWG) in Chinese Han patients (120).
The HTR2C receptor is one of the most highly studied in
relation to AIWG stemming from a study by Tecott et al. in
1995 that depicted HTR2C knockout mice overeating and
developing obesity (121, 122). Furthermore, a study by
Bonhaus et al. showed that HTR2C antagonists increase
food intake (123). In their review, Altar et al. reported
22 studies showing significant pharmacodynamic associa-
tion between HTR2C and weight gain (5). Recently,
promising findings surrounding obesity-related genes
have come in to play, such as the leptin and melanocortin
receptor 4 (MC4R) genes. The protein products of these
genes are influenced by APs, making them potential key
factors in AIWG (124). A GWAS has recently identified
marker rs489693, approx. 200 kb downstream of the
MC4R gene to be associated with AIWG (125). Given
that this finding was replicated across various samples in
different populations using different APs, a major role for
rs489693 is likely in AIWG (125Á127). The findings by
Nurmi et al. also indicated that the same gene variant
associated with AIWG in adults is implicated in AIWG in
children and adolescents as well (127). A study by Zai et al.
found that patients with a Val66Met G-A haplotype
(rs6265) of the BDNF gene (frequency 57%) were asso-
ciated with more pronounced weight gain compared with
patients taking clozapine orolanzapine (88). Given the role
of dopamine in motivational aspects related to rewarding
effects such as food intake, the dopamine receptors DRD1-
DRD5 were investigated in one study suggesting an
association among a DRD2 promoter region variant,
(141C Ins/Del (rs1799732), and AIWG (128). Another
studyon the DRD1-DRD5 receptors by Mu¨ller et al. found
three DRD2 SNPs (rs6277 (C957T), rs1079598, and
rs1800497 (Taq1A)) to be associated with weight gain
after stratifying their sample by ethnicity and high-risk
APs (129). Another gene that has recently been suggested
to be linked to AP-induced metabolic side effects is the
methylenetetrahydrofolate reductase (MTHFR) gene.
Deficiency of MTHFR will affect the central nervous
system and cardiovascular system and in severe cases can
lead to homocystinuria (130). Three studies focused on the
association between APs, MTHFR polymorphisms, and
metabolic disturbances. All of these studies reported on
two variants: the A1298C variants (rs1801131) and
the C677T variant (rs1801133). Two of them reported
that the (1298C variant and the C677/1298C haplotype
were associated with increased weight and metabolic
syndrome, whereas the third reported that the (677T,
not the (1298C, variant was associated with AP-induced
metabolic syndrome (130Á133).
Clozapine is particularly used in treatment-resistant
schizophrenia. Unfortunately, clozapine has the potential
to cause agranulocytosis (potentially fatal drop of white
blood cells) in up to 1% of patients. For this reason,
recurrent white blood cell counts are mandatory for
clozapine which limits its use (134). A large-scale, retro-
spective study in 2012 by Lahdelma et al. analyzed 163
Finnish patients with clozapine-induced agranulocytosis
and reported that the highest risk is during the first
year of treatment (135). There are a couple of theories
surrounding clozapine-induced agranulocytosis; the first
being that clozapine activates electrophilic nitrenium ions,
which is the first step in agranulocytosis, and the second
theory suggests an immune-mediated mechanism (136).
Genetics of antipsychotic drug outcome and clinical implications
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9. A few gene variants have been clearly implicated in
clozapine-induced agranulocytosis with the most promis-
ing being variants of the HLA-DQB1 region of the major
histocompatibility complex (136). The 6672G!C marker
of HLA-DQB1 was recently implicated in agranulocytosis
and can help identify a small subset of individuals with
extremely high-risk for agranulocytosis (137).
Another common and distressing side effect of
treatment with many AP drugs is hyperprolactinemia
potentially contributing to sexual dysfunction. Hyperpro-
lactinemia causes a variety of reversible symptoms such
as menstrual dysfunction, lactation, gynecomastia, infer-
tility and loss of libido. In addition, APs may cause other
sexual side effects such as erectile dysfunction, delayed
orgasm and impaired lubrication (138Á140). Sexual side
effects are most prevalent in those APs that have the
most pronounced D2 antagonism, mainly typical APs and
risperidone (141). One study suggests that erectile dysfunc-
tion and other sexual dysfunctions in men, as a side effect
of AP treatment, is linked to a polymorphism of the
dopamine D2 receptor ((141C Ins/Del [rs179973]) (142).
A case study by Mesa et al. suggested the addition of a
D2 agonist could eliminate the sexual side effects caused
by AP use (143). Overall, genetic causes of AP-induced
sexual side effects have not been studied extensively and
there is a paucity of literature on this subject.
All of the aforementioned side effects may affect patient
compliance, self-esteem, and quality of life. Note that for
research purposes, side effects can be advantageous as
some side effects can be measured with high reliability
(e.g. weight gain or WBC counts) when compared to
response which is often assessed using different scales.
In addition, identifying possible genetic candidates may
be easier in cases where AP effects are known to interfere
with other pathways. For example, and as mentioned
above, the HTR2C receptor is known to be involved
in appetite regulation and also antagonized by most APs
which cause AIWG.
Available pharmacogenetic tests. A number of pharmaco-
genetic tests are available either directly to the consumer or
through their healthcare providers. Since proof of clinical
and economic benefits of using genetic tests through large
randomized controlled trials on a global level are still
pending, insurance providers are disinclined to provide
coverage, causing a financial barrier to the dissemination
of the tests (144).
The following are commercially available pharmaco-
genetic tests relating to AP treatment:
Amplichip†
CYP450 test
The Amplichip†
CYP450 Test from Roche Molecular
Diagnostics was the first FDA-approved pharmacoge-
netic test. It is intended as an aid to treatment with
APs and personalizing AP choice. The test identifies a
patient’s CYP2D6 and CYP2C19 genotype, which is
an important factor in the patient’s metabolizing rate
for different drugs that are substrates for the CYP
enzymes, and can provide information on which medica-
tions to prescribe (145, 146). In a study by Dunbar et al.,
sponsored by Roche Molecular Diagnostics, the authors
report that upon surveying 33 clinicians who were using
the Amplichip†
test there were some logistic difficulties
with the test (i.e. ordering and receiving results) however,
the clinicians widely reported advantages to the test,
such as support of their dosing decisions (147). The
reported disadvantages varied from over-reliance on the
test to the actual implementation of a new clinical
procedure, breaking away from routine practice. Their
findings indicate that overall, psychiatric clinicians
are open to pharmacogenetic testing in clinical practice
if its implementation is done with economic considera-
tion (147). On the patient side, Swen et al. performed
a study using the Amplichip†
to investigate the feasibility
of pharmacy-initiated pharmacogenetic testing of CYP
metabolizer status by inviting 93 patients to participate in
the testing. They found that approximately 60% of
patients consented to the testing; a high percentage
considering the screening was not directly related to their
clinical treatment. Their study provided evidence for
pharmacy-initiated pharmacogenetic screening to be fea-
sible in a primary care setting (148). A retrospective pilot
study by Mu¨ller et al. examined 35 patients with
schizophrenia genotyped for CYP2D6 and CYP2C19
metabolizer status using the Amplichip†
test. They
reported no significant association of CYP2D6 metabo-
lizer status with treatment response. However, case
reports of PM and UM metabolizers showed generally
poor response or high rates of side effects to APs
suggesting a potential clinical benefit for preemptive
testing (12).
DMETTM
plus panel
The DMETTM
Plus Panel from Affymetrix, Inc. is a
large-scale test that covers a number of genetic variants
including frequent and uncommon SNPs (145). It includes
1,936 SNPs, copy number, and index markers across
231 genes and 100% coverage of ‘Core ADME (Absorp-
tion, Distribution, Metabolism and Excretion) Genes’
(total 32 genes) and 95% coverage of ‘Core ADME
Markers’ (185 variants) selected by PharmaADME;
a multidisciplinary group of representatives from an
academic center and the pharmaceutical industry (149,
150). The test also allows for the translation of genotypes
into metabolizer status groups to help indicate which
drugs will be the best ‘fit’ for the patient (149).
PGxPredict:Clozapine†
test
The PGxPredict:Clozapine†
test from PGxHealth, Divi-
sion of Clinical Data, Inc. was developed in 2007 and
based on two variants of the HLA-DQB1 gene, aiming to
predict if an individual has a lower versus higher risk
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10. of developing agranulocytosis (151). However, this test
was discontinued due to lack of general interest at that
time since individuals still would require regular blood
tests.
GeneSight†
test
The GeneSight†
test from Assurex Health Inc.†
analyzes
four cytochrome genes (CYP2D6, CYP2C19, CYP2C9
and CYP1A2) as well as the serotonin transporter gene
(SLC6A4) and serotonin 2A receptor (HTR2A). The
genotype results are then converted into a ‘bin’ system;
each medication is placed into either the red, yellow,
or green bin based on level of recommended caution
when prescribing a given drug (152). Winner et al. of
Assurex Health Inc.†
performed a 1-year blinded and
retrospective study evaluating the GeneSight test†
and
eight direct or indirect health care utilization mea-
sures of 96 patients with a diagnosis of depression or
anxiety. Their results demonstrated that patients carrying
gene variants with higher risk for non-response or side
effects had significantly higher health care visits, more
general medical visits, more medical absence days, and
more disability claims (152). Hall-Flavin et al. also of
Assurex Health Inc.†
conducted a study to evaluate the
potential benefit of using the GeneSight Test†
for the
management of psychotropic medication used to treat
major depression and compared one group where genetic
testing was considered versus one ‘treatment-as-usual’
group. Their findings demonstrated that use of the test
would lead to improved outcomes with antidepressant
medication. The guided group experienced greater im-
provement in three depression scores from baseline on
the HAMD, QIDS, and PHQ, when compared to the
unguided group (153).
GeneceptTM
assay
The GeneceptTM
Assay from Genomind, L.L.C. investi-
gates 10 genes including three cytochromes (CYP2D6,
CYP2C19, and CYP3A4) as well as the serotonin 2C
receptor (HTR2C) and the serotonin transporter gene
(SLC6A4). These genes were chosen because they have
each been associated with multiple psychiatric disorders,
an increased likelihood of side effects to AP treatment
and/or poor response to treatment, or the metabolism
of APs. The test’s purpose is to aid clinicians in finding
a fast and suitable treatment for the patient (154).
HILOmet PhyzioTypeTM
system test
The Genomas, Inc. Laboratory of Personalized Health
(LPH) offers various tests such as the High-Low Meta-
bolic Risk for Neuro-Psychiatric and Cardio-Metabolic
Drugs (HILOmet) PhyzioTypeTM
System test. This test
aims to guide drug choices for patients with treatment
resistance or drug intolerance and investigates a total of
37 variants in the genes coding for CYP2D6 (20 alleles),
CYP2C9 (7 alleles), and CYP2C19 (10 alleles), assessing
metabolizer status in a patient (155, 156). Further
information on additional pharmacogenetic tests can be
found at http://www.genomas.com/.
Resources
There are several resources clinicians may use to gather
information on the strength of evidence related to
pharmacogenetic-based dosing and treatment decisions
and specific dosing guidelines. These include resources
from:
1. The Clinical Pharmacogenetics Implementation
Consortium (CPIC) of the Pharmacogenomics
Research Network, established in 2009 and offer
peer-reviewed guidelines along with providing
supplemental information and data (http://www.
pharmgkb.org/page/cpic).
2. The Pharmacogenomic Knowledgebase (Pharm
GKB) provides regular updates on pharmacoge-
nomics (http://www.pharmgkb.org/index.jsp).
3. The Pharmacogenetic Research Network Á funded
by the National Institutes of Health; and involving
distinct research initiatives (http://www.nigms.nih.
gov/Research/SpecificAreas/PGRN/Pages/default.
aspx).
4. The Royal Dutch Association for the Advance-
ment of Pharmacy established the Pharmacoge-
netics Working Group to provide dosing guidelines
and recommendations (48).
5. The Evaluation of Genomic Applications in Prac-
tice and Prevention (EGAPP) initiative, established
in 2004 by the Centers for Disease Control and
Prevention (CDC), aims to establish and evaluate
a process to assess evidence-based applications of
genetic tests (http://www.egappreviews.org/about.
htm).
Discussion
Pharmacogenetic testing has made progress in recent
years to build toward personalized medicine and to reduce
the trial-and-error process of AP prescription. There are
many studies suggesting benefits of pharmacogenetic
testing in psychiatry and the most consistent findings
relate to the CYP450 enzymes. In this context, our
Pharmacogenetics Research Clinic at CAMH in Toronto
is conducting a study where testing of CYP2D6 and
CYP2C19 was found to be well accepted by physicians and
patients and considered useful to guide future treatment
decisions (11). We have now expanded this study and have
included several other genes (for more details, see www.
im-pact.ca and (157)).
Given that genotyping costs are constantly dropping,
more attention is given to the clinical applications of
the CYP genetic test results (11). Initially, genotyping
for two drug-metabolizing genes often exceeded US
Genetics of antipsychotic drug outcome and clinical implications
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11. $1,000 whereas now a much larger amount of informative
gene panels can be genotyped for an equivalent cost.
Also, more public and private insurance companies have
consistently been willing to cover the cost of pharmaco-
genetic testing for psychiatric patients, in the case of
appropriate indications (15).
With respect to pharmacogenetic studies reviewed
above, several limitations should be kept in mind such as
relatively small sample sizes, low statistical power, retro-
spective designs, heterogeneity in study design, and
inconsistencies in genotyping or phenotyping predictions
(1). There is also a paucity of psychiatric pharmacogenetic
research on patient populations such as elderly, incapable
patients and children (see also section above on CYP2D6).
Given their limited capability to report symptoms and
side effects, tools such as genetic markers may even be
of greater benefit in these populations. Another general
limitation is that large randomized control trials (RCT)
have not been conducted. RCTs could evaluate whether
improved response to treatment, including the reduced
likelihood of adverse effects, is associated with genetic
testing (including CYP genes) (1). Although RCTs are
costly and labor intensive, such studies are needed to
evaluate in more depth the clinical and health-cost benefits
of routine CYP testing (1, 11, 158).
General ethical concerns regarding pharmacogenetic
testing were raised in the studies by Haga et al. who
assessed attitudes toward pharmacogenetic testing in the
general public and in various focus groups (healthcare
professionals, primary care professionals and geneticists)
(159, 160). In the focus groups, they found that the overall
attitude was generally positive, but a few concerns
were raised in both groups. These included clinical utility,
insurance coverage, treatment delay, and the communica-
tion of ancillary disease information as principal concerns
(161). Those studies concluded that additional educa-
tional resources, access to genetic counseling, improved
clinical guidelines and cost-benefit analyses are warranted
prior to large-scale implementation (159, 160).
The FDA provides a table of approved drugs con-
taining pharmacogenomic information in their labeling
(http://www.fda.gov/drugs/scienceresearch/researchareas/
pharmacogenetics/ucm083378.htm; last updated January
22, 2014). Some labeling sections include which actions
should be taken depending on the biomarker information
provided. The table also provides which CYP enzyme
metabolizes the drug. Included in the list are APs such
as aripiprazole, clozapine, iloperidone, perphenazine,
pimozide, and risperidone. Other drugs such as atomox-
etine, clomipramine, fluvoxamine, fluoxetine, paroxetine,
thioridazine, and valproic acid used for children are also
included.
Altogether, outcomes of most medications in psychiatry
have been linked to specific gene variants and as suggested
by the FDA labeling, information of drug-metabolizing
genes is currently recommended to be considered if
metabolizer status is known. This clearly suggests that
pharmacogenetics is becoming an increasingly impor-
tant source of information for use in clinical practice in
addition to other geneÁdrug pairs discussed in this review
article that are likely to become implemented in the near
future.
Future studies should include larger samples, popu-
lations with a wider age range (i.e. children and geri-
atric populations); address potential gender effects; and
consider variations due to ethnicity. In addition, further
studies comparing pharmacogenetic-guided treatment
versus treatment as usual (TAU) are required, such as
the study on antidepressants published by Hall-Flavin
et al. (153).
Once these obstacles are overtaken, pharmacogenetic
testing will be a great asset to clinical practice. As it was
insightfully pointed out elsewhere, pharmacogenetic test-
ing was quickly adopted by other fields of medicine once
its importance became clear (15). We are confident that
clinical implementation in the field of psychiatry is
impending.
In conclusion, there is substantial evidence for the
benefit of pharmacogenetic testing in clinical psychiatry.
Promising first steps have been taken and will likely lead
to a wider acceptance and implementation in clinical
practice.
Conflict of interest and funding
Brain & Behaviour Research Foundation (NARSAD
Independent Investigator) Award to DJM, CIHR Michael
Smith New Investigator Salary Prize for Research in
Schizophrenia to DJM, and an Early Researcher Award
by the Ministry of Research and Innovation of Ontario
to DJM.
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*Daniel J. Mu¨ ller
Pharmacogenetics Research Clinic
Centre for Addiction and Mental Health
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Email: daniel.mueller@camh.ca
Genetics of antipsychotic drug outcome and clinical implications
Citation: Translational Developmental Psychiatry 2014, 2: 24663 - http://dx.doi.org/10.3402/tdp.v2.24663 15(page number not for citation purpose)