ABSTRACT
Treatment with antipsychotics is marred by frequent failure and adverse reactions. About a third of treated patients will not improve adequately, and more than 60% will develop severe and long-lasting side-effects, including weight gain (developed by 10-57% of treated patients) and tardive dyskinesia (4-65%) among others. Genetic, clinical and environmental factors contribute to the variability observed in response to antipsychotic treatment. Genetic research has identified several polymorphisms in pharmacokinetic and pharmacodynamic genes contributing to response variability. In particular, functional polymorphisms in genes coding for cytochrome P450 (CYP) enzymes have been demonstrated to influence antipsychotic biotransformation rates and response variability, whereas genes coding for drug targets have been suggested to influence the level of efficacy of antipsychotics. Characterization of key pharmacogenetic genes before the start or change of antipsychotic treatment may help to improve the efficacy and safety of pharmacological treatments. Although evaluation studies are still sparse, there is growing evidence of the clinical and economic benefits of introducing pharmacogenetic information as a prescription aid in clinical settings.
Introduction
Antipsychotic drugs are the mainstay treatment of schizophrenia and are used for the treatment of other mental disorders such as bipolar disorder, psychotic depression, and dementia. However, treatment failure and adverse reactions hinder the use of antipsychotic drugs. About a third of treated patients do not respond adequately to treatment with antipsychotic drugs, and even patients who respond develop severe, long-lasting, and sometimes life-threatening side effects. Movement disorders (4–80%), weight gain (10–57%), and sexual dysfunction (8–50%) are the most prevalent, although their frequency varies greatly according to the type, dosing, and duration of antipsychotic treatment. Other common adverse reactions associated with antipsychotic treatment include diabetes, hypertension, somnolence, anxiety, and cardiovascular events amongst others. The reasons for treatment failure are unclear, and treatment is mostly provided on a trial/error strategy. A common feature of currently used antipsychotics is their affinity for dopaminergic receptors. Other neurotransmitter receptors including serotonergic, glutamatergic, muscarinic, and adrenergic receptors are also important antipsychotic targets [Citation1], although their level of contribution to their therapeutic effect is unclear. Pharmacogenetic research aims to identify the predictors of response to antipsychotic treatment and to improve understanding of their mechanism of action.
One of the main problems hampering the advance of research in the field is the difficulty in clearly determining the response to antipsychotic medications. Treatment response is the result of complex interactions between genetic, clinical, and environmental factors. Several clinical and environmental factors have been related to treatment variability. Clinical factors such as symptom severity and age of onset, amongst others have been associated with the level of improvement with antipsychotic treatment [Citation2,Citation3], whereas environmental factors such as diet, smoking habits, and concomitant treatment may influence drug metabolism rates and clinical outcome [Citation3]. Determining the presence and magnitude of treatment-induced side effects is relatively easier, and this may partially explain why stronger genetic associations have been discovered with specific side effects [Citation3]. Nevertheless, genetic studies point toward a relatively strong influence of genetic factors on the variability observed in response to antipsychotic treatment. Twin studies, although scarce, provide evidence of similar levels of response and development of side effects in genetically identical pairs treated with the same antipsychotics [Citation2]. Although there is no large twin study that permits quantification of treatment response heritability, it is estimated that the genetic contribution to response variability is moderate to large, in particular when considering the biotransformation of antipsychotic medications. During the last few decades, pharmacogenetic studies have identified many genetic variants that may contribute to the heritability of treatment response, in varying degrees. The search engines Web of Science (wok.mimas.ac.uk) and Scopus (www.scopus.com) were used to find pharmacogenetic studies using the search words ‘antipsychotic’ and ‘gene or polymorphism’ and ‘response or efficacy or side effect or adverse reaction’. We reviewed more than 1400 publications and selected studies reporting statistically significant findings. The most replicated findings include genes involved in the pharmacokinetic (drug metabolism) and pharmacodynamic (drug targets) processes of antipsychotic drugs and will be described in the following sections.
Variation in drug-metabolizing enzymes
Cytochrome P450 (CYP) enzymes are involved in the metabolism of more than 85% of drugs, including antipsychotic medications. CYP1A2, CYP2C9, CYP2C19, CYP2D6, and CYP3A4 are the main metabolic pathways of currently used antipsychotic drugs [Citation4]. Functional polymorphisms that render CYP enzymes inactive or slow (Poor Metabolizers or PM) or that induce high metabolic rates (Ultrarapid metabolizers or UM) have been described as early as the 1950s. Since then, numerous polymorphisms that alter the metabolic rate of CYP enzymes have been described. summarizes the most common polymorphisms described in CYP involved in antipsychotic metabolism and their functionality, if known.
Table 1. List of common polymorphisms described in genes coding for CYPs involved in the metabolism of antipsychotic drugs (information gathered from www.cypalleles.ki.se & www.ensembl.org).
Numerous pharmacokinetic studies provide evidence of the direct relation between the presence of CYP PM variants and high plasma levels of antipsychotic drugs, and between the presence of CYP UM variants and low plasma levels of substrate drugs [Citation5–Citation10]. In addition, pharmacogenetic research has provided evidence of the importance of these variants in psychiatric treatment, with numerous studies associating their presence with treatment response. summarizes significant findings reported with CYP variants (for reasons of brevity, only the most relevant findings are reported). Functional polymorphic variants affecting metabolic rates were first described in the CYP2D6 gene and several studies have associated them with antipsychotic efficacy [Citation11] and induced side effects [Citation11–Citation18]. CYP1A2 UM variants have been associated with lack of response to the antipsychotic clozapine [Citation7,Citation9], whereas variants in the same gene associated with reduced enzyme activity have been related to drug-induced side effects such as Tardive Dyskinesia (TD) and seizures [Citation19–Citation23]. A recent study associated CYP2C9 polymorphisms and the development of somnolence during antipsychotic treatment [Citation24]. Finally, CYP3A4 and CYP3A43 variants may influence response to second-generation antipsychotics (SGAs) [Citation25,Citation26].
Table 2. Summary of significant pharmacogenetic findings between CYPs variants and response to antipsychotic medications.
In summary, these studies show a clear association between the presence of functional polymorphisms in metabolic enzymes and the development of adverse reactions, although the associations with the level of efficacy of antipsychotic drugs are not so clear. Nevertheless, it has been proposed that the characterization of the genetically determined metabolic status of the patients before the start of pharmacological treatment may help adjust clinical doses accordingly and significantly improve the efficacy and safety of drugs [Citation27]. This strategy is supported by the pharmacokinetic and pharmacogenetic findings indicating that the presence of PM mutations may be highly influential for the metabolic rates of drugs with one or few metabolic pathways and/or narrow dose ranges, such as haloperidol [Citation28]. While the importance of these PM variants may be diluted in modern drugs with multiple metabolic pathways, the presence of genetically determined UM phenotypes in any one of the drug metabolic pathways may become more influential. Nevertheless, given that environmental (e.g. caffeine) and clinical (e.g. concomitant treatments) factors may reduce enzyme activity, poor metabolizing rates will still pose a problem in the future.
Variation in drug targets
In spite of decades of research, the mechanism of action of antipsychotic medications remains unclear. First-generation antipsychotics (FGAs) target mainly dopaminergic receptors, whereas SGAs display a more varied pharmacodynamic profile, including affinities for dopaminergic, serotonergic, adrenergic, histaminic, muscarinic, and glutamatergic receptors [Citation1,Citation3]. Although dopamine receptors constitute a common target, it is not clear which neurotransmitter receptors mediate antipsychotic activity. It has been suggested that the blocking of dopamine transmission improves positive psychotic symptoms, whereas targeting of serotonergic receptors improves negative symptoms [Citation29–Citation31]. However, the complex interaction of serotonergic/dopaminergic targeting and the contribution of other neurotransmitter receptors is not well understood. Because of the pharmacological profile of most commonly used antipsychotics, pharmacogenetic studies have focused on genetic variants in dopaminergic and serotonergic receptors in an attempt to discern their therapeutic value. summarizes the most common polymorphisms described in the genes coding for dopamine and serotonergic receptors targeted by antipsychotic drugs, and their functional effect, if known.
Table 3. List of common polymorphisms described in dopamine and serotonin receptors and transporters (information gathered from www.ensembl.org, www.ncbi.nlm.nih.gov & www.snpedia.com).
Numerous studies have investigated the relation between these genetic variants and antipsychotic response. Genetic variants in dopamine receptors type 1, 2, 3, and 4 (D1, D2, D3, and D4, respectively) have been associated with the level of response to a variety of FGA and SGA [Citation29,Citation32–Citation44]. summarizes the most relevant results, listing only significant findings. In general, dopamine receptor variants associated with reduced expression of the receptor protein or altered functioning were also associated with poorer response to antipsychotic drugs, indicating that these receptors mediate antipsychotic activity. Several studies have also associated dopamine receptor variants with antipsychotic-induced adverse reactions. D2 variants have been associated with movement disorders [Citation18,Citation45–Citation47], weight gain [Citation48], and sexual dysfunction [Citation49]. D3 variants have been associated with movement disorders, particularly with TD [Citation50–Citation54]. The strongest of these associations showed that a D3 Gly9 variant with high affinity for dopamine was associated with a higher risk of TD and other movement disorders, as shown in a large combined study of 780 patients [Citation50]. The increased dopamine affinity of the Gly9 variant may lead to high levels of occupation of dopamine receptors, surpassing the threshold associated with the development of movement disorders. Finally, D4 variants have also been associated with the development of TD [Citation55,Citation56] and weight gain [Citation57] during treatment with antipsychotics.
Table 4. Summary of significant pharmacogenetic findings between dopamine and serotonin genetic variants and antipsychotic medications.
Clear associations have been observed between polymorphisms in serotonergic receptors and SGA, which display high affinities for these receptors, but also with FGA. Several studies have linked variants of the serotonin receptors type 2A (5-HT2A) with clinical response. In particular, a silent 102-C allele linked to a promoter region variant with reduced expression of the receptor protein, -1430-G, and a structural 452Tyr variant with altered receptor functioning have been associated with poor response to SGA and FGA [Citation61–Citation66] and with TD, weight gain, and obesity [Citation17,Citation56,Citation67,Citation68]. The associations of 5-HT2A polymorphisms with antipsychotic response and TD were confirmed in meta-analyses and combined studies [Citation64,Citation68]. A -759-C/T polymorphism in the promoter region of the 5-HT2C gene has been repeatedly associated with weight gain, although the direction of the associations is not clear [Citation17,Citation72–Citation77,Citation91]. Polymorphisms in the 5-HT2C gene have also been associated with other side effects such as TD and Parkinsonism [Citation45,Citation78–Citation80]. However, only few studies have related 5-HT2C genetic variants with treatment efficacy [Citation69–Citation71], suggesting that this receptor does not have a clear therapeutic role but contributes to the development of side effects during treatment. Genetic variants in 5-HT1A, 5-HT3A, and 5-HT6 have also been associated with response to SGA, although these findings need confirmation [Citation58–Citation60,Citation81–Citation84]. These pharmacogenetic findings suggest that the targeting of serotonergic receptors mediates, at least partially, the therapeutic activity of SGA, and plays a major contributing role in the development of adverse reactions.
Finally, a limited number of studies have investigated genetic variants in the adrenergic receptors alpha-1A and alpha-2A (ADRA1A and ADRA2A, respectively) and found them associated with TD and weight gain [Citation92–Citation95], and polymorphisms in histamine receptors 2, 3, and 4 (H2, H3, and H4) have been marginally associated with response to the antipsychotics clozapine and risperidone [Citation96–Citation98].
Taken together, these results indicate that the dopamine and the serotonergic systems play major roles in the therapeutic action of currently available antipsychotics, although they also contribute to treatment-associated side effects. The role of other targeted neurotransmitter systems is less clear, and there is insufficient evidence to evaluate their clinical value. Nevertheless, in view of the numerous reported associations with adverse reactions, the number of targets (especially those with no proven therapeutic effect) could be reduced in order to increase drug safety.
Alternative genetic markers
Aside from CYP enzymes and directly targeted receptors, numerous polymorphisms in schizophrenia risk genes, other neurotransmitter receptors, metabolic enzymes, and energy regulating proteins amongst others, have been associated with treatment variability. This section will summarize the most relevant of these findings.
Regarding drug efficacy, the most replicated finding associates genetic variants in the Catechol-o-methyltansferase (COMT) enzyme with antipsychotic response. COMT regulates the metabolic degradation of catecholamines, including dopamine catabolism, and is located in a region linked to mental disorders. A structural variant in the COMT gene, Met158, displays lower enzymatic activity, which leads to higher dopamine availability. This variant has been repeatedly associated with better response to SGA treatments [Citation99–Citation106]. COMT variants have also been associated with adverse reactions such as TD and Parkinsonism [Citation55,Citation78,Citation85]. The Brain-Derived Neurotrophic Factor (BDNF) protein promotes neural survival in the adult brain and has been linked to memory impairment and mental disorders [Citation107–Citation110]. Interestingly, functional variants and haplotype combinations of the BDNF gene have been associated with response to antipsychotics [Citation111,Citation112], TD [Citation113,Citation114], and weight gain [Citation17,Citation115,Citation116]. Polymorphisms in the glutamate metabotropic receptor 3 (GRM3), although not strongly targeted by currently available antipsychotics, have also been related to response [Citation102,Citation117,Citation118]. Several studies investigated the multidrug resistance 1 (MDR1) enzyme, also known as ATP binding cassette B1 (ABCB1). MDR1 is a pump integral of the blood-brain barrier that regulates antipsychotic transport and availability in the brain. MDR1 genetic variants have been associated with the level of response to a variety of antipsychotics [Citation119–Citation121] and with movement disorders and weight gain [Citation122,Citation123]. A recent study found associations between the hypothalamic-pituitary-adrenal system gene FKBP5 and the neurotrophic factor NTRK2 and clozapine response [Citation124]. Dopamine and serotonin transporters (DAT 1 and 5-HTT, or SLC6A3 and SLC6A4, respectively), although not directly targeted by antipsychotic medications, may influence neurotransmitter availability and contribute to treatment variability. A number of studies reporting association between polymorphisms in the genes coding for these transporters and level of response [Citation69,Citation86–Citation90] and adverse reactions [Citation67,Citation85] support this hypothesis. Interestingly, 5-HTT polymorphisms are also clearly associated with response to selective-serotonin-reuptake-inhibitors (SSRIs) antidepressant medications [Citation125].
There are a number of genes that have been mostly associated with drug-induced side effects. Several genes involved in energy expenditure and regulation fall within this group: Leptin (LEP), Leptin receptor (LEPR), Ghrelin (GHRL), insulin-induced gene 1 and 2 (INSIG1 and INSIG2), and Fat mass and obesity (FTO) have been associated with weight gain, dyslipidemia, and metabolic syndrome [Citation3,Citation91,Citation126–Citation129]. A gene related to obesity in the general population, the melanocortin 4 receptor (MC4R) gene, has been clearly associated with drug-induced weight gain in several independent studies, constituting a putative susceptibility biomarker for this side effect [Citation130–Citation132]. The Methylenetetrahydrofolate reductase (MTHFR) gene has been linked to depression, and variants of this gene have been found associated with Parkinsonism and extra-pyramidal symptoms [Citation133,Citation134]. Finally, polymorphisms in the regulator of G-protein signaling 2 (RGS2) and cannabinoid receptor 1 (CNR1) genes have been associated with movement disorders, Parkinsonism, weight gain, and metabolic syndrome [Citation135–Citation139]. These findings provide valuable information toward the development of novel and safer drugs that may avoid interactions with systems exclusively associated with adverse reactions. For instance, safety of current antipsychotic may be increased by avoiding interactions with adrenergic receptors, LEP and LEPR, FTO, and MC4R amongst others.
There are numerous single-report associations with a variety of genes directly or indirectly related to antipsychotic pharmacological profile or susceptibility risk. However, confirmation of findings in independent studies is required given the large number of false positives produced by candidate-gene studies. In general, the reported associations indicate that genetic information may be clinically useful to detect susceptibility to side-effects, whereas the moderate/low strength of the associations with level of efficacy may not suffice to use genetic variants in drug targets as predictors of treatment response.
Genomic findings
Most clinically applicable findings have been obtained by candidate-gene strategies so far. However, candidate-gene strategies are based on previous pharmacological knowledge and have not contributed novel information on the mechanism of action of antipsychotics, merely confirming existing knowledge. The development of genome-wide-association studies (GWAs) that facilitate the interrogation of the entire genome provided the tools to investigate beyond current knowledge. However, only a limited number of GWAs investigating antipsychotic response have been conducted to date, probably because of the difficulty of obtaining large samples of schizophrenia patients with detailed information on antipsychotic response. summarizes the findings of these studies.
Table 5. Summary of the most significant findings of GWAs studies on antipsychotic response.
The CATIE study was a multicenter research project investigating the effectiveness of SGA and FGA medications, in which several GWAs have been conducted in relation to treatment response and adverse reactions. In a first analyses, several polymorphisms in the ankyrin repeat and sterile a-motif domain containing 1B (ANK1SB), contactin-associated protein-like 5 (CNTNAP5), and transient receptor potential cation channel subfamily M member 1 (TRPM1) genes were found associated with treatment efficacy [Citation141]. Later studies in the CATIE cohort found variants in the ETS (E26 transformation-specific) homologous factor (EHF), sulfate transporter, D2, G-protein-coupled receptor 137B (GPR137B), carbohydrate sulfotransferase 8 (CHST8), and IL-1a genes associated with neurocognition improvement during treatment [Citation142]. A GWAs conducted on iloperidone-treated patients revealed polymorphisms in the neuronal PAS domain protein 3 (NPAS3) and kell blood group complex subunit-related family member 4 (XKR4) genes to be associated with treatment efficacy [Citation140].
Several GWAs have investigated specifically drug-induced adverse reactions. Chagnon and collaborators identified a region containing the pro-melanin-concentrating hormone (PMCH) gene, involved in energy expenditure and food intake, linked to drug-induced obesity [Citation143]. Finally, a GWAs, conducted on a small cohort, revealed several genes from the g-aminobutyric acid (GABA) receptor pathway to be involved in drug-induced TD [Citation144].
Further analyses in the CATIE cohort revealed novel associations with common side effects: the MeisHomeobox 2 (MEIS2) gene associated with the effects of risperidone on hip and waist circumference [Citation146], ZNF202 and PLP1 genetic variants were associated with EPS [Citation145], and genetic variants in a gene encoding for a transcription factor that controls neurogenesis (EPF1), in a cochaperone gene (FIGN) and in a neuronal-specific RNA-binding protein gene (NOVA1) associated with Parkinsonism [Citation147]. Finally, OGFRL1 and IBA57 genetic variants were associated with weight gain in the same cohort [Citation148].
These studies have succeeded in finding novel information that may constitute new therapeutic areas of interest. However, the genetic associations detected by GWAs need to be replicated in independent studies using candidate-gene approaches to evaluate their clinical utility. Further research is required to discern the mechanism of action of antipsychotic medications, complementing current genomic studies with gene expression and epigenetic studies and large and prospectively assessed samples [Citation149].
Clinical application of pharmacogenetic information in psychiatry
Candidate-gene studies have provided evidence of the contribution of genetic variants to variability in response to antipsychotic treatment. However, many of these findings are difficult to translate into clinical practice, given the moderate to small magnitudes of the reported associations and the lack of universal replication. Besides, clinical response to antipsychotic medications can also be influenced by nongenetic factors that are difficult to control. However, it is important to point out that pharmacogenetic information does not predict risk of developing a severe mental illness, for which a high sensitivity and specificity would be a requirement. Pharmacogenetic tests provide information on the probabilities of responding to a particular treatment or developing a side effect, and therefore do not need to be as accurate as a diagnostic test for a severe disease. Pharmacogenetic information can be used as a prescription tool by the clinician to improve their selection of dose and type of antipsychotic for each patient. An additional benefit of using pharmacogenetic information is that it can be obtained before the start of the treatment and can be stored within the patients’ medical notes for future use with other medications.
To date, the most clinically applicable pharmacogenetic findings on antipsychotics are the associations of CYP functional polymorphisms with metabolic rates and the presence of side effects. Although no systematic study has evaluated the clinical and economic benefits of adjusting antipsychotic clinical doses according to the patients’ CYP profile, it has been estimated that such an intervention may significantly improve the efficacy and safety of treatments [Citation27]. A limited number of studies have provided evidence of the clinical benefits of using pharmacogenetic information on CYPs for the selection of type and dose of antidepressants [Citation150–Citation152]. Other findings with translational potential are the associations of MC4R, dopaminergic and serotonergic polymorphisms with antipsychotic-induced side effects discussed in the previous sections. However, these encouraging findings require further research to assess their clinical validity before using them in clinical settings. Unfortunately, most of the findings relating genetic variants in drug targets with level of efficacy are of modest significance, and may not be clinically useful. Nevertheless, a combination of information in several genes, clinical and environmental factors may improve their applicability for the personalization of antipsychotic treatment and should be investigated. An early study showed that the combination of polymorphisms in several drug targets could predict the response to the antipsychotic clozapine [Citation69], and the addition of clinical and environmental information could improve the level of response prediction[Citation3,Citation152].
Currently, there are several commercial tests that provide pharmacogenetic information that could be used for the personalization of antipsychotic treatment. Most of these tests characterize CYP functional polymorphisms of proven clinical value, and several of them provide information on pharmacodynamics markers that may be of use. However, several of them provide additional information to characterize genetic variants that have not been confirmed as clinically valuable and should be used with care. Despite the availability of these pharmacogenetic tests, and of the relative simplicity of the assays required for CYP status characterization, the application of pharmacogenetic information in clinical settings is minimal. The lack of research evaluating the clinical and economic benefits of a pharmacogenetic intervention in psychiatry may be one of the main causes hampering their application. Recent studies on the benefits of using pharmacogenetic information to improve treatment with antidepressant medications have provided encouraging results [Citation152]. However, randomised clinical trials evaluating the clinical and economic benefits of using genetic information to improve antipsychotic treatment are required. This will help convince the clinicians of the utility of the tests and to expand their use in clinical settings.
Conclusions
Pharmacogenetic research has identified genetic markers in CYP enzymes that can be used to improve the efficacy of antipsychotics and reduce the treatment-associated side effects. Further research into the clinical utility of dopaminergic and serotonergic genetic variants is required. Studies evaluating the clinical and economic benefits of pharmacogenetic interventions will help expand their use in clinical settings.
Expert commentary
Decades of pharmacogenetic research have succeeded in identifying genetic variants associated with variability in antipsychotic treatment. However, most of these findings are of moderate clinical value. Nevertheless, key genetic variants in CYP enzymes may prove useful in improving antipsychotic efficacy and safety. Several pharmacogenetic tests are already available that include CYP polymorphisms and other genetic variants that may be of clinical value. However, these tests are rarely used in clinical settings. Clinical trials are required to prove their clinical and economic benefits to promote their use for the improvement of antipsychotic treatments.
Five-year view
Algorithms combining information in key genetic polymorphisms, clinical data, and environmental factors will be developed for the prediction of likelihood of response and adverse reactions to antipsychotic treatment. The implementation of pharmacogenetic tests for the improvement of antipsychotic treatment will have increased following data from clinical trials proving their clinical value.
Financial & competing interests disclosure
The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.
Key Issues
Antipsychotic response difficult to determine and to associate with genetic variants.
Moderate to strong associations identified between genetic variants and antipsychotic-induced adverse reactions.
Most associations are of limited clinical value.
Genetic variants in CYP enzymes clearly associated with presence of antipsychotic-induced side effects and moderately associated with antipsychotic efficacy.
Dopamine and serotonin genetic variants moderately associated with antipsychotic response and side effects.
Commercial pharmacogenetic tests with applicability in psychiatry already available.
The use of pharmacogenetic information in clinical settings is limited.
Studies proving the clinical and economic benefits of using pharmacogenetic information to improve efficacy and safety of antipsychotic treatment required.
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