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There are limited data on clinical and biological predictors of antipsychotic drug response. The ability to identify those patients who will respond well to psychotropic drug treatment or who will be at a higher risk for adverse effects could help clinicians avoid lengthy ineffective drug trials and limit patients’ exposure to those effects. Moreover, better predictability of treatment response early in the course of a patient’s illness can result in enhanced medication adherence, a significant predictor of relapse prevention.
There are limited data on clinical and biological predictors of antipsychotic drug response. The ability to identify those patients who will respond well to psychotropic drug treatment or who will be at a higher risk for adverse effects could help clinicians avoid lengthy ineffective drug trials and limit patients’ exposure to those effects. Moreover, better predictability of treatment response early in the course of a patient’s illness can result in enhanced medication adherence, a significant predictor of relapse prevention.1
Pharmacogenetics involves the use of molecular genetic informa-tion to predict drug effectiveness and drug-induced adverse events. Pharmacogenetic data could be vital to the development of individualized treatment approaches by providing a better understanding of the molecular substrates of psychotropic drug action.
Pharmacogenetics provides a number of distinct advantages in the search for informative correlates of psychotropic drug response. First, an individual’s genotype is essentially invariable. Collection of the independent measure for analysis versus treatment response can be performed at any time during the treatment (or thereafter), but the genotype remains unaffected by the treatment itself. Second, current molecular biology techniques provide an accurate assessment of an individual’s genotype, and measurement error plays little role in these analyses. Third, the dramatic increase in the amount of publicly available genomic information provides the necessary data to conduct comprehensive studies of individual genes and broad investigation of genome-wide variation. Finally, the ease of accessibility to genotype information by means of peripheral blood or saliva samples, coupled with advances in molecular techniques, has increased the feasibility of routine DNA collection and genotyping in large-scale clinical trials.
Candidate gene approaches to pharmacogenetics
Most pharmacogenetic studies in psychiatry have focused on a candidate gene approach in which single nucleotide polymorphisms within a gene implicated in psychotropic drug action are tested for association to clinical response phenotypes. Candidates may be selected based on a priori hypotheses (such as the known binding sites of psychotropic drugs or reports of association) or because of their location in genomic regions implicated in drug action or disease pathophysiology. Candidate gene approach studies of antidepressant drugs have focused on a polymorphism (5-HTTLPR) in the gene that codes for the serotonin transporter-the putative site of action of serotonin reuptake inhibitors-and many antipsychotic pharmacogenetic drug studies have targeted the dopamine D2 receptor (DRD2) gene, to which all known antipsychotic drugs have binding affinity.
5-HTTLPR and antidepressant drug efficacy
The serotonin transporter gene is located on chromosome 17q and contains a functional polymorphism in the transcriptional control region upstream of the coding sequence. Because SSRIs block reuptake via the serotonin transporter, the 5-HTTLPR polymorphism has been frequently studied in antidepressant pharmacogenetics. Initial results with fluvoxamine indicated that the l allele of 5-HTTLPR was linked with better clinical response. Findings from many subsequent studies with multiple antidepressant agents suggest a similar relationship.2
Serretti and colleagues3 published a meta-analysis of 15 studies that included more than 1400 participants and reported that the l allele was significantly associated with antidepressant response and remission rates. Nevertheless, the relative effect size overall was modest and influenced by factors that included treatment duration, genetic analytic strategy used, and ethnicity. Subsequently, serotonin transporter genotype was not significantly associated with clinical response to the antidepressant citalopram in the large (N = 1914) Sequenced Treatment Alternatives to Relieve Depression (STAR*D) trial. Currently, the 5-HTTLPR genotype does not seem to provide sufficient predictive validity for use in clinical practice.4
DRD2 and antipsychotic drug efficacy
To date, pharmacogenetic studies in schizophrenia have revealed few compelling candidate genes (or variants) for antipsychotic drug efficacy.5 Early studies concentrated on response to the atypical antipsychotic clozapine (in part because of the ease of collecting blood samples from clozapine-treated patients who require regular venipuncture to rule out agranulocytosis). These studies primarily focused on 1 or a few single nucleotide polymorphisms derived from genes encoding dopamine (DRD3, DRD3) or serotonin receptors (HTR2A, HTR2C) for which clozapine has potent affinities.
Later candidate gene studies have followed this basic strategy with olanzapine and risperidone, with mixed results. The lack of compelling results may be related to small sample sizes (often fewer than 100 patients), short trials (4 to 8 weeks), the lack of comprehensive phenotype information with often only a single rating, and the clinical heterogeneity of the study populations (in which patients with early-phase illness are combined with those who have chronic illness).
The largest candidate gene pharmacogenetic study published to date in schizophrenia assessed 678 patients assigned to 1 of 5 antipsychotic drugs as part of the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE).6 This study was primarily made up of chronically ill patients who were recruited from approximately 50 academic and nonacademic centers across the United States. It focused on the relationship of treatment response to 8 single nucleotide polymorphisms within a candidate gene for schizophrenia susceptibility-regulator of G protein signaling 4 (RGS4). No results survived correction for the number of phenotypes and single nucleotide polymorphisms tested, although nominally significant results (P = .01 and P = .002) were obtained for 2 individual analyses relating specific drugs to a clinical response phenotype.
Taken together, the early pharmacogenetic studies in schizophrenia have not provided any compelling evidence that any gene, or combination of genes, influences treatment response. This is particularly surprising when one considers the fact that all antipsychotic drugs share at least one property (the ability to bind potently to DRD2), although no clear identification of variants within DRD2 that influence antipsychotic response has been reported.7 This may be because most pharmacogenetic studies have comprised patients who have chronic schizophrenia and have received multiple antipsychotic drugs. In vivo neuroimaging studies have shown that exposure to treatment influences D2 receptor density. Thus, variation in antipsychotic drug exposure could result in considerable interindividual variation in D2 receptor and would introduce heterogeneity into analyses of single nucleotide polymorphisms that produce functional effects via DRD2 expression.8
A 16-week double-blind clinical trial of olanzapine versus risperidone focused on DRD2 genetic variation in a small cohort of patients with first-episode schizophrenia.9 A significant relationship between a promoter region polymorphism, 2141C Ins/Del, and the a priori response was seen: patients who carried the Del allele (Del carriers) were less likely to respond clinically to either antipsychotic (Figure 1).10
Although these data are intriguing, the small sample size limits the interpretation of the results. Therefore, a meta-analysis was undertaken of all published DRD2 pharmacogenetic studies for which sufficient data to calculate odds ratios across a common metric of a 50% reduction in symptoms from baseline to follow-up were available.11 Results from the meta-analysis of more than 700 patients showed a significant relationship between the 2141C Ins/Del variant and clinical response.
Genome-wide approaches to pharmacogenetics
A complementary approach to the candidate gene approach to pharmacogenetics is the genome-wide association study (GWAS) approach. In contrast with candidate gene studies, the GWAS approach uses recently developed microarrays to interrogate hundreds of thousands of single nucleotide polymorphisms randomly distributed across the genome.12 GWAS provides the advantage of comprehensive coverage of the genome without using a priori hypotheses on drug action. The drawback to this comprehensive coverage is the need for large sample sizes. Markedly higher thresholds are needed to achieve statistical significance when so many single nucleotide polymorphisms are being tested. Consequently, there have been a limited number of pharmacogenetic GWAS studies.
McClay and colleagues13 conducted a GWAS on the CATIE sample of more than 700 patients. In patients treated with ziprasidone, the strongest evidence for an association with clinical response was seen with an intergenic single nucleotide polymorphism with positive symptom response. (Other single nucleotide polymorphisms showed more modest association with additional drug response phenotypes). Unfortunately, this single nucleotide polymorphism is not located near or within known genes, and interpretation of these results is hampered by methodological considerations, including the lower number of ziprasidone-treated patients. Nevertheless, this study highlights the predictive potential of this approach in psychiatric pharmacogenetics.
There have been 3 antidepressant studies using the GWAS approach. Ising and colleagues14 reported the results of a GWAS. Replication genotyping was conducted in a subset of the STAR*D sample. Garriock and colleagues15 conducted a GWAS on level 1 of the STAR*D sample that included more than 1400 patients treated with citalopram. Uher and colleagues16 recently reported results of a novel antidepressant study, the Genome-Based Therapeutic Drugs for Depression (GENDEP) project, in which the study design was specifically based on pharmacogenetic considerations. Despite this, none of the studies using the GWAS approach detected genetic variants that met criteria for genome-wide significance. This suggests that larger sample sizes or alternative study designs are needed to detect common variants that influence the clinical response to antidepressant treatment.
Pharmacogenetics of adverse events
A potentially more robust phenotype for examination with pharmacogenetics is susceptibility to treatment-related adverse effects. In other branches of medicine, there have been notable successes in using genetic approaches to identify powerful predictors of drug-induced adverse events. A specific HLA allele markedly increases the risk of liver injury as a result of flucloxacillin treatment (odds ratio = 80.6). Furthermore, the HLA allele provides 100% sensitivity for development of an immunologically confirmed hypersensitivity reaction to the nucleoside reverse transcriptase inhibitor abacavir, used in the treatment of AIDS.17,18 In the abacavir study, 23 patients carried the specific HLA risk allele: the hypersensitivity reaction developed in every one of these patients. In contrast, the overall occurrence rate is less than 3% in noncarriers.
Rare, yet important, adverse effects such as these may also occur with psychotropic drugs. The prototypical antipsychotic, clozapine, is associated with potentially fatal agranulocytosis in fewer than 1% of patients. A recent candidate gene study detected a significant association of the HLA-DQB1 locus with risk of agranulocytosis in 2 small clozapine-treated cohorts. Odds ratios were significantly higher than those typically reported in pharmacogenetic studies of clozapine’s efficacy.19 Additional work is ongoing to enhance the sensitivity and specificity of this result, but the early data are encouraging. It may soon be possible to use genetic markers to prospectively identify individuals at high risk for this rare adverse effect, which could lead to increased use of this important agent.
A more common adverse effect is antipsychotic-induced weight gain. Studies have shown that many of the atypical antipsychotics are associated with marked weight gain, particularly in pediatric patients and in those patients with no previous exposure to antipsychotics.20 Reynolds and colleagues21 studied 123 antipychotic drug–naive schizophrenic Chinese patients (61 men, 62 women) and reported that a promoter region polymorphism, 2759 C/T in the 5-HT2C receptor gene, significantly influenced weight gain following antipsychotic treatment. Study participants with the T allele at this locus gained significantly less weight than those with the C allele at 6 weeks (P < .0001) and at 10 weeks (P = .0003) of treatment. This effect was observed in 46 patients who received risperidone and 69 patients who received chlorpromazine. The effect remained significant after exclusion of patients who were either underweight or obese at baseline. None of the 27 patients carrying the T allele met criteria for severe weight gain (greater than 7% increase from baseline body weight) after 6 weeks of treatment, compared with 28% of the 96 patients without the T allele.
Templeman and colleagues22 reported similar results in a small first-episode cohort treated with a mix of antipsychotic medications including olanzapine. Reynolds and colleagues23 also demonstrated an association between 2759C/T and weight gain in a small group of clozapine-treated patients. However, subsequent studies in previously treated patients have been inconsistent. A critical factor in these studies may be the degree of drug exposure. Studies with previously treated patients may underestimate the amount of true weight liability of each drug; variable histories of drug exposure in each cohort may confound analyses intended to identify subtle genetic effects on a complex phenotype such as weight gain.
A preliminary pharmacogenetic analysis of antipsychotic drug-induced weight gain in patients with first-episode schizophrenia who had little or no prior antipsychotic drug exposure has recently been completed.24 All currently available antipsychotics act on DRD2 and are associated with significant weight gain. Lencz and colleagues24 examined the relationship between DRD2 2141C Ins/Del and weight gain in first-episode patients enrolled in a randomized trial of risperidone (n = 32) and olanzapine (n = 26). DRD2 Del carriers (n = 29) were compared with Ins/Ins homozygotes (noncarriers, n = 29) in a mixed model of 10 measurements over 16 weeks. There were significant main effects of genotype: DRD2 Del carriers demonstrated substantially more weight gain than noncarriers after 6 weeks of treatment, regardless of medication (Figure 2). Mean weight gain in Del carriers at 6 weeks was approximately 6 lb higher than in noncarriers.
Although pharmacogenetics research is still early in its development, the initial results suggest that detection of molecular variants associated with psychotropic drug response may soon be possible. Examination of patients with early illness who have had less drug exposure may enhance the power of this approach. Moreover, a focus on drug-induced adverse effects may be valuable, because these effects may be more amenable to detection than more complex clinical efficacy phenotypes that may require larger study populations.
For those interested in more information on this rapidly developing field, a yearly conference-Pharmacogenetics in Psychiatry-is held in New York. For information, go to www.pharmacogeneticsinpsychiatry.com or call 718-470-8418.
Robinson DG, Woerner MG, Alvir JM, et al. Predictors of treatment response from a first episode of schizophrenia or schizoaffective disorder.
Am J Psychiatry
Smeraldi E, Zanardi R, Benedetti F, et al. Polymorphism within the promoter of the serotonin transporter gene and antidepressant efficacy of fluvoxamine.
Serretti A, Kato M, De Ronchi D, Kinoshita T. Meta-analysis of serotonin transporter gene promoter polymorphism (5-HTTLPR) association with selective serotonin reuptake inhibitor efficacy in depressed patients.
Kraft JB, Peters EJ, Slager SL, et al. Analysis of association between the serotonin transporter and antidepressant response in a large clinical sample.
Malhotra AK, Murphy GM Jr, Kennedy JL. Pharmacogenetics of psychotropic drug response.
Am J Psychiatry
Campbell DB, Ebert PJ, Skelly T, et al. Ethnic stratification of the association of RGS4 variants with antipsychotic treatment response in schizophrenia.
Kapur S, Mamo D. Half a century of antipsychotics and still a central role for dopamine D2 receptors.
Prog Neuropsychopharmacol Biol Psychiatry
Silvestri S, Seeman MV, Negrete JC, et al. Increased dopamine D2 receptor binding after long-term treatment with antipsychotics in humans: a clinical PET study.
Robinson DG, Woerner MG, Napolitano B, et al. Randomized comparison of olanzapine versus risperidone for the treatment of first-episode schizophrenia: 4-month outcomes.
Am J Psychiatry
Lencz T, Robinson DG, Xu K, et al.
promoter region variation as a predictor sustained response to antipsychotic medication in first episode-schizophrenia patients.
Am J Psychiatry
Zhang J, Lencz T, Malhotra AK. Dopamine D2 receptor genetic variation and clinical response to antipsychotic drug treatment: a meta-analysis.
Am J Psychiatry
. In press.
Lencz T, Morgan TV, Athanasiou M, et al. Converging evidence for a pseudoautosomal cytokine receptor gene locus in schizophrenia.
McClay JL, Adkins DE, Aberg K, et al. Genome-wide pharmacogenomic analysis of response to treatment with antipsychotics.
. 2009 Sep 1; [Epub ahead of print]. doi:10.1038/mp.2009.89.
Ising M, Lucae S, Binder EB, et al. A genomewide association study points to multiple loci that predict antidepressant drug treatment outcome in depression.
Arch Gen Psychiatry
Garriock HA, Kraft JB, Shyn SI, et al. A genomewide association study of citalopram response in major depressive disorder.
Uher R, Perroud N, Ng M, et al. Genome-wide pharmacogenetics of antidepressant response in the GENDEP project.
Am J Psychiatry
. In press.
Daly AK, Donaldson PT, Bhatnagar P, et al; DILIGEN Study, International SAE Consortium. HLA-B*5701 genotype is a major determinant of drug-induced liver in jury due to flucloxacillin.
Mallal S, Phillips E, Carosi G, et al; PREDICT-1 Study Team. HLA-B*5701 screening for hypersensitivity to abacavir.
N Engl J Med.
Athanasiou MC, Dettling M, Cascorbi I, et al. Candidate gene analysis identifies a polymorphism in HLA-DQB1 associated with clozapine-induced agranulocytosis.
J Clin Psychiatry
. In press.
Correll CU, Manu P, Olshanskiy V, et al. Cardiometabolic risk of second-generation antipsychotic medications during first-time use in children and adolescents [published correction appears in
Reynolds GP, Zhang ZH, Zhang XB. Association of antipsychotic drug-induced weight gain with a 5-HT2C receptor gene polymorphism.
Templeman LA, Reynolds GP, Arranz B, San L. Polymorphisms of the 5-HT2C receptor and leptin genes are associated with antipsychotic drug-induced weight gain in Caucasian subjects with a first-episode psychosis.
Reynolds GP, Zhang Z, Zhang X. Polymorphism of the promoter region of the serotonin 5-HT(2C)receptor gene and clozapine-induced weight gain.
Am J Psychiatry
Lencz T, Robinson DG, Xu K, et al.
variation and weight gain in first episode schizophrenia.
2009;35:107. Paper presented at: the 2009 meeting of the International Congress of Schizophrenia Research; San Diego.