Genetic determinants of variable metabolism have little impact on the clinical use of leading antipsychotics in the CATIE study

Optimisation of pharmacotherapy in psychiatry through therapeutic drug monitoring, molecular brain imaging and pharmacogenetic tests: Focus on antipsychotics

BACKGROUND

For psychotic disorders (i.e. schizophrenia), pharmacotherapy plays a key role in controlling acute and long-term symptoms. To find the optimal individual dose and dosage strategy, specialised tools are used. Three tools have been proven useful to personalise drug treatments: therapeutic drug monitoring (TDM) of drug levels, pharmacogenetic testing (PG), and molecular neuroimaging.

METHODS

In these Guidelines, we provide an in-depth review of pharmacokinetics, pharmacodynamics, and pharmacogenetics for 45 antipsychotics. Over 30 international experts in psychiatry selected studies that have measured drug concentrations in the blood (TDM), gene polymorphisms of enzymes involved in drug metabolism, or receptor/transporter occupancies in the brain (positron emission tomography (PET)).

RESULTS

Study results strongly support the use of TDM and the cytochrome P450 (CYP) genotyping and/or phenotyping to guide drug therapies. Evidence-based target ranges are available for titrating drug doses that are often supported by PET findings.

CONCLUSION

All three tools discussed in these Guidelines are essential for drug treatment. TDM goes well beyond typical indications such as unclear compliance and polypharmacy. Despite its enormous potential to optimise treatment effects, minimise side effects and ultimately reduce the global burden of diseases, personalised drug treatment has not yet become the standard of care in psychiatry.

Influence of CYP2C19 and CYP2D6 on side effects of aripiprazole and risperidone: A systematic review

Variability in hepatic cytochrome P450 (CYP) enzymes such as 2C19 and 2D6 may influence side-effect and efficacy outcomes for antipsychotics. Aripiprazole and risperidone are two commonly prescribed antipsychotics, metabolized primarily through CYP2D6. Here, we aimed to provide an overview of the effect of CYP2C19 and CYP2D6 on side-effects of aripiprazole and risperidone, and expand on existing literature by critically examining methodological issues associated with pharmacogenetic studies. A PRISMA compliant search of six electronic databases (Pubmed, PsychInfo, Embase, Central, Web of Science, and Google Scholar) identified pharmacogenetic studies on aripiprazole and risperidone. 2007 publications were first identified, of which 34 were included. Quality of literature was estimated using Newcastle-Ottowa Quality Assessment Scale (NOS) and revised Cochrane Risk of Bias tool. The average NOS score was 5.8 (range: 3-8) for risperidone literature and 5 for aripiprazole (range: 4-6). All RCTs on aripiprazole were rated as high risk of bias, and four out of six for risperidone literature. Study populations ranged from healthy volunteers to inpatient individuals in psychiatric units and included adult and pediatric samples. All n = 34 studies examined CYP2D6. Only one study genotyped for CYP2C19 and found a positive association with neurological side-effects of risperidone. Most studies did not report any relationship between CYP2D6 and any side-effect outcome. Heterogeneity between and within studies limited the ability to synthesize data and draw definitive conclusions. Studies lacked statistical power due to small sample size, selective genotyping methods, and study design. Large-scale randomized trials with multiple measurements, providing robust evidence on this topic, are suggested.

The polymorphisms of candidate pharmacokinetic and pharmacodynamic genes and their pharmacogenetic impacts on the effectiveness of risperidone maintenance therapy among Saudi children with autism

BACKGROUND

Antipsychotics, including risperidone (RIS), are frequently indicated for various autism spectrum disorder (ASD) manifestations; however, "actionable" PGx testing in psychiatry regarding antipsychotic dosing and selection has limited applications in routine clinical practice because of the lack of standard guidelines, mostly due to the inconsistency and scarcity of genetic variant data. The current study is aimed at examining the association of RIS effectiveness, according to ABC-CV and CGI indexes, with relevant pharmacokinetics (PK) and pharmacodynamics (PD) genes.

METHODS

Eighty-nine ASD children who received a consistent RIS-based regimen for at least 8 weeks were included. The Axiom PharmacoFocus Array technique was employed to generate accurate star allele-predicted phenotypes of 3 PK genes (CYP3A4, CYP3A5, and CYP2D6). Genotype calls for 5 candidate PD receptor genes (DRD1, DRD2, DRD3, HTR2C, and HTR2A) were obtained and reported as wild type, heterozygous, or homozygous for 11 variants.

RESULTS

Based on the ABC total score, 42 (47.2%) children were classified as responders, while 47 (52.8%) were classified as nonresponders. Multivariate logistic regression analyses, adjusted for nongenetic factors, suggested nonsignificant impacts of the star allele-predicted phenotypes of all 3 PK genes on improvement in ASD symptoms or CGI scores. However, significant positive or negative associations of certain PD variants involved in dopaminergic and serotonergic pathways were observed with specific ASD core and noncore symptom subdomains. Our significant polymorphism findings, mainly those in DRD2 (rs1800497, rs1799978, and rs2734841), HTR2C (rs3813929), and HTR2A (rs6311), were largely consistent with earlier findings (predictors of RIS effectiveness in adult schizophrenia patients), confirming their validity for identifying ASD children with a greater likelihood of core symptom improvement compared to noncarriers/wild types. Other novel findings of this study, such as significant improvements in DRD3 rs167771 carriers, particularly in ABC total and lethargy/social withdrawal scores, and DRD1 rs1875964 homozygotes and DRD2 rs1079598 wild types in stereotypic behavior, warrant further verification in biochemical and clinical studies to confirm their feasibility for inclusion in a PGx panel.

CONCLUSION

In conclusion, we provide evidence of potential genetic markers involved in clinical response variability to RIS therapy in ASD children. However, replication in prospective samples with greater ethnic diversity and sample sizes is necessary.

Genetic Factors Associated With Tardive Dyskinesia: From Pre-clinical Models to Clinical Studies

Tardive dyskinesia is a severe motor adverse event of antipsychotic medication, characterized by involuntary athetoid movements of the trunk, limbs, and/or orofacial areas. It affects two to ten patients under long-term administration of antipsychotics that do not subside for years even after the drug is stopped. Dopamine, serotonin, cannabinoid receptors, oxidative stress, plasticity factors, signaling cascades, as well as CYP isoenzymes and transporters have been associated with tardive dyskinesia (TD) occurrence in terms of genetic variability and metabolic capacity. Besides the factors related to the drug and the dose and patients’ clinical characteristics, a very crucial variable of TD development is individual susceptibility and genetic predisposition. This review summarizes the studies in experimental animal models and clinical studies focusing on the impact of genetic variations on TD occurrence. We identified eight genes emerging from preclinical findings that also reached statistical significance in at least one clinical study. The results of clinical studies are often conflicting and non-conclusive enough to support implementation in clinical practice.

CYP2D6 Genetic Polymorphisms and Risperidone Pharmacokinetics: A Systematic Review and Meta-analysis

BACKGROUND

Risperidone is a second-generation antipsychotic drug metabolized to an active metabolite, 9-hydroxyrisperidone, primarily by cytochrome P450 (CYP) 2D6 and to a lesser extent by CYP3A4. The extent to which drug metabolism genetics impacts risperidone and 9-hydroxyrisperidone exposure has not been clarified.

OBJECTIVE

A systematic review and meta-analysis evaluated the impact of genetically defined CYP2D6 function on risperidone pharmacokinetics applying a standardized genotype-phenotype translation system.

METHODS

A comprehensive electronic database search identified studies reporting relationships between genetically determined CYP2D6 metabolism and risperidone pharmacokinetic properties. The exposure of risperidone or active moiety (risperidone + 9-hydroxyrisperidone) was measured by dose-adjusted steady-state serum or plasma concentration or area under the concentration-time curve as primary outcomes. Subjects were assigned to CYP2D6 poor metabolizer, intermediate metabolizer, normal metabolizer, or ultrarapid metabolizer groups using a standardized genotype-phenotype translation method. Effect sizes between groups were pooled and stratified by single or multiple dosing regimens.

RESULTS

A total of 15 studies involving 2125 adult subjects were included in the meta-analysis. Following multiple-dose oral administration, compared with CYP2D6 normal metabolizers, the risperidone dose-adjusted steady-state serum/plasma concentration was 2.35-fold higher in intermediate metabolizers (95% confidence interval [CI] 1.77-3.13, p<0.0001) and 6.20-fold higher in poor metabolizers (95% CI 5.05-7.62, p<0.0001); the active moiety dose-adjusted steady-state concentration was 1.18-fold higher in intermediate metabolizers (95% CI 1.11-1.25, p<0.0001) and 1.44-fold higher in poor metabolizers (95% CI 1.23-1.69, p<0.0001). Higher area under the concentration-time curve of risperidone and active moiety was also found in single-dose studies.

CONCLUSION

Genetically defined impaired CYP2D6 activity is associated with increased exposure of both risperidone and risperidone + 9-hydroxyrisperidone in adults receiving oral formulations. Additional studies are needed to quantify the clinical impact of these relationships.

Exploring Biologic Predictors Response Disparities to Atypical Antipsychotics among Blacks: A Quasi-Systematic Review

Purpose

Management of schizophrenia among Blacks in the United States is affected by persistent disparities. This review explored response to atypical antipsychotics among Blacks compared with other groups to assess systematic variation that may contribute to disparities.

Methods

We conducted a quasi-systematic review of studies reporting response to atypical antipsychotics among Blacks compared with other groups, including effects of genetic variation.

Results

Of 48 identified research articles, 29 assessed differences in outcomes without inclusion of genetic variation and 20 explored effects of genetic variation; of note: one article included both types of data. Analysis of the 29 papers with clinical outcomes only suggests that while data on efficacy and risk of movement disorders were heterogeneous, findings indicate increased risk of metabolic effects and neutropenia among Blacks. Of the 20 articles exploring effects of genetic variation, allelic or genotypic variations involving several genes were associated with altered efficacy or safety among Blacks but not Whites, including risk of decreased response involving variation in DRD4 and DRD1, and improved efficacy associated with variants in DRD2, COMT, and RGS4. Others showed significant improvement in treatment response only among Whites, including variation in DTNBP1, DRD4, and GNB3.

Conclusions

The current analysis can help tailor management among Blacks using an atypical antipsychotic. Heterogeneity in genetic variation effects and response allele frequency suggests that pharmacogenetics approaches for atypical antipsychotics will need to explicitly incorporate race and ethnicity.

Genetic predictors of antipsychotic response to lurasidone identified in a genome wide association study and by schizophrenia risk genes

Biomarkers which predict response to atypical antipsychotic drugs (AAPDs) increases their benefit/risk ratio. We sought to identify common variants in genes which predict response to lurasidone, an AAPD, by associating genome-wide association study (GWAS) data and changes (Δ) in Positive And Negative Syndrome Scale (PANSS) scores from two 6-week randomized, placebo-controlled trials of lurasidone in schizophrenia (SCZ) patients. We also included SCZ risk SNPs identified by the Psychiatric Genomics Consortium using a polygenic risk analysis. The top genomic loci, with uncorrected p<10^-4, include: 1) synaptic adhesion (PTPRD, LRRC4C, NRXN1, ILIRAPL1, SLITRK1) and scaffolding (MAGI1, MAGI2, NBEA) genes, both essential for synaptic function; 2) other synaptic plasticity-related genes (NRG1/3 and KALRN); 3) the neuron-specific RNA splicing regulator, RBFOX1; and 4) ion channel genes, e.g. KCNA10, KCNAB1, KCNK9 and CACNA2D3). Some genes predicted response for patients with both European and African Ancestries. We replicated some SNPs reported to predict response to other atypical APDs in other GWAS. Although none of the biomarkers reached genome-wide significance, many of the genes and associated pathways have previously been linked to SCZ. Two polygenic modeling approaches, GCTA-GREML and PLINK-Polygenic Risk Score, demonstrated that some risk genes related to neurodevelopment, synaptic biology, immune response, and histones, also contributed to prediction of response. The top hits predicting response to lurasidone did not predict improvement with placebo. This is the first evidence from clinical trials that SCZ risk SNPs are related to clinical response to an AAPD. These results need to be replicated in an independent sample.

A computational algorithm for personalized medicine in schizophrenia

Despite advances in sequencing candidate genes and whole genomes, no method has accurately predicted who will or will not benefit from a specific antipsychotic medication among patients with schizophrenia. We propose a computational algorithm that utilizes a person-centered approach that directly identifies individual patients who will respond to a specific antipsychotic medication. The algorithm was applied to the data obtained from the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) study. The predictors were either (1) 13 single-nucleotide polymorphisms (SNPs) and 53 baseline variables or (2) 25 SNPs and the same 53 baseline variables, depending on the existing findings and data availability. The outcome variables were either (1) improvement in the Positive and Negative Syndrome Scale (PANSS) (Yes/No) or (2) completion of phase 1/1A (Yes/No). Each of those four predictor-outcome combinations was tried for each of the five antipsychotic medications (Perphenazine, Olanzapine, Quetiapine, Risperidone, and Ziprasidone), leading to 20 prediction experiments. For 18 out of 20 experiments, all three performance measures were greater than 0.50 (sensitivity 0.51-0.79, specificity 0.52-0.79, accuracy 0.52-0.74). Notably, the model provided a promising prediction for Ziprasidone for the case involving completion of phase 1/1A (Yes/No) predicted by 13 SNPs and 53 baseline variables (sensitivity 0.75, specificity 0.74, accuracy 0.74). The proposed algorithm simultaneously used both genetic information and clinical profiles to predict individual patients' response to antipsychotic medications. As the method is not disease-specific but a general algorithm, it can be easily adopted in many other clinical practices for personalized medicine.

Pharmacogenetic tests for antipsychotic medications: clinical implications and considerations

Optimizing antipsychotic pharmacotherapy is often challenging due to significant variability in effectiveness and tolerability. Genetic factors influencing pharmacokinetics and pharmacodynamics may contribute to some of this variability. Research studies have characterized these pharmacogenetic relationships, and some genetic markers are now available as clinical tests. These advances in pharmacogenetics research and test availability have great potential to improve clinical outcomes and quality of life in psychiatric patients. For clinicians considering using pharmacogenetics, it is important to understand the clinical implications and also the limitations of markers included in currently available tests. This review focuses on pharmacokinetic and pharmacodynamic gene variants that are currently available in commercial genetic testing panels. Associations of these variants with clinical efficacy and adverse effects, as well as other clinical implications, in antipsychotic pharmacotherapy are discussed.

Pharmacogenetic tests for antipsychotic medications: clinical implications and considerations

Optimizing antipsychotic pharmacotherapy is often challenging due to significant variability in effectiveness and tolerability. Genetic factors influencing pharmacokinetics and pharmacodynamics may contribute to some of this variability. Research studies have characterized these pharmacogenetic relationships, and some genetic markers are now available as clinical tests. These advances in pharmacogenetics research and test availability have great potential to improve clinical outcomes and quality of life in psychiatric patients. For clinicians considering using pharmacogenetics, it is important to understand the clinical implications and also the limitations of markers included in currently available tests. This review focuses on pharmacokinetic and pharmacodynamic gene variants that are currently available in commercial genetic testing panels. Associations of these variants with clinical efficacy and adverse effects, as well as other clinical implications, in antipsychotic pharmacotherapy are discussed.

WEIGHT GAIN AND ANTIPSYCHOTICS. DATA FROM EUFEST STUDY

Context

Schizophrenia is a chronic disease most frequently necessitating lifelong antipsychotic treatment. Selecting which antipsychotic is to be prescribed in an individual schizophrenia patient represents an important clinical decision that need to take into account efficacy and side effects.

Objective

Evaluating weight gain related with one year antipsychotic treatment in antipsychotic naive first-episode schizophrenia patients.

Design

This study is an analysis of weight gain associated with typical or atypical antipsychotics used in European First Episode Schizophrenia Trial (EUFEST) study.

Subjects and Methods

113 first episode naïve antipsychotic schizophrenia patients included in EUFEST - Romanian cohort, who were randomized to one of the 5 treatment arms. Weight was obtained at baseline, 3, 6, 9 and 12 months for the 5 antipsychotics (typical-Haloperidol; atypical-Olanzapine, Amisulpride, Ziprasidone, Quetiapine).

Results

There are no statistically significant differences between groups treated with typical or atypical antipsychotics or between any individual antipsychotics concerning weight gain during the study. Weight gain was the highest in the first 3 months (57.49%) for all the studied neuroleptics. At the end of the study, the less increase was observed with ziprasidone (3.87 kg) and the highest with olanzapine (9.83 kg).

Conclusion

Increase in weight has taken place for each individual neuroleptic, but also as a group (all neuroleptics) in the first three months (57.49%). Therefore, we should address the issue of weight gain with great care, especially in first period of antipsychotic administration, in order to fast deploy intervention tailored to maintain pre-treatment weight.

Pharmacogenomics of neuropsychiatric disorders: analysis of genetic variability in 162 identified neuroreceptors using 1000 Genomes Project data

BACKGROUND

Neuroreceptors are considered to be primary drug targets and their abrupt signaling is a notable cause of interindividual drug response variability and treatment failure for complex neuropsychiatric diseases. In view of recent evidence, it is believed that common genetic risk factors mainly highly polymorphic neuroreceptors are being shared among neuropsychiatric disorders.

MATERIALS & METHODS

We identified 162 neuroreceptors from the 639 known receptors in Homo sapiens and investigated 231,683 SNPs using 1000 Genomes Project data and evaluated their biological effect using in silico tools including RegulomeDB, SIFT, PolyPhen-2 and CAROL. Furthermore, data from the 1000 Genomes Project was utilized to retrieve minor allele frequency and calculate pairwise logartithm of the odds score among these SNPs for African, American, Asian and European populations separately as well as when combined together using Haploview v4.2. LRTag was used to identify tagSNPs in populations.

RESULTS

A total of 52,381 (22.60%) SNPs were predicted as functionally important genetic variations. We identified sets of 603, 495, 450, 453 and 646 informative tagSNPs for African, American, Asian, European and combined populations, respectively. We propose construction of a 'neuroreceptor variants array' with these informative SNPs for future pharmacogenomic studies of neuropsychiatric disorders.

CONCLUSION

Such an approach might improve genotype-phenotype correlation across different populations and lead to identification of reliable genetic markers and novel drug targets. Integration of these SNPs in literature would further provide evidence relevant to underlying mechanisms of genetics based nosology, pathophysiology and development of new drugs for the treatment of neuropsychiatric disorders.

Clinical significance of pharmacogenomic studies in tardive dyskinesia associated with patients with psychiatric disorders

Pharmacogenomics is the study of the effects of genetic polymorphisms on medication pharmacokinetics and pharmacodynamics. It offers advantages in predicting drug efficacy and/or toxicity and has already changed clinical practice in many fields of medicine. Tardive dyskinesia (TD) is a movement disorder that rarely remits and poses significant social stigma and physical discomfort for the patient. Pharmacokinetic studies show an association between cytochrome P450 enzyme-determined poor metabolizer status and elevated serum antipsychotic and metabolite levels. However, few prospective studies have shown this to correlate with the occurrence of TD. Many retrospective, case-control and cross-sectional studies have examined the association of cytochrome P450 enzyme, dopamine (receptor, metabolizer and transporter), serotonin (receptor and transporter), and oxidative stress enzyme gene polymorphisms with the occurrence and severity of TD. These studies have produced conflicting and confusing results secondary to heterogeneous inclusion criteria and other patient characteristics that also act as confounding factors. This paper aims to review and summarize the pharmacogenetic findings in antipsychotic-associated TD and assess its clinical significance for psychiatry patients. In addition, we hope to provide insight into areas that need further research.

Effect of polymorphisms on the pharmacokinetics, pharmacodynamics, and safety of risperidone in healthy volunteers

OBJECTIVE

To identify genetic markers capable of predicting the pharmacokinetics, pharmacodynamics, and adverse effects of risperidone.

METHODS

Genotyping was performed in 70 healthy volunteers receiving a single 1mg oral dose of risperidone. Risperidone and hydroxyrisperidone plasma levels were measured using high-performance liquid chromatography combined with tandem mass spectrometry.Prolactin concentration was quantified by direct chemiluminescence.

RESULTS

Poor CYP2D6 metabolizers showed higher risperidone Cmax, area under the curve (AUC), and t1/2, as well as lower clearance. They also showed lower Cmax and AUC and higher t1/2 for hydroxyrisperidone. Furthermore, individuals with a mutant VKORC1 genotype had a lower risperidone AUC and t1/2 and higher clearance. The hydroxyrisperidone AUC was lower in individuals with the COMT mutant genotype. Risperidone increased prolactin levels (iAUC and iCmax), which were higher in women than in men. The most frequent reactions were somnolence (47.1%), headache (21.4%), and dizziness (17.1%). Women had neurological effects and headache more frequently than men. The incidence of headache was associated with polymorphisms in the AGTR1 and NAT2; neurological effects were associated with CYP2C19.

CONCLUSIONS

Differences in the pharmacokinetics of risperidone are due to polymorphisms in CYP2D6, COMT, and VKORC1. Differences in adverse reactions can be explained by gender and polymorphisms in CYP2C19, AGTR1, and NAT2.

CYP450 pharmacogenetic treatment strategies for antipsychotics: a review of the evidence

Although a number of first- and second-generation antipsychotics are available, achieving optimal therapeutic response for patients with schizophrenia can be challenging. The presence of polymorphic alleles for cytochrome P (CYP) 450 may result in lack of expression, altered levels of expression, or altered function of CYP450 enzymes. CYP2D6, CYP1A2, and CYP3A4/5 are major enzymes in the metabolism of antipsychotics and polymorphisms of alleles for these proteins are associated with altered plasma levels. Consequently, standard dosing may result in drug plasma concentrations that are subtherapeutic or toxic in some patients. Patient CYP450 genotype testing can predict altered pharmacokinetics, and is currently available and relatively inexpensive. Evidence-based guidelines provide dose recommendations for some antipsychotics. To date few studies have demonstrated a significant association with genotype-guided antipsychotic use and clinical efficacy. However, many studies have been small, retrospective or cohort designs, and many have not been adequately powered. Numerous studies have shown a significant association between genotype and adverse effects, such as CYP2D6 polymorphisms and tardive dyskinesia. This review summarizes evidence for the role of CYP450 genetic variants in the response to antipsychotic medications and the clinical implications of pharmacogenetics in the management of patients with schizophrenia.

Pharmacogenetics of antipsychotic-induced weight gain: review and clinical implications

Second-generation antipsychotics (SGAs), such as risperidone, clozapine and olanzapine, are the most common drug treatments for schizophrenia. SGAs presented an advantage over first-generation antipsychotics (FGAs), particularly regarding avoidance of extrapyramidal symptoms. However, most SGAs, and to a lesser degree FGAs, are linked to substantial weight gain. This substantial weight gain is a leading factor in patient non-compliance and poses significant risk of diabetes, lipid abnormalities (that is, metabolic syndrome) and cardiovascular events including sudden death. The purpose of this article is to review the advances made in the field of pharmacogenetics of antipsychotic-induced weight gain (AIWG). We included all published association studies in AIWG from December 2006 to date using the Medline and ISI web of knowledge databases. There has been considerable progress reaffirming previous findings and discovery of novel genetic factors. The HTR2C and leptin genes are among the most promising, and new evidence suggests that the DRD2, TNF, SNAP-25 and MC4R genes are also prominent risk factors. Further promising findings have been reported in novel susceptibility genes, such as CNR1, MDR1, ADRA1A and INSIG2. More research is required before genetically informed, personalized medicine can be applied to antipsychotic treatment; nevertheless, inroads have been made towards assessing genetic liability and plausible clinical application.

The promise and reality of pharmacogenetics in psychiatry

Existing psychotropic medications for the treatment of mental illnesses, including antidepressants, mood stabilizers, and antipsychotics, are clinically suboptimal. They are effective in only a subset of patients or produce partial responses, and they are often associated with debilitating side effects that discourage adherence. There is growing enthusiasm in the promise of pharmacogenetics to personalize the use of these treatments to maximize their efficacy and tolerability; however, there is still a long way to go before this promise becomes a reality. This article reviews the progress that has been made in research toward understanding how genetic factors influence psychotropic drug responses and the challenges that lie ahead in translating the research findings into clinical practices that yield tangible benefits for patients with mental illnesses.

Pharmacogenetics and schizophrenia

The wide interindividual variability in clinical response and tolerability of antipsychotic medications has led investigators to postulate that these variabilities may be under genetic control. Although not always consistent, there are promising indications from emergent pharmacogenetic studies that efficacy of antipsychotic medications for the various symptom domains of psychopathology in schizophrenia may be genetically regulated. This is an encouraging approach. Moreover, there are also suggestive findings that the side-effect profiles of second-generation antipsychotic medications and their propensity to cause weight gain and glucose and lipid abnormalities as well as tardive dyskinesia may be related to pharmacogenetic factors in this patient population. Ultimately, such approaches could drive choices of antipsychotic medication based on the likelihood of clinical response and development of side effects in light of a particular patient's genetic profile. In the future, this targeted approach (personalized medicine) may become informative for clinicians choosing an antipsychotic medication for an individual patient with schizophrenia.

Impact of race on efficacy and safety during treatment with olanzapine in schizophrenia, schizophreniform or schizoaffective disorder

BACKGROUND

To examine potential differences in efficacy and safety of treatment with olanzapine in patients with schizophrenia of white and black descent.

METHODS

A post-hoc, pooled analysis of 6 randomized, double-blind trials in the treatment of schizophrenia, schizophreniform disorder, or schizoaffective disorder compared white (N = 605) and black (N = 375) patients treated with olanzapine (5 to 20 mg/day) for 24 to 28 weeks. Efficacy measurements included the Positive and Negative Syndrome Scale (PANSS) total score; and positive, negative, and general psychopathology scores; and the Clinical Global Impression of Severity (CGI-S) scores at 6 months. Safety measures included differences in the frequencies of adverse events along with measures of extrapyramidal symptoms, weight, glucose, and lipid changes over time.

RESULTS

51% of black patients and 45% of white patients experienced early study discontinuation (P = .133). Of those who discontinued, significantly more white patients experienced psychiatric worsening (P = .002) while significantly more black patients discontinued for reasons other than efficacy or tolerability (P = .014). Discontinuation for intolerability was not different between groups (P = .320). For the estimated change in PANSS total score over 6 months, there was no significant difference in efficacy between white and black patients (P = .928), nor on the estimated PANSS positive (P = .435), negative (P = .756) or general psychopathology (P = .165) scores. Overall, there was no significant difference in the change in CGI-S score between groups from baseline to endpoint (P = .979). Weight change was not significantly different in white and black patients over 6 months (P = .127). However, mean weight change was significantly greater in black versus white patients at Weeks 12 and 20 only (P = .028 and P = .026, respectively). Additionally, a significantly greater percentage of black patients experienced clinically significant weight gain (≥ 7%) at anytime compared to white patients (36.1% vs. 30.4%, P = .021). Changes across metabolic parameters (combined fasting and random lipids and glucose) were also not significantly different between groups, with the exception of a greater categorical change in total cholesterol from borderline to high among white subjects and a categorical change from normal to low in high density lipoprotein (HDL) cholesterol among white males.

CONCLUSIONS

The findings did not demonstrate overall substantive differences in efficacy or safety between white and black patients diagnosed with schizophrenia or related disorders treated with olanzapine. However, a significantly greater percentage of black patients (36.1%) experienced clinically significant weight gain compared to white patients (30.4%).

Variants in the ITPA gene protect against ribavirin-induced hemolytic anemia and decrease the need for ribavirin dose reduction

BACKGROUND & AIMS

In a genome-wide association study of patients being treated for chronic hepatitis C, 2 functional variants in ITPA that cause inosine triphosphatase (ITPase) deficiency were shown to protect against ribavirin (RBV)-induced hemolytic anemia during early stages of treatment. We aimed to replicate this finding in an independent cohort from the Study of Viral Resistance to Antiviral Therapy of Chronic Hepatitis C and to investigate the effects of these variants beyond week 4.

METHODS

Genetic material was available from 318 patients. The ITPA variants, rs1127354 (exon 2, P32T) and rs7270101 (intron 2, splice altering), were genotyped and tested for association with hemoglobin (Hb) reduction at week 4. An ITPase deficiency variable was defined that combined both ITPA variants according to documented effect on ITPase activity. We investigated the impact of ITPA variants on Hb levels over the course of therapy and on the need for RBV dose reduction.

RESULTS

The final analysis included 304 patients with genotype 1 hepatitis C virus (167 white patients and 137 black patients). The polymorphisms rs1127354 and rs7270101 were associated with Hb reduction at week 4 (P = 3.1 × 10(-13) and 1.3 × 10(-3), respectively). The minor alleles of each variant protected against Hb reduction. Combining the variants into the ITPase deficiency variable strengthened the association (P = 2.4 × 10(-18)). The ITPase deficiency variable was associated with lower rates of anemia over the entire treatment period (48 weeks), as well as a lower rate of anemia-related RBV dose reduction (hazard ratio, 0.52; P = .0037). No association with sustained virological response was observed.

CONCLUSIONS

Two polymorphisms that cause ITPase deficiency are strongly associated with protection from RBV-induced hemolytic anemia and decrease the need for RBV dose reduction.

Pharmacogenetics of tomorrow: the 1 + 1 = 3 principle

Disappointing results from replicating pharmacogenetic association studies have prompted the search for novel statistical techniques to analyze the data, while taking into account the biological complexity underlying drug response. Two of these techniques – multifactor dimensionality reduction and classification and regression tree analysis – will probably be applied in increasing numbers of future pharmacogenetic studies. In this article, we describe the concepts underlying both techniques and illustrate their application in a recent pharmacogenetic study.

Pharmacogenetic testing and therapeutic drug monitoring are complementary tools for optimal individualization of drug therapy

Genetic factors contribute to the phenotype of drug response, but the translation of pharmacogenetic outcomes into drug discovery, drug development or clinical practice has proved to be surprisingly disappointing. Despite significant progress in pharmacogenetic research, only a few drugs, such as cetuximab, dasatinib, maraviroc and trastuzumab, require a pharmacogenetic test before being prescribed. There are several gaps that limit the application of pharmacogenetics based upon the complex nature of the drug response itself. First, pharmacogenetic tests could be more clinically applicable if they included a comprehensive survey of variation in the human genome and took into account the multigenic nature of many phenotypes of drug disposition and response. Unfortunately, much of the existing research in this area has been hampered by limitations in study designs and the nonoptimal selection of gene variants. Secondly, although responses to drugs can be influenced by the environment, only fragmentary information is currently available on how the interplay between genetics and environment affects drug response. Third, the use of a pharmacogenetic test as a standard of care for drug therapy has to overcome significant scientific, economic, commercial, political and educational barriers, among others, in order for clinically useful information to be effectively communicated to practitioners and patients. Meanwhile, the lack of efficacy is in this process is quite as costly as drug toxicity, especially for very expensive drugs, and there is a widespread need for clinically and commercially robust pharmacogenetic testing to be applied. In this complex scenario, therapeutic drug monitoring of parent drugs and/or metabolites, alone or combined with available pharmacogenetic tests, may be an alternative or complementary approach when attempts are made to individualize dosing regimen, maximize drug efficacy and enhance drug safety with certain drugs and populations (e.g. antidepressants in older people).

The intersection of pharmacology, imaging, and genetics in the development of personalized medicine

We currently rely on large randomized trials and meta-analyses to make clinical decisions; this places us at a risk of discarding subgroup or individually specific treatment options owing to their failure to prove efficacious across entire populations. There is a new era emerging in personalized medicine that will focus on individual differences that are not evident phenomenologically. Much research is directed towards identifying genes, endophenotypes, and biomarkers of disease that will facilitate diagnosis and predict treatment outcome. We are at the threshold of being able to predict treatment response, primarily through genetics and neuroimaging. In this review we discuss the most promising markers of treatment response and adverse effects emerging from the areas of pharmacogenetics and neuroimaging in depression and schizophrenia.

Antipsychotics and schizophrenia: from efficacy and effectiveness to clinical decision-making

OBJECTIVE

To comprehensively review the 2 recent and large antipsychotic effectiveness trials for treatment of schizophrenia: the United Kingdom's Cost Utility of the Latest Antipsychotic Drugs in Schizophrenia Study (CUtLASS), and the National Institute of Mental Health-initiated Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) schizophrenia trial.

METHOD

We present a review of the rationale, methodology, and findings to date from the CUtLASS and CATIE schizophrenia trials, including all primary and secondary outcomes.

RESULTS

The primary findings from both trials, CUtLASS and CATIE, suggest that first-generation antipsychotics (FGAs) and second-generation antipsychotics (SGAs) are equally effective in the treatment of schizophrenia. The exception is in treatment-resistant populations where clozapine exhibits superiority, compared with other SGAs. In the CATIE trial, there is a suggestion that olanzapine is superior in effectiveness, compared with other nonclozapine SGAs, although this seems to be mediated by past history of olanzapine use, and carries with it increased weight gain and metabolic adverse events. From a cost-effectiveness perspective, there is no evidence that SGAs are superior to FGAs, with findings suggesting the possibility that FGAs may be superior.

CONCLUSION

Past efficacy trials have strongly supported the position that SGAs are superior to FGAs in the treatment of schizophrenia and in side effect profile. Two large independent effectiveness trials, CUtLASS and CATIE, have offered a strong challenge to these claims. Both suggest that SGAs, except clozapine in the treatment-resistant population, offer little, if any, clinical benefits, and, moreover, harbour their own significant side effects.

The promise and reality of pharmacogenetics in psychiatry

Existing psychotropic medications for the treatment of mental illnesses, including antidepressants, mood stabilizers, and antipsychotics, are clinically suboptimal. They are effective in only a subset of patients or produce partial responses, and they are often associated with debilitating side effects that discourage adherence. There is growing enthusiasm in the promise of pharmacogenetics to personalize the use of these treatments to maximize their efficacy and tolerability; however, there is still a long way to go before this promise becomes a reality. This article reviews the progress that has been made in research toward understanding how genetic factors influence psychotropic drug responses and the challenges that lie ahead in translating the research findings into clinical practices that yield tangible benefits for patients with mental illnesses.

A candidate gene study of Tardive dyskinesia in the CATIE schizophrenia trial

Tardive dyskinesia (TD) is a movement disorder characterized by involuntary oro-facial, limb, and truncal movements. As a genetic basis for inter-individual variation is assumed, there have been a sizeable number of candidate gene studies. All subjects met diagnostic criteria for schizophrenia and were randomized to receive antipsychotic medications as participants in the Clinical Antipsychotic Trials of Intervention Effectiveness project (CATIE). TD was assessed via the Abnormal Involuntary Movement Scale at regular intervals. Probable TD was defined as meeting Schooler-Kane criteria at any scheduled CATIE visit (207/710 subjects, 29.2%). A total of 128 candidate genes were studied in 710 subjects-2,580 SNPs in 118 candidate genes selected from the literature (e.g., dopamine, serotonin, glutamate, and GABA pathways) and composite genotypes for 10 drug-metabolizing enzymes. No single marker or haplotype association reached statistical significance after adjustment for multiple comparisons. Thus, we found no support for either novel or prior associations from the literature.

Pharmacogenetics of antipsychotic response in the CATIE trial: a candidate gene analysis

The Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) Phase 1 Schizophrenia trial compared the effectiveness of one typical and four atypical antipsychotic medications. Although trials such as CATIE present important opportunities for pharmacogenetics research, the very richness of the clinical data presents challenges for statistical interpretation, and in particular the risk that data mining will lead to false-positive discoveries. For this reason, it is both misleading and unhelpful to perpetuate the current practice of reporting association results for these trials one gene at a time, ignoring the fact that multiple gene-by-phenotype tests are being carried out on the same data set. On the other hand, suggestive associations in such trials may lead to new hypotheses that can be tested through both replication efforts and biological experimentation. The appropriate handling of these forms of data therefore requires dissemination of association statistics without undue emphasis on select findings. Here we attempt to illustrate this approach by presenting association statistics for 2769 polymorphisms in 118 candidate genes evaluated for 21 pharmacogenetic phenotypes. On current evidence it is impossible to know which of these associations may be real, although in total they form a valuable resource that is immediately available to the scientific community.