Intuitive pharmacogenetic dosing of risperidone according to CYP2D6 phenotype extrapolated from genotype in a cohort of first episode psychosis patients

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.

Association of CYP2C19 and CYP2D6 Poor and Intermediate Metabolizer Status With Antidepressant and Antipsychotic Exposure: A Systematic Review and Meta-analysis

IMPORTANCE

Precise estimation of the drug metabolism capacity for individual patients is crucial for adequate dose personalization.

OBJECTIVE

To quantify the difference in the antipsychotic and antidepressant exposure among patients with genetically associated CYP2C19 and CYP2D6 poor (PM), intermediate (IM), and normal (NM) metabolizers.

DATA SOURCES

PubMed, Clinicaltrialsregister.eu, ClinicalTrials.gov, International Clinical Trials Registry Platform, and CENTRAL databases were screened for studies from January 1, 1990, to June 30, 2020, with no language restrictions.

STUDY SELECTION

Two independent reviewers performed study screening and assessed the following inclusion criteria: (1) appropriate CYP2C19 or CYP2D6 genotyping was performed, (2) genotype-based classification into CYP2C19 or CYP2D6 NM, IM, and PM categories was possible, and (3) 3 patients per metabolizer category were available.

DATA EXTRACTION AND SYNTHESIS

The Meta-analysis of Observational Studies in Epidemiology (MOOSE) guidelines were followed for extracting data and quality, validity, and risk of bias assessments. A fixed-effects model was used for pooling the effect sizes of the included studies.

MAIN OUTCOMES AND MEASURES

Drug exposure was measured as (1) dose-normalized area under the plasma level (time) curve, (2) dose-normalized steady-state plasma level, or (3) reciprocal apparent total drug clearance. The ratio of means (RoM) was calculated by dividing the mean drug exposure for PM, IM, or pooled PM plus IM categories by the mean drug exposure for the NM category.

RESULTS

Based on the data derived from 94 unique studies and 8379 unique individuals, the most profound differences were observed in the patients treated with aripiprazole (CYP2D6 PM plus IM vs NM RoM, 1.48; 95% CI, 1.41-1.57; 12 studies; 1038 patients), haloperidol lactate (CYP2D6 PM vs NM RoM, 1.68; 95% CI, 1.40-2.02; 9 studies; 423 patients), risperidone (CYP2D6 PM plus IM vs NM RoM, 1.36; 95% CI, 1.28-1.44; 23 studies; 1492 patients), escitalopram oxalate (CYP2C19 PM vs NM, RoM, 2.63; 95% CI, 2.40-2.89; 4 studies; 1262 patients), and sertraline hydrochloride (CYP2C19 IM vs NM RoM, 1.38; 95% CI, 1.27-1.51; 3 studies; 917 patients). Exposure differences were also observed for clozapine, quetiapine fumarate, amitriptyline hydrochloride, mirtazapine, nortriptyline hydrochloride, fluoxetine hydrochloride, fluvoxamine maleate, paroxetine hydrochloride, and venlafaxine hydrochloride; however, these differences were marginal, ambiguous, or based on less than 3 independent studies.

CONCLUSIONS AND RELEVANCE

In this systematic review and meta-analysis, the association between CYP2C19/CYP2D6 genotype and drug levels of several psychiatric drugs was quantified with sufficient precision as to be useful as a scientific foundation for CYP2D6/CYP2C19 genotype-based dosing recommendations.

The usefulness of Olanzapine plasma concentrations in monitoring treatment efficacy and metabolic disturbances in first-episode psychosis

INTRODUCTION

The role of Olanzapine therapeutic drug monitoring is controversial. The present study explores the associations of Olanzapine plasma concentrations with clinical response and metabolic side effects in first episode psychosis (FEP) after 2 months of treatment.

METHODS

Forty-seven patients were included. Improvement in clinical symptomatology was assessed using the PANSS. Metabolic assessment included weight, blood pressure, waist circumference, blood glucose, total cholesterol, high-density lipoprotein, low-density lipoprotein, and triglycerides.

RESULTS

The Olanzapine plasma concentrations after 2 months of treatment were positively correlated with weight gain (r = 0.49, p = 0.003), and a concentration > 23.28 ng/mL was identified as a positive predictor of weight gain (≥ 7%). The Olanzapine concentration to dose (C/D) ratio was positively correlated with the percentage of improvement in the total PANSS (r = 0.46, p = 0.004), and a C/D ratio > 2.12 was identified as a positive predictor of a good response (percentage of improvement > 30%) after 2 months of treatment. We also identified several factors that could alter Olanzapine pharmacokinetics: gender (p = 0.03), diagnosis (p = 0.05), smoking habit (p = 0.05), and co-medications such as valproic acid (p = 0.05) and anxiolytics (p = 0.01).

DISCUSSION

In conclusion, our results suggest that therapeutic drug monitoring of Olanzapine could be helpful to evaluate therapeutic efficacy and metabolic dysfunction in FEP patients treated with Olanzapine.

The polymorphic variants DRD2 rs1800497 and ABCB1 3435C>T are associated with antipsychotic safety parameters in adolescents with an acute psychotic episode: the results of a pilot study

Children and adolescents are more likely than adults to experience adverse side effects when taking antipsychotics. Pharmacogenetic testing allows one to more accurately choose the initial dose of a drug. The genes of pharmacokinetic factors have been shown to be of high prognostic value for the safety of antipsychotics in adults.

Patients and methods. The study enrolled 36 adolescents (58.3% male) (mean age, 14.83±1.84 years). All the patients took an antipsychotic. The follow-up lasted 28 days. On 14 and 28 days of treatment, its efficiency and safety were evaluated using the Children's Global Assessment Scale (CGAS), the Positive and Negative Syndrome Scale (PANSS), the Udvalg for Kliniske Undersњgelser Side Effects Rating Scale (UKU-SERS), the Simpson-Angus Scale (SAS), and the Barnes Akathisia Rating Scale (BARS). The patients were genotyped for CYP3A4*22, CYP3A5*3, CYP2D6*4, *9, *10, ABCB1 1236C>T, 2677G>T/A, 3435C>T, DRD2 rs1800497, DRD4 rs1800955, and HTR2A rs6313.

Results and discussion. The decrease in the mean score of the PANSS subscale “Productive symptoms” was more pronounced in carriers of the DRD2 rs1800497 polymorphic variant (-6.5 [-10.25; -3.75] vs -3 [-6.5; -2 ] on 14 day (p=0.028) and (-11 [-13; -9.5] vs -5 [-9; -3.5] on 28 day (p=0.001) compared to baseline. The carriage of ABCB1 3435CT+TT was associated with worse tolerance to pharmacotherapy on 14 day (the total score of the UKU-SERS M, 8 [3; 11.75] vs M, 2 [1; 6]; p=0.034). The carriers of DRD2 rs1800497 reported a greater severity of antipsychotic-induced neurological disorders (UKU-SERS subscale score M, 1 [0; 2.25] vs M 0 [0; 1]; p=0.029).

Conclusion. The polymorphic variants DRD2 rs1800497 and ABCB1 3435C>T were established to be significantly associated with the efficacy and safety of antipsychotics in adolescents with an acute psychotic episode.

Pharmacogenetics of antipsychotics in adolescents with acute psychotic episode during first 14 days after admission: effectiveness and safety evaluation

Objectives Prediction of the antipsychotic's effectiveness is a relevant topic in the field of personalized medicine. Methods The research design of this study is a prospective observation with posthoc analysis of associations of genetic polymorphisms with safety parameters and effectiveness of antipsychotic therapy. We observed 53 adolescents with an acute psychotic episode which were prescribed antipsychotics for 14 days. We evaluated the effectiveness of antipsychotics with the Positive and Negative Symptoms Scale and the safety with the UKU Side Effects Rating Scale, Simpson-Angus Scale, and Barnes Akathisia rating scale. We genotyped CYP3A4*22 (rs2740574), CYP3A5*3 (6986A>G, rs7767746), CYP2D6*4, *9, *10 (rs3892097, rs1065852), ABCB1 1236C>T (rs1128503), 2677G>T/A (rs2032582), 3435C>T (rs1045642), DRD2 (rs1800497), DRD4 (rs1800955), HTR2A (rs6313) by the real-time polymerase chain reaction method. Results We found significantly more frequent "increased dream activity" between CYP2D6 intermediate metabolizers and normal metabolizers (54 vs. 22%; p=0.043). The «increased duration of sleep» was more often observed in homozygotes TT of ABCB1 2677G>T/A (50 vs. 15.8%, p=0.006) and TT of 3435C>T (41.7 vs. 8.2%, p=0.007). Conclusions We found that CYP2D6 and ABCB1 polymorphisms were associated with the safety of antipsychotics in adolescents with an acute psychotic episode.

Personalized medicine begins with the phenotype: identifying antipsychotic response phenotypes in a first-episode psychosis cohort

AIMS

Here, we present a clustering strategy to identify phenotypes of antipsychotic (AP) response by using longitudinal data from patients presenting first-episode psychosis (FEP).

METHOD

One hundred and ninety FEP with complete data were selected from the PEPs project. The efficacy was assessed using total PANSS, and adverse effects using total UKU, during one-year follow-up. We used the Klm3D method to cluster longitudinal data.

RESULTS

We identified four clusters: cluster A, drug not toxic and beneficial; cluster B, drug beneficial but toxic; cluster C, drug neither toxic nor beneficial; and cluster D, drug toxic and not beneficial. These groups significantly differ in baseline demographics, clinical, and neuropsychological characteristics (PAS, total PANSS, DUP, insight, pIQ, age of onset, cocaine use and family history of mental illness).

CONCLUSIONS

The results presented here allow the identification of phenotypes of AP response that differ in well-known simple and classic clinical variables opening the door to clinical prediction and application of personalized medicine.

A pathway-driven predictive model of tramadol pharmacogenetics

Predicting metabolizer phenotype (MP) is typically performed using data from a single gene. Cytochrome p450 family 2 subfamily D polypeptide 6 (CYP2D6) is considered the primary gene for predicting MP in reference to approximately 30% of marketed drugs and endogenous toxins. CYP2D6 predictions have proven clinically effective but also have well-documented inaccuracies due to relatively high genotype-phenotype discordance in certain populations. Herein, a pathway-driven predictive model employs genetic data from uridine diphosphate glucuronosyltransferase, family 1, polypeptide B7 (UGT2B7), adenosine triphosphate (ATP)-binding cassette, subfamily B, number 1 (ABCB1), opioid receptor mu 1 (OPRM1), and catechol-O-methyltransferase (COMT) to predict the tramadol to primary metabolite ratio (T:M1) and the resulting toxicologically inferred MP (t-MP). These data were then combined with CYP2D6 data to evaluate performance of a fully combinatorial model relative to CYP2D6 alone. These data identify UGT2B7 as a potentially significant explanatory marker for T:M1 variability in a population of tramadol-exposed individuals of Finnish ancestry. Supervised machine learning and feature selection were used to demonstrate that a set of 16 loci from 5 genes can predict t-MP with over 90% accuracy, depending on t-MP category and algorithm, which was significantly greater than predictions made by CYP2D6 alone.

Variations in Dysbindin-1 are associated with cognitive response to antipsychotic drug treatment

Antipsychotics are the most widely used medications for the treatment of schizophrenia spectrum disorders. While such drugs generally ameliorate positive symptoms, clinical responses are highly variable in terms of negative symptoms and cognitive impairments. However, predictors of individual responses have been elusive. Here, we report a pharmacogenetic interaction related to a core cognitive dysfunction in patients with schizophrenia. We show that genetic variations reducing dysbindin-1 expression can identify individuals whose executive functions respond better to antipsychotic drugs, both in humans and in mice. Multilevel ex vivo and in vivo analyses in postmortem human brains and genetically modified mice demonstrate that such interaction between antipsychotics and dysbindin-1 is mediated by an imbalance between the short and long isoforms of dopamine D2 receptors, leading to enhanced presynaptic D2 function within the prefrontal cortex. These findings reveal one of the pharmacodynamic mechanisms underlying individual cognitive response to treatment in patients with schizophrenia, suggesting a potential approach for improving the use of antipsychotic drugs.