Pharmacogenomics of Antidepressant and Antipsychotic Treatment: How Far Have We Got and Where Are We Going?

Effect of pharmacogenomic testing on the clinical treatment of patients with depressive disorder: A randomized clinical trial

BACKGROUND

Pharmacotherapy is one of the primary treatment modalities for depression. However, there is considerable variability in the individual response to antidepressant medications. Personalized medicine guided by pharmacogenomic testing may hold promise in addressing this issue.

METHODS

In this study, 665 depressive patients were randomly enrolled into two groups: the pharmacogenomic testing group (n = 333) and the control group (n = 332). In the testing group, participants underwent pharmacogenomic testing, and clinicians customized the treatment plan with the result, while the control group relied solely on clinicians' experience. The primary outcomes were the proportion of remission and response, assessed with Hamilton Depression Rating Scale (HDRS). The secondary outcomes included changes in HDRS scores over time and frequency of adverse drug reactions by the participants.

RESULTS

At week 8, the pharmacogenomic testing group showed significantly higher remission rates (24.0 % v.s. 15.1 %; RR = 1.117; P = 0.007) and response rates (39.3 % v.s. 25.7 %; RR = 1.225; P < 0.001) compared to the control group. By week 12, the pharmacogenomic testing group continued to demonstrate significant advantages in remission (31.0 % v.s. 20.0 %; RR = 1.159; P = 0.003) and response (48.7 % v.s. 37.3 %; RR = 1.224; P = 0.006). Additionally, adverse drug reactions were less frequent in the pharmacogenomic testing group.

LIMITATIONS

This study is not blind to clinicians and it's a single-center study.

CONCLUSIONS

Pharmacogenomic testing-guided drug therapy can provide greater assistance in the treatment of depression.

Dutch Pharmacogenetics Working Group (DPWG) guideline for the gene-drug interaction of CYP2C9, HLA-A and HLA-B with anti-epileptic drugs

By developing evidence-based pharmacogenetics guidelines to optimize pharmacotherapy, the Dutch Pharmacogenetics Working Group (DPWG) aims to advance the implementation of pharmacogenetics (PGx). This guideline outlines the gene-drug interaction of CYP2C9 and HLA-B with phenytoin, HLA-A and HLA-B with carbamazepine and HLA-B with oxcarbazepine and lamotrigine. A systematic review was performed and pharmacotherapeutic recommendations were developed. For CYP2C9 intermediate and poor metabolisers, the DPWG recommends lowering the daily dose of phenytoin and adjust based on effect and serum concentration after 7-10 days. For HLA-B*15:02 carriers, the risk of severe cutaneous adverse events associated with phenytoin, carbamazepine, oxcarbazepine, and lamotrigine is strongly increased. For carbamazepine, this risk is also increased in HLA-B*15:11 and HLA-A*31:01 carriers. For HLA-B*15:02, HLA-B*15:11 and HLA-A*31:01 positive patients, the DPWG recommends choosing an alternative anti-epileptic drug. If not possible, it is recommended to advise the patient to report any rash while using carbamazepine, lamotrigine, oxcarbazepine or phenytoin immediately. Carbamazepine should not be used in an HLA-B*15:02 positive patient. DPWG considers CYP2C9 genotyping before the start of phenytoin "essential" for toxicity prevention. For patients with an ancestry in which the abovementioned HLA-alleles are prevalent, the DPWG considers HLA-B*15:02 genotyping before the start of carbamazepine, phenytoin, oxcarbazepine, and lamotrigine "beneficial", as well as genotyping for HLA-B*15:11 and HLA-A*31:01 before initiating carbamazepine.

Dutch Pharmacogenetics Working Group (DPWG) guideline for the gene-drug interaction between CYP2D6, CYP2C19 and non-SSRI/non-TCA antidepressants

The Dutch Pharmacogenetics Working Group (DPWG) aims to facilitate pharmacogenetics implementation in clinical practice by developing evidence-based guidelines to optimize pharmacotherapy based on pharmacogenetic test results. The current guideline describes the gene-drug interaction between CYP2D6 and venlafaxine, mirtazapine and duloxetine. In addition, the interaction between CYP2C19 and mirtazapine and moclobemide is presented. The DPWG identified a gene-drug interaction that requires therapy adjustment for CYP2D6 and venlafaxine. However, as the side effects do not appear to be related to plasma concentrations, it is not possible to offer a substantiated advice for dose reduction. Therefore, the DPWG recommends avoiding venlafaxine for CYP2D6 poor and intermediate metabolisers. Instead, an alternative antidepressant, which is not, or to a lesser extent, metabolized by CYP2D6 is recommended. When it is not possible to avoid venlafaxine and side effects occur, it is recommended to reduce the dose and monitor the effect and side effects or plasma concentrations. No action is required for ultra-rapid metabolisers as kinetic effects are minimal and no clinical effect has been demonstrated. In addition, a gene-drug interaction was identified for CYP2D6 and mirtazapine and CYP2C19 and moclobemide, but no therapy adjustment is required as no effect regarding effectiveness or side effects has been demonstrated for these gene-drug interactions. Finally, no gene-drug interaction and need for therapy adjustment between CYP2C19 and mirtazapine and CYP2D6 and duloxetine were identified. The DPWG classifies CYP2D6 genotyping as being "potentially beneficial" for venlafaxine, indicating that genotyping prior to treatment can be considered on an individual patient basis.

Association of CYP2D6 and CYP2C19 metabolizer status with switching and discontinuing antidepressant drugs: an exploratory study

BACKGROUND

Tailoring antidepressant drugs (AD) to patients' genetic drug-metabolism profile is promising. However, literature regarding associations of ADs' treatment effect and/or side effects with drug metabolizing genes CYP2D6 and CYP2C19 has yielded inconsistent results. Therefore, our aim was to longitudinally investigate associations between CYP2D6 (poor, intermediate, and normal) and CYP2C19 (poor, intermediate, normal, and ultrarapid) metabolizer-status, and switching/discontinuing of ADs. Next, we investigated whether the number of perceived side effects differed between metabolizer statuses.

METHODS

Data came from the multi-site naturalistic longitudinal cohort Netherlands Study of Depression and Anxiety (NESDA). We selected depression- and/or anxiety patients, who used AD at some point in the course of the 9 years follow-up period (n = 928). Medication use was followed to assess patterns of AD switching/discontinuation over time. CYP2D6 and CYP2C19 alleles were derived using genome-wide data of the NESDA samples and haplotype data from the PharmGKB database. Logistic regression analyses were conducted to investigate the association of metabolizer status with switching/discontinuing ADs. Mann-Whitney U-tests were conducted to compare the number of patient-perceived side effects between metabolizer statuses.

RESULTS

No significant associations were observed of CYP metabolizer status with switching/discontinuing ADs, nor with the number of perceived side effects.

CONCLUSIONS

We found no evidence for associations between CYP metabolizer statuses and switching/discontinuing AD, nor with side effects of ADs, suggesting that metabolizer status only plays a limited role in switching/discontinuing ADs. Additional studies with larger numbers of PM and UM patients are needed to further determine the potential added value of pharmacogenetics to guide pharmacotherapy.

The association of FKBP5 gene polymorphism with genetic susceptibility to depression and response to antidepressant treatment- a systematic review

BACKGROUND

Given the inconsistencies in current studies regarding the impact of FKBP5 gene polymorphisms on depression, arising from variations in study methods, subjects, and treatment strategies, this paper provides a comprehensive review of the relationship between FKBP5 gene polymorphisms and genetic susceptibility to depression, as well as their influence on response to antidepressant treatment.

METHODS

Electronic databases were searched up to April 11, 2023, for all literature in English and Chinese on depression, FKBP5 gene polymorphisms, and antidepressant treatment. Data extraction and quality assessment were performed for key study characteristics. Qualitative methods were used to synthesize the study results.

RESULTS

A total of 21 studies were included, with the majority exhibiting average to moderate quality. Six SNPs (rs3800373, rs1360780, rs9470080, rs4713916, rs9296158, rs9394309) were broadly implicated in susceptibility to depression, while rs1360780 and rs3800373 were linked to antidepressant treatment sensitivity. Additionally, rs1360780 was associated with adverse reactions to antidepressant drug treatment. However, these associations were largely unconfirmed in replication studies.

CONCLUSIONS

Depression is recognized as a polygenic genetic disorder, with multiple genes contributing, each exerting relatively small effects. Future studies should explore not only multiple gene interactions but also epigenetic changes. Presently, research on FKBP5 in affective disorders remains notably limited, highlighting the necessity for further investigations in this domain.

Proportion of Antipsychotics with CYP2D6 Pharmacogenetic (PGx) Associations Prescribed in an Early Intervention in Psychosis (EIP) Cohort: A Cross-Sectional Study

BACKGROUND

Prescribing drugs for psychosis (antipsychotics) is challenging due to high rates of poor treatment outcomes, which are in part explained by an individual's genetics. Pharmacogenomic (PGx) testing can help clinicians tailor the choice or dose of psychosis drugs to an individual's genetics, particularly psychosis drugs with known variable response due to CYP2D6 gene variants ('CYP2D6-PGx antipsychotics').

AIMS

This study aims to investigate differences between demographic groups prescribed 'CYP2D6-PGx antipsychotics' and estimate the proportion of patients eligible for PGx testing based on current pharmacogenomics guidance.

METHODS

A cross-sectional study took place extracting data from 243 patients' medical records to explore psychosis drug prescribing, including drug transitions. Demographic data such as age, sex, ethnicity, and clinical sub-team were collected and summarised. Descriptive statistics explored the proportion of 'CYP2D6-PGx antipsychotic' prescribing and the nature of transitions. We used logistic regression analysis to investigate associations between demographic variables and prescription of 'CYP2D6-PGx antipsychotic' versus 'non-CYP2D6-PGx antipsychotic'.

RESULTS

Two-thirds (164) of patients had been prescribed a 'CYP2D6-PGx antipsychotic' (aripiprazole, risperidone, haloperidol or zuclopenthixol). Over a fifth (23%) of patients would have met the suggested criteria for PGx testing, following two psychosis drug trials. There were no statistically significant differences between age, sex, or ethnicity in the likelihood of being prescribed a 'CYP2D6-PGx antipsychotic'.

CONCLUSIONS

This study demonstrated high rates of prescribing 'CYP2D6-PGx-antipsychotics' in an EIP cohort, providing a rationale for further exploration of how PGx testing can be implemented in EIP services to personalise the prescribing of drugs for psychosis.

Case report: Avoiding intolerance to antipsychotics through a personalized treatment approach based on pharmacogenetics

Introduction

The standard approach to treatment in psychiatry is known as "treatment as usual" (TAU), in which the same types of treatment are administered to a group of patients. TAU often requires numerous dose adjustments and medication changes due to ineffectiveness and/or the occurrence of adverse drug reactions (ADRs). This process is not only time-consuming but also costly. Antipsychotic medications are commonly used to treat various psychiatric disorders such as schizophrenia and mood disorders. Some of the inter-individual differences in efficacy and ADRs observed in psychopharmacotherapy can be explained by genetic variability in the pharmacokinetics and pharmacodynamics of antipsychotics. A better understanding of (in)efficacy and possible ADRs can be achieved by pharmacogenetic analysis of genes involved in the metabolism of antipsychotics. Most psychotropic drugs are metabolized by genetically variable CYP2D6, CYP1A2, CYP3A4, and CYP2C19 enzymes. To demonstrate the utility of pharmacogenetic testing for tailoring antipsychotic treatment, in this paper, we present the case of a patient in whom a pharmacogenetic approach remarkably altered an otherwise intolerant or ineffective conventional TAU with antipsychotics.

Methods

In this case report, we present a 60-year-old patient with psychotic symptoms who suffered from severe extrapyramidal symptoms and a malignant neuroleptic syndrome during treatment with risperidone, fluphenazine, aripiprazole, brexpiprazole, and olanzapine. Therefore, we performed a pharmacogenetic analysis by genotyping common functional variants in genes involved in the pharmacokinetic pathways of prescribed antipsychotics, namely, CYP2D6, CYP3A4, CYP3A5, CYP1A2, ABCB1, and ABCG2. Treatment recommendations for drug-gene pairs were made according to available evidence-based pharmacogenetic recommendations from the Dutch Pharmacogenetics Working Group (DPWG) or Clinical Pharmacogenetics Implementation Consortium (CPIC).

Results

Pharmacogenetic testing revealed a specific metabolic profile and pharmacokinetic phenotype of the patient, which in retrospect provided possible explanations for the observed ADRs. Based on the pharmacogenetic results, the choice of an effective and safe medication proved to be much easier. The psychotic symptoms disappeared after treatment, while the negative symptoms persisted to a lesser extent.

Conclusion

With the case presented, we have shown that taking into account the pharmacogenetic characteristics of the patient can explain the response to antipsychotic treatment and associated side effects. In addition, pharmacogenetic testing enabled an informed choice of the most appropriate drug and optimal dose adjustment. This approach makes it possible to avoid or minimize potentially serious dose-related ADRs and treatment ineffectiveness. However, due to the complexity of psychopathology and the polypharmacy used in this field, it is of great importance to conduct further pharmacokinetic and pharmacogenetic studies to better assess gene-drug and gene-gene-drug interactions.

Dutch Pharmacogenetics Working Group (DPWG) guideline for the gene-drug interaction between CYP2D6, CYP3A4 and CYP1A2 and antipsychotics

The Dutch Pharmacogenetics Working Group (DPWG) aims to facilitate pharmacogenetics implementation in clinical practice by developing evidence-based guidelines to optimize pharmacotherapy. A guideline describing the gene-drug interaction between the genes CYP2D6, CYP3A4 and CYP1A2 and antipsychotics is presented here. The DPWG identified gene-drug interactions that require therapy adjustments when respective genotype is known for CYP2D6 with aripiprazole, brexpiprazole, haloperidol, pimozide, risperidone and zuclopenthixol, and for CYP3A4 with quetiapine. Evidence-based dose recommendations were obtained based on a systematic review of published literature. Reduction of the normal dose is recommended for aripiprazole, brexpiprazole, haloperidol, pimozide, risperidone and zuclopenthixol for CYP2D6-predicted PMs, and for pimozide and zuclopenthixol also for CYP2D6 IMs. For CYP2D6 UMs, a dose increase or an alternative drug is recommended for haloperidol and an alternative drug or titration of the dose for risperidone. In addition, in case of no or limited clinical effect, a dose increase is recommended for zuclopenthixol for CYP2D6 UMs. Even though evidence is limited, the DPWG recommends choosing an alternative drug to treat symptoms of depression or a dose reduction for other indications for quetiapine and CYP3A4 PMs. No therapy adjustments are recommended for the other CYP2D6 and CYP3A4 predicted phenotypes. In addition, no action is required for the gene-drug combinations CYP2D6 and clozapine, flupentixol, olanzapine or quetiapine and also not for CYP1A2 and clozapine or olanzapine. For identified gene-drug interactions requiring therapy adjustments, genotyping of CYP2D6 or CYP3A4 prior to treatment should not be considered for all patients, but on an individual patient basis only.

Clinical implementation of preemptive pharmacogenomics in psychiatry

BACKGROUND

Pharmacogenomics (PGx) holds promise to revolutionize modern healthcare. Although there are several prospective clinical studies in oncology and cardiology, demonstrating a beneficial effect of PGx-guided treatment in reducing adverse drug reactions, there are very few such studies in psychiatry, none of which spans across all main psychiatric indications, namely schizophrenia, major depressive disorder and bipolar disorder. In this study we aim to investigate the clinical effectiveness of PGx-guided treatment (occurrence of adverse drug reactions, hospitalisations and re-admissions, polypharmacy) and perform a cost analysis of the intervention.

METHODS

We report our findings from a multicenter, large-scale, prospective study of pre-emptive genome-guided treatment named as PREemptive Pharmacogenomic testing for preventing Adverse drug REactions (PREPARE) in a large cohort of psychiatric patients (n = 1076) suffering from schizophrenia, major depressive disorder and bipolar disorder.

FINDINGS

We show that patients with an actionable phenotype belonging to the PGx-guided arm (n = 25) present with 34.1% less adverse drug reactions compared to patients belonging to the control arm (n = 36), 41.2% less hospitalisations (n = 110 in the PGx-guided arm versus n = 187 in the control arm) and 40.5% less re-admissions (n = 19 in the PGx-guided arm versus n = 32 in the control arm), less duration of initial hospitalisations (n = 3305 total days of hospitalisation in the PGx-guided arm from 110 patients, versus n = 6517 in the control arm from 187 patients) and duration of hospitalisation upon readmission (n = 579 total days of hospitalisation upon readmission in the PGx-guided arm, derived from 19 patients, versus n = 928 in the control arm, from 32 patients respectively). It was also shown that in the vast majority of the cases, there was less drug dose administrated per drug in the PGx-guided arm compared to the control arm and less polypharmacy (n = 124 patients prescribed with at least 4 psychiatric drugs in the PGx-guided arm versus n = 143 in the control arm) and smaller average number of co-administered psychiatric drugs (2.19 in the PGx-guided arm versus 2.48 in the control arm. Furthermore, less deaths were reported in the PGx-guided arm (n = 1) compared with the control arm (n = 9). Most importantly, we observed a 48.5% reduction of treatment costs in the PGx-guided arm with a reciprocal slight increase of the quality of life of patients suffering from major depressive disorder (0.935 versus 0.925 QALYs in the PGx-guided and control arm, respectively).

INTERPRETATION

While only a small proportion (∼25%) of the entire study sample had an actionable genotype, PGx-guided treatment can have a beneficial effect in psychiatric patients with a reciprocal reduction of treatment costs. Although some of these findings did not remain significant when all patients were considered, our data indicate that genome-guided psychiatric treatment may be successfully integrated in mainstream healthcare.

FUNDING

European Union Horizon 2020.

Pharmacogenetics in Child and Adolescent Psychiatry: Background and Evidence-Based Clinical Applications

The efficacy and tolerability of psychotropic medications can vary significantly among children and adolescents, and some of this variability relates to pharmacogenetic factors. Pharmacogenetics (PGx) in child and adolescent psychiatry can potentially improve treatment outcomes and minimize adverse drug reactions. This article reviews key pharmacokinetic and pharmacodynamic genes and principles of pharmacogenetic testing and discusses the evidence base for clinical decision-making concerning PGx testing. This article reviews current guidelines from the United States Food and Drug Administration (FDA), the Clinical Pharmacogenetics Implementation Consortium (CPIC), and the Dutch Pharmacogenetics Working Group (DPWG) and explores potential future directions. This review discusses key clinical considerations for clinicians prescribing psychotropic medications in children and adolescents, focusing on antidepressants, antipsychotics, stimulants, norepinephrine reuptake inhibitors, and alpha-2 agonists. Finally, this review synthesizes the practical use of pharmacogenetic testing and clinical decision support systems.

A New Intervention for Implementation of Pharmacogenetics in Psychiatry: A Description of the PSY-PGx Clinical Study

(1) Background Pharmacological treatment for psychiatric disorders has shown to only be effective in about one-third of patients, as it is associated with frequent treatment failure, often because of side effects, and a long process of trial-and-error pharmacotherapy until an effective and tolerable treatment is found. This notion emphasizes the urgency for a personalized medicine approach in psychiatry. (2) Methods This prospective patient- and rater-blinded, randomized, controlled study will investigate the effect of dose-adjustment of antidepressants escitalopram and sertraline or antipsychotics risperidone and aripiprazole according to the latest state-of-the-art international dosing recommendations for CYP2C19 and CYP2D6 metabolizer status in patients with mood, anxiety, and psychotic disorders. A total sample of N = 2500 will be recruited at nine sites in seven countries (expected drop-out rate of 30%). Patients will be randomized to a pharmacogenetic group or a dosing-as-usual group and treated over a 24-week period with four study visits. The primary outcome is personal recovery using the Recovery Assessment Scale as assessed by the patient (RAS-DS), with secondary outcomes including clinical effects (response or symptomatic remission), side effects, general well-being, digital phenotyping, and psychosocial functioning. (3) Conclusions This is, to our knowledge, the first international, multi-center, non-industry-sponsored randomized controlled trial (RCT) that may provide insights into the effectiveness and utility of implementing pharmacogenetic-guided treatment of psychiatric disorders, and as such, results will be incorporated in already available dosing guidelines.

The Effects of CYP2C19 Genotype on Proxies of SSRI Antidepressant Response in the UK Biobank

Selective serotonin reuptake inhibitors (SSRIs) are the most commonly used psychopharmaceutical treatment for major depressive disorder (MDD), but individual responses to SSRIs vary greatly. CYP2C19 is a key enzyme involved in the metabolism of several drugs, including SSRIs. Variations in the CYP2C19 gene are associated with differential metabolic activity, and thus differential SSRI exposure; accordingly, the CYP2C19 genotype may affect the therapeutic response and clinical outcomes, though existing evidence of this link is not entirely consistent. Therefore, we analysed data from the UK Biobank, a large, deeply phenotyped prospective study, to investigate the effects of CYP2C19 metaboliser phenotypes on several clinical outcomes derived from primary care records, including multiple measures of antidepressant switching, discontinuation, duration, and side effects. In this dataset, 24,729 individuals were prescribed citalopram, 3012 individuals were prescribed escitalopram, and 12,544 individuals were prescribed sertraline. Consistent with pharmacological expectations, CYP2C19 poor metabolisers on escitalopram were more likely to switch antidepressants, have side effects following first prescription, and be on escitalopram for a shorter duration compared to normal metabolisers. CYP2C19 poor and intermediate metabolisers on citalopram also exhibited increased odds of discontinuation and shorter durations relative to normal metabolisers. Generally, no associations were found between metabolic phenotypes and proxies of response to sertraline. Sensitivity analyses in a depression subgroup and metabolic activity scores corroborated results from the primary analysis. In summary, our findings suggest that CYP2C19 genotypes, and thus metabolic phenotypes, may have utility in determining clinical responses to SSRIs, particularly escitalopram and citalopram, though further investigation of such a relationship is warranted.

Pharmacogenomics and the Management of Mood Disorders-A Review

Due to the chronic relapsing nature of mental disorders and increased life expectancy, the societal burden of these non-communicable diseases will increase even further. Treatments for mental disorders, such as depression, are available, but their effect is limited due to patients' (genetic) heterogeneity, low treatment compliance and frequent side effects. In general, only one-third of the patients respond to treatment. Today, medication selection in psychiatry relies on a trial-and-error approach based mainly on physicians' experience. Pharmacogenetic (PGx) testing can help in this process by determining the person-specific genetic factors that may predict clinical response and side effects associated with genetic variants that impact drug-metabolizing enzymes, drug transporters or drug targets. PGxis a discipline that investigates genetic factors that affect the absorption, metabolism, and transport of drugs, thereby affecting therapy outcome. These genetic factors can, among other things, lead to differences in the activity of enzymes that metabolize drugs. Studies in depressed patients show that genotyping of drug-metabolizing enzymes can increase the effectiveness of treatment, which could benefit millions of patients worldwide. This review highlights these studies, gives recommendations and provides future perspectives on how to proceed with PGx testing. Finally, it is recommended to consider genotyping for CYP2D6 and CYP2C19, when there is an indication (side effects or inefficacy).

Association of Single Nucleotide Polymorphisms of Cytokine Genes with Depression, Schizophrenia and Bipolar Disorder

Immune gene variants are known to be associated with the risk of psychiatric disorders, their clinical manifestations, and their response to therapy. This narrative review summarizes the current literature over the past decade on the association of polymorphic variants of cytokine genes with risk, severity, and response to treatment for severe mental disorders such as bipolar disorder, depression, and schizophrenia. A search of literature in databases was carried out using keywords related to depressive disorder, bipolar disorder, schizophrenia, inflammation, and cytokines. Gene lists were extracted from publications to identify common genes and pathways for these mental disorders. Associations between polymorphic variants of the IL1B, IL6, and TNFA genes were the most replicated and relevant in depression. Polymorphic variants of the IL1B, IL6, IL6R, IL10, IL17A, and TNFA genes have been associated with schizophrenia. Bipolar disorder has mainly been associated with polymorphic variants of the IL1B gene. Interestingly, the IL6R gene polymorphism (rs2228145) was associated with all three diseases. Some cytokine genes have also been associated with clinical presentation and response to pharmacotherapy. There is also evidence that some specific polymorphic variants may affect the expression of cytokine genes. Thus, the data from this review indicate a link between neuroinflammation and severe mental disorders.

The Role of Pharmacogenetics in Personalizing the Antidepressant and Anxiolytic Therapy

Pharmacotherapy for neuropsychiatric disorders, such as anxiety and depression, has been characterized by significant inter-individual variability in drug response and the development of side effects. Pharmacogenetics, as a key part of personalized medicine, aims to optimize therapy according to a patient's individual genetic signature by targeting genetic variations involved in pharmacokinetic or pharmacodynamic processes. Pharmacokinetic variability refers to variations in a drug's absorption, distribution, metabolism, and elimination, whereas pharmacodynamic variability results from variable interactions of an active drug with its target molecules. Pharmacogenetic research on depression and anxiety has focused on genetic polymorphisms affecting metabolizing cytochrome P450 (CYP) and uridine 5'-diphospho-glucuronosyltransferase (UGT) enzymes, P-glycoprotein ATP-binding cassette (ABC) transporters, and monoamine and γ-aminobutyric acid (GABA) metabolic enzymes, transporters, and receptors. Recent pharmacogenetic studies have revealed that more efficient and safer treatments with antidepressants and anxiolytics could be achieved through genotype-guided decisions. However, because pharmacogenetics cannot explain all observed heritable variations in drug response, an emerging field of pharmacoepigenetics investigates how epigenetic mechanisms, which modify gene expression without altering the genetic code, might influence individual responses to drugs. By understanding the epi(genetic) variability of a patient's response to pharmacotherapy, clinicians could select more effective drugs while minimizing the likelihood of adverse reactions and therefore improve the quality of treatment.

Effectiveness of Genotype-Specific Tricyclic Antidepressant Dosing in Patients With Major Depressive Disorder: A Randomized Clinical Trial

Importance

Evidence of the clinical benefit of pharmacogenetics-informed treatment (PIT) with antidepressants is still limited. Especially for tricyclic antidepressants (TCAs), pharmacogenetics may be of interest because therapeutic plasma concentrations are well defined, identification of optimal dosing can be time consuming, and treatment is frequently accompanied by adverse effects.

Objective

To determine whether PIT results in faster attainment of therapeutic TCA plasma concentrations compared with usual treatment in patients with unipolar major depressive disorder (MDD).

Design, Setting, and Participants

This randomized clinical trial compared PIT with usual treatment among 111 patients at 4 centers in the Netherlands. Patients were treated with the TCAs nortriptyline, clomipramine, or imipramine, with clinical follow-up of 7 weeks. Patients were enrolled from June 1, 2018, to January 1, 2022. At inclusion, patients had unipolar nonpsychotic MDD (with a score of ≥19 on the 17-item Hamilton Rating Scale for Depression [HAMD-17]), were aged 18 to 65 years, and were eligible for TCA treatment. Main exclusion criteria were a bipolar or psychotic disorder, substance use disorder, pregnancy, interacting comedications, and concurrent use of psychotropic medications.

Intervention

In the PIT group, the initial TCA dosage was based on CYP2D6 and CYP2C19 genotypes. The control group received usual treatment, which comprised the standard initial TCA dosage.

Main Outcomes and Measures

The primary outcome was days until attainment of a therapeutic TCA plasma concentration. Secondary outcomes were severity of depressive symptoms (measured by HAMD-17 scores) and frequency and severity of adverse effects (measured by Frequency, Intensity, and Burden of Side Effects Rating scores).

Results

Of 125 patients randomized, 111 (mean [SD] age, 41.7 [13.3] years; 69 [62.2%] female) were included in the analysis; of those, 56 were in the PIT group and 55 were in the control group. The PIT group reached therapeutic concentrations faster than the control group (mean [SD], 17.3 [11.2] vs 22.0 [10.2] days; Kaplan-Meier χ21 = 4.30; P = .04). No significant difference in reduction of depressive symptoms was observed. Linear mixed-model analyses showed that the interaction between group and time differed for the frequency (F6,125 = 4.03; P = .001), severity (F6,114 = 3.10; P = .008), and burden (F6,112 = 2.56; P = .02) of adverse effects, suggesting that adverse effects decreased relatively more for those receiving PIT.

Conclusions and Relevance

In this randomized clinical trial, PIT resulted in faster attainment of therapeutic TCA concentrations, with potentially fewer and less severe adverse effects. No effect on depressive symptoms was observed. These findings indicate that pharmacogenetics-informed dosing of TCAs can be safely applied and may be useful in personalizing treatment for patients with MDD.

Trial Registration

ClinicalTrials.gov Identifier: NCT03548675.

The Progress and Pitfalls of Pharmacogenetics-Based Precision Medicine in Schizophrenia Spectrum Disorders: A Systematic Review and Meta-Analysis

The inadequate efficacy and adverse effects of antipsychotics severely affect the recovery of patients with schizophrenia spectrum disorders (SSD). We report the evidence for associations between pharmacogenetic (PGx) variants and antipsychotics outcomes, including antipsychotic response, antipsychotic-induced weight/BMI gain, metabolic syndrome, antipsychotic-related prolactin levels, antipsychotic-induced tardive dyskinesia (TD), clozapine-induced agranulocytosis (CLA), and drug concentration level (pharmacokinetics) in SSD patients. Through an in-depth systematic search in 2010–2022, we identified 501 records. We included 29 meta-analyses constituting pooled data from 298 original studies over 69 PGx variants across 39 genes, 4 metabolizing phenotypes of CYP2D9, and 3 of CYP2C19. We observed weak unadjusted nominal significant (p < 0.05) additive effects of PGx variants of DRD1, DRD2, DRD3, HTR1A, HTR2A, HTR3A, and COMT (10 variants) on antipsychotic response; DRD2, HTR2C, BDNF, ADRA2A, ADRB3, GNB3, INSIG2, LEP, MC4R, and SNAP25 (14 variants) on weight gain; HTR2C (one variant) on metabolic syndrome; DRD2 (one variant) on prolactin levels; COMT and BDNF (two variants) on TD; HLA-DRB1 (one variant) on CLA; CYP2D6 (four phenotypes) and CYP2C19 (two phenotypes) on antipsychotics plasma levels. In the future, well-designed longitudinal naturalistic multi-center PGx studies are needed to validate the effectiveness of PGx variants in antipsychotic outcomes before establishing any reproducible PGx passport in clinical practice.

Multi-omics data integration methods and their applications in psychiatric disorders

To study mental illness and health, in the past researchers have often broken down their complexity into individual subsystems (e.g., genomics, transcriptomics, proteomics, clinical data) and explored the components independently. Technological advancements and decreasing costs of high throughput sequencing has led to an unprecedented increase in data generation. Furthermore, over the years it has become increasingly clear that these subsystems do not act in isolation but instead interact with each other to drive mental illness and health. Consequently, individual subsystems are now analysed jointly to promote a holistic understanding of the underlying biological complexity of health and disease. Complementing the increasing data availability, current research is geared towards developing novel methods that can efficiently combine the information rich multi-omics data to discover biologically meaningful biomarkers for diagnosis, treatment, and prognosis. However, clinical translation of the research is still challenging. In this review, we summarise conventional and state-of-the-art statistical and machine learning approaches for discovery of biomarker, diagnosis, as well as outcome and treatment response prediction through integrating multi-omics and clinical data. In addition, we describe the role of biological model systems and in silico multi-omics model designs in clinical translation of psychiatric research from bench to bedside. Finally, we discuss the current challenges and explore the application of multi-omics integration in future psychiatric research. The review provides a structured overview and latest updates in the field of multi-omics in psychiatry.

The pharmacogenetics of CYP2D6 and CYP2C19 in a case series of antidepressant responses

Pharmacogenetics has potential for optimizing use of psychotropics. CYP2D6 and CYP2C19 are two clinically relevant pharmacogenes in the prescribing of antidepressants. Using cases recruited from the Understanding Drug Reactions Using Genomic Sequencing (UDRUGS) study, we aimed to evaluate the clinical utility of genotyping CYP2D6 and CYP2C19 in antidepressant response. Genomic and clinical data for patients who were prescribed antidepressants for mental health disorders, and experienced adverse reactions (ADRs) or ineffectiveness, were extracted for analysis. Genotype-inferred phenotyping of CYP2D6 and CYP2C19 was carried out as per Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines. A total of 52 patients, predominantly New Zealand Europeans (85%) with a median age (range) of 36 years (15-73), were eligible for analysis. Thirty-one (60%) reported ADRs, 11 (21%) ineffectiveness, and 10 (19%) reported both. There were 19 CYP2C19 NMs, 15 IMs, 16 RMs, one PM and one UM. For CYP2D6, there were 22 NMs, 22 IMs, four PMs, three UMs, and one indeterminate. CPIC assigned a level to each gene-drug pair based on curated genotype-to-phenotype evidence. We analyzed a subgroup of 45 cases, inclusive of response type (ADRs/ineffectiveness). Seventy-nine (N = 37 for CYP2D6, N = 42 for CYP2C19) gene-drug/antidepressant-response pairs with CPIC evidence levels of A, A/B, or B were identified. Pairs were assigned as 'actionable' if the CYP phenotypes potentially contributed to the observed response. We observed actionability in 41% (15/37) of CYP2D6-antidepressant-response pairs and 36% (15/42) of CYP2C19-antidepressant-response pairs. In this cohort, CYP2D6 and CYP2C19 genotypes were actionable for a total of 38% pairs, consisting of 48% in relation to ADRs and 21% in relation to drug ineffectiveness.

Precision Medicine in Antidepressants Treatment

Precision medicine uses innovative approaches to improve disease prevention and treatment outcomes by taking into account people's genetic backgrounds, environments, and lifestyles. Treatment of depression is particularly challenging, given that 30-50% of patients do not respond adequately to antidepressants, while those who respond may experience unpleasant adverse drug reactions (ADRs) that decrease their quality of life and compliance. This chapter aims to present the available scientific data that focus on the impact of genetic variants on the efficacy and toxicity of antidepressants. We compiled data from candidate gene and genome-wide association studies that investigated associations between pharmacodynamic and pharmacokinetic genes and response to antidepressants regarding symptom improvement and ADRs. We also summarized the existing pharmacogenetic-based treatment guidelines for antidepressants, used to guide the selection of the right antidepressant and its dose based on the patient's genetic profile, aiming to achieve maximum efficacy and minimum toxicity. Finally, we reviewed the clinical implementation of pharmacogenomics studies focusing on patients on antidepressants. The available data demonstrate that precision medicine can increase the efficacy of antidepressants and reduce the occurrence of ADRs and ultimately improve patients' quality of life.

Opportunity for pharmacogenetics testing in patients with sickle cell anemia

Background: Patients with sickle cell disease (SCD) are exposed to numerous drugs over their lifespan, and many of these drugs have Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines for personalized dosing. The authors' aim was to ascertain the number of drugs with CPIC guidelines prescribed to SCD patients. Materials & methods: A search of Indiana University Health affiliated hospitals' electronic medical record identified 957 patients with a diagnosis of SCD. Drugs or drug classes with CPIC actionable guidelines ordered as inpatient and outpatient prescriptions were collected from SCD patients. Results: During the 16-year period, 892 (93%) patients received at least one drug that could have been dosed according to CPIC guidelines. Conclusion: Preemptive pharmacogenetics testing should be considered in SCD patients in order to utilize these data throughout the patient's life.

Dutch Pharmacogenetics Working Group (DPWG) guideline for the gene-drug interaction between CYP2C19 and CYP2D6 and SSRIs

The Dutch Pharmacogenetics Working Group (DPWG) guideline presented here, presents the gene-drug interaction between the genes CYP2C19 and CYP2D6 and antidepressants of the selective serotonin reuptake inhibitor type (SSRIs). Both genes' genotypes are translated into predicted normal metabolizer (NM), intermediate metabolizer (IM), poor metabolizer (PM), or ultra-rapid metabolizer (UM). Evidence-based dose recommendations were obtained, based on a structured analysis of published literature. In CYP2C19 PM patients, escitalopram dose should not exceed 50% of the normal maximum dose. In CYP2C19 IM patients, this is 75% of the normal maximum dose. Escitalopram should be avoided in UM patients. In CYP2C19 PM patients, citalopram dose should not exceed 50% of the normal maximum dose. In CYP2C19 IM patients, this is 70% (65-75%) of the normal maximum dose. In contrast to escitalopram, no action is needed for CYP2C19 UM patients. In CYP2C19 PM patients, sertraline dose should not exceed 37.5% of the normal maximum dose. No action is needed for CYP2C19 IM and UM patients. In CYP2D6 UM patients, paroxetine should be avoided. No action is needed for CYP2D6 PM and IM patients. In addition, no action is needed for the other gene-drug combinations. Clinical effects (increase in adverse events or decrease in efficacy) were lacking for these other gene-drug combinations. DPWG classifies CYP2C19 genotyping before the start of escitalopram, citalopram, and sertraline, and CYP2D6 genotyping before the start of paroxetine as "potentially beneficial" for toxicity/effectivity predictions. This indicates that genotyping prior to treatment can be considered on an individual patient basis.

A Longitudinal Study of the Association between the LEPR Polymorphism and Treatment Response in Patients with Bipolar Disorder

Patients with bipolar disorder (BD) exhibit individual variability in the treatment outcome, and genetic background could contribute to BD itself and the treatment outcome. Leptin levels significantly change in BD patients treated with valproate (VPA), but whether LEPR polymorphisms are associated with treatment response is still unknown. This longitudinal study aimed to investigate the associations between LEPR polymorphisms and VPA treatment response in BD patients who were drug naïve at their first diagnosis of BD. The single-nucleotide polymorphisms (SNPs) of LEPR (rs1137101, rs1137100, rs8179183, and rs12145690) were assayed, and the LEPR polymorphism frequencies of alleles and genotypes were not significantly different between the controls (n = 77) and BD patients (n = 130). In addition, after the 12-week course of VPA treatment in BD patients, the LEPR polymorphisms showed significant effects on changes in disease severity. Moreover, considering the effect of the LEPR haplotype, the frequency of the CAGG haplotype in BD patients was higher than that in the controls (9.3 vs. 2.9%, p = 0.016), and the LEPR CAGG haplotype was associated with a better treatment response than the other haplotypes in BD patients receiving VPA treatment. Therefore, LEPR polymorphisms might serve as mediators involved in the therapeutic action of VPA treatment.

Drug metabolic enzyme genotype-phenotype discrepancy: High phenoconversion rate in patients treated with antidepressants

Cytochromes from the P450 family (CYP) play a central role in the primary metabolism of frequently prescribed antidepressants, potentially affecting their efficacy and tolerance. There are however important differences in the drug metabolic capacities of each individual resulting from a combination of intrinsic and environmental factors. This variability can present an important risk for patients and increases the difficulty of drug prescription in clinical practice. Pharmacogenetic studies have uncovered a number of alleles defining the intrinsic metabolizer status, however, additional factors affecting cytochrome activity can modify this activity and result in a phenoconversion. The present study investigates the discrepancy between the genetically predicted and actually measured activities for the six most important liver cytochromes (CYP1A2, CYP2B6, CYP2C9, CYP2C19, CYP2D6 and CYP3A4) in a cohort of patients under antidepressant treatment, previously shown to have a high proportion of patients with low metabolizing activities. We now performed the genetic characterization of this cohort to determine the extent of the genetic versus environmental contribution in these decreased activities. For all enzyme tested, we observed an important rate of phenoconversion, affecting between 33 % and 65 % of the patients, as well as a significant (p < 1E-06) global reduction in the effective but not predicted activities of CYP2D6, CYP2C9 and CYP2C19 compared to the general population. Our results highlight the advantages of phenotyping versus genotyping as well as the increased risk of treatment failure or adverse effect occurrence in a polymedicated population.

Correlation of 1846G>A Polymorphism of CYP2D6 Gene with Haloperidol Efficacy and Safety in Patients with Alcoholic Hallucinoses

BACKGROUND

Previous studies have shown that haloperidol biotransformation occurs with participation of the CYP2D6 isoenzyme. The CYP2D6 gene is highly polymorphic, which may contribute to differences in its activity and in the haloperidol biotransformation rates across different individuals, resulting in variable drug efficacy and safety profiles.

PURPOSE

The study aimed to investigate the correlation of the 1846G> A polymorphism of CYP2D6 gene with the efficacy and safety rates of haloperidol in patients with alcoholic hallucinoses.

MATERIAL AND METHODS

One hundred male patients received 5-10 mg/day haloperidol by injections for 5 days. The efficacy and safety assessments were performed using the validated psychometric scales PANSS, UKU, and SAS. For genotyping, the real-time polymerase chain reaction was performed.

RESULTS

We revealed no statistically significant results in terms of haloperidol efficacy in patients with different genotypes (dynamics of the PANSS scores: (GG) -13.00 [-16.00; -11.00], (GA) -15.00 [-16.75; -13.00], p = 0,728). Our findings revealed the statistically significant results in terms of treatment safety evaluation (dynamics of the UKU scores: (GG) 8.00 [7.00; 10.00], (GA) 15.0 [9.25; 18.0], p < 0.001; dynamics of the SAS scores: (GG) 11.0 [9.0; 14.0], (GA) 14.50 [12.0; 18.0], p < 0.001.

CONCLUSION

These results suggest that genotyping for common CYP3A variants might have the potential to guide benzodiazepine withdrawal treatment. The effect of of the 1846G>A polymorphism of CYP2D6 gene on the safety profile of haloperidol was demonstrated in a group of 100 patients with alcoholic hallucinoses.

Pharmacogenomics: a tool to improve medication safety and efficacy in patients with cystic fibrosis

Cystic fibrosis is a genetic, multiorgan system disease that involves the use of many medications to control symptoms associated with the underlying condition. Many of these medications have Clinical Pharmacogenetics Implementation Consortium evidence-based guidelines for pharmacogenomics that are available to guide dosing. The aim of this article is to review relevant literature and evaluate the utility of preemptive pharmacogenomics testing for persons with cystic fibrosis and propose a pharmacogenomics panel that could be considered standard of care for persons with cystic fibrosis.

Opportunity for pharmacogenomic testing in patients with cystic fibrosis

BACKGROUND

Patients with cystic fibrosis (CF) are exposed to many drugs in their lifetime and many of these drugs have Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines that are available to guide dosing. Contemporary CF treatments are targeted to specific mutations in the CF transmembrane conductance regulator (CFTR) gene, and thus, require patients to have genetic testing before initiation of modulator therapy. However, aside from CFTR genetic testing, pharmacogenomic testing is not standard of care for CF patients.

AIM

The aim of this study is to determine the number of non-CFTR modulator medications with CPIC guidelines that are prescribed to patients with CF.

MATERIALS & METHODS

We identified all patients with a diagnosis of CF and queried our hospital electronic medical records (EMR) for all orders, including inpatient and prescriptions, for all drugs or drug classes that have CPIC actionable guidelines for drug-gene pairs that can be used to guide therapy.

RESULTS

We identified 576 patients with a diagnosis of CF that were treated at our institution during this 16-year period between June 2005 and May 2021. Of these patients, 504 patients (87.5%) received at least one drug that could have been dosed according to CPIC guidelines if pharmacogenomic results would have been available.

CONCLUSIONS

Patients with CF have high utilization of drugs with CPIC guidelines, therefore preemptive pharmacogenomic testing should be considered in CF patients at the time of CFTR genetic testing.

Identifying the Common Genetic Basis of Antidepressant Response

Background

Antidepressants are a first-line treatment for depression. However, only a third of individuals experience remission after the first treatment. Common genetic variation, in part, likely regulates antidepressant response, yet the success of previous genome-wide association studies has been limited by sample size. This study performs the largest genetic analysis of prospectively assessed antidepressant response in major depressive disorder to gain insight into the underlying biology and enable out-of-sample prediction.

Methods

Genome-wide analysis of remission (n remit = 1852, n nonremit = 3299) and percentage improvement (n = 5218) was performed. Single nucleotide polymorphism-based heritability was estimated using genome-wide complex trait analysis. Genetic covariance with eight mental health phenotypes was estimated using polygenic scores/AVENGEME. Out-of-sample prediction of antidepressant response polygenic scores was assessed. Gene-level association analysis was performed using MAGMA and transcriptome-wide association study. Tissue, pathway, and drug binding enrichment were estimated using MAGMA.

Results

Neither genome-wide association study identified genome-wide significant associations. Single nucleotide polymorphism-based heritability was significantly different from zero for remission (h 2 = 0.132, SE = 0.056) but not for percentage improvement (h 2 = -0.018, SE = 0.032). Better antidepressant response was negatively associated with genetic risk for schizophrenia and positively associated with genetic propensity for educational attainment. Leave-one-out validation of antidepressant response polygenic scores demonstrated significant evidence of out-of-sample prediction, though results varied in external cohorts. Gene-based analyses identified ETV4 and DHX8 as significantly associated with antidepressant response.

Conclusions

This study demonstrates that antidepressant response is influenced by common genetic variation, has a genetic overlap schizophrenia and educational attainment, and provides a useful resource for future research. Larger sample sizes are required to attain the potential of genetics for understanding and predicting antidepressant response.

Mitigating the Risk of Adverse Effects Related to Augmentation Therapy for Resistant Major Depressive Disorder: A Case Report

Polypharmacy of psychotropic medications predisposes older adults to adverse drug events (ADEs). One contributing factor is inhibition of metabolic pathways between substrates (competitive inhibition) or between substrates and inhibitors of the same cytochrome P450 (CYP450) isoforms. The purpose of this case report is to demonstrate observed sedation and difficulty concentrating from augmentation therapy for resistant major depressive disorder (MDD) and to highlight the value of clinical tools to identify opportunities for treatment optimization to reduce ADEs. The pharmacist identified significant medication burden and competitive inhibition of drug metabolism in the CYP450 system during a telehealth medication therapy management consultation with a 69-year-old male. The pharmacist recommended clinical monitoring and communicated concerns about medication-induced sedation, difficulty concentrating, and other medication-related problems (MRP) to providers. Several recommendations were implemented which helped improved patient’s outcomes. Individualizing MDD pharmacotherapy based on pharmacokinetic and pharmacodynamic drug interactions and geriatric dosage considerations may lead to better outcomes and tolerability among older adults.

Metabolizing status of CYP2C19 in response and side effects to medications for depression: Results from a naturalistic study

Major depressive disorder (MDD) is one of the leading causes of disability worldwide. Polymorphisms in cytochrome P450 genes (CYP450) were demonstrated to play a significant role in antidepressant response and side effects, but their effect in real-world clinical practice is poorly known. We determined the metabolic status of CYP2C19 based on the combination of *1, *2, *3 and *17 alleles extracted from genome-wide data in 1239 patients with MDD, pharmacologically treated in a naturalistic setting. Symptom improvement and side effects were assessed using the Montgomery and Åsberg Depression Rating Scale and the Udvalg for Kliniske Undersøgelse scale, respectively. We tested if symptom improvement, response and side effects were associated with CYP2C19 metabolic status adjusting for potential confounders. We considered patients treated with drugs for depression having CYP2C19 genotyping recommended by guidelines (T1 Drugs); secondarily, with all psychotropic drugs having CYP2C19 as relevant metabolic path (T2 Drugs). In the group treated with T1 drugs (n = 540), poor metabolizers (PMs) showed higher response and higher symptom improvement compared to normal metabolizers (p = 0.023 and p = 0.009, respectively), but also higher risk of autonomic and neurological side effects (p = 0.022 and p = 0.022 respectively). In patients treated with T2 drugs (n = 801), similar results were found. No associations between metabolizer status and other types of side effects were found (psychic and other side effects). Our study suggests potential advantages of CYP2C19 pharmacogenetic testing to guide treatment prescription, that may not be limited to the drugs currently recommended by guidelines.

The benefit of diagnostic whole genome sequencing in schizophrenia and other psychotic disorders

Schizophrenia has a multifactorial etiology, involving a polygenic architecture. The potential benefit of whole genome sequencing (WGS) in schizophrenia and other psychotic disorders is not well studied. We investigated the yield of clinical WGS analysis in 251 families with a proband diagnosed with schizophrenia (N = 190), schizoaffective disorder (N = 49), or other conditions involving psychosis (N = 48). Participants were recruited in Israel and USA, mainly of Jewish, Arab, and other European ancestries. Trio (parents and proband) WGS was performed for 228 families (90.8%); in the other families, WGS included parents and at least two affected siblings. In the secondary analyses, we evaluated the contribution of rare variant enrichment in particular gene sets, and calculated polygenic risk score (PRS) for schizophrenia. For the primary outcome, diagnostic rate was 6.4%; we found clinically significant, single nucleotide variants (SNVs) or small insertions or deletions (indels) in 14 probands (5.6%), and copy number variants (CNVs) in 2 (0.8%). Significant enrichment of rare loss-of-function variants was observed in a gene set of top schizophrenia candidate genes in affected individuals, compared with population controls (N = 6,840). The PRS for schizophrenia was significantly increased in the affected individuals group, compared to their unaffected relatives. Last, we were also able to provide pharmacogenomics information based on CYP2D6 genotype data for most participants, and determine their antipsychotic metabolizer status. In conclusion, our findings suggest that WGS may have a role in the setting of both research and genetic counseling for individuals with schizophrenia and other psychotic disorders and their families.

Pharmacist assessment of drug-gene interactions and drug-induced phenoconversion in major depressive disorder: a case report

BACKGROUND

Response to antidepressant therapy is highly variable among individuals. Pharmacogenomic (PGx) testing presents an opportunity to guide drug selection while optimizing therapy outcomes and/or decreasing the risk for toxicity.

CASE PRESENTATION

A patient with multiple comorbidities, including severe major depressive disorder (MDD), experienced adverse drug events and undesirable response to multiple antidepressant medications (i.e., bupropion, escitalopram, and venlafaxine). A clinical pharmacist assessed significant drug-gene, drug-drug, and drug-drug-gene interactions as well as other clinical factors to provide recommendations for antidepressant therapy optimization.

CONCLUSION

This case highlights the importance of PGx testing and the key role of pharmacists in identifying and mitigating drug-related problems and optimizing drug therapy in patients with MDD.

Genophenotypic Factors and Pharmacogenomics in Adverse Drug Reactions

Adverse drug reactions (ADRs) rank as one of the top 10 leading causes of death and illness in developed countries. ADRs show differential features depending upon genotype, age, sex, race, pathology, drug category, route of administration, and drug–drug interactions. Pharmacogenomics (PGx) provides the physician effective clues for optimizing drug efficacy and safety in major problems of health such as cardiovascular disease and associated disorders, cancer and brain disorders. Important aspects to be considered are also the impact of immunopharmacogenomics in cutaneous ADRs as well as the influence of genomic factors associated with COVID-19 and vaccination strategies. Major limitations for the routine use of PGx procedures for ADRs prevention are the lack of education and training in physicians and pharmacists, poor characterization of drug-related PGx, unspecific biomarkers of drug efficacy and toxicity, cost-effectiveness, administrative problems in health organizations, and insufficient regulation for the generalized use of PGx in the clinical setting. The implementation of PGx requires: (i) education of physicians and all other parties involved in the use and benefits of PGx; (ii) prospective studies to demonstrate the benefits of PGx genotyping; (iii) standardization of PGx procedures and development of clinical guidelines; (iv) NGS and microarrays to cover genes with high PGx potential; and (v) new regulations for PGx-related drug development and PGx drug labelling.

The Influence of CYP2D6 and CYP2C19 Genetic Variation on Diabetes Mellitus Risk in People Taking Antidepressants and Antipsychotics

CYP2D6 and CYP2C19 enzymes are essential in the metabolism of antidepressants and antipsychotics. Genetic variation in these genes may increase risk of adverse drug reactions. Antidepressants and antipsychotics have previously been associated with risk of diabetes. We examined whether individual genetic differences in CYP2D6 and CYP2C19 contribute to these effects. We identified 31,579 individuals taking antidepressants and 2699 taking antipsychotics within UK Biobank. Participants were classified as poor, intermediate, or normal metabolizers of CYP2D6, and as poor, intermediate, normal, rapid, or ultra-rapid metabolizers of CYP2C19. Risk of diabetes mellitus represented by HbA1c level was examined in relation to the metabolic phenotypes. CYP2D6 poor metabolizers taking paroxetine had higher Hb1Ac than normal metabolizers (mean difference: 2.29 mmol/mol; p < 0.001). Among participants with diabetes who were taking venlafaxine, CYP2D6 poor metabolizers had higher HbA1c levels compared to normal metabolizers (mean differences: 10.15 mmol/mol; p < 0.001. Among participants with diabetes who were taking fluoxetine, CYP2D6 intermediate metabolizers and decreased HbA1c, compared to normal metabolizers (mean difference -7.74 mmol/mol; p = 0.017). We did not observe any relationship between CYP2D6 or CYP2C19 metabolic status and HbA1c levels in participants taking antipsychotic medication. Our results indicate that the impact of genetic variation in CYP2D6 differs depending on diabetes status. Although our findings support existing clinical guidelines, further research is essential to inform pharmacogenetic testing for people taking antidepressants and antipsychotics.

What Are the Barriers and Enablers to the Implementation of Pharmacogenetic Testing in Mental Health Care Settings?

In psychiatry, the selection of antipsychotics and antidepressants is generally led by a trial-and-error approach. The prescribing of these medications is complicated by sub-optimal efficacy and high rates of adverse drug reactions (ADRs). These both contribute to poor levels of adherence. Pharmacogenetics (PGx) considers how genetic variation can influence an individual’s response to a drug. Pharmacogenetic testing is a tool that could aid clinicians when selecting psychotropic medications, as part of a more personalized approach to prescribing. This may improve the use of and adherence to these medications. Yet to date, the implementation of PGx in mental health environments in the United Kingdom has been slow. This review aims to identify the current barriers and enablers to the implementation of PGx in psychiatry and determine how this can be applied to the uptake of PGx by NHS mental health providers. A systematic searching strategy was developed, and searches were carried out on the PsychInfo, EmBase, and PubMed databases, yielding 11 appropriate papers. Common barriers to the implementation of PGx included cost, concerns over incorporation into current workflow and a lack of knowledge about PGx; whilst frequent enablers included optimism that PGx could lead to precision medicine, reduce ADRs and become a more routine part of psychiatric clinical care. The uptake of PGx in psychiatric care settings in the NHS should consider and overcome these barriers, while looking to capitalize on the enablers identified in this review.

Exploring the Role of Alcohol Metabolizing Genotypes in a 12-Week Clinical Trial of Naltrexone for Alcohol Use Disorder

Background: The efficacy of naltrexone in the treatment of alcohol use disorder (AUD) has been associated with a set of variables not directly related with the expression of opioid receptors. All the variables have been found to be highly associated with AUD itself or more severe clinical levels of AUD. Objectives: Given the high association between alcohol metabolizing enzymes (AME) and the outcome of AUD, the present study aims to investigate the role of AME genotype variants in the treatment of AUD with naltrexone. Methods: We carried out a 12-week longitudinal clinical trial based on the treatment of AUD patients with naltrexone (N = 101), stratified by different alcohol metabolization genotypes. Genotyping was performed after the inclusion of the patients in the study, based on the individual presence of single nucleotide polymorphisms (SNPs) in the ADH (alcohol dehydrogenase)1B (ADH1B*2 and ADH1B*3), ADH1C (ADHC*1) and ALDH (aldehyde dehydrogenase) 2 (ALDH2*2) genes. The outcome of alcohol use has been monitored employing the timeline follow-back during the treatment. Results: The ADH1C*1 (Ile350Val, rs698) and ALDH2*2 (Glu504Lys, rs671) polymorphisms were associated with a better response to naltrexone treatment, whereas the ADH1B*3 (Arg370Cys, rs2066702) allelic variant showed a negative outcome. Conclusions: The present study explores a genomic setting for the treatment of AUD with naltrexone. According to our findings, the association between ADH1C*1 and ALDH2*2 variants and better outcomes suggests a successful treatment, whereas the ADH1B*3 mutated allele might lead to an unsuccessful treatment. Further studies should be performed to investigate the relationship between alcohol metabolizing genotypes, the family history of alcohol use disorders and the effect of naltrexone on the outcomes. Genotyping may be a valuable tool for precision-medicine and individualized approach, especially in the context of alcohol use disorders. The small number of subjects was the main limitation of the present study.

Pharmacist-Led Medication Evaluation Considering Pharmacogenomics and Drug-Induced Phenoconversion in the Treatment of Multiple Comorbidities: A Case Report

Pharmacogenomic (PGx) information can guide drug and dose selection, optimize therapy outcomes, and/or decrease the risk of adverse drug events (ADEs). This report demonstrates the impact of a pharmacist-led medication evaluation, with PGx assisted by a clinical decision support system (CDSS), of a patient with multiple comorbidities. Following several sub-optimal pharmacotherapy attempts, PGx testing was recommended. The results were integrated into the CDSS, which supported the identification of clinically significant drug–drug, drug–gene, and drug–drug–gene interactions that led to the phenoconversion of cytochrome P450. The pharmacist evaluated PGx results, concomitant medications, and patient-specific factors to address medication-related problems. The results identified the patient as a CYP2D6 intermediate metabolizer (IM). Duloxetine-mediated competitive inhibition of CYP2D6 resulted in phenoconversion, whereby the patient’s CYP2D6 phenotype was converted from IM to poor metabolizer for CYP2D6 co-medication. The medication risk score suggested a high risk of ADEs. Recommendations that accounted for PGx and drug-induced phenoconversion were accepted. After 1.5 months, therapy changes led to improved pain control, depression status, and quality of life, as well as increased heart rate, evidenced by patient-reported improved sleep patterns, movement, and cognition. This case highlights the pharmacist’s role in using PGx testing and a CDSS to identify and mitigate medication-related problems to optimize medication regimen and medication safety.

Economic Impact of the Application of a Precision Medicine Model (5SPM) on Psychotic Patients

BACKGROUND

Schizophrenia is a severe mental disorder that often manifests within the first three decades of life. Its prognosis is uncertain and may result in a prolonged treatment that could extend throughout the entire lifespan of the patient. Antipsychotic drugs are characterized by a high interindividual variability when considering therapeutic effect and emergence of adverse effects. Such interindividual variability is thought to be associated primarily with pharmacokinetic matters.

OBJECTIVE

The objective of this study was to evaluate the economic impact of the application of the 5-Step Precision Medicine model (5SPM), an approach based on the pharmacogenetic analysis of the primary genes involved in the metabolism of the therapy for each patient, restructuring treatment as necessary.

PATIENTS AND METHODS

One hundred eighty-eight psychiatry patients were analysed for single nucleotide polymorphisms on genes CYP1A2, CYP2B6, CYP2C9, CYP2C19, CYP2D6, CYP3A5 and ABCB1. Information on patients' diagnosis, pharmacotherapy, and hospitalizations was collected.

RESULTS

We achieved a cost-benefit ratio of 3.31-3.59 with a reduction of direct cost (hospitalizations plus pharmacotherapy) with a reduction of total cost in 67% of the patients who underwent the clinical intervention.

CONCLUSION

A rational Precision Medicine-based approach to psychiatric patients could result in a reduction on number of drugs required to control exacerbations, and the underlying pathologies, reducing the risk of adverse effects and improving adherence to treatment, leading to a potential decrease in direct costs. This methodology has been shown to be cost-dominant and, being based on a pharmacogenetic analysis, it has a lifelong nature, as the data obtained can be applied to other medical disciplines.

CYP2D6 phenotype and ABCB1 haplotypes are associated with antipsychotic safety in adolescents experiencing acute psychotic episodes

OBJECTIVES

To identify possible associations of CYP2D6, CYP3A4/5, and ABCB1 gene polymorphisms with the efficacy and safety of antipsychotics in adolescents with acute psychotic episodes.

METHODS

We examined the associations of pharmacogenetic factors with the efficacy and safety of antipsychotics in 101 adolescents with acute psychotic episodes. The diagnosis on admission was "Brief psychotic disorder" (F23.0-23.9 by ICD-10). All patients were administered antipsychotics for 14 days. Treatment efficacy and safety were assessed using the PANSS, CGAS, CGI-S(I), UKU SERS, BARS, and SAS scales. Pharmacokinetic genotyping was performed for the CYP2D6*4, *10, ABCB1 1236C>T, 2677G>T, and 3435C>T genes.

RESULTS

CYP2D6 intermediate metabolisers had "Micturition disturbances" more often than extensive metabolisers (24.2 vs. 7.4%; p=0.026). "Wild" homozygote ABCB1 3435C>T CC was associated with more prominent akathisia. Haplotype analysis of three ABCB1 polymorphisms revealed that the "wild" alleles "C-G-C" (ABCB1 1236-2677-3435) were associated with higher risk of "Reduced salivation" (OR=2.95; 95% CI=1.35-6.45; p=0.0078).

CONCLUSIONS

CYP2D6 intermediate metabolism was associated with the risk of urinary difficulties under treatment with antipsychotics. We found that "wild" homozygotes ABCB1 1236C>T, 2677G>T, and 3435C>T were predictors of adverse drug effects caused by treatment with antipsychotics.

CYP2D6 phenotype and ABCB1 haplotypes are associated with antipsychotic safety in adolescents experiencing acute psychotic episodes

OBJECTIVES

To identify possible associations of CYP2D6, CYP3A4/5, and ABCB1 gene polymorphisms with the efficacy and safety of antipsychotics in adolescents with acute psychotic episodes.

METHODS

We examined the associations of pharmacogenetic factors with the efficacy and safety of antipsychotics in 101 adolescents with acute psychotic episodes. The diagnosis on admission was "Brief psychotic disorder" (F23.0-23.9 by ICD-10). All patients were administered antipsychotics for 14 days. Treatment efficacy and safety were assessed using the PANSS, CGAS, CGI-S(I), UKU SERS, BARS, and SAS scales. Pharmacokinetic genotyping was performed for the CYP2D6*4, *10, ABCB1 1236C>T, 2677G>T, and 3435C>T genes.

RESULTS

CYP2D6 intermediate metabolisers had "Micturition disturbances" more often than extensive metabolisers (24.2 vs. 7.4%; p=0.026). "Wild" homozygote ABCB1 3435C>T CC was associated with more prominent akathisia. Haplotype analysis of three ABCB1 polymorphisms revealed that the "wild" alleles "C-G-C" (ABCB1 1236-2677-3435) were associated with higher risk of "Reduced salivation" (OR=2.95; 95% CI=1.35-6.45; p=0.0078).

CONCLUSIONS

CYP2D6 intermediate metabolism was associated with the risk of urinary difficulties under treatment with antipsychotics. We found that "wild" homozygotes ABCB1 1236C>T, 2677G>T, and 3435C>T were predictors of adverse drug effects caused by treatment with antipsychotics.

Clinical Relevance of a 16-Gene Pharmacogenetic Panel Test for Medication Management in a Cohort of 135 Patients

There is a growing number of evidence-based indications for pharmacogenetic (PGx) testing. We aimed to evaluate clinical relevance of a 16-gene panel test for PGx-guided pharmacotherapy. In an observational cohort study, we included subjects tested with a PGx panel for variants of ABCB1, COMT, CYP1A2, CYP2B6, CYP3A4, CYP3A5, CYP2C9, CYP2C19, CYP2D6, CYP4F2, DPYD, OPRM1, POR, SLCO1B1, TPMT and VKORC1. PGx-guided pharmacotherapy management was supported by the PGx expert system SONOGEN XP. The primary study outcome was PGx-based changes and recommendations regarding current and potential future medication. PGx-testing was triggered by specific drug-gene pairs in 102 subjects, and by screening in 33. Based on PharmGKB expert guidelines we identified at least one "actionable" variant in all 135 (100%) tested patients. Drugs that triggered PGx-testing were clopidogrel in 60, tamoxifen in 15, polypsychopharmacotherapy in 9, opioids in 7, and other in 11 patients. Among those, PGx variants resulted in clinical recommendations to change PGx-triggering drugs in 33 (32.4%), and other current pharmacotherapy in 23 (22.5%). Additional costs of panel vs. single gene tests are moderate, and the efficiency of PGx panel testing challenges traditional cost-benefit calculations for single drug-gene pairs. However, PGx-guided pharmacotherapy requires specialized expert consultations with interdisciplinary collaborations.

Antipsychotic Polypharmacy for the Management of Schizophrenia: Evidence and Recommendations

Schizophrenia is a debilitating illness with a lifetime prevalence estimate of 0.6% and consists of symptoms from the positive, negative, and cognitive domains. Social support, therapy, psychoeducation, and overall case management are very important aspects of the treatment of schizophrenia. However, as abnormalities in neurotransmission are one of the key findings of schizophrenia pathology, pharmacotherapies are cornerstones of the management of schizophrenia. Antipsychotics have been used as the primary pharmacological treatment of schizophrenia. These agents often have a good effect on reducing positive symptoms, but may not markedly improve negative symptoms or cognitive defects. However, at least 20% of individuals with schizophrenia do not experience a substantial response from monotherapy with antipsychotics. Further, despite evolving treatment protocols and advances in early recognition of the disorder, 70% of patients with schizophrenia require long-term, even lifetime, medication to control their symptoms and do not achieve complete recovery. To address these shortcomings, clinicians and research scientists have explored different combinations of treatments, polypharmacy, to improve the treatment of patients. Antipsychotic polypharmacy has been shown to cause more side effects than monotherapy, which is the main reason why most treatment guidelines caution against it. Antipsychotic monotherapy should be strived for and clozapine should be tried at the latest if two monotherapy trials with other antipsychotics have failed and no absolute contraindications exist. If residual symptoms exist despite trials of adequate dose and duration, other reasons that may reduce treatment effect should be ruled out. Long-acting injectables or blood concentration measurements should be considered to affirm compliance and proper serum levels. Antipsychotic polypharmacy should be considered and discussed with patients from whom the aforementioned procedures do not produce a satisfactory treatment result. In some cases, antipsychotic polypharmacy may produce better results than other forms of treatment augmentation, such as benzodiazepines. In particular, combining aripiprazole with clozapine may be effective in reducing treatment side effects or residual symptoms, and this is likely to hold true for combining other partial dopamine D₂ agonists with clozapine as well, although currently scant data exist. More research is needed, both in controlled but also real-world settings, to define optimal antipsychotic polypharmacy and/or other psychotropic treatment augmentation strategies for specific patient groups and situations.

Prescription Pattern of Antidepressants and the Potential for Personalized Medicine in the Qatari Population

Studying the prescription pattern of medications will help in understanding potential unnecessary prescriptions, due to the trial-and-error method of prescribing, and the need for personalized medicine in a population. Therefore, in this study, our aim was to explore the prescribing pattern and off-label use of antidepressants in the Qatari population. We conducted a retrospective study of Qatari patients who received prescriptions for antidepressants from the major healthcare providers in Qatar, for a period of 24 months between June 2018 and May 2020. The number of patients, prescriptions, and diagnostic indications were analyzed. The chi-square test was used for identifying statistically significant association of the number of individuals prescribed with age category or gender. Of the 14,601 Qatari patients who were prescribed antidepressants, the majority were female (61%, p < 2.2 × 10^-16), and were at or above 60 years of age (27%, p < 2.2 × 10^-16). More numbers of selective serotonin reuptake inhibitors (SSRIs) (22,085 out of 48,031; 46%), were dispensed than other classes of antidepressants, with escitalopram (26%) at the top of the list. Preponderance of prescription of antidepressants for non-mental health diseases was observed. Population-level prescription trends, as we reported here, when combined with patient genetic variability and outcome data, will have the power to predict the potential for treatment failures and adverse effects of these medications in the population. We also recommend educating non-mental health prescribers about the adherence to evidence and guidelines to ensure patient safety while prescribing antidepressants.

CYP2D6 Reduced Function Variants and Genotype/Phenotype Translations of CYP2D6 Intermediate Metabolizers: Implications for Personalized Drug Dosing in Psychiatry

Genetic differences in cytochrome P450 (CYP)-mediated metabolism have been known for several decades. The clinically most important polymorphic CYP enzyme is CYP2D6, which plays a key role in the metabolism of many antidepressants and antipsychotics, along with a range of non-psychiatric medications. Dose individualization based on CYP2D6 genotype to improve the effect and safety of drug treatment has been an ambition for a long time. Clinical use of CYP2D6 genotyping is steadily increasing; however, for pre-emptive genotyping to be successful in predicting individual dose requirements, high precision of genotype-to-phenotype translations are required. Recently, guidelines for assigning CYP2D6 enzyme activity scores of CYP2D6 variant alleles, and subsequent diplotype-to-phenotype translations, were published by the Clinical Pharmacogenetics Implementation Consortium (CPIC) and the Dutch Pharmacogenetics Working Group. Consensus on assigning activity scores of CYP2D6 variant alleles and translating diplotype scores into CYP2D6 poor, intermediate, normal, or ultrarapid metabolizer groups were obtained by consulting 37 international experts. While assigning enzyme activities of non-functional (score 0) and fully functional (score 1) alleles are straightforward, reduced function variant alleles are more complex. In this article, we present data showing that the assigned activity scores of reduced function variant alleles in current guidelines are not of sufficient precision; especially not for CYP2D6*41, where the guideline activity score is 0.5 compared to 0.05–0.15 in pharmacogenetic studies. Due to these discrepancies, CYP2D6 genotypes with similar guidelinediplotype scores exhibit substantial differences in CYP2D6 metabolizer phenotypes. Thus, it is important that the guidelines are updated to be valid in predicting individual dose requirements of psychiatric drugs and others metabolized by CYP2D6.

A Novel CYP2C-Haplotype Associated With Ultrarapid Metabolism of Escitalopram

Escitalopram is one of the most commonly used antidepressant drugs but exhibits a substantial interindividual variation in clinical response. A key factor underlying response differences is the polymorphic nature of the CYP2C19 gene encoding the major enzyme responsible for escitalopram metabolism. Although pre-emptive CYP2C19 genotyping may improve escitalopram treatment outcome by dose individualization, much of the interindividual variability cannot be assigned to the currently known CYP2C19 gene variants. The aim of the present study was to search for novel CYP2C-haplotypes for better genetic prediction of escitalopram metabolism. First, the CYP2C18/CYP2C19 locus was sequenced from gDNA obtained from 24 patients previously genotyped as CYP2C19*1/*1 showing consistently low serum concentrations of escitalopram (< 25 nM/10 mg). Three new haplotypes of the CYP2C locus (CYP2C:TG, CYP2C:TA, and CYP2C:CG) were here identified, and their functional roles were evaluated using gDNA from 875 previously genotyped escitalopram-treated patients. The CYP2C:CG and CYP2C:TA haplotypes had no significant impact on escitalopram concentration. Based on the estimated effects of the novel CYP2C-haplotypes on escitalopram exposure, the predicted serum concentrations of escitalopram in homozygous CYP2C:TG and CYP2C19*17 carriers were 24.8% and 17.3% lower compared with the baseline (CYP2C:CG and CYP2C:TA), respectively. In conclusion, a novel CYP2C-haplotype defined by rs2860840T and rs11188059G associated with ultrarapid metabolism of escitalopram was identified. Further studies should clarify the genetic basis for the enhanced escitalopram metabolism and the impact of the CYP2C:TG haplotype on the metabolism of other CYP2C19 substrates like omeprazole, voriconazole, and clopidogrel.

Policy and Practice Review: A First Guideline on the Use of Pharmacogenetics in Clinical Psychiatric Practice

Effective pharmacologic treatments for psychiatric disorders are available, but their effect is limited due to patients' genetic heterogeneity and low compliance-related to frequent adverse events. Only one third of patients respond to treatment and experience remission. Pharmacogenetics is a relatively young field which focusses on genetic analyses in the context of the metabolism and outcome of drug treatment. These genetic factors can, among other things, lead to differences in the activity of enzymes that metabolize drugs. Recently, a clinical guideline was authorized by the Dutch Clinical Psychiatric Association (NVvP) on the clinical use of pharmacogenetics in psychiatry. The main goal was to provide guidance, based on current evidence, on how to best use genotyping in clinical psychiatric practice. A systematic literature search was performed, and available publications were assessed using the GRADE methodology. General recommendations for psychiatric clinical practice were provided, and specific recommendations per medication were made available. This clinical guideline for caregivers prescribing psychotropic drugs is the product of a broad collaboration of professionals from different disciplines, making use of the information available at the Dutch Pharmacogenetics Working Group (DPWG) and the Clinical Pharmacogenetics Implementation Consortium (CPIC) so far. We summarize the relevant literature and all recommendations in this article. General recommendations are provided and also detailed recommendations per medication. In summary we advise to consider genotyping, when there are side effects or inefficacy for CYP2C19 and CYP2D6. When genotype information is available use this to select the right drug in the right dose for the right patient.

Prospects for personalization of depression treatment with genome sequencing

The effectiveness of antidepressants in the treatment of major depressive disorder varies considerably between patients. With these interindividual differences and a number of antidepressants to choose from, the first choice of treatment often fails to produce improvement in the patient's condition. A substantial part of the variation in response to antidepressants can be explained by genetic factors. Accordingly, variants related to drug metabolism in two pharmacogenes, CYP2D6 and CYP2C19, have already been translated into guidelines for antidepressant prescriptions. The role of variants in other genes that influence antidepressant responses is not yet understood. Furthermore, rare and individual variants account for a substantial part of genetic differences in antidepressant efficacy. Recent years have brought a tremendous increase in the accessibility of genome sequencing in terms of data availability and its clinical use. In this review, we summarize recent developments and current issues in the personalization of major depressive disorder treatment through pharmacogenomics.

CYP2D6 and Antipsychotic Treatment Outcomes in Children and Youth: A Systematic Review

Objective: To systematically review the impact of CYP2D6 genetic variation on antipsychotic pharmacokinetics, efficacy, and adverse drug reactions among children and youth. Method: The published literature was systematically searched in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses recommendations and critically evaluated using standardized tools and consensus criteria. Results: A total of 20 eligible studies comprising 1078 children and youth were evaluated. The included studies were of fair to moderate quality and included mostly males, individuals of European ancestry, and those treated with risperidone. CYP2D6 poor metabolizers (PMs) were consistently shown to have increased concentrations of risperidone relative to normal metabolizers (NMs). PMs were also consistently shown to have a greater propensity to experience antipsychotic (primarily risperidone) associated adverse drug reactions relative to NMs. However, robust evidence for an association between CYP2D6 and efficacy was less apparent. Conclusion and Clinical Significance: The current knowledge base suggests that CYP2D6 genetic variation has an appreciable impact on antipsychotic pharmacokinetics and the propensity for adverse drug reactions, particularly among children receiving risperidone treatment. However, several limitations with the current literature (e.g., sample sizes, study design, sample heterogeneity) should be addressed in future studies. Assuming that future studies support the link between CYP2D6 genetic variation and antipsychotic outcomes, we would anticipate an increase in the implementation of CYP2D6-guided antipsychotic drug selection and dose optimization in child and adolescent psychiatric services.

Towards personalized pharmacology: Antipsychotics and schizophrenia

Since the discovery of the first antipsychotic in 1952, many antipsychotic drugs have been developed, each with different pharmacokinetic and pharmacodynamic properties. The pharmacological heterogeneity of antipsychotic drugs should allow a personalized drug prescription adapted to the different clinical picture of schizophrenia. Schizophrenia is a chronic disease, during which 3 stages of pharmacological intervention can be identified: the first episode psychotic (FEP), the phase of therapeutic stabilization that can progress to situations of resistance, and the question of long-term prescription. During FEP, the choice of the first antipsychotic treatment seems to be underpinned by its safety profile in relation to the patient for whom it is prescribed, according to the adage start low and go-slow. The therapeutic stabilization phase is based on treatment optimization through a rigorous evaluation of the benefits-harm balance, with the use of tools such as personalized therapeutic drug monitoring and pharmacogenetics. Generally speaking, while some antipsychotic drugs seem to present a more favorable efficacy profile in certain situations, the differences are small, whereas the differences in safety are more important and should be considered in the first line. Individual factors such as the presence of co-morbidities, as well as previously experienced treatments must also be taken into account. Finally, the question of maintaining the prescription of antipsychotic drugs over the long term arises in view of the iatrogenic risk with controversial current data. Overall, the personalized prescription of antipsychotic drugs in schizophrenia remains limited by a lack of data in the literature, justifying the development of clinical studies in this field. But at present, the dogma remains that of primum non nocere.