Impact of polymorphisms in transporter and metabolizing enzyme genes on olanzapine pharmacokinetics and safety in healthy volunteers

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

BACKGROUND

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

METHODS

In these Guidelines, we provide an in-depth review of pharmacokinetics, pharmacodynamics, and pharmacogenetics for 50 antipsychotics. Over 30 international experts in psychiatry selected studies that have measured drug concentrations in the blood (TDM), gene polymorphisms of enzymes involved in drug metabolism, or receptor/transporter occupancies in the brain (positron emission tomography (PET)).

RESULTS

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

CONCLUSION

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

Effects of CYP2D6 gene polymorphism on plasma concentration and therapeutic effect of olanzapine

This study aimed to evaluate the relationship between gene polymorphisms of metabolic enzymes, particularly the CYP2D6 gene, and the plasma concentration of olanzapine, as well as treatment response in patients with chronic schizophrenia. We recruited olanzapine-treated patients and examined their plasma olanzapine levels. Additionally, a common mutation site within each of the nine exons of the full-length CYP2D6 sequence was assayed. The Positive and Negative Syndrome Scale, Brief Psychiatric Rating Scale, and Overall Clinical Impression were used to assess schizophrenic symptoms, whereas the Barnes Akathisia Scale and Extrapyramidal Symptom Rating Scale were used to evaluate adverse effects. The results showed no significant differences in plasma olanzapine concentrations, treatment response, or the occurrence of adverse effects among different CYP2D6 genotypes. However, an association between olanzapine concentrations and improvement in clinical symptoms and adverse reactions was observed. In conclusion, the CYP2D6 genotype did not significantly impact plasma olanzapine concentrations, treatment response, or the occurrence of adverse effects.

CYP1A2 expression rather than genotype is associated with olanzapine concentration in psychiatric patients

Olanzapine is a commonly prescribed atypical antipsychotic agent for treatment of patients with schizophrenia and bipolar disorders. Previous in vitro studies using human liver microsomes identified CYP1A2 and CYP2D6 enzymes being responsible for CYP-mediated metabolism of olanzapine. The present work focused on the impact of CYP1A2 and CYP2D6 genetic polymorphisms as well as of CYP1A2 metabolizing capacity influenced by non-genetic factors (sex, age, smoking) on olanzapine blood concentration in patients with psychiatric disorders (N = 139). CYP2D6 genotype-based phenotype appeared to have negligible contribution to olanzapine metabolism, whereas a dominant role of CYP1A2 in olanzapine exposure was confirmed. However, CYP1A2 expression rather than CYP1A2 genetic variability was demonstrated to be associated with olanzapine concentration in patients. Significant contribution of - 163C > A (rs762551), the most common SNP (single nucleotide polymorphism) in CYP1A2 gene, to enhanced inducibility was confirmed by an increase in CYP1A2 mRNA expression in smokers carrying - 163A, and smoking was found to have appreciable impact on olanzapine concentration normalized by the dose/bodyweight. Furthermore, patients' olanzapine exposure was in strong association with CYP1A2 expression; therefore, assaying CYP1A2 mRNA level in leukocytes can be an appropriate tool for the estimation of patients' olanzapine metabolizing capacity and may be relevant in optimizing olanzapine dosage.

Pharmacogenetics and Schizophrenia-Can Genomics Improve the Treatment with Second-Generation Antipsychotics?

Schizophrenia (SCZ) is a complex psychiatric disorder of multifactorial origin, in which both genetic and environmental factors have an impact on its onset, course, and outcome. Large variability in response and tolerability of medication among individuals makes it difficult to predict the efficacy of a chosen therapeutic method and create universal and precise guidelines for treatment. Pharmacogenetic research allows for the identification of genetic polymorphisms associated with response to a chosen antipsychotic, thus allowing for a more effective and personal approach to treatment. This review focuses on three frequently prescribed second-generation antipsychotics (SGAs), risperidone, olanzapine, and aripiprazole, and aims to analyze the current state and future perspectives in research dedicated to identifying genetic factors associated with antipsychotic response. Multiple alleles of genes involved in pharmacokinetics (particularly isoenzymes of cytochrome P450), as well as variants of genes involved in dopamine, serotonin, and glutamate neurotransmission, have already been identified as ones of significant impact on antipsychotic response. It must, however, be noted that although currently obtained results are promising, trials with bigger study groups and unified protocols are crucial for standardizing methods and determining objective antipsychotic response status.

CYP2C8*3 and *4 define CYP2C8 phenotype: An approach with the substrate cinitapride

Cinitapride is a gastrointestinal prokinetic drug, prescribed for the treatment of functional dyspepsia, and as an adjuvant therapy for gastroesophageal reflux disease. In this study, we aimed to explore the impact of relevant variants in CYP3A4 and CYP2C8 and other pharmacogenes, along with demographic characteristics, on cinitapride pharmacokinetics and safety; and to evaluate the impact of CYP2C8 alleles on the enzyme's function. Twenty-five healthy volunteers participating in a bioequivalence clinical trial consented to participate in the study. Participants were genotyped for 56 variants in 19 genes, including cytochrome P450 (CYP) enzymes (e.g., CYP2C8 or CYP3A4) or transporters (e.g., SLC or ABC), among others. CYP2C8*3 carriers showed a reduction in AUC of 42% and C_max of 35% compared to *1/*1 subjects (p = 0.003 and p = 0.011, respectively). *4 allele carriers showed a 45% increase in AUC and 63% in C_max compared to *1/*1 subjects, although these differences did not reach statistical significance. CYP2C8*3 and *4 alleles may be used to infer the following pharmacogenetic phenotypes: ultrarapid (UM) (*3/*3), rapid (RM) (*1/*3), normal (NM) (*1/*1), intermediate (IM) (*1/*4), and poor (PM) metabolizers (*4/*4). In this study, we properly characterized RMs, NMs, and IMs; however, additional studies are required to properly characterize UMs and PMs. These findings should be relevant with respect to cinitapride, but also to numerous CYP2C8 substrates such as imatinib, loperamide, montelukast, ibuprofen, paclitaxel, pioglitazone, repaglinide, or rosiglitazone.

Is the CYP2D6 Genotype Associated with Antipsychotic-Induced Weight Gain?

Antipsychotic-induced weight gain (AIWG) is a serious adverse effect. Studies have linked genetically-predicted CYP2D6 metabolic capacity to AIWG. The evidence, however, is ambiguous. We performed multiple regression analyses examining the association between genetic-predicted CYP2D6 metabolic capacity and AIWG. Analyses were based on previously unpublished data from an RCT investigating the clinical utility of routine genotyping of CYP2D6 and CYP2C19 in patients with schizophrenia. A total of 211 patients, corresponding to 71% of the original study population, were included. Our analyses indicated an effect of genetically predicted CYP2D6 metabolic capacity on AIWG with significant weight gain in both CYP2D6 poor metabolizers (PMs) (4.00 kg (95% CI: 0.80; 7.21)) and ultrarapid metabolizers (UMs) (6.50 kg (95% CI: 1.03; 12.0)). This finding remained stable after adjustment for covariates (PMs: 4.26 kg (0.88; 7.64), UMs: 7.26 kg (1.24; 13.3)). In addition to the CYP2D6 metabolic capacity, both baseline body mass index (−0.24 (95% CI: −0.44; −0.03)) and chlorpromazine equivalents per day (0.0041 (95% CI: 0.0005; 0.0077)) were statistically significantly associated with weight change in the adjusted analysis. Our results support that the genetically predicted CYP2D6 metabolic capacity matters for AIWG.

Association between CYP2C19 and CYP2B6 phenotypes and the pharmacokinetics and safety of diazepam

Diazepam is a benzodiazepine (BZD) used worldwide for a variety of conditions. Long-term use of diazepam increases the risk for developing tolerance and dependence and for the occurrence of adverse drug reactions (ADRs). CYP3A4 and CYP2C19 mainly metabolize diazepam and are therefore the primary pharmacogenetic candidate biomarkers. In this work, we aimed to explore the impact of CYP3A4 and CYP2C19 phenotypes and of 99 additional variants in other 31 pharmacogenes (including other CYP, UGT, NAT2 and CES enzymes, ABC and SLC transporters) on diazepam pharmacokinetic variability and safety. 30 healthy volunteers that had participated in a single-dose bioequivalence clinical trial of two diazepam formulations were enrolled in the present candidate gene pharmacogenetic study. CYP2C19 poor metabolizers (PMs) showed an almost 2-fold increase in AUC_0-∞/DW compared to rapid (RMs) or normal (NM) metabolizers, and a 1.46-fold increase compared to intermediate metabolizers (IMs). CYP2B6 PMs showed a 2,74-fold higher AUC_0-∞/DW compared to RMs, and 2.10-fold compared to NMs (p < 0.007). A dose reduction of 25-50 % may be appropriate for CYP2C19 or CYP2B6 PMs to avoid ADRs, dependence and tolerance. Combined CYP2C19 +CYP2B6 PMs may not use diazepam or sharper dose adjustments (e.g., a dose reduction of 50-70 %) may be advisable. To our knowledge, this is the first work to report a strong relationship between CYP2B6 phenotype and diazepam pharmacokinetics. Additional nominal associations (i.e., 0.007 <p < 0.05) between ABCG2, ABCB1, NAT2 and UGT1A4 polymorphisms and pharmacokinetic variability were observed; further research should elaborate on the clinical relevance of the described associations.

Integrative omics of schizophrenia: from genetic determinants to clinical classification and risk prediction

Schizophrenia (SCZ) is a debilitating neuropsychiatric disorder with high heritability and complex inheritance. In the past decade, successful identification of numerous susceptibility loci has provided useful insights into the molecular etiology of SCZ. However, applications of these findings to clinical classification and diagnosis, risk prediction, or intervention for SCZ have been limited, and elucidating the underlying genomic and molecular mechanisms of SCZ is still challenging. More recently, multiple Omics technologies - genomics, transcriptomics, epigenomics, proteomics, metabolomics, connectomics, and gut microbiomics - have all been applied to examine different aspects of SCZ pathogenesis. Integration of multi-Omics data has thus emerged as an approach to provide a more comprehensive view of biological complexity, which is vital to enable translation into assessments and interventions of clinical benefit to individuals with SCZ. In this review, we provide a broad survey of the single-omics studies of SCZ, summarize the advantages and challenges of different Omics technologies, and then focus on studies in which multiple omics data are integrated to unravel the complex pathophysiology of SCZ. We believe that integration of multi-Omics technologies would provide a roadmap to create a more comprehensive picture of interactions involved in the complex pathogenesis of SCZ, constitute a rich resource for elucidating the potential molecular mechanisms of the illness, and eventually improve clinical assessments and interventions of SCZ to address clinical translational questions from bench to bedside.

Effects of Cytochrome P450 and Transporter Polymorphisms on the Bioavailability and Safety of Dutasteride and Tamsulosin

Dutasteride and tamsulosin are one of the first-line combination therapies for the management of benign prostatic hyperplasia (BPH). Despite being more effective than monotherapies, they produce frequent adverse drug reactions (ADRs). Institutions such as Food and Drug Administration and European Medicines Agency recommend precaution with CYP2D6 poor metabolizers (PMs) that receive CYP3A4 inhibitors and tamsulosin. However, no specific pharmacogenetic guideline exists for tamsulosin. Furthermore, to date, no pharmacogenetic information is available for dutasteride. Henceforth, we studied the pharmacokinetics and safety of dutasteride/tamsulosin 0.5 mg/0.4 mg capsules according to 76 polymorphisms in 17 candidate pharmacogenes. The study population comprised 79 healthy male volunteers enrolled in three bioequivalence, phase-I, crossover, open, randomized clinical trials with different study designs: the first was single dose in fed state, the second was a single dose in fasting state, and the third was a multiple dose. As key findings, CYP2D6 PMs (i.e., *4/*4 and *4/*5 subjects) and intermediate metabolizers (IMs) (i.e., *1/*4, *1/*5, *4/*15 individuals) presented higher AUC (p = 0.004), higher t_1/2 (p = 0.008), and lower Cl/F (p = 0.006) when compared with NMs (*1/*1 individuals) and UMs (1/*1 × 2 individuals) after multiple testing correction. Moreover, fed volunteers showed significantly higher t_max than fasting individuals. Nominally significant associations were observed between dutasteride exposure and CYP3A4 and CYP3A5 genotype and between tamsulosin and ABCG2, CYP3A5, and SLC22A1 genotypes. No association between the occurrence of adverse drug reactions and genotype was observed. Nonetheless, higher incidence of adverse events was found in a multiple-dose clinical trial. Based on our results, we suggest that dose adjustments for PMs and UMs could be considered to ensure drug safety and effectiveness, respectively. Further studies are warranted to confirm other pharmacogenetic associations.

Genetic Polymorphisms Associated With the Pharmacokinetics, Pharmacodynamics and Adverse Effects of Olanzapine, Aripiprazole and Risperidone

Olanzapine, aripiprazole and risperidone are atypical antipsychotics or neuroleptics widely used for schizophrenia treatment. They induce various adverse drug reactions depending on their mechanisms of action: metabolic effects, such as weight gain and alterations of glucose and lipid metabolism; hyperprolactinemia and extrapyramidal effects, such as tremor, akathisia, dystonia, anxiety and distress. In this review, we listed polymorphisms associated with individual response variability to olanzapine, aripiprazole and risperidone. Olanzapine is mainly metabolized by cytochrome P450 enzymes, CYP1A2 and CYP2D6, whereas aripiprazole and risperidone metabolism is mainly mediated by CYP2D6 and CYP3A4. Polymorphisms in these genes and other enzymes and transporters, such as enzymes from the uridine 5'-diphospho-glucuronosyltransferase (UGT) family and ATP-binding cassette sub-family B member 1 (ABCB1), are associated to differences in pharmacokinetics. The three antipsychotics act on dopamine and serotonin receptors, among others, and several studies found associations between polymorphisms in these genes and variations in the incidence of adverse effects and in the response to the drug. Since olanzapine is metabolized by CYP1A2, a lower starting dose should be considered in patients treated with fluvoxamine or other CYP1A2 inhibitors. Regarding aripiprazole, a reduced dose should be administered in CYP2D6 poor metabolizers (PMs). Additionally, a reduction to a quarter of the normal dose is recommended if the patient is treated with concomitant CYP3A4 inhibitors. Risperidone dosage should be reduced for CYP2D6 PMs and titrated for CYPD6 ultrarapid metabolizers (UMs). Moreover, risperidone dose should be evaluated when a CYP2D6, CYP3A4 or ABCB1 inhibitor is administered concomitantly.

Second-generation antipsychotic use during pregnancy and risk of congenital malformations

Purpose

To study if second-generation antipsychotic (S-GA) use during the first trimester of pregnancy is associated with an increased risk of major congenital malformations (MCM).

Methods

A population-based birth cohort study using national register data extracted from the Drugs and Pregnancy database in Finland, years 1996–2017. The sampling frame included 1,273,987 pregnant women. We included singleton pregnancies ending in live or stillbirth or termination of pregnancy due to severe malformation. Pregnancies with exposure to known teratogens were excluded. Women were categorized into three groups: exposed to S-GAs (n = 3478), exposed to first-generation antipsychotics (F-GAs) (n = 1030), and unexposed (no purchases of S-GAs or F-GAs during pregnancy, n = 22,540). We excluded genetic conditions and compared the prevalence of MCMs in S-GA users to the two comparison groups using multiple logistic regression models.

Results

Use of S-GAs during early pregnancy was not associated with an increased risk of overall MCMs compared to unexposed (adjusted odds ratio, OR 0.92; 95% CI 0.72–1.19) or to F-GA users (OR 0.82; 95% CI 0.56–1.20). Of individual S-GAs, olanzapine use was associated with an increased risk of overall MCMs (OR 2.12; 95% CI 1.19–3.76), and specifically, an increased risk of musculoskeletal malformations (OR 3.71; 95% CI 1.35–10.1) when compared to unexposed, while comparisons to F-GA users did not show significant results.

Conclusions

Olanzapine use is associated with an increased risk of major congenital malformations and specifically, musculoskeletal malformations. Use during pregnancy should be restricted to situations where no safer alternatives exist.

Supplementary information

The online version contains supplementary material available at 10.1007/s00228-021-03169-y.

SLCO1B1 Phenotype and CYP3A5 Polymorphism Significantly Affect Atorvastatin Bioavailability

Atorvastatin, prescribed for the treatment of hypercholesterolemia, demonstrated overwhelming benefits in reducing cardiovascular morbidity and mortality. However, many patients discontinue therapy due to adverse reactions, especially myopathy. The Dutch Pharmacogenetics Working Group (DPWG) recommends an alternative agent to atorvastatin and simvastatin or a dose adjustment depending on other risk factors for statin-induced myopathy in SLCO1B1 rs4149056 CC or TC carriers. In contrast, the Clinical Pharmacogenetics Implementation Consortium (CPIC) published their guideline on simvastatin, but not on atorvastatin. In this work, we aimed to demonstrate the effect of SLCO1B1 phenotype and other variants (e.g., in CYP3A4/5, UGT enzymes or SLC transporters) on atorvastatin pharmacokinetics. For this purpose, a candidate-gene pharmacogenetic study was proposed. The study population comprised 156 healthy volunteers enrolled in atorvastatin bioequivalence clinical trials. The genotyping strategy comprised a total of 60 variants in 15 genes. Women showed higher exposure to atorvastatin compared to men (p = 0.001), however this difference disappeared after dose/weight (DW) correction. The most relevant pharmacogenetic differences were the following: AUC/DW and C_max /DW based on (a) SLCO1B1 phenotype (p < 0.001 for both) and (b) CYP3A5*3 (p = 0.004 and 0.018, respectively). As secondary findings: SLC22A1 *2/*2 genotype was related to higher C_max/DW (ANOVA p = 0.030) and SLC22A1 *1/*5 genotype was associated with higher Vd/F (ANOVA p = 0.032) compared to SLC22A1 *1/*1, respectively. Finally, UGT2B7 rs7439366 *1/*1 genotype was associated with higher t_max as compared with the *1/*3 genotype (ANOVA p = 0.024). Based on our results, we suggest that SLCO1B1 is the best predictor for atorvastatin pharmacokinetic variability and that prescription should be adjusted based on it. We suggest that the CPIC should include atorvastatin in their statin-SLCO1B1 guidelines. Interesting and novel results were observed based on CYP3A5 genotype, which should be confirmed with further studies.

Atorvastatin, prescribed for the treatment of hypercholesterolemia, demonstrated overwhelming benefits in reducing cardiovascular morbidity and mortality. However, many patients discontinue therapy due to adverse reactions, especially myopathy. The Dutch Pharmacogenetics Working Group (DPWG) recommends an alternative agent to atorvastatin and simvastatin or a dose adjustment depending on other risk factors for statin-induced myopathy in SLCO1B1 rs4149056 CC or TC carriers. In contrast, the Clinical Pharmacogenetics Implementation Consortium (CPIC) published their guideline on simvastatin, but not on atorvastatin. In this work, we aimed to demonstrate the effect of SLCO1B1 phenotype and other variants (e.g., in CYP3A4/5, UGT enzymes or SLC transporters) on atorvastatin pharmacokinetics. For this purpose, a candidate-gene pharmacogenetic study was proposed. The study population comprised 156 healthy volunteers enrolled in atorvastatin bioequivalence clinical trials. The genotyping strategy comprised a total of 60 variants in 15 genes. Women showed higher exposure to atorvastatin compared to men (p = 0.001), however this difference disappeared after dose/weight (DW) correction. The most relevant pharmacogenetic differences were the following: AUC/DW and C_max /DW based on (a) SLCO1B1 phenotype (p < 0.001 for both) and (b) CYP3A5*3 (p = 0.004 and 0.018, respectively). As secondary findings: SLC22A1 *2/*2 genotype was related to higher C_max/DW (ANOVA p = 0.030) and SLC22A1 *1/*5 genotype was associated with higher Vd/F (ANOVA p = 0.032) compared to SLC22A1 *1/*1, respectively. Finally, UGT2B7 rs7439366 *1/*1 genotype was associated with higher t_max as compared with the *1/*3 genotype (ANOVA p = 0.024). Based on our results, we suggest that SLCO1B1 is the best predictor for atorvastatin pharmacokinetic variability and that prescription should be adjusted based on it. We suggest that the CPIC should include atorvastatin in their statin-SLCO1B1 guidelines. Interesting and novel results were observed based on CYP3A5 genotype, which should be confirmed with further studies.