The Polymorphic Nuclear Factor NFIB Regulates Hepatic CYP2D6 Expression and Influences Risperidone Metabolism in Psychiatric Patients

Phenoconversion Due to Drug-Drug Interactions in CYP2C19 Genotyped Healthy Volunteers

To compensate for drug response variability, drug metabolism phenotypes are determined based on the results of genetic testing, and if necessary, drug dosages are adjusted. In some cases, discrepancies between predicted and observed phenotypes (phenoconversion) may occur due to drug-drug interactions caused by concomitant medications. We conducted a prospective, exploratory study to evaluate the risk of CYP2C19 phenoconversion in genotyped healthy volunteers exposed to CYP2C19 inhibitors. Three groups of volunteers were enrolled: CYP2C19 g-RM, g-NM, and g-IM (g- for genetically predicted). All volunteers received as CYP2C19 phenotyping substrate 10 mg omeprazole (OME) alone at the control session and in co-administration with CYP2C19 inhibitors: voriconazole 400 mg and fluvoxamine 50 mg in second and third study sessions, respectively. Phenoconversion occurred in over 80% of healthy volunteers, with variations among genotypic groups, revealing distinct proportions in response to fluvoxamine and voriconazole. Statistically significant differences were observed in mean metabolic ratios between CYP2C19 intermediate metabolizers (g-IMs) with *1/*2 and *2/*17 genotypes, with the *2/*17 group exhibiting lower ratios, and distinctions were noted between genotypic groups, emphasizing the impact of genetic variations on drug metabolism. When reclassified according to CYP2C19 baseline-measured phenotype into p-RM, p-NM, and p-IM (p- for measured phenotype), we observed 100% phenoconversion of p-RMs and a significant phenotype switch in p-NMs, p-IMs, and p-PMs after fluvoxamine and voriconazole, and complete phenoconversion of p-IMs to p-PMs on both inhibitors, emphasizing the impact of genetic variations on the vulnerability to CYP2C19 phenoconversion and the importance of considering both genotyping and phenotyping in predicting drug response.

Impact of CYP2D6*2, CYP2D6*35, rs5758550, and related haplotypes on risperidone clearance in vivo

PURPOSE

The CYP2D6 gene exhibits significant polymorphism, contributing to variability in responses to drugs metabolized by CYP2D6. While CYP2D6*2 and CYP2D6*35 are presently designated as alleles encoding normal metabolism, this classification is based on moderate level evidence. Additionally, the role of the formerly called "enhancer" single nucleotide polymorphism (SNP) rs5758550 is unclear. In this study, the impacts of CYP2D6*2, CYP2D6*35 and rs5758550 on CYP2D6 activity were investigated using risperidone clearance as CYP2D6 activity marker.

METHODS

A joint parent-metabolite population pharmacokinetic model was used to describe 1,565 serum concentration measurements of risperidone and 9-hydroxyrisperidone in 512 subjects. Risperidone population clearance was modeled as the sum of a CYP2D6-independent clearance term and the partial clearances contributed from each individually expressed CYP2D6 allele or haplotype. In addition to the well-characterized CYP2D6 alleles (*3-*6, *9, *10 and *41), *2, *35 and two haplotypes assigned as CYP2D6*2-rs5758550G and CYP2D6*2-rs5758550A were evaluated.

RESULTS

Each evaluated CYP2D6 allele was associated with significantly lower risperidone clearance than the reference normal function allele CYP2D6*1 (p < 0.001). Further, rs5758550 differentiated the effect of CYP2D6*2 (p = 0.005). The haplotype-specific clearances for CYP2D6*2-rs5758550A, CYP2D6*2-rs5758550G and CYP2D6*35 were estimated to 30%, 66% and 57%, respectively, relative to the clearance for CYP2D6*1. Notably, rs5758550 is in high linkage disequilibrium (R2 > 0.85) with at least 24 other SNPs and cannot be assigned as a functional SNP.

CONCLUSION

CYP2D6*2 and CYP2D6*35 encode reduced risperidone clearance, and the extent of reduction for CYP2D6*2 is differentiated by rs5758550. Genotyping of these haplotypes might improve the precision of genotype-guided prediction of CYP2D6-mediated clearance.

Phenotype-Genotype Correlation Applying a Cocktail Approach and an Exome Chip Analysis Reveals Further Variants Contributing to Variation of Drug Metabolism

Although great progress has been made in the fine-tuning of diplotypes, there is still a need to further improve the predictability of individual phenotypes of pharmacogenetically relevant enzymes. The aim of this study was to analyze the additional contribution of sex and variants identified by exome chip analysis to the metabolic ratio of five probe drugs. A cocktail study applying dextromethorphan, losartan, omeprazole, midazolam, and caffeine was conducted on 200 healthy volunteers. CYP2D6, 2C9, 2C19, 3A4/5, and 1A2 genotypes were analyzed and correlated with metabolic ratios. In addition, an exome chip analysis was performed. These SNPs correlating with metabolic ratios were confirmed by individual genotyping. The contribution of various factors to metabolic ratios was assessed by multiple regression analysis. Genotypically predicted phenotypes defined by CPIC discriminated very well the log metabolic ratios with the exception of caffeine. There were minor sex differences in the activity of CYP2C9, 2C19, 1A2, and CYP3A4/5. For dextromethorphan (CYP2D6), IP6K2 (rs61740999) and TCF20 (rs5758651) affected metabolic ratios, but only IP6K2 remained significant after multiple regression analysis. For losartan (CYP2C9), FBXW12 (rs17080138), ZNF703 (rs79707182), and SLC17A4 (rs11754288) together with CYP diplotypes, and sex explained 50% of interindividual variability. For omeprazole (CYP2C19), no significant influence of CYP2C:TG haplotypes was observed, but CYP2C19 rs12777823 improved the predictability. The comprehensive genetic analysis and inclusion of sex in a multiple regression model significantly improved the explanation of variability of metabolic ratios, resulting in further improvement of algorithms for the prediction of individual phenotypes of drug-metabolizing enzymes.

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.

Rapid Metabolism Underlying Subtherapeutic Serum Levels of Atypical Antipsychotics Preceding Clozapine Treatment: A Retrospective Analysis of Real-World Data

INTRODUCTION

Adequate antipsychotic treatment intensity is required before diagnosing resistant schizophrenia and initiating clozapine treatment. We aimed to investigate potential rapid drug metabolism underlying low dose-adjusted serum concentration (CD) of non-clozapine atypical antipsychotics preceding clozapine treatment.

METHODS

Patients using non-clozapine, atypical antipsychotics (aripiprazole, risperidone, olanzapine, or quetiapine) within 1 year before starting clozapine were included in this study from a therapeutic drug monitoring service in Oslo, Norway, between 2005 and 2023. Patients were assigned into low CD (LCD) and normal CD (NCD) subgroups. Using a reference sample with 147,964 antipsychotic measurements, LCD was defined as CDs below the 25th percentile, while patients with NCD exhibited CDs between the 25th and 75th percentile of the respective reference measurements. Metabolic ratios, doses, and frequency of subtherapeutic levels of non-clozapine antipsychotics were compared between LCD and NCD groups.

RESULTS

Preceding clozapine treatment, 110 out of 272 included patients (40.4%) were identified with LCD. Compared with the NCD group, LCD patients exhibited higher metabolic ratios of olanzapine (1.5-fold; p < 0.001), quetiapine (3.0-fold; p < 0.001), and risperidone (6.0-fold; p < 0.001). Metabolic ratio differences were independent of smoking and CYP2D6 genotype for olanzapine (p = 0.008) and risperidone (p = 0.016), respectively. Despite higher doses of olanzapine (1.25-fold; p = 0.054) and quetiapine (1.6-fold; p = 0.001) in LCD versus NCD patients, faster metabolism among the former was accompanied by higher frequencies of subtherapeutic levels of olanzapine (3.3-fold; p = 0.044) and quetiapine (1.8-fold; p = 0.005).

CONCLUSION

LCD and associated rapid metabolism of non-clozapine antipsychotics is frequent before starting clozapine treatment. For olanzapine and quetiapine, this is associated with significantly increased risk of having subtherapeutic concentrations.

Solanidine is a sensitive and specific dietary biomarker for CYP2D6 activity

BACKGROUND

Individual assessment of CYP enzyme activities can be challenging. Recently, the potato alkaloid solanidine was suggested as a biomarker for CYP2D6 activity. Here, we aimed to characterize the sensitivity and specificity of solanidine as a CYP2D6 biomarker among Finnish volunteers with known CYP2D6 genotypes.

RESULTS

Using non-targeted metabolomics analysis, we identified 9152 metabolite features in the fasting plasma samples of 356 healthy volunteers. Machine learning models suggested strong association between CYP2D6 genotype-based phenotype classes with a metabolite feature identified as solanidine. Plasma solanidine concentration was 1887% higher in genetically poor CYP2D6 metabolizers (gPM) (n = 9; 95% confidence interval 755%, 4515%; P = 1.88 × 10-11), 74% higher in intermediate CYP2D6 metabolizers (gIM) (n = 89; 27%, 138%; P = 6.40 × 10-4), and 35% lower in ultrarapid CYP2D6 metabolizers (gUM) (n = 20; 64%, - 17%; P = 0.151) than in genetically normal CYP2D6 metabolizers (gNM; n = 196). The solanidine metabolites m/z 444 and 430 to solanidine concentration ratios showed even stronger associations with CYP2D6 phenotypes. Furthermore, the areas under the receiver operating characteristic and precision-recall curves for these metabolic ratios showed equal or better performances for identifying the gPM, gIM, and gUM phenotype groups than the other metabolites, their ratios to solanidine, or solanidine alone. In vitro studies with human recombinant CYP enzymes showed that solanidine was metabolized mainly by CYP2D6, with a minor contribution from CYP3A4/5. In human liver microsomes, the CYP2D6 inhibitor paroxetine nearly completely (95%) inhibited the metabolism of solanidine. In a genome-wide association study, several variants near the CYP2D6 gene associated with plasma solanidine metabolite ratios.

CONCLUSIONS

These results are in line with earlier studies and further indicate that solanidine and its metabolites are sensitive and specific biomarkers for measuring CYP2D6 activity. Since potato consumption is common worldwide, this biomarker could be useful for evaluating CYP2D6-mediated drug-drug interactions and to improve prediction of CYP2D6 activity in addition to genotyping.

Effect of the NFIB rs28379954 T>C polymorphism on CYP2D6-catalyzed metabolism of solanidine

Cytochrome P450 2D6 (CYP2D6) is important for metabolism of 20%-25% of all clinically used drugs. Many known genetic variants contribute to the large interindividual variability in CYP2D6 metabolism, but much is still unexplained. We recently described that nuclear factor 1B (NFIB) regulates hepatic CYP2D6 expression with the minor allele of NFIB rs28379954 T>C significantly increasing CYP2D6-mediated risperidone metabolism. In this study, we investigated the effect of NFIB T>C on metabolism of solanidine, a dietary CYP2D6 substrate. Analyses of solanidine and metabolites (M414, M416, and M444) were performed by ultra-high performance liquid chromatography-high-resolution mass spectrometry in a cohort of 463 CYP2D6-genotyped patients of which with 58 (12.5%) carried NFIB TC (n = 56) or CC (n = 2). Increased metabolism of solanidine was found in CYP2D6 normal metabolizers (NMs; n = 258, 55.7%) carrying the NFIB C variant (n = 27, 5.8%) with 2.83- and 3.38-fold higher M416-to-solanidine (p = 0.039) and M444-to-solanidine (p = 0.046) ratios, respectively, whereas this effect was not significant among intermediate metabolizers (n = 166, 35.9%) (p ≥ 0.09). Importantly, no effect of the NFIB polymorphism on solanidine metabolism was seen in TC or CC carriers lacking CYP2D6 activity (poor metabolizers, n = 30, 6.5%, p ≥ 0.74). Furthermore, the NFIB polymorphism significantly explained variability in solanidine metabolism (M414 p = 0.013, M416 p = 0.020, and M416 and M444 p = 0.009) in multiple linear regression models for each metabolic ratio in the entire population, correcting for covariates (including CYP2D6 genotypes). Thus, the study confirms the effect of NFIB in regulating CYP2D6 activity, suggesting an about 200% increase in CYP2D6-mediated clearance in NMs being NFIB CT or CC carriers, comprising around 6% of Europeans.

Pharmacogenomics Beyond Single Common Genetic Variants: The Way Forward

Interindividual variability in genes encoding drug-metabolizing enzymes, transporters, receptors, and human leukocyte antigens has a major impact on a patient's response to drugs with regard to efficacy and safety. Enabled by both technological and conceptual advances, the field of pharmacogenomics is developing rapidly. Major progress in omics profiling methods has enabled novel genotypic and phenotypic characterization of patients and biobanks. These developments are paralleled by advances in machine learning, which have allowed us to parse the immense wealth of data and establish novel genetic markers and polygenic models for drug selection and dosing. Pharmacogenomics has recently become more widespread in clinical practice to personalize treatment and to develop new drugs tailored to specific patient populations. In this review, we provide an overview of the latest developments in the field and discuss the way forward, including how to address the missing heritability, develop novel polygenic models, and further improve the clinical implementation of pharmacogenomics.

PharmVar Tutorial on CYP2D6 Structural Variation Testing and Recommendations on Reporting

The Pharmacogene Variation Consortium (PharmVar) provides nomenclature for the highly polymorphic human CYP2D6 gene locus and a comprehensive summary of structural variation. CYP2D6 contributes to the metabolism of numerous drugs and, thus, genetic variation in its gene impacts drug efficacy and safety. To accurately predict a patient's CYP2D6 phenotype, testing must include structural variants including gene deletions, duplications, hybrid genes, and combinations thereof. This tutorial offers a comprehensive overview of CYP2D6 structural variation, terms, and definitions, a review of methods suitable for their detection and characterization, and practical examples to address the lack of standards to describe CYP2D6 structural variants or any other pharmacogene. This PharmVar tutorial offers practical guidance on how to detect the many, often complex, structural variants, as well as recommends terms and definitions for clinical and research reporting. Uniform reporting is not only essential for electronic health record-keeping but also for accurate translation of a patient's genotype into phenotype which is typically utilized to guide drug therapy.

Cross-Ancestry Genome-Wide Association Study Defines the Extended CYP2D6 Locus as the Principal Genetic Determinant of Endoxifen Plasma Concentrations

The therapeutic efficacy of tamoxifen is predominantly mediated by its active metabolites 4-hydroxy-tamoxifen and endoxifen, whose formation is catalyzed by the polymorphic cytochrome P450 2D6 (CYP2D6). Yet, known CYP2D6 polymorphisms only partially determine metabolite concentrations in vivo. We performed the first cross-ancestry genome-wide association study with well-characterized patients of European, Middle-Eastern, and Asian descent (n = 497) to identify genetic factors impacting active and parent metabolite formation. Genome-wide significant variants were functionally evaluated in an independent liver cohort (n = 149) and in silico. Metabolite prediction models were validated in two independent European breast cancer cohorts (n = 287, n = 189). Within a single 1-megabase (Mb) region of chromosome 22q13 encompassing the CYP2D6 gene, 589 variants were significantly associated with tamoxifen metabolite concentrations, particularly endoxifen and metabolic ratio (MR) endoxifen/N-desmethyltamoxifen (minimal P = 5.4E-35 and 2.5E-65, respectively). Previously suggested other loci were not confirmed. Functional analyses revealed 66% of associated, mostly intergenic variants to be significantly correlated with hepatic CYP2D6 activity or expression (ρ = 0.35 to -0.52), and six hotspot regions in the extended 22q13 locus impacting gene regulatory function. Machine learning models based on hotspot variants (n = 12) plus CYP2D6 activity score (AS) increased the explained variability (~ 9%) compared with AS alone, explaining up to 49% (median R² ) and 72% of the variability in endoxifen and MR endoxifen/N-desmethyltamoxifen, respectively. Our findings suggest that the extended CYP2D6 locus at 22q13 is the principal genetic determinant of endoxifen plasma concentration. Long-distance haplotypes connecting CYP2D6 with adjacent regulatory sites and nongenetic factors may account for the unexplained portion of variability.

Pharmacogenomics in treatment of depression and psychosis: an update

Genetic factors can, to a certain extent, successfully predict the therapeutic effects, metabolism, and adverse reactions of drugs. This research field, pharmacogenomics, is well developed in oncology and is currently expanding in psychiatry. Here, we summarize the latest development in pharmacogenomic psychiatry, where results of several recent large studies indicate a true benefit and cost-effectiveness of pre-emptive genotyping for more successful psychotherapy. However, it is apparent that we still lack knowledge of many additional heritable genetic factors of importance for explanation of the interindividual differences in response to psychiatric drugs. Thus, more effort to further develop pharmacogenomic psychiatry should be invested to achieve a broader clinical implementation.

Drug metabolism and drug transport of the 100 most prescribed oral drugs

Safe and effective use of drugs requires an understanding of metabolism and transport. We identified the 100 most prescribed drugs in six countries and conducted a literature search on in vitro data to assess contribution of Phase I and II enzymes and drug transporters to metabolism and transport. Eighty-nine of the 100 drugs undergo drug metabolism or are known substrates for drug transporters. Phase I enzymes are involved in metabolism of 67 drugs, while Phase II enzymes mediate metabolism of 18 drugs. CYP3A4/5 is the most important Phase I enzyme involved in metabolism of 43 drugs followed by CYP2D6 (23 drugs), CYP2C9 (23 drugs), CYP2C19 (22 drugs), CYP1A2 (14 drugs) and CYP2C8 (11 drugs). More than half of the drugs (54 drugs) are known substrates for drug transporters. P-glycoprotein (P-gp) is known to be involved in transport of 30 drugs, while breast cancer resistance protein (BCRP) facilitates transport of 11 drugs. A considerable proportion of drugs are subject to a combination of Phase I metabolism, Phase II metabolism and/or drug transport. We conclude that the majority of the most frequently prescribed drugs depend on drug metabolism or drug transport. Thus, understanding variability of drug metabolism and transport remains a priority.

Impact of NFIB and CYP1A variants on clozapine serum concentration-A retrospective naturalistic cohort study on 526 patients with known smoking habits

Clinical response of clozapine is closely associated with serum concentration. Although tobacco smoking is the key environmental factor underlying interindividual variability in clozapine metabolism, recent genome-wide studies suggest that CYP1A and NFIB genetic variants may also be of significant importance, but their quantitative impact is unclear. We investigated the effects of the rs2472297 C>T (CYP1A) and rs28379954 T>C (NFIB) polymorphisms on serum concentrations in smokers and nonsmokers. The study retrospectively included 526 patients with known smoking habits (63.7% smokers) from a therapeutic drug monitoring service in Norway. Clozapine dose-adjusted concentrations (C/D) and patient proportions with subtherapeutic levels (<1070 nmol/L) were compared between CYP1A/NFIB variant allele carriers and homozygous wild-type carriers (noncarriers), in both smokers and nonsmokers. Clozapine C/D was reduced in patients carrying CYP1A-T and NFIB-C variants versus noncarriers, both among smokers (-48%; p < 0.0001) and nonsmokers (-35%; p = 0.028). Patients who smoke carrying CYP1A-T and NFIB-C variants had a 66% reduction in clozapine C/D versus nonsmoking noncarriers (p < 0.0001). The patient proportion with subtherapeutic levels was 2.9-fold higher in patients who smoke carrying NFIB-C and CYP1A-T variants versus nonsmoking noncarriers (p < 0.0001). In conclusion, CYP1A and NFIB variants have significant and additive impact on clozapine dose requirements for reaching target serum concentrations. Patients who smoke carrying the studied CYP1A and NFIB variants, comprising 2.5% of the study population, may need threefold higher doses to prevent risk of clozapine undertreatment. The results suggest that pre-emptive genotyping of NFIB and CYP1A may be utilized to guide clozapine dosing and improve clinical outcomes in patients with treatment-resistant schizophrenia.

Challenges and opportunities associated with rare-variant pharmacogenomics

Recent advances in next-generation sequencing (NGS) have resulted in the identification of tens of thousands of rare pharmacogenetic variations with unknown functional effects. However, although such pharmacogenetic variations have been estimated to account for a considerable amount of the heritable variability in drug response and toxicity, accurate interpretation at the level of the individual patient remains challenging. We discuss emerging strategies and concepts to close this translational gap. We illustrate how massively parallel experimental assays, artificial intelligence (AI), and machine learning can synergize with population-scale biobank projects to facilitate the interpretation of NGS data to individualize clinical decision-making and personalized medicine.

Pharmacogenetics of the cytochromes P450: Selected pharmacological and toxicological aspects

With the availability of detailed genomic data on all 57 human cytochrome P450 genes, it is clear that there is substantial variability in gene product activity with functionally significant polymorphisms reported across almost all isoforms. This article is concerned mainly with 13 P450 isoforms of particular relevance to xenobiotic metabolism. After brief review of the extent of polymorphism in each, the relevance of selected P450 isoforms to both adverse drug reaction and disease susceptibility is considered in detail. Bleeding due to warfarin and other coumarin anticoagulants is considered as an example of a type A reaction with idiosyncratic adverse drug reactions affecting the liver and skin as type B. It is clear that CYP2C9 variants contribute significantly to warfarin dose requirement and also risk of bleeding, with a minor contribution from CYP4F2. In the case of idiosyncratic adverse drug reactions, CYP2B6 variants appear relevant to both liver and skin reactions to several drugs with CYP2C9 variants also relevant to phenytoin-related skin rash. The relevance of P450 genotype to disease susceptibility is also considered but detailed genetic studies now suggest that CYP2A6 is the only P450 relevant to risk of lung cancer with alleles associated with low or absent activity clearly protective against disease. Other cytochrome P450 genotypes are generally not predictors for risk of cancer or other complex disease development.

Cytochrome P450 polymorphism: From evolution to clinical use

The cytochromes P450s can be divided in two groups, those of high importance for endogenous functions being evolutionary quite stable and those participating in detoxification of drugs and other xenobiotics having less important endogenous functions. In the latter group extensive genetic diversity has been allowed and in addition this is of high importance for survival in different environments. The genetic polymorphisms in these genes have evolved to some extent based on dietary restrictions and environmental factors and have not been subject of conservation due to less importance for survival. In cases of high dietary selection events, gene multiplication and amplification events have been seen. The different variants in genes encoding drug metabolizing enzymes can be used as genetic biomarkers (pharmacogenomic labels) for adjustment of drug treatment leading to less adverse drug reactions and better response. Indeed, this has improved the use of personalized medicine, although the missing heredity seen based on twin studies indicates that there are indeed many more genetic variants to be discovered before one can achieve a satisfactory relationship between genotype and phenotype with respect to drug metabolism and toxicity.