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.

A 12-gene pharmacogenetic panel to prevent adverse drug reactions: an open-label, multicentre, controlled, cluster-randomised crossover implementation study.

BACKGROUND: The benefit of pharmacogenetic testing before starting drug therapy has been well documented for several single gene-drug combinations. However, the clinical utility of a pre-emptive genotyping strategy using a pharmacogenetic panel has not been rigorously assessed. METHODS: We conducted an open-label, multicentre, controlled, cluster-randomised, crossover implementation study of a 12-gene pharmacogenetic panel in 18 hospitals, nine community health centres, and 28 community pharmacies in seven European countries (Austria, Greece, Italy, the Netherlands, Slovenia, Spain, and the UK). Patients aged 18 years or older receiving a first prescription for a drug clinically recommended in the guidelines of the Dutch Pharmacogenetics Working Group (ie, the index drug) as part of routine care were eligible for inclusion. Exclusion criteria included previous genetic testing for a gene relevant to the index drug, a planned duration of treatment of less than 7 consecutive days, and severe renal or liver insufficiency. All patients gave written informed consent before taking part in the study. Participants were genotyped for 50 germline variants in 12 genes, and those with an actionable variant (ie, a drug-gene interaction test result for which the Dutch Pharmacogenetics Working Group [DPWG] recommended a change to standard-of-care drug treatment) were treated according to DPWG recommendations. Patients in the control group received standard treatment. To prepare clinicians for pre-emptive pharmacogenetic testing, local teams were educated during a site-initiation visit and online educational material was made available. The primary outcome was the occurrence of clinically relevant adverse drug reactions within the 12-week follow-up period. Analyses were irrespective of patient adherence to the DPWG guidelines. The primary analysis was done using a gatekeeping analysis, in which outcomes in people with an actionable drug-gene interaction in the study group versus the control group were compared, and only if the difference was statistically significant was an analysis done that included all of the patients in the study. Outcomes were compared between the study and control groups, both for patients with an actionable drug-gene interaction test result (ie, a result for which the DPWG recommended a change to standard-of-care drug treatment) and for all patients who received at least one dose of index drug. The safety analysis included all participants who received at least one dose of a study drug. This study is registered with ClinicalTrials.gov, NCT03093818 and is closed to new participants. FINDINGS: Between March 7, 2017, and June 30, 2020, 41 696 patients were assessed for eligibility and 6944 (51·4 % female, 48·6% male; 97·7% self-reported European, Mediterranean, or Middle Eastern ethnicity) were enrolled and assigned to receive genotype-guided drug treatment (n=3342) or standard care (n=3602). 99 patients (52 [1·6%] of the study group and 47 [1·3%] of the control group) withdrew consent after group assignment. 652 participants (367 [11·0%] in the study group and 285 [7·9%] in the control group) were lost to follow-up. In patients with an actionable test result for the index drug (n=1558), a clinically relevant adverse drug reaction occurred in 152 (21·0%) of 725 patients in the study group and 231 (27·7%) of 833 patients in the control group (odds ratio [OR] 0·70 [95% CI 0·54-0·91]; p=0·0075), whereas for all patients, the incidence was 628 (21·5%) of 2923 patients in the study group and 934 (28·6%) of 3270 patients in the control group (OR 0·70 [95% CI 0·61-0·79]; p <0·0001). INTERPRETATION: Genotype-guided treatment using a 12-gene pharmacogenetic panel significantly reduced the incidence of clinically relevant adverse drug reactions and was feasible across diverse European health-care system organisations and settings. Large-scale implementation could help to make drug therapy increasingly safe. FUNDING: European Union Horizon 2020.

Precision medicine in cardiovascular therapeutics: Evaluating the role of pharmacogenetic analysis prior to drug treatment.

Pharmacogenomics is the examination of how genetic variation influences drug metabolism and response, in terms of both efficacy and safety. In cardiovascular disease, patient-specific diplotypes determine phenotypes, thereby influencing the efficacy and safety of drug treatments, including statins, antiarrhythmics, anticoagulants and antiplatelets. Notably, polymorphisms in key genes, such as CYP2C9, CYP2C19, VKORC1 and SLCO1B1, significantly impact the outcomes of treatment with clopidogrel, warfarin and simvastatin. Furthermore, the CYP2C19 polymorphism influences the pharmacokinetics and safety of the novel hypertrophic cardiomyopathy inhibitor, mavacamten. In this review, we critically assess the clinical application of pharmacogenomics in cardiovascular disease and delineate present and future utilization of pharmacogenomics. This includes insights into identifying missing heritability, the integration of whole genome sequencing and the application of polygenic risk scores to enhance the precision of personalized drug therapy. Our discussion encompasses health economic analyses that underscore the cost benefits associated with pre-emptive genotyping for warfarin and clopidogrel treatments, albeit acknowledging the need for further research in this area. In summary, we contend that cardiovascular pharmacogenomic analyses are underpinned by a wealth of evidence, and implementation is already occurring for some of these gene-drug pairs, but as with any area of medicine, we need to continually gather more information to optimize the use of pharmacogenomics in clinical practice.

Individualized Pharmacotherapy Utilizing Genetic Biomarkers and Novel In Vitro Systems As Predictive Tools for Optimal Drug Development and Treatment.

In the area of drug development and clinical pharmacotherapy, a profound understanding of the pharmacokinetics and potential adverse reactions associated with the drug under investigation is paramount. Essential to this endeavor is a comprehensive understanding about interindividual variations in absorption, distribution, metabolism, and excretion (ADME) genetics and the predictive capabilities of in vitro systems, shedding light on metabolite formation and the risk of adverse drug reactions (ADRs). Both the domains of pharmacogenomics and the advancement of in vitro systems are experiencing rapid expansion. Here we present an update on these burgeoning fields, providing an overview of their current status and illuminating potential future directions. SIGNIFICANCE STATEMENT: There is very rapid development in the area of pharmacogenomics and in vitro systems for predicting drug pharmacokinetics and risk for adverse drug reactions. We provide an update of the current status of pharmacogenomics and developed in vitro systems on these aspects aimed to achieve a better personalized pharmacotherapy.

Therapeutic drug monitoring, liquid biopsies or pharmacogenomics for prediction of human drug metabolism and response.

Pharmacokinetics plays a central role in understanding the significant interindividual differences that exist in drug metabolism and response. Effectively addressing these differences requires a multi-faceted approach that encompasses a variety of tools and methods. In this review, we examine three key strategies to achieve this goal, namely pharmacogenomics, therapeutic drug monitoring (TDM) and liquid biopsy-based monitoring of hepatic ADME gene expression and highlight their advantages and limitations. We note that larger cohort studies are needed to validate the utility of liquid biopsy-based assessment of hepatic ADME gene expression, which includes prediction of drug metabolism in the clinical setting. Modern mass spectrometers have improved traditional TDM methods, offering versatility and sensitivity. In addition, the identification of endogenous or dietary markers for CYP metabolic traits offers simpler and more cost-effective alternatives to determine the phenotype. We believe that future pharmacogenomic applications in clinical practice should prioritize the identification of missing heritable factors, using larger, well-characterized patient studies and controlling for confounding factors such as diet, concomitant medication and physical health. The intricate regulation of ADME gene expression implies that large-scale studies combining long-read next-generation sequencing (NGS) of complete genomes with phenotyping of patients taking different medications are essential to identify these missing heritabilities. The continuous integration of such data into AI-driven analytical systems could provide a comprehensive and useful framework. This could lead to the development of highly effective algorithms to improve genetics-based precision treatment by predicting drug metabolism and response, significantly improving clinical outcomes.

Evidence for solanidine as a dietary CYP2D6 biomarker: Significant correlation with risperidone metabolism.

AIMS: The extensive variability in cytochrome P450 2D6 (CYP2D6) metabolism is mainly caused by genetic polymorphisms. However, there is large, unexplained variability in CYP2D6 metabolism within CYP2D6 genotype subgroups. Solanidine, a dietary compound found in potatoes, is a promising phenotype biomarker predicting individual CYP2D6 metabolism. The aim of this study was to investigate the correlation between solanidine metabolism and the CYP2D6-mediated metabolism of risperidone in patients with known CYP2D6 genotypes. METHODS: The study included therapeutic drug monitoring (TDM) data from CYP2D6-genotyped patients treated with risperidone. Risperidone and 9-hydroxyrisperidone levels were determined during TDM, and reprocessing of the respective TDM full-scan high-resolution mass spectrometry files was applied for semi-quantitative measurements of solanidine and five metabolites (M402, M414, M416, M440 and M444). Spearman's tests determined the correlations between solanidine metabolic ratios (MRs) and the 9-hydroxyrisperidone-to-risperidone ratio. RESULTS: A total of 229 patients were included. Highly significant, positive correlationswere observed between all solanidine MRs and the 9-hydroxyrisperidone-to-risperidone ratio (ρ > 0.6, P < .0001). The strongest correlation was observed for the M444-to-solanidine MR in patients with functional CYP2D6 metabolism, i.e., genotype activity scores of 1 and 1.5 (ρ 0.72-0.77, P < .0001). CONCLUSION: The present study shows strong, positive correlations between solanidine metabolism and CYP2D6-mediated risperidone metabolism. The strong correlation within patients carrying CYP2D6 genotypes encoding functional CYP2D6 metabolism suggests that solanidine metabolism may predict individual CYP2D6 metabolism, and hence potentially improve personalized dosing of drugs metabolized by CYP2D6.

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.

The humanised CYP2C19 transgenic mouse exhibits cerebellar atrophy and movement impairment reminiscent of ataxia.

AIMS: CYP2C19 transgenic mouse expresses the human CYP2C19 gene in the liver and developing brain, and it exhibits altered neurodevelopment associated with impairments in emotionality and locomotion. Because the validation of new animal models is essential for the understanding of the aetiology and pathophysiology of movement disorders, the objective was to characterise motoric phenotype in CYP2C19 transgenic mice and to investigate its validity as a new animal model of ataxia. METHODS: The rotarod, paw-print and beam-walking tests were utilised to characterise the motoric phenotype. The volumes of 20 brain regions in CYP2C19 transgenic and wild-type mice were quantified by 9.4T gadolinium-enhanced post-mortem structural neuroimaging. Antioxidative enzymatic activity was quantified biochemically. Dopaminergic alterations were characterised by chromatographic quantification of concentrations of dopamine and its metabolites and by subsequent immunohistochemical analyses. The beam-walking test was repeated after the treatment with dopamine receptor antagonists ecopipam and raclopride. RESULTS: CYP2C19 transgenic mice exhibit abnormal, unilateral ataxia-like gait, clasping reflex and 5.6-fold more paw-slips in the beam-walking test; the motoric phenotype was more pronounced in youth. Transgenic mice exhibited a profound reduction of 12% in cerebellar volume and a moderate reduction of 4% in hippocampal volume; both regions exhibited an increased antioxidative enzyme activity. CYP2C19 mice were hyperdopaminergic; however, the motoric impairment was not ameliorated by dopamine receptor antagonists, and there was no alteration in the number of midbrain dopaminergic neurons in CYP2C19 mice. CONCLUSIONS: Humanised CYP2C19 transgenic mice exhibit altered gait and functional motoric impairments; this phenotype is likely caused by an aberrant cerebellar development.

The clinically relevant CYP2C8*3 and CYP2C9*2 haplotype is inherited from Neandertals.

Genetic variation in genes encoding cytochrome P450 enzymes influences the metabolism of drugs and endogenous compounds. The locus containing the cytochrome genes CYP2C8 and CYP2C9 on chromosome 10 exhibits linkage disequilibrium between the CYP2C8*3 and CYP2C9*2 alleles, forming a haplotype of ~300 kilobases. This haplotype is associated with altered metabolism of several drugs, most notably reduced metabolism of warfarin and phenytoin, leading to toxicity at otherwise therapeutic doses. Here we show that this haplotype is inherited from Neandertals.

AMP-activated protein kinase activation and NADPH oxidase inhibition by inorganic nitrate and nitrite prevent liver steatosis.

Advanced age and unhealthy dietary habits contribute to the increasing incidence of obesity and type 2 diabetes. These metabolic disorders, which are often accompanied by oxidative stress and compromised nitric oxide (NO) signaling, increase the risk of adverse cardiovascular complications and development of fatty liver disease. Here, we investigated the therapeutic effects of dietary nitrate, which is found in high levels in green leafy vegetables, on liver steatosis associated with metabolic syndrome. Dietary nitrate fuels a nitrate-nitrite-NO signaling pathway, which prevented many features of metabolic syndrome and liver steatosis that developed in mice fed a high-fat diet, with or without combination with an inhibitor of NOS (l-NAME). These favorable effects of nitrate were absent in germ-free mice, demonstrating the central importance of host microbiota in bioactivation of nitrate. In a human liver cell line (HepG2) and in a validated hepatic 3D model with primary human hepatocyte spheroids, nitrite treatment reduced the degree of metabolically induced steatosis (i.e., high glucose, insulin, and free fatty acids), as well as drug-induced steatosis (i.e., amiodarone). Mechanistically, the salutary metabolic effects of nitrate and nitrite can be ascribed to nitrite-derived formation of NO species and activation of soluble guanylyl cyclase, where xanthine oxidoreductase is proposed to mediate the reduction of nitrite. Boosting this nitrate-nitrite-NO pathway results in attenuation of NADPH oxidase-derived oxidative stress and stimulation of AMP-activated protein kinase and downstream signaling pathways regulating lipogenesis, fatty acid oxidation, and glucose homeostasis. These findings may have implications for novel nutrition-based preventive and therapeutic strategies against liver steatosis associated with metabolic dysfunction.

Pharmacoepigenetics and Toxicoepigenetics: Novel Mechanistic Insights and Therapeutic Opportunities.

Pharmacological treatment and exposure to xenobiotics can cause substantial changes in epigenetic signatures. The majority of these epigenetic changes, caused by the compounds in question, occur downstream of transcriptional activation mechanisms, whereby the epigenetic alterations can create a transcriptional memory and stably modulate cell function. The increasing understanding of epigenetic mechanisms and their importance in disease has prompted the development of therapeutic interventions that target epigenetic modulatory mechanisms, particularly in oncology where inhibitors of epigenetic-modifying proteins (epidrugs) have been successfully used in treatment, mostly in combination with standard-of-care chemotherapy, either provoking direct cytotoxicity or inhibiting resistance to anticancer drugs. In addition, emerging methods for detecting epigenetically modified DNA in bodily fluids may provide information about tumor phenotype or drug treatment success. However, it is important to note that many technical pitfalls, such as the nondeconvolution of methylcytosine and hydroxymethylcytosine, compromise epigenetic analyses and the interpretation of results. In this review, we provide an update on the field, with an emphasis on the novel therapeutic opportunities made possible by epidrugs.

Application of Microphysiological Systems to Enhance Safety Assessment in Drug Discovery.

Enhancing the early detection of new therapies that are likely to carry a safety liability in the context of the intended patient population would provide a major advance in drug discovery. Microphysiological systems (MPS) technology offers an opportunity to support enhanced preclinical to clinical translation through the generation of higher-quality preclinical physiological data. In this review, we highlight this technological opportunity by focusing on key target organs associated with drug safety and metabolism. By focusing on MPS models that have been developed for these organs, alongside other relevant in vitro models, we review the current state of the art and the challenges that still need to be overcome to ensure application of this technology in enhancing drug discovery.

Primary human hepatocyte spheroids as an in vitro tool for investigating drug compounds with low clearance.

Characterizing the pharmacokinetic properties of drug candidates represents an essential task during drug development. In the past, liver microsomes and primary suspended hepatocytes have been extensively used for this purpose, but their relatively short stability limits the applicability of such in vitro systems for drug compounds with low metabolic turnover. In the present study, we used 3D primary human hepatocyte spheroids to predict the hepatic clearance of seven drugs with low to intermediate clearance in humans. Our results indicate that hepatocyte spheroids maintain their in vivo like phenotype during prolonged incubations allowing to monitor the depletion of parent drug for seven days. In contrast, attempts to increase the relative metabolic capacity by pooling hepatocyte spheroids resulted in an immediate fusion of the spheroids followed by hepatocellular de-differentiation processes, demonstrating limited applicability of the pooling approach for quantitative pharmacokinetic studies. The hepatic clearance values obtained from incubations with individual spheroids were in close correlation with the clinical reference data with six out of seven drug compounds being predicted within a three-fold deviation and average fold and absolute average fold errors of 0.57 and 1.74, respectively. In conclusion, the hepatocyte spheroid model enables accurate hepatic clearance predictions for slowly metabolized drug compounds and represents a valuable tool for determining the pharmacokinetic properties of new drug candidates as well as for mechanistic pharmacokinetic studies. Significance Statement Traditional in vitro systems often fail to predict the hepatic clearance of slowly metabolized drug compounds. The current study demonstrates the ability of primary human hepatocyte spheroids to provide accurate projections on the hepatic clearance of drug compounds with low and intermediate clearance.

Transcriptional and post-transcriptional regulation of the pregnane X receptor: a rationale for interindividual variability in drug metabolism.

The pregnane X receptor (PXR, encoded by the NR1I2 gene) is a ligand-regulated transcription factor originally described as a master regulator of xenobiotic detoxification. Later, however, PXR was also shown to interact with endogenous metabolism and to be further associated with various pathological states. This review focuses predominantly on such aspects, currently less covered in literature, as the control of PXR expression per se in the context of inter-individual differences in drug metabolism. There is growing evidence that non-coding RNAs post-transcriptionally regulate PXR. Effects on PXR have especially been reported for microRNAs (miRNAs), which include miR-148a, miR-18a-5p, miR-140-3p, miR-30c-1-3p and miR-877-5p. Likewise, miRNAs control the expression of both transcription factors involved in PXR expression and regulators of PXR function. The impact of NR1I2 genetic polymorphisms on miRNA-mediated PXR regulation is also discussed. As revealed recently, long non-coding RNAs (lncRNAs) appear to interfere with PXR expression. Reciprocally, PXR activation regulates non-coding RNA expression, thus comprising another level of PXR action in addition to the direct transactivation of protein-coding genes. PXR expression is further controlled by several transcription factors (cross-regulation) giving rise to different PXR transcript variants. Controversies remain regarding the suggested role of feedback regulation (auto-regulation) of PXR expression. In this review, we comprehensively summarize the miRNA-mediated, lncRNA-mediated and transcriptional regulation of PXR expression, and we propose that deciphering the precise mechanisms of PXR expression may bridge our knowledge gap in inter-individual differences in drug metabolism and toxicity.

CYP2E1 in Alcoholic and Non-Alcoholic Liver Injury. Roles of ROS, Reactive Intermediates and Lipid Overload.

CYP2E1 is one of the fifty-seven cytochrome P450 genes in the human genome and is highly conserved. CYP2E1 is a unique P450 enzyme because its heme iron is constitutively in the high spin state, allowing direct reduction of, e.g., dioxygen, causing the formation of a variety of reactive oxygen species and reduction of xenobiotics to toxic products. The CYP2E1 enzyme has been the focus of scientific interest due to (i) its important endogenous function in liver homeostasis, (ii) its ability to activate procarcinogens and to convert certain drugs, e.g., paracetamol and anesthetics, to cytotoxic end products, (iii) its unique ability to effectively reduce dioxygen to radical species causing liver injury, (iv) its capability to reduce compounds, often generating radical intermediates of direct toxic or indirect immunotoxic properties and (v) its contribution to the development of alcoholic liver disease, steatosis and NASH. In this overview, we present the discovery of the enzyme and studies in humans, 3D liver systems and genetically modified mice to disclose its function and clinical relevance. Induction of the CYP2E1 enzyme either by alcohol or high-fat diet leads to increased severity of liver pathology and likelihood to develop ALD and NASH, with subsequent influence on the occurrence of hepatocellular cancer. Thus, fat-dependent induction of the enzyme might provide a link between steatosis and fibrosis in the liver. We conclude that CYP2E1 has many important physiological functions and is a key enzyme for hepatic carcinogenesis, drug toxicity and liver disease.

Generating evidence for precision medicine: considerations made by the Ubiquitous Pharmacogenomics Consortium when designing and operationalizing the PREPARE study.

OBJECTIVES: Pharmacogenetic panel-based testing represents a new model for precision medicine. A sufficiently powered prospective study assessing the (cost-)effectiveness of a panel-based pharmacogenomics approach to guide pharmacotherapy is lacking. Therefore, the Ubiquitous Pharmacogenomics Consortium initiated the PREemptive Pharmacogenomic testing for prevention of Adverse drug Reactions (PREPARE) study. Here, we provide an overview of considerations made to mitigate multiple methodological challenges that emerged during the design. METHODS: An evaluation of considerations made when designing the PREPARE study across six domains: study aims and design, primary endpoint definition and collection of adverse drug events, inclusion and exclusion criteria, target population, pharmacogenomics intervention strategy, and statistical analyses. RESULTS: Challenges and respective solutions included: (1) defining and operationalizing a composite primary endpoint enabling measurement of the anticipated effect, by including only severe, causal, and drug genotype-associated adverse drug reactions; (2) avoiding overrepresentation of frequently prescribed drugs within the patient sample while maintaining external validity, by capping drugs of enrolment; (3) designing the pharmacogenomics intervention strategy to be applicable across ethnicities and healthcare settings; and (4) designing a statistical analysis plan to avoid dilution of effect by initially excluding patients without a gene-drug interaction in a gatekeeping analysis. CONCLUSION: Our design considerations will enable quantification of the collective clinical utility of a panel of pharmacogenomics-markers within one trial as a proof-of-concept for pharmacogenomics-guided pharmacotherapy across multiple actionable gene-drug interactions. These considerations may prove useful to other investigators aiming to generate evidence for precision medicine.

Integrating rare genetic variants into pharmacogenetic drug response predictions.

BACKGROUND: Variability in genes implicated in drug pharmacokinetics or drug response can modulate treatment efficacy or predispose to adverse drug reactions. Besides common genetic polymorphisms, recent sequencing projects revealed a plethora of rare genetic variants in genes encoding proteins involved in drug metabolism, transport, and response. RESULTS: To understand the global importance of rare pharmacogenetic gene variants, we mapped the variability in 208 pharmacogenes by analyzing exome sequencing data from 60,706 unrelated individuals and estimated the importance of rare and common genetic variants using a computational prediction framework optimized for pharmacogenetic assessments. Our analyses reveal that rare pharmacogenetic variants were strongly enriched in mutations predicted to cause functional alterations. For more than half of the pharmacogenes, rare variants account for the entire genetic variability. Each individual harbored on average a total of 40.6 putatively functional variants, rare variants accounting for 10.8% of these. Overall, the contribution of rare variants was found to be highly gene- and drug-specific. Using warfarin, simvastatin, voriconazole, olanzapine, and irinotecan as examples, we conclude that rare genetic variants likely account for a substantial part of the unexplained inter-individual differences in drug metabolism phenotypes. CONCLUSIONS: Combined, our data reveal high gene and drug specificity in the contributions of rare variants. We provide a proof-of-concept on how this information can be utilized to pinpoint genes for which sequencing-based genotyping can add important information to predict drug response, which provides useful information for the design of clinical trials in drug development and the personalization of pharmacological treatment.

Significantly lower CYP2D6 metabolism measured as the O/N-desmethylvenlafaxine metabolic ratio in carriers of CYP2D6*41 versus CYP2D6*9 or CYP2D6*10: a study on therapeutic drug monitoring data from 1003 genotyped Scandinavian patients.

AIMS: CYP2D6*9, CYP2D6*10 and CYP2D6*41 are the most frequent reduced-function CYP2D6 alleles in Caucasians. Despite lacking in vivo evidence, they are collectively classified with an enzyme activity score of 0.5. Thus, the aim of this study was to compare the functional impact of CYP2D6*9, CYP2D6*10 and CYP2D6*41 on CYP2D6 metabolism in a large patient population. METHODS: A total of 1003 patients (mainly Caucasians) with data on CYP2D6 genotype and serum concentrations of venlafaxine and metabolites were included from a therapeutic drug monitoring service in Oslo, Norway. The O-desmethyl-to-N-desmethyl-venlafaxine metabolic ratio (MR) was applied as CYP2D6 biomarker and compared (Mann-Whitney) between carriers of CYP2D6*9-10 (merged) and CYP2D6*41, either combined with CYP2D6*1 or non-coding (null) alleles. MR subgroup estimates were obtained by multiple linear regression for calculations of CYP2D6*9-10 and CYP2D6*41 activity scores. RESULTS: MR was significantly lower in carriers of CYP2D6*41 than CYP2D6*9-10 (P < 0.002). The majority of CYP2D6*41/null carriers (86.7%) had MR in the observed range of CYP2D6null/null carriers compared with the minority of CYP2D6*9-10/null carriers (17.4%). CYP2D6 genotype explained 60.7% of MR variability in the multivariate analysis providing subgroup estimates of 9.54 (95% CI; 7.45-12.20), 3.55 (2.06-6.10), 1.33 (0.87-2.05) and 0.47 (0.35-0.61) in carriers of CYP2D6*1/null (n = 269), CYP2D6*9-10/null (n = 17), CYP2D6*41/null (n = 30) and CYP2D6null/null (n = 95), respectively. Based on these estimates, the calculated activity score of CYP2D6*41 was 0.095 compared to 0.34 for CYP2D6*9-10. CONCLUSIONS: CYP2D6 metabolism measured as the O/N-desmethylvenlafaxine ratio is significantly lower in Scandinavian carriers of CYP2D6*41 vs. CYP2D6*9-10. Thus, these alleles should be differentiated when classifying CYP2D6 phenotype from genotype.

Characterisation of the NRF2 transcriptional network and its response to chemical insult in primary human hepatocytes: implications for prediction of drug-induced liver injury.

The transcription factor NRF2, governed by its repressor KEAP1, protects cells against oxidative stress. There is interest in modelling the NRF2 response to improve the prediction of clinical toxicities such as drug-induced liver injury (DILI). However, very little is known about the makeup of the NRF2 transcriptional network and its response to chemical perturbation in primary human hepatocytes (PHH), which are often used as a translational model for investigating DILI. Here, microarray analysis identified 108 transcripts (including several putative novel NRF2-regulated genes) that were both downregulated by siRNA targeting NRF2 and upregulated by siRNA targeting KEAP1 in PHH. Applying weighted gene co-expression network analysis (WGCNA) to transcriptomic data from the Open TG-GATES toxicogenomics repository (representing PHH exposed to 158 compounds) revealed four co-expressed gene sets or 'modules' enriched for these and other NRF2-associated genes. By classifying the 158 TG-GATES compounds based on published evidence, and employing the four modules as network perturbation metrics, we found that the activation of NRF2 is a very good indicator of the intrinsic biochemical reactivity of a compound (i.e. its propensity to cause direct chemical stress), with relatively high sensitivity, specificity, accuracy and positive/negative predictive values. We also found that NRF2 activation has lower sensitivity for the prediction of clinical DILI risk, although relatively high specificity and positive predictive values indicate that false positive detection rates are likely to be low in this setting. Underpinned by our comprehensive analysis, activation of the NRF2 network is one of several mechanism-based components that can be incorporated into holistic systems toxicology models to improve mechanistic understanding and preclinical prediction of DILI in man.