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Statins reduce cholesterol, prevent cardiovascular disease, and are among the most commonly prescribed medications in the world. Statin-associated musculoskeletal symptoms (SAMS) impact statin adherence and ultimately can impede the long-term effectiveness of statin therapy. There are several identified pharmacogenetic variants that impact statin disposition and adverse events during statin therapy. SLCO1B1 encodes a transporter (SLCO1B1; alternative names include OATP1B1 or OATP-C) that facilitates the hepatic uptake of all statins. ABCG2 encodes an efflux transporter (BCRP) that modulates the absorption and disposition of rosuvastatin. CYP2C9 encodes a phase I drug metabolizing enzyme responsible for the oxidation of some statins. Genetic variation in each of these genes alters systemic exposure to statins (i.e., simvastatin, rosuvastatin, pravastatin, pitavastatin, atorvastatin, fluvastatin, lovastatin), which can increase the risk for SAMS. We summarize the literature supporting these associations and provide therapeutic recommendations for statins based on SLCO1B1, ABCG2, and CYP2C9 genotype with the goal of improving the overall safety, adherence, and effectiveness of statin therapy. This document replaces the 2012 and 2014 Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines for SLCO1B1 and simvastatin-induced myopathy.

The Pharmacogene Variation Consortium (PharmVar) serves as a global repository providing star (*) allele nomenclature for the polymorphic human CYP4F2 gene. CYP4F2 genetic variation impacts the metabolism of vitamin K, which is associated with warfarin dose requirements, and the metabolism of drugs, such as imatinib or fingolimod, and certain endogenous compounds including vitamin E and eicosanoids. This GeneFocus provides a comprehensive overview and summary of CYP4F2 genetic variation including the characterization of 14 novel star alleles, CYP4F2*4 through *17. A description of how haplotype information cataloged by PharmVar is utilized by the Pharmacogenomics Knowledgebase (PharmGKB) and the Clinical Pharmacogenetics Implementation Consortium (CPIC) is also provided. [ABSTRACT FROM AUTHOR]

The Pharmacogene Variation Consortium (PharmVar) provides nomenclature for the human CYP2A gene locus containing the highly polymorphic CYP2A6 gene. CYP2A6 plays a role in the metabolism of nicotine and various drugs. Thus, genetic variation can substantially contribute to the function of this enzyme and associated efficacy and safety. This GeneFocus provides an overview of the clinical significance of CYP2A6, including its genetic variation and function. We also highlight and discuss caveats in the identification and characterization of allelic variation of this complex pharmacogene, a prerequisite for accurate genotype determination and prediction of phenotype status. [ABSTRACT FROM AUTHOR]

Beta‐blockers are widely used medications for a variety of indications, including heart failure, myocardial infarction, cardiac arrhythmias, and hypertension. Genetic variability in pharmacokinetic (e.g., CYP2D6) and pharmacodynamic (e.g., ADRB1, ADRB2, ADRA2C, GRK4, GRK5) genes have been studied in relation to beta‐blocker exposure and response. We searched and summarized the strength of the evidence linking beta‐blocker exposure and response with the six genes listed above. The level of evidence was high for associations between CYP2D6 genetic variation and both metoprolol exposure and heart rate response. Evidence indicates that CYP2D6 poor metabolizers experience clinically significant greater exposure and lower heart rate in response to metoprolol compared with those who are not poor metabolizers. Therefore, we provide therapeutic recommendations regarding genetically predicted CYP2D6 metabolizer status and metoprolol therapy. However, there was insufficient evidence to make therapeutic recommendations for CYP2D6 and other beta‐blockers or for any beta‐blocker and the other five genes evaluated (updates at www.cpicpgx.org). [ABSTRACT FROM AUTHOR]

Background: CYP2D6 testing is increasingly used to guide drug therapy and thus, reliable methods are needed to test this complex and polymorphic gene locus. A particular challenge arises from the detection and interpretation of structural variants (SVs) including gene deletions, duplications, and hybrids with the CYP2D7 pseudogene. This study validated the Absolute Q™ platform for digital PCR-based CYP2D6 copy number variation (CNV) determination by comparing results to those obtained with a previously established method using the QX200 platform. In addition, protocols for streamlining CYP2D6 CNV testing were established and validated including the "One-pot" single-step restriction enzyme digestion and a multiplex assay simultaneously targeting the CYP2D6 5'UTR, intron 6, and exon 9 regions. Methods: Genomic DNA (gDNA) samples from Coriell (n = 13) and from blood, saliva, and liver tissue (n = 17) representing 0-6 copies were tested on the Absolute Q and QX200 platforms. Custom TaqMan™ copy number (CN) assays targeting CYP2D6 the 5'UTR, intron 6, and exon 9 regions and a reference gene assay (TERT or RNaseP) were combined for multiplexing by optical channel. In addition, two digestion methods (One-pot digestion and traditional) were assessed. Inconclusive CN values on the Absolute Q were resolved using an alternate reference gene and/or diluting gDNA. Results: Overall, results between the two platforms and digestions methods were consistent. The "One-pot" digestion method and optically multiplexing up to three CYP2D6 regions yielded consistent result across DNA sample types and diverse SVs, reliably detecting up to 6 gene copies. Rare variation in reference genes were found to interfere with results and interpretation, which were resolved by using a different reference. Conclusion: The Absolute Q produced accurate and reliable CYP2D6 copy number results allowing for a streamlined and economical protocol using One-pot digestion and multiplexing three target regions. Protocols are currently being expanded to other pharmacogenes presenting with SVs/CNVs. [ABSTRACT FROM AUTHOR]

ObjectivesThe objective of this study was to evaluate the performance of pediatric pharmacogenetic-based dose prediction models by using an independent cohort of pediatric patients from a multicenter trial.MethodsClinical and genetic data (CYP2C9 [cytochrome P450 2C9] and VKORC1 [vitamin K epoxide reductase]) were collected from pediatric patients aged 3 months to 17 years who were receiving warfarin as part of standard care at 3 separate clinical sites. The accuracy of 8 previously published pediatric pharmacogenetic-based dose models was evaluated in the validation cohort by comparing predicted maintenance doses to actual stable warfarin doses. The predictive ability was assessed by using the proportion of variance (R(2)), mean prediction error (MPE), and the percentage of predictions that fell within 20% of the actual maintenance dose.ResultsThirty-two children reached a stable international normalized ratio and were included in the validation cohort. The pharmacogenetic-based warfarin dose models showed a proportion of variance ranging from 35% to 78% and an MPE ranging from -2.67 to 0.85 mg/day in the validation cohort. Overall, the model developed by Hamberg et al showed the best performance in the validation cohort (R(2) = 78%; MPE = 0.15 mg/day) with 38% of the predictions falling within 20% of observed doses.ConclusionsPharmacogenetic-based algorithms provide better predictions than a fixed-dose approach, although an optimal dose algorithm has not yet been developed.

CYP2D6 contributes to the metabolism of many clinically used drugs and is increasingly tested to individualize drug therapy. The CYP2D6 gene is challenging to genotype due to the highly complex nature of its gene locus. TaqMan technology is widely used in the clinical and research settings for genotype analysis due to assay reliability, low cost, and the availability of commercially available assays. The assay identifying 1023C>T (rs28371706) defining a reduced function (CYP2D6*17) and several nonfunctional alleles, produced a small number of unexpected diplotype calls in three independent sets of samples, i.e. calls suggested the presence of a CYP2D6*4 subvariant containing 1023C>T. Gene resequencing did not reveal any unknown SNPs in the primer or probe binding sites in any of the samples, but all affected samples featured a trio of SNPs on their CYP2D6*4 allele between one of the PCR primer and probe binding sites. While the phenomenon was ultimately overcome by an alternate assay utilizing a PCR primer excluding the SNP trio, the mechanism causing this phenomenon remains elusive. This rare and unexpected event underscores the importance of assay validation in samples representing a variety of genotypes, but also vigilance of assay performance in highly polymorphic genes such as CYP2D6.

AimWe sought to discover endogenous urinary biomarkers of human CYP2D6 activity.Patients & methodsHealthy pediatric subjects (n = 189) were phenotyped using dextromethorphan and randomized for candidate biomarker selection and validation. Global urinary metabolomics was performed using liquid chromatography quadrupole time-of-flight mass spectrometry. Candidate biomarkers were tested in adults receiving fluoxetine, a CYP2D6 inhibitor.ResultsA biomarker, M1 (m/z 444.3102) was correlated with CYP2D6 activity in both the pediatric training and validation sets. Poor metabolizers had undetectable levels of M1, whereas it was present in subjects with other phenotypes. In adult subjects, a 9.56-fold decrease in M1 abundance was observed during CYP2D6 inhibition.ConclusionIdentification and validation of M1 may provide a noninvasive means of CYP2D6 phenotyping.

Liver cytochrome P450s (P450s) play critical roles in drug metabolism, toxicology, and metabolic processes. Despite rapid progress in the understanding of these enzymes, a systematic investigation of the full spectrum of functionality of individual P450s, the interrelationship or networks connecting them, and the genetic control of each gene/enzyme is lacking. To this end, we genotyped, expression-profiled, and measured P450 activities of 466 human liver samples and applied a systems biology approach via the integration of genetics, gene expression, and enzyme activity measurements. We found that most P450s were positively correlated among themselves and were highly correlated with known regulators as well as thousands of other genes enriched for pathways relevant to the metabolism of drugs, fatty acids, amino acids, and steroids. Genome-wide association analyses between genetic polymorphisms and P450 expression or enzyme activities revealed sets of SNPs associated with P450 traits, and suggested the existence of both cis-regulation of P450 expression (especially for CYP2D6) and more complex trans-regulation of P450 activity. Several novel SNPs associated with CYP2D6 expression and enzyme activity were validated in an independent human cohort. By constructing a weighted coexpression network and a Bayesian regulatory network, we defined the human liver transcriptional network structure, uncovered subnetworks representative of the P450 regulatory system, and identified novel candidate regulatory genes, namely, EHHADH, SLC10A1, and AKR1D1. The P450 subnetworks were then validated using gene signatures responsive to ligands of known P450 regulators in mouse and rat. This systematic survey provides a comprehensive view of the functionality, genetic control, and interactions of P450s.

Serotonin reuptake inhibitor antidepressants, including selective serotonin reuptake inhibitors (SSRIs; i.e., citalopram, escitalopram, fluoxetine, fluvoxamine, paroxetine, and sertraline), serotonin and norepinephrine reuptake inhibitors (i.e., desvenlafaxine, duloxetine, levomilnacipran, milnacipran, and venlafaxine), and serotonin modulators with SSRI‐like properties (i.e., vilazodone and vortioxetine) are primary pharmacologic treatments for major depressive and anxiety disorders. Genetic variation in CYP2D6, CYP2C19, and CYP2B6 influences the metabolism of many of these antidepressants, which may potentially affect dosing, efficacy, and tolerability. In addition, the pharmacodynamic genes SLC6A4 (serotonin transporter) and HTR2A (serotonin‐2A receptor) have been examined in relation to efficacy and side effect profiles of these drugs. This guideline updates and expands the 2015 Clinical Pharmacogenetics Implementation Consortium (CPIC) guideline for CYP2D6 and CYP2C19 genotypes and SSRI dosing and summarizes the impact of CYP2D6, CYP2C19, CYP2B6, SLC6A4, and HTR2A genotypes on antidepressant dosing, efficacy, and tolerability. We provide recommendations for using CYP2D6, CYP2C19, and CYP2B6 genotype results to help inform prescribing these antidepressants and describe the existing data for SLC6A4 and HTR2A, which do not support their clinical use in antidepressant prescribing. [ABSTRACT FROM AUTHOR]

Over 20% of US Food and Drug Administration (FDA)‐approved drugs in the United States are metabolized by the hepatic enzyme cytochrome P450 2D6 (CYP2D6). The gene encoding CYP2D6 is highly polymorphic and genetic variation has been shown to impact drug response for many commonly dispensed drugs including opioids and antidepressants. Thus, it is important to understand an individual's CYP2D6 metabolizer status to optimize treatment outcomes for patients taking medications that are metabolized by this enzyme. Consequently, clinical CYP2D6 pharmacogenetic testing is being implemented by a growing number of health centers. Furthermore, clinical guidelines currently recommend adapting therapeutic regimens based on CYP2D6 genotype‐informed phenotype. However, CYP2D6 genetic variation varies considerably across global populations and many allelic variants, or star alleles, are predominantly found in certain ancestral populations. Although CYP2D6 genetic variation has been extensively studied, there is still a paucity of information for many non‐European populations. As has been shown for other pharmacogenes in randomized controlled trials, results from European populations cannot simply be extrapolated to other groups and, in some cases, even has the potential to cause harm. Therefore, enhanced inclusion in pharmacogenetic studies is urgently needed to increase ancestral representation, determine the extent of global CYP2D6 genetic variation (e.g., ancestry‐specific variants), and determine the clinical impact of this variation on clinical treatment outcome. This review highlights knowledge gaps, challenges, and future directions in CYP2D6 pharmacogenomics through a unique pharmacoequity lens to address health inequities that hamper our ability to optimize drug therapy for improved pharmacological outcomes in diverse populations globally. [ABSTRACT FROM AUTHOR]

The Pharmacogene Variation Consortium (PharmVar) is now providing star (*) allele nomenclature for the highly polymorphic human SLCO1B1 gene encoding the organic anion transporting polypeptide 1B1 (OATP1B1) drug transporter. Genetic variation within the SLCO1B1 gene locus impacts drug transport, which can lead to altered pharmacokinetic profiles of several commonly prescribed drugs. Variable OATP1B1 function is of particular importance regarding hepatic uptake of statins and the risk of statin‐associated musculoskeletal symptoms. To introduce this important drug transporter gene into the PharmVar database and serve as a unified reference of haplotype variation moving forward, an international group of gene experts has performed an extensive review of all published SLCO1B1 star alleles. Previously published star alleles were self‐assigned by authors and only loosely followed the star nomenclature system that was first developed for cytochrome P450 genes. This nomenclature system has been standardized by PharmVar and is now applied to other important pharmacogenes such as SLCO1B1. In addition, data from the 1000 Genomes Project and investigator‐submitted data were utilized to confirm existing haplotypes, fill knowledge gaps, and/or define novel star alleles. The PharmVar‐developed SLCO1B1 nomenclature has been incorporated by the Clinical Pharmacogenetics Implementation Consortium (CPIC) 2022 guideline on statin‐associated musculoskeletal symptoms. [ABSTRACT FROM AUTHOR]