Functional characterization of CYP2D6 enhancer polymorphisms

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.

A Genome-Wide Association Study of Endoxifen Serum Concentrations and Adjuvant Tamoxifen Efficacy in Early-Stage Breast Cancer Patients

Tamoxifen is part of the standard of care of endocrine therapy for adjuvant treatment of breast cancer. However, survival outcomes with tamoxifen are highly variable. The concentration of endoxifen, the 30-100 times more potent metabolite of tamoxifen and bioactivated by the CYP2D6 enzyme, has been described as the most relevant metabolite of tamoxifen metabolism. A genome-wide association study (GWAS) was performed with the objective to identify genetic polymorphisms associated with endoxifen serum concentration levels and clinical outcome in early-stage breast cancer patients receiving tamoxifen. A GWAS was conducted in 608 women of the CYPTAM study (NTR1509/PMID: 30120701). Germline DNA and clinical and survival characteristics were readily available. Genotyping was performed on Infinium Global Screening Array (686,082 markers) and single nucleotide polymorphism (SNP) imputation by using 1000 Genomes. Relapse-free survival during tamoxifen (RFSt) was defined the primary clinical outcome. Endoxifen serum concentration was analyzed as a continuous variable. Several genetic variants reached genome-wide significance (P value: ≤5 × 10-8). Endoxifen concentrations analysis identified 430 variants, located in TCF20 and WBP2NL genes (chromosome 22), which are in strong linkage disequilibrium with CYP2D6 variants. In the RFSt analysis, several SNP were identified (LPP gene: rs77693286, HR 18.3, 95% CI: 15.2-21.1; rs6790761, OR 18.2, 95% CI: 15.5-21.1). Endoxifen concentrations have a strong association with the chromosome 22, which contains the CYP2D6 gene.

Novel Independent Trans- and Cis-Genetic Variants Associated with CYP2D6 Expression and Activity in Human Livers

Cytochrome P450 2D6 (CYP2D6) is a critical hepatic drug-metabolizing enzyme in humans, responsible for metabolizing approximately 20%-25% of commonly used medications such as codeine, desipramine, fluvoxamine, paroxetine, and tamoxifen. The CYP2D6 gene is highly polymorphic, resulting in substantial interindividual variability in its catalytic function and the pharmacokinetics and therapeutic outcomes of its substrate drugs. Although many functional CYP2D6 variants have been discovered and validated, a significant portion of the variability in the expression and activity of CYP2D6 remains unexplained. In this study, we performed a genome-wide association study (GWAS) to identify novel variants associated with CYP2D6 protein expression in individual human livers, followed by a conditional analysis to control for the effect of functional CYP2D6 star alleles. We also examined their impact on hepatic CYP2D6 activity. Genotyping on a genome-wide scale was achieved using the Illumina Multi-Ethnic Genotyping Array (MEGA). A data-independent acquisition (DIA)-based proteomics method was used to quantify CYP2D6 protein concentrations. CYP2D6 activity was determined by measuring the dextromethorphan O-demethylation in individual human liver s9 fractions. The GWAS identified 44 single nuclear polymorphisms (SNPs) that are significantly associated with CYP2D6 protein expressions with a P value threshold of 5.0 × 10-7 After the conditional analysis, five SNPs, including the cis-variants rs1807493 and rs1062753 and the trans-variants rs4073010, rs729559, and rs80274432, emerged as independent variants significantly correlated with hepatic CYP2D6 protein expressions. Notably, four of these SNPs, except for rs80274432, also exhibited a significant association with CYP2D6 activities in human livers, suggesting their potential as novel and independent cis- and trans-variants regulating CYP2D6. SIGNIFICANT STATEMENT: Using individual human livers, we identified four novel cis- and trans-pQTLs/aQTLs (protein quantitative trait loci/activity quantitative trait loci) of Cytochrome P450 2D6 (CYP2D6) that are independent from known functional CYP2D6 star alleles. This study connects the CYP2D6 gene expression and activity, enhancing our understanding of the genetic variants associated with CYP2D6 protein expression and activity, potentially advancing our insight into the interindividual variability in CYP2D6 substrate medication response.

Genetic polymorphisms are associated with individual susceptibility to dexmedetomidine

Introduction: Dexmedetomidine (DXM) is widely used as an adjuvant to anesthesia or a sedative medicine, and differences in individual sensitivity to the drug exist. This study aimed to investigate the effect of genetic polymorphisms on these differences. Methods: A total of 112 patients undergoing hand surgery were recruited. DXM 0.5 μg/kg was administered within 10 min and then continuously injected (0.4 μg/kg/h). Narcotrend index, effective dose and onset time of sedation, MAP, and HR were measured. Forty-five single nucleotide polymorphisms (SNPs) were selected for genotype. Results: We observed individual differences in the sedation and hemodynamics induced by DXM. ABCG2 rs2231142, CYP2D6 rs16947, WBP2NL rs5758550, KATP rs141294036, KCNMB1 rs11739136, KCNMA1 rs16934182, ABCC9 rs11046209, ADRA2A rs1800544, and ADRB2 rs1042713 were shown to cause statistically significant (p < 0.05) influence on the individual variation of DXM on sedation and hemodynamics. Moreover, the multiple linear regression analysis indicated sex, BMI, and ADRA2A rs1800544 are statistically related to the effective dose of DXM sedation. Discussion: The evidence suggests that the nine SNPs involved in transport proteins, metabolic enzymes, and target proteins of DXM could explain the individual variability in the sedative and hemodynamic effects of DXM. Therefore, with SNP genotyping, these results could guide personalized medication and promote clinical and surgical management.

A frequent CYP2D6 variant promotes skipping of exon 3 and reduces CYP2D6 protein expression in human liver samples

CYP2D6 is one of the most polymorphic drug-metabolizing enzymes in the liver. While genetic CYP2D6 variants serve as clinical biomarkers to predict CYP2D6 activity, large inter-person variability in CYP2D6 expression remains unaccounted for. Previous results suggest that there is variable expression of a CYP2D6 splice isoform with an in-frame deletion of exon 3 (CYP2D6ΔE3) encoding a protein lacking numerous active site residues. Here, using fragment analysis and RT-qPCR, we revealed that rs1058164 G (MAF = 27%-43%) is associated with increased formation of CYP2D6∆E3 in human liver samples (1.4-2.5-fold) and transfected cells. Furthermore, western blots showed that rs1058164 G was associated with a 50% decrease in full-length hepatic CYP2D6 protein expression. In addition, by studying a larger liver cohort, we confirmed our previous results that rs16947 (CYP2D6*2) reduces full-length CYP2D6 mRNA by increasing the production of an unstable splice isoform lacking exon 6 (CYP2D6ΔE6) and that the impact of CYP2D6ΔE6 is offset in carriers of the downstream enhancer variant rs5758550. The three frequent SNPs (rs1058164, rs16947, and rs5758550) form various 3-SNP-haplotypes, each with distinct CYP2D6 expression characteristics. Using an expression score (ES) system, we tested the impact of the 3-SNP-haplotype on improving the standard model to predict hepatic CYP2D6 protein expression based on genotype. A model that incorporates the 3-SNP-haplotype provided the best fit for CYP2D6 expression and also accounted for more variability in CYP2D6 protein levels (59%) than a model based on the accepted standard (36%) or one that only adds rs16947 and rs5758550 (42%). Clinical studies are needed to determine whether including the 3-SNP-haplotype alongside current standard CYP2D6 models improves the predictive value of CYP2D6 panels.

Pharmacogenomics: Driving Personalized Medicine

Personalized medicine tailors therapies, disease prevention, and health maintenance to the individual, with pharmacogenomics serving as a key tool to improve outcomes and prevent adverse effects. Advances in genomics have transformed pharmacogenetics, traditionally focused on single gene-drug pairs, into pharmacogenomics, encompassing all "-omics" fields (e.g., proteomics, transcriptomics, metabolomics, and metagenomics). This review summarizes basic genomics principles relevant to translation into therapies, assessing pharmacogenomics' central role in converging diverse elements of personalized medicine. We discuss genetic variations in pharmacogenes (drug-metabolizing enzymes, drug transporters, and receptors), their clinical relevance as biomarkers, and the legacy of decades of research in pharmacogenetics. All types of therapies, including proteins, nucleic acids, viruses, cells, genes, and irradiation, can benefit from genomics, expanding the role of pharmacogenomics across medicine. Food and Drug Administration approvals of personalized therapeutics involving biomarkers increase rapidly, demonstrating the growing impact of pharmacogenomics. A beacon for all therapeutic approaches, molecularly targeted cancer therapies highlight trends in drug discovery and clinical applications. To account for human complexity, multicomponent biomarker panels encompassing genetic, personal, and environmental factors can guide diagnosis and therapies, increasingly involving artificial intelligence to cope with extreme data complexities. However, clinical application encounters substantial hurdles, such as unknown validity across ethnic groups, underlying bias in health care, and real-world validation. This review address the underlying science and technologies germane to pharmacogenomics and personalized medicine, integrated with economic, ethical, and regulatory issues, providing insights into the current status and future direction of health care. SIGNIFICANCE STATEMENT: Personalized medicine aims to optimize health care for the individual patients with use of predictive biomarkers to improve outcomes and prevent adverse effects. Pharmacogenomics drives biomarker discovery and guides the development of targeted therapeutics. This review addresses basic principles and current trends in pharmacogenomics, with large-scale data repositories accelerating medical advances. The impact of pharmacogenomics is discussed, along with hurdles impeding broad clinical implementation, in the context of clinical care, ethics, economics, and regulatory affairs.

PEACOCK: a machine learning approach to assess the validity of cell type-specific enhancer-gene regulatory relationships

The vast majority of disease-associated variants identified in genome-wide association studies map to enhancers, powerful regulatory elements which orchestrate the recruitment of transcriptional complexes to their target genes' promoters to upregulate transcription in a cell type- and timing-dependent manner. These variants have implicated thousands of enhancers in many common genetic diseases, including nearly all cancers. However, the etiology of most of these diseases remains unknown because the regulatory target genes of the vast majority of enhancers are unknown. Thus, identifying the target genes of as many enhancers as possible is crucial for learning how enhancer regulatory activities function and contribute to disease. Based on experimental results curated from scientific publications coupled with machine learning methods, we developed a cell type-specific score predictive of an enhancer targeting a gene. We computed the score genome-wide for every possible cis enhancer-gene pair and validated its predictive ability in four widely used cell lines. Using a pooled final model trained across multiple cell types, all possible gene-enhancer regulatory links in cis (~17 M) were scored and added to the publicly available PEREGRINE database ( www.peregrineproj.org ). These scores provide a quantitative framework for the enhancer-gene regulatory prediction that can be incorporated into downstream statistical analyses.

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.

From Croatian Roma to 1000 Genomes: The Story of the CYP2D6 Gene Promoter and Enhancer SNPs

The CYP2D6 gene encodes an enzyme responsible for the metabolism of ~20% of clinically prescribed drugs. In this study, 18 SNPs from the enhancer and promoter regions of CYP2D6 in 323 Roma from Croatia were genotyped, to find out whether the demographic history of Roma affected the distribution of the studied SNPs and their linkage disequilibrium (LD) values, with the major SNPs defining the CYP2D6 star alleles. No differences were found between the three Roma groups in allele and genotype frequencies. The distribution of LD values of Roma was compared with LD values of European and Asian populations. Regulatory CYP2D6 SNPs (rs5758550, rs28624811, rs1080985 and rs1080983) showed similar distribution and the highest LDs with rs16947 from the gene-coding region in all populations. In the promoter region, a complete LD between rs1080989 and rs28588594, and between rs1080983 and rs28624811, was found in Croatian Roma and investigated populations from 1000 genomes. A high LD was also found between rs1080985 from the promoter and rs5758550 from the enhancer region. SNP rs28735595 from the gene promoter region had the highest LD, with two gene region SNPs, rs1058164 and rs1135840. To conclude, the Croatian Roma population shows an LD pattern of the CYP2D6 gene region similar to the 1000 Genomes European and Asian populations.

From pharmacogenetics to pharmaco-omics: Milestones and future directions

The origins of pharmacogenetics date back to the 1950s, when it was established that inter-individual differences in drug response are partially determined by genetic factors. Since then, pharmacogenetics has grown into its own field, motivated by the translation of identified gene-drug interactions into therapeutic applications. Despite numerous challenges ahead, our understanding of the human pharmacogenetic landscape has greatly improved thanks to the integration of tools originating from disciplines as diverse as biochemistry, molecular biology, statistics, and computer sciences. In this review, we discuss past, present, and future developments of pharmacogenetics methodology, focusing on three milestones: how early research established the genetic basis of drug responses, how technological progress made it possible to assess the full extent of pharmacological variants, and how multi-dimensional omics datasets can improve the identification, functional validation, and mechanistic understanding of the interplay between genes and drugs. We outline novel strategies to repurpose and integrate molecular and clinical data originating from biobanks to gain insights analogous to those obtained from randomized controlled trials. Emphasizing the importance of increased diversity, we envision future directions for the field that should pave the way to the clinical implementation of pharmacogenetics.

The Impact of the CYP2D6 "Enhancer" Single Nucleotide Polymorphism on CYP2D6 Activity

rs5758550 has been associated with enhanced transcription and suggested to be a useful marker of CYP2D6 activity. As there are limited and inconsistent data regarding the utility of this distant "enhancer" single nucleotide polymorphism (SNP), our goal was to further assess the impact of rs5758550 on CYP2D6 activity toward two probe substrates, atomoxetine (ATX) and dextromethorphan (DM), using in vivo urinary metabolite (DM; n = 188) and pharmacokinetic (ATX; n = 70) and in vitro metabolite formation (ATX and DM; n = 166) data. All subjects and tissues were extensively genotyped, the "enhancer" SNP phased with established CYP2D6 haplotypes either computationally or experimentally, and the impact on CYP2D6 activity investigated using several linear models of varying complexity to determine the proportion of variability in CYP2D6 activity captured by each model. For all datasets and models, the "enhancer" SNP had no or only a modest impact on CYP2D6 activity prediction. An increased effect, when present, was more pronounced for ATX than DM suggesting potential substate-dependency. In addition, CYP2D6*2 alleles with the "enhancer" SNP were associated with modestly higher metabolite formation rates in vitro, but not in vivo; no effect was detected for CYP2D6*1 alleles with "enhancer" SNP. In summary, it remains inconclusive whether the small effects detected in this investigation are indeed caused by the "enhancer" SNP or are rather due to its incomplete linkage with other variants within the gene. Taken together, there does not appear to be sufficient evidence to warrant the "enhancer" SNP be included in clinical CYP2D6 pharmacogenetic testing.

Recommendations for Clinical CYP2D6 Genotyping Allele Selection: A Joint Consensus Recommendation of the Association for Molecular Pathology, College of American Pathologists, Dutch Pharmacogenetics Working Group of the Royal Dutch Pharmacists Association, and the European Society for Pharmacogenomics and Personalized Therapy

The goals of the Association for Molecular Pathology Clinical Practice Committee's Pharmacogenomics (PGx) Working Group are to define the key attributes of pharmacogenetic alleles recommended for clinical testing, and to determine a minimal set of variants that should be included in clinical PGx genotyping assays. This document series provides recommendations on a minimal panel of variant alleles (Tier 1) and an extended panel of variant alleles (Tier 2) that will aid clinical laboratories in designing assays for PGx testing. When developing these recommendations, the Association for Molecular Pathology PGx Working Group considered the functional impact of the variant alleles, allele frequencies in multiethnic populations, the availability of reference materials, as well as other technical considerations with regard to PGx testing. The ultimate goal of this Working Group is to promote standardization of PGx gene/allele testing across clinical laboratories. This document is focused on clinical CYP2D6 PGx testing that may be applied to all cytochrome P450 2D6-metabolized medications. These recommendations are not meant to be interpreted as prescriptive but to provide a reference guide for clinical laboratories that may be either implementing PGx testing or reviewing and updating their existing platform.

Monitoring Plasmodium vivax resistance to antimalarials: Persisting challenges and future directions

Emerging antimalarial drug resistance may undermine current efforts to control and eliminate Plasmodium vivax, the most geographically widespread yet neglected human malaria parasite. Endemic countries are expected to assess regularly the therapeutic efficacy of antimalarial drugs in use in order to adjust their malaria treatment policies, but proper funding and trained human resources are often lacking to execute relatively complex and expensive clinical studies, ideally complemented by ex vivo assays of drug resistance. Here we review the challenges for assessing in vivo P. vivax responses to commonly used antimalarials, especially chloroquine and primaquine, in the presence of confounding factors such as variable drug absorption, metabolism and interaction, and the risk of new infections following successful radical cure. We introduce a simple modeling approach to quantify the relative contribution of relapses and new infections to recurring parasitemias in clinical studies of hypnozoitocides. Finally, we examine recent methodological advances that may render ex vivo assays more practical and widely used to confirm P. vivax drug resistance phenotypes in endemic settings and review current approaches to the development of robust genetic markers for monitoring chloroquine resistance in P. vivax populations.

ESR1 ChIP-Seq Identifies Distinct Ligand-Free ESR1 Genomic Binding Sites in Human Hepatocytes and Liver Tissue

The estrogen receptor alpha (ESR1) is an important gene transcriptional regulator, known to mediate the effects of estrogen. Canonically, ESR1 is activated by its ligand estrogen. However, the role of unliganded ESR1 in transcriptional regulation has been gaining attention. We have recently shown that ligand-free ESR1 is a key regulator of several cytochrome P450 (CYP) genes in the liver, however ligand-free ESR1 has not been characterized genome-wide in the human liver. To address this, ESR1 ChIP-Seq was conducted in human liver samples and in hepatocytes with or without 17beta-estradiol (E2) treatment. We identified both ligand-dependent and ligand-independent binding sites throughout the genome. These two ESR1 binding categories showed different genomic localization, pathway enrichment, and cofactor colocalization, indicating different ESR1 regulatory function depending on ligand availability. By analyzing existing ESR1 data from additional human cell lines, we uncovered a potential ligand-independent ESR1 activity, namely its co-enrichment with the zinc finger protein 143 (ZNF143). Furthermore, we identified ESR1 binding sites near many gene loci related to drug therapy, including the CYPs. Overall, this study shows distinct ligand-free and ligand-bound ESR1 chromatin binding profiles in the liver and suggests the potential broad influence of ESR1 in drug metabolism and drug therapy.

How Can Drug Metabolism and Transporter Genetics Inform Psychotropic Prescribing?

Many genetic variants in drug metabolizing enzymes and transporters have been shown to be relevant for treating psychiatric disorders. Associations are strong enough to feature on drug labels and for prescribing guidelines based on such data. A range of commercial tests are available; however, there is variability in included genetic variants, methodology, and interpretation. We herein provide relevant background for understanding clinical associations with specific variants, other factors that are relevant to consider when interpreting such data (such as age, gender, drug-drug interactions), and summarize the data relevant to clinical utility of pharmacogenetic testing in psychiatry and the available prescribing guidelines. We also highlight areas for future research focus in this field.

Transfer learning enables prediction of CYP2D6 haplotype function

Cytochrome P450 2D6 (CYP2D6) is a highly polymorphic gene whose protein product metabolizes more than 20% of clinically used drugs. Genetic variations in CYP2D6 are responsible for interindividual heterogeneity in drug response that can lead to drug toxicity and ineffective treatment, making CYP2D6 one of the most important pharmacogenes. Prediction of CYP2D6 phenotype relies on curation of literature-derived functional studies to assign a functional status to CYP2D6 haplotypes. As the number of large-scale sequencing efforts grows, new haplotypes continue to be discovered, and assignment of function is challenging to maintain. To address this challenge, we have trained a convolutional neural network to predict functional status of CYP2D6 haplotypes, called Hubble.2D6. Hubble.2D6 predicts haplotype function from sequence data and was trained using two pre-training steps with a combination of real and simulated data. We find that Hubble.2D6 predicts CYP2D6 haplotype functional status with 88% accuracy in a held-out test set and explains 47.5% of the variance in in vitro functional data among star alleles with unknown function. Hubble.2D6 may be a useful tool for assigning function to haplotypes with uncurated function, and used for screening individuals who are at risk of being poor metabolizers.

Examination of Metoprolol Pharmacokinetics and Pharmacodynamics Across CYP2D6 Genotype-Derived Activity Scores

Recent CYP2D6 phenotype standardization efforts by CYP2D6 activity score (AS) are based on limited pharmacokinetic (PK) and pharmacodynamic (PD) data. Using data from two independent clinical trials of metoprolol, we compared metoprolol PK and PD across CYP2D6 AS with the goal of determining whether the PK and PD data support the new phenotype classification. S‐metoprolol apparent oral clearance (CLo), adjusted for clinical factors, was correlated with CYP2D6 AS (P < 0.001). The natural log of CLo was lower with an AS of 1 (7.6 ± 0.4 mL/minute) vs. 2–2.25 (8.3 ± 0.6 mL/minute; P = 0.012), similar between an AS of 1 and 1.25–1.5 (7.8 ± 0.5 mL/minute; P = 0.702), and lower with an AS of 1.25–1.5 vs. 2–2.25 (P = 0.03). There was also a greater reduction in heart rate with metoprolol among study participants with AS of 1 (−10.8 ± 5.5) vs. 2–2.25 (−7.1 ± 5.6; P < 0.001) and no significant difference between those with an AS of 1 and 1.25–1.5 (−9.2 ± 4.7; P = 0.095). These data highlight linear trends among CYP2D6 AS and metoprolol PK and PD, but inconsistencies with the phenotypes assigned by AS based on the current standards. Overall, this case study with metoprolol suggests that utilizing CYP2D6 AS, instead of collapsing AS into phenotype categories, may be the most precise approach for utilizing CYP2D6 pharmacogenomics in clinical practice.

Tri-Allelic Haplotypes Determine and Differentiate Functionally Normal Allele CYP2D6*2 and Impaired Allele CYP2D6*41

CYP2D6 metabolizes 20-25% of all clinically used drugs and its complex genetic polymorphism is a major determinant of drug safety and efficacy. We investigated the basis for the functional difference between the two common alleles *2 (g.2851C>T + g.4181G>C, normal function) and *41 (additional intronic g.2989G>A, reduced function). A recently reported far-distant enhancer polymorphism rs5758550A/G linked to *2 has been suggested to play a decisive role. Genotyping of two white cohorts confirmed strong linkage of rs5758550G to *2, whereas no influence was found on metabolic ratio of sparteine or hepatic expression. Genomic plasmid constructs carrying individual variants or combinations thereof were expressed in COS1 and Huh7 cells. Both g.2851C>T(R296C) and g.2989G>A reduced enzyme activity and protein levels similarly by ~ 50-65% compared to reference (*1), whereas the double variant had only ~ 20% activity. Although the unexpected loss of function caused by g.2851C>T was compensated by g.4181G>C (mimicking the EM-phenotype of *2), the additional loss of function due to intronic g.2989G>A in the triple variant was not compensated (mimicking the IM-phenotype of *41). We also confirmed increased erroneous splicing in carriers of g.2989G>A but not of g.2851C>T as a likely explanation for the impaired function of *41. In conclusion, our data demonstrate g.2989G>A as causal variant of impaired allele CYP2D6*41 whereas triple-haplotypes have to be considered to explain the functional difference between *2 and *41. These data are important for genotyping strategies and clinical implementation of CYP2D6 pharmacogenetics.

CYP2D6 Genotype-Based Dose Recommendations for Risperidone in Asian People

The aim of this study was to provide dose recommendations for risperidone in Asian people based on cytochrome P450 enzyme CYP2D6 genotype. First, we investigated the influence of CYP2D6 polymorphism on the pharmacokinetics of risperidone in Chinese patients with schizophrenia. Then, we performed a search for studies covering the relationship between pharmacokinetic parameters of risperidone and CYP2D6 genotype. Pooled pharmacokinetic parameters were meta-analyzed using a random-effects model. Lastly, we calculated the dose adjustment for risperidone based on CYP2D6 genotype for white and Asian people. Significant differences between the extensive metabolizer and intermediate metabolizer groups were observed for dose-adjusted risperidone level, 9-hydroxyrisperidone level, and risperidone/9-hydroxyrisperidone ratio, but not for the total active moiety. Meta-analysis showed that significant differences were observed among the four phenotype groups, including steady state concentration, peak risperidone concentration, and the area under the curve, using the Kruskal-Wallis test. No differences were found in oral clearance. For risperidone, dose recommendations for poor and ultrarapid metabolizers of CYP2D6 for Asians were different compared to that for white people for poor metabolizers (dose adjustment around 45% for white people, while for Asians the risperidone dose should be reduced by 26%). For ultrarapid metabolizers, risperidone dose should be increased by about 33% for white people and 30% for Asians. This was a first attempt to apply pharmacogenetics to suggest dose-regimens for Asian people; further research to replicate and extend these findings is recommended.

Noncoding SNPs associated with increased GDF15 levels located in a metformin-activated enhancer region upstream of GDF15

Aim: GDF15 levels are a biomarker for metformin use. We performed the functional annotation of noncoding genome-wide association study (GWAS) SNPs for GDF15 levels and the Genotype-Tissue Expression (GTEx)-expression quantitative trait loci (eQTLs) for GDF15 expression within metformin-activated enhancers around GDF15. Materials & methods: These enhancers were identified using chromatin immunoprecipitation followed by sequencing data for active (H3K27ac) and silenced (H3K27me3) histone marks on human hepatocytes treated with metformin, Encyclopedia of DNA Elements data and cis-regulatory elements assignment tools. Results: The GWAS lead SNP rs888663, the SNP rs62122429 associated with GDF15 levels in the Outcome Reduction with Initial Glargine Intervention trial, and the GTEx-expression quantitative trait locus rs4808791 for GDF15 expression in whole blood are located in a metformin-activated enhancer upstream of GDF15 and tightly linked in Europeans and East Asians. Conclusion: Noncoding variation within a metformin-activated enhancer may increase GDF15 expression and help to predict GDF15 levels.

Long-Distance Phasing of a Tentative "Enhancer" Single-Nucleotide Polymorphism With CYP2D6 Star Allele Definitions

BACKGROUND

The CYP2D6 gene locus has been extensively studied over decades, yet a portion of variability in CYP2D6 activity cannot be explained by known sequence variations within the gene, copy number variation, or structural rearrangements. It was proposed that rs5758550, located 116 kb downstream of the CYP2D6 gene locus, increases gene expression and thus contributes to variability in CYP2D6 activity. This finding has, however, not been validated. The purpose of the study was to address a major technological barrier, i.e., experimentally linking rs5758550, also referred to as the "enhancer" single-nucleotide polymorphism (SNP), to CYP2D6 haplotypes >100 kb away. To overcome this challenge is essential to ultimately determine the contribution of the "enhancer" SNP to interindividual variability in CYP2D6 activity.

METHODS

A large ethnically mixed population sample (n=3,162) was computationally phased to determine linkage between the "enhancer" SNP and CYP2D6 haplotypes (or star alleles). To experimentally validate predicted linkages, DropPhase2D6, a digital droplet PCR (ddPCR)-based method was developed. 10X Genomics Linked-Reads were utilized as a proof of concept.

RESULTS

Phasing predicted that the "enhancer" SNP can occur on numerous CYP2D6 haplotypes including CYP2D6*1, *2, *5, and *41 and suggested that linkage is incomplete, i.e., a portion of these alleles do not have the "enhancer" SNP. Phasing also revealed differences among the European and African ancestry data sets regarding the proportion of alleles with and without the "enhancer" SNP. DropPhase2D6 was utilized to confirm or refute the predicted "enhancer" SNP location for individual samples, e.g., of n=3 samples genotyped as *1/*41, rs5758550 was on the *41 allele of two samples and on the *1 allele of one sample. Our findings highlight that the location of the "enhancer" SNP must not be assigned by "default." Furthermore, linkage between the "enhancer" SNP and CYP2D6 star allele haplotypes was confirmed with 10X Genomics technology.

CONCLUSIONS

Since the "enhancer" SNP can be present on a portion of normal, decreased, or no function alleles, the phase of the "enhancer" SNP must be considered when investigating the impact of the "enhancer" SNP on CYP2D6 activity.

Cis-acting regulatory elements regulating CYP3A4 transcription in human liver

The CYP3A4 enzyme is the most abundant drug-metabolizing enzyme in the liver, metabolizing ~50% of commonly used medications. CYP3A4 displays large interperson variability in expression and enzyme activity with unknown causes. This study aims to identify cis-acting regulatory elements controlling the transcription of CYP3A4, using chromatin conformation capture (4C and 3C assays), chromatin immunoprecipitation followed by quantitative PCR (ChIP-qPCR), clustered regularly interspaced short palindromic repeats (CRISPR)-mediated deletions of genomic regions and reporter gene assays in primary culture human hepatocytes and hepatic cell lines. 4C assays identified four regions (R1-R4) interacting with the CYP3A4 promoter, one of which overlaps with the previously identified upstream enhancers CLEM4/XREM (R2) while the other three are novel. ChIP-qPCR, reporter gene assays and CRISPR-mediated deletion experiments indicate regulatory roles for both R2 and R4. Interestingly, the deletion of R4 increased CYP3A4 while decreasing CYP3A43 expression, possibly due to competitive domain-domain interactions within the CYP3A cluster, supported by deletion of R4 increasing interaction between the CYP3A4 promoter and R2. We also identified a single nucleotide polymorphism rs62471956 within R4, with the variant allele A having increased transcriptional activity in a reporter gene assay. The rs62471956 A allele is associated with higher CYP3A43 expression and lower CYP3A4 expression in a cohort of 136 liver samples, further supporting the opposing effects of R4 on CYP3A4 and CYP3A43. rs62471956 is in complete linkage disequilibrium with CYP3A4*22, potentially contributing to reduced expression of CYP3A4*22. These results validate previously identified enhancers (CLEM4 and XREM) of CYP3A4 and demonstrate additional regulatory mechanisms underlying CYP3A4 transcriptional control via competitive domain-domain interactions within the CYP3A cluster.

CYP2D6 haplotypes with enhancer single-nucleotide polymorphism rs5758550 and rs16947 (*2 allele): implications for CYP2D6 genotyping panels

INTRODUCTION

CYP2D6 metabolizes ∼25% of all clinically used drugs, with numerous genetic polymorphisms affecting enzyme activity and drug response. Clinical utility of current CYP2D6 genotyping is partially compromised the unresolved complex haplotype structure of the CYP2D6 locus. We have identified a distal enhancer single-nucleotide polymorphism rs5758550 that robustly increases CYP2D6 expression, whereas rs16947 (CYP2D6*2), previously considered inert, reduces correct mRNA splicing and expression, thereby affecting presumed activity of other alleles on the *2 haplotype.

OBJECTIVE

This study aims to determine the structure and frequency of haplotypes containing either rs5758550 or rs16947, or both, together with other relevant CYP2D6 alleles, assigning predictive enzyme activity scores to each, and addressing ambiguities in estimating diplotypes in different populations.

METHODS

The structure and frequency of haplotypes containing rs5758550 and/or rs16947 in different populations were determined by using phased genotype data from 'The 1000 Genomes Project'. The assigned haplotype-phenotype relationship was tested by associating assigned CYP2D6 activity score with CYP2D6 enzyme activity in a cohort of 122 human liver microsomes.

RESULTS

Addition of enhancer single-nucleotide polymorphism rs5758550 and *2 to a CYP2D6 panel improves prediction of CYP2D6 activity. Moreover, the haplotype containing rs5758550 and rs16947 predict extensive CYP2D6 activity more accurately than CYP2D6*2A, a surrogate marker for extensive activity.

CONCLUSION

With further studies, the results support possible incorporation of rs5758550 and rs16947 into CYP2D6 biomarker panels for more accurate prediction of CYP2D6 metabolizer status.

PharmVar GeneFocus: CYP2D6

The Pharmacogene Variation Consortium (PharmVar) provides nomenclature for the highly polymorphic human CYP2D6 gene locus. CYP2D6 genetic variation impacts the metabolism of numerous drugs and, thus, can impact drug efficacy and safety. This GeneFocus provides a comprehensive overview and summary of CYP2D6 genetic variation and describes how the information provided by PharmVar is utilized by the Pharmacogenomics Knowledgebase (PharmGKB) and the Clinical Pharmacogenetics Implementation Consortium (CPIC).

Interrogation of CYP2D6 Structural Variant Alleles Improves the Correlation Between CYP2D6 Genotype and CYP2D6-Mediated Metabolic Activity

The cytochrome P450 2D6 (CYP2D6) gene locus is challenging to accurately genotype due to numerous single nucleotide variants and complex structural variation. Our goal was to determine whether the CYP2D6 genotype‐phenotype correlation is improved when diplotype assignments incorporate structural variation, identified by the bioinformatics tool Stargazer, with next‐generation sequencing data. Using CYP2D6 activity measured with substrates dextromethorphan and metoprolol, activity score explained 40% and 34% of variability in metabolite formation rates, respectively, when diplotype calls incorporated structural variation, increasing from 36% and 31%, respectively, when diplotypes did not incorporate structural variation. We also investigated whether the revised Clinical Pharmacogenetics Implementation Consortium (CPIC) recommendations for translating genotype to phenotype improve CYP2D6 activity predictions over the current system. Although the revised recommendations do not improve the correlation between activity score and CYP2D6 activity, perhaps because of low frequency of the CYP2D6*10 allele, the correlation with metabolizer phenotype group was significantly improved for both substrates. We also measured the function of seven rare coding variants: one (A449D) exhibited decreased (44%) and another (R474Q) increased (127%) activity compared with reference CYP2D6.1 protein. Allele‐specific analysis found that A449D is part of a novel CYP2D6*4 suballele, CYP2D6*4.028. The novel haplotype containing R474Q was designated CYP2D6*138 by PharmVar; another novel haplotype containing R365H was designated CYP2D6*139. Accuracy of CYP2D6 phenotype prediction is improved when the CYP2D6 gene locus is interrogated using next‐generation sequencing coupled with structural variation analysis. Additionally, revised CPIC genotype to phenotype translation recommendations provides an improvement in assigning CYP2D6 activity.

Ligand-Free Estrogen Receptor α (ESR1) as Master Regulator for the Expression of CYP3A4 and Other Cytochrome P450 Enzymes in the Human Liver

Cytochrome P450 3A4 isoform (CYP3A4) transcription is controlled by hepatic transcription factors (TFs), but how TFs dynamically interact remains uncertain. We hypothesize that several TFs form a regulatory network with nonlinear, dynamic, and hierarchical interactions. To resolve complex interactions, we have applied a computational approach for estimating Sobol's sensitivity indices (SSI) under generalized linear models to existing liver RNA expression microarray data (GSE9588) and RNA-seq data from genotype-tissue expression (GTEx), generating robust importance ranking of TF effects and interactions. The SSI-based analysis identified TFs and interacting TF pairs, triplets, and quadruplets involved in CYP3A4 expression. In addition to known CYP3A4 TFs, estrogen receptor α (ESR1) emerges as key TF with the strongest main effect and as the most frequently included TF interacting partner. Model predictions were validated using small interfering RNA (siRNA)/short hairpin RNA (shRNA) gene knockdown and clustered regularly interspaced short palindromic repeats (CRISPR)-mediated transcriptional activation of ESR1 in biliary epithelial Huh7 cells and human hepatocytes in the absence of estrogen. Moreover, ESR1 and known CYP3A4 TFs mutually regulate each other. Detectable in both male and female hepatocytes without added estrogen, the results demonstrate a role for unliganded ESR1 in CYP3A4 expression consistent with unliganded ESR1 signaling reported in other cell types. Added estrogen further enhances ESR1 effects. We propose a hierarchical regulatory network for CYP3A4 expression directed by ESR1 through self-regulation, cross regulation, and TF-TF interactions. We also demonstrate that ESR1 regulates the expression of other P450 enzymes, suggesting broad influence of ESR1 on xenobiotics metabolism in human liver. Further studies are required to understand the mechanisms underlying role of ESR1 in P450 regulation. SIGNIFICANCE STATEMENT: This study focuses on identifying key transcription factors and regulatory networks for CYP3A4, the main drug metabolizing enzymes in liver. We applied a new computational approach (Sobol's sensitivity analysis) to existing hepatic gene expression data to determine the role of transcription factors in regulating CYP3A4 expression, and used molecular genetics methods (siRNA/shRNA gene knockdown and CRISPR-mediated transcriptional activation) to test these interactions in life cells. This approach reveals a robust network of TFs, including their putative interactions and the relative impact of each interaction. We find that ESR1 serves as a key transcription factor function in regulating CYP3A4, and it appears to be acting at least in part in a ligand-free fashion.

Non-CYP2D6 Variants Selected by a GWAS Improve the Prediction of Impaired Tamoxifen Metabolism in Patients with Breast Cancer

A certain minimum plasma concentration of (Z)-endoxifen is presumably required for breast cancer patients to benefit from tamoxifen therapy. In this study, we searched for DNA variants that could aid in the prediction of risk for insufficient (Z)-endoxifen exposure. A metabolic ratio (MR) corresponding to the (Z)-endoxifen efficacy threshold level was adopted as a cutoff value for a genome-wide association study comprised of 287 breast cancer patients. Multivariate regression was used to preselect variables exhibiting an independent impact on the MR and develop models to predict below-threshold MR values. In total, 15 single-nucleotide polymorphisms (SNPs) were significantly associated with below-threshold MR values. The strongest association was with rs8138080 (WBP2NL). Two alternative models for MR prediction were developed. The predictive accuracy of Model 1, including rs7245, rs6950784, rs1320308, and the CYP2D6 genotype, was considerably higher than that of the CYP2D6 genotype alone (AUC 0.879 vs 0.758). Model 2, which was developed using the same three SNPs as for Model 1 plus rs8138080, appeared as an interesting alternative to the full CYP2D6 genotype testing. In conclusion, the four novel SNPs, tested alone or in combination with the CYP2D6 genotype, improved the prediction of impaired tamoxifen-to-endoxifen metabolism, potentially allowing for treatment optimization.

Assessment of CYP2C9, CYP2C19, and CYP2D6 Polymorphisms in Allergic Patients with Chemical Sensitivity

BACKGROUND

Self-reported chemical sensitivity (SCS) is characterized by adverse effects due to exposure to low levels of chemical substances. The clinical manifestations of SCS are similar to the allergy, and a high percentage of individuals with both diseases have been found. Various genes, especially genes of importance to the metabolism of xenobiotic compounds, have been associated with SCS.

OBJECTIVES

The purpose of this study was to investigate whether allergic individuals with chemical sensitivity differed from allergic patients without chemical sensitivity with regard to the distribution of genotype and phenotype of CYP2C9, CYP2C19, and CYP2D6 polymorphisms.

METHODS

A total of 180 patients were enrolled for this study. A questionnaire was employed to collect information on individual chemical sensitivity, while the Skin prick test and the PATCH test were used to verify the presence of an allergic condition against inhalants or contact allergens, respectively. For the evaluation of the CYP2C9, CYP2C19, and CYP2D6 polymorphisms, we used a strategy based on the amplification of the entire gene coupled to direct genomic DNA sequencing analysis.

RESULTS

Overall, a total of 15 different CYP2C9, CYP2C19, and CYP2D6 haplotypes were identified in our population. If the 5 CYP2C9 and the 2 CYP2C19 identified alleles correspond to the previously described ones, 4 of the 8 CYP2D6 haplotypes, detected in the study group, present new SNPs combinations. These new suballeles were categorized as CYP2D6*2M Sa-lento Variant 1, CYP2D6*35B Salento Variant 2, CYP2D6*41 Salento Variant 3, and CYP2D6*4P Salento Variant 4 due to the presence of the key SNPs 2,850 C>T, 31G>A, 2,988 G>A, and 1,846 G>A, respectively. When the allergic individuals are divided into 2 groups according to their SCS score, we observed that the distribution of the CYP2D6 phenotypes was significantly different between the 2 groups.

CONCLUSIONS

Our idea is that the application of the questionnaire that we have adopted has enabled us to diagnose a degree of chemical sensitivity, which results as comorbid of the allergic disease and in which a condition of poor or intermediate metabolizes for the detrimental CYP2D6 alleles, could represent a discriminant between the chemical sensitivity and the health state.

CYP2D6 Protein Level Is the Major Contributor to Interindividual Variability in CYP2D6-Mediated Drug Metabolism in Healthy Human Liver Tissue

CYP2D6 genetic polymorphisms are considered a major contributor to the large interindividual variability in CYP2D6-mediated drug metabolism, but fail to explain a significant portion of the variability. The aim of this study was to assess the ability of the CYP2D6 activity score (AS) estimated from CYP2D6 genotype to predict CYP2D6 expression and enzyme activity. The CYP2D6 gene region was sequenced in 115 healthy human liver tissue samples to determine their CYP2D6 AS. Additionally, CYP2D6 enzyme activity, protein, and mRNA levels were estimated. CYP2D6 AS explained 23% of the interindividual variability in CYP2D6 activity, but only 7.5% in tissues assigned AS 1-2. The CYP2D6 protein level was found to be the major determinant of CYP2D6 activity, explaining 59% of variability. These findings suggest that while CYP2D6 AS is a good predictor of poor metabolizer phenotype, additional nongenetic factors may govern the rate of CYP2D6-mediated metabolism in those without the poor metabolizer phenotype.

Interactions Between Regulatory Variants in CYP7A1 (Cholesterol 7α-Hydroxylase) Promoter and Enhancer Regions Regulate CYP7A1 Expression

BACKGROUND

CYP7A1 (cholesterol 7α-hydroxylase) catalyzes the rate-limiting step in bile acid biosynthesis from cholesterol-a main pathway for cholesterol removal from the body. CYP7A1 single-nucleotide polymorphisms (SNPs) are associated with total cholesterol and LDL (low-density lipoprotein) levels, risk of cardiovascular diseases, and other phenotypes; however, results are inconsistent, and causative variants remain uncertain, except for a frequent promoter SNP (rs3808607).

METHODS

We used chromatin conformation capture (4C assay), chromatin immunoprecipitation qPCR assay in hepatocytes, and CRISPR (clustered regularly interspaced short palindromic repeats)-mediated genome editing in hepatocellular carcinoma cell line cells to identify regulatory regions for CYP7A1. We then screened for SNPs located in regulatory regions, testing effects on reporter gene assays and on hepatic CYP7A1 expression by measuring allelic mRNA expression imbalance.

RESULTS

4C assays showed several regions interacting with CYP7A1 promoter. CRISPR-mediated genome editing in hepatocellular carcinoma cell line cells revealed a novel CYP7A1 enhancer and a repressor region, located >10 kb downstream of the CYP7A1 promoter. SNP screening with an allelic mRNA expression imbalance in human livers and reporter gene assays identified a frequent functional SNP (rs9297994) located in the downstream CYP7A1 enhancer region. SNP rs9297994 is in high linkage disequilibrium with promoter SNP rs3808607 but has opposite effects on CYP7A1 mRNA expression. Their combined effects using a 2-SNP model robustly associate with hepatic CYP7A1 mRNA expression, ranging >2 orders of magnitude. Moreover, only the 2-SNP model, but not each SNP alone, is significantly associated with LDL levels, risk of coronary artery disease, statin response, and diabetes mellitus in several clinical cohorts, including CATHGEN (Catheterization Genetics) and Framingham.

CONCLUSIONS

Two interacting regulatory SNPs modulate CYP7A1 expression and are associated with risk of coronary artery disease and diabetes mellitus.

CYP2D6 genotype analysis of a Thai population: platform comparison

The highly polymorphic CYP2D6 gene locus leads to a wide range of enzyme activity. Since there are limited data for Thai, the major aim was to investigate CYP2D6 genetic variation in a large Thai population (n = 920). CYP2D6 genotyping was performed using four different platforms. Genotype call rates of the Luminex xTAG® and AmpliChip CYP450 test were 96.5% and 87.4%, respectively. Based on Luminex xTAG® data, the most common alleles and genotypes were *1 0 (49.6%), *1 (24.6%), *2 (10.8%), *5 (6.7%), *41 (6.5%) and *1/*10 (23.9%), *10/*10 (21.5%), *2/*10 (9.4%), *5/*10 (6.9%), *10/*41 (5.7%), respectively. Challenges and limitations of the platforms evaluated are discussed. These data add to our knowledge regarding interethnic variability in CYP2D6 activity and contribute to improving drug therapy in the Thai.

Ten Years' Experience with the CYP2D6 Activity Score: A Perspective on Future Investigations to Improve Clinical Predictions for Precision Therapeutics

The seminal paper on the CYP2D6 Activity Score (AS) was first published ten years ago and, since its introduction in 2008, it has been widely accepted in the field of pharmacogenetics. This scoring system facilitates the translation of highly complex CYP2D6 diplotype data into a patient’s phenotype to guide drug therapy and is at the core of all CYP2D6 gene/drug pair guidelines issued by the Clinical Pharmacogenetics Implementation Consortium (CPIC). The AS, however, only explains a portion of the variability observed among individuals and ethnicities. In this review, we provide an overview of sources in addition to CYP2D6 genotype that contribute to the variability in CYP2D6-mediated drug metabolism and discuss other factors, genetic and non-genetic, that likely contribute to the observed variability in CYP2D6 enzymatic activity.

Frequency of CYP2D6 Alleles Including Structural Variants in the United States

The CYP2D6 gene encodes an enzyme important in the metabolism of many commonly used medications. Variation in CYP2D6 is associated with inter-individual differences in medication response, and genetic testing is used to optimize medication therapy. This report describes a retrospective study of CYP2D6 allele frequencies in a large population of 104,509 de-identified patient samples across all regions of the United States (US). Thirty-seven unique CYP2D6 alleles including structural variants were identified. A majority of these alleles had frequencies which matched published frequency data from smaller studies, while eight had no previously published frequencies. Importantly, CYP2D6 structural variants were observed in 13.1% of individuals and accounted for 7% of the total variants observed. The majority of structural variants detected (73%) were decreased-function or no-function alleles. As such, structural variants were found in approximately one-third (30%) of CYP2D6 poor metabolizers in this study. This is the first CYP2D6 study to evaluate, with a consistent methodology, both structural variants and single copy alleles in a large US population, and the results suggest that structural variants have a substantial impact on CYP2D6 function.

Impact of CYP2D6 on venlafaxine metabolism in Trinidadian patients with major depressive disorder

AIM

This study aimed to assess the impact of CYP2D6 and CYP2C19 variation on venlafaxine (VEN) at steady state in patients from Trinidad and Tobago of Indian and African descent with major depressive disorder.

PATIENTS & METHODS

Patients were phenotyped with dextromethorphan, genotyped for CYP2D6 and CYP2C19, and metabolic ratios for VEN obtained at 2-week intervals.

RESULTS

Of 61 patients, 55 were genotyped and phenotyped and 47 completed 8 weeks of VEN treatment. The majority of patients had metabolic ratios for VEN that were consistent with those for dextromethorphan and genotype-predicted phenotype using activity scores. One subject presented with a novel no-function allele, CYP2D6*99. No correlations were observed with CYP2C19 genotype.

CONCLUSION

CYP2D6 genotype analysis provides valuable information to individualize drug therapy with VEN.

Pharmacogenetic Variation in Over 100 Genes in Patients Receiving Acenocumarol

Coumarins are widely prescribed worldwide, and in Mexico acenocumarol is the preferred form. It is well known that despite its efficacy, coumarins show a high variability for dose requirements. We investigated the pharmacogenetic variation of 110 genes in patients receiving acenocumarol using a targeted NGS approach. We report relevant population differentiation for variants on CYP2C8, CYP2C19, CYP4F11, CYP4F2, PROS, and GGCX, VKORC1, CYP2C18, NQO1. A higher proportion of novel-to-known variants for 10 genes was identified on 41 core pharmacogenomics genes related to the PK (29), PD (3), of coumarins, and coagulation proteins (9) including, CYP1A1, CYP3A4, CYP3A5, and F8, and a low proportion of novel-to-known variants on CYP2E1, VKORC1, and SULT1A1/2. Using a Bayesian approach, we identified variants influencing acenocumarol dosing on, VKORC1 (2), SULT1A1 (1), and CYP2D8P (1) explaining 40–55% of dose variability. A collection of pharmacogenetic variation on 110 genes related to the PK/PD of coumarins is also presented. Our results offer an initial insight into the use of a targeted NGS approach in the pharmacogenomics of coumarins in Mexican Mestizos.

Relationship between DNA Methylation in the 5' CpG Island of the SLC47A1 (Multidrug and Toxin Extrusion Protein MATE1) Gene and Interindividual Variability in MATE1 Expression in the Human Liver

Multidrug and toxin extrusion protein 1 (MATE1), which is encoded by solute carrier 47A1 (SLC47A1), mediates the excretion of organic cations into bile and urine. Some genetic variants in human MATE1 altered its transport function in in vitro experiments; however, differences in the pharmacokinetics of substrate drugs cannot be explained by genetic variations in humans. In this study, we investigated whether DNA methylation was involved in interindividual variability in MATE1 expression in the human liver. Approximately 20-fold interindividual variability in MATE1 mRNA expression levels was observed in liver samples and mRNA expression levels negatively correlated with methylation levels of the CpG island in the 27 kb upstream of SLC47A1 DNA demethylation by treatment with 5-aza-2'-deoxycytidine increased MATE1 mRNA expression in MATE1-negative cell lines. The luciferase reporter assay showed that the CpG island increased the transcriptional activity of the SLC47A1 promoter. MATE1 mRNA expression levels were significantly lower in CpG island knockout HepG2 cells than in control cells. These results suggest that the 5' CpG island of SLC47A1 acts as an enhancer for SLC47A1, and DNA methylation in the CpG island plays an important role in interindividual differences in hepatic MATE1 expression.

Improved Prediction of Endoxifen Metabolism by CYP2D6 Genotype in Breast Cancer Patients Treated with Tamoxifen

Purpose: Prediction of impaired tamoxifen (TAM) to endoxifen metabolism may be relevant to improve breast cancer treatment, e.g., via TAM dose increase. The polymorphic cytochrome P450 2D6 (CYP2D6) strongly determines an individual's capacity for endoxifen formation, however, CYP2D6 phenotype assignments inferred from genotype widely differ between studies. Thus, we modeled plasma endoxifen predictability depending on variable CYP2D6 genotype groupings. Methods: CYP2D6 diplotype and metabolite plasma concentrations were assessed in 908 pre- and post-menopausal estrogen receptor (ER)-positive, TAM treated early breast cancer patients of Caucasian (N = 678), Middle-Eastern Arab (N = 77), and Asian (N = 153) origin. Robust coefficients of determination (R2) were estimated for endoxifen (E) or metabolic ratio endoxifen/desmethyl-TAM (E/DMT) as dependent and different CYP2D6 phenotype assignments as independent variables. Allele activity scores (ASs) were modified with respect to a reduced ∗10 allele activity. Predictability of endoxifen plasma concentrations above the clinical threshold of 5.9 ng/mL was investigated by receiver operating characteristic (ROC) analysis. Results: CYP2D6 diplotypes (N = 898) were strongly associated with E and E/DMT independent of age (P < 10-15). Across all ethnicities, 68-82% inter-patient variability of E/DMT was explained by CYP2D6 diplotype, while plasma endoxifen was predictable by 39-58%. The previously used codeine specific phenotype classification showed worse prediction for both endpoints particularly in Asians (median R2< 20%; P < 10-9). Downgrading of ∗10 activity slightly improved the explanatory value of metabolizer phenotype (P < 0.002). Endoxifen plasma concentrations above the clinical threshold of 5.9 ng/mL were achieved in 82.3% of patients and were predictable (96% sensitivity, 57% specificity) by CYP2D6 diplotypes with AS > 0.5, i.e., omitting PM/PM and PM/IM patients. Conclusion: The CYP2D6 explanatory power for active drug level assessment is maximized by TAM-specific phenotype assignments while a genotype cutoff that separates PM/PM and PM/IM from the remaining patients may improve clinical benefit via increased endoxifen concentrations.

The effect of rs5758550 on CYP2D6*2 phenotype and formation of endoxifen in breast cancer patients using tamoxifen

Aim: CYP2D6*2 is considered fully active, but it has been suggested that it only happens in the presence of rs5758550. This study aims to elucidate the impact of this enhancer. Materials & methods: DNA and blood samples from women enrolled in the CYPTAM study (NTR1509) were analyzed. Fourteen CYP2D6*2 carriers without the enhancer were reclassified. The relationship of CYP2D6 phenotypes and drug levels was studied. Results: After correction for the absence of the enhancer, the correlation between CYP2D6 phenotypes and endoxifen did not improve (R2: 0.290 vs 0.279). No difference was observed in mean concentrations between CYP2D6*2 individuals with and without the enhancer. Conclusion: The rs5758550 enhancer does not lead to improved prediction of endoxifen levels in breast cancer patients.

CRISPR/Cas9: at the cutting edge of hepatology

Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/Cas9 genome engineering has revolutionised biomedical science and we are standing on the cusp of medical transformation. The therapeutic potential of this technology is tremendous, however, its translation to the clinic will be challenging. In this article, we review recent progress using this genome editing technology and explore its potential uses in studying and treating diseases of the liver. We discuss the development of new research tools and animal models as well as potential clinical applications, strategies and challenges.

Sequencing the CYP2D6 gene: from variant allele discovery to clinical pharmacogenetic testing

CYP2D6 is one of the most studied enzymes in the field of pharmacogenetics. The CYP2D6 gene is highly polymorphic with over 100 catalogued star (*) alleles, and clinical CYP2D6 testing is increasingly accessible and supported by practice guidelines. However, the degree of variation at the CYP2D6 locus and homology with its pseudogenes make interrogating CYP2D6 by short-read sequencing challenging. Moreover, accurate prediction of CYP2D6 metabolizer status necessitates analysis of duplicated alleles when an increased copy number is detected. These challenges have recently been overcome by long-read CYP2D6 sequencing; however, such platforms are not widely available. This review highlights the genomic complexities of CYP2D6, current sequencing methods and the evolution of CYP2D6 from allele discovery to clinical pharmacogenetic testing.

Chronic Intermittent Hypoxia Causes Lipid Peroxidation and Altered Phase 1 Drug Metabolizing Enzymes in the Neonatal Rat Liver

Critically ill preterm neonates requiring oxygen therapy often experience frequent apneas with intermittent hypoxia (IH). IH-induced oxidative stress causes lipid peroxidation, which targets the liver and contributes to toxic drug reactions. We tested the hypothesis that incremental IH episodes induce oxidative damage in the neonatal liver and alter the expression of genes that regulate drug metabolism. Newborn rats were exposed to increasing IH episodes (12% O₂) during hyperoxia (50% O₂), or placed in room air (RA) until postnatal day 21 (P21) for recovery from IH (IHR). RA littermates served as controls, and pups exposed to 50% O₂ served as hyperoxia controls. Hepatic histopathology, biomarkers of oxidative stress and oxidative DNA damage, antioxidants, and expression of genes that regulate drug metabolism were assessed. Oxidative stress and DNA damage, evidenced by 8-isoprostaglandin F_2α (8-isoPGF_2α) and 8-hydroxy-2'-deoxyguanosine (8-OH-dG), respectively, increased as a function of IH episodes, and was associated with decreased superoxide dismutase (SOD) and increased catalase activities. Pathological changes including cellular swelling, steatosis, necrosis, and focal sinusoid congestion were seen in IH, but not in IHR. Similarly, IH was associated with upregulation of several genes involved in DNA repair, which were downregulated during IHR. Of the genes involved in drug metabolism, aldehyde dehydrogenases (involved in lipid peroxidation) and cytochrome P450 (CYP) genes of the 2C family (involved in oxidative stress) were robustly upregulated both in IH and in IHR. Hepatic oxidative stress and lipid peroxidation occurring in response to chronic IH have implications for preterm infants, and may explain, in part, the pharmacokinetic variations and drug toxicities in this vulnerable population.

Transcriptional Regulation of CYP2D6 Expression

CYP2D6-mediated drug metabolism exhibits large interindividual variability. Although genetic variations in the CYP2D6 gene are well known contributors to the variability, the sources of CYP2D6 variability in individuals of the same genotype remain unexplained. Accumulating data indicate that transcriptional regulation of CYP2D6 may account for part of CYP2D6 variability. Yet, our understanding of factors governing transcriptional regulation of CYP2D6 is limited. Recently, mechanistic studies of increased CYP2D6-mediated drug metabolism in pregnancy revealed two transcription factors, small heterodimer partner (SHP) and Krüppel-like factor 9, as a transcriptional repressor and an activator, respectively, of CYP2D6. Chemicals that increase SHP expression (e.g., retinoids and activators of farnesoid X receptor) were shown to downregulate CYP2D6 expression in the humanized mice as well as in human hepatocytes. This review summarizes the series of studies on the transcriptional regulation of CYP2D6 expression, potentially providing a basis to better understand the large interindividual variability in CYP2D6-mediated drug metabolism.

Prediction of CYP2D6 phenotype from genotype across world populations

Purpose:

Owing to its highly polymorphic nature and major contribution to the metabolism and bioactivation of numerous clinically used drugs, CYP2D6 is one of the most extensively studied drug-metabolizing enzymes and pharmacogenes. CYP2D6 alleles confer no, decreased, normal, or increased activity and cause a wide range of activity among individuals and between populations. However, there is no standard approach to translate diplotypes into predicted phenotype.

Methods:

We exploited CYP2D6 allele-frequency data that have been compiled for Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines (>60,000 subjects, 173 reports) in order to estimate genotype-predicted phenotype status across major world populations based on activity score (AS) assignments.

Results:

Allele frequencies vary considerably across the major ethnic groups predicting poor metabolizer status (AS = 0) between 0.4 and 5.4% across world populations. The prevalence of genotypic intermediate (AS = 0.5) and normal (AS = 1, 1.5, or 2) metabolizers ranges between 0.4 and 11% and between 67 and 90%, respectively. Finally, 1 to 21% of subjects (AS >2) are predicted to have ultrarapid metabolizer status.

Conclusions:

This comprehensive study summarizes allele frequencies, diplotypes, and predicted phenotype across major populations, providing a rich data resource for clinicians and researchers. Challenges of phenotype prediction from genotype data are highlighted and discussed.

Genet Med19 1, 69–76.

Characterization of Atomoxetine Biotransformation and Implications for Development of PBPK Models for Dose Individualization in Children

Atomoxetine (ATX) is a second-line nonstimulant medication used to control symptoms of attention deficit hyperactivity disorder (ADHD). Inconsistent therapeutic efficacy has been reported with ATX, which may be related to variable CYP2D6-mediated drug clearance. We characterized ATX metabolism in a panel of human liver samples as a basis for a bottom-up PBPK model to aid in ATX exposure prediction and control. Km, Vmax, and Clint values in pooled human liver microsomes (HLMs) were 2.4 µM, 479 pmol/min/mg protein, and 202 µl/min/mg protein, respectively. Mean population values of kinetic parameters are not adequate to describe variability in a population, given that Km, Vmax, and Clint values from single-donor HLMs ranged from 0.93 to 79.2 µM, 20.0 to 1600 pmol/min/mg protein, and 0.3 to 936 µl/min/mg protein. All kinetic parameters were calculated from 4-hydroxyatomoxetine (4-OH-ATX) formation. CYP2E1 and CYP3A contributed to 4-OH-ATX formation in livers with CYP2D6 intermediate and poor metabolizer status. In HLMs with lower CYP2D6 activity levels, 2-hydroxymethylatomoxetine (2-CH2OH-ATX) formation became a more predominant pathway of metabolism, which appeared to be catalyzed by CYP2B6. ATX biotransformation at clinically relevant plasma concentrations was characterized in a panel of pediatric HLM (n = 116) samples by evaluating primary metabolites. Competing pathways of ATX metabolism [N-desmethylatomoxetine (NDM-ATX) and 2-CH2OH-ATX formation] had increasing importance in livers with lesser CYP2D6 activity, but, overall ATX clearance was still compromised. Modeling ATX exposure to individualize therapy would require comprehensive knowledge of factors that affect CYP2D6 activity as well as an understanding of competing pathways, particularly for individuals with lower CYP2D6 activity.

Practical interpretation of CYP2D6 haplotypes: Comparison and integration of automated and expert calling

We describe a population genetic approach to compare samples interpreted with expert calling (EC) versus automated calling (AC) for CYP2D6 haplotyping. The analysis represents 4812 haplotype calls based on signal data generated by the Luminex xMap analyzers from 2406 patients referred to a high-complexity molecular diagnostics laboratory for CYP450 testing. DNA was extracted from buccal swabs. We compared the results of expert calls (EC) and automated calls (AC) with regard to haplotype number and frequency. The ratio of EC to AC was 1:3. Haplotype frequencies from EC and AC samples were convergent across haplotypes, and their distribution was not statistically different between the groups. Most duplications required EC, as only expansions with homozygous or hemizygous haplotypes could be automatedly called. High-complexity laboratories can offer equivalent interpretation to automated calling for non-expanded CYP2D6 loci, and superior interpretation for duplications. We have validated scientific expert calling specified by scoring rules as standard operating procedure integrated with an automated calling algorithm. The integration of EC with AC is a practical strategy for CYP2D6 clinical haplotyping.

Single dose, CYP2D6 genotype-stratified pharmacokinetic study of atomoxetine in children with ADHD

The effect of CYP2D6 genotype on the dose-exposure relationship for atomoxetine has not been well characterized in children. Children 6-17 years of age diagnosed with attention-deficit hyperactivity disorder (ADHD) were stratified by CYP2D6 genotype into groups with 0 (poor metabolizers [PMs], n = 4), 0.5 (intermediate metabolizers [IMs], n = 3), one (extensive metabolizer [EM]1, n = 8) or two (EM2, n = 8) functional alleles and administered a single 0.5 mg/kg oral dose of atomoxetine (ATX). Plasma and urine samples were collected for 24 (IM, EM1, and EM2) or 72 hours (PMs). Dose-corrected ATX systemic exposure (area under the curve [AUC]0-∞ ) varied 29.6-fold across the study cohort, ranging from 4.4 ± 2.7 μM*h in EM2s to 5.8 ± 1.7 μM*h, 16.3 ± 2.9 μM*h, and 50.2 ± 7.3 μM*h in EM1s, IMs, and PMs, respectively (P < 0.0001). Simulated steady state profiles at the maximum US Food and Drug Administration (FDA)-recommended dose suggest that most patients are unlikely to attain adequate ATX exposures. These data support the need for individualized dosing strategies for more effective use of the medication.

Uncovering drug-responsive regulatory elements

Nucleotide changes in gene regulatory elements can have a major effect on interindividual differences in drug response. For example, by reviewing all published pharmacogenomic genome-wide association studies, we show here that 96.4% of the associated single nucleotide polymorphisms reside in noncoding regions. We discuss how sequencing technologies are improving our ability to identify drug response-associated regulatory elements genome-wide and to annotate nucleotide variants within them. We highlight specific examples of how nucleotide changes in these elements can affect drug response and illustrate the techniques used to find them and functionally characterize them. Finally, we also discuss challenges in the field of drug-responsive regulatory elements that need to be considered in order to translate these findings into the clinic.