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

Metabolic activity of CYP2C19 and CYP2D6 on antidepressant response from 13 clinical studies using genotype imputation: a meta-analysis

Cytochrome P450 enzymes including CYP2C19 and CYP2D6 are important for antidepressant metabolism and polymorphisms of these genes have been determined to predict metabolite levels. Nonetheless, more evidence is needed to understand the impact of genetic variations on antidepressant response. In this study, individual clinical and genetic data from 13 studies of European and East Asian ancestry populations were collected. The antidepressant response was clinically assessed as remission and percentage improvement. Imputed genotype was used to translate genetic polymorphisms to metabolic phenotypes (poor, intermediate, normal, and rapid+ultrarapid) of CYP2C19 and CYP2D6. CYP2D6 structural variants cannot be imputed from genotype data, limiting the determination of metabolic phenotypes, and precluding testing for association with response. The association of CYP2C19 metabolic phenotypes with treatment response was examined using normal metabolizers as the reference. Among 5843 depression patients, a higher remission rate was found in CYP2C19 poor metabolizers compared to normal metabolizers at nominal significance but did not survive after multiple testing correction (OR = 1.46, 95% CI [1.03, 2.06], p = 0.033, heterogeneity I2 = 0%, subgroup difference p = 0.72). No metabolic phenotype was associated with percentage improvement from baseline. After stratifying by antidepressants primarily metabolized by CYP2C19, no association was found between metabolic phenotypes and antidepressant response. Metabolic phenotypes showed differences in frequency, but not effect, between European- and East Asian-ancestry studies. In conclusion, metabolic phenotypes imputed from genetic variants using genotype were not associated with antidepressant response. CYP2C19 poor metabolizers could potentially contribute to antidepressant efficacy with more evidence needed. Sequencing and targeted pharmacogenetic testing, alongside information on side effects, antidepressant dosage, depression measures, and diverse ancestry studies, would more fully capture the influence of metabolic phenotypes.

Investigation of cannabidiol-induced cytotoxicity in human hepatic cells

Cannabidiol (CBD) is one of the primary cannabinoids present in extracts of the plant Cannabis sativa L. A CBD-based drug, Epidiolex, has been approved by the U.S. FDA for the treatment of seizures in childhood-onset epileptic disorders. Although CBD-associated liver toxicity has been reported in clinical studies, the underlying mechanisms remain unclear. In this study, we demonstrated that CBD causes cytotoxicity in primary human hepatocytes and hepatic HepG2 cells. A 24-h CBD treatment induced cell cycle disturbances, cellular apoptosis, and endoplasmic reticulum (ER) stress in HepG2 cells. A potent ER stress inhibitor, 4-phenylbutyrate, markedly attenuated CBD-induced apoptosis and cell death. Additionally, we investigated the role of cytochrome P450 (CYP)-mediated metabolism in CBD-induced cytotoxicity using HepG2 cell lines engineered to express 14 individual CYPs. We identified CYP2C9, 2C19, 2D6, 2C18, and 3A5 as participants in CBD metabolism. Notably, cells overexpressing CYP2C9, 2C19, and 2C18 produced 7-hydroxy-CBD, while cells overexpressing CYP2C9, 2C19, 2D6, and 2C18 generated 7-carboxy-CBD. Furthermore, CBD-induced cytotoxicity was significantly attenuated in the cells expressing CYP2D6. Taken together, these data suggest that cell cycle disturbances, apoptosis, and ER stress are associated with CBD-induced cytotoxicity, and CYP2D6-mediated metabolism plays a critical role in decreasing the cytotoxicity of CBD.

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.

Clinical Pharmacogenetics Implementation Consortium Guideline (CPIC) for CYP2D6, ADRB1, ADRB2, ADRA2C, GRK4, and GRK5 Genotypes and Beta-Blocker Therapy

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).

Ziprasidone population pharmacokinetics and co-medication effects in Chinese patients

Ziprasidone is widely used in the treatment of psychiatric disorders. Despite its prevalence, there is a notable lack of population pharmacokinetics (PPK) studies on ziprasidone in serum, both domestically and internationally. This study aimed to comprehensively investigate the various factors influencing the PPK characteristics of Ziprasidone, thereby providing a scientific basis for personalized treatment strategies in clinical settings. This is a retrospective study. A non-linear mixed-effects modeling method was used for data analysis, with the ziprasidone PPK model established using the Phoenix NLME 8.1 software. Model evaluation employed goodness-of-fit plots, visual predictive checks, and Bootstrap methods to ensure reliability and accuracy. To further validate the model's applicability, data from an additional 30 patients meeting the same inclusion criteria but not included in the final model were collected for external validation. Simulations were performed to explore the personalized dosage regimens. This retrospective analysis collected 547 drug concentration data points from 185 psychiatric disorder patients, along with related medical records. The data included detailed demographic information (such as age, gender, weight), dosing regimens, laboratory test results, and concomitant medication details. In the final model, Ka was fixed at 0.5 h-1 based on literature, and the population typical values for ziprasidone clearance (CL) and volume of distribution (V) were 18.74 L/h and 110.24 L, respectively. Co-administration of lorazepam and valproic acid significantly influenced the clearance of ziprasidone. Moreover, the model evaluation indicated good stability and predictive accuracy. A simple to use dosage regimen table was derived based on the results of simulations. This study successfully established and validated a PPK model for ziprasidone in Chinese patients with psychiatric disorders. The model provides a scientific reference for individualized dosing of ziprasidone and holds the potential to optimize treatment strategies, thereby enhancing therapeutic efficacy and safety.

Pharmacogenomic allele coverage of genome-wide genotyping arrays: a comparative analysis

The use of genome-wide genotyping arrays in pharmacogenomics (PGx) research and clinical implementation applications is increasing but it is unclear which arrays are best suited for these applications. Here, we conduct a comparative coverage analysis of PGx alleles included on genome-wide genotyping arrays, with an emphasis on alleles in genes with PGx-based prescribing guidelines. Genomic manifest files for seven arrays including the Axiom Precision Medicine Diversity Array (PMDA), Axiom PMDA Plus, Axiom PangenomiX, Axiom PangenomiX Plus, Infinium Global Screening Array, Infinium Global Diversity Array (GDA) and Infinium GDA with enhanced PGx (GDA-PGx) Array, were evaluated for coverage of 523 star alleles across 19 pharmacogenes included in prescribing guidelines developed by the Clinical Pharmacogenetic Implementation Consortium and Dutch Pharmacogenomics Working Group. Specific attention was given to coverage of the Association of Molecular Pathology's Tier 1 and Tier 2 allele sets for CYP2C9, CYP2C19, CYP2D6, CYP3A4, CYP3A5, NUDT15, TPMT and VKORC1 . Coverage of the examined PGx alleles was highest for the Infinium GDA-PGx (88%), Axiom PangenomiX Plus (77%), Axiom PangenomiX (72%) and Axiom PMDA Plus (70%). Three arrays (Infinium GDA-PGx, Axiom PangenomiX Plus and Axiom PMDA Plus) fully covered the Tier 1 alleles and the Axiom PangenomiX array provided full coverage of Tier 2 alleles. In conclusion, PGx allele coverage varied by gene and array. A superior array for all PGx applications was not identified. Future comparative analyses of genotype data produced by these arrays are needed to determine the robustness of the reported coverage estimates.

Dose adjustment of paroxetine based on CYP2D6 activity score inferred metabolizer status in Chinese Han patients with depressive or anxiety disorders: a prospective study and cross-ethnic meta-analysis

BACKGROUND

Understanding the impact of CYP2D6 metabolism on paroxetine, a widely used antidepressant, is essential for precision dosing.

METHODS

We conducted an 8-week, multi-center, single-drug, 2-week wash period prospective cohort study in 921 Chinese Han patients with depressive or anxiety disorders (ChiCTR2000038462). We performed CYP2D6 genotyping (single nucleotide variant and copy number variant) to derive the CYP2D6 activity score and evaluated paroxetine treatment outcomes including steady-state concentration, treatment efficacy, and adverse reaction. CYP2D6 metabolizer status was categorized into poor metabolizers (PMs), intermediate metabolizers (IMs), extensive metabolizers (EMs), and ultrarapid metabolizers (UMs). The influence of CYP2D6 metabolic phenotype on paroxetine treatment outcomes was examined using multiple regression analysis and cross-ethnic meta-analysis. The therapeutic reference range of paroxetine was estimated by receiver operating characteristic (ROC) analyses.

FINDINGS

After adjusting for demographic factors, the steady-state concentrations of paroxetine in PMs, IMs, and UMs were 2.50, 1.12, and 0.39 times that of EMs, with PM and UM effects being statistically significant (multiple linear regression, P = 0.03 and P = 0.04). Sex and ethnicity influenced the comparison between IMs and EMs. Moreover, poor efficacy of paroxetine was associated with UM, and a higher risk of developing adverse reactions was associated with lower CYP2D6 activity score. Lastly, cross-ethnic meta-analysis suggested dose adjustments for PMs, IMs, EMs, and UMs in the East Asian population to be 35%, 40%, 143%, and 241% of the manufacturer's recommended dose, and 62%, 68%, 131%, and 159% in the non-East Asian population.

INTERPRETATION

Our findings advocate for precision dosing based on the CYP2D6 metabolic phenotype, with sex and ethnicity being crucial considerations in this approach.

FUNDING

National Natural Science Foundation of China; Academy of Medical Sciences Research Unit.

Rationale and design for a pragmatic randomized trial to assess gene-based prescribing for SSRIs in the treatment of depression

Specific selective serotonin reuptake inhibitors (SSRIs) metabolism is strongly influenced by two pharmacogenes, CYP2D6 and CYP2C19. However, the effectiveness of prospectively using pharmacogenetic variants to select or dose SSRIs for depression is uncertain in routine clinical practice. The objective of this prospective, multicenter, pragmatic randomized controlled trial is to determine the effectiveness of genotype-guided selection and dosing of antidepressants on control of depression in participants who are 8 years or older with ≥3 months of depressive symptoms who require new or revised therapy. Those randomized to the intervention arm undergo pharmacogenetic testing at baseline and receive a pharmacy consult and/or automated clinical decision support intervention based on an actionable phenotype, while those randomized to the control arm have pharmacogenetic testing at the end of 6-months. In both groups, depression and drug tolerability outcomes are assessed at baseline, 1 month, 3 months (primary), and 6 months. The primary end point is defined by change in Patient-Reported Outcomes Measurement Information System (PROMIS) Depression score assessed at 3 months versus baseline. Secondary end points include change inpatient health questionnaire (PHQ-8) measure of depression severity, remission rates defined by PROMIS score < 16, medication adherence, and medication side effects. The primary analysis will compare the PROMIS score difference between trial arms among those with an actionable CYP2D6 or CYP2C19 genetic result or a CYP2D6 drug-drug interaction. The trial has completed accrual of 1461 participants, of which 562 were found to have an actionable phenotype to date, and follow-up will be complete in April of 2024.

Prevalence of CYP2D6 structural variation in large retrospective study

CYP2D6 is a highly polymorphic gene with clinically important structural variations. Commonly, only exon 9 is assayed on clinical pharmacogenomics panels, as it allows for accurate functional characterization even in the presence of a CYP2D6::CYP2D7 conversion. However, this method does not capture CYP2D7::CYP2D6 (CYP2D6*13) conversions, possibly leading to inaccurate phenotype assignment. The study's purpose was to determine the frequency of structural variations in CYP2D6 utilizing multiple copy number variation (CNV) assay locations to quantify the potential impact on clinical phenotype classification. A retrospective analysis was conducted of de-identified pharmacogenomics data submitted through the Translational Software, Inc. platform. Samples with CYP2D6 CNV data for exon 9 and at least one additional CNV location (5'UTR, exon 1, intron 2, exon 5 or intron 6) were included. CYP2D7::CYP2D6 and CYP2D6::CYP2D7 conversions were classified according to PharmVar nomenclature. The CYP2D6 copies were capped at four total copies to account for assay limitations in detecting more than four copies. A total of 106,474 samples were included for analysis. CYP2D7::CYP2D6 conversions were present in approximately 2.44% of samples, and 5.84% of samples had CYP2D6::CYP2D7 conversions. Many samples did not have a CYP2D7 conversion detected (91.5%; 97,462/106,474). A full gene deletion was detected in 0.15%, and 5.98% had a duplication or multiplication present. This retrospective study underscores the importance of testing more than one CNV site for CYP2D6 . Over 2% of patients were found to have a CYP2D7::CYP2D6 conversion. This translates into potentially misclassified phenotype classification and incongruent clinical recommendations.

Pharmacogenomic insights in psychiatric care: uncovering novel actionability, allele-specific CYP2D6 copy number variation, and phenoconversion in 15,000 patients

Pharmacogenomic testing has emerged as an aid in clinical decision making for psychiatric providers, but more data is needed regarding its utility in clinical practice and potential impact on patient care. In this cross-sectional study, we determined the real-world prevalence of pharmacogenomic actionability in patients receiving psychiatric care. Potential actionability was based on the prevalence of CYP2C19 and CYP2D6 phenotypes, including CYP2D6 allele-specific copy number variations (CNVs). Combined actionability additionally incorporated CYP2D6 phenoconversion and the novel CYP2C-TG haplotype in patients with available medication data. Across 15,000 patients receiving clinical pharmacogenomic testing, 65% had potentially actionable CYP2D6 and CYP2C19 phenotypes, and phenotype assignment was impacted by CYP2D6 allele-specific CNVs in 2% of all patients. Of 4114 patients with medication data, 42% had CYP2D6 phenoconversion from drug interactions and 20% carried a novel CYP2C haplotype potentially altering actionability. A total of 87% had some form of potential actionability from genetic findings and/or phenoconversion. Genetic variation detected via next-generation sequencing led to phenotype reassignment in 22% of individuals overall (2% in CYP2D6 and 20% in CYP2C19). Ultimately, pharmacogenomic testing using next-generation sequencing identified potential actionability in most patients receiving psychiatric care. Early pharmacogenomic testing may provide actionable insights to aid clinicians in drug prescribing to optimize psychiatric care.

Contradiction in Star-Allele Nomenclature of Pharmacogenes between Common Haplotypes and Rare Variants

The nomenclature of star alleles has been widely used in pharmacogenomics to enhance treatment outcomes, predict drug response variability, and reduce adverse reactions. However, the discovery of numerous rare functional variants through genome sequencing introduces complexities into the star-allele system. This study aimed to assess the nature and impact of the rapid discovery of numerous rare functional variants in the traditional haplotype-based star-allele system. We developed a new method to construct haplogroups, representing a common ancestry structure, by iteratively excluding rare and functional variants of the 25 representative pharmacogenes using the 2504 genomes from the 1000 Genomes Project. In total, 192 haplogroups and 288 star alleles were identified, with an average of 7.68 ± 4.2 cross-ethnic haplogroups per gene. Most of the haplogroups (70.8%, 136/192) were highly aligned with their corresponding classical star alleles (VI = 1.86 ± 0.78), exhibiting higher genetic diversity than the star alleles. Approximately 41.3% (N = 119) of the star alleles in the 2504 genomes did not belong to any of the haplogroups, and most of them (91.3%, 105/116) were determined by a single variant according to the allele-definition table provided by CPIC. These functional single variants had low allele frequency (MAF < 1%), high evolutionary conservation, and variant deleteriousness, which suggests significant negative selection. It is suggested that the traditional haplotype-based naming system for pharmacogenetic star alleles now needs to be adjusted by balancing both traditional haplotyping and newly emerging variant-sequencing approaches to reduce naming complexity.

A New Cloud-Native Tool for Pharmacogenetic Analysis

BACKGROUND

The advancement of next-generation sequencing (NGS) technologies provides opportunities for large-scale Pharmacogenetic (PGx) studies and pre-emptive PGx testing to cover a wide range of genotypes present in diverse populations. However, NGS-based PGx testing is limited by the lack of comprehensive computational tools to support genetic data analysis and clinical decisions.

METHODS

Bioinformatics utilities specialized for human genomics and the latest cloud-based technologies were used to develop a bioinformatics pipeline for analyzing the genomic sequence data and reporting PGx genotypes. A database was created and integrated in the pipeline for filtering the actionable PGx variants and clinical interpretations. Strict quality verification procedures were conducted on variant calls with the whole genome sequencing (WGS) dataset of the 1000 Genomes Project (G1K). The accuracy of PGx allele identification was validated using the WGS dataset of the Pharmacogenetics Reference Materials from the Centers for Disease Control and Prevention (CDC).

RESULTS

The newly created bioinformatics pipeline, Pgxtools, can analyze genomic sequence data, identify actionable variants in 13 PGx relevant genes, and generate reports annotated with specific interpretations and recommendations based on clinical practice guidelines. Verified with two independent methods, we have found that Pgxtools consistently identifies variants more accurately than the results in the G1K dataset on GRCh37 and GRCh38.

CONCLUSIONS

Pgxtools provides an integrated workflow for large-scale genomic data analysis and PGx clinical decision support. Implemented with cloud-native technologies, it is highly portable in a wide variety of environments from a single laptop to High-Performance Computing (HPC) clusters and cloud platforms for different production scales and requirements.

Development and validation of a pharmacogenomics reporting workflow based on the illumina global screening array chip

Background: Microarrays are a well-established and widely adopted technology capable of interrogating hundreds of thousands of loci across the human genome. Combined with imputation to cover common variants not included in the chip design, they offer a cost-effective solution for large-scale genetic studies. Beyond research applications, this technology can be applied for testing pharmacogenomics, nutrigenetics, and complex disease risk prediction. However, establishing clinical reporting workflows requires a thorough evaluation of the assay's performance, which is achieved through validation studies. In this study, we performed pre-clinical validation of a genetic testing workflow based on the Illumina Global Screening Array for 25 pharmacogenomic-related genes. Methods: To evaluate the accuracy of our workflow, we conducted multiple pre-clinical validation studies. Here, we present the results of accuracy and precision assessments, involving a total of 73 cell lines. These assessments encompass reference materials from the Genome-In-A-Bottle (GIAB), the Genetic Testing Reference Material Coordination Program (GeT-RM) projects, as well as additional samples from the 1000 Genomes project (1KGP). We conducted an accuracy assessment of genotype calls for target loci in each indication against established truth sets. Results: In our per-sample analysis, we observed a mean analytical sensitivity of 99.39% and specificity 99.98%. We further assessed the accuracy of star-allele calls by relying on established diplotypes in the GeT-RM catalogue or calls made based on 1KGP genotyping. On average, we detected a diplotype concordance rate of 96.47% across 14 pharmacogenomic-related genes with star allele-calls. Lastly, we evaluated the reproducibility of our findings across replicates and observed 99.48% diplotype and 100% phenotype inter-run concordance. Conclusion: Our comprehensive validation study demonstrates the robustness and reliability of the developed workflow, supporting its readiness for further development for applied testing.

Overcoming Barriers to Discovery and Implementation of Equitable Pharmacogenomic Testing in Oncology

Pharmacogenomics (PGx), the study of inherited genomic variation and drug response or safety, is a vital tool in precision medicine. In oncology, testing to identify PGx variants offers patients the opportunity for customized treatments that can minimize adverse effects and maximize the therapeutic benefits of drugs used for cancer treatment and supportive care. Because individuals of shared ancestry share specific genetic variants, PGx factors may contribute to outcome disparities across racial and ethnic categories when genetic ancestry is not taken into account or mischaracterized in PGx research, discovery, and application. Here, we examine how the current scientific understanding of the role of PGx in differential oncology safety and outcomes may be biased toward a greater understanding and more complete clinical implementation of PGx for individuals of European descent compared with other genetic ancestry groups. We discuss the implications of this bias for PGx discovery, access to care, drug labeling, and patient and provider understanding and use of PGx approaches. Testing for somatic genetic variants is now the standard of care in treatment of many solid tumors, but the integration of PGx into oncology care is still lacking despite demonstrated actionable findings from PGx testing, reduction in avoidable toxicity and death, and return on investment from testing. As the field of oncology is poised to expand and integrate germline genetic variant testing, it is vital that PGx discovery and application are equitable for all populations. Recommendations are introduced to address barriers to facilitate effective and equitable PGx application in cancer care.

Leveraging in Vitro Models for Clinically Relevant Rare CYP2D6 Variants in Pharmacogenomics

Cytochrome P450 2D6 (CYP2D6) is responsible for the metabolism of up to 20% of small-molecule drugs and therefore, may impact the safety and efficacy of medicines in broad therapeutic areas. CYP2D6 is highly polymorphic, and the frequency of variants can differ across racial and ethnic populations, significantly affecting enzymatic function and drug metabolism. However, rare variants of CYP2D6 present a unique challenge for academia, industry, and regulatory agencies alike due to the lack of feasibility of characterizing their clinical relevance in clinical trials, particularly in variants that exhibit population-specific frequencies in racial and ethnic groups that are poorly represented in clinical trials. Despite significant advancement in pharmacogenomics, the substrate specificity and related clinical relevance of these CYP2D6 rare variants remain largely unclear, and further efforts are warranted to characterize the burden of these variants on adverse drug reactions and drug efficacy. Thus, cell-based in vitro systems can be used to inform substrate-specific effects and the overall relevance of a rare variant. Liver microsomes, cell-based expression systems, ex vivo primary samples, and purified variant protein have all been used with various substrates to potentially predict the clinical impact of new substrates. In this review, we identify rare variants of CYP2D6 that demonstrate differences across races in prevalence and thus are often unassessed in clinical trials. Accordingly, we examine current pharmacogenomic in vitro models used to analyze the functional impact of these rare variants in a substrate-specific manner. SIGNIFICANCE STATEMENT: Variants of CYP2D6 play a clinically relevant role in drug metabolism, leading to potential safety and efficacy concerns. Although the influence of prevalent variants is often well characterized, rare variants are traditionally not included in clinical trials. This review captures the clinical relevance of rare variants in CYP2D6 by highlighting in vitro models that analyze their impact on the metabolism of CYP2D6 substrates.

Impact of Cytochrome P450 Genetic Variation on Patient-Reported Symptom Improvement and Side Effects Among Children and Adolescents Treated with Fluoxetine

Background: Clinical practice guidelines recommend the use of fluoxetine, a selective serotonin reuptake inhibitor (SSRI), as a first-line pharmacotherapy for major depressive disorder (MDD) and obsessive compulsive disorder (OCD) in children and adolescents. However, response and tolerability to fluoxetine varies from child to child, which may in part, be a result of interindividual differences in fluoxetine metabolism. In this study, we examined whether genotype-predicted activity scores of cytochrome P450 enzymes were associated with patient-reported symptom improvement and side effects in children and adolescents treated with fluoxetine. Methods: Ninety children and adolescents aged 7-18 with a MDD or OCD diagnosis and a history of fluoxetine treatment were recruited from Western Canada. For each participant, fluoxetine dose and duration information were collected, as well as questions about adherence, side effects, and symptom improvement. DNA was extracted from a saliva sample and genotyped for CYP2D6, CYP2C19, CYP2C9, CYP3A4, and CYP3A5. Logistic regression models were fitted to assess the impact of activity scores on symptom improvement and side effects. Results: Increased CYP2D6 activity score was significantly associated with reduced odds of symptom improvement (odds ratio [OR] = 0.46, 95% confidence interval [CI] = 0.23-0.91, p = 0.028) as well as a trend association with reduced side effects (OR = 0.49, 95% CI = 0.22-1.07, p = 0.072), after adjusting for age, sex, diagnosis, dose, duration, adherence, and activity scores of the other assessed CYP enzymes. No associations with symptom improvement or side effects were detected for the other CYP enzymes examined. Conclusions: Our results suggest that an increase in the genotype-predicted CYP2D6 activity score was associated with a decrease in the odds of reporting symptom improvement among children and adolescents treated with fluoxetine. These findings will contribute to future updates of pharmacogenetic-based SSRI prescribing guidelines and if replicated, could inform fluoxetine treatment in children and adolescents with MDD or OCD. Clinical Trial Registration: NCT04797364.

Pharmacogenetics in Child and Adolescent Psychiatry: Background and Evidence-Based Clinical Applications

The efficacy and tolerability of psychotropic medications can vary significantly among children and adolescents, and some of this variability relates to pharmacogenetic factors. Pharmacogenetics (PGx) in child and adolescent psychiatry can potentially improve treatment outcomes and minimize adverse drug reactions. This article reviews key pharmacokinetic and pharmacodynamic genes and principles of pharmacogenetic testing and discusses the evidence base for clinical decision-making concerning PGx testing. This article reviews current guidelines from the United States Food and Drug Administration (FDA), the Clinical Pharmacogenetics Implementation Consortium (CPIC), and the Dutch Pharmacogenetics Working Group (DPWG) and explores potential future directions. This review discusses key clinical considerations for clinicians prescribing psychotropic medications in children and adolescents, focusing on antidepressants, antipsychotics, stimulants, norepinephrine reuptake inhibitors, and alpha-2 agonists. Finally, this review synthesizes the practical use of pharmacogenetic testing and clinical decision support systems.

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.

Interrogating Pharmacogenetics Using Next-Generation Sequencing

BACKGROUND

Pharmacogenetics or pharmacogenomics (PGx) is the study of the role of inherited or acquired sequence change in drug response. With the rapid evolution of molecular techniques, bioinformatic tools, and increased throughput of functional genomic studies, the discovery of PGx associations and clinical implementation of PGx test results have now moved beyond a handful variants in single pharmacogenes and multi-gene panels that interrogate a few pharmacogenes to whole-exome and whole-genome scales. Although some laboratories have adopted next-generation sequencing (NGS) as a testing platform for PGx and other molecular tests, most clinical laboratories that offer PGx tests still use targeted genotyping approaches.

CONTENT

This article discusses primarily the technical considerations for clinical laboratories to develop NGS-based PGx tests including whole-genome and whole-exome sequencing analyses and highlights the challenges and opportunities in test design, content selection, bioinformatic pipeline for PGx allele and diplotype assignment, rare variant classification, reporting, and briefly touches a few additional areas that are important for successful clinical implementation of PGx results.

SUMMARY

The accelerated speed of technology development associated with continuous cost reduction and enhanced ability to interrogate complex genome regions makes it inevitable for most, if not all, clinical laboratories to transition PGx testing to an NGS-based platform in the near future. It is important for laboratories and relevant professional societies to recognize both the potential and limitations of NGS-based PGx profiling, and to work together to develop a standard and consistent practice to maximize the variant or allele detection rate and utility of PGx testing.

Psychiatric Level 1A evidence pharmacogenomics in a Brazilian admixed cohort and global populations

Purpose: To compare minor allele frequencies (MAFs) of psychiatric drug response variants in a Brazilian admixed cohort with global populations and other Brazilian groups. Methods: PharmGKB MAFs were gathered from publicly available genetic datasets for Brazil and worldwide. Results: Among 146 variants in CYP2D6 and CYP2C19, 41 were present in Brazil, mostly rare (MAF <1%). 11 variants showed significant MAF differences with large effect sizes compared with global populations. CYP2C19*3 (rs4986893), CYP2C19*17 (rs12248560), CYP2D6*17 (rs28371706-A) and CYP2D6*29 (rs61736512) exhibited higher frequencies in Brazil, with the latter three also differing from other Brazilian groups. Conclusion: This study highlights significant pharmacogenomic diversity in Brazil and globally, underscoring the need for more research in personalized psychiatric drug therapy.

Meta-analysis of CYP2C19 and CYP2D6 metabolic activity on antidepressant response from 13 clinical studies using genotype imputation

Cytochrome P450 enzymes including CYP2C19 and CYP2D6 are important for antidepressant metabolism and polymorphisms of these genes have been determined to predict metabolite levels. Nonetheless, more evidence is needed to understand the impact of genetic variations on antidepressant response. In this study, individual clinical and genetic data from 13 studies of European and East Asian ancestry populations were collected. The antidepressant response was clinically assessed as remission and percentage improvement. Imputed genotype was used to translate genetic polymorphisms to metabolic phenotypes (poor, intermediate, normal, and rapid+ultrarapid) of CYP2C19 and CYP2D6. The association of CYP2C19 and CYP2D6 metabolic phenotypes with treatment response was examined using normal metabolizers as the reference. Among 5843 depression patients, a higher remission rate was found in CYP2C19 poor metabolizers compared to normal metabolizers at nominal significance but did not survive after multiple testing correction (OR=1.46, 95% CI [1.03, 2.06], p=0.033, heterogeneity I2=0%, subgroup difference p=0.72). No metabolic phenotype was associated with percentage improvement from baseline. After stratifying by antidepressants primarily metabolized by CYP2C19 and CYP2D6, no association was found between metabolic phenotypes and antidepressant response. Metabolic phenotypes showed differences in frequency, but not effect, between European- and East Asian-ancestry studies. In conclusion, metabolic phenotypes imputed from genetic variants using genotype were not associated with antidepressant response. CYP2C19 poor metabolizers could potentially contribute to antidepressant efficacy with more evidence needed. CYP2D6 structural variants cannot be imputed from genotype data, limiting inference of pharmacogenetic effects. Sequencing and targeted pharmacogenetic testing, alongside information on side effects, antidepressant dosage, depression measures, and diverse ancestry studies, would more fully capture the influence of metabolic phenotypes.

The Intersection between Pharmacogenomics and Health Equity: A Case Example

Pharmacogenomics (PGx) and the study of precision medicine has substantial power to either uplift health equity efforts or further widen the gap of our already existing health disparities. In either occurrence, the medication experience plays an integral role within this intersection on an individual and population level. Examples of this intertwined web are highlighted through a case discussion. With these perspectives in mind, several recommendations for the research and clinical communities are highlighted to promote equitable healthcare with PGx integrated.

PharmVar Tutorial on CYP2D6 Structural Variation Testing and Recommendations on Reporting

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

Evolution of pharmacogenomic services and implementation of a multi-state pharmacogenomics clinic across a large rural healthcare system

Introduction: Pharmacogenomics (PGx) aims to maximize drug benefits while minimizing risk of toxicity. Although PGx has proven beneficial in many settings, clinical uptake lags. Lack of clinician confidence and limited availability of PGx testing can deter patients from completing PGx testing. A few novel PGx clinic models have been described as a way to incorporate PGx testing into the standard of care. Background: A PGx clinic was implemented to fill an identified gap in provider availability, confidence, and utilization of PGx across our health system. Through a joint pharmacist and Advanced Practice Provider (APP) collaborative clinic, patients received counseling and PGx medication recommendations both before and after PGx testing. The clinic serves patients both in-person and virtually across four states in the upper Midwest. Results: The majority of patients seen in the PGx clinic during the early months were clinician referred (77%, n = 102) with the remainder being self-referred. Patients were, on average, taking two medications with Clinical Pharmacogenetics Implementation Consortium guidelines. Visits were split almost equally between in-person and virtual visits. Conclusion: Herein, we describe the successful implementation of an interdisciplinary PGx clinic to further enhance our PGx program. Throughout the implementation of the PGx clinic we have learned valuable lessons that may be of interest to other implementors. Clinicians were actively engaged in clinic referrals and early adoption of telemedicine was key to the clinic's early successes.

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

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

CYP2D6 and CYP2C19 Variant Coverage of Commercial Antidepressant Pharmacogenomic Testing Panels Available in Victoria, Australia

Pharmacogenomic (PGx) testing to inform antidepressant medication selection and dosing is gaining attention from healthcare professionals, patients, and payors in Australia. However, there is often uncertainty regarding which test is most suitable for a particular patient. Here, we identified and evaluated the coverage of CYP2D6 and CYP2C19 variants in commercial antidepressant PGx testing panels in Victoria, a large and ethnically diverse state of Australia. Test characteristics and star alleles tested for both genes were obtained directly from pathology laboratories offering PGx testing and compared against the Association of Molecular Pathology's recommended minimum (Tier 1) and extended (Tier 2) allele sets. Although all tests covered the minimum recommended alleles for CYP2C19, this was not the case for CYP2D6. This study emphasizes that PGx tests might not be suitable for all individuals in Australia due to the limited range of star alleles assessed. Inadequate haplotype coverage may risk misclassification of an individual's predicted metabolizer phenotype, which has ramifications for depression medication selection and dosage. This study underscores the urgent need for greater standardization in PGx testing and emphasizes the importance of considering genetic ancestry when choosing a PGx testing panel to ensure optimal clinical applicability.

Multigenetic Pharmacogenomics-Guided Treatment vs Treatment As Usual Among Hospitalized Men With Schizophrenia: A Randomized Clinical Trial

Importance

Limited evidence supports multigenetic pharmacogenomics-guided treatment (MPGT) in schizophrenia.

Objective

To evaluate the clinical effectiveness of MPGT in schizophrenia in a randomized clinical trial (RCT).

Design, Setting, and Participants

This RCT was conducted from March 2020 to March 2022. Male Chinese Han inpatients aged 18 to 60 years diagnosed with schizophrenia with a Positive and Negative Symptom Scale (PANSS) score of 60 or more from 2 selected study hospitals were included. Patients and raters were masked to MPGT or treatment as usual (TAU) randomization.

Interventions

Participants were randomly assigned in a 1:1 ratio to receive either MPGT or TAU for 12 weeks.

Main Outcomes and Measures

The primary efficacy outcome was the percentage change in PANSS total scores (range, 30 to 210) from baseline to week 6 analyzed by a modified intention-to-treat mixed model for repeated measures. The secondary outcome included response and symptomatic remission rates.

Results

A total of 210 participants (mean [SD] age, 29.2 [8.8] years) were enrolled and analyzed, with 113 assigned to MPGT and 97 to TAU. Compared with those randomized to TAU, participants randomized to MPGT demonstrated a significantly higher percentage change in PANSS score (74.2% vs 64.9%; adjusted mean difference, 9.2 percentage points; 95% CI, 4.4-14.1 percentage points; P < .001) and a higher response rate (93 of 113 [82.3%] vs 63 of 97 [64.9%]; adjusted odds ratio, 2.48; 95% CI, 1.28-4.80; P = .01) at the end of week 6.

Conclusions and Relevance

In this RCT of MPGT, MPGT was more effective than TAU in treating patients with schizophrenia. These findings suggest that multigenetic pharmacogenomic testing could serve as an effective tool to guide the treatment of schizophrenia.

Trial Registration

Chinese Clinical Trial Registry Identifier: ChiCTR2000029671.

Response to the FDA Decision Regarding DPYD Testing Prior to Fluoropyrimidine Chemotherapy

Fluoropyrimidine (FP) chemotherapy is associated with severe, life-threatening toxicities, particularly among patients who carry deleterious germline variants in the DPYD gene. Pretreatment DPYD testing is standard of care throughout most of Europe; however, it has not been recommended in clinical practice guidelines in the United States. Due to increased risk of severe toxicity, a Citizen's Petition asked the US Food and Drug Administration (FDA) to update language in FP drug labels to recommend DPYD testing as part of a boxed warning and recommend FP dose reduction in patients carrying deleterious germline variants. In response, the FDA updated the capecitabine package insert to inform patients about the toxicity risk and test availability and consider DPYD testing. However, the FDA did not include a testing recommendation or requirement, or a boxed warning. Additionally, the FDA did not recommend FP dose adjustment in DPYD variant carriers. This review provides a critical assessment of the DPYD-FP pharmacogenetic association using the FDA's previously published Pharmacogenetic Pyramid, demonstrating that the evidence is compelling for recommending DPYD testing prior to FP treatment. Additionally, the FDA's stated concerns about recommending DPYD testing and DPYD-guided FP dose adjustment are addressed and discussed in the context of the FDA's other genetic testing and dose adjustment recommendations. We call on the FDA to follow our European counterparts in recommending DPYD testing and genotype-based dose adjustment to ensure patients with cancer receive safe and effective FP chemotherapy.

Outpatient Pharmacogenomic Screenings to Prevent Addiction, Overdose, and Suicide

Point-of-care genetic testing for single nucleotide polymorphisms (SNPs) to improve psychiatric treatment in outpatient settings remains a challenge. The presence or absence of certain genomic alleles determines the activity of the encoded enzymes, which ultimately defines the individual's drug metabolism rate. Classification of poor metabolizers (PMs) and rapid/ultrarapid metabolizers (RMs/UMs) would facilitate personalization and precision of treatment. However, current pharmacogenomic (PGx) testing of multiple genes is comprehensive and requires quantitative analyses for interpretations. We recommend qualitative, fast-track, point-of-care screenings, which are one- or-two gene-based analyses, as a quick initial screening tool to potentially eliminate the need for an expensive quantitative send-out test, which is a costly and lengthy process. We speculate that these tests will be relevant in two major scenarios: 1) clinical psychiatry for treating disease states such as major depressive disorder (MDD) and posttraumatic stress disorder (PTSD), where trial and error is still the mainstay of drug selection and symptom management, a process that is associated with significant delay in optimizing individualized treatment and dose, and thus response; and 2) pain management, where quickly determining an effective level of analgesia while avoiding a toxic level can cause a drastic improvement in mental health.

Pharmacogenetics of Long-Term Outcomes of Schizophrenia Spectrum Disorders: The Functional Role of CYP2D6 and CYP2C19

Schizophrenia spectrum disorders (SSD) are complex mental disorders, and while treatment with antipsychotics is important, many patients do not respond or develop serious side effects. Genetic variation has been shown to play a considerable role in determining an individual's response to antipsychotic medication. However, previous pharmacogenetic (PGx) studies have been limited by small sample sizes, lack of consensus regarding relevant genetic variants, and cross-sectional designs. The current study aimed to investigate the association between PGx variants and long-term clinical outcomes in 691 patients of European ancestry with SSD. Using evidence from the literature on candidate genes involved in antipsychotic pharmacodynamics, we created a polygenic risk score (PRS) to investigate its association with clinical outcomes. We also created PRS using core variants of psychotropic drug metabolism enzymes CYP2D6 and CYP2C19. Furthermore, the CYP2D6 and CYP2C19 functional activity scores were calculated to determine the relationship between metabolism and clinical outcomes. We found no association for PGx PRSs and clinical outcomes; however, an association was found with CYP2D6 activity scores by the traditional method. Higher CYP2D6 metabolism was associated with high positive and high cognitive impairment groups relative to low symptom severity groups. These findings highlight the need to test PGx efficacy with different symptom domains. More evidence is needed before pharmacogenetic variation can contribute to personalized treatment plans.

CYP3A4 and CYP3A5 Genotyping Recommendations: A Joint Consensus Recommendation of the Association for Molecular Pathology, Clinical Pharmacogenetics Implementation Consortium, College of American Pathologists, Dutch Pharmacogenetics Working Group of the Royal Dutch Pharmacists Association, European Society for Pharmacogenomics and Personalized Therapy, and Pharmacogenomics Knowledgebase

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 a minimum set of variants that should be included in clinical PGx genotyping assays. This document series provides recommendations for a minimum panel of variant alleles (tier 1) and an extended panel of variant alleles (tier 2) that will aid clinical laboratories when designing assays for PGx testing. The Association for Molecular Pathology PGx Working Group considered functional impact of the variant alleles, allele frequencies in multiethnic populations, the availability of reference materials, and other technical considerations for PGx testing when developing these recommendations. The goal of this Working Group is to promote standardization of PGx gene/allele testing across clinical laboratories. This document will focus on clinical CYP3A4 and CYP3A5 PGx testing that may be applied to all CYP3A4- and CYP3A5-related medications. These recommendations are not to be interpreted as prescriptive but to provide a reference guide.

Characterization of Reference Materials for CYP3A4 and CYP3A5: A (GeT-RM) Collaborative Project

Pharmacogenetic testing for CYP3A4 is increasingly provided by clinical and research laboratories; however, only a limited number of quality control and reference materials are currently available for many of the CYP3A4 variants included in clinical tests. To address this need, the Division of Laboratory Systems, CDC-based Genetic Testing Reference Material Coordination Program (GeT-RM), in collaboration with members of the pharmacogenetic testing and research communities and the Coriell Institute for Medical Research, has characterized 30 DNA samples derived from Coriell cell lines for CYP3A4. Samples were distributed to five volunteer laboratories for genotyping using a variety of commercially available and laboratory-developed tests. Sanger and next-generation sequencing were also utilized by some of the laboratories. Whole-genome sequencing data from the 1000 Genomes Projects were utilized to inform genotype. Twenty CYP3A4 alleles were identified in the 30 samples characterized for CYP3A4: CYP3A4∗4, ∗5, ∗6, ∗7, ∗8, ∗9, ∗10, ∗11, ∗12, ∗15, ∗16, ∗18, ∗19, ∗20, ∗21, ∗22, ∗23, ∗24, ∗35, and a novel allele, CYP3A4∗38. Nineteen additional samples with preexisting data for CYP3A4 or CYP3A5 were re-analyzed to generate comprehensive reference material panels for these genes. These publicly available and well-characterized materials can be used to support the quality assurance and quality control programs of clinical laboratories performing clinical pharmacogenetic testing.

CYP2D6 and ADRB1 genetic polymorphisms and the selection of antihypertensive beta-receptor blockers for hypertensive patients

BACKGROUND

Genetic factors contribute to the variability in individual response to antihypertensive medications. We sought to investigate the frequencies of allele and genotype for CYP2D6 and ADRB1 genetic polymorphisms and explore their potential impact in influencing the selection of antihypertensive beta-receptor blockers.

METHODS

The study population was selected from the Han Chinese patients in Zhongda Hospital, which contained 2419 Han Chinese hypertensive individuals and 151 normotensive controls. Each of the above participants underwent venous blood sampling. Then, the gene chip platform was adopted to evaluate the CYP2D6 and ADRB1 genetic polymorphisms. The allele as well as genotype frequencies for each gene, along with the combined genotypes, were subjected to analysis.

RESULTS

The frequency of *1/*1 wild-type homozygous for CYP2D6 was 9.71%, while the frequency of *1/*10 heterozygous or *10/*10 mutant homozygous was 59.16% or 31.13%, respectively, as established by gene chip analysis. Similarly, we observed that the genotype frequencies of GG wild-type homozygous for ADRB1 was 10.29%, while that of GC heterozygous, or CC mutant homozygous was 44.98%, or 44.73%, respectively. Notably, combined genotypes *1/*10 + CC (25.88%) and *1/*10 + CG (27.78%) had the highest frequencies. Importantly, no substantial differences in the distributions of CYP2D6 and ADRB1 polymorphism were noted between hypertensive patients and normotensive controls, or among all different grades of hypertension.

CONCLUSION

These findings provide insights into the CYP2D6 and ADRB1 polymorphisms in hypertensive patients from Han Chinese, which show significant differences compared to other geographic groups of Han Chinese hypertensive patients. These results offer valuable information for future prospective clinical studies on the antihypertensive effects of beta-receptor blockers in Han Chinese hypertensive patients.

Deletion of the CYP2D6 gene as a likely explanation for the serious side effects of the antipsychotic drug pimozide: a case report

CYP2D6 analysis prior to the prescription of pimozide is required above a certain dose by the Food and Drug Administration in order to detect individuals with the poor metabolizer status. This precautionary measure aims to prevent the occurrence of serious adverse drug reactions. This study presents a case of a patient diagnosed with schizophrenia spectrum disorder. The patient suffered re-admission in the psychiatry ward because of severe secondary symptoms due to the antipsychotic drug pimozide, previously prescribed on a first admission. In order to assess the patient's medication profile, real-time PCR was performed to analyze the main genes responsible for its metabolization, namely, CYP2D6 and CYP3A4. The pharmacogenetic study revealed that the patient is a poor metabolizer for CYP2D6, presenting deletion of both copies of the gene (diplotype *5/*5). Fortunately, the symptomatology disappeared after the withdrawal of the responsible drug. In conclusion, abiding by the pharmacogenetic clinical practice guidelines and the pharmacogenetic analysis of CYP2D6 when prescribing pimozide would have probably saved the patient from the consequences of severe side effects and the health system expenditure. There is an important need for more training in the pharmacogenetic field for specialists in psychiatry.

The Clinical Laboratory Is an Integral Component to Health Care Delivery : An Expanded Representation of the Total Testing Process

OBJECTIVES

Developing an expanded representation of the total testing process that includes contemporary elements of laboratory practice can be useful to understanding and optimizing testing workflows across clinical laboratory and patient care settings.

METHODS

Published literature and meeting reports were used by the coauthors to inform the development of the expanded representation of the total testing process and relevant examples describing its uses.

RESULTS

A visual representation of the total testing process was developed and contextualized to patient care scenarios using a number of examples covering the detection of blood culture contamination, use of next-generation sequencing, and pharmacogenetic testing.

CONCLUSIONS

The expanded representation of the total testing process can serve as a model and framework to document and improve the use of clinical testing within the broader context of health care delivery. This representation recognizes increased engagement among clinical laboratory professionals with patients and other health care providers as essential to making informed decisions. The increasing use of data is highlighted as important to ensuring quality, appropriate test utilization, and sustaining an efficient workflow across clinical laboratory and patient care settings. Maintaining a properly resourced and competent workforce is also featured as an essential component to the testing process.

Computational pharmacogenotype extraction from clinical next-generation sequencing

Background

Next-generation sequencing (NGS), including whole genome sequencing (WGS) and whole exome sequencing (WES), is increasingly being used for clinic care. While NGS data have the potential to be repurposed to support clinical pharmacogenomics (PGx), current computational approaches have not been widely validated using clinical data. In this study, we assessed the accuracy of the Aldy computational method to extract PGx genotypes from WGS and WES data for 14 and 13 major pharmacogenes, respectively.

Methods

Germline DNA was isolated from whole blood samples collected for 264 patients seen at our institutional molecular solid tumor board. DNA was used for panel-based genotyping within our institutional Clinical Laboratory Improvement Amendments- (CLIA-) certified PGx laboratory. DNA was also sent to other CLIA-certified commercial laboratories for clinical WGS or WES. Aldy v3.3 and v4.4 were used to extract PGx genotypes from these NGS data, and results were compared to the panel-based genotyping reference standard that contained 45 star allele-defining variants within CYP2B6, CYP2C8, CYP2C9, CYP2C19, CYP2D6, CYP3A4, CYP3A5, CYP4F2, DPYD, G6PD, NUDT15, SLCO1B1, TPMT, and VKORC1.

Results

Mean WGS read depth was >30x for all variant regions except for G6PD (average read depth was 29 reads), and mean WES read depth was >30x for all variant regions. For 94 patients with WGS, Aldy v3.3 diplotype calls were concordant with those from the genotyping reference standard in 99.5% of cases when excluding diplotypes with additional major star alleles not tested by targeted genotyping, ambiguous phasing, and CYP2D6 hybrid alleles. Aldy v3.3 identified 15 additional clinically actionable star alleles not covered by genotyping within CYP2B6, CYP2C19, DPYD, SLCO1B1, and NUDT15. Within the WGS cohort, Aldy v4.4 diplotype calls were concordant with those from genotyping in 99.7% of cases. When excluding patients with CYP2D6 copy number variation, all Aldy v4.4 diplotype calls except for one CYP3A4 diplotype call were concordant with genotyping for 161 patients in the WES cohort.

Conclusion

Aldy v3.3 and v4.4 called diplotypes for major pharmacogenes from clinical WES and WGS data with >99% accuracy. These findings support the use of Aldy to repurpose clinical NGS data to inform clinical PGx.

Implementation of CYP2D6-guided opioid therapy at Cincinnati Children's Hospital Medical Center

PURPOSE

We describe the implementation of CYP2D6-focused pharmacogenetic testing to guide opioid prescribing in a quaternary care, nonprofit pediatric academic medical center.

SUMMARY

Children are often prescribed oral opioids after surgeries, for cancer pain, and occasionally for chronic pain. In 2004, Cincinnati Children's Hospital Medical Center implemented pharmacogenetic testing for CYP2D6 metabolism phenotype to inform codeine prescribing. The test and reports were updated to align with changes over time in the testing platform, the interpretation of genotype to phenotype, the electronic health record, and Food and Drug Administration (FDA) guidance. The use of the test increased when a research project required testing and decreased as prescribing of oxycodone increased due to FDA warnings about codeine. Education about the opioid-focused pharmacogenetic test was provided to prescribers (eg, the pain and sickle cell teams) as well as patients and families. Education and electronic health record capability increased provider compliance with genotype-guided postsurgical prescribing of oxycodone, although there was a perceived lack of utility for oxycodone prescribing.

CONCLUSION

The implementation of pharmacogenetic testing to inform opioid prescribing for children has evolved with accumulating evidence and guidelines, requiring changes in reporting of results and recommendations.

Determination of the Duplicated CYP2D6 Allele Using Real-Time PCR Signal: An Alternative Approach

CYP2D6 duplication has important pharmacogenomic implications. Reflex testing with long-range PCR (LR-PCR) can resolve the genotype when a duplication and alleles with differing activity scores are detected. We evaluated whether visual inspection of plots from real-time-PCR-based targeted genotyping with copy number variation (CNV) detection could reliably determine the duplicated CYP2D6 allele. Six reviewers evaluated QuantStudio OpenArray CYP2D6 genotyping results and the TaqMan Genotyper plots for seventy-three well-characterized cases with three copies of CYP2D6 and two different alleles. Reviewers blinded to the final genotype visually assessed the plots to determine the duplicated allele or opt for reflex sequencing. Reviewers achieved 100% accuracy for cases with three CYP2D6 copies that they opted to report. Reviewers did not request reflex sequencing in 49-67 (67-92%) cases (and correctly identified the duplicated allele in each case); all remaining cases (6-24) were marked by at least one reviewer for reflex sequencing. In most cases with three copies of CYP2D6, the duplicated allele can be determined using a combination of targeted genotyping using real-time PCR with CNV detection without need for reflex sequencing. In ambiguous cases and those with >3 copies, LR-PCR and Sanger sequencing may still be necessary for determination of the duplicated allele.

The Role of Pharmacogenetics in Personalizing the Antidepressant and Anxiolytic Therapy

Pharmacotherapy for neuropsychiatric disorders, such as anxiety and depression, has been characterized by significant inter-individual variability in drug response and the development of side effects. Pharmacogenetics, as a key part of personalized medicine, aims to optimize therapy according to a patient's individual genetic signature by targeting genetic variations involved in pharmacokinetic or pharmacodynamic processes. Pharmacokinetic variability refers to variations in a drug's absorption, distribution, metabolism, and elimination, whereas pharmacodynamic variability results from variable interactions of an active drug with its target molecules. Pharmacogenetic research on depression and anxiety has focused on genetic polymorphisms affecting metabolizing cytochrome P450 (CYP) and uridine 5'-diphospho-glucuronosyltransferase (UGT) enzymes, P-glycoprotein ATP-binding cassette (ABC) transporters, and monoamine and γ-aminobutyric acid (GABA) metabolic enzymes, transporters, and receptors. Recent pharmacogenetic studies have revealed that more efficient and safer treatments with antidepressants and anxiolytics could be achieved through genotype-guided decisions. However, because pharmacogenetics cannot explain all observed heritable variations in drug response, an emerging field of pharmacoepigenetics investigates how epigenetic mechanisms, which modify gene expression without altering the genetic code, might influence individual responses to drugs. By understanding the epi(genetic) variability of a patient's response to pharmacotherapy, clinicians could select more effective drugs while minimizing the likelihood of adverse reactions and therefore improve the quality of treatment.

The Evaluation of CYP2D6, CYP2C9, CYP2C19, and CYP2B6 Phenoconversion in Post-Mortem Casework: The Challenge of Forensic Toxicogenetics

In toxicogenetics, an integrative approach including the prediction of phenotype based on post-mortem genotyping of drug-metabolising enzymes might help explain the cause of death (CoD) and manner of death (MoD). The use of concomitant drugs, however, might lead to phenoconversion, a mismatch between the phenotype based on the genotype and the metabolic profile actually observed after phenoconversion. The aim of our study was to evaluate the phenoconversion of CYP2D6, CYP2C9, CYP2C19, and CYP2B6 drug-metabolising enzymes in a series of autopsy cases tested positive for drugs that are substrates, inducers, or inhibitors of these enzymes. Our results showed a high rate of phenoconversion for all enzymes and a statistically significant higher frequency of poor and intermediate metabolisers for CYP2D6, CYP2C9, and CYP2C19 after phenoconversion. No association was found between phenotypes and CoD or MoD, suggesting that, although phenoconversion might be useful for a forensic toxicogenetics approach, more research is needed to overcome the challenges arising from the post-mortem setting.

PharmVar GeneFocus: SLCO1B1

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.

Evidence Regarding Pharmacogenetics in Pain Management and Cancer

Patients experience interindividual variation in response to analgesics, which may be partially explained by genetics. This commentary discusses a recently published trial on COMT genotype and opioid dose requirements and describes the potential role for COMT and other genes (eg, CYP2D6) on opioid therapy and the current evidence for germline pharmacogenetics and resources for opioid pharmacogenetics.

Potential Impact of Pharmacogenomic Single Nucleotide Variants in a Rural Caucasian Population

BACKGROUND

In the US adverse drug reactions (ADRs) are estimated to cause 100 000 fatalities and cost over $136 billion annually. A patient's genes play a significant role in their response to a drug. Pharmacogenomics aims to optimize drug choice and dose for individual patients by characterizing patients' pharmacologically relevant genes to identify variants of known impact.

METHODS

DNA was extracted from randomly selected remnant whole blood samples from Caucasian patients with previously performed complete blood counts. Samples were genotyped by mass spectrometry using a customized pharmacogenomics panel. A third-party result interpretation service used genotypic results to predict likely individual responses to frequently prescribed drugs.

RESULTS

Complete genotypic and phenotypic calls for all tested Cytochrome P450 isoenzymes and other genes were obtained from 152 DNA samples. Of these 152 unique genomic DNA samples, 140 had genetic variants suggesting dose adjustment for at least one drug. Cardiovascular and psychiatry drugs had the highest number of recommendations, which included United States Food and Drug Administration warnings for highly prescribed drugs metabolized by CYP2C19, CYP2C9, CYP2D6, HLA-A, and VKORC1.

CONCLUSIONS

Risk for each drug:gene pairing primarily depends upon the degree of predicted enzyme impairment or activation, width of the therapeutic window, and whether parent compound or metabolite is pharmacologically active. The resulting metabolic variations range from risk of toxicity to therapeutic failure. Pharmacogenomic profiling likely reduces ADR potential by allowing up front drug/dose selection to fit a patient's unique drug-response profile.

Pharmacogenetic allele variant frequencies: An analysis of the VA's Million Veteran Program (MVP) as a representation of the diversity in US population

We present allele frequencies of pharmacogenomics relevant variants across multiple ancestry in a sample representative of the US population. We analyzed 658,582 individuals with genotype data and extracted pharmacogenomics relevant single nucleotide variant (SNV) alleles, human leukocyte antigens (HLA) 4-digit alleles and an important copy number variant (CNV), the full deletion/duplication of CYP2D6. We compiled distinct allele frequency tables for European, African American, Hispanic, and Asian ancestry individuals. In addition, we compiled allele frequencies based on local ancestry reconstruction in the African-American (2-way deconvolution) and Hispanic (3-way deconvolution) cohorts.

Impact of polymorphisms in CYP and UGT enzymes and ABC and SLCO1B1 transporters on the pharmacokinetics and safety of desvenlafaxine

Venlafaxine pharmacokinetic variability and pharmacotherapy outcomes are well known to be related to CYP2D6 pharmacogenetic phenotype. In contrast, scarce pharmacogenetic information is available nowadays concerning desvenlafaxine, its active metabolite first marketed in 2012. The aim of this study was to evaluate the impact of 29 alleles in 12 candidate genes (e.g., CYP enzymes like CYP2D6, CYP3A4, or CYP2C19; ABC transporters like ABCB1; SLCO1B1; and UGT enzymes like UGT1A1) on desvenlafaxine pharmacokinetic variability and tolerability. Pharmacokinetic parameters and adverse drug reaction (ADR) incidence obtained from six bioequivalence clinical trials (n = 98) evaluating desvenlafaxine formulations (five with single dose administration and one with multiple-dose administration) were analyzed. No genetic polymorphism was related to pharmacokinetic variability or ADR incidence. Volunteers enrolled in the multiple-dose clinical trial also showed a higher incidence of ADRs, e.g., xerostomia or appetite disorders. Volunteers experiencing any ADR showed a significantly higher area under the time-concentration curve (AUC) than those not experiencing any ADR (5115.35 vs. 4279.04 ng*h/mL, respectively, p = 0.034). In conclusion, the strong dose-dependent relationship with the occurrence of ADRs confirms that the mechanism of action of desvenlafaxine is essentially dose-dependent.

Pediatric considerations for pharmacogenetic selective serotonin reuptake inhibitors clinical decision support

Pharmacogenetic testing for psychiatry is growing at a rapid pace, with multiple sites utilizing results to help clinical decision-making. Genotype-guided dosing and drug selection have been implemented at several sites, including Vanderbilt University Medical Center, where clinical decision support (CDS) based on pharmacogenetic results went live for selective serotonin reuptake inhibitors in 2020 for both adult and pediatric patients. Effective and appropriate implementation of CYP2D6- and CYP2C19-guided CDS for the pediatric population requires consideration of the evidence for the pharmacogenetic associations, medication indications, and appropriate alternative therapies to be used when a pharmacogenetic contraindication is identified. In this article, we review these pediatric pharmacogenetic considerations for selective serotonin reuptake inhibitor CDS. We include a case study, the current literature supporting clinical recommendations, considerations when designing pediatric CDS, future implications, and examples of sertraline, (es)citalopram, paroxetine, and fluvoxamine alerts.

Toward a More Just System of Care in Molecular Pathology

Policy Points American health care policy must be critically assessed to establish the role it plays in sustaining and alleviating the health disparities that currently exist in molecular genetic testing. It is critical to understand the economic and sociocultural influences that drive patients to undergo or forgo molecular testing, especially in marginalized patient populations. A multipronged solution with actions necessary from multiple stakeholders is required to reduce the cost of health care, rebalance regional disparities, encourage physician engagement, reduce data bias, and earn patients' trust.

CONTEXT

The health status of a population is greatly influenced by both biological processes and external factors. For years, minority and low socioeconomic patient populations have faced worse outcomes and poorer health in the United States. Experts have worked extensively to understand the issues and find solutions to alleviate this disproportionate burden of disease. As a result, there have been some improvements and successes, but wide gaps still exist. Diagnostic molecular genetic testing and so-called personalized medicine are just now being integrated into the current American health care system. The way in which these tests are integrated can either exacerbate or reduce health disparities.

METHODS

We provide case scenarios-loosely based on real-life patients-so that nonexperts can see the impacts of complex policy decisions and unintentional biases in technology without needing to understand all the intricacies. We use data to explain these findings from an extensive literature search examining both peer-reviewed and gray literature.

FINDINGS

Access to diagnostic molecular genetic testing is not equitable or sufficient, owing to at least five major factors: (1) cost to the patient, (2) location, (3) lack of provider buy-in, (4) data-set bias, and (5) lack of public trust.

CONCLUSIONS

Molecular genetic pathology can be made more equitable with the concerted efforts of multiple stakeholders. Confronting the five major factors identified here may help us usher in a new era of precision medicine without its discriminatory counterpart.

PharmVar GeneFocus: CYP3A5

The Pharmacogene Variation Consortium (PharmVar) catalogs star (*) allele nomenclature for the polymorphic human CYP3A5 gene. Genetic variation within the CYP3A5 gene locus impacts the metabolism of several clinically important drugs, including the immunosuppressants tacrolimus, sirolimus, cyclosporine, and the benzodiazepine midazolam. Variable CYP3A5 activity is of clinical importance regarding tacrolimus metabolism. This GeneFocus provides a CYP3A5 gene summary with a focus on aspects regarding standardized nomenclature. In addition, this review also summarizes recent changes and updates, including the retirement of several allelic variants and provides an overview of how PharmVar CYP3A5 star allele nomenclature is utilized by the Pharmacogenomics Knowledgebase (PharmGKB) and the Clinical Pharmacogenetics Implementation Consortium (CPIC).

How to Implement a Pharmacogenetics Service at your Institution

The vast majority of patients possess one or more pharmacogenetic variants that can influence optimal medication use. When pharmacogenetic data are used to guide drug choice and dosing, evidence points to improved disease outcomes, fewer adverse effects, and lower healthcare spending. Although its science is well established, clinical use of pharmacogenetic data to guide drug therapy is still in its infancy. Pharmacogenetics essentially involves the intersection of an individual's genetic data with their medications, which makes pharmacists uniquely qualified to provide clinical support and education in this field. In fact, most pharmacogenetics implementations, to date, have been led by pharmacists as leaders or members of a multidisciplinary team or as individual practitioners. A successful large-scale pharmacogenetics implementation requires coordination and synergy among administrators, clinicians, informatics teams, laboratories, and patients. Because clinical implementation of pharmacogenetics is in its early stages, there is an urgent need for guidance and dissemination of shared experiences to provide a framework for clinicians. Many early adopters of pharmacogenetics have explored various strategies among diverse practice settings. This article relies on the experiences of early adopters to provide guidance for critical steps along the pathway to implementation, including strategies to engage stakeholders; evaluate pharmacogenetic evidence; coordinate laboratory testing, results interpretation and their integration into the electronic health record; identify reimbursement avenues; educate providers and patients; and maintain a successful program. Learning from early adopters' published experiences and strategies can allow clinicians leading a new pharmacogenetics implementation to avoid pitfalls and adapt and apply lessons learned by others to their own practice.