Targeted Genotyping in Clinical Pharmacogenomics: What Is Missing?

Next-generation sequencing in pharmacogenomics - fit for clinical decision support?

INTRODUCTION

The technological advances of sequencing methods during the past 20 years have fuelled the generation of large amounts of sequencing data that comprise common variations, as well as millions of rare and personal variants that would not be identified by conventional genotyping. While comprehensive sequencing is technically feasible, its clinical utility for guiding personalized treatment decisions remains controversial.

AREAS COVERED

We discuss the opportunities and challenges of comprehensive sequencing compared to targeted genotyping for pharmacogenomic applications. Current pharmacogenomic sequencing panels are heterogeneous and clinical actionability of the included genes is not a major focus. We provide a current overview and critical discussion of how current studies utilize sequencing data either retrospectively from biobanks, databases or repurposed diagnostic sequencing, or prospectively using pharmacogenomic sequencing.

EXPERT OPINION

While sequencing-based pharmacogenomics has provided important insights into genetic variations underlying the safety and efficacy of a multitude pharmacological treatments, important hurdles for the clinical implementation of pharmacogenomic sequencing remain. We identify gaps in the interpretation of pharmacogenetic variants, technical challenges pertaining to complex loci and variant phasing, as well as unclear cost-effectiveness and incomplete reimbursement. It is critical to address these challenges in order to realize the promising prospects of pharmacogenomic sequencing.

Implementation of pharmacogenomics testing for precision medicine

Great strides have been made in the past decade to lower barriers to clinical pharmacogenomics implementation. Nevertheless, PGx consultation prior to prescribing therapeutics is not yet mainstream. This review addresses the current climate surrounding PGx implementation, focusing primarily on strategies for implementation at academic institutions, particularly at The University of Chicago, and provides an up-to-date guide of resources supporting the development of PGx programs. Remaining challenges and recent strategies for overcoming these challenges to implementation are discussed.

A call for increased inclusivity and global representation in pharmacogenetic testing

Commercial pharmacogenetic testing panels capture a fraction of the genetic variation underlying medication metabolism and predisposition to adverse reactions. In this study we compared variation in six pharmacogenes detected by whole genome sequencing (WGS) to a targeted commercial panel in a cohort of 308 individuals with family history of pediatric heart disease. In 1% of the cohort, WGS identified rare variants that altered the interpretation of metabolizer status and would thus prevent potential errors in gene-based dosing.

Impact of sex on antidepressant discontinuation in groups of similar cytochrome P450 phenotypes

Introduction

Although there are studies assessing reasons for antidepressant discontinuation, little is known about the impact of sex differences or cytochrome P450 phenotypes. Our objective is to assess discontinuation rates between males and females and whether CYP450 phenotype influences discontinuation.

Methods

This is a retrospective review of patients previously enrolled in the Right Drug, Right Dose, Right Time: Using Genomic Data to Individualize Treatment database with major depressive disorder. Patients were evaluated for antidepressants trialed between January 1, 2009, and September 30, 2019. Survival analyses with competing risks were used to analyze discontinuation reasons. A Kaplan-Meier estimation method was used to assess the time to discontinuation and discontinuation rates. Analyses were also completed to assess discontinuation between men and women by phenotypic groups. All tests were two-sided, and p-values ≤ .05 were considered statistically significant.

Results

There were 620 antidepressant discontinuation events discovered from 1015 antidepressant trials included. Overall, the median time to discontinuation for males was 2.6 years and 1.9 years for females (hazard ratio [HR] 0.97 [95% confidence interval (CI): 0.80, 1.19], p = .77). The risk of discontinuation was not different between males and females in any of the phenotype groups, which was consistent in the multivariable analyses. Concomitant use of medications that inhibited or induced antidepressant metabolism increased the overall risk of discontinuation (HR 1.45, 95% CI [1.06, 1.99], p = .020) in a time-dependent analysis.

Discussion

We did not detect a significant difference in risk of antidepressant discontinuation rates between males and females even when accounting for cytochrome P450 phenotype. Future studies should account for whether medications that inhibit or induce antidepressant metabolism may be a crucial factor in antidepressant discontinuation.

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.

The effect of genetic variation in estrogen transportation and metabolism on the severity of menopause symptoms: A study from the RIGHT 10K cohort

OBJECTIVE

The severity of menopause-related symptoms varies considerably among women. The determinants of this variation are incompletely understood. The aim of this study was to assess the association between genetic variation in estrogen metabolism and transport pathways and the severity of menopause symptoms.

METHODS

This was a cross-sectional study of 60 peri- and postmenopausal women in the Mayo Clinic RIGHT study (which involved sequencing of genes involved in drug metabolism and transport), who had also been evaluated in the Women's Health Clinic at Mayo Clinic in Rochester, MN. All participants completed the Menopause Rating Scale (MRS) for assessment of menopause symptoms, including hot flashes. The association between severity of menopause symptoms and the variation in genes encoding 8 enzymes and transporters involved in estrogen metabolism was evaluated.

RESULTS

Lower CYP3A4 activity and higher COMT activity were associated with lower severity of somatic menopause symptoms (p = 0.04 and 0.06, respectively). These associations did not persist after adjustment for hormone therapy use. No differences in MRS scores or hot flash severity were noted among other genetic variant groups. Age at natural menopause was not affected by variations in the genes studied.

CONCLUSION

The current study did not show an association between genetic variation in estrogen metabolism and transport pathways and the severity of menopause symptoms. Further studies with larger sample sizes may be required to understand this potentially complex association.

A real-life pilot study of the clinical application of pharmacogenomics testing on saliva in epilepsy

Response to antiseizure medications (ASMs) can be influenced by several gene polymorphisms, causing either lower efficacy or higher occurrence of adverse drug reactions (ADRs). We investigated the clinical utility of salivary pharmacogenomic testing on epilepsy patients. A commercialized pharmacogenomic salivary test was performed in a cohort of epileptic patients. Genetic variants on five genes (i.e., CYP1A2, CYP2C9, CYP2C19, EPHX1, and ABCB1) involved in common ASMs metabolism were selected. Twenty-one individuals (median age [Q1 -Q3 ]: 15 [6.5-28] years) were enrolled. Six patients harboring the homozygous *1F allele in CYP1A2 could have reduced chance of response to stiripentol due to fast metabolism. CYP2C9 had reduced activity in 10 patients (alleles *2 and *3), potentially affecting phenytoin (PHT), phenobarbital (PB), primidone, lacosamide (LCM), and valproic acid metabolism. Seven patients, carrying the *2 allele of CYP2C19, had an increased risk of ADRs with clobazam (CLB), PB, PHT, LCM, brivaracetam; while one individual with the *17 allele in heterozygosity reported a CLB fast metabolism. Six patients showed a CC polymorphism of EPHX1 associated with the impaired efficacy of carbamazepine. ABCB1 polymorphisms related to drug-resistance (3435 CC) or drug-sensitive phenotype (CT or TT) were found in 6 out of 7 patients. Pharmacogenomic testing on saliva proved easy and safe in clinical practice to convey information for the management of epileptic patients, especially those resistant to treatment or sensitive to severe ADRs.

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.

Development of an extensive workflow for comprehensive clinical pharmacogenomic profiling: lessons from a pilot study on 100 whole exome sequencing data

This pilot study is aimed at implementing an approach for comprehensive clinical pharmacogenomics (PGx) profiling. Fifty patients with cardiovascular diseases and 50 healthy individuals underwent whole-exome sequencing. Data on 1800 PGx genes were extracted and analyzed through deep filtration separately. Theoretical drug induced phenoconversion was assessed for the patients, using sequence2script. In total, 4539 rare variants (including 115 damaging non-synonymous) were identified. Four publicly available PGx bioinformatics algorithms to assign PGx haplotypes were applied to nine selected very important pharmacogenes (VIP) and revealed a 45-70% concordance rate. To ensure availability of the results at point-of-care, actionable variants were stored in a web-hosted database and PGx-cards were developed for quick access and handed to the study subjects. While a comprehensive clinical PGx profile could be successfully extracted from WES data, available tools to interpret these data demonstrated inconsistencies that complicate clinical application.

Rare genetic variant burden in DPYD predicts severe fluoropyrimidine-related toxicity risk

Preemptive targeted pharmacogenetic testing of candidate variations in DPYD is currently being used to limit toxicity associated with fluoropyrimidines. The use of innovative next generation sequencing (NGS) approaches could unveil additional rare (minor allele frequency <1%) genetic risk variants. However, their predictive value and management in clinical practice are still controversial, at least partly due to the challenges associated with functional analyses of rare variants. The aim of this study was to define the predictive power of rare DPYD variants burden on the risk of severe fluoropyrimidine-related toxicity.

The DPYD coding sequence and untranslated regions were analyzed by NGS in 120 patients developing grade 3–5 (NCI-CTC vs3.0) fluoropyrimidine-related toxicity and 104 matched controls (no-toxicity). The functional impact of rare variants was assessed using two different in silico predictive tools (i.e., Predict2SNP and ADME Prediction Framework) and structural modeling. Plasma concentrations of uracil (U) and dihydrouracil (UH2) were quantified in carriers of the novel variants.

Here, we demonstrate that the burden of rare variants was significantly higher in patients with toxicity compared to controls (p = 0.007, Mann-Whitney test). Carriers of at least one rare missense DPYD variant had a 16-fold increased risk in the first cycle and an 11-fold increased risk during the entire course of chemotherapy of developing a severe adverse event compared to controls (p = 0.013 and p = 0.0250, respectively by multinomial regression model). Quantification of plasmatic U/UH2 metabolites and in silico visualization of the encoded protein were consistent with the predicted functional effect for the novel variations.

Analysis and consideration of rare variants by DPYD-sequencing could improve prevention of severe toxicity of fluoropyrimidines and improve patients’ quality of life.

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DPYD genotype-guided dosing reduces fluoropyrimidine (FP) toxicity risk.

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Rare DPYD variants associate with severe FP toxicities.

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Carriers of rare DPYD variants have 11-fold increased risk of toxicity.

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DPYD sequencing and in silico functional prediction could prevent FP toxicity events.

Association between CYP metabolizer phenotypes and selective serotonin reuptake inhibitors induced weight gain: a retrospective cohort study

BACKGROUND

Prescription medications such as selective serotonin reuptake inhibitors (SSRIs), commonly used to treat depression, are associated with weight gain. The role of pharmacogenomics in predicting SSRI-induced weight gain is unclear.

METHODS

In this retrospective cohort study from participants in the Mayo Clinic RIGHT study who were prescribed citalopram, paroxetine, sertraline, or fluoxetine, our aim was to evaluate the association of metabolizer phenotype and total body weight after 6 months of SSRIs initiation. We evaluated the metabolizer phenotypes (poor/intermediate, normal, and rapid/ultra-rapid) of the cytochromes P450 enzymes genes: CYP2C9, CYP2C19, and CYP2D6 known to influence the metabolism of SSRI medications: CYP2C19 for citalopram, CYP2D6 for paroxetine, CYP2D6 and CYP2C19 for sertraline, and CYP2D6 and CYP2C9 fluoxetine. In addition, we assessed the association of metabolizer phenotype and total body weight change at six months following SSRI prescription using parametric analysis of covariance adjusted for baseline body weight and multivariate regression models.

RESULTS

CYP2C19 poor/intermediate metabolizers prescribed citalopram gained significantly more weight than normal or rapid/ultra-rapid metabolizers at 6 months (TBWG %: 2.6 [95% CI 1.3-4.1] vs. 0.4 [95% CI -0.5 - 1.3] vs. -0.1 [-95% CI -1.5-1.1]; p = 0.001). No significant differences in weight outcomes at six months of treatment with paroxetine, sertraline, or fluoxetine were observed by metabolizer status.

CONCLUSIONS

Weight gain observed with citalopram may be mediated by CYP2C19 metabolizer status.

Analytical Validation of a Computational Method for Pharmacogenetic Genotyping from Clinical Whole Exome Sequencing

Germline whole exome sequencing from molecular tumor boards has the potential to be repurposed to support clinical pharmacogenomics. However, accurately calling pharmacogenomics-relevant genotypes from exome sequencing data remains challenging. Accordingly, this study assessed the analytical validity of the computational tool, Aldy, in calling pharmacogenomics-relevant genotypes from exome sequencing data for 13 major pharmacogenes. Germline DNA from whole blood was obtained for 164 subjects seen at an institutional molecular solid tumor board. All subjects had whole exome sequencing from Ashion Analytics and panel-based genotyping from an institutional pharmacogenomics laboratory. Aldy version 3.3 was operationalized on the LifeOmic Precision Health Cloud with copy number fixed to two copies per gene. Aldy results were compared with those from genotyping for 56 star allele-defining variants within CYP2B6, CYP2C8, CYP2C9, CYP2C19, CYP2D6, CYP3A4, CYP3A5, CYP4F2, DPYD, G6PD, NUDT15, SLCO1B1, and TPMT. Read depth was >100× for all variants except CYP3A4∗22. For 75 subjects in the validation cohort, all 3393 Aldy variant calls were concordant with genotyping. Aldy calls for 736 diplotypes containing alleles assessed by both platforms were also concordant. Aldy identified additional star alleles not covered by targeted genotyping for 139 diplotypes. Aldy accurately called variants and diplotypes for 13 major pharmacogenes, except for CYP2D6 variants involving copy number variations, thus allowing repurposing of whole exome sequencing to support clinical pharmacogenomics.