Implementation of preemptive DNA sequence-based pharmacogenomics testing across a large academic medical center: The Mayo-Baylor RIGHT 10K Study

Forging the path to precision medicine in Qatar: a public health perspective on pharmacogenomics initiatives

Pharmacogenomics (PGx) is an important component of precision medicine that promises tailored treatment approaches based on an individual's genetic information. Exploring the initiatives in research that help to integrate PGx test into clinical setting, identifying the potential barriers and challenges as well as planning the future directions, are all important for fruitful PGx implementation in any population. Qatar serves as an exemplar case study for the Middle East, having a small native population compared to a diverse immigrant population, advanced healthcare system, national genome program, and several educational initiatives on PGx and precision medicine. This paper attempts to outline the current state of PGx research and implementation in Qatar within the global context, emphasizing ongoing initiatives and educational efforts. The inclusion of PGx in university curricula and healthcare provider training, alongside precision medicine conferences, showcase Qatar's commitment to advancing this field. However, challenges persist, including the requirement for population specific implementation strategies, complex genetic data interpretation, lack of standardization, and limited awareness. The review suggests policy development for future directions in continued research investment, conducting clinical trials for the feasibility of PGx implementation, ethical considerations, technological advancements, and global collaborations to overcome these barriers.

Implementation of whole-exome sequencing for pharmacogenomics profiling and exploring its potential clinical utilities

Whole-exome sequencing (WES) is widely used in clinical settings; however, the exploration of its use in pharmacogenomic analysis remains limited. Our study compared the variant callings for 28 core absorption, distribution, metabolism and elimination genes by WES and array-based technology using clinical trials samples. The results revealed that WES had a positive predictive value of 0.71-0.92 and a sensitivity of single-nucleotide variants between 0.68 and 0.95, compared with array-based technology, for the variants in the commonly targeted regions of the WES and PhamacoScan™ assay. Besides the common variants detected by both assays, WES identified 200-300 exclusive variants per sample, totalling 55 annotated exclusive variants, including important modulators of metabolism such as rs2032582 (ABCB1) and rs72547527 (SULT1A1). This study highlights the potential clinical advantages of using WES to identify a wider range of genetic variations and enabling precision medicine.

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.

Does Preoperative Pharmacogenomic Testing of Patients Undergoing TKA Improve Postoperative Pain? A Randomized Trial

BACKGROUND

Pharmacogenomics is an emerging and affordable tool that may improve postoperative pain control. One challenge to successful pain control is the large interindividual variability among analgesics in their efficacy and adverse drug events. Whether preoperative pharmacogenomic testing is worthwhile for patients undergoing TKA is unclear.

QUESTIONS/PURPOSES

(1) Are the results of preoperative pharmacogenetic testing associated with lower postoperative pain scores as measured by the Overall Benefit of Analgesic Score (OBAS)? (2) Do the results of preoperative pharmacogenomic testing lead to less total opioids given? (3) Do the results of preoperative pharmacogenomic testing lead to changes in opioid prescribing patterns?

METHODS

Participants of this randomized trial were enrolled from September 2018 through December 2021 if they were aged 18 to 80 years and were undergoing primary TKA under general anesthesia. Patients were excluded if they had chronic kidney disease, a history of chronic pain or narcotic use before surgery, or if they were undergoing robotic surgery. Preoperatively, patients completed pharmacogenomic testing (RightMed, OneOME) and a questionnaire and were randomly assigned to the experimental group or control group. Of 99 patients screened, 23 were excluded, one before randomization; 11 allocated patients in each group did not receive their allocated interventions for reasons such as surgery canceled, patients ultimately undergoing spinal anesthesia, and change in surgery plan. Another four patients in each group were excluded from the analysis because they were missing an OBAS report. This left 30 patients for analysis in the control group and 38 patients in the experimental group. The control and experimental groups were similar in age, gender, and race. Pharmacogenomic test results for patients in the experimental group were reviewed before surgery by a pharmacist, who recommended perioperative medications to the clinical team. A pharmacist also assessed for clinically relevant drug-gene interactions and recommended drug and dose selection according to guidelines from the Clinical Pharmacogenomics Implementation Consortium for each patient enrolled in the study. Patients were unaware of their pharmacogenomic results. Pharmacogenomic test results for patients in the control group were not reviewed before surgery; instead, standard perioperative medications were administered in adherence to our institutional care pathways. The OBAS (maximum 28 points) was the primary outcome measure, recorded 24 hours postoperatively. A two-sample t-test was used to compare the mean OBAS between groups. Secondary measures were the mean 24-hour pain score, total morphine milligram equivalent, and frequency of opioid use. Postoperatively, patients were assessed for pain with a VAS (range 0 to 10). Opioid use was recorded preoperatively, intraoperatively, in the postanesthesia care unit, and 24 hours after discharge from the postanesthesia care unit. Changes in perioperative opioid use based on pharmacogenomic testing were recorded, as were changes in prescription patterns for postoperative pain control. Preoperative characteristics were also compared between patients with and without various phenotypes ascertained from pharmacogenomic test results.

RESULTS

The mean OBAS did not differ between groups (mean ± SD 4.7 ± 3.7 in the control group versus 4.2 ± 2.8 in the experimental group, mean difference 0.5 [95% CI -1.1 to 2.1]; p = 0.55). Total opioids given did not differ between groups or at any single perioperative timepoint (preoperative, intraoperative, or postoperative). We found no difference in opioid prescribing pattern. After adjusting for multiple comparisons, no difference was observed between the treatment and control groups in tramadol use (41% versus 71%, proportion difference 0.29 [95% CI 0.05 to 0.53]; nominal p = 0.02; adjusted p > 0.99).

CONCLUSION

Routine use of pharmacogenomic testing for patients undergoing TKA did not lead to better pain control or decreased opioid consumption. Future studies might focus on at-risk populations, such as patients with chronic pain or those undergoing complex, painful surgical procedures, to test whether pharmacogenomic results might be beneficial in certain circumstances.

LEVEL OF EVIDENCE

Level I, therapeutic study.

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.

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.

Influence of pharmacogenetics on the diversity of response to statins associated with adverse drug reactions

Background

Statins are one of the most prescribed medications in developed countries as the treatment of choice for reducing cholesterol and preventing cardiovascular diseases. However, a large proportion of patients experience adverse drug reactions, especially myotoxicity. Among the factors that influence the diversity of response, pharmacogenetics emerges as a relevant factor of influence in inter-individual differences in response to statins and can be useful in the prevention of adverse drug effects.

Content

A systematic review was performed of current knowledge of the influence of pharmacogenetics on the occurrence and prevention of statin-associated adverse reactions and clinical benefits of preemptive pharmacogenetics testing.

Summary

Genetic variants SLCO1B1 (rs4149056) for all statins; ABCG2 (rs2231142) for rosuvastatin; or CYP2C9 (rs1799853 and rs1057910) for fluvastatin are associated with an increase in muscle-related adverse effects and poor treatment adherence. Besides, various inhibitors of these transporters and biotransformation enzymes increase the systemic exposure of statins, thereby favoring the occurrence of adverse drug reactions.

Outlook

The clinical preemptive testing of this pharmacogenetic panel would largely prevent the incidence of adverse drug reactions. Standardized methods should be used for the identification of adverse effects and the performance and interpretation of genotyping test results. Standardization would allow to obtain more conclusive results about the association between SLCO1B1, ABCG and CYP2C9 variants and the occurrence of adverse drug reactions. As a result, more personalized recommendations could be established for each statin.

Influencia de la farmacogenética en la diversidad de respuesta a las estatinas asociada a las reacciones adversas

Introducción

Las estatinas son unos de los medicamentos más prescritos en los países desarrollados por ser el tratamiento de elección para reducir los niveles de colesterol ayudando así a prevenir la enfermedad cardiovascular. Sin embargo, un gran número de pacientes sufre reacciones adversas, en especial miotoxicidad. Entre los factores que influyen en la diversidad de respuesta, la farmacogenética puede jugar un papel relevante especialmente en la prevención de los efectos adversos asociados a estos medicamentos.

Contenido

Revisión de los conocimientos actuales sobre la influencia de la farmacogenética en la aparición y prevención de las reacciones adversas asociadas a estatinas, así como del beneficio clínico del test farmacogenético anticipado.

Resumen

Variaciones genéticas en SLCO1B1 (rs4149056) para todas las estatinas; en ABCG2 (rs2231142) para rosuvastatina; o en CYP2C9 (rs1799853 y rs1057910) para fluvastatina están asociadas a un incremento de las reacciones adversas de tipo muscular y a una baja adherencia al tratamiento. Además, diversos fármacos inhibidores de estos transportadores y enzimas de biotransformación incrementan la exposición sistémica de las estatinas favoreciendo la aparición de las reacciones adversas.

Perspectiva

La implementación clínica del análisis anticipado de este panel de farmacogenética evitaría en gran parte la aparición de reacciones adversas. Además, la estandarización en la identificación de los efectos adversos, en la metodología e interpretación del genotipo, permitirá obtener resultados más concluyentes sobre la asociación entre las variantes genéticas del SLCO1B1, ABCG y CYP2C9 y la aparición de reacciones adversas y establecer recomendaciones para alcanzar tratamientos más personalizados para cada estatina.

Pharmacists' role in supporting the return of over 10,000 preemptive pharmacogenomics results: The Mayo Clinic experience

PURPOSE

To develop a pharmacist-driven, exploratory pharmacogenomics implementation model with the goal of creating a process for pharmacists to interpret pharmacogenomics results from RIGHT 10K Study samples and provide electronic consults to providers.

SUMMARY

A train-the-trainer model program was initiated whereby pharmacogenomics pharmacists developed a documentation template and a quick reference guide as a standard guide to train other pharmacists. Pharmacists completed electronic consults (e-consults) reviewing pharmacogenomics results, with reference to drug-gene interactions, for patients with "semi-urgent" and "clinically actionable" results, defined as those indicating a potential for gene-drug interactions to cause major harm and those indicating a potential for an adverse drug reaction or reduced efficacy, respectively. Outcomes measured included the number of consults over time, number and role of pharmacists involved, average time to complete e-consults over time, and gene-drug pairs for semi-urgent consults per month. A total of 395 pharmacists were trained. The total number of e-consults completed was 2,843: 61 semi-urgent and 2,782 clinically actionable consults. The average time spent per consult was 24 minutes, and the average number of e-consults per pharmacist was 7. CYP2C19-clopidogrel was the most common gene-drug pair targeted in semi-urgent consults.

CONCLUSION

Pharmacy leaders planning to implement similar pharmacogenomics programs can utilize this data to estimate hiring needs for future pharmacogenomics implementation, while also considering the potential additional cost of developing resources.

Implementation of pre-emptive testing of a pharmacogenomic panel in clinical practice: Where do we stand?

Adverse drug reactions (ADRs) account for a large proportion of hospitalizations among adults and are more common in multimorbid patients, worsening clinical outcomes and burdening healthcare resources. Over the past decade, pharmacogenomics has been developed as a practical tool for optimizing treatment outcomes by mitigating the risk of ADRs. Some single-gene reactive tests are already used in clinical practice, including the DPYD test for fluoropyrimidines, which demonstrates how integrating pharmacogenomic data into routine care can improve patient safety in a cost-effective manner. The evolution from reactive single-gene testing to comprehensive pre-emptive genotyping panels holds great potential for refining drug prescribing practices. Several implementation projects have been conducted to test the feasibility of applying different genetic panels in clinical practice. Recently, the results of a large prospective randomized trial in Europe (the PREPARE study by Ubiquitous Pharmacogenomics consortium) have provided the first evidence that prospective application of a pre-emptive pharmacogenomic test panel in clinical practice, in seven European healthcare systems, is feasible and yielded a 30% reduction in the risk of developing clinically relevant toxicities. Nevertheless, some important questions remain unanswered and will hopefully be addressed by future dedicated studies. These issues include the cost-effectiveness of applying a pre-emptive genotyping panel, the role of multiple co-medications, the transferability of currently tested pharmacogenetic guidelines among patients of non-European origin and the impact of rare pharmacogenetic variants that are not detected by currently used genotyping approaches.

Age-Dependent Sex Differences in the Prevalence of Selective Serotonin Reuptake Inhibitor Treatment: A Retrospective Cohort Analysis

Background: Antidepressants are among the most prescribed medications in the United States. The aim of this study was to explore the prevalence of antidepressant prescriptions and investigate sex differences and age-sex interactions in adults enrolled in the Right Drug, Right Dose, Right Time: Using Genomic Data to Individualize Treatment (RIGHT) study. Materials and Methods: We conducted a retrospective analysis of the RIGHT study. Using electronic prescriptions, we assessed 12-month prevalence of antidepressant treatment. Sex differences and age-sex interactions were evaluated using multivariable logistic regression and flexible recursive smoothing splines. Results: The sample consisted of 11,087 participants (60% women). Antidepressant prescription prevalence was 22.24% (27.96% women, 13.58% men). After adjusting for age and enrollment year, women had significantly greater odds of antidepressant prescription (odds ratio = 2.29; 95% confidence interval = 2.07, 2.54). Furthermore, selective serotonin reuptake inhibitors (SSRIs) had a significant age-sex interaction. While SSRI prescriptions in men showed a sustained decrease with age, there was no such decline for women until after reaching ∼50 years of age. There are important limitations to consider in this study. Electronic prescription data were cross-sectional; information on treatment duration or adherence was not collected; this cohort is not nationally representative; and enrollment occurred over a broad period, introducing confounding by changes in temporal prescribing practices. Conclusions: Underscored by the significant interaction between age and sex on odds of SSRI prescription, our results warrant age to be incorporated as a mediator when investigating sex differences in mental illness, especially mood disorders and their treatment.

The INGENIOUS trial: Impact of pharmacogenetic testing on adverse events in a pragmatic clinical trial

Adverse drug events (ADEs) account for a significant mortality, morbidity, and cost burden. Pharmacogenetic testing has the potential to reduce ADEs and inefficacy. The objective of this INGENIOUS trial (NCT02297126) analysis was to determine whether conducting and reporting pharmacogenetic panel testing impacts ADE frequency. The trial was a pragmatic, randomized controlled clinical trial, adapted as a propensity matched analysis in individuals (N = 2612) receiving a new prescription for one or more of 26 pharmacogenetic-actionable drugs across a community safety-net and academic health system. The intervention was a pharmacogenetic testing panel for 26 drugs with dosage and selection recommendations returned to the health record. The primary outcome was occurrence of ADEs within 1 year, according to modified Common Terminology Criteria for Adverse Events (CTCAE). In the propensity-matched analysis, 16.1% of individuals experienced any ADE within 1-year. Serious ADEs (CTCAE level ≥ 3) occurred in 3.2% of individuals. When combining all 26 drugs, no significant difference was observed between the pharmacogenetic testing and control arms for any ADE (Odds ratio 0.96, 95% CI: 0.78-1.18), serious ADEs (OR: 0.91, 95% CI: 0.58-1.40), or mortality (OR: 0.60, 95% CI: 0.28-1.21). However, sub-group analyses revealed a reduction in serious ADEs and death in individuals who underwent pharmacogenotyping for aripiprazole and serotonin or serotonin-norepinephrine reuptake inhibitors (OR 0.34, 95% CI: 0.12-0.85). In conclusion, no change in overall ADEs was observed after pharmacogenetic testing. However, limitations incurred during INGENIOUS likely affected the results. Future studies may consider preemptive, rather than reactive, pharmacogenetic panel testing.

High-Evidence, Actionable Phenotype Gene Distribution in a Multispecialty, Tertiary Care Clinic: Potentially Actionable Genes and a Referring Department Profile

Background There has been a trend in recent years toward individualized medicine. Pharmacogenomics (PGx) is the use of patient-specific genetic variations to guide medication selection and treatment. Objective: The primary objective was to characterize the population of referring department patients and identify the number of high-evidence, actionable phenotype (HEAP) genes in this referred population to help guide marketing efforts to the most applicable patient populations and departments. Practice description: Located in a destination, tertiary care clinic. Providers refer patients to a Pharmacogenomics (PGx) specialist for a comprehensive medication review using their pharmacogenomic results. Practice Innovation: The practice is innovative because it has been using PGx in the pharmacy and medical practices since 2016 and has been routinely developing and incorporating PGx best practice alerts (BPAs) into the electronic medical record (EMR) since 2020. Evaluation Methods Genetic results were analyzed from a 27-gene PGx panel test which tests for both pharmacokinetic and pharmacodynamic genes. High-Evidence Actionable Phenotypes (HEAP) are defined as phenotypes with guideline support that may suggest an action by healthcare provider. Low-Evidence Nonactionable Phenotypes (LENP) are defined as phenotypes that do not recommend action. Results There were 1,236 atypical phenotypes identified in the 154 patients referred. Of the atypical genes, 39.97% were HEAP and 60.03% were LENP. Of the HEAP's identified, the majority came from CYP2D6, VKORC1, and UGT1A1. At least 1 HEAP was found in 98.7% of patients (n=152). Conclusion There are a variety of High Evidence Actionable Phenotypes (HEAPs) with a high likelihood of at least one HEAP gene in every patient. These phenotypes can result in serious safety concerns when combined with a medication impacted by one of these HEAP genes. Thus, referral to a pharmacogenomics consultation service may lead to an overall decrease in morbidity and mortality with potential cost avoidance.

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.

Pharmacogenomic panel testing provides insight and enhances medication management in people with HIV

OBJECTIVE

Our study aimed to assess the impact of pharmacogenomic panel testing in people with HIV (PWH).

DESIGN

Prospective, observational intervention assessment.

METHODS

One hundred PWH were provided a comprehensive pharmacogenomic panel during routine care visits within the HIV specialty clinic of a large academic medical center. The panel determined the presence of specific genetic variants that could predict response or toxicity to commonly prescribed antiretroviral therapy (ART) and non-ART medications. An HIV specialty pharmacist reviewed the results with participants and the care team. The pharmacist (1) recommended clinically actionable interventions based on the participants' current drug therapy, (2) assessed for genetic explanations for prior medication failures, adverse effects, or intolerances, and (3) advised on potential future clinically actionable care interventions based on individual genetic phenotypes.

RESULTS

Ninety-six participants (median age 53 years, 74% white, 84% men, 89% viral load <50 copies/ml) completed panel testing, yielding 682 clinically relevant pharmacogenomic results (133 major, 549 mild-moderate). Ninety participants (89 on ART) completed follow-up visits with 65 (72%) receiving clinical recommendations based on current medication profiles. Of the 105 clinical recommendations, 70% advised additional monitoring for efficacy or toxicity, and 10% advised alteration of drug therapy. Panel results offered explanation for prior ART inefficacy in one participant and ART intolerance in 29%. Genetic explanation for non-ART toxicity was seen in 21% of participants, with genetic contributors to inefficacy of non-ART therapy identified in 39% of participants.

CONCLUSION

Preliminary data in a small cohort of PWH demonstrates benefit of routine pharmacogenomic panel testing.

Intersecting Pathways in Bioinformatics and Translational Informatics: A One Health Perspective on Key Contributions and Future Directions

OBJECTIVES

To identify and summarize the top bioinformatics and translational informatics (BTI) papers published in 2022 for the International Medical Informatics Association (IMIA) Yearbook 2023.

METHODS

We conducted a comprehensive literature search to identify the top BTI papers, resulting in a set of ten candidate papers. The candidates were reviewed by the section co-editors and external reviewers to select the top three papers from 2022.

RESULTS

From a total of 558 papers, we identified a final candidate list of ten BTI papers for peer-review. These papers apply new statistical frameworks and experimental designs to better capture individual variability in disease and incorporate data that captures differences between single cells and across environmental exposures. In addition, they highlight the importance of model generalization across diverse cohorts and scalability to large medical centers.

CONCLUSIONS

We note several important trends in the candidate top BTI papers this year, including a continued focus on developing accurate and scalable computational models to predict disease risk across diverse cohorts and new strategies to capture the molecular heterogeneity of disease.

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.

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.

Cytochrome P450 Transcriptional Regulation by Testis-Specific Y-Encoded-Like Protein: Identification of Novel Upstream Transcription Factors

Cytochrome P450s (CYPs) display significant inter-individual variation in expression, much of which remains unexplained by known CYP single-nucleotide polymorphisms (SNPs). Testis-specific Y-encoded-like proteins (TSPYLs) are transcriptional regulators for several drug-metabolizing CYPs including CYP3A4 However, transcription factors (TFs) that might influence CYP expression through an effect on TSPYL expression are unknown. Therefore, we studied regulators of TSPYL expression in hepatic cell lines and their possible SNP-dependent variation. Specifically, we identified candidate TFs that might influence TSPYL expression using the ENCODE ChIPseq database. Subsequently, the expression of TSPYL1/2/4 as well as that of selected CYP targets for TSPYL regulation were assayed in hepatic cell lines before and after knockdown of TFs that might influence CYP expression through TSPYL-dependent mechanisms. Those results were confirmed by studies of TF binding to TSPYL1/2/4 gene promoter regions. In hepatic cell lines, knockdown of the REST and ZBTB7A TFs resulted in decreased TSPYL1 and TSPYL4 expression and increased CYP3A4 expression, changes reversed by TSPYL1/4 overexpression. Potential binding sites for REST and ZBTB7A on the promoters of TSPYL1 and TSPYL4 were confirmed by chromatin immunoprecipitation. Finally, common SNP variants in upstream binding sites on the TSPYL1/4 promoters were identified and luciferase reporter constructs confirmed SNP-dependent modulation of TSPYL1/4 gene transcription. In summary, we identified REST and ZBTB7A as regulators of the expression of TSPYL genes which themselves can contribute to regulation of CYP expression and-potentially-of drug metabolism. SNP-dependent modulation of TSPYL transcription may contribute to individual variation in both CYP expression and-downstream-drug response phenotypes. SIGNIFICANCE STATEMENT: Testis-specific Y-encoded-like proteins (TSPYLs) are transcriptional regulators of cytochrome P450 (CYP) gene expression. Here, we report that variation in TSPYL expression as a result of the effects of genetically regulated TSPYL transcription factors is an additional factor that could result in downstream variation in CYP expression and potentially, as a result, variation in drug biotransformation.

Chronic Serotonin Toxicity in the Older Patient With Polypharmacy

Clinical pharmacists with experience may identify prescribing patterns resulting in iatrogenic disease, which is commonly encountered in geriatric populations where polypharmacy is common. Serotonin toxicity is one toxidrome clinicians may identify, where specific medications are used in treatment. As a result of their pharmacology training, pharmacists may identify toxidromes caused by medications that other clinicians may overlook. Pharmacogenomic (PGx) testing can provide added insight into a potentially iatrogenic cause for serotonin toxicity, because testing can elucidate how well an individual patient may metabolize serotonergic medications. Using PGx as a resource in addition to clinical experience, pharmacists can better guide therapy in the geriatric, polypharmacy population to avoid serotonin toxicity.

Characterizing pharmacogenetic programs using the consolidated framework for implementation research: A structured scoping review

Several healthcare organizations have developed pre-emptive pharmacogenetic testing programs, where testing is undertaken prior to the prescription of a medicine. This review characterizes the barriers and facilitators which influenced the development of these programs. A bidirectional citation searching strategy identified relevant publications before a standardized data extraction approach was applied. Publications were grouped by program and data synthesis was undertaken using the Consolidated Framework for Implementation Research (CFIR). 104 publications were identified from 40 programs and 4 multi-center initiatives. 26 (66%) of the programs were based in the United States and 95% in high-income countries. The programs were heterogeneous in their design and scale. The Characteristics of the Intervention, Inner Setting, and Process domains were referenced by 92.5, 80, and 77.5% of programs, respectively. A positive institutional culture, leadership engagement, engaging stakeholders, and the use of clinical champions were frequently described as facilitators to implementation. Clinician self-efficacy, lack of stakeholder knowledge, and the cost of the intervention were commonly cited barriers. Despite variation between the programs, there were several similarities in approach which could be categorized via the CFIR. These form a resource for organizations planning the development of pharmacogenetic programs, highlighting key facilitators which can be leveraged to promote successful implementation.

A Mixed-Methods Protocol to Identify Best Practices for Implementing Pharmacogenetic Testing in Clinical Settings

Using a patient’s genetic information to inform medication prescriptions can be clinically effective; however, the practice has not been widely implemented. Health systems need guidance on how to engage with providers to improve pharmacogenetic test utilization. Approaches from the field of implementation science may shed light on the complex factors affecting pharmacogenetic test use in real-world settings and areas to target to improve utilization. This paper presents an approach to studying the application of precision medicine that utilizes mixed qualitative and quantitative methods and implementation science frameworks to understand which factors or combinations consistently account for high versus low utilization of pharmocogenetic testing. This approach involves two phases: (1) collection of qualitative and quantitative data from providers—the cases—at four clinical institutions about their experiences with, and utilization of, pharmacogenetic testing to identify salient factors; and (2) analysis using a Configurational Comparative Method (CCM), using a mathematical algorithm to identify the minimally necessary and sufficient factors that distinguish providers who have higher utilization from those with low utilization. Advantages of this approach are that it can be used for small to moderate sample sizes, and it accounts for conditions found in real-world settings by demonstrating how they coincide to affect utilization.