Clinically actionable genotypes among 10,000 patients with preemptive pharmacogenomic testing

Incorporating G6PD genotyping to identify patients with G6PD deficiency

Glucose-6-phosphate-dehydrogenase (G6PD) deficiency is a common X-linked enzyme disorder associated with hemolytic anemia after exposure to fava beans or certain medications. Activity testing is the gold standard for detecting G6PD deficiency; however, this test is affected by various hematologic parameters. Clinical G6PD genotyping is now included in pharmacogenetic arrays and clinical sequencing efforts and may be reconciled with activity results. Patients (n = 1391) enrolled on an institutional pharmacogenetic testing protocol underwent clinical G6PD genotyping for 164 G6PD variants. An algorithm accounting for known interferences with the activity assay is proposed. We developed clinical decision support alerts to inform prescribers when high-risk medications were prescribed, warning of gene-drug interactions and recommending therapy alteration. Of 1391 patients with genotype results, 1334 (95.9%) patients were predicted to have normal G6PD activity, 30 (2.1%) were predicted to have variable G6PD activity and 27 (2%) were predicted to have deficient G6PD activity. Of the 417 patients with a normal genotype and an activity result, 415 (99.5%) had a concordant normal G6PD phenotype. Of the 21 patients with a deficient genotype and an activity result, 18 (85.7%) had a concordant deficient activity result. Genotyping reassigned phenotype in five patients with discordant genotype and activity results: three switched from normal to deficient, and two switched from deficient to normal. G6PD activity and genotyping are two independent testing methods that can be used in conjunction to assign a more informed G6PD phenotype than either method alone.

Pharmacogenetic interventions to improve outcomes in patients with multimorbidity or prescribed polypharmacy: a systematic review

Conventional medicines optimisation interventions in people with multimorbidity and polypharmacy are complex and yet limited; a more holistic and integrated approach to healthcare delivery is required. Pharmacogenetics has potential as a component of medicines optimisation. Studies involving multi-medicine pharmacogenetics in adults with multimorbidity or polypharmacy, reporting on outcomes derived from relevant core outcome sets, were included in this systematic review. Narrative synthesis was undertaken to summarise the data; meta-analysis was inappropriate due to study heterogeneity. Fifteen studies of diverse design and variable quality were included. A small, randomised study involving pharmacist-led medicines optimisation, including pharmacogenetics, suggests this approach could have significant benefits for patients and health systems. However, due to study design heterogeneity and the quality of the included studies, it is difficult to draw generalisable conclusions. Further pragmatic, robust pharmacogenetics studies in diverse, real-world patient populations, are required to establish the benefit of multi-medicine pharmacogenetic screening on patient outcomes.

Identification of pharmacogenetic variants from large scale next generation sequencing data in the Saudi population

It is well documented that drug responses are related to Absorption, Distribution, Metabolism, and Excretion (ADME) characteristics of individual patients. Several studies have identified genetic variability in pharmacogenes, that are either directly responsible for or are associated with ADME, giving rise to individualized treatments. Our objective was to provide a comprehensive overview of pharmacogenetic variation in the Saudi population. We mined next generation sequencing (NGS) data from 11,889 unrelated Saudi nationals, to determine the presence and frequencies of known functional SNP variants in 8 clinically relevant pharmacogenes (CYP2C9, CYP2C19, CYP3A5, CYP4F2, VKORC1, DPYD, TPMT and NUDT15), recommended by the Clinical Pharmacogenetics Implementation Consortium (CPIC), and collectively identified 82 such star alleles. Functionally significant pharmacogenetic variants were prevalent especially in CYP genes (excluding CYP3A5), with 10-44.4% of variants predicted to be inactive or to have decreased activity. In CYP3A5, inactive alleles (87.5%) were the most common. Only 1.8%, 0.7% and 0.7% of NUDT15, TPMT and DPYD variants respectively, were predicted to affect gene activity. In contrast, VKORC1 was found functionally, to be highly polymorphic with 53.7% of Saudi individuals harboring variants predicted to result in decreased activity and 31.3% having variants leading to increased metabolic activity. Furthermore, among the 8 pharmacogenes studied, we detected six rare variants with an aggregated frequency of 1.1%, that among several other ethnicities, were uniquely found in Saudi population. Similarly, within our cohort, the 8 pharmacogenes yielded forty-six novel variants predicted to be deleterious. Based upon our findings, 99.2% of individuals from the Saudi population carry at least one actionable pharmacogenetic variant.

Clinical pharmacogenetic analysis in 5,001 individuals with diagnostic Exome Sequencing data

Exome sequencing is utilized in routine clinical genetic diagnosis. The technical robustness of repurposing large-scale next-generation sequencing data for pharmacogenetics has been demonstrated, supporting the implementation of preemptive pharmacogenetic strategies based on adding clinical pharmacogenetic interpretation to exomes. However, a comprehensive study analyzing all actionable pharmacogenetic alleles contained in international guidelines and applied to diagnostic exome data has not been performed. Here, we carried out a systematic analysis based on 5001 Spanish or Latin American individuals with diagnostic exome data, either Whole Exome Sequencing (80%), or the so-called Clinical Exome Sequencing (20%) (60 Mb and 17 Mb, respectively), to provide with global and gene-specific clinical pharmacogenetic utility data. 788 pharmacogenetic alleles, distributed through 19 genes included in Clinical Pharmacogenetics Implementation Consortium guidelines were analyzed. We established that Whole Exome and Clinical Exome Sequencing performed similarly, and 280 alleles in 11 genes (CACNA1S, CYP2B6, CYP2C9, CYP4F2, DPYD, G6PD, NUDT15, RYR1, SLCO1B1, TPMT, and UGT1A1) could be used to inform of pharmacogenetic phenotypes that change drug prescription. Each individual carried in average 2.2 alleles and overall 95% (n = 4646) of the cohort could be informed of at least one actionable pharmacogenetic phenotype. Differences in variant allele frequency were observed among the populations studied and the corresponding gnomAD population for 7.9% of the variants. In addition, in the 11 selected genes we uncovered 197 novel variants, among which 27 were loss-of-function. In conclusion, we provide with the landscape of actionable pharmacogenetic information contained in diagnostic exomes, that can be used preemptively in the clinics.

Perspectives from the Society for Pediatric Research: pharmacogenetics for pediatricians

This review evaluates the pediatric evidence for pharmacogenetic associations for drugs that are commonly prescribed by or encountered by pediatric clinicians across multiple subspecialties, organized from most to least pediatric evidence. We begin with the pharmacogenetic research that led to the warning of increased risk of death in certain pediatric populations ("ultrarapid metabolizers") who are prescribed codeine after tonsillectomy or adenoidectomy. We review the evidence for genetic testing for thiopurine metabolism, which has become routine in multiple pediatric subspecialties. We discuss the pharmacogenetic research in proton pump inhibitors, for which clinical guidelines have recently been made available. With an increase in the prevalence of behavioral health disorders including attention deficit hyperactivity disorder (ADHD), we review the pharmacogenetic literature on selective serotonin reuptake inhibitors, selective norepinephrine reuptake inhibitors, and ADHD medications. We will conclude this section on the current pharmacogenetic data on ondansetron. We also provide our perspective on how to integrate the current research on pharmacogenetics into clinical care and what further research is needed. We discuss how institutions are managing pharmacogenetic test results and implementing them clinically, and how the electronic health record can be leveraged to ensure testing results are available and taken into consideration when prescribing medications. IMPACT: While many reviews of pharmacogenetics literature are available, there are few focused on pediatrics. Pediatricians across subspecialties will become more comfortable with pharmacogenetics terminology, know resources they can use to help inform their prescribing habits for drugs with known pharmacogenetic associations, and understand the limitations of testing and where further research is needed.

Nine-gene pharmacogenomics profile service: The Mayo Clinic experience

PURPOSE

The Pharmacogenomics (PGx) Profile Service was a proof-of-concept project to implement PGx in patient care at Mayo Clinic.

METHODS

Eighty-two healthy individuals aged 18 and older underwent genotyping of CYP1A2, CYP2C9, CYP2C19, CYP2D6, CYP3A4, CYP3A5, SLCO1B1, HLA-B*58:01, and VKORC1. A PGx pharmacist was involved in ordering, meeting with patients, interpreting, reviewing, and documenting results.

RESULTS

Ninety three percent were CYP1A2 rapid metabolizers, 92% CYP3A4 normal metabolizers, and 88% CYP3A5 poor metabolizers; phenotype frequencies for CYP2C19 and CYP2D6 varied. Seventy-three percent had normal functioning SLCO1B1 transporter, 4% carried the HLA-B*58:01 risk variant, and 35% carried VKORC1 and CYP2C9 variants that increased warfarin sensitivity.

CONCLUSION

Pre-emptive PGx testing offered medication improvement opportunity in 56% of participants for commonly used medications. A collaborative approach involving a PGx pharmacist integrated within a clinical practice with regards to utility of PGx results allowed for implementation of the PGx Profile Service.

KEY POINTS

The Mayo Clinic PGx (PGx) Profile Service was a proof-of-concept project to utilize PGx testing as another clinical tool to enhance medication selection and decrease serious adverse reactions or medication failures. Over one-half of participants in the pilot using the PGx Profile Service were predicted to benefit from pre-emptive PGx testing to guide pharmacotherapy. PGx pharmacists played a crucial role in the PGx Profile Service by educating participants, identifying medication-gene interactions, and providing evidence-based (CPIC and DPWG) PGx recommendations for past, current, and future medication us.

Reducing severe cutaneous adverse and type B adverse drug reactions using pre-stored human leukocyte antigen genotypes

BACKGROUND

Several type B adverse drug reactions (ADRs), especially severe cutaneous adverse reactions (SCARs), are associated with particular human leukocyte antigen (HLA) genotypes. However, pre-stored HLA information obtained from other clinical workups has not been used to prevent ADRs. We aimed to simulate the preemptive use of pre-stored HLA information in electronic medical records to evaluate whether this information can prevent ADRs.

METHODS

We analyzed the incidence and the risk of ADRs for selected HLA alleles (HLA-B*57:01, HLA-B*58:01, HLA-A*31:01, HLA-B*15:02, HLA-B*15:11, HLA-B*13:01, HLA-B*59:01, and HLA-A*32:01) and seven drugs (abacavir, allopurinol, carbamazepine, oxcarbazepine, dapsone, methazolamide, and vancomycin) using pre-stored HLA information of transplant patients based on the Pharmacogenomics Knowledge Base guidelines and experts' consensus.

RESULTS

Among 11,988 HLA-tested transplant patients, 4092 (34.1%) had high-risk HLA alleles, 4583 (38.2%) were prescribed risk drugs, and 580 (4.8%) experienced type B ADRs. Patients with HLA-B*58:01 had a significantly higher incidence of type B ADR and SCARs associated with allopurinol use than that of patients without HLA-B*58:01 (17.2% vs. 11.9%, odds ratio [OR] 1.53 [95% confidence interval {CI} 1.09-2.13], p = 0.001, 2.3% versus 0.3%, OR 7.13 [95% CI 2.19-22.69], p < 0.001). Higher risks of type B ADR and SCARs were observed in patients taking carbamazepine or oxcarbazepine if they had one of HLA-A*31:01, HLA-B*15:02, or HLA-B*15:11 alleles. Vancomycin and dapsone use in HLA-A*32:01 and HLA-B*13:01 carriers, respectively, showed trends toward increased risk of type B ADRs.

CONCLUSION

Utilization of pre-stored HLA data can prevent type B ADRs including SCARs by screening high-risk patients.

Pharmacogenomic testing in paediatrics: clinical implementation strategies

Pharmacogenomics (PGx) relates to the study of genetic factors determining variability in drug response. Implementing PGx testing in paediatric patients can enhance drug safety, helping to improve drug efficacy or reduce the risk of toxicity. Despite its clinical relevance, the implementation of PGx testing in paediatric practice to date has been variable and limited.

As with most paediatric pharmacological studies, there are well‐recognised barriers to obtaining high‐quality PGx evidence, particularly when patient numbers may be small, and off‐label or unlicensed prescribing remains widespread. Furthermore, trials enrolling small numbers of children can rarely, in isolation, provide sufficient PGx evidence to change clinical practice, so extrapolation from larger PGx studies in adult patients, where scientifically sound, is essential.

This review paper discusses the relevance of PGx to paediatrics and considers implementation strategies from a child health perspective. Examples are provided from Canada, the Netherlands and the UK, with consideration of the different healthcare systems and their distinct approaches to implementation, followed by future recommendations based on these cumulative experiences.

Improving the evidence base demonstrating the clinical utility and cost‐effectiveness of paediatric PGx testing will be critical to drive implementation forwards. International, interdisciplinary collaborations will enhance paediatric data collation, interpretation and evidence curation, while also supporting dedicated paediatric PGx educational initiatives. PGx consortia and paediatric clinical research networks will continue to play a central role in the streamlined development of effective PGx implementation strategies to help optimise paediatric pharmacotherapy.

Evaluation of the Veterans Affairs Pharmacogenomic Testing for Veterans (PHASER) clinical program at initial test sites

Aim: The first Plan-Do-Study-Act cycle for the Veterans Affairs Pharmacogenomic Testing for Veterans pharmacogenomic clinical testing program is described. Materials & methods: Surveys evaluating implementation resources and processes were distributed to implementation teams, providers, laboratory and health informatics staff. Survey responses were mapped to the Consolidated Framework for Implementation Research constructs to identify implementation barriers. The Expert Recommendation for Implementing Change strategies were used to address implementation barriers. Results: Survey response rate was 23-73% across personnel groups at six Veterans Affairs sites. Nine Consolidated Framework for Implementation Research constructs were most salient implementation barriers. Program revisions addressed these barriers using the Expert Recommendation for Implementing Change strategies related to three domains. Conclusion: Beyond providing free pharmacogenomic testing, additional implementation barriers need to be addressed for improved program uptake.

Clinical Implications of Combinatorial Pharmacogenomic Tests Based on Cytochrome P450 Variant Selection

Despite the potential to improve patient outcomes, the application of pharmacogenomics (PGx) is yet to be routine. A growing number of PGx implementers are leaning toward using combinatorial PGx (CPGx) tests (i.e., multigene tests) that are reusable over patients’ lifetimes. However, selecting a single best available CPGx test is challenging owing to many patient- and population-specific factors, including variant frequency differences across ethnic groups. The primary objective of this study was to evaluate the detection rate of currently available CPGx tests based on the cytochrome P450 (CYP) gene variants they target. The detection rate was defined as the percentage of a given population with an “altered metabolizer” genotype predicted phenotype, where a CPGx test targeted both gene variants a prospective diplotypes. A potential genotype predicted phenotype was considered an altered metabolizer when it resulted in medication therapy modification based on Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines. Targeted variant CPGx tests found in the Genetic Testing Registry (GTR), gene selection information, and diplotype frequency data from the Pharmacogenomics Knowledge Base (PharmGKB) were used to determine the detection rate of each CPGx test. Our results indicated that the detection rate of CPGx tests covering CYP2C19, CYP2C9, CYP2D6, and CYP2B6 show significant variation across ethnic groups. Specifically, the Sub-Saharan Africans have 63.9% and 77.9% average detection rates for CYP2B6 and CYP2C19 assays analyzed, respectively. In addition, East Asians (EAs) have an average detection rate of 55.1% for CYP2C9 assays. Therefore, the patient’s ethnic background should be carefully considered in selecting CPGx tests.

What Are the Barriers and Enablers to the Implementation of Pharmacogenetic Testing in Mental Health Care Settings?

In psychiatry, the selection of antipsychotics and antidepressants is generally led by a trial-and-error approach. The prescribing of these medications is complicated by sub-optimal efficacy and high rates of adverse drug reactions (ADRs). These both contribute to poor levels of adherence. Pharmacogenetics (PGx) considers how genetic variation can influence an individual’s response to a drug. Pharmacogenetic testing is a tool that could aid clinicians when selecting psychotropic medications, as part of a more personalized approach to prescribing. This may improve the use of and adherence to these medications. Yet to date, the implementation of PGx in mental health environments in the United Kingdom has been slow. This review aims to identify the current barriers and enablers to the implementation of PGx in psychiatry and determine how this can be applied to the uptake of PGx by NHS mental health providers. A systematic searching strategy was developed, and searches were carried out on the PsychInfo, EmBase, and PubMed databases, yielding 11 appropriate papers. Common barriers to the implementation of PGx included cost, concerns over incorporation into current workflow and a lack of knowledge about PGx; whilst frequent enablers included optimism that PGx could lead to precision medicine, reduce ADRs and become a more routine part of psychiatric clinical care. The uptake of PGx in psychiatric care settings in the NHS should consider and overcome these barriers, while looking to capitalize on the enablers identified in this review.

Clinical implementation of drug metabolizing gene-based therapeutic interventions worldwide

Over the last few years, the field of pharmacogenomics has gained considerable momentum. The advances of new genomics and bioinformatics technologies propelled pharmacogenomics towards its implementation in the clinical setting. Since 2007, and especially the last-5 years, many studies have focused on the clinical implementation of pharmacogenomics while identifying obstacles and proposed strategies and approaches for overcoming them in the real world of primary care as well as outpatients and inpatients clinics. Here, we outline the recent pharmacogenomics clinical implementation projects and provide details of the study designs, including the most predominant and innovative, as well as clinical studies worldwide that focus on outpatients and inpatient clinics, and primary care. According to these studies, pharmacogenomics holds promise for improving patients' health in terms of efficacy and toxicity, as well as in their overall quality of life, while simultaneously can contribute to the minimization of healthcare expenditure.

An Analysis of Pharmacogenomic-Guided Pathways and Their Effect on Medication Changes and Hospital Admissions: A Systematic Review and Meta-Analysis

Ninety-five percent of the population are estimated to carry at least one genetic variant that is discordant with at least one medication. Pharmacogenomic (PGx) testing has the potential to identify patients with genetic variants that puts them at risk of adverse drug reactions and sub-optimal therapy. Predicting a patient's response to medications could support the safe management of medications and reduce hospitalization. These benefits can only be realized if prescribing clinicians make the medication changes prompted by PGx test results. This review examines the current evidence on the impact PGx testing has on hospital admissions and whether it prompts medication changes. A systematic search was performed in three databases (Medline, CINAHL and EMBASE) to search all the relevant studies published up to the year 2020, comparing hospitalization rates and medication changes amongst PGx tested patients with patients receiving treatment-as-usual (TAU). Data extracted from full texts were narratively synthesized using a process model developed from the included studies, to derive themes associated to a suggested workflow for PGx-guided care and its expected benefit for medications optimization and hospitalization. A meta-analysis was undertaken on all the studies that report the number of PGx tested patients that had medication change(s) and the number of PGx tested patients that were hospitalized, compared to participants that received TAU. The search strategy identified 5 hospitalization themed studies and 5 medication change themed studies for analysis. The meta-analysis showed that medication changes occurred significantly more frequently in the PGx tested arm across 4 of 5 studies. Meta-analysis showed that all-cause hospitalization occurred significantly less frequently in the PGx tested arm than the TAU. The results show proof of concept for the use of PGx in prescribing that produces patient benefit. However, the review also highlights the opportunities and evidence gaps that are important when considering the introduction of PGx into health systems; namely patient involvement in PGx prescribing decisions, thus a better understanding of the perspective of patients and prescribers. We highlight the opportunities and evidence gaps that are important when considering the introduction of PGx into health systems.

Delivery of Pharmacogenetic Testing with or without Medication Therapy Management in a Community Pharmacy Setting

Objective

The delivery of pharmacogenetic (PGx) testing has primarily been through clinical and hospital settings. We conducted a study to explore the feasibility of delivering PGx testing through community pharmacies, a less-studied setting.

Methods

We conducted a cluster randomized trial of community pharmacies in North Carolina through two approaches: the provision of PGx testing alone or PGx testing with medication therapy management (MTM).

Results

A total of 150 patient participants were enrolled at 17 pharmacies and reported high satisfaction with their testing experience. Participants in the PGx plus MTM arm were more likely to recall a higher number of results (p=0.04) and more likely to clearly understand their choices for prevention or early detection of side effects (p=0.01). A medication or dose change based on the PGx results was made for 8.7% of participants.

Conclusion

Limited differences were observed in the provision of PGx testing as a standalone test or combined with MTM. A limited number of treatment changes were made based on PGx test results. Patient acceptance of PGx testing offered through the community pharmacy was very high, but the addition of MTM did not impact patient-reported perceptions about PGx testing or medication adherence.

Opportunity for Genotype-Guided Prescribing Among Adult Patients in 11 US Health Systems

The value of utilizing a multigene pharmacogenetic panel to tailor pharmacotherapy is contingent on the prevalence of prescribed medications with an actionable pharmacogenetic association. The Clinical Pharmacogenetics Implementation Consortium (CPIC) has categorized over 35 gene-drug pairs as "level A," for which there is sufficiently strong evidence to recommend that genetic information be used to guide drug prescribing. The opportunity to use genetic information to tailor pharmacotherapy among adult patients was determined by elucidating the exposure to CPIC level A drugs among 11 Implementing Genomics In Practice Network (IGNITE)-affiliated health systems across the US. Inpatient and/or outpatient electronic-prescribing data were collected between January 1, 2011 and December 31, 2016 for patients ≥ 18 years of age who had at least one medical encounter that was eligible for drug prescribing in a calendar year. A median of ~ 7.2 million adult patients was available for assessment of drug prescribing per year. From 2011 to 2016, the annual estimated prevalence of exposure to at least one CPIC level A drug prescribed to unique patients ranged between 15,719 (95% confidence interval (CI): 15,658-15,781) in 2011 to 17,335 (CI: 17,283-17,386) in 2016 per 100,000 patients. The estimated annual exposure to at least 2 drugs was above 7,200 per 100,000 patients in most years of the study, reaching an apex of 7,660 (CI: 7,632-7,687) per 100,000 patients in 2014. An estimated 4,748 per 100,000 prescribing events were potentially eligible for a genotype-guided intervention. Results from this study show that a significant portion of adults treated at medical institutions across the United States is exposed to medications for which genetic information, if available, should be used to guide prescribing.

Moving Pharmacogenetics Into Practice: It's All About the Evidence!

The evidence for pharmacogenetics has grown rapidly in recent decades. However, the strength of evidence required for the clinical implementation of pharmacogenetics is highly debated. Therefore, the purpose of this review is to summarize different perspectives on the evidence required for the clinical implementation of pharmacogenetics. First, we present two patient cases that demonstrate how knowledge of pharmacogenetic evidence affected their care. Then we summarize resources that curate pharmacogenetic evidence, types of evidence (with an emphasis on randomized controlled trials [RCT]) and their limitations, and different perspectives from implementers, clinicians, and patients. We compare pharmacogenetics to a historical example (i.e., the evidence required for the clinical implementation of pharmacokinetics/therapeutic drug monitoring), and we provide future perspectives on the evidence for pharmacogenetic panels and the need for more education in addition to evidence. Although there are differences in the interpretation of pharmacogenetic evidence across resources, efforts for standardization are underway. Survey data illustrate the value of pharmacogenetic testing from the patient perspective, with their providers seen as key to ensuring maximum benefit from test results. However, clinicians and practice guidelines from medical societies often rely on RCT data to guide treatment decisions, which are not always feasible or ethical in pharmacogenetics. Thus, recognition of other types of evidence to support pharmacogenetic implementation is needed. Among pharmacogenetic implementers, consistent evidence of pharmacogenetic associations is deemed most critical. Ultimately, moving pharmacogenetics into practice will require consideration of multiple stakeholder perspectives, keeping particularly attuned to the voice of the ultimate stakeholder-the patient.

High-throughput framework for genetic analyses of adverse drug reactions using electronic health records

Understanding the contribution of genetic variation to drug response can improve the delivery of precision medicine. However, genome-wide association studies (GWAS) for drug response are uncommon and are often hindered by small sample sizes. We present a high-throughput framework to efficiently identify eligible patients for genetic studies of adverse drug reactions (ADRs) using “drug allergy” labels from electronic health records (EHRs). As a proof-of-concept, we conducted GWAS for ADRs to 14 common drug/drug groups with 81,739 individuals from Vanderbilt University Medical Center’s BioVU DNA Biobank. We identified 7 genetic loci associated with ADRs at P < 5 × 10⁻⁸, including known genetic associations such as CYP2D6 and OPRM1 for CYP2D6-metabolized opioid ADR. Additional expression quantitative trait loci and phenome-wide association analyses added evidence to the observed associations. Our high-throughput framework is both scalable and portable, enabling impactful pharmacogenomic research to improve precision medicine.

Adverse drug reactions are a considerable burden on the healthcare system. Genetic studies can improve our understanding of the pathophysiological mechanisms of adverse drug reactions but have been hindered by small sample sizes. Drug responses are less often recorded than physiological traits and common diseases. Here, we present a high-throughput framework to efficiently identify eligible patients for genetic studies of adverse drug reactions from electronic health records. We validated our approach by conducting genome-wide association studies for adverse reactions to 14 common drug/drug groups with 81,739 individuals from Vanderbilt University Medical Centre’s BioVU DNA Biobank, identifying 7 genetic loci associated with adverse drug reactions. Our high-throughput framework can enable impactful pharmacogenomic research to help develop clinical guidelines for the delivery of the right drug to the right person.

Implementation of Pharmacogenomics and Artificial Intelligence Tools for Chronic Disease Management in Primary Care Setting

Chronic disease management often requires use of multiple drug regimens that lead to polypharmacy challenges and suboptimal utilization of healthcare services. While the rising costs and healthcare utilization associated with polypharmacy and drug interactions have been well documented, effective tools to address these challenges remain elusive. Emerging evidence that proactive medication management, combined with pharmacogenomic testing, can lead to improved health outcomes and reduced cost burdens may help to address such gaps. In this report, we describe informatic and bioanalytic methodologies that integrate weak signals in symptoms and chief complaints with pharmacogenomic analysis of ~90 single nucleotide polymorphic variants, CYP2D6 copy number, and clinical pharmacokinetic profiles to monitor drug–gene pairs and drug–drug interactions for medications with significant pharmacogenomic profiles. The utility of the approach was validated in a virtual patient case showing detection of significant drug–gene and drug–drug interactions of clinical significance. This effort is being used to establish proof-of-concept for the creation of a regional database to track clinical outcomes in patients enrolled in a bioanalytically-informed medication management program. Our integrated informatic and bioanalytic platform can provide facile clinical decision support to inform and augment medication management in the primary care setting.

Pharmacogenetic genotype and phenotype frequencies in a large Danish population-based case-cohort sample

Pharmacogenetics aims to improve clinical care by studying the relationship between genetic variation and variable drug response. Large population-based datasets could improve our current understanding of pharmacogenetics from selected study populations. We provide real-world pharmacogenetic frequencies of genotypes and (combined) phenotypes of a large Danish population-based case-cohort sample (iPSYCH2012; data of the Integrative Psychiatric Research consortium). The genotyped sample consists of 77,684 individuals, of which 51,464 individuals had diagnoses of severe mental disorders (SMD case-cohort) and 26,220 were individuals randomly selected from the Danish population (population cohort). Array-based genotype data imputed to 8.4 million genetic variants was searched for a selected pharmacogenetic panel of 42 clinically relevant variants and a CYP2D6 gene deletion and duplication. We identified 19 of 42 variants. Minor allele frequencies (MAFs) were consistent with previously reported MAFs, and did not differ between SMD cases and population cohorts. Almost all individuals carried at least one genetic variant (> 99.9%) and 87% carried three or more genetic variants. When genotypes were translated into phenotypes, also > 99.9% of individuals had at least one divergent phenotype (i.e. divergent from the common phenotypes considered normal, e.g. extensive metabolizer). The high number of identified individuals with at least one pharmacogenetic variant or divergent phenotype indicates the importance of pharmacogenetic panel-based genotyping. Combined CYP2C19-CYP2D6 phenotypes revealed that 72.7% of individuals had divergent phenotypes for one or both enzymes. As CYP2D6 and CYP2C19 have an important role in the metabolism of psychotropic drugs, this indicates the relevance of pharmacogenetic testing specifically in individuals using psychotropic drugs.

Pharmacogenomics in the United States Community Pharmacy Setting: The Clopidogrel-CYP2C19 Example

Pharmacogenomics (PGx) is expanding across health-care practice settings, including the community pharmacy. In the United States, models of implementation of PGx in the community pharmacy have described independent services and those layered on to medication therapy management. The drug-gene pair of clopidogrel-CYP2C19 has been a focus of implementation of PGx in community pharmacy and serves as an example of the evolution of the application of drug-gene interaction information to help optimize drug therapy. Expanded information related to this drug-gene pair has been provided by the US Food and Drug Administration and clinical PGx guidelines have and continue to be updated to support clinical decision-making. Most recently direct-to-consumer (DTC) PGx has resulted in patient generated sample collection and submission to a genetic testing-related company for analysis, with reporting of genotype and related phenotype information directly to the patient without a health-care professional guiding or even being involved in the process. The DTC testing approach needs to be considered in the development or modification of PGx service models in the community pharmacy setting. The example of clopidogrel-CYP2C19 is discussed and current models of PGx implementation in the community pharmacy in the United States are presented. New approaches to PGx services are offered as implementation continues to evolve and may now include DTC information.

Implementing Pharmacogenomics Testing: Single Center Experience at Arkansas Children's Hospital

Pharmacogenomics (PGx) is a growing field within precision medicine. Testing can help predict adverse events and sub-therapeutic response risks of certain medications. To date, the US FDA lists over 280 drugs which provide biomarker-based dosing guidance for adults and children. At Arkansas Children’s Hospital (ACH), a clinical PGx laboratory-based test was developed and implemented to provide guidance on 66 pediatric medications for genotype-guided dosing. This PGx test consists of 174 single nucleotide polymorphisms (SNPs) targeting 23 clinically actionable PGx genes or gene variants. Individual genotypes are processed to provide per-gene discrete results in star-allele and phenotype format. These results are then integrated into EPIC- EHR. Genomic indicators built into EPIC-EHR provide the source for clinical decision support (CDS) for clinicians, providing genotype-guided dosing.

Assessment of the Implementation of Pharmacogenomic Testing in a Pediatric Tertiary Care Setting

IMPORTANCE

Pharmacogenomic (PGx) testing provides preemptive pharmacotherapeutic guidance regarding the lack of therapeutic benefit or adverse drug reactions of PGx targeted drugs. Pharmacogenomic information is of particular value among children with complex medical conditions who receive multiple medications and are at higher risk of developing adverse drug reactions.

OBJECTIVES

To assess the implementation outcomes of a PGx testing program comprising both a point-of-care model that examined targeted drugs and a preemptive model informed by whole-genome sequencing that evaluated a broad range of drugs for potential therapy among children in a pediatric tertiary care setting.

DESIGN, SETTING, AND PARTICIPANTS

This cohort study was conducted at The Hospital for Sick Children in Toronto, Ontario, from January 2017 to September 2020. Pharmacogenomic analyses were performed among 172 children who were categorized into 2 groups: a point-of-care cohort and a preemptive cohort. The point-of-care cohort comprised 57 patients referred to the consultation clinic for planned therapy with PGx targeted drugs and/or for adverse drug reactions, including lack of therapeutic benefit, after the receipt of current or past medications. The preemptive cohort comprised 115 patients who received exploratory whole-genome sequencing-guided PGx testing for their heart conditions from the cardiac genome clinic at the Ted Rogers Centre for Heart Research.

EXPOSURES

Patients received PGx analysis of whole-genome sequencing data and/or multiplex genotyping of 6 pharmacogenes (CYP2C19, CYP2C9, CYP2D6, CYP3A5, VKORC1, and TPMT) that have established PGx clinical guidelines.

MAIN OUTCOMES AND MEASURES

The number of patients for whom PGx test results warranted deviation from standard dosing regimens.

RESULTS

A total of 172 children (mean [SD] age, 8.5 [5.6] years; 108 boys [62.8%]) were enrolled in the study. In the point-of-care cohort, a median of 2 target genes (range, 1-5 genes) were investigated per individual, with CYP2C19 being the most frequently examined; genotypes in 21 of 57 children (36.8%) were incompatible with standard treatment regimens. As expected from population allelic frequencies, among the 115 children in the whole-genome sequencing-guided preemptive cohort, 92 children (80.0%) were recommended to receive nonstandard treatment regimens for potential drug therapies based on their 6-gene pharmacogenetic profile.

CONCLUSIONS AND RELEVANCE

In this cohort study, among both the point-of-care and preemptive cohorts, the multiplex PGx testing program provided dosing recommendations that deviated from standard regimens at an overall rate that was similar to the population frequencies of relevant variants.

Towards population-specific pharmacogenomics in the era of next-generation sequencing

Pharmacogenomics (PGx) has essential roles in identifying optimal drug responders, optimizing dosage regimens and avoiding adverse events. Population-specific therapeutic interventions that tackle the genetic root causes of clinical outcomes are an important precision medicine strategy. In this perspective, we discuss next-generation sequencing genotyping and its significance for population-specific PGx applications. We emphasize the potential of NGS for preemptive pharmacogenotyping, which is crucial to population-specific clinical studies and patient care. We also provide examples that use publicly available population-based genomics data for population-specific PGx studies. Last, we discuss the remaining challenges and regulatory efforts towards improvements in this field.

Pharmacogenomics-guided supportive oncology: A tale of two trials

Cancer-related symptoms, like depression, nausea, and pain, are common and negatively affect quality of life. Unfortunately, there is large inter-individual variability in response to supportive care medications for these symptoms. Pharmacogenomics may inform prescribing by identification of those genetically at risk for drug related adverse events or therapeutic failure. While such information can be applied to many drugs, there are specific oncology populations that could greatly benefit from pharmacogenomics-guided supportive care management due to high symptom burden, including those receiving palliative medicine and hematopoietic stem cell transplantation. The goal of this paper is to provide an overview of, and lessons learned from, the development of two prospective pharmacogenomics-guided interventional trials ("Supportive Care PGx Trial" and "Transplant PGx Trial") across two different clinical settings at the Levine Cancer Institute: the Department of Supportive Oncology and the Transplant and Cellular Therapy section. Key considerations included the appropriate study design and endpoints (balancing study goals and resources), dissemination and application of individual pharmacogenetics results, technical details about assay development, and overall care coordination to minimize clinic disruption.

Global distribution of CYP2C19 risk phenotypes affecting safety and effectiveness of medications

Genetic variability of CYP2C19 may affect safety or efficacy of many clinically important medications as outlined in the clinical pharmacogenetics implementation consortium (CPIC) dosing guidelines. To determine the predictive prevalence of high-risk phenotypes due to CYP2C19 genetic variants collectively in the world population and to establish a correlation how the identified high-risk phenotypes may affect safety or effectiveness of drugs, this study was conducted. Frequency of CYP2C19*2, *3 and *17 alleles were obtained from 1000 Genomes project Phase III in line with Fort Lauderdale principles. Phenotypes were assigned using international standardized consensus terms based on the carrier of characteristics alleles. Association of predicted high-risk phenotypes with the safety or effectiveness of medications was gained from CPIC dosing guidelines. Ultrarapid and poor metabolizers were considered as being as high-risk phenotypes for at least ten clinically important medications. Meta-analysis of the prevalence of high-risk phenotypes showed that it was statistically significant (p<0.0001) in different ethnic groups with pooled prevalence of 27.4% (95% CI 18-37%). The present study suggests that African (37.2; 95% CI 34-41%) and European (35.4; 95% CI 31-40%) population are being at particularly higher risk of either sub therapeutic drug responses or toxicities due to combined effects of CYP2C19*2, *3 and *17 variants. Large scale clinical studies are warranted to assess clinical outcomes of these medications considering CYP2C19 pharmacogenomics effects.

Opportunities and challenges for the computational interpretation of rare variation in clinically important genes

Genome sequencing is enabling precision medicine-tailoring treatment to the unique constellation of variants in an individual's genome. The impact of recurrent pathogenic variants is often understood, however there is a long tail of rare genetic variants that are uncharacterized. The problem of uncharacterized rare variation is especially acute when it occurs in genes of known clinical importance with functionally consequential variants and associated mechanisms. Variants of uncertain significance (VUSs) in these genes are discovered at a rate that outpaces current ability to classify them with databases of previous cases, experimental evaluation, and computational predictors. Clinicians are thus left without guidance about the significance of variants that may have actionable consequences. Computational prediction of the impact of rare genetic variation is increasingly becoming an important capability. In this paper, we review the technical and ethical challenges of interpreting the function of rare variants in two settings: inborn errors of metabolism in newborns and pharmacogenomics. We propose a framework for a genomic learning healthcare system with an initial focus on early-onset treatable disease in newborns and actionable pharmacogenomics. We argue that (1) a genomic learning healthcare system must allow for continuous collection and assessment of rare variants, (2) emerging machine learning methods will enable algorithms to predict the clinical impact of rare variants on protein function, and (3) ethical considerations must inform the construction and deployment of all rare-variation triage strategies, particularly with respect to health disparities arising from unbalanced ancestry representation.

PGx in psychiatry: Patients' knowledge, interest, and uncertainty management preferences in the context of pharmacogenomic testing

OBJECTIVE

Pharmacogenomic testing (PGx) is expanding into psychiatric care. PGx could potentially offer a unique benefit to psychiatric patients, providing information about patients' reaction to medications that could reduce the time and financial burdens of drug optimization. The aims of this study were to: (1) examine psychiatry patients' familiarity and interest in PGx, and (2) explore how Uncertainty Management Theory relates to PGx testing in psychiatry.

METHOD

We surveyed psychiatric patients, measuring their PGx familiarity and interest, attitudes toward PGx testing, and preference for managing illness uncertainty.

RESULTS

We analyzed data from 598 patients. Patients' familiarity of PGx was low, but interest was high. Thirty percent of patients were familiar with the test from communication with their healthcare provider or their own online health information seeking. A preference for seeking information was a significant positive predictor of testing interest (p < .001).

CONCLUSION

Psychiatric patients were interested in PGx testing, regardless of their uncertainty management preferences.

PRACTICE IMPLICATIONS

This study is one of the first to examine psychiatric patients' perspectives on PGx testing in mental health care. Our findings show that psychiatric patients are interested in the test and are familiar enough with PGx to be included in future research on the topic.

PharmaKU: A Web-Based Tool Aimed at Improving Outreach and Clinical Utility of Pharmacogenomics

With the tremendous advancements in genome sequencing technology in the field of pharmacogenomics, data have to be made accessible to be more efficiently utilized by broader clinical disciplines. Physicians who require the drug–genome interactome information, have been challenged by the complicated pharmacogenomic star-based classification system. We present here an end-to-end web-based pharmacogenomics tool, PharmaKU, which has a comprehensive easy-to-use interface. PharmaKU can help to overcome several hurdles posed by previous pharmacogenomics tools, including input in hg38 format only, while hg19/GRCh37 is now the most popular reference genome assembly among clinicians and geneticists, as well as the lack of clinical recommendations and other pertinent dosage-related information. This tool extracts genetic variants from nine well-annotated pharmacogenes (for which diplotype to phenotype information is available) from whole genome variant files and uses Stargazer software to assign diplotypes and apply prescribing recommendations from pharmacogenomic resources. The tool is wrapped with a user-friendly web interface, which allows for choosing hg19 or hg38 as the reference genome version and reports results as a comprehensive PDF document. PharmaKU is anticipated to enable bench to bedside implementation of pharmacogenomics knowledge by bringing precision medicine closer to a clinical reality.

Precision medicine in 2030-seven ways to transform healthcare

Precision medicine promises improved health by accounting for individual variability in genes, environment, and lifestyle. Precision medicine will continue to transform healthcare in the coming decade as it expands in key areas: huge cohorts, artificial intelligence (AI), routine clinical genomics, phenomics and environment, and returning value across diverse populations.

Clinical Utility of Pharmacogenomic Data Collected by a Health-System Biobank to Predict and Prevent Adverse Drug Events

INTRODUCTION

Medication-related harm represents a significant issue for patient safety and quality of care. One strategy to avoid preventable adverse drug events is to utilize patient-specific factors such as pharmacogenomics (PGx) to individualize therapy.

OBJECTIVE

We measured the number of patients enrolled in a health-system biobank with actionable PGx results who received relevant medications and assessed the incidence of adverse drug events (ADEs) that might have been prevented had the PGx results been used to inform prescribing.

METHODS

Patients with actionable PGx results in the following four genes with Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines were identified: HLA-A*31:01, HLA-B*15:02, TPMT, and VKORC1. The patients who received interacting medications (carbamazepine, oxcarbazepine, thiopurines, or warfarin) were identified, and electronic health records were reviewed to determine the incidence of potentially preventable ADEs.

RESULTS

Of 36,424 patients with PGx results, 2327 (6.4%) were HLA-A*31:01 positive; 3543 (9.7%) were HLA-B*15:02 positive; 2893 (7.9%) were TPMT intermediate metabolizers; and 4249 (11.7%) were homozygous for the VKORC1 c.1639 G>A variant. Among patients positive for one of the HLA variants who received carbamazepine or oxcarbazepine (n = 92), four (4.3%) experienced a rash that warranted drug discontinuation. Among the TPMT intermediate metabolizers who received a thiopurine (n = 56), 11 (19.6%) experienced severe myelosuppression that warranted drug discontinuation. Among patients homozygous for the VKORC1 c.1639 G>A variant who received warfarin (n = 379), 85 (22.4%) experienced active bleeding and/or international normalized ratio (INR) > 5 that warranted drug discontinuation or dose reduction.

CONCLUSION

Patients with actionable PGx results from a health-system biobank who received relevant medications experienced predictable ADEs. These ADEs may have been prevented if the patients' PGx results were available in the electronic health record with clinical decision support prior to prescribing.

Estimating the potential impact of implementing pre-emptive pharmacogenetic testing in primary care across the UK

AIMS

Pharmacogenetics (PGx) in the UK is currently implemented in secondary care for a small group of high-risk medicines. However, most prescribing takes place in primary care, with a large group of medicines influenced by commonly occurring genetic variations. The goal of this study is to quantitatively estimate the volumes of medicines impacted by implementation of a population-level, pre-emptive pharmacogenetic screening programme for nine genes related to medicines frequently dispensed in primary care in 2019.

METHODS

A large community pharmacy database was analysed to estimate the national incidence of first prescriptions for 56 PGx drugs used in the UK for the period 1 January-31 December 2019. These estimated prescription volumes were combined with phenotype frequency data to estimate the occurrence of actionable drug-gene interactions (DGI) in daily practice in community pharmacies.

RESULTS

In between 19.1 and 21.1% (n = 5 233 353-5 780 595) of all new prescriptions for 56 drugs (n = 27 411 288 new prescriptions/year), an actionable drug-gene interaction (DGI) was present according to the guidelines of the Dutch Pharmacogenetics Working Group and/or the Clinical Pharmacogenetics Implementation Consortium. In these cases, the DGI would result in either increased monitoring, guarding against a maximum ceiling dose or an optional or immediate drug/dose change. An immediate dose adjustment or change in drug regimen accounted for 8.6-9.1% (n = 2 354 058-2 500 283) of these prescriptions.

CONCLUSIONS

Actionable drug-gene interactions frequently occur in UK primary care, with a large opportunity to optimise prescribing.

Evaluation of clinical impact of pharmacogenomics knowledge involved in CPIC guidelines on Chinese pediatric patients

Aim: To evaluate the clinical benefits of implementing pharmacogenomics testing for Chinese pediatric patients. Materials & methods : Based on the drug-gene interactions involved in the Clinical Pharmacogenetics Implementation Consortium guidelines, whole-genome sequencing data from the Chinese Academy of Sciences Precision Medicine Initiative project and the medication data of pediatric patients from a children's hospital, the prevalence of the Chinese population with actionable pharmacogenomic variants was calculated, the prescribing pattern for pediatric patients was analyzed. Results: 37.0% of the drugs involved in the Clinical Pharmacogenetics Implementation Consortium guidelines were used by Chinese pediatric patients, 8.91% inpatients and 0.89% outpatients received at least one pharmacogenomics medication, 1.24% (4803) inpatients and 0.16% (2940) outpatients were estimated to be at high risk of pharmacogenomic-related adverse therapeutic outcomes. Conclusion: Implementing pharmacogenomics testing can improve therapeutic outcomes for many Chinese pediatric patients.

Pharmacogenetic information in Swiss drug labels - a systematic analysis

Implementation of pharmacogenetics (PGx) and individualization of drug therapy is supposed to obviate adverse drug reactions or therapy failure. Health care professionals (HCPs) use drug labels (DLs) as reliable information about drugs. We analyzed the Swiss DLs to give an overview on the currently available PGx instructions. We screened 4306 DLs applying natural language processing focusing on drug metabolism (pharmacokinetics) and we assigned PGx levels following the classification system of PharmGKB. From 5979 hits, 2564 were classified as PGx-relevant affecting 167 substances. 55% (n = 93) were classified as "actionable PGx". Frequently, PGx information appeared in the pharmacokinetics section and in DLs of the anatomic group "nervous system". Unstandardized wording, appearance of PGx information in different sections and unclear instructions challenge HCPs to identify and interpret PGx information and translate it into practice. HCPs need harmonization and standardization of PGx information in DLs to personalize drug therapies and tailor pharmaceutical care.

Retrospective Review of Pharmacogenetic Testing at an Academic Children's Hospital

There is limited evidence to support pharmacogenetic (PGx) testing in children. We conducted a retrospective review of PGx testing among 452 patients at an academic children's hospital to determine the potential utility of PGx in diseases of childhood and to identify targets for future pediatric pharmacogenetic research. An actionable gene-drug pair associated with the 28 genes tested (Clinical Pharmacogenetics Implementation Consortium (CPIC) level A or B, Pharmacogenomics Knowledge Base (PharmGKB) level 1A or B, or US Food and Drug Administration (FDA) recommendation and a PharmGKB level) was present in 98.7% of patients. We identified 203 actionable gene-drug-diagnosis groups based on the indications for each actionable drug listed in Lexicomp. Among patients with an actionable gene-drug-diagnosis group, 49.3% had a diagnosis where the drug was a therapeutic option and PGx could be used to guide treatment selection. Among patients with an associated diagnosis, 30.9% had a prescription for the actionable drug allowing PGx guided dosing. Three genes (CYP2C19, CYP2D6, and CYP3A5) accounted for all the gene-drug-diagnosis groups with matching diagnoses and prescriptions. The most common gene-drug-diagnosis groups with matching diagnoses and prescriptions were CYP2C19-citalopram-escitalopram-depression 3.3% of patients tested; CYP2C19-dexlansoprazole-gastritis-esophagitis 3.1%; CYP2C19-omeprazole-gastritis-esophagitis 2.4%; CYP2D6-atomoxetine-attention deficit hyperactivity disorder 2.2%; and CYP2C19-citalopram-escitalopram-obsessive-compulsive disorder 1.5%. PGx could be used to guide selection of current treatment options or medication dosing in almost half (48.7%) of pediatric patients tested. Mood disorders and gastritis/esophagitis are promising targets for future study of PGx testing because of the high prevalence of these diagnoses and associated actionable gene-drug pairs in the pediatric population.

Practical Barriers and Facilitators Experienced by Patients, Pharmacists and Physicians to the Implementation of Pharmacogenomic Screening in Dutch Outpatient Hospital Care-An Explorative Pilot Study

Pharmacogenomics (PGx) can provide optimized treatment to individual patients while potentially reducing healthcare costs. However, widespread implementation remains absent. We performed a pilot study of PGx screening in Dutch outpatient hospital care to identify the barriers and facilitators to implementation experienced by patients (n = 165), pharmacists (n = 58) and physicians (n = 21). Our results indeed suggest that the current practical experience of healthcare practitioners with PGx is limited, that proper education is necessary, that patients want to know the exact implications of the results, that healthcare practitioners heavily rely on their computer systems, that healthcare practitioners encounter practical problems in the systems used, and a new barrier was identified, namely that there is an unclear allocation of responsibilities between healthcare practitioners about who should discuss PGx with patients and apply PGx results in healthcare. We observed a positive attitude toward PGx among all the stakeholders in our study, and among patients, this was independent of the occurrence of drug-gene interactions during their treatment. Facilitators included the availability of and adherence to Dutch Pharmacogenetics Working Group guidelines. While clinical decision support (CDS) is available and valued in our medical center, the lack of availability of CDS may be an important barrier within Dutch healthcare in general.

Pharmacogenetics at Scale: An Analysis of the UK Biobank

Pharmacogenetics (PGx) studies the influence of genetic variation on drug response. Clinically actionable associations inform guidelines created by the Clinical Pharmacogenetics Implementation Consortium (CPIC), but the broad impact of genetic variation on entire populations is not well understood. We analyzed PGx allele and phenotype frequencies for 487,409 participants in the UK Biobank, the largest PGx study to date. For 14 CPIC pharmacogenes known to influence human drug response, we find that 99.5% of individuals may have an atypical response to at least 1 drug; on average they may have an atypical response to 10.3 drugs. Nearly 24% of participants have been prescribed a drug for which they are predicted to have an atypical response. Non-European populations carry a greater frequency of variants that are predicted to be functionally deleterious; many of these are not captured by current PGx allele definitions. Strategies for detecting and interpreting rare variation will be critical for enabling broad application of pharmacogenetics.

Effect of Pharmacogenetic Testing for Statin Myopathy Risk vs Usual Care on Blood Cholesterol: A Randomized Clinical Trial

IMPORTANCE

Nonadherence to statin guidelines is common. The solute carrier organic anion transporter family member 1B1 (SLCO1B1) genotype is associated with simvastatin myopathy risk and is proposed for clinical implementation. The unintended harms of using pharmacogenetic information to guide pharmacotherapy remain a concern for some stakeholders.

OBJECTIVE

To determine the impact of delivering SLCO1B1 pharmacogenetic results to physicians on the effectiveness of atherosclerotic cardiovascular disease (ASCVD) prevention (measured by low-density lipoprotein cholesterol [LDL-C] levels) and concordance with prescribing guidelines for statin safety and effectiveness.

DESIGN, SETTING, AND PARTICIPANTS

This randomized clinical trial was performed from December 2015 to July 2019 at 8 primary care practices in the Veterans Affairs Boston Healthcare System. Participants included statin-naive patients with elevated ASCVD risk. Data analysis was performed from October 2019 to September 2020.

INTERVENTIONS

SLCO1B1 genotyping and results reporting to primary care physicians at baseline (intervention group) vs after 1 year (control group).

MAIN OUTCOMES AND MEASURES

The primary outcome was the 1-year change in LDL-C level. The secondary outcomes were 1-year concordance with American College of Cardiology-American Heart Association and Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines for statin therapy and statin-associated muscle symptoms (SAMS).

RESULTS

Among 408 patients (mean [SD] age, 64.1 [7.8] years; 25 women [6.1%]), 193 were randomized to the intervention group and 215 were randomized to the control group. Overall, 120 participants (29%) had a SLCO1B1 genotype indicating increased simvastatin myopathy risk. Physicians offered statin therapy to 65 participants (33.7%) in the intervention group and 69 participants (32.1%) in the control group. Compared with patients whose physicians did not know their SLCO1B1 results at baseline, patients whose physicians received the results had noninferior reductions in LDL-C at 12 months (mean [SE] change in LDL-C, -1.1 [1.2] mg/dL in the intervention group and -2.2 [1.3] mg/dL in the control group; difference, -1.1 mg/dL; 90% CI, -4.1 to 1.8 mg/dL; P < .001 for noninferiority margin of 10 mg/dL). The proportion of patients with American College of Cardiology-American Heart Association guideline-concordant statin prescriptions in the intervention group was noninferior to that in the control group (12 patients [6.2%] vs 14 patients [6.5%]; difference, -0.003; 90% CI, -0.038 to 0.032; P < .001 for noninferiority margin of 15%). All patients in both groups were concordant with CPIC guidelines for safe statin prescribing. Physicians documented 2 and 3 cases of SAMS in the intervention and control groups, respectively, none of which was associated with a CPIC guideline-discordant prescription. Among patients with a decreased or poor SLCO1B1 transporter function genotype, simvastatin was prescribed to 1 patient in the control group but none in the intervention group.

CONCLUSIONS AND RELEVANCE

Clinical testing and reporting of SLCO1B1 results for statin myopathy risk did not result in poorer ASCVD prevention in a routine primary care setting and may have been associated with physicians avoiding simvastatin prescriptions for patients at genetic risk for SAMS. Such an absence of harm should reassure stakeholders contemplating the clinical use of available pharmacogenetic results.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT02871934.

A secure system for genomics clinical decision support

We developed a prototype genomic archiving and communications system to securely store genome data and provide clinical decision support (CDS). This system operates on a client-server model. The client encrypts the data, and the server stores data and performs the computations necessary for CDS. Computations are directly performed on encrypted data, and the client decrypts results. The server cannot decrypt inputs or outputs, which provides strong guarantees of security. We have validated our system with three genomics-based CDS applications. The results demonstrate that it is possible to resolve a long-standing dilemma in genomic data privacy and accessibility, by using a principled cryptographical framework and a mathematical representation of genome data and CDS questions.

An Automated Functional Annotation Pipeline That Rapidly Prioritizes Clinically Relevant Genes for Autism Spectrum Disorder

Human genetic studies have implicated more than a hundred genes in Autism Spectrum Disorder (ASD). Understanding how variation in implicated genes influence expression of co-occurring conditions and drug response can inform more effective, personalized approaches for treatment of individuals with ASD. Rapidly translating this information into the clinic requires efficient algorithms to sort through the myriad of genes implicated by rare gene-damaging single nucleotide and copy number variants, and common variation detected in genome-wide association studies (GWAS). To pinpoint genes that are more likely to have clinically relevant variants, we developed a functional annotation pipeline. We defined clinical relevance in this project as any ASD associated gene with evidence indicating a patient may have a complex, co-occurring condition that requires direct intervention (e.g., sleep and gastrointestinal disturbances, attention deficit hyperactivity, anxiety, seizures, depression), or is relevant to drug development and/or approaches to maximizing efficacy and minimizing adverse events (i.e., pharmacogenomics). Starting with a list of all candidate genes implicated in all manifestations of ASD (i.e., idiopathic and syndromic), this pipeline uses databases that represent multiple lines of evidence to identify genes: (1) expressed in the human brain, (2) involved in ASD-relevant biological processes and resulting in analogous phenotypes in mice, (3) whose products are targeted by approved pharmaceutical compounds or possessing pharmacogenetic variation and (4) whose products directly interact with those of genes with variants recommended to be tested for by the American College of Medical Genetics (ACMG). Compared with 1000 gene sets, each with a random selection of human protein coding genes, more genes in the ASD set were annotated for each category evaluated (p ≤ 1.99 × 10⁻²). Of the 956 ASD-implicated genes in the full set, 18 were flagged based on evidence in all categories. Fewer genes from randomly drawn sets were annotated in all categories (x = 8.02, sd = 2.56, p = 7.75 × 10⁻⁴). Notably, none of the prioritized genes are represented among the 59 genes compiled by the ACMG, and 78% had a pathogenic or likely pathogenic variant in ClinVar. Results from this work should rapidly prioritize potentially actionable results from genetic studies and, in turn, inform future work toward clinical decision support for personalized care based on genetic testing.

Pharmacogenomics for Primary Care: An Overview

Most of the prescribing and dispensing of medicines happens in primary care. Pharmacogenomics (PGx) is the study and clinical application of the role of genetic variation on drug response. Mounting evidence suggests PGx can improve the safety and/or efficacy of several medications commonly prescribed in primary care. However, implementation of PGx has generally been limited to a relatively few academic hospital centres, with little adoption in primary care. Despite this, many primary healthcare providers are optimistic about the role of PGx in their future practice. The increasing prevalence of direct-to-consumer genetic testing and primary care PGx studies herald the plausible gradual introduction of PGx into primary care and highlight the changes needed for optimal translation. In this article, the potential utility of PGx in primary care will be explored and on-going barriers to implementation discussed. The evidence base of several drug-gene pairs relevant to primary care will be outlined with a focus on antidepressants, codeine and tramadol, statins, clopidogrel, warfarin, metoprolol and allopurinol. This review is intended to provide both a general introduction to PGx with a more in-depth overview of elements relevant to primary care.

[Pharmacogenomics: precision tool in routine prescription]

Pharmacogenomics is an emerging tool to improve the efficacy and safety of drug treatment through the DNA analysis in the genes related to drug concentrations (pharmacokinetics) and drug actions (pharmacodynamics). Clinicians need to integrate the genomic data in their benefit-risk assessment and then provide the right drug to the right patient at the right time. This tool can help to prevent an ineffective treatment, select right dose and reduce adverse drug reactions that are common in the current practice under the trial-observation-adjustment model. Pharmacogenomics may have extensive impacts on unique paediatric patients to enhance a better relationship between medical professionals and affected children or their guardians and to improve the drug compliance. Clinicians should embrace the advancements in pharmacogenomics and actively participate in clinical research to identify the ancestor-related alleles and develop the population-specific gene panel. It will allow patients to enjoy more achievements in pharmacogenomics by implementing it in first line clinical practice.

Genotype and Phenotype Concordance for Pharmacogenetic Tests Through Proficiency Survey Testing

CONTEXT.—

As pharmacogenetic testing is incorporated into routine care, it is essential for laboratories to provide accurate and consistent results. Certified laboratories must successfully complete proficiency testing.

OBJECTIVES.—

To understand and examine trends in participation and performance of laboratories participating in the College of American Pathologists pharmacogenetic proficiency testing surveys.

DESIGN.—

Results from College of American Pathologists pharmacogenetic proficiency testing challenges from 2012 through 2017 were reviewed for concordance with expected genotype and phenotype for each sample (intended responses).

RESULTS.—

Laboratories correctly reported results for 96.7% to 100% of samples with no variants. Excluding CYP2D6, laboratories correctly detected and reported variant alleles for each gene (93.7%-99.2% correct). CYP2D6 showed lower concordance, with 83.1% of laboratories reporting the intended genotype across all samples; however, in many cases, the laboratories that did not report a variant allele did not test for that allele. Among laboratories reporting the intended genotype, most successfully reported the intended phenotype (85.9%-99.0%).

CONCLUSIONS.—

Although laboratories are generally performing well, there is room for additional improvement, particularly for challenging genes, such as CYP2D6. Efforts in the field of pharmacogenomics to recommend alleles that should be included in clinical tests, identify reference materials, and standardize translation from genotype to phenotype may address some of the remaining variability in results.

The Pharmacogenetics of Rituximab: Potential Implications for Anti-CD20 Therapies in Multiple Sclerosis

There are a broad range of disease-modifying therapies (DMTs) available in relapsing-remitting multiple sclerosis (RRMS), but limited biomarkers exist to personalise DMT choice. All DMTs, including monoclonal antibodies such as rituximab and ocrelizumab, are effective in preventing relapses and preserving neurological function in MS. However, each agent harbours its own risk of therapeutic failure or adverse events. Pharmacogenetics, the study of the effects of genetic variation on therapeutic response or adverse events, could improve the precision of DMT selection. Pharmacogenetic studies of rituximab in MS patients are lacking, but pharmacogenetic markers in other rituximab-treated autoimmune conditions have been identified. This review will outline the wider implications of pharmacogenetics and the mechanisms of anti-CD20 agents in MS. We explore the non-MS rituximab literature to characterise pharmacogenetic variants that could be of prognostic relevance in those receiving rituximab, ocrelizumab or other monoclonal antibodies for MS.

Assessment of the clinical utility of pharmacogenetic guidance in a comprehensive medication management service

INTRODUCTION

Pharmacists are poised to be the health care professionals best suited to provide medication-related consults and services based on a patient's genetics. Despite its potential benefits, the implementation of pharmacogenetic (PGx) testing into primary clinical settings has been slow among medically underserved populations. To our knowledge, this is the first time that PGx-driven recommendations have been incorporated into a Comprehensive Medication Management (CMM) service in a Hispanic population.

OBJECTIVES

The aim of this study is to evaluate the clinical utility of adding PGx guidance into pharmacist-driven CMM.

METHODS

This is a pre- and post-interventional design study. Patients were recruited from a psychologist's clinic. A total of 24 patients had a face-to-face interview with a pharmacist to complete a CMM, Personal Medication Record, and Medication-Related Action Plan (MAP) blind to PGx findings. Collected buccal DNA samples were genotyped using drug-metabolizing enzymes and transporters (DMET) Plus Array.

RESULTS

The pharmacist generated new MAPs for each patient based on PGx results. Genetic variants that could potentially affect the safety and effectiveness of at least one drug in the pharmacotherapy were identified in 96% of patients, for whom the pharmacist changed the initial recommendations. Polymorphisms in genes encoding for isoenzymes CYP2D6, CYP2C19, and CYP2C9 were identified in 83%, 52%, and 41% of patients, respectively. Pharmacists performing CMM identified 22 additional medication problems after PGx determinations. Moreover, they agreed with the clinical utility of PGx in the studied sample based on perceived value of adding PGx to traditional CMM and its utility in the decision-making process of pharmacists.

CONCLUSIONS

The study confirmed the critical role to be played by pharmacists in facilitating the clinical usage of relevant genetic information to optimize drug therapy decisions as well as their involvement on many levels of these multidisciplinary implementation efforts, including championing and leading PGx-guided CMM services.

Precision Medicine for Lysosomal Disorders

Precision medicine (PM) is an emerging approach for disease treatment and prevention that accounts for the individual variability in the genes, environment, and lifestyle of each person. Lysosomal diseases (LDs) are a group of genetic metabolic disorders that include approximately 70 monogenic conditions caused by a defect in lysosomal function. LDs may result from primary lysosomal enzyme deficiencies or impairments in membrane-associated proteins, lysosomal enzyme activators, or modifiers that affect lysosomal function. LDs are heterogeneous disorders, and the phenotype of the affected individual depends on the type of substrate and where it accumulates, which may be impacted by the type of genetic change and residual enzymatic activity. LDs are individually rare, with a combined incidence of approximately 1:4000 individuals. Specific therapies are already available for several LDs, and many more are in development. Early identification may enable disease course prediction and a specific intervention, which is very important for clinical outcome. Driven by advances in omics technology, PM aims to provide the most appropriate management for each patient based on the disease susceptibility or treatment response predictions for specific subgroups. In this review, we focused on the emerging diagnostic technologies that may help to optimize the management of each LD patient and the therapeutic options available, as well as in clinical developments that enable customized approaches to be selected for each subject, according to the principles of PM.

Biomedical Data Science and Informatics Challenges to Implementing Pharmacogenomics with Electronic Health Records

Pharmacogenomic information must be incorporated into electronic health records (EHRs) with clinical decision support in order to fully realize its potential to improve drug therapy. Supported by various clinical knowledge resources, pharmacogenomic workflows have been implemented in several healthcare systems. Little standardization exists across these efforts, however, which limits scalability both within and across clinical sites. Limitations in information standards, knowledge management, and the capabilities of modern EHRs remain challenges for the widespread use of pharmacogenomics in the clinic, but ongoing efforts are addressing these challenges. Although much work remains to use pharmacogenomic information more effectively within clinical systems, the experiences of pioneering sites and lessons learned from those programs may be instructive for other clinical areas beyond genomics. We present a vision of what can be achieved as informatics and data science converge to enable further adoption of pharmacogenomics in the clinic.

Prescription patterns of outpatients and the potential of multiplexed pharmacogenomic testing

BACKGROUND

Pre-emptive pharmacogenomic (PGx) testing is potentially an efficient approach to improve drug safety and efficacy but the target population to test is unclear.

OBJECTIVES

We aim to describe the prescription pattern of PGx drugs among adult medical outpatients.

METHODS

We estimated the 5-year cumulative incidence (CI) for receiving three groups of PGx drugs using competing risks analysis: (i) all PGx drugs, (ii) PGx drugs with guidelines and (iii) PGx drugs with serious clinical effects. Comparisons of CIs were also done by patient characteristics using Gray's test.

RESULTS

The 5-year CIs of receiving any new PGx drug, PGx drug with guidelines and serious clinical effects were 42.6%, 37.3% and 13.7%, respectively. The 5-year CI of receiving any new PGx drug was higher for patients >40 years old (43.6% vs ≤40 years old 36.0%, P < 2.2 × 10^-22 ), Malays and Indians (50.3% and 49.8% vs Chinese 31.1%, P < 2.2 × 10^-22 ), those who attended one of the following four specialties at the index visit compared to other specialties (infectious diseases [46.2% vs 42.6%, P = 2.9 × 10^-4 ], psychiatry [48.3% vs 42.3%, P = 7.4 × 10^-13 ], renal [49.8% vs 40.9%, P < 2.2 × 10^-22 ], and rheumatology and immunology [54.8% vs 41.7%, P < 2.2 × 10^-22 ]) and those prescribed ≥5 drugs at index visit (51.7% vs 0-4 drugs 41.7%, P < 2.2 × 10^-22 ).

CONCLUSIONS

Medical outpatients have a substantial probability of benefiting from pre-emptive PGx testing and this is higher in certain subgroups of patients.

PARC report: a health-systems focus on reimbursement and patient access to pharmacogenomics testing

Pharmacogenomics test coverage and reimbursement are major obstacles to clinical uptake. Several early adopter programs have been successfully initiated through dedicated investments by federal and institutional research funding. As a result of research endeavors, evidence has grown sufficiently to support development of pharmacogenomics guidelines. However, clinical uptake is still limited. Third-party payer support plays an important role in increasing adoption, which to date has been limited to reactive single-gene testing. Access to and interest in direct-to-consumer genetic testing are driving demand for increasing healthcare providers and third-party awareness of this burgeoning field. Pharmacogenomics implementation models developed by early adopters promise to expand patient access and options, as testing continues to increase due to growing consumer interest and falling test prices.