Clinical Pharmacogenetics Implementation Consortium Guidelines for HLA-B Genotype and Abacavir Dosing: 2014 update

The expanding role of HLA gene tests for predicting drug side effects

Adverse drug reactions can be either dose-dependent (Type A) or idiosyncratic (Type B). Type B adverse drug reactions tend to be extremely rare and difficult to predict. They are usually immune-mediated. Examples include severe skin reactions and drug-induced liver injury. For many commonly prescribed drugs (such as antibiotics), the risk of developing an idiosyncratic adverse drug reaction is influenced by variability in the human leukocyte antigen (HLA) genes. Because these HLA-mediated adverse drug reactions can be lethal, there is growing interest in defining which specific drug-gene relationships might benefit from pre-emptive HLA genotyping and automated clinical decision support. This review summarizes the literature for HLA-mediated adverse reactions linked to common drugs.

Prevalence of the HLA-B*5701 Allele and Abacavir Hypersensitivity in Saudi HIV Patients: A Multicenter Study

Introduction Human immunodeficiency virus (HIV) incidence and prevalence are increasing in Saudi Arabia, with a total prevalence of 12,000 in 2020. Treatment of HIV patients includes multiple regimens that may involve abacavir (ABC), which is a potent drug for treating HIV and can be used as a single or combined pill. Unfortunately, its use was limited by the known associated hypersensitivity reaction (HSR). A worldwide literature review over the past decades reported that the incidence of ABC-related HSR is 5-8%. Methods The study was a cross-sectional multicentric study involving five governmental hospitals in Saudi Arabia and included all HIV patients who were following in these centers. Results Out of 3082 patients, 1293 were tested for HLA-B*5701. The prevalence for ABC-HSR is 1.59%, with variability among the five hospitals, with the highest in King Fahad Hospital in Hafuf (KFH-H) at 4.00% and the lowest in Dammam Medical Complex (DMC) at 0.49%. In previous studies, HLA-B*5701 associated with ABC-HSR varied among different ethnic groups. Our study showed that two patients developed ABC-HSR clinically while they were both negative for HLA-B*5701. Conclusion The fact that patients with negative genetic testing are still at risk of developing ABC-HSR makes continuing screening for HLA-B*5701 status essential, as the consequences of missing such a life-threatening HSR could be detrimental.

Statistical assessment of biomarker replicability using MAJAR method

In the era of precision medicine, many biomarkers have been discovered to be associated with drug efficacy and safety responses, which can be used for patient stratification and drug response prediction. Due to the small sample size and limited power of randomized clinical studies, meta-analysis is usually conducted to aggregate all available studies to maximize the power for identifying prognostic and predictive biomarkers. However, it is often challenging to find an independent study to replicate the discoveries from the meta-analysis (e.g. meta-analysis of pharmacogenomics genome-wide association studies (PGx GWAS)), which seriously limits the potential impacts of the discovered biomarkers. To overcome this challenge, we develop a novel statistical framework, MAJAR (meta-analysis of joint effect associations for biomarker replicability assessment), to jointly test prognostic and predictive effects and assess the replicability of identified biomarkers by implementing an enhanced expectation-maximization algorithm and calculating their posterior-probability-of-replicabilities and Bayesian false discovery rates (Fdr). Extensive simulation studies were conducted to compare the performance of MAJAR and existing methods in terms of Fdr, power, and computational efficiency. The simulation results showed improved statistical power with well-controlled Fdr of MAJAR over existing methods and robustness to outliers under different data generation processes. We further demonstrated the advantages of MAJAR over existing methods by applying MAJAR to the PGx GWAS summary statistics data from a large cardiovascular randomized clinical trial. Compared to testing main effects only, MAJAR identified 12 novel variants associated with the treatment-related low-density lipoprotein cholesterol reduction from baseline.

Implementation of Pharmacogenetics in First-Line Care: Evaluation of Its Use by General Practitioners

Pharmacogenetics (PGx) can explain/predict drug therapy outcomes. There is, however, unclarity about the use and usefulness of PGx in primary care. In this study, we investigated PGx tests ordered by general practitioners (GPs) in 2021 at Dept. Clinical Chemistry, Erasmus MC, and analyzed the gene tests ordered, drugs/drug groups, reasons for testing and single-gene versus panel testing. Additionally, a survey was sent to 90 GPs asking about their experiences and barriers to implementing PGx. In total, 1206 patients and 6300 PGx tests were requested by GPs. CYP2C19 was requested most frequently (17%), and clopidogrel was the most commonly indicated drug (23%). Regarding drug groups, antidepressants (51%) were the main driver for requesting PGx, followed by antihypertensives (26%). Side effects (79%) and non-response (27%) were the main indicators. Panel testing was preferred over single-gene testing. The survey revealed knowledge on when and how to use PGx as one of the main barriers. In conclusion, PGx is currently used by GPs in clinical practice in the Netherlands. Side effects are the main reason for testing, which mostly involves antidepressants. Lack of knowledge is indicated as a major barrier, indicating the need for more education on PGx for GPs.

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.

Integrating multiple traits for improving polygenic risk prediction in disease and pharmacogenomics GWAS

Polygenic risk score (PRS) has been recently developed for predicting complex traits and drug responses. It remains unknown whether multi-trait PRS (mtPRS) methods, by integrating information from multiple genetically correlated traits, can improve prediction accuracy and power for PRS analysis compared with single-trait PRS (stPRS) methods. In this paper, we first review commonly used mtPRS methods and find that they do not directly model the underlying genetic correlations among traits, which has been shown to be useful in guiding multi-trait association analysis in the literature. To overcome this limitation, we propose a mtPRS-PCA method to combine PRSs from multiple traits with weights obtained from performing principal component analysis (PCA) on the genetic correlation matrix. To accommodate various genetic architectures covering different effect directions, signal sparseness and across-trait correlation structures, we further propose an omnibus mtPRS method (mtPRS-O) by combining P values from mtPRS-PCA, mtPRS-ML (mtPRS based on machine learning) and stPRSs using Cauchy Combination Test. Our extensive simulation studies show that mtPRS-PCA outperforms other mtPRS methods in both disease and pharmacogenomics (PGx) genome-wide association studies (GWAS) contexts when traits are similarly correlated, with dense signal effects and in similar effect directions, and mtPRS-O is consistently superior to most other methods due to its robustness under various genetic architectures. We further apply mtPRS-PCA, mtPRS-O and other methods to PGx GWAS data from a randomized clinical trial in the cardiovascular domain and demonstrate performance improvement of mtPRS-PCA in both prediction accuracy and patient stratification as well as the robustness of mtPRS-O in PRS association test.

PAnno: A pharmacogenomics annotation tool for clinical genomic testing

Introduction: Next-generation sequencing (NGS) technologies have been widely used in clinical genomic testing for drug response phenotypes. However, the inherent limitations of short reads make accurate inference of diplotypes still challenging, which may reduce the effectiveness of genotype-guided drug therapy. Methods: An automated Pharmacogenomics Annotation tool (PAnno) was implemented, which reports prescribing recommendations and phenotypes by parsing the germline variant call format (VCF) file from NGS and the population to which the individual belongs. Results: A ranking model dedicated to inferring diplotypes, developed based on the allele (haplotype) definition and population allele frequency, was introduced in PAnno. The predictive performance was validated in comparison with four similar tools using the consensus diplotype data of the Genetic Testing Reference Materials Coordination Program (GeT-RM) as ground truth. An annotation method was proposed to summarize prescribing recommendations and classify drugs into avoid use, use with caution, and routine use, following the recommendations of the Clinical Pharmacogenetics Implementation Consortium (CPIC), etc. It further predicts phenotypes of specific drugs in terms of toxicity, dosage, efficacy, and metabolism by integrating the high-confidence clinical annotations in the Pharmacogenomics Knowledgebase (PharmGKB). PAnno is available at https://github.com/PreMedKB/PAnno. Discussion: PAnno provides an end-to-end clinical pharmacogenomics decision support solution by resolving, annotating, and reporting germline variants.

Pharmacogenomics in Asians: Differences and similarities with other human populations

INTRODUCTION

Various pharmacogenomic (PGx) variants differ widely in different ethnicities. and clinical outcomes associated with these variants may also be substantially varied. Literature was searched in different databases, i.e. PubMed, ScienceDirect, Web of Science, and PharmGKB, from inception to 30 June 2022 for this review.

AREAS COVERED

Certain PGx variants were distinctly varied in Asian populations compared to the other human populations, e.g. CYP2C19*2,*3,*17; CYP2C9*2,*3; CYP2D6*4,*5,*10,*41; UGT1A1*6,*28; HLA-B*15:02, HLA-B*15:21, HLA-B*58:01, and HLA-A*31:01. However, certain other variants do not vary greatly between Asian and other ethnicities, e.g. CYP3A5*3; ABCB1, and SLCO1B1*5. As evident in this review, the risk of major adverse cardiovascular events (MACE) was much stronger in Asian patients taking clopidogrel and who inherited the CYP2C19 loss-of-function alleles, e.g. CYP2C19*2 and*3, when compared to the western/Caucasian patients. Additionally, the risk of carbamazepine-induced severe cutaneous adverse drug reactions (SCARs) for the patients inheriting HLA-B*15:02 and HLA-B*15:21 alleles varied significantly between Asian and other ethnicities. In contrast, both Caucasian and Asian patients inheriting the SLCO1B1*5 variant possessed a similar magnitude of muscle toxicity, i.e. myopathy.

EXPERT OPINION

Asian countries should take measures toward expanding PGx research, as well as initiatives for the purposes of obtaining clinical benefits from this newly evolving and economically viable treatment model.

The Implementation of Pharmacogenetics in the United Kingdom

There is considerable inter-individual variability in the effectiveness and safety of pharmaceutical interventions. This phenomenon can be attributed to a multitude of factors; however, it is widely acknowledged that common genetic variation affecting drug absorption or metabolism play a substantial contributory role. This is a concept known as pharmacogenetics. Understanding how common genetic variants influence responses to medications, and using this knowledge to inform prescribing practice, could yield significant advantages for both patients and healthcare systems. Some health services around the world have introduced pharmacogenetics into routine practice, whereas others are less advanced along the implementation pathway. This chapter introduces the field of pharmacogenetics, the existing body of evidence, and discusses barriers to implementation. The chapter will specifically focus on efforts to introduce pharmacogenetics in the NHS, highlighting key challenges related to scale, informatics, and education.

The Prevalence of HLA-B*57 Serotype Associated with Hypersensitivity Reactions in the Treatment of HIV İnfection in the Turkish Population

OBJECTIVES

The aim of our study is to reveal the prevalence of HLA-B*57 in the Turkish population and to provide new perspectives to physicians starting abacavir therapy in HIV patients.

BACKGROUND

Abacavir, one of the drugs used to treat HIV infection, can cause hypersensitivity reactions in some patients. These hypersensitivity reactions have been shown to be associated with the HLA-B*57:01 allele. High-resolution HLA-B*57:01 scanning has a time and cost disadvantage compared with low-resolution HLA-B*57 scanning. Before starting abacavir treatment, we will discuss whether high-resolution scanning is more beneficial in individuals who are positive on HLAB* 57 screening. This is the study with the largest cohort to investigate the prevalence of HLA-B*57 in Turkey.

METHODS

The results of 25 thousand 318 people who applied to Bursa Uludağ University Faculty of Medicine, Department of Immunology for HLA-B* typing were scanned.

RESULTS

In our study, the HLA-B*57 serotype was detected in 827 (3.3%) individuals.

CONCLUSION

Considering these results, it can be assumed that the prevalence of HLA-B*57:01 in Turkey is lower than 3.3%. Instead of a high-resolution HLA-B*57:01 scan in all patients starting abacavir therapy, a high-resolution HLA-B*57:01 scan might be of greater benefit in patients who are positive on a low-resolution HLA-B*57 scan.

Implementation of pharmacogenomics: Where are we now?

Pharmacogenomics (PGx), examining the effect of genetic variation on interpatient variation in drug disposition and response, has been widely studied for several decades. However, as cost, as well as turnaround time associated with PGx testing, has significantly improved, the use of PGx in the clinical setting has been gaining momentum. Nevertheless, challenges have emerged in the broader clinical implementation of PGx. In this review, we will outline current models of PGx delivery and methodologies of evaluation, and discuss clinically relevant PGx tests and associated medications. Additionally, we will describe our approach for the broad implementation of pre-emptive DPYD genotyping in patients taking fluoropyrimidines in Ontario, Canada, as an example of clinically actionable PGx testing with sufficient clinical evidence of patient benefit that can become a new standard of patient care. We will highlight challenges associated with PGx testing, including a lack of diversity in PGx studies as well as general limitations that impact the broad adoption of PGx testing. Lastly, we examine the future of PGx, discussing new clinical targets, methodologies and analysis approaches.

How paediatric drug development and use could benefit from OMICs: a c4c expert group white paper

The safety and efficacy of pharmacotherapy in children, particularly preterms, neonates, and infants, is limited by a paucity of good quality data from prospective clinical drug trials. A specific challenge is the establishment of valid biomarkers. OMICs technologies may support these efforts, by complementary information about targeted and non-targeted molecules through systematic characterization and quantitation of biological samples. OMICs technologies comprise at least genomics, epigenomics, transcriptomics, proteomics, metabolomics, and microbiomics in addition to the patient's phenotype. OMICs technologies are in part hypothesis-generating allowing an in depth understanding of disease pathophysiology and pharmacological mechanisms. Application of OMICs technologies in paediatrics faces major challenges before routine adoption. First, developmental processes need to be considered, including a sub-division into specific age groups as developmental changes clearly impact OMICs data. Second, compared to the adult population, the number of patients is limited as well as type and amount of necessary biomaterial, especially in neonates and preterms. Thus, advanced trial designs and biostatistical methods, non-invasive biomarkers, innovative biobanking concepts including data and samples from healthy children, as well as analytical approaches (e.g. liquid biopsies) should be addressed to overcome these obstacles. The ultimate goal is to link OMICs technologies with innovative analysis tools, like artificial intelligence at an early stage. The use of OMICs data based on a feasible approach will contribute to identify complex phenotypes and subpopulations of patients to improve development of medicines for children with potential economic advantages.

Human Leukocyte Antigen (HLA) Testing in Pharmacogenomics

The genetic region on the short arm of chromosome 6 where the human leukocyte antigen (HLA) genes are located is the major histocompatibility complex. The genes in this region are highly polymorphic, and some loci have a high degree of homology with other genes and pseudogenes. Histocompatibility testing has traditionally been performed in the setting of transplantation and involves determining which specific alleles are present. Several HLA alleles have been associated with disease risk or increased risk of adverse drug reaction (ADR) when treated with certain medications. Testing for these applications differs from traditional histocompatibility in that the desired result is simply presence or absence of the allele of interest, rather than determining which allele is present. At present, the majority of HLA typing is done by molecular methods using commercially available kits. A subset of pharmacogenomics laboratories has developed their own methods, and in some cases, query single nucleotide variants associated with certain HLA alleles rather than directly testing for the allele. In this chapter, a brief introduction to the HLA system is provided, followed by an overview of a variety of testing technologies including those specifically used in pharmacogenomics, and the chapter concludes with details regarding specific HLA alleles associated with ADR.

A Comprehensive Review of HLA and Severe Cutaneous Adverse Drug Reactions: Implication for Clinical Pharmacogenomics and Precision Medicine

Human leukocyte antigen (HLA) encoded by the HLA gene is an important modulator for immune responses and drug hypersensitivity reactions as well. Genetic polymorphisms of HLA vary widely at population level and are responsible for developing severe cutaneous adverse drug reactions (SCARs) such as Stevens-Johnson syndrome (SJS), toxic epidermal necrolysis (TEN), drug reaction with eosinophilia and systemic symptoms (DRESS), maculopapular exanthema (MPE). The associations of different HLA alleles with the risk of drug induced SJS/TEN, DRESS and MPE are strongly supportive for clinical considerations. Prescribing guidelines generated by different national and international working groups for translation of HLA pharmacogenetics into clinical practice are underway and functional in many countries, including Thailand. Cutting edge genomic technologies may accelerate wider adoption of HLA screening in routine clinical settings. There are great opportunities and several challenges as well for effective implementation of HLA genotyping globally in routine clinical practice for the prevention of drug induced SCARs substantially, enforcing precision medicine initiatives.

Efficacy of personal pharmacogenomic testing as an educational tool in the pharmacy curriculum: A nonblinded, randomized controlled trial

Personal genomic educational testing (PGET) has been suggested as a strategy to improve student learning for pharmacogenomics (PGx), but no randomized studies have evaluated PGET’s educational benefit. We investigated the effect of PGET on student knowledge, comfort, and attitudes related to PGx in a nonblinded, randomized controlled trial. Consenting participants were randomized to receive PGET or no PGET (NPGET) during 4 subsequent years of a PGx course. All participants completed a pre‐survey and post‐survey designed to assess (1) PGx knowledge, (2) comfort with PGx patient education and clinical skills, and (3) attitudes toward PGx. Instructors were blinded to PGET assignment. The Wilcoxon Rank Sum test was used to compare pre‐survey and post‐survey PGx knowledge, comfort, and attitudes. No differences in baseline characteristics were observed between PGET (n = 117) and NPGET (n = 116) participants. Among all participants, significant improvement was observed in PGx knowledge (mean 57% vs. 39% correct responses; p < 0.001) with similar results for student comfort and attitudes. Change in pre/post‐PGx knowledge, comfort, and attitudes were not significantly different between PGET and NPGET groups (mean 19.5% vs. 16.7% knowledge improvement, respectively; p = 0.41). Similar results were observed for PGET participants carrying a highly actionable PGx variant versus PGET participants without an actionable variant. Significant improvement in Likert scale responses were observed in PGET versus NPGET for questions that assessed student engagement (p = 0.020) and reinforcement of course concepts (p = 0.006). Although some evidence of improved engagement and participation was observed, the results of this study suggest that PGET does not directly improve student PGx knowledge, comfort, and attitudes.

Genotyping HLA alleles to predict the development of Severe cutaneous adverse drug reactions (SCARs): state-of-the-art

Introduction: Pharmacogenomics has great potential in reducing drug-induced severe cutaneous adverse drug reactions (SCARs). Pharmacogenomic studies have revealed an association between HLA genes and SCARs including acute generalized exanthematous pustulosis (AGEP), drug reaction with eosinophilia and systemic symptoms (DRESS), Stevens-Johnson syndrome (SJS), and toxic epidermal necrolysis (TEN).Areas covered: Pharmacogenomics-guided therapy could prevent severe drug hypersensitivity reactions. The US Food and Drug Administration (FDA), Clinical Pharmacogenetics Implementation Consortium (CPIC), and Dutch Pharmacogenetics Working Group (DPWG) provided guidelines in the translation of clinically relevant and evidence-based SCARs pharmacogenomics research into clinical practice. In this review, we intended to summarize the significant HLA alleles associated with SCARs induced by different drugs in different populations. We also summarize the SCARs associated with genetic and non-genetic factors and the cost-effectiveness of screening tests.Expert opinion: The effectiveness of HLA screening on a wider scale in clinical practice requires significant resources, including state-of-the-art laboratory; multidisciplinary team approach and health care provider education and engagement; clinical decision support alert system via electronic medical record (EMR); laboratory standards and quality assurance; evidence of cost-effectiveness; and cost of pharmacogenomics tests and reimbursement.

NUDT15 polymorphism influences the metabolism and therapeutic effects of acyclovir and ganciclovir

Nucleobase and nucleoside analogs (NNA) are widely used as anti-viral and anti-cancer agents, and NNA phosphorylation is essential for the activity of this class of drugs. Recently, diphosphatase NUDT15 was linked to thiopurine metabolism with NUDT15 polymorphism associated with drug toxicity in patients. Profiling NNA drugs, we identify acyclovir (ACV) and ganciclovir (GCV) as two new NNAs metabolized by NUDT15. NUDT15 hydrolyzes ACV and GCV triphosphate metabolites, reducing their effects against cytomegalovirus (CMV) in vitro. Loss of NUDT15 potentiates cytotoxicity of ACV and GCV in host cells. In hematopoietic stem cell transplant patients, the risk of CMV viremia following ACV prophylaxis is associated with NUDT15 genotype (P = 0.015). Donor NUDT15 deficiency is linked to graft failure in patients receiving CMV-seropositive stem cells (P = 0.047). In conclusion, NUDT15 is an important metabolizing enzyme for ACV and GCV, and NUDT15 variation contributes to inter-patient variability in their therapeutic effects.

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.

North Carolina's multi-institutional pharmacogenomics efforts with the North Carolina Precision Health Collaborative

The North Carolina Precision Health Collaborative is an interdisciplinary, public-private consortium of precision health experts who strategically align statewide resources and strengths to elevate precision health in the state and beyond. Pharmacogenomics (PGx) is a key area of focus for the North Carolina Precision Health Collaborative. Experts from Atrium Health's Levine Cancer Institute, Duke University/Duke Health System, Mission Health and the University of North Carolina (UNC) at Chapel Hill/UNC Health System have collaborated since 2017 to implement strategic PGx initiatives, including basic sciences research, translational research and clinical implementation of germline testing into practice and policy. This institutional profile highlights major PGx programs and initiatives across these organizations and how the collaborative is working together to advance PGx science and implementation.

Identifying End Users' Preferences about Structuring Pharmacogenetic Test Orders in an Electronic Health Record System

Pharmacogenetics (PGx) testing can be used for detecting genetic variations that may affect an individual's anticipated metabolism of, or response to, medications. Although several studies have focused on developing tools for delivering results from PGx testing, there is a relative dearth of information about how to design provider-friendly electronic order-entry systems for PGx. The U.S. Department of Veterans Affairs (VA) is preparing to implement a new electronic health records system. In this study, VA PGx test end users were surveyed about their preferences for how electronic test orders for PGx should be structured, including the nomenclature that should be used to search for and identify PGx-test orders, whether to offer single- versus multigene tests, and whether information about test methodology should be included in the order name. Responses were analyzed systematically to identify areas of agreement and disagreement with the survey options, and areas where respondents' opinions diverged. End users endorsed preferences for flexible ways to identify and order PGx tests and multigene panel tests; opinions on whether test methodology should be included in the test name were divergent. The results could be used for both informing the VA's new electronic health records implementation (including how PGx tests are searched for and ordered) and for providing insights for other health systems implementing PGx-testing programs.

Clinical pharmacology applications in clinical drug development and clinical care: A focus on Saudi Arabia

Drug development, from preclinical to clinical studies, is a lengthy and complex process. There is an increased interest in the Kingdom of Saudi Arabia (KSA) to promote innovation, research and local content including clinical trials (Phase I-IV). Currently, there are over 650 registered clinical trials in Saudi Arabia, and this number is expected to increase. An important part of drug development and clinical trials is to assure the safe and effective use of drugs. Clinical pharmacology plays a vital role in informed decision making during the drug development stage as it focuses on the effects of drugs in humans. Disciplines such as pharmacokinetics, pharmacodynamics and pharmacogenomics are components of clinical pharmacology. It is a growing discipline with a range of applications in all phases of drug development, including selecting optimal doses for Phase I, II and III studies, evaluating bioequivalence and biosimilar studies and designing clinical studies. Incorporating clinical pharmacology in research as well as in the requirements of regulatory agencies will improve the drug development process and accelerate the pipeline. Clinical pharmacology is also applied in direct patient care with the goal of personalizing treatment. Tools such as therapeutic drug monitoring, pharmacogenomics and model informed precision dosing are used to optimize dosing for patients at an individual level. In KSA, the science of clinical pharmacology is underutilized and we believe it is important to raise awareness and educate the scientific community and healthcare professionals in terms of its applications and potential. In this review paper, we provide an overview on the use and applications of clinical pharmacology in both drug development and clinical care.

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.

Current Understanding of an Emerging Role of HLA-DRB1 Gene in Rheumatoid Arthritis-From Research to Clinical Practice

Rheumatoid arthritis (RA) is an autoimmune disease with an unclear pathogenic mechanism. However, it has been proven that the key underlying risk factor is a genetic predisposition. Association studies of the HLA-DRB1 gene clearly indicate its importance in RA morbidity. This review presents the current state of knowledge on the impact of HLA-DRB1 gene, functioning both as a component of the patient’s genome and as an environmental risk factor. The impact of known HLA-DRB1 risk variants on the specific structure of the polymorphic HLA-DR molecule, and epitope binding affinity, is presented. The issues of the potential influence of HLA-DRB1 on the occurrence of non-articular disease manifestations and response to treatment are also discussed. A deeper understanding of the role of the HLA-DRB1 gene is essential to explore the complex nature of RA, which is a result of multiple contributing factors, including genetic, epigenetic and environmental factors. It also creates new opportunities to develop modern and personalized forms of therapy.

Variant discovery using next-generation sequencing and its future role in pharmacogenetics

Next-generation sequencing (NGS) has enabled the discovery of a multitude of novel and mostly rare variants in pharmacogenes that may alter a patient’s therapeutic response to drugs. In addition to single nucleotide variants, structural variation affecting the number of copies of whole genes or parts of genes can be detected. While current guidelines concerning clinical implementation mostly act upon well-documented, common single nucleotide variants to guide dosing or drug selection, in silico and large-scale functional assessment of rare variant effects on protein function are at the forefront of pharmacogenetic research to facilitate their clinical integration. Here, we discuss the role of NGS in variant discovery, paving the way for more comprehensive genotype-guided pharmacotherapy that can translate to improved clinical care.

Pharmacogenomics in pregnancy

Pregnant women frequently take prescription and over the counter medications. The efficacy of medications is affected by the many physiological changes during pregnancy, and these events may be further impacted by genetic factors. Research on pharmacogenomic and pharmacokinetic influences on drug disposition during pregnancy has lagged behind other fields. Clinical investigators have demonstrated altered activity of several drug metabolizing enzymes during pregnancy. Emerging evidence also supports the influence of pharmacogenomic variability in drug response for many important classes of drugs commonly used in pregnancy. Prescribing medications during pregnancy requires an understanding of the substantial dynamic physiologic and metabolic changes that occur during gestation. Pharmacogenomics also contributes to the inter-individual variability in response to many medications, and more research is needed to understand how best to manage drug therapy in pregnant women.

HLADQA1*05 genotype predicts anti-drug antibody formation and loss of response during infliximab therapy for inflammatory bowel disease

BACKGROUND

Anti-drug antibodies (ADAs) are a leading contributor to infliximab loss of response and adverse drug events. It is not feasible to identify patients at risk of antibody formation before initiating infliximab. The genetic variation HLADQA1*05 (rs2097432) has been linked to infliximab antibody formation in Crohn's disease (CD).

AIMS

To evaluate the association between HLADQA1*05 and infliximab antibody formation, infliximab loss of response, treatment discontinuation and adverse drug events in patients with inflammatory bowel disease (IBD) METHODS: In a retrospective cohort study, infliximab-exposed patients with IBD (n = 262) were screened for the genetic variation, HLADQA1*05A>G (rs2097432). Risk of infliximab ADA formation, infliximab loss of response, adverse events and discontinuation were assessed in wild-type (GG) and variant-carrying (AG or AA) individuals.

RESULTS

Forty per cent of all participants were HLADQA1*05A>G variant carriers, with 79% of participants with infliximab antibodies carrying at least one variant allele. The risk of infliximab antibody formation was higher in HLADQA1*05A>G variant carriers (adjusted HR = 7.29, 95% confidence interval (CI) = 2.97-17.191, P = 1.46 × 10^-5 ) independent of age, sex, weight, dose and co-immunosuppression with an immunomodulator. Variant carrier status was associated with an increased risk of infliximab loss of response (adjusted HR = 2.34, 95% CI = 1.41-3.88, P = .001) and discontinuation (adjusted HR = 2.27, 95% CI = 1.46-3.43, P = 2.53 × 10^-4 ) although not with infliximab-associated adverse drug events.

CONCLUSIONS

HLADQA1*05 is independently associated with a high risk of infliximab antibody formation in addition to infliximab loss of response and treatment discontinuation. There may be a role for genotype-guided application of combination therapy in IBD.

PGxCorpus, a manually annotated corpus for pharmacogenomics

Pharmacogenomics (PGx) studies how individual gene variations impact drug response phenotypes, which makes PGx-related knowledge a key component towards precision medicine. A significant part of the state-of-the-art knowledge in PGx is accumulated in scientific publications, where it is hardly reusable by humans or software. Natural language processing techniques have been developed to guide experts who curate this amount of knowledge. But existing works are limited by the absence of a high quality annotated corpus focusing on PGx domain. In particular, this absence restricts the use of supervised machine learning. This article introduces PGxCorpus, a manually annotated corpus, designed to fill this gap and to enable the automatic extraction of PGx relationships from text. It comprises 945 sentences from 911 PubMed abstracts, annotated with PGx entities of interest (mainly gene variations, genes, drugs and phenotypes), and relationships between those. In this article, we present the corpus itself, its construction and a baseline experiment that illustrates how it may be leveraged to synthesize and summarize PGx knowledge.

An Update on the Immunological, Metabolic and Genetic Mechanisms in Drug Hypersensitivity Reactions

Drug hypersensitivity reactions (DHRs) represent a major burden on the healthcare system since their diagnostic and management are complex. As they can be influenced by individual genetic background, it is conceivable that the identification of variants in genes potentially involved could be used in genetic testing for the prevention of adverse effects during drug administration. Most genetic studies on severe DHRs have documented HLA alleles as risk factors and some mechanistic models support these associations, which try to shed light on the interaction between drugs and the immune system during lymphocyte presentation. In this sense, drugs are small molecules that behave as haptens, and currently three hypotheses try to explain how they interact with the immune system to induce DHRs: the hapten hypothesis, the direct pharmacological interaction of drugs with immune receptors hypothesis (p-i concept), and the altered self-peptide repertoire hypothesis. The interaction will depend on the nature of the drug and its reactivity, the metabolites generated and the specific HLA alleles. However, there is still a need of a better understanding of the different aspects related to the immunological mechanism, the drug determinants that are finally presented as well as the genetic factors for increasing the risk of suffering DHRs. Most available information on the predictive capacity of genetic testing refers to abacavir hypersensitivity and anticonvulsants-induced severe cutaneous reactions. Better understanding of the underlying mechanisms of DHRs will help us to identify the drugs likely to induce DHRs and to manage patients at risk.

The Clinical Pharmacogenetics Implementation Consortium: 10 Years Later

In 2009, the Clinical Pharmacogenetics Implementation Consortium (CPIC, www.cpicpgx.org), a shared project between Pharmacogenomics Knowledge Base (PharmGKB, http://www.pharmgkb.org) and the National Institutes of Health (NIH), was created to provide freely available, evidence-based, peer-reviewed, and updated pharmacogenetic clinical practice guidelines. To date, CPIC has published 23 guidelines (of which 11 have been updated), covering 19 genes and 46 drugs across several therapeutic areas. CPIC also now provides additional resources to facilitate the implementation of pharmacogenetics into routine clinical practice and the electronic health record. Furthermore, since its inception, CPIC's interactions with other resources, databases, websites, and genomic communities have grown. The purpose of this paper is to highlight the progress of CPIC over the past 10 years.

Towards precision medicine: interrogating the human genome to identify drug pathways associated with potentially functional, population-differentiated polymorphisms

Drug response variations amongst different individuals/populations are influenced by several factors including allele frequency differences of single nucleotide polymorphisms (SNPs) that functionally affect drug-response genes. Here, we aim to identify drugs that potentially exhibit population differences in response using SNP data mining and analytics. Ninety-one pairwise-comparisons of >22,000,000 SNPs from the 1000 Genomes Project, across 14 different populations, were performed to identify ‘population-differentiated’ SNPs (pdSNPs). Potentially-functional pdSNPs (pf-pdSNPs) were then selected, mapped into genes, and integrated with drug–gene databases to identify ‘population-differentiated’ drugs enriched with genes carrying pf-pdSNPs. 1191 clinically-approved drugs were found to be significantly enriched (Z > 2.58) with genes carrying SNPs that were differentiated in one or more population-pair comparisons. Thirteen drugs were found to be enriched with such differentiated genes across all 91 population-pairs. Notably, 82% of drugs, which were previously reported in the literature to exhibit population differences in response were also found by this method to contain a significant enrichment of population specific differentiated SNPs. Furthermore, drugs with genetic testing labels, or those suspected to cause adverse reactions, contained a significantly larger number (P < 0.01) of population-pairs with enriched pf-pdSNPs compared with those without these labels. This pioneering effort at harnessing big-data pharmacogenomics to identify ‘population differentiated’ drugs could help to facilitate data-driven decision-making for a more personalized medicine.

Pharmacogenomic Testing: Clinical Evidence and Implementation Challenges

Pharmacogenomics can enhance patient care by enabling treatments tailored to genetic make-up and lowering risk of serious adverse events. As of June 2019, there are 132 pharmacogenomic dosing guidelines for 99 drugs and pharmacogenomic information is included in 309 medication labels. Recently, the technology for identifying individual-specific genetic variants (genotyping) has become more accessible. Next generation sequencing (NGS) is a cost-effective option for genotyping patients at many pharmacogenomic loci simultaneously, and guidelines for implementation of these data are available from organizations such as the Clinical Pharmacogenetics Implementation Consortium (CPIC) and the Dutch Pharmacogenetics Working Group (DPWG). NGS and related technologies are increasing knowledge in the research sphere, yet rates of genomic literacy remain low, resulting in a widening gap in knowledge translation to the patient. Multidisciplinary teams—including physicians, nurses, genetic counsellors, and pharmacists—will need to combine their expertise to deliver optimal pharmacogenomically-informed care.

Genetic testing for prevention of severe drug-induced skin rash

BACKGROUND

Drug-induced skin reactions present with a range of clinical symptoms, from mild maculopapular skin rashes to potentially fatal blistering skin rashes - such as Stevens-Johnson syndrome (SJS) or toxic epidermal necrolysis (TEN) - which may result in death. Milder reactions may be troublesome and lead to low drug compliance. The pathogenesis of these drug reactions is not yet fully understood; however, there is evidence that pretreatment genetic testing may help to predict and prevent these reactions in some cases.

OBJECTIVES

To assess the effects of prospective pharmacogenetic screening to reduce drug-associated skin reactions in a patient population.

SEARCH METHODS

We searched the following databases up to July 2018: the Cochrane Skin Specialised Register, CENTRAL, MEDLINE, Embase and LILACS. We also searched five trials registers, and checked the reference lists of included studies and relevant reviews for further references to relevant randomised controlled trials (RCTs).

SELECTION CRITERIA

We included RCTs of participants who had prospective pharmacogenetic screening to determine genetic variants associated with hypersensitivity reactions, compared with those who did not have prospective pharmacogenetic screening. We included participants in any setting, who were of any age, gender, and ethnicity, who had been prescribed drugs known to cause delayed type hypersensitivity reactions.

DATA COLLECTION AND ANALYSIS

We used standard methodological procedures expected by Cochrane. To assess studies for inclusion, two review authors independently screened all of the titles and abstracts of publications identified by the searches. Because there was only one included study, many of the planned data analyses were not applicable to the review. We used GRADE to assess the quality of the included study.The review's primary outcomes were the incidence of severe skin rashes with systemic symptoms (such as fever and multiple organ involvement), and long-term effects (such as scarring of eyelids or lung tissue). Secondary outcomes were hospitalisation for drug-induced skin reactions, blistering skin reactions (such as SJS, hypersensitivity (HSS) syndrome), and death.

MAIN RESULTS

One study, which was a randomised, double-blind, controlled, multicentre trial, fulfilled our inclusion criteria. The trial included 1956 adult participants (74% men, with a mean age of 42 years) across 265 centres (medical centres, hospitals, outpatient clinics) in 19 countries around the world who were infected with HIV-type 1 and who had not received abacavir previously. The participants, who had a clinical need for treatment with an antiretroviral-drug regimen containing abacavir, were randomly assigned to undergo prospective human leukocyte antigen (HLA) Class I, locus B, allele 57:01 (HLA-B*57:01) screening (prospective-screening group) before this treatment, or to undergo a standard-care approach of abacavir use without prospective HLA-B*57:01 screening (control group). Participants who tested positive for HLA-B*57:01 were not given abacavir; instead, they received antiretroviral therapy that did not include abacavir. The control group did have retrospective HLA-B*57:01 pharmacogenetic testing. The trial duration was six months. Each participant was observed for six weeks. Assessments were performed at the time of study entry, at baseline (day one of abacavir treatment), and at weeks one, two and six. This study was funded by the manufacturer of abacavir, GlaxoSmithKline.The study did not assess any of our primary outcomes, and it measured none of our secondary outcomes in isolation. However, it did assess an outcome of (characteristically severe) hypersensitivity reaction which included (but was not limited to) our secondary outcomes of HSS and SJS/TEN.The study demonstrated that prospective HLA-B*57:01 screening probably reduces the incidence of hypersensitivity reaction to abacavir. The incidence of clinically diagnosed HSS reaction to abacavir was lower in the screening arm (risk ratio (RR) 0.43, 95% confidence interval (CI) 0.28 to 0.67; 1650 participants; moderate-quality evidence), as was immunologically confirmed HSS reaction (RR 0.02, 95% 0.00 to 0.37; 1644 participants; moderate-quality evidence). A positive result from an epicutaneous patch test performed six to ten weeks after clinical diagnosis provided immunological confirmation.Overall, the study demonstrates a low risk of bias across five out of seven domains. There was a high risk of detection bias because hypersensitivity reactions were diagnosed by the principal investigator at the recruitment site without the use of predefined clinical criteria. Although there was also high risk of attrition bias due to excluding participants with incomplete follow-up from analyses, the authors did undertake a series of sensitivity analyses based on the intention-to-treat population, which demonstrated consistent results with the primary analysis. We rated the study quality as moderate-quality using GRADE criteria.

AUTHORS' CONCLUSIONS

Prospective screening for HLA-B*57:01 probably reduces severe hypersensitivity skin reactions to abacavir in patients positive for HIV-type 1. However, these results are only based on one study, which was at high risk of attrition and detection bias.Our primary outcomes (incidence of severe skin rashes with systemic symptoms, and long-term effects) were not assessed by the trial, and only one of the review's secondary outcomes was measured (hypersensitivity reaction); thus, we found no evidence relating to hospitalisation, death, or long-term conditions resulting from drug injury.We found no eligible evidence on genetic testing for severe drug-induced skin rash in relation to different drugs and classes of drugs. Further clinical trials based on other drugs, and in different patient populations, would be useful for advising policy changes for improving the prevention of adverse skin reactions to drug treatments.

Targeted next generation sequencing as a tool for precision medicine

BACKGROUND

Targeted next-generation sequencing (NGS) enables rapid identification of common and rare genetic variation. The detection of variants contributing to therapeutic drug response or adverse effects is essential for implementation of individualized pharmacotherapy. Successful application of short-read based NGS to pharmacogenes with high sequence homology, nearby pseudogenes and complex structure has been previously shown despite anticipated technical challenges. However, little is known regarding the utility of such panels to detect copy number variation (CNV) in the highly polymorphic cytochrome P450 (CYP) 2D6 gene, or to identify the promoter (TA)₇ TAA repeat polymorphism UDP glucuronosyltransferase (UGT) 1A1*28. Here we developed and validated PGxSeq, a targeted exome panel for pharmacogenes pertinent to drug disposition and/or response.

METHODS

A panel of capture probes was generated to assess 422 kb of total coding region in 100 pharmacogenes. NGS was carried out in 235 subjects, and sequencing performance and accuracy of variant discovery validated in clinically relevant pharmacogenes. CYP2D6 CNV was determined using the bioinformatics tool CNV caller (VarSeq). Identified SNVs were assessed in terms of population allele frequency and predicted functional effects through in silico algorithms.

RESULTS

Adequate performance of the PGxSeq panel was demonstrated with a depth-of-coverage (DOC) ≥ 20× for at least 94% of the target sequence. We showed accurate detection of 39 clinically relevant gene variants compared to standard genotyping techniques (99.9% concordance), including CYP2D6 CNV and UGT1A1*28. Allele frequency of rare or novel variants and predicted function in 235 subjects mirrored findings from large genomic datasets. A large proportion of patients (78%, 183 out of 235) were identified as homozygous carriers of at least one variant necessitating altered pharmacotherapy.

CONCLUSIONS

PGxSeq can serve as a comprehensive, rapid, and reliable approach for the detection of common and novel SNVs in pharmacogenes benefiting the emerging field of precision medicine.

Novel genetic and epigenetic factors of importance for inter-individual differences in drug disposition, response and toxicity

Individuals differ substantially in their response to pharmacological treatment. Personalized medicine aspires to embrace these inter-individual differences and customize therapy by taking a wealth of patient-specific data into account. Pharmacogenomic constitutes a cornerstone of personalized medicine that provides therapeutic guidance based on the genomic profile of a given patient. Pharmacogenomics already has applications in the clinics, particularly in oncology, whereas future development in this area is needed in order to establish pharmacogenomic biomarkers as useful clinical tools. In this review we present an updated overview of current and emerging pharmacogenomic biomarkers in different therapeutic areas and critically discuss their potential to transform clinical care. Furthermore, we discuss opportunities of technological, methodological and institutional advances to improve biomarker discovery. We also summarize recent progress in our understanding of epigenetic effects on drug disposition and response, including a discussion of the only few pharmacogenomic biomarkers implemented into routine care. We anticipate, in part due to exciting rapid developments in Next Generation Sequencing technologies, machine learning methods and national biobanks, that the field will make great advances in the upcoming years towards unlocking the full potential of genomic data.

Precision medicine: a call for increased pharmacogenomic education

Precision medicine is an emerging model of care where providers consider patients' genetic profiles, lifestyles and environments to offer more precise therapy. The potential of precision medicine is boundless as interdisciplinary teams utilize genetic technologies to improve patient outcomes. The integration of precision medicine into healthcare faces many barriers, including a lack of standardization and reimbursement concerns. This article argues that increased pharmacogenetics education and system-wide implementation is necessary to overcome some of these challenges. Extensive expansion of pharmacogenomics education is a step toward producing knowledgeable clinicians who are poised to apply its methodology and champion for patient-centered care.

PGxO and PGxLOD: a reconciliation of pharmacogenomic knowledge of various provenances, enabling further comparison

Background

Pharmacogenomics (PGx) studies how genomic variations impact variations in drug response phenotypes. Knowledge in pharmacogenomics is typically composed of units that have the form of ternary relationships gene variant – drug – adverse event. Such a relationship states that an adverse event may occur for patients having the specified gene variant and being exposed to the specified drug. State-of-the-art knowledge in PGx is mainly available in reference databases such as PharmGKB and reported in scientific biomedical literature. But, PGx knowledge can also be discovered from clinical data, such as Electronic Health Records (EHRs), and in this case, may either correspond to new knowledge or confirm state-of-the-art knowledge that lacks “clinical counterpart” or validation. For this reason, there is a need for automatic comparison of knowledge units from distinct sources.

Results

In this article, we propose an approach, based on Semantic Web technologies, to represent and compare PGx knowledge units. To this end, we developed PGxO, a simple ontology that represents PGx knowledge units and their components. Combined with PROV-O, an ontology developed by the W3C to represent provenance information, PGxO enables encoding and associating provenance information to PGx relationships. Additionally, we introduce a set of rules to reconcile PGx knowledge, i.e. to identify when two relationships, potentially expressed using different vocabularies and levels of granularity, refer to the same, or to different knowledge units. We evaluated our ontology and rules by populating PGxO with knowledge units extracted from PharmGKB (2701), the literature (65,720) and from discoveries reported in EHR analysis studies (only 10, manually extracted); and by testing their similarity. We called PGxLOD (PGx Linked Open Data) the resulting knowledge base that represents and reconciles knowledge units of those various origins.

Conclusions

The proposed ontology and reconciliation rules constitute a first step toward a more complete framework for knowledge comparison in PGx. In this direction, the experimental instantiation of PGxO, named PGxLOD, illustrates the ability and difficulties of reconciling various existing knowledge sources.

Electronic supplementary material

The online version of this article (10.1186/s12859-019-2693-9) contains supplementary material, which is available to authorized users.

Recent developments in genetic/genomic medicine

Advances in genetic technology are having a major impact in the clinic, and mean that many perceptions of the role and scope of genetic testing are having to change. Genomic testing brings with it a greater opportunity for diagnosis, or predictions of future diagnoses, but also an increased chance of uncertain or unexpected findings, many of which may have impacts for multiple members of a person's family. In the past, genetic testing was rarely able to provide rapid results, but the increasing speed and availability of genomic testing is changing this, meaning that genomic information is increasingly influencing decisions around patient care in the acute inpatient setting. The landscape of treatment options for genetic conditions is shifting, which has evolving implications for clinical discussions around previously untreatable disorders. Furthermore, the point of access to testing is changing with increasing provision direct to the consumer outside the formal healthcare setting. This review outlines the ways in which genetic medicine is developing in light of technological advances.

Pharmacogenomics in dermatology: tools for understanding gene-drug associations

Pharmacogenomics aims to associate human genetic variability with differences in drug phenotypes in order to tailor drug treatment to individual patients. The massive amount of genetic data generated from large cohorts of patients with variable drug phenotypes have led to advances in this field. Understanding the application of pharmacogenomics in dermatology could inform clinical practice and provide insight for future research. The Pharmacogenomics Knowledge Base and the Clinical Pharmacogenetics Implementation Consortium are among the resources to help clinicians and researchers navigate the many gene-drug associations that have already been discovered. The implementation of clinical pharmacogenomics within health care systems remains an area of ongoing development. This review provides an introduction to the field of pharmacogenomics and to current pharmacogenomics resources using examples of gene-drug associations relevant to the field of dermatology.

The Role of Next-Generation Sequencing in Pharmacogenetics and Pharmacogenomics

Inherited genetic variations in pharmacogenetic loci are widely acknowledged as important determinants of phenotypic differences in drug response, and may be actionable in the clinic. However, recent studies suggest that a considerable number of novel rare variants in pharmacogenes likely contribute to a still unexplained fraction of the observed interindividual variability. Next-generation sequencing (NGS) represents a rapid, relatively inexpensive, large-scale DNA sequencing technology with potential relevance as a comprehensive pharmacogenetic genotyping platform to identify genetic variation related to drug therapy. However, many obstacles remain before the clinical use of NGS-based test results, including technical challenges, functional interpretation, and strict requirements for diagnostic tests. Advanced computational analyses, high-throughput screening methodologies, and generation of shared resources with cell-based and clinical information will facilitate the integration of NGS data into candidate genotyping approaches, likely enhancing future drug phenotype predictions in patients.

Pharmacogenomics research and clinical implementation in Brazil

We searched PubMed entries and the Lattes database of Brazilian Pharmacogenetics Network investigators, for pharmacogenetic/genomic (PGx) studies in the Brazilian population, focusing on the drugs and genes included in the Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines. Warfarin was the most extensively studied drug in a PGx context: a genomewide association study targeting warfarin stable dose identified significant signals in VKORC1 and CYP2C9, several PGx dosing algorithms were developed based on these and other genes, and the implications of population admixture on extrapolation of dosing recommendations in the CPIC guidelines were examined. A study in renal transplanted patients disclosed association of CYP3A5*6 and CYP3A5*7 with tacrolimus dosing, which led to addition of these variants to CYP3A5*3 in the CPIC tacrolimus guideline. Studies verified predisposition of HIV-positive carriers of UGT1A1*28 to severe atazanavir-induced hyperbilirubinaemia, intolerance to 5-fluorouracyl in gastrointestinal cancer patients with deleterious DPYD variants, failure of HCV-infected carriers of IFNL3 rs12979860 to obtain a sustained viral response to PEG-IFN-α, and hypersensitivity reactions to abacavir in HIV-positive carriers of HLA-B*57:01. No prospective analyses of drug therapy outcomes or cost-effectiveness assessments of PGx-guided therapy were found. In conclusion, the limited adoption of PGx-informed drug prescription in Brazil reflects combination of recognized barriers to PGx implementation worldwide plus factors specific to the Brazilian population. The latter include rarity/absence of genetic variants on which international PGx guidelines are based (eg HLA-B*15.02 for phenytoin and carbamazepine) and the caveat of extrapolating to the admixed Brazilian population, guidelines based on categorical variables, such as continental ancestry (eg warfarin guidelines), "race" or ethnicity.

Implementing a personalized medicine program in a community health system

The implementation of a de novo personalized medicine program in a rural community health system serving an underserved population is described. Focusing on the safe use of drugs impacted by genetic variations in the non-oncology setting, we first addressed drug-gene pairs designated by the US FDA in black-box warnings (codeine, clopidogrel, abacavir, carbamazepine). The program's first success was a policy change to remove codeine from the pediatric formulary, rather than a testing recommendation. Pilot studies were then conducted with primary care providers to get them familiar with pharmacogenetic testing, and a consultative outpatient clinic for patients was developed. The assessment, planning, implementation, challenges, successes and lessons learned are described.

Genetic Basis of Delayed Hypersensitivity Reactions to Drugs in Jewish and Arab Populations

Genetic variation can affect drug pharmacokinetics and pharmacodynamics and contribute to variability between individuals in response to medications. Specifically, differences in allele frequencies among individuals and ethnic groups have been associated with variation in their propensity to develop drug hypersensitivity reactions (HSRs). This article reviews the current knowledge on the genetic background of HSRs and its relevance to Jewish and Arab populations. The focus is on human leukocyte antigen (HLA) alleles and haplotypes as predictive markers of HSRs ("immunopharmacogenetics"), but other genes and alleles are described as well. Also discussed is the translation of the pharmacogenetic information to practice recommendations.

PharmGKB: A worldwide resource for pharmacogenomic information

As precision medicine becomes increasingly relevant in healthcare, the field of pharmacogenomics (PGx) also continues to gain prominence in the clinical setting. Leading institutions have begun to implement PGx testing and the amount of published PGx literature increases yearly. The Pharmacogenomics Knowledgebase (PharmGKB; www.pharmgkb.org) is one of the foremost worldwide resources for PGx knowledge, and the organization has been adapting and refocusing its mission along with the current revolution in genomic medicine. The PharmGKB website provides a diverse array of PGx information, from annotations of the primary literature to guidelines for adjusting drug treatment based on genetic information. It is freely available and accessible to everyone from researchers to clinicians to everyday citizens. PharmGKB was found over 17 years ago, but continues to be a vital resource for the entire PGx community and the general public. This article is categorized under: Translational, Genomic, and Systems Medicine > Translational Medicine.

Clinical pharmacogenomics testing in the era of next generation sequencing: challenges and opportunities for precision medicine

INTRODUCTION

The rapid development and dramatic decrease in cost of sequencing techniques have ushered the implementation of genomic testing in patient care. Next generation DNA sequencing (NGS) techniques have been used increasingly in clinical laboratories to scan the whole or part of the human genome in order to facilitate diagnosis and/or prognostics of genetic disease. Despite many hurdles and debates, pharmacogenomics (PGx) is believed to be an area of genomic medicine where precision medicine could have immediate impact in the near future. Areas covered: This review focuses on lessons learned through early attempts of clinically implementing PGx testing; the challenges and opportunities that PGx testing brings to precision medicine in the era of NGS. Expert commentary: Replacing targeted analysis approach with NGS for PGx testing is neither technically feasible nor necessary currently due to several technical limitations and uncertainty involved in interpreting variants of uncertain significance for PGx variants. However, reporting PGx variants out of clinical whole exome or whole genome sequencing (WES/WGS) might represent additional benefits for patients who are tested by WES/WGS.

HLA-A*31:01 and Oxcarbazepine-Induced DRESS in a Patient With Seizures and Complete DCX Deletion

Oxcarbazepine is an antiepileptic drug (AED) commonly used as a first-line treatment option for focal epilepsy. Several AEDs, including carbamazepine, oxcarbazepine, and phenytoin are associated with various delayed-hypersensitivity reactions such as drug reaction with eosinophilia and systemic symptoms, Stevens-Johnson syndrome, or toxic epidermal necrolysis. The Food and Drug Administration-approved label for oxcarbazepine currently presents information regarding a pharmacogenomic association with the HLA antigen allele HLA-B*15:02 and hypersensitivity reactions in certain ancestry groups with a high incidence of this allele. However, unlike carbamazepine, screening for the presence of this allele is not routinely recommended before administration of oxcarbazepine. In practice, even with carbamazepine, HLA antigen testing is not always performed before initiating treatment because of lack of physician awareness of the recommendations and because of the desire to initiate treatment without delay. We present the clinical course of a pediatric patient with focal epilepsy refractory to several AEDs who developed drug reaction with eosinophilia and systemic symptoms after oxcarbazepine administration. The pharmacogenomic testing for various HLA antigen alleles was performed post hoc, and results were evaluated for structural similarities between AEDs and their molecular associations with HLA antigen proteins. In addition, we review the population-wide prevalence of various hypersensitivity reactions to AEDs and associated HLA antigen alleles. Finally, we discuss the potential utility of preemptive pharmacogenomic screening of patients before pharmacological treatment of epilepsy to assess the risk of developing hypersensitivity reactions.