Comparison of genome sequencing and clinical genotyping for pharmacogenes

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

INTRODUCTION

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

AREAS COVERED

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

EXPERT OPINION

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

Should secondary pharmacogenomic variants be actively screened and reported when diagnostic genome-wide sequencing is performed in a child?

This white paper was prepared by the Global Alliance for Genomics and Health Regulatory and Ethics Work Stream's Pediatric Task Team to review and provide perspective with respect to ethical, legal, and social issues regarding the return of secondary pharmacogenomic variants in children who have a serious disease or developmental disorder and are undergoing exome or genome sequencing to identify a genetic cause of their condition. We discuss actively searching for and reporting pharmacogenetic/genomic variants in pediatric patients, different methods of returning secondary pharmacogenomic findings to the patient/parents and/or treating clinicians, maintaining these data in the patient's health record over time, decision supports to assist using pharmacogenetic results in future treatment decisions, and sharing information in public databases to improve the clinical interpretation of pharmacogenetic variants identified in other children. We conclude by presenting a series of points to consider for clinicians and policymakers regarding whether, and under what circumstances, routine screening and return of pharmacogenomic variants unrelated to the indications for testing is appropriate in children who are undergoing genome-wide sequencing to assist in the diagnosis of a suspected genetic disease.

Updated DPYD HapB3 haplotype structure and implications for pharmacogenomic testing

The DPYD gene encodes dihydropyrimidine dehydrogenase, the rate-limiting enzyme for the metabolism of fluoropyrimidines 5-fluorouracil and capecitabine. Genetic variants in DPYD have been associated with altered enzyme activity, therefore accurate detection and interpretation is critical to predict metabolizer status for individualized fluoropyrimidine therapy. The most commonly observed deleterious variation is the causal variant linked to the previously described HapB3 haplotype, c.1129-5923C>G (rs75017182) in intron 10, which introduces a cryptic splice site. A benign synonymous variant in exon 11, c.1236G>A (rs56038477) is also linked to HapB3 and is commonly used for testing. Previously, these single-nucleotide polymorphisms (SNPs) have been reported to be in perfect linkage disequilibrium (LD); therefore, c.1236G>A is often utilized as a proxy for the function-altering intronic variant. Clinical genotyping of DPYD identified a patient who had c.1236G>A, but not c.1129-5923C>G, suggesting that these two SNPs may not be in perfect LD, as previously assumed. Additional individuals with c.1236G>A, but not c.1129-5923C>G, were identified in the Children's Mercy Data Warehouse and the All of Us Research Program version 7 cohort substantiating incomplete SNP linkage. Consequently, testing only c.1236G>A can generate false-positive results in some cases and lead to suboptimal dosing that may negatively impact patient therapy and prospect of survival. Our data show that DPYD genotyping should include the functional variant c.1129-5923C>G, and not the c.1236G>A proxy, to accurately predict DPD activity.

Current status of the analytical validation of next generation sequencing applications for pharmacogenetic profiling

BACKGROUND

Analytical validity is a prerequisite to use a next generation sequencing (NGS)-based application as an in vitro diagnostic test or a companion diagnostic in clinical practice. Currently, in the United States and the European Union, the intended use of such NGS-based tests does not refer to guided drug therapy on the basis of pharmacogenetic profiling of drug metabolizing enzymes, although the value of pharmacogenetic testing has been reported. However, in research, a large variety of NGS-based tests are used and have been confirmed to be at least comparable to array-based testing.

METHODS AND RESULTS

A systematic evaluation was performed screening and assessing published literature on analytical validation of NGS applications for pharmacogenetic profiling of CYP2C9, CYP2C19, CYP2D6, VKORC1 and/or UGT1A1. Although NGS applications are also increasingly used for implementation assessments in clinical practice, we show in the present systematic literature evaluation that published information on the current status of analytical validation of NGS applications targeting drug metabolizing enzymes is scarce. Furthermore, a comprehensive performance evaluation of whole exome and whole genome sequencing with the intended use for pharmacogenetic profiling has not been published so far.

CONCLUSIONS

A standard in reporting on analytical validation of NGS-based tests is not in place yet. Therefore, many relevant performance criteria are not addressed in published literature. For an appropriate analytical validation of an NGS-based qualitative test for pharmacogenetic profiling at least accuracy, precision, limit of detection and specificity should be addressed to facilitate the implementation of such tests in clinical use.

Translating pharmacogenomic sequencing data into drug response predictions-How to interpret variants of unknown significance

The rapid development of sequencing technologies during the past 20 years has provided a variety of methods and tools to interrogate human genomic variations at the population level. Pharmacogenes are well known to be highly polymorphic and a plethora of pharmacogenomic variants has been identified in population sequencing data. However, so far only a small number of these variants have been functionally characterized regarding their impact on drug efficacy and toxicity and the significance of the vast majority remains unknown. It is therefore of high importance to develop tools and frameworks to accurately infer the effects of pharmacogenomic variants and, eventually, aggregate the effect of individual variations into personalized drug response predictions. To address this challenge, we here first describe the technological advances, including sequencing methods and accompanying bioinformatic processing pipelines that have enabled reliable variant identification. Subsequently, we highlight advances in computational algorithms for pharmacogenomic variant interpretation and discuss the added value of emerging strategies, such as machine learning and the integrative use of omics techniques that have the potential to further contribute to the refinement of personalized pharmacological response predictions. Lastly, we provide an overview of experimental and clinical approaches to validate in silico predictions. We conclude that the iterative feedback between computational predictions and experimental validations is likely to rapidly improve the accuracy of pharmacogenomic prediction models, which might soon allow for an incorporation of the entire pharmacogenetic profile into personalized response predictions.

Comparison of variants in TPMT and NUDT15 between sequencing and genotyping methods in a multistate pediatric institution

The risk of severe adverse events related to thiopurine therapy can be reduced by personalizing dosing based on TPMT and NUDT15 genetic polymorphisms. However, the optimal genetic testing platform has not yet been established. In this study, we report on the TPMT and NUDT15 genotypes and phenotypes generated from 320 patients from a multicenter pediatric healthcare system using both Sanger sequencing and polymerase chain reaction genotyping (hereafter: genotyping) methods to determine the appropriateness of genotyping in our patient population. Sanger sequencing identified variant TPMT alleles including *3A (8, 3.2% of alleles), *3C (4, 1.6%), and *2 (1, 0.4%), and NUDT15 alleles including *2 (5, 3.6%) and *3 (1, 0.7%). For genotyped patients, variants identified in TPMT included *3A (12, 3.1%), *3C (4, 1%), *2 (2, 0.5%), and *8 (1, 0.25%), whereas NUDT15 included *4 (2, 1.9%) and *2 or *3 (1, 1%). Between Sanger sequencing and genotyping, no significant difference in allele, genotype, or phenotype frequency was identified for either TPMT or NUDT15. All patients who were tested using Sanger sequencing would have been accurately phenotyped for either TPMT (124/124), NUDT15 (69/69), or both genes (68/68) if they were assayed using the genotyping method. Considering 193 total TPMT and NUDT15 Sanger Sequencing tests reviewed, all tests would have resulted in an appropriate clinical recommendation if the test had instead been conducted using the comparison genotyping platforms. These results suggest that, in this study population, genotyping would be sufficient to provide accurate phenotype calls and clinical recommendations.

Attitudes on pharmacogenomic results as secondary findings among medical geneticists

OBJECTIVES

As evidence mounts supporting the utility of pharmacogenomic-guided medication management, incorporating pharmacogenomic genes into secondary finding results from sequencing panels is increasingly under consideration. We studied medical geneticists' attitudes on receiving pharmacogenomic results as secondary finding.

METHODS

Four focus groups with 16 medical geneticists total were conducted followed by thematic analysis.

RESULTS

All participants ordered genetic sequencing tests; however, the majority had rarely or never ordered pharmacogenomic tests (10/16) or prescribed medications with established response variability (11/16). In total 81.3% expressed low comfort interpreting pharmacogenomic results without appropriate clinical resources (13/16). The positives of receiving pharmacogenomic results as secondary finding included prevention of adverse drug reactions in adults, grateful information-seeking patients, the ability to rapidly prescribe more effective treatments and appreciation of the recent advances in both pharmacogenomic knowledge and available guidelines. Negatives included laboratory reporting issues, exclusivity of pharmacogenomic results to certain populations, lengthy reports concealing pharmacogenomic results in patient charts and laboratories marketing to individuals without prior pharmacogenomic knowledge or targeting inappropriate populations. The most desirable pharmacogenomic resources included a universal electronic health record clinical decision support tool to assist identifying and implementing pharmacogenomic results, a specialized pharmacist as part of the care team, additional pharmacogenomic training during medical/graduate school, and a succinct interpretation of pharmacogenomic results included on laboratory reports.

CONCLUSIONS

The majority of participants agreed that adding certain actionable pharmacogenomic genes to the American College of Medical Genetics and Genomics SF list is reasonable; however, this was qualified with a need for additional resources to support implementation.

Advancing Pharmacogenomics from Single-Gene to Preemptive Testing

Pharmacogenomic testing can be an effective tool to enhance medication safety and efficacy. Pharmacogenomically actionable medications are widely used, and approximately 90-95% of individuals have an actionable genotype for at least one pharmacogene. For pharmacogenomic testing to have the greatest impact on medication safety and clinical care, genetic information should be made available at the time of prescribing (preemptive testing). However, the use of preemptive pharmacogenomic testing is associated with some logistical concerns, such as consistent reimbursement, processes for reporting preemptive results over an individual's lifetime, and result portability. Lessons can be learned from institutions that have implemented preemptive pharmacogenomic testing. In this review, we discuss the rationale and best practices for implementing pharmacogenomics preemptively.

Molecular Variants in Genes related to the Response to Ocular Hypotensive Drugs in an Afro-Colombian Population

Aims:

This study aimed to conduct an exploratory analysis of the pharmacogenomic variants involved in ocular hypotensive drugs to understand the individual differential response in an Afro-descendant population.

Background:

Glaucoma is the leading cause of irreversible blindness worldwide. The pharmacologic treatment available consists of lowering intraocular pressure by administering topical drugs. In Asian and Caucasian people, pharmacogenomic variants associated with the efficacy of these treatments have been identified. However, in Afro-descendant populations, there is a profound gap in this knowledge.

Objective:

This study identified the pharmacogenomic variants related to ocular hypotensive efficacy treatment in Afro-descendant individuals from the Archipelago of San Andres and Providence, Colombia.

Methods:

An analysis of whole-exome sequencings (WES), functional annotation, and clinical significance was performed for pharmacogenomic variants reported in PharmGKB databases; in turn, an in silico available prediction analysis was carried out for the novel variants.

Results:

We identified six out of 18 non-synonymous variants with a clinical annotation in PharmGKB. Five were classified as level three evidence for the hypotensive drugs; rs1801252 and rs1801253 in the ADRB1 gene and rs1042714 in the ADRB2 gene. These pharmacogenomic variants have been involved in a lack of efficacy of topical beta-blockers and higher systolic and diastolic pressure under treatment with ophthalmic timolol drug. The rs1045642 in the ABCB1 gene was associated with greater efficacy of treatments with latanoprost drug. Also, we found the haplotypes *17 for CYP2D6 and *10 for CYP2C19; both related to reducing the enzyme activity to timolol drug metabolization. In addition, we observed 50 novel potentially actionable variants; 36 synonymous, two insertion variants that caused frameshift mutations, and 12 non-synonymous, where five were predicted to be pathogenic based on several pathogenicity predictions.

Conclusion:

Our results suggested that the pharmacogenomic variants were found to decrease the ocular hypotensive efficacy treatment in a Colombian Afro-descendant population and revealed a significant proportion of novel variants with a potential to influence drug response.

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.

Application of long-read sequencing to elucidate complex pharmacogenomic regions: a proof of principle

The use of pharmacogenomics in clinical practice is becoming standard of care. However, due to the complex genetic makeup of pharmacogenes, not all genetic variation is currently accounted for. Here, we show the utility of long-read sequencing to resolve complex pharmacogenes by analyzing a well-characterised sample. This data consists of long reads that were processed to resolve phased haploblocks. 73% of pharmacogenes were fully covered in one phased haploblock, including 9/15 genes that are 100% complex. Variant calling accuracy in the pharmacogenes was high, with 99.8% recall and 100% precision for SNVs and 98.7% precision and 98.0% recall for Indels. For the majority of gene-drug interactions in the DPWG and CPIC guidelines, the associated genes could be fully resolved (62% and 63% respectively). Together, these findings suggest that long-read sequencing data offers promising opportunities in elucidating complex pharmacogenes and haplotype phasing while maintaining accurate variant calling.

Validation of a multi-gene qPCR-based pharmacogenomics panel across major ethnic groups in Singapore and Indonesia

Aim: The clinical utility of pharmacogenomics (PGx) has been gaining traction alongside growing evidence that adverse drug reactions (ADRs) have significant genetic associations. Nala PGx Core^® is a multi-gene qPCR-based panel of 20 allele variants, comprising 18 SNPs and two CYP2D6 copy number markers across four pharmacogenes - CYP2C9, CYP2C19, CYP2D6 and SLCO1B1. Methods: In this study, we validated the performance of Nala PGx Core^® against benchmark methods, on the Singaporean and Indonesian populations. Results & conclusion: Nala PGx Core^® demonstrated robust and accurate genotyping when compared with other established benchmarks. Furthermore, the panel successfully characterized alleles of clinical relevance, such as CYP2D6*10 and CYP2D6*36, across major ethnic groups present of Singapore and Indonesia, suggesting its potential for adoption in clinical workflows regionally.

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.

Identification of CYP2D6 Haplotypes that Interfere with Commonly Used Assays for Copy Number Variation Characterization

Cytochrome P450 2D6 (CYP2D6) copy number (CN) variation affects the metabolism of numerous prescribed drugs. Sequence variation within primer or probe target regions of hydrolysis probe CN assays can generate false-positive calls for CN loss. Furthermore, CYP2D6-CYP2D7 hybrids and gene conversions can cause difficult to interpret discordant CN calls. The identification of haplotypes with CN variations and structural arrangements is important to predict phenotype accurately. During clinical testing with hydrolysis probe assays targeting three CYP2D6 regions (intron 2, intron 6, and exon 9), samples with haplotypes causing inconsistent CN calls were identified. To resolve these cases, next-generation sequencing and allele-specific Sanger sequencing was performed. Sequence analysis of 16 samples, all but one from subjects of African descent, identified six novel suballeles containing single-nucleotide polymorphisms, which cause false-positive calls for CN loss in introns 2 and 6. Five samples with an exon 9 CN loss contained CYP2D6/CYP2D7 hybrids (∗13 or ∗36) and one sample was found to have a novel haplotype, CYP2D6∗141. Interestingly, CYP2D6∗141 contains a CYP2D7-derived exon 9 conversion and core single-nucleotide polymorphisms that are otherwise found in CYP2D6∗17 and ∗27. Although these variants are rare, they can cause inconsistent CN calls that typically are reported as no calls or indeterminant, and thus may deprive patients, particularly those of African descent, from taking full benefit of pharmacogenetic testing.

Technologies for Pharmacogenomics: A Review

The continuous development of new genotyping technologies requires awareness of their potential advantages and limitations concerning utility for pharmacogenomics (PGx). In this review, we provide an overview of technologies that can be applied in PGx research and clinical practice. Most commonly used are single nucleotide variant (SNV) panels which contain a pre-selected panel of genetic variants. SNV panels offer a short turnaround time and straightforward interpretation, making them suitable for clinical practice. However, they are limited in their ability to assess rare and structural variants. Next-generation sequencing (NGS) and long-read sequencing are promising technologies for the field of PGx research. Both NGS and long-read sequencing often provide more data and more options with regard to deciphering structural and rare variants compared to SNV panels-in particular, in regard to the number of variants that can be identified, as well as the option for haplotype phasing. Nonetheless, while useful for research, not all sequencing data can be applied to clinical practice yet. Ultimately, selecting the right technology is not a matter of fact but a matter of choosing the right technique for the right problem.

Repurposing of Diagnostic Whole Exome Sequencing Data of 1,583 Individuals for Clinical Pharmacogenetics

For ~ 80 drugs, widely recognized pharmacogenetics dosing guidelines are available. However, the use of these guidelines in clinical practice remains limited as only a fraction of patients is subjected to pharmacogenetic screening. We investigated the feasibility of repurposing whole exome sequencing (WES) data for a panel of 42 variants in 11 pharmacogenes to provide a pharmacogenomic profile. Existing diagnostic WES‐data from child‐parent trios totaling 1,583 individuals were used. Results were successfully extracted for 39 variants. No information could be extracted for three variants, located in CYP2C19, UGT1A1, and CYP3A5, and for CYP2D6 copy number. At least one actionable phenotype was present in 86% of the individuals. Haplotype phasing proved relevant for CYP2B6 assignments as 1.5% of the phenotypes were corrected after phasing. In conclusion, repurposing WES‐data can yield meaningful pharmacogenetic profiles for 7 of 11 important pharmacogenes, which can be used to guide drug treatment.

Pharmacist-Initiated Pre-Emptive Pharmacogenetic Panel Testing with Clinical Decision Support in Primary Care: Record of PGx Results and Real-World Impact

Logistics and (cost-)effectiveness of pharmacogenetic (PGx)-testing may be optimized when delivered through a pre-emptive panel-based approach, within a clinical decision support system (CDSS). Here, clinical recommendations are automatically deployed by the CDSS when a drug-gene interaction (DGI) is encountered. However, this requires record of PGx-panel results in the electronic medical record (EMR). Several studies indicate promising clinical utility of panel-based PGx-testing in polypharmacy and psychiatry, but is undetermined in primary care. Therefore, we aim to quantify both the feasibility and the real-world impact of this approach in primary care. Within a prospective pilot study, community pharmacists were provided the opportunity to request a panel of eight pharmacogenes to guide drug dispensing within a CDSS for 200 primary care patients. In this side-study, this cohort was cross-sectionally followed-up after a mean of 2.5-years. PGx-panel results were successfully recorded in 96% and 68% of pharmacist and general practitioner (GP) EMRs, respectively. This enabled 97% of patients to (re)use PGx-panel results for at least one, and 33% for up to four newly initiated prescriptions with possible DGIs. A total of 24.2% of these prescriptions had actionable DGIs, requiring pharmacotherapy adjustment. Healthcare utilization seemed not to vary among those who did and did not encounter a DGI. Pre-emptive panel-based PGx-testing is feasible and real-world impact is substantial in primary care.

Sequencing XMET genes to promote genotype-guided risk assessment and precision medicine

High-throughput next generation sequencing (NGS) is a shotgun approach applied in a parallel fashion by which the genome is fragmented and sequenced through small pieces and then analyzed either by aligning to a known reference genome or by de novo assembly without reference genome. This technology has led researchers to conduct an explosion of sequencing related projects in multidisciplinary fields of science. However, due to the limitations of sequencing-based chemistry, length of sequencing reads and the complexity of genes, it is difficult to determine the sequences of some portions of the human genome, leaving gaps in genomic data that frustrate further analysis. Particularly, some complex genes are difficult to be accurately sequenced or mapped because they contain high GC-content and/or low complexity regions, and complicated pseudogenes, such as the genes encoding xenobiotic metabolizing enzymes and transporters (XMETs). The genetic variants in XMET genes are critical to predicate inter-individual variability in drug efficacy, drug safety and susceptibility to environmental toxicity. We summarized and discussed challenges, wet-lab methods, and bioinformatics algorithms in sequencing "complex" XMET genes, which may provide insightful information in the application of NGS technology for implementation in toxicogenomics and pharmacogenomics.

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.

Population-scale genomics-Enabling precision public health

The current excitement for affordable genomics technologies and national precision medicine initiatives marks a turning point in worldwide healthcare practices. The last decade of global population sequencing efforts has defined the enormous extent of genetic variation in the human population resulting in insights into differential disease burden and response to therapy within and between populations. Population-scale pharmacogenomics helps to provide insights into the choice of optimal therapies and an opportunity to estimate, predict and minimize adverse events. Such an approach can potentially empower countries to formulate national selection and dosing policies for therapeutic agents thereby promoting public health with precision. We review the breadth and depth of worldwide population-scale sequencing efforts and its implications for the implementation of clinical pharmacogenetics toward making precision medicine a reality.

Translating genotype data of 44,000 biobank participants into clinical pharmacogenetic recommendations: challenges and solutions

PURPOSE

Biomedical databases combining electronic medical records and phenotypic and genomic data constitute a powerful resource for the personalization of treatment. To leverage the wealth of information provided, algorithms are required that systematically translate the contained information into treatment recommendations based on existing genotype-phenotype associations.

METHODS

We developed and tested algorithms for translation of preexisting genotype data of over 44,000 participants of the Estonian biobank into pharmacogenetic recommendations. We compared the results obtained by genome sequencing, exome sequencing, and genotyping using microarrays, and evaluated the impact of pharmacogenetic reporting based on drug prescription statistics in the Nordic countries and Estonia.

RESULTS

Our most striking result was that the performance of genotyping arrays is similar to that of genome sequencing, whereas exome sequencing is not suitable for pharmacogenetic predictions. Interestingly, 99.8% of all assessed individuals had a genotype associated with increased risks to at least one medication, and thereby the implementation of pharmacogenetic recommendations based on genotyping affects at least 50 daily drug doses per 1000 inhabitants.

CONCLUSION

We find that microarrays are a cost-effective solution for creating preemptive pharmacogenetic reports, and with slight modifications, existing databases can be applied for automated pharmacogenetic decision support for clinicians.

Intracrine Regulation of Estrogen and Other Sex Steroid Levels in Endometrium and Non-gynecological Tissues; Pathology, Physiology, and Drug Discovery

Our understanding of the intracrine (or local) regulation of estrogen and other steroid synthesis and degradation expanded in the last decades, also thanks to recent technological advances in chromatography mass-spectrometry. Estrogen responsive tissues and organs are not passive receivers of the pool of steroids present in the blood but they can actively modify the intra-tissue steroid concentrations. This allows fine-tuning the exposure of responsive tissues and organs to estrogens and other steroids in order to best respond to the physiological needs of each specific organ. Deviations in such intracrine control can lead to unbalanced steroid hormone exposure and disturbances. Through a systematic bibliographic search on the expression of the intracrine enzymes in various tissues, this review gives an up-to-date view of the intracrine estrogen metabolisms, and to a lesser extent that of progestogens and androgens, in the lower female genital tract, including the physiological control of endometrial functions, receptivity, menopausal status and related pathological conditions. An overview of the intracrine regulation in extra gynecological tissues such as the lungs, gastrointestinal tract, brain, colon and bone is given. Current therapeutic approaches aimed at interfering with these metabolisms and future perspectives are discussed.

Concordance between glucose-6-phosphate dehydrogenase (G6PD) genotype and phenotype and rasburicase use in patients with hematologic malignancies

Phenotypic rather than genotypic tests remain the gold standard for diagnosing glucose-6-phosphate dehydrogenase (G6PD) deficiency. However, with increasing use of genomic arrays and whole exome or genome sequencing, G6PD genetic data are increasingly available. We examined the utility of G6PD genetic data in patients with hematologic malignancies and the association of G6PD genotype and phenotype with rasburicase-induced methemoglobinemia. We analyzed G6PD activity for 990 patients. Genotype data were available from the Affymetrix DMET array (n=379), whole exome sequencing (n=374), and/or the Illumina exome array (n=634) for 645 patients. Medical records of 341 patients with methemoglobin measures were assessed for the administration of rasburicase. We observed 5 non-synonymous SNPs, 4 of which were known to be associated with deficient G6PD activity (WHO Class I-III). Genotyping 367 males resulted in a positive predictive value of 81.8% (47.8–96.8%), and two males with a Class I-III allele having normal activity both received a red blood cell transfusion prior to the activity assay. However, genotyping males had only 39.1% (20.5–61.2%) sensitivity. Two of the 12 heterozygous females had deficient G6PD activity. Rasburicase-induced methemoglobinemia occurred in 6 patients, 5 of whom had at least one Class I-III allele, despite 2 of these having normal G6PD activity. We conclude that although an apparent nondeficient genotype does not necessarily imply a normal phenotype, a deficient genotype result indicates a deficient phenotype in those without transfusions, and may be a useful adjuct to phenotype to prevent adverse drug reactions.

Standardization can accelerate the adoption of pharmacogenomics: current status and the path forward

Successfully implementing pharmacogenomics into routine clinical practice requires an efficient process to order genetic tests and report the results to clinicians and patients. Lack of standardized approaches and terminology in clinical laboratory processes, ordering of the test and reporting of test results all impede this workflow. Expert groups such as the Association for Molecular Pathology and the Clinical Pharmacogenetics Implementation Consortium have published recommendations for standardizing laboratory genetic testing, reporting and terminology. Other resources such as PharmGKB, ClinVar, ClinGen and PharmVar have established databases of nomenclature for pharmacogenetic alleles and variants. Opportunities remain to develop new standards and further disseminate existing standards which will accelerate the implementation of pharmacogenomics.

Pharmacogenetic Information in Clinical Guidelines: The European Perspective

Surveys among pharmacists and physicians show that these healthcare professionals have successfully adopted the concept of pharmacogenomics (PGx).^1-3 In addition, patients are willing to consent to participate in PGx implementation studies.⁴ However, the surveys also show that healthcare professionals do not frequently order or recommend a PGx test.^1,2 Among others, a frequently perceived hurdle for clinical uptake of PGx is the availability of guidelines translating PGx test results into clinical actions for individual patients.^5,6.

Integrating pharmacogenomics into electronic health records with clinical decision support

PURPOSE

Existing pharmacogenomic informatics models, key implementation steps, and emerging resources to facilitate the development of pharmacogenomic clinical decision support (CDS) are described.

SUMMARY

Pharmacogenomics is an important component of precision medicine. Informatics, especially CDS in the electronic health record (EHR), is a critical tool for the integration of pharmacogenomics into routine patient care. Effective integration of pharmacogenomic CDS into the EHR can address implementation challenges, including the increasing volume of pharmacogenomic clinical knowledge, the enduring nature of pharmacogenomic test results, and the complexity of interpreting results. Both passive and active CDS provide point-of-care information to clinicians that can guide the systematic use of pharmacogenomics to proactively optimize pharmacotherapy. Key considerations for a successful implementation have been identified; these include clinical workflows, identification of alert triggers, and tools to guide interpretation of results. These considerations, along with emerging resources from the Clinical Pharmacogenetics Implementation Consortium and the National Academy of Medicine, are described.

CONCLUSION

The EHR with CDS is essential to curate pharmacogenomic data and disseminate patient-specific information at the point of care. As part of the successful implementation of pharmacogenomics into clinical settings, all relevant clinical recommendations pertaining to gene-drug pairs must be summarized and presented to clinicians in a manner that is seamlessly integrated into the clinical workflow of the EHR. In some situations, ancillary systems and applications outside the EHR may be integrated to augment the capabilities of the EHR.

Patient Decisions to Receive Secondary Pharmacogenomic Findings and Development of a Multidisciplinary Practice Model to Integrate Results Into Patient Care

Whole exome sequencing (WES) has the potential of identifying secondary findings that are predictive of poor pharmacotherapy outcomes. The purpose of this study was to investigate patients’ wishes regarding the reporting of secondary pharmacogenomic findings. WES results (n = 106 patients) were retrospectively reviewed to determine the number of patients electing to receive secondary pharmacogenomic results. Phenotypes were assigned based on Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines. The percent of patients with a predicted phenotype associated with a gene‐based CPIC dosing recommendation was determined. Ninety‐nine patients (93.4%) elected to receive secondary pharmacogenomic findings. For each gene–drug pair analyzed, the number of patients with an actionable phenotype ranged from two (2%) to 43 patients (43.4%). Combining all gene–drug pairs, 84 unique patients (84.8%) had an actionable phenotype. A prospective multidisciplinary practice model was developed for integrating secondary pharmacogenomic findings into clinical practice. Our model highlights a unique collaboration between physician‐geneticists, pharmacists, and genetic counselors.

Genome sequencing as a platform for pharmacogenetic genotyping: a pediatric cohort study

Whole-genome sequencing and whole-exome sequencing have proven valuable for diagnosing inherited diseases, particularly in children. However, usage of sequencing data as a pharmacogenetic screening tool to ensure medication safety and effectiveness remains to be explored. Sixty-seven variants in 19 genes with known effects on drug response were compared between genome sequencing and targeted genotyping data for coverage and concordance in 98 pediatric patients. We used targeted genotyping data as a benchmark to assess accuracy of variant calling, and to identify copy number variations of the CYP2D6 gene. We then predicted clinical impact of these variants on drug therapy. We find genotype concordance across those panels to be > 97%. Concordance of CYP2D6 predicted phenotype between estimates of whole-genome sequencing and targeted genotyping panel were 90%; a result from a lower coverage depth or variant calling difficulties in our whole-genome sequencing data when copy number variation and/or the CYP2D6*4 haplotype were present. Importantly, 95 children had at least one clinically actionable pharmacogenetic variant. Diagnostic genomic sequencing data can be used for pre-emptive pharmacogenetic screening. However, concordance between genome-wide sequencing and target genotyping needs to be characterized for each of the pharmacologically important genes.

Genome sequencing, in addition to helping diagnose disease, can inform medication decisions and improve drug safety for children. Ronald Cohn, Shinya Ito and colleagues at the Hospital for Sick Children in Toronto, Canada, studied a cohort of 98 pediatric patients who had undergone whole genome sequencing to help diagnose their unexplained congenital malformations or neurodevelopmental disorders. The researchers looked for 67 DNA variants found in 19 genes with known effects on drug responses. They used targeted genotyping to assess the accuracy of the sequence data. Sequencing proved to be more than 99% accurate for all but one of the pharmacologically important genes, showing the power of diagnostic genomic sequencing to identify DNA variants in children that affect medication safety and effectiveness. However, the accuracy of the method may need to be validated for each relevant gene.

Concordance between Research Sequencing and Clinical Pharmacogenetic Genotyping in the eMERGE-PGx Study

There has been extensive debate about both the necessity of orthogonal confirmation of next-generation sequencing (NGS) results in Clinical Laboratory Improvement Amendments-approved laboratories and return of research NGS results to participants enrolled in research studies. In eMERGE-PGx, subjects underwent research NGS using PGRNseq and orthogonal targeted genotyping in clinical laboratories, which prompted a comparison of genotyping results between platforms. Concordance (percentage agreement) was reported for 4077 samples tested across nine combinations of research and clinical laboratories. Retesting was possible on a subset of 1792 samples, and local laboratory directors determined sources of genotype discrepancy. Research NGS and orthogonal clinical genotyping had an overall per sample concordance rate of 0.972 and per variant concordance rate of 0.997. Genotype discrepancies attributed to research NGS were because of sample switching (preanalytical errors), whereas the majority of genotype discrepancies (92.3%) attributed to clinical genotyping were because of allele dropout as a result of rare variants interfering with primer hybridization (analytical errors). These results highlight the analytical quality of clinically significant pharmacogenetic variants derived from NGS and reveal important areas for research and clinical laboratories to address with quality management programs.

African Genetic Diversity: Implications for Cytochrome P450-mediated Drug Metabolism and Drug Development

Genetic diversity is greater in Africa than in other continental populations. Genetic variability in genes encoding drug metabolizing enzymes may contribute to the high numbers of adverse drug reactions reported in Africa. We reviewed publications (1995-April 2016) reporting frequencies of known cytochrome P450 (CYP) variants in African populations. Using principal components analysis (PCA) we identified CYP alleles of potential clinical relevance with a marked difference in distribution in Africa, compared with Asian and Caucasian populations. These were CYP2B6*6, CYP2C8*2, CYP2D6*3, CYP2D6*17, CYP2D6*29, CYP3A5*6, and CYP3A5*7. We show clearly that there is greater diversity in CYP distribution in Africa than in other continental populations and identify a need for optimization of drug therapy and drug development there. Further pharmacogenetic studies are required to confirm the CYP distributions we identified using PCA, to discover uniquely African alleles and to identify populations at a potentially increased risk of drug-induced adverse events or drug inefficacy.

Next-Generation Sequencing in Oncology: Genetic Diagnosis, Risk Prediction and Cancer Classification

Next-generation sequencing (NGS) technology has expanded in the last decades with significant improvements in the reliability, sequencing chemistry, pipeline analyses, data interpretation and costs. Such advances make the use of NGS feasible in clinical practice today. This review describes the recent technological developments in NGS applied to the field of oncology. A number of clinical applications are reviewed, i.e., mutation detection in inherited cancer syndromes based on DNA-sequencing, detection of spliceogenic variants based on RNA-sequencing, DNA-sequencing to identify risk modifiers and application for pre-implantation genetic diagnosis, cancer somatic mutation analysis, pharmacogenetics and liquid biopsy. Conclusive remarks, clinical limitations, implications and ethical considerations that relate to the different applications are provided.