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The Pharmacogene Variation Consortium (PharmVar) catalogs star (*) allele nomenclature for the polymorphic human CYP3A5 gene. Genetic variation within the CYP3A5 gene locus impacts the metabolism of several clinically important drugs, including the immunosuppressants tacrolimus, sirolimus, cyclosporine, and the benzodiazepine midazolam. Variable CYP3A5 activity is of clinical importance regarding tacrolimus metabolism. This GeneFocus provides a CYP3A5 gene summary with a focus on aspects regarding standardized nomenclature. In addition, this review also summarizes recent changes and updates, including the retirement of several allelic variants and provides an overview of how PharmVar CYP3A5 star allele nomenclature is utilized by the Pharmacogenomics Knowledgebase (PharmGKB) and the Clinical Pharmacogenetics Implementation Consortium (CPIC).

The goals of the Association for Molecular Pathology Clinical Practice Committee's Pharmacogenomics (PGx) Working Group are to define the key attributes of pharmacogenetic alleles recommended for clinical testing and a minimum set of variants that should be included in clinical PGx genotyping assays. This article provides recommendations for a minimum panel of variant alleles (Tier 1) and an extended panel of variant alleles (Tier 2) that will aid clinical laboratories when designing assays for PGx testing. The Association for Molecular Pathology PGx Working Group considered the functional impact of the variant alleles, allele frequencies in multiethnic populations, the availability of reference materials, as well as other technical considerations for PGx testing when developing these recommendations. The ultimate goal of this Working Group is to promote standardization of PGx gene/allele testing across clinical laboratories. This article focuses on clinical TPMT and NUDT15 PGx testing, which may be applied to all thiopurine S-methyltransferase (TPMT) and nudix hydrolase 15 (NUDT15)-related medications. These recommendations are not to be interpreted as prescriptive, but to provide a reference guide.

The goals of the Association for Molecular Pathology Clinical Practice Committee's Pharmacogenomics (PGx) Working Group are to define the key attributes of pharmacogenetic alleles recommended for clinical testing, and to determine a minimal set of variants that should be included in clinical PGx genotyping assays. This document series provides recommendations on a minimal panel of variant alleles (Tier 1) and an extended panel of variant alleles (Tier 2) that will aid clinical laboratories in designing assays for PGx testing. When developing these recommendations, the Association for Molecular Pathology PGx Working Group considered the functional impact of the variant alleles, allele frequencies in multiethnic populations, the availability of reference materials, as well as other technical considerations with regard to PGx testing. The ultimate goal of this Working Group is to promote standardization of PGx gene/allele testing across clinical laboratories. This document is focused on clinical CYP2D6 PGx testing that may be applied to all cytochrome P450 2D6–metabolized medications. These recommendations are not meant to be interpreted as prescriptive but to provide a reference guide for clinical laboratories that may be either implementing PGx testing or reviewing and updating their existing platform.

Pharmacogenetic testing is increasingly available from clinical and research laboratories. However, only a limited number of quality control and other reference materials are currently available for many of the variants that are tested. The Association for Molecular Pathology Pharmacogenetic Work Group has published a series of papers recommending alleles for inclusion in clinical testing. Several of the alleles were not considered for tier 1 because of a lack of reference materials. To address this need, the Division of Laboratory Systems, Centers for Disease Control and Prevention–based Genetic Testing Reference Material (GeT-RM) program, in collaboration with members of the pharmacogenetic testing and research communities and the Coriell Institute for Medical Research, has characterized 18 DNA samples derived from Coriell cell lines. DNA samples were distributed to five volunteer testing laboratories for genotyping using three commercially available and laboratory developed tests. Several tier 2 variants, including CYP2C9∗13, CYP2C19∗35, the CYP2C cluster variant (rs12777823), two variants in VKORC1 (rs61742245 and rs72547529) related to warfarin resistance, and two variants in GGCX (rs12714145 and rs11676382) related to clotting factor activation, were identified among these samples. These publicly available materials complement the pharmacogenetic reference materials previously characterized by the GeT-RM program and will support the quality assurance and quality control programs of clinical laboratories that perform pharmacogenetic testing.

Pediatric intensive care unit (PICU) patients are exposed to multiple medications and are at high risk for adverse drug reactions. Pharmacogenomic (PGx) testing could help decrease their risk of adverse reactions. Although whole blood is preferred for PGx testing, blood volume in this population is often limited. However, for patients on mechanical ventilation, tracheal secretions are abundant, frequently suctioned, and discarded. Thus, the aim of this pilot study was to determine if tracheal aspirates could be used as a source of human genomic DNA for PGx testing. We successfully extracted DNA from tracheal secretions of all 23 patients in the study. The samples were successfully genotyped for ten clinically actionable single nucleotide variants across three cytochrome P450 genes (CYP2D6, CYP2C19, and CYP3A5). Using DNA from whole blood samples in eleven of the patients, we confirmed the accuracy of the genotyping with 100% concordance. Therefore, our results support the use of tracheal aspirates from mechanically ventilated children as an adequate biospecimen for clinical genetic testing.

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

Pharmacogenetic testing is increasingly provided by clinical and research laboratories; however, only a limited number of quality control and reference materials are currently available for many of the TPMT and NUDT15 variants included in clinical tests. To address this need, the Division of Laboratory Systems, Centers for Disease Control and Prevention-based Genetic Testing Reference Material (GeT-RM) coordination program, in collaboration with members of the pharmacogenetic testing and research communities and the Coriell Institute for Medical Research, has characterized 19 DNA samples derived from Coriell cell lines. DNA samples were distributed to four volunteer testing laboratories for genotyping using a variety of commercially available and laboratory developed tests and/or Sanger sequencing. Of the 12 samples characterized for TPMT, newly identified variants include TPMT∗2, ∗6, ∗12, ∗16, ∗21, ∗24, ∗32, ∗33, and ∗40; for the 7 NUDT15 reference material samples, newly identified variants are NUDT15∗2, ∗3, ∗4, ∗5, ∗6, and ∗9. In addition, a novel haplotype, TPMT∗46, was identified in this study. Preexisting data on an additional 11 Coriell samples, as well as some supplemental testing, were used to create comprehensive reference material panels for TPMT and NUDT15. These publicly available and well-characterized materials can be used to support the quality assurance and quality control programs of clinical laboratories performing clinical pharmacogenetic testing.

Patients with CKD often have uncontrolled hypertension despite polypharmacy. Pharmacogenomic drug-gene interactions (DGIs) may affect the metabolism or efficacy of antihypertensive agents. We report changes in hypertension control after providing a panel of 11 pharmacogenomic predictors of antihypertensive response.A prospective cohort with CKD and hypertension was followed to assess feasibility of pharmacogenomic testing implementation, self-reported provider utilization, and BP control. The analysis population included 382 subjects with hypertension who were genotyped for cross-sectional assessment of DGIs, and 335 subjects followed for 1 year to assess systolic BP (SBP) and diastolic BP (DBP).Most participants (58%) with uncontrolled hypertension had a DGI reducing the efficacy of one or more antihypertensive agents. Subjects with a DGI had 1.85-fold (95% CI, 1.2- to 2.8-fold) higher odds of uncontrolled hypertension, as compared with those without a DGI, adjusted for race, health system (safety-net hospital versus other locations), and advanced CKD (eGFR30 ml/min).There is a potential role for the addition of pharmacogenomic testing to optimize antihypertensive regimens in patients with CKD.

PURPOSE Precision medicine approaches, including germline pharmacogenetics (PGx) and management of drug-drug interactions (DDIs), are likely to benefit patients with advanced cancer who are frequently prescribed multiple concomitant medications to treat cancer and associated conditions. Our objective was to assess the potential opportunities for PGx and DDI management within a cohort of adults with advanced cancer. METHODS Medication data were collected from the electronic health records for 481 subjects since their first cancer diagnosis. All subjects were genotyped for variants with clinically actionable recommendations in Clinical Pharmacogenetics Implementation Consortium guidelines for 13 pharmacogenes. DDIs were defined as concomitant prescription of strong inhibitors or inducers with sensitive substrates of the same drug-metabolizing enzyme and were assessed for six major cytochrome P450 (CYP) enzymes. RESULTS Approximately 60% of subjects were prescribed at least one medication with Clinical Pharmacogenetics Implementation Consortium recommendations, and approximately 14% of subjects had an instance for actionable PGx, defined as a prescription for a drug in a subject with an actionable genotype. The overall subject-level prevalence of DDIs and serious DDIs were 50.3% and 34.8%, respectively. Serious DDIs were most common for CYP3A, CYP2D6, and CYP2C19, occurring in 24.9%, 16.8%, and 11.7% of subjects, respectively. When assessing PGx and DDIs together, approximately 40% of subjects had at least one opportunity for a precision medicine–based intervention and approximately 98% of subjects had an actionable phenotype for at least one CYP enzyme. CONCLUSION Our findings demonstrate numerous clinical opportunities for germline PGx and DDI management in adults with advanced cancer.

The Pharmacogene Variation Consortium (PharmVar) catalogues star (*) allele nomenclature for the polymorphic human CYP2C9 gene. Genetic variation within the CYP2C9 gene locus impacts the metabolism or bioactivation of many clinically important drugs, including nonsteroidal anti-inflammatory drugs, phenytoin, antidiabetic agents, and angiotensin receptor blockers. Variable CYP2C9 activity is of particular importance regarding efficacy and safety of warfarin and siponimod as indicated in their package inserts. This GeneFocus provides a comprehensive overview and summary of CYP2C9 and describes how haplotype information catalogued by PharmVar is utilized by the Pharmacogenomics Knowledgebase and the Clinical Pharmacogenetics Implementation Consortium.

Purpose: A number of institutions have clinically implemented CYP2D6 genotyping to guide drug prescribing. We compared implementation strategies of early adopters of CYP2D6 testing, barriers faced by both early adopters and institutions in the process of implementing CYP2D6 testing, and approaches taken to overcome these barriers. Methods: We surveyed eight early adopters of CYP2D6 genotyping and eight institutions in the process of adoption. Data were collected on testing approaches, return of results procedures, applications of genotype results, challenges faced, and lessons learned. Results: Among early adopters, CYP2D6 testing was most commonly ordered to assist with opioid and antidepressant prescribing. Key differences among programs included test ordering and genotyping approaches, result reporting, and clinical decision support. However, all sites tested for copy number variation and 9 common variants, and reported results in the medical record. Most sites provided automatic consultation and had designated personnel to assist with genotype-informed therapy recommendations. Primary challenges were related to stakeholder support, CYP2D6 gene complexity, phenotype assignment, and sustainability. Conclusion: There are specific challenges unique to CYP2D6 testing given the complexity of the gene and its relevance to multiple medications. Consensus lessons learned may guide those interested in pursuing similar clinical pharmacogenetic programs.

APOL1 risk alleles are associated with increased cardiovascular and chronic kidney disease (CKD) risk. It is unknown whether knowledge of APOL1 risk status motivates patients and providers to attain recommended blood pressure (BP) targets to reduce cardiovascular disease.Multicenter, pragmatic, randomized controlled clinical trial.6650 individuals with African ancestry and hypertension from 13 health systems.APOL1 genotyping with clinical decision support (CDS) results are returned to participants and providers immediately (intervention) or at 6 months (control). A subset of participants are re-randomized to pharmacogenomic testing for relevant antihypertensive medications (pharmacogenomic sub-study). CDS alerts encourage appropriate CKD screening and antihypertensive agent use.Blood pressure and surveys are assessed at baseline, 3 and 6 months. The primary outcome is change in systolic BP from enrollment to 3 months in individuals with two APOL1 risk alleles. Secondary outcomes include new diagnoses of CKD, systolic blood pressure at 6 months, diastolic BP, and survey results. The pharmacogenomic sub-study will evaluate the relationship of pharmacogenomic genotype and change in systolic BP between baseline and 3 months.To date, the trial has enrolled 3423 participants.The effect of patient and provider knowledge of APOL1 genotype on systolic blood pressure has not been well-studied. GUARDD-US addresses whether blood pressure improves when patients and providers have this information. GUARDD-US provides a CDS framework for primary care and specialty clinics to incorporate APOL1 genetic risk and pharmacogenomic prescribing in the electronic health record.ClinicalTrials.govNCT04191824.

(1) Background: Clinical decision support (CDS) is a vitally important adjunct to the implementation of pharmacogenomic-guided prescribing in clinical practice. A novel CDS was sought for the APOL1, NAT2, and YEATS4 genes to guide optimal selection of antihypertensive medications among the African American population cared for at multiple participating institutions in a clinical trial. (2) Methods: The CDS committee, made up of clinical content and CDS experts, developed a framework and contributed to the creation of the CDS using the following guiding principles: 1. medical algorithm consensus, 2. actionability, 3. context-sensitive triggers, 4. workflow integration, 5. feasibility, 6. interpretability, 7. portability, and 8. discrete reporting of lab results. (3) Results: Utilizing the principle of discrete patient laboratory and vital information, a novel CDS for APOL1, NAT2, and YEATS4 was created for use in a multi-institutional trial based on a medical algorithm consensus. The alerts are actionable and easily interpretable, clearly displaying the purpose and recommendations with pertinent laboratory results, vitals and links to ordersets with suggested antihypertensive dosages. Alerts were either triggered immediately once a provider starts to order relevant antihypertensive agents or strategically placed in workflow-appropriate general CDS sections in the electronic health record (EHR). Detailed implementation instructions were shared across institutions to achieve maximum portability. (4) Conclusions: Using sound principles, the created genetic algorithms were applied across multiple institutions. The framework outlined in this study should apply to other disease-gene and pharmacogenomic projects employing CDS.

Pharmacogenetic testing is increasingly available from clinical and research laboratories. However, only a limited number of quality control and other reference materials are currently available for many of the variants that are tested. The Association for Molecular Pathology Pharmacogenetic Work Group has published a series of papers recommending alleles for inclusion in clinical testing. Several of the alleles were not considered for tier 1 because of a lack of reference materials. To address this need, the Division of Laboratory Systems, Centers for Disease Control and Prevention–based Genetic Testing Reference Material (GeT-RM) program, in collaboration with members of the pharmacogenetic testing and research communities and the Coriell Institute for Medical Research, has characterized 18 DNA samples derived from Coriell cell lines. DNA samples were distributed to five volunteer testing laboratories for genotyping using three commercially available and laboratory developed tests. Several tier 2 variants, including CYP2C9∗13, CYP2C19∗35, the CYP2C cluster variant (rs12777823), two variants in VKORC1 (rs61742245 and rs72547529) related to warfarin resistance, and two variants in GGCX (rs12714145 and rs11676382) related to clotting factor activation, were identified among these samples. These publicly available materials complement the pharmacogenetic reference materials previously characterized by the GeT-RM program and will support the quality assurance and quality control programs of clinical laboratories that perform pharmacogenetic testing.

Purpose: The increased availability of clinical pharmacogenetic (PGx) guidelines and decreasing costs for genetic testing have slowly led to increased utilization of PGx testing in clinical practice. Preemptive PGx testing, where testing is performed in advance of drug prescribing, is one means to ensure results are available at the time of prescribing decisions. However, the most efficient and effective methods to clinically implement this strategy remain unclear. Methods: In this report, we compare and contrast implementation strategies for preemptive PGx testing by 15 early-adopter institutions. We surveyed these groups, collecting data on testing approaches, team composition, and workflow dynamics, in addition to estimated third-party reimbursement rates. Results: We found that while preemptive PGx testing models varied across sites, institutions shared several commonalities, including methods to identify patients eligible for testing, involvement of a precision medicine clinical team in program leadership, and the implementation of pharmacogenes with Clinical Pharmacogenetics Implementation Consortium guidelines available. Lastly, while reimbursement rate data were difficult to obtain, the data available suggested that reimbursement rates for preemptive PGx testing remain low. Conclusion: These findings should inform the establishment of future implementation efforts at institutions considering a preemptive PGx testing program.

Background Translating pharmacogenetic research findings that have shown clinical efficacy into sustainable, routine clinical care at the institutional level requires strong evidence of improved patient outcomes bolstered by equitable reimbursement and a sound financial analysis. Although extensive research on the clinical value of pharmacogenetics has been completed, adoption into clinical practice lags due to a lack of evidence of clinical effectiveness and limited reimbursement. Methods The Sustainability Working Group within the NHGRI IGNITE I Network conducted an online survey of funded and non-funded IGNITE members to determine which genes they are researching, which have been translated into clinical practice, and how tests are billed. Data from the online surveys was consolidated and analyzed with results being tabulated for key findings. Due to the limited sample size, statistical analysis was forgone and results should be considered directional in nature. Results Fifteen out of twenty (75%) online survey responses were received and analyzed from IGNITE member sites delivering clinical care. Forty different genes were identified as being used for either research or clinical care. Thirty-two different genes were reported as being used clinically, an average of 6.9 genes were reported per site. Twenty-two and twenty-one genes were reported as being billed to third party payers or patients respectively. Although the survey did not ask whether sites submitting for reimbursement received payment, Medicare and Medicaid only reimburse for 6 of the 40 (15%) genes being tested. Of the 40 genes, 18 are rated by CPIC as having A/B level of evidence with the remainder being rated as C/D or having no rating. Approximately 32% more A/B rated genes were being reported clinically than non-A/B. Conclusion Adoption of pharmacogenetic testing continues to lag even at sites where leading experts conduct research and have the capability to report tests clinically. Clinical research that supports CPIC A level of evidence is important for provider and payer support. Adoption of pharmacogentic testing must also be justified financially, reimbursement is one key factor, and more health economic studies are needed in order to capture the value created by preventing drug-gene adverse events, emergency room visits, and hospitalizations.

The Pharmacogene Variation Consortium (PharmVar) catalogues star (*) allele nomenclature for the polymorphic human CYP2C19 gene. CYP2C19 genetic variation impacts the metabolism of many drugs and has been associated with both, efficacy and safety issues for several commonly prescribed medications. This GeneFocus provides a comprehensive overview and summary of CYP2C19 and describes how haplotype information catalogued by PharmVar is utilized by the Pharmacogenomics Knowledgebase (PharmGKB) and the Clinical Pharmacogenetics Implementation Consortium (CPIC).

Chronic administration of efavirenz is associated with decreased serum bilirubin levels, probably through induction of UGT1A1. We assessed the impact of efavirenz monotherapy and UGT1A1 phenotypes on total, conjugated, and unconjugated serum bilirubin levels in healthy volunteers. Healthy volunteers were enrolled into a clinical study designed to address efavirenz pharmacokinetics, drug interactions, and pharmacogenetics. Volunteers received multiple oral doses (600 mg/day for 17 days) of efavirenz. Serum bilirubin levels were obtained at study entry and 1 week after completion of the study. DNA genotyping was performed for UGT1A1 [*80 (C>T), *6 (G>A), *28 (TA(7)), *36 (TA(5)), and *37 (TA(8))] and for SLCO1B1 [*5 (521T>C) and *1b (388A>G] variants. Diplotype predicted phenotypes were classified as normal, intermediate, and slow metabolizers. Compared with bilirubin levels at screening, treatment with efavirenz significantly reduced total, conjugated, and unconjugated bilirubin. After stratification by UGT1A1 phenotypes, there was a significant decrease in total bilirubin among all phenotypes, conjugated bilirubin among intermediate metabolizers, and unconjugated bilirubin among normal and intermediate metabolizers. The data also show that UGT1A1 genotype predicts serum bilirubin levels at baseline, but this relationship is lost after efavirenz treatment. SLCO1B1 genotypes did not predict bilirubin levels at baseline or after efavirenz treatment. Our data suggest that efavirenz may alter bilirubin disposition mainly through induction of UGT1A1 metabolism and efflux through multidrug resistance–associated protein 2. SIGNIFICANCE STATEMENT: Efavirenz likely alters the pharmacokinetics of coadministered drugs, potentially causing lack of efficacy or increased adverse effects, as well as the disposition of endogenous compounds relevant in homeostasis through upregulation of UGT1A1 and multidrug resistance–associated protein 2. Measurement of unconjugated and conjugated bilirubin during new drug development may provide mechanistic understanding regarding enzyme and transporters modulated by the new drug.

Aims: To validate a laboratory-developed test for the nucleoside transporter, SLC28A3, which has been associated with an increased risk of anthracycline-induced cardiomyopathy. Methods: We used Taqman(®) allele discrimination to test for two variants of the SLC28A3 gene: rs7853758 (c.1381C>T) and rs885004 (c.862-360C>T). Results: During the validation process, we noted that several DNA samples obtained from the Coriell Cell Repository (Camden, NJ) were positive for both the c.1381 C > T and c.862-360C>T variants and another variant allele for either c.1381 C > T or c.862-360C>T (e.g., c.1381C>T homozygous/c.862-360C>T heterozygous, c.1381C>T homozygous/c.862-360C>T homozygous). We used de-identified DNA samples from trios of family members (mother, father, and child) to establish that the c.1381 C > T and c.862-360C>T variant alleles could be inherited in cis on the same chromosome. Conclusions: Samples containing three variant alleles suggest that the c.1381 C > T and c.862-360C>T are in cis on the chromosome in some individuals and may have implications when calculating anthracycline-induced cardiomyopathy risk. In this study, we confirm a novel haplotype of SLC28A3 using familial studies.

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.

Background: Tramadol and codeine are metabolized by CYP2D6 and are subject to drug–gene and drug–drug interactions. Methods: This interim analysis examined prescribing behavior and efficacy in 102 individuals prescribed tramadol or codeine while receiving pharmaco-genotyping as part of the INGENIOUS trial (NCT02297126). Results: Within 60 days of receiving tramadol or codeine, clinicians more frequently prescribed an alternative opioid in ultrarapid and poor metabolizers (odds ratio: 19.0; 95% CI: 2.8–160.4) as compared with normal or indeterminate metabolizers (p = 0.01). After adjusting the CYP2D6 activity score for drug–drug interactions, uncontrolled pain was reported more frequently in individuals with reduced CYP2D6 activity (odds ratio: 0.50; 95% CI: 0.25–0.94). Conclusion: Phenoconversion for drug–drug and drug–gene interactions is an important consideration in pharmacogenomic implementation; drug–drug interactions may obscure the potential benefits of genotyping.

Hospital systems increasingly utilize pharmacogenomic testing to inform clinical prescribing. Successful implementation efforts have been modeled at many academic centers. In contrast, this report provides insights into the formation of a pharmacogenomics consultation service at a safety-net hospital, which predominantly serves low-income, uninsured, and vulnerable populations. The report describes the INdiana GENomics Implementation: an Opportunity for the UnderServed (INGENIOUS) trial and addresses concerns of adjudication, credentialing, and funding.

Pharmacogenetic testing is increasingly available from clinical laboratories. However, only a limited number of quality control and other reference materials are currently available to support clinical testing. To address this need, the Centers for Disease Control and Prevention–based Genetic Testing Reference Material Coordination Program, in collaboration with members of the pharmacogenetic testing community and the Coriell Cell Repositories, has characterized 137 genomic DNA samples for 28 genes commonly genotyped by pharmacogenetic testing assays (CYP1A1, CYP1A2, CYP2A6, CYP2B6, CYP2C8, CYP2C9, CYP2C19, CYP2D6, CYP2E1, CYP3A4, CYP3A5, CYP4F2, DPYD, GSTM1, GSTP1, GSTT1, NAT1, NAT2, SLC15A2, SLC22A2, SLCO1B1, SLCO2B1, TPMT, UGT1A1, UGT2B7, UGT2B15, UGT2B17, and VKORC1). One hundred thirty-seven Coriell cell lines were selected based on ethnic diversity and partial genotype characterization from earlier testing. DNA samples were coded and distributed to volunteer testing laboratories for targeted genotyping using a number of commercially available and laboratory developed tests. Through consensus verification, we confirmed the presence of at least 108 variant pharmacogenetic alleles. These samples are also being characterized by other pharmacogenetic assays, including next-generation sequencing, which will be reported separately. Genotyping results were consistent among laboratories, with most differences in allele assignments attributed to assay design and variability in reported allele nomenclature, particularly for CYP2D6, UGT1A1, and VKORC1. These publicly available samples will help ensure the accuracy of pharmacogenetic testing.

The Clinical Laboratory Improvement Amendments of 1988 require that pharmacogenetic genotyping methods need to be established according to technical standards and laboratory practice guidelines before testing can be offered to patients. Testing methods for variants in ABCB1, CBR3, COMT, CYP3A7, C8ORF34, FCGR2A, FCGR3A, HAS3, NT5C2, NUDT15, SBF2, SEMA3C, SLC16A5, SLC28A3, SOD2, TLR4, and TPMT were validated in a Clinical Laboratory Improvement Amendments–accredited laboratory. Because no known reference materials were available, existing DNA samples were used for the analytical validation studies. Pharmacogenetic testing methods developed here were shown to be accurate and 100% analytically sensitive and specific. Other Clinical Laboratory Improvement Amendments–accredited laboratories interested in offering pharmacogenetic testing for these genetic variants, related to genotype-guided therapy for oncology, could use these publicly available samples as reference materials when developing and validating new genetic tests or refining current assays.

Purpose: The Veterans Health Administration (VHA) Clinical Pharmacogenetics Subcommittee is charged with making recommendations about whether specific pharmacogenetic tests should be used in healthcare at VHA facilities. We describe a process to inform VHA pharmacogenetic testing policy. Methods: After developing consensus definitions of clinical validity and utility, the Subcommittee identified salient drug-gene pairs with potential clinical application in VHA. Members met monthly to discuss each drug-gene pair, the evidence of clinical utility for the associated pharmacogenetic test, and any VHA-specific testing considerations. The Subcommittee classified each test as strongly recommended, recommended, or not routinely recommended before drug initiation. Results: Of 30 drug-gene pair tests reviewed, the Subcommittee classified 4 (13%) as strongly recommended, including HLA-B*15:02 for carbamazepine-associated Stevens-Johnston syndrome and G6PD for rasburicase-associated hemolytic anemia; 12 (40%) as recommended, including CYP2D6 for codeine toxicity; and 14 (47%) as not routinely recommened, such as CYP2C19 for clopidogrel dosing. Conclusion: Only half of drug-gene pairs with high clinical validity received Subcommittee support for policy promoting their widespread use across VHA. The Subcommittee generally found insufficient evidence of clinical utility or available, effective alternative strategies for the remainders. Continual evidence review and rigorous outcomes research will help promote the translation of pharmacogenetic discovery to healthcare.

Objectives This multicenter pragmatic investigation assessed outcomes following clinical implementation of CYP2C19 genotype–guided antiplatelet therapy after percutaneous coronary intervention (PCI). Background CYP2C19 loss-of-function alleles impair clopidogrel effectiveness after PCI. Methods After clinical genotyping, each institution recommended alternative antiplatelet therapy (prasugrel, ticagrelor) in PCI patients with a loss-of-function allele. Major adverse cardiovascular events (defined as myocardial infarction, stroke, or death) within 12 months of PCI were compared between patients with a loss-of-function allele prescribed clopidogrel versus alternative therapy. Risk was also compared between patients without a loss-of-function allele and loss-of-function allele carriers prescribed alternative therapy. Cox regression was performed, adjusting for group differences with inverse probability of treatment weights. Results Among 1,815 patients, 572 (31.5%) had a loss-of-function allele. The risk for major adverse cardiovascular events was significantly higher in patients with a loss-of-function allele prescribed clopidogrel versus alternative therapy (23.4 vs. 8.7 per 100 patient-years; adjusted hazard ratio: 2.26; 95% confidence interval: 1.18 to 4.32; p = 0.013). Similar results were observed among 1,210 patients with acute coronary syndromes at the time of PCI (adjusted hazard ratio: 2.87; 95% confidence interval: 1.35 to 6.09; p = 0.013). There was no difference in major adverse cardiovascular events between patients without a loss-of-function allele and loss-of-function allele carriers prescribed alternative therapy (adjusted hazard ratio: 1.14; 95% confidence interval: 0.69 to 1.88; p = 0.60). Conclusions These data from real-world observations demonstrate a higher risk for cardiovascular events in patients with a CYP2C19 loss-of-function allele if clopidogrel versus alternative therapy is prescribed. A future randomized study of genotype-guided antiplatelet therapy may be of value.

This manuscript provides nomenclature recommendations developed by an international workgroup to increase transparency and standardization of pharmacogenetic (PGx) result reporting. Presently, sequence variants identified by PGx tests are described using different nomenclature systems. In addition, PGx analysis may detect different sets of variants for each gene, which can affect interpretation of results. This practice has caused confusion and may thereby impede the adoption of clinical PGx testing. Standardization is critical to move PGx forward.

The US Food and Drug Administration (FDA) notified Congress July 31, 2014,1 of its intent to regulate laboratory developed tests. These encompass thousands of clinical assays currently used in medical practice including most pharmacogenetic tests. This guidance has the potential to impact the innovation and sustainability of pharmacogenetic research and its clinical implementation. We anticipate that several requirements could have substantial implications for both clinical research and the clinical implementation of pharmacogenetics. Input from federal funding agencies (eg, National Institutes of Health, Agency for Health Research Quality, Patient-Centered Outcomes Research Institute) will be needed to clarify who will bear the financial burden of some of the increased requirements. Further, key clarifications will be required from the FDA to understand how implementation will occur over the next decade (Figure 1). Clarity now will allow the research and clinical communities to effectively plan and budget for these changes. Below, we identify and describe the key issues. Figure 1 FDA timeline for implementation of oversight of laboratory-developed tests. *Time from FDA comment review and congressional input to the release of the final guidance is unknown. **PMA process is based on a per se demonstration of safety and effectiveness ... Over the past decades, many pharmacogenomics biomarkers that are responsible for clinical variability in the pharmacokinetics and pharmacodynamics of drug therapy have been identified. These studies have mostly been conducted using laboratory-developed procedures or tests (LDTs).2 According to the published guidance, it appears that these clinical discovery and validation studies will now need to obtain investigational device exemptions (IDEs) from the FDA. For example, conducting a simple clinical study to determine if genetic variants in a drug-metabolizing enzyme are associated with the pharmacokinetics of a drug would require that the genotyping assay laboratory obtain an IDE before conducting the study. IDE submissions require substantial expertise and resources that are not typically common in academic research centers or Clinical Laboratory Improvement Amendment (CLIA)–certified clinical laboratories. This may even be new for drug companies that may have expertise in new drug application submissions, but not IDEs. Therefore, it will substantially increase the cost and resources needed to conduct these studies. It is not clear to us what harm has been done that will be solved by the IDE requirement that justifies such a change. The question of funding is important. Will funding agencies be willing to support these additional costs, or will it just reduce the scope or number of studies that will be able to be conducted? We suggest that the FDA use its enforcement discretion and not require IDEs for these types of translational studies. Based on the language in the guidance document, clinical (ie, CLIA) laboratories providing pharmacogenetic genotyping using an LDT will be required to obtain premarket approvals (PMAs). As there are very few FDA-approved pharmacogenetic in vitro diagnostic devices, most clinical testing using LDTs is performed in CLIA laboratories, often with College of American Pathologists accreditation. The time and costs involved in obtaining PMAs are high. In a 2010 survey and analysis conducted by AdvaMed,3 US patients waited an average of 2 years longer than those in Europe to gain access to new medical technologies, which was attributable to the FDA device approval. In addition, the average total cost to bring a low to moderate in vitro diagnostic through the FDA 510(k) process was $31 million, with $24 million spent on FDA-dependent or -related activities. For higher-risk products submitted for approval, the average cost increased to $94 million, with $75 million linked to FDA requirements. In addition, the industry reported an average time from first communication with the FDA to clearance or approval ranging from 31 to 54 months. The FDA claims that CLIA certification of a laboratory performing an LDT does not provide the safety, oversight, and adverse event reporting requirements that exist with devices cleared or approved by the agency; however, this has not been supported by statistically valid evidence that this has caused harm to patients. At least publicly, they have only cited antidotal cases where a patient received inappropriate therapy as a result of a faulty LDT. In the FDA's notice to Congress of its intent to initiate oversight of LDTs (Federal Register/Vol. 79, No. 192/Friday, October 3, 2014), there was no data submitted that supports the claim that the status quo condition was causing harm. Despite this lack of evidence, it does express a concern about the potential risk to patients if LDTs do not receive oversight. The FDA in their October 2014 filing in the Federal Register noted that the complexity and expanded use of LDTs today are significantly different from 1976 when the Congress enacted Medical Device Amendment (MDA) and expanded the FDA oversight of medical devices intended for human use. To support the oversight of LDTs, the FDA is using the 1976 MDA in attempt to redefine laboratories that perform LDTs as manufacturers of medical devices intended for human use. There are potentially many implications, including financial and health economics, if the FDA is allowed to categorize these laboratories as manufacturers. During the September 9, 2014 House Committee on Energy and Commerce Hearing on the Proposed FDA Laboratory Developed Test Policy, Dr. Jeff Shuren, the Director of the Center for Devices and Radiological Health at the FDA, stated that the “FDA has not conducted a formal economic analysis” to justify the increased time and cost required to implement the proposed framework. In this context, it would be valuable to consider a “fast track” approval process or other creative approaches for new tests that have evidence of life-saving benefits (i.e., HLA-B*57:01 and abacavir), in the same way as drugs has occurred for drug approvals. Currently, many laboratories decide on a genotyping platform that fits the needs of their laboratory and then design LDTs for multiple assays on a single platform. However, with companion diagnostics in which the drug and device are approved together by the FDA, drug and device manufacturers essentially have 1 instrument per drug, making it necessary for the laboratories to obtain multiple different instruments to provide pharmacogenomic services for multiple drugs. The initial capital investment and routine running costs (eg, maintenance contracts, training, and competency) will thus be much higher for laboratories. Depending on the device labeling, it could even require different instruments for the same genetic test when used for different drugs (eg, CYP2D6 testing for codeine and antidepressants), even though they test the exact same genetic variants. If the device (ie, instrument and test kit) is used for a different intended use (ie, same gene, different drug), then the laboratory will need to submit to the FDA to demonstrate cross-platform equivalency. Last, input from payers will be needed to understand how reimbursement for clinical testing will be handled. For example, once a test is FDA-approved or -cleared, will the payers reimburse those tests at a significantly higher rate, so the clinical laboratory can recoup its cost for the FDA submission? The current procedural terminology coding system for reimbursement is platform agnostic. Though Centers for Medicare and Medicaid Service has a pilot program to differentiate reimbursement based on platform,4 will the payers even allow reimbursement for non-FDA-approved tests when there are FDA-approved tests available? In conclusion, many questions remain to be answered related to the new FDA guidance on LDTs with respect to clinical research and implementation of pharmacogenetic testing. The FDA should provide specific evidence about the harm caused by LDTs, so a less obstructive solution could be identified. Although it may be true that there are some CLIA-accredited laboratories that have developed their own methods and tests that do not meet acceptable quality standards, why not selectively pursue these entities through existing or enhanced CLIA regulations rather than imposing FDA-directed oppressive and costly guidance across the entire spectrum of laboratory service providers and researchers?

Pharmacogenetic testing is becoming more common; however, very few quality control and other reference materials that cover alleles commonly included in such assays are currently available. To address these needs, the Centers for Disease Control and Prevention's Genetic Testing Reference Material Coordination Program, in collaboration with members of the pharmacogenetic testing community and the Coriell Cell Repositories, have characterized a panel of 107 genomic DNA reference materials for five loci (CYP2D6, CYP2C19, CYP2C9, VKORC1, and UGT1A1) that are commonly included in pharmacogenetic testing panels and proficiency testing surveys. Genomic DNA from publicly available cell lines was sent to volunteer laboratories for genotyping. Each sample was tested in three to six laboratories using a variety of commercially available or laboratory-developed platforms. The results were consistent among laboratories, with differences in allele assignments largely related to the manufacturer's assay design and variable nomenclature, especially for CYP2D6. The alleles included in the assay platforms varied, but most were identified in the set of 107 DNA samples. Nine additional pharmacogenetic loci (CYP4F2, EPHX1, ABCB1, HLAB, KIF6, CYP3A4, CYP3A5, TPMT, and DPD) were also tested. These samples are publicly available from Coriell and will be useful for quality assurance, proficiency testing, test development, and research.