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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.

Spinal muscular atrophy (SMA) is an autosomal recessive disorder predominately caused by bi-allelic loss of the SMN1 gene. Increased copies of SMN2, a low functioning nearly identical paralog, are associated with a less severe phenotype. SMA was recently recommended for inclusion in newborn screening. Clinical laboratories must accurately measure SMN1 and SMN2 copy number to identify SMA patients and carriers, and to identify individuals likely to benefit from therapeutic interventions. Having publicly available and appropriately characterized reference materials with various combinations of SMN1 and SMN2 copy number variants is critical to assure accurate SMA clinical testing. To address this need, the CDC-based Genetic Testing Reference Materials Coordination Program, in collaboration with members of the genetic testing community and the Coriell Institute for Medical Research, has characterized 15 SMA reference materials derived from publicly available cell lines. DNA samples were distributed to four volunteer testing laboratories for genotyping using three different methods. The characterized samples had zero to four copies of SMN1 and zero to five copies SMN2. The samples also contained clinically important allele combinations (eg, zero copies SMN1, three copies SMN2), and several had markers indicative of an SMA carrier. These and other reference materials characterized by the Genetic Testing Reference Materials Coordination Program are available from the Coriell Institute and are proposed to support the quality of clinical laboratory 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.

SWI/SNF-related intellectual disability disorders (SSRIDDs) are rare neurodevelopmental disorders characterized by developmental disability, coarse facial features, and fifth digit/nail hypoplasia that are caused by pathogenic variants in genes that encode for members of the SWI/SNF (or BAF) family of chromatin remodeling complexes. We have identified 12 individuals with rare variants (10 loss-of-function, 2 missense) in the BICRA (BRD4 interacting chromatin remodeling complex-associated protein) gene, also known as GLTSCR1, which encodes a subunit of the non-canonical BAF (ncBAF) complex. These individuals exhibited neurodevelopmental phenotypes that include developmental delay, intellectual disability, autism spectrum disorder, and behavioral abnormalities as well as dysmorphic features. Notably, the majority of individuals lack the fifth digit/nail hypoplasia phenotype, a hallmark of most SSRIDDs. To confirm the role of BICRA in the development of these phenotypes, we performed functional characterization of the zebrafish and Drosophila orthologs of BICRA. In zebrafish, a mutation of bicra that mimics one of the loss-of-function variants leads to craniofacial defects possibly akin to the dysmorphic facial features seen in individuals harboring putatively pathogenic BICRA variants. We further show that Bicra physically binds to other non-canonical ncBAF complex members, including the BRD9/7 ortholog, CG7154, and is the defining member of the ncBAF complex in flies. Like other SWI/SNF complex members, loss of Bicra function in flies acts as a dominant enhancer of position effect variegation but in a more context-specific manner. We conclude that haploinsufficiency of BICRA leads to a unique SSRIDD in humans whose phenotypes overlap with those previously reported.

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

The goal of the Association for Molecular Pathology (AMP) Clinical Practice Committee's AMP Pharmacogenomics (PGx) Working Group is to define the key attributes of PGx alleles recommended for clinical testing and a minimum set of variants that should be included in clinical PGx genotyping assays. This document series 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 AMP PGx Working Group considered functional impact of the variants, 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 is to promote standardization of PGx gene/allele testing across clinical laboratories. These recommendations are not to be interpreted as prescriptive but to provide a reference guide. Of note, a separate article with recommendations for CYP2C9 allele selection was previously developed by the PGx Working Group that can be applied broadly to CYP2C9-related medications. The warfarin allele recommendations in this report incorporate the previous CYP2C9 allele recommendations and additional genes and alleles that are specific to warfarin 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.

The goals of the Association for Molecular Pathology Pharmacogenomics (PGx) Working Group of the Association for Molecular Pathology Clinical Practice Committee are to define the key attributes of PGx alleles recommended for clinical testing and a minimum set of variants that should be included in clinical PGx genotyping assays. This document 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 CYP2C9 testing. The Working Group considered the functional impact of the variants, allele frequencies in different populations and ethnicities, the availability of reference materials, and other technical considerations for PGx testing when developing these recommendations. Our goal is to promote standardization of testing PGx genes and alleles across clinical laboratories. These recommendations are not to be interpreted as restrictive but to provide a reference guide. The current document will focus on CYP2C9 testing that can be applied to all CYP2C9-related medications. A separate recommendation on warfarin PGx testing is being developed to include recommendations on CYP2C9 alleles and additional warfarin sensitivity–associated genes and alleles.

(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.

BackgroundPatients with chronic kidney disease (CKD) often have uncontrolled hypertension despite polypharmacy. Pharmacogenomic drug-gene interactions (DGIs) may impact the metabolism or efficacy of antihypertensive agents. We hypothesized that providing a panel of 11 pharmacogenomic predictors of antihypertensive response would improve hypertension control.MethodsA prospective cohort with CKD and hypertension was followed to assess the effect of pharmacogenomic testing on blood pressure control. The analysis population included 382 hypertensive subjects genotyped for cross-sectional assessment of drug-gene interactions and 335 subjects followed for 1 year to assess systolic (SBP) and diastolic blood pressure (DBP).ResultsMost participants (58.2%) with uncontrolled hypertension had a DGI reducing the efficacy of one or more antihypertensive agents. Subjects with a DGI had 1.88-fold (95% CI 1.2-2.8) higher odds of uncontrolled hypertension as compared to those without a DGI, adjusted for race and CKD grade. CYP2C9 reduced metabolism genotypes were associated with losartan response and uncontrolled hypertension (Odds Ratio 5.2, CI 1.9 -14.7). CYP2D6 intermediate or poor metabolizers had less frequent uncontrolled hypertension compared to normal metabolizers taking metoprolol or carvedilol (OR 0.55, CI 0.3-0.95). In 335 subjects completing 1 year follow-up, SBP (−4.0 mmHg, CI 1.6-6.5) and DBP (−3.3 mmHg, CI 2.0-4.6) were improved. The magnitude of reductions in SBP (−14.8 mmHg, CI 10.3-19.3) and DBP (−8.4 mmHg, CI 5.9-10.9) were greatest in the 90 individuals with uncontrolled hypertension and an actionable genotype.ConclusionsThere is a potential role for the addition of pharmacogenomic testing to optimize antihypertensive regimens in patients with CKD.

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.

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 Pharmacogenomics (PGx) testing can reduce toxicities and improve efficacy of several drugs used to treat cancer and associated symptoms. PGx results can be determined from germline whole-exome sequencing (WES), but somatic mutations may cause discordance between tumor and germline DNA. Since clinical diagnostic sequencing in oncology frequently only includes tumor DNA, there would be clinical value in calling germline PGx genotypes from tumor DNA. Thus, the purpose of this study was to assess the feasibility of using somatic WES data to call germline PGx genotypes. Methods Germline and somatic WES data were obtained as part of the clinical workflow for 64 patients treated at the solid molecular tumor board clinic at Indiana University. Aldy v3.3 was implemented in LifeOmic’s Precision Health Cloud™ to call PGx genotypes from somatic WES. Somatic Aldy calls were compared with previously validated Aldy germline calls for 8 genes: CYP2C9, CYP2C19, CYP2D6, CYP3A4, CYP3A5, CYP4F2, DPYD, and TPMT. Somatic read depth was >100x, except for the intronic CYP3A4*22 variant, which was >30x. Results Somatic and germline Aldy calls were compared for a total of 512 genotypes and 56 (11%) calls were discordant. Discordant calls were most common for CYP2B6 (23.4%), followed by CYP2D6 (14.1%), CYP2C19 (10.9%), CYP2C8 (6.3%), and DPYD (6.3%). In contrast, all Aldy calls were concordant for CYP3A5 and TPMT. 38 out of 64 subjects (59%) had discordant calls for at least one gene. The most common first cancer diagnoses in our cohort were colorectal (9.3%), breast (7.8%), and pancreatic (7.8%), and the rates of discordant Aldy calls did not differ by cancer type (p>0.05 for all cancer types). Based on our analyses of discordant calls, we anticipate that adjusting Aldy’s thresholds for variant calling may allow Aldy to determine genotypes from somatic WES data. Conclusion In most cases, genotype calls of drug metabolism genes from tumor DNA reflected the germline genotypes; however, additional work needs to be done to determine if the remaining discordant calls can be corrected by modifying the informatics tools or if they are due to somatic mutations. Citation Format: Wilberforce A. Osei, Tyler Shugg, Reynold C. Ly, Steven M. Bray, Benjamin A. Salisbury, Ryan R. Ratcliff, Victoria M. Pratt, Ibrahim Numanagić, Todd Skaar. Pharmacogenomics genotyping from clinical somatic whole exome sequencing: Aldy, a computational tool [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1151.

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).

A precision health initiative was implemented across a multi-hospital health system, wherein a panel of genetic variants was tested and utilized in the clinical care of chronic kidney disease (CKD) patients. Pharmacogenomic predictors of antihypertensive response and genomic predictors of CKD were provided to clinicians caring for nephrology patients. To assess clinician knowledge, attitudes, and willingness to act on genetic testing results, a Likert-scale survey was sent to and self-administered by these nephrology providers (N = 76). Most respondents agreed that utilizing pharmacogenomic-guided antihypertensive prescribing is valuable (4.0 &plusmn, 0.7 on a scale of 1 to 5, where 5 indicates strong agreement). However, the respondents also expressed reluctance to use genetic testing for CKD risk stratification due to a perceived lack of supporting evidence (3.2 &plusmn, 0.9). Exploratory sub-group analyses associated this reluctance with negative responses to both knowledge and attitude discipline questions, thus suggesting reduced exposure to and comfort with genetic information. Given the evolving nature of genomic implementation in clinical care, further education is warranted to help overcome these perception barriers.

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.

Purpose While there is growing scientific evidence for and significant advances in the use of genomic technologies in medicine, there is a significant lag in the clinical adoption and sustainability of genomic medicine. Here we describe the findings from the National Human Genome Research Institute’s (NHGRI) Implementing GeNomics In pracTicE (IGNITE) Network in identifying key constructs, opportunities, and challenges associated with driving sustainability of genomic medicine in clinical practice. Methods Network members and affiliates were surveyed to identify key drivers associated with implementing and sustaining a genomic medicine program. Tallied results were used to develop and weigh key constructs/drivers required to support sustainability of genomic medicine programs. Results The top 3 driver-stakeholder dyads were 1. Genomic training for providers, 2. Genomic clinical decision support (CDS) tools embedded in the Electronic Health Record (EHR), 3. Third party reimbursement for genomic testing. Conclusion Priorities may differ depending on healthcare systems when comparing the current state of key drivers vs. projected needs for supporting genomic medicine sustainability. Thus we provide gap-filling guidance based on IGNITE members’ experiences. Although results are limited to findings from the IGNITE network, their implementation, scientific and clinical experience may be used as a road map by others considering implementing genomic medicine programs.

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.

This document was developed by the Pharmacogenomics (PGx) Working Group of the Association for Molecular Pathology Clinical Practice Committee, whose aim is to recommend variants for inclusion in clinical pharmacogenomic testing panels. The goals of the Association for Molecular Pathology PGx Working Group are to define the key attributes of PGx alleles recommended for clinical testing and to define a minimum set of variants that should be included in clinical PGx genotyping assays. These recommendations include a minimum panel of variant alleles (tier 1) and an extended panel of variant alleles (tier 2) that will aid clinical laboratories when designing PGx assays. The Working Group considered variant allele frequencies in different populations and ethnicities, the availability of reference materials, and other technical considerations for PGx testing when developing these recommendations. These CYP2C19 genotyping recommendations are the first of a series of recommendations for PGx testing. These recommendations are not to be interpreted as restrictive, but they are meant to provide a helpful guide.

High-throughput sequencing provides the means to determine the allelic decomposition for any gene of interest—the number of copies and the exact sequence content of each copy of a gene. Although many clinically and functionally important genes are highly polymorphic and have undergone structural alterations, no high-throughput sequencing data analysis tool has yet been designed to effectively solve the full allelic decomposition problem. Here we introduce a combinatorial optimization framework that successfully resolves this challenging problem, including for genes with structural alterations. We provide an associated computational tool Aldy that performs allelic decomposition of highly polymorphic, multi-copy genes through using whole or targeted genome sequencing data. For a large diverse sequencing data set, Aldy identifies multiple rare and novel alleles for several important pharmacogenes, significantly improving upon the accuracy and utility of current genotyping assays. As more data sets become available, we expect Aldy to become an essential component of genotyping toolkits., Many genes of functional and clinical significance are highly polymorphic and experience structural alterations. Here, Numanagić et al. develop Aldy, a computational tool for resolving the copy number and the sequence content of each copy of a gene by analyzing whole or targeted genome sequencing data.

Objectives Implementing new programs to support precision medicine in clinical settings is a complex endeavor. We describe challenges and potential solutions based on the Indiana GENomics Implementation: an Opportunity for the Underserved (INGenious) program at Eskenazi Health—one of six sites supported by the Implementing GeNomics In pracTicE network grant of the National Institutes of Health/National Human Genome Research Institute. INGenious is an implementation of a panel of genomic tests. Methods We conducted a descriptive case study of the implementation of this pharmacogenomics program, which has a wide scope (14 genes, 27 medications) and a diverse population (patients who often have multiple chronic illnesses, in a large urban safety-net hospital and its outpatient clinics). Challenges We placed the clinical pharmacogenomics implementation challenges into six categories: patient education and engagement in care decision making; clinician education and changes in standards of care; integration of technology into electronic health record systems; translational and implementation sciences in real-world clinical environments; regulatory and reimbursement considerations, and challenges in measuring outcomes. A cross-cutting theme was the need for careful attention to workflow. Our clinical setting, a safety-net health care system, presented some distinctive challenges. Patients often had multiple chronic illnesses and sometimes were taking more than one pharmacogenomics-relevant medication. Reaching patients for recruitment or follow-up was another challenge. Conclusions New, large-scale endeavors in health care are challenging. A description of the challenges that we encountered and the approaches that we adopted to address them may provide insights for those who implement and study innovations in other health care systems.

Coffin-Lowry syndrome (CLS) is a rare X-linked disorder characterized by moderate to severe intellectual disability, hypotonia, craniofacial features, tapering digits, short stature, and skeletal deformities. Using whole exome sequencing and high-resolution targeted comparative genomic hybridization array analysis, we identified a novel microduplication encompassing exons five through nine of RPS6KA3 in three full brothers. Each brother presented with intellectual disability and clinical and radiographic features consistent with CLS. qRT-PCR analyses performed on mRNA from the peripheral blood of the three siblings revealed a marked reduction of RPS6KA3 levels suggesting a loss-of-function mechanism. PCR analysis of the patients' cDNA detected a band greater than expected for an exon 4-10 amplicon, suggesting this was likely a direct duplication that lies between exons 4 through 10, which was later confirmed by Sanger sequencing. This microduplication is only the third intragenic duplication of RPS6KA3, and the second and smallest reported to date thought to cause CLS. Our study further supports the clinical utility of methods such as next-generation sequencing and high-resolution genomic arrays to detect small intragenic duplications. These methods, coupled with expression studies and cDNA structural analysis have the capacity to confirm the diagnosis of CLS in these rare cases.

Pharmacogenetic testing increasingly is available from clinical and research laboratories. However, only a limited number of quality control and other reference materials currently are available for the complex rearrangements and rare variants that occur in the CYP2D6 gene. To address this need, the Division of Laboratory Systems, CDC-based Genetic Testing Reference Material Coordination Program, in collaboration with members of the pharmacogenetic testing and research communities and the Coriell Cell Repositories (Camden, NJ), has characterized 179 DNA samples derived from Coriell cell lines. Testing included the recharacterization of 137 genomic DNAs that were genotyped in previous Genetic Testing Reference Material Coordination Program studies and 42 additional samples that had not been characterized previously. DNA samples were distributed to volunteer testing laboratories for genotyping using a variety of commercially available and laboratory-developed tests. These publicly available samples will support the quality-assurance and quality-control programs of clinical laboratories performing CYP2D6 testing.

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.