Pharmacogenetics can improve clinical outcomes by reducing adverse drug effects and enhancing therapeutic efficacy for commonly used drugs that treat a wide range of cardiovascular diseases. One of the major barriers to the clinical implementation of cardiovascular pharmacogenetics is limited education on this field for current healthcare providers and students. The abundance of pharmacogenetic literature underscores its promise, but it can also be challenging to learn such a wealth of information. Moreover, current clinical recommendations for cardiovascular pharmacogenetics can be confusing because they are outdated, incomplete, or inconsistent. A myriad of misconceptions about the promise and feasibility of cardiovascular pharmacogenetics among healthcare providers also has halted clinical implementation. Therefore, the main goal of this tutorial is to provide introductory education on the use of cardiovascular pharmacogenetics in clinical practice. The target audience is any healthcare provider (or student) with patients that use or have indications for cardiovascular drugs. This tutorial is organized into the following 6 steps: (1) understand basic concepts in pharmacogenetics; (2) gain foundational knowledge of cardiovascular pharmacogenetics; (3) learn the different organizations that release cardiovascular pharmacogenetic guidelines and recommendations; (4) know the current cardiovascular drugs/drug classes to focus on clinically and the supporting evidence; (5) discuss an example patient case of cardiovascular pharmacogenetics; and (6) develop an appreciation for emerging areas in cardiovascular pharmacogenetics. Ultimately, improved education among healthcare providers on cardiovascular pharmacogenetics will lead to a greater understanding for its potential in improving outcomes for a leading cause of morbidity and mortality.

Background Pharmacogenomics (PGx) aims to utilize a patient’s genetic data to enable safer and more effective prescribing of medications. The Clinical Pharmacogenetics Implementation Consortium (CPIC) provides guidelines with strong evidence for 24 genes that affect 72 medications. Despite strong evidence linking PGx alleles to drug response, there is a large gap in the implementation and return of actionable pharmacogenetic findings to patients in standard clinical practice. In this study, we evaluated opportunities for genetically guided medication prescribing in a diverse health system and determined the frequencies of actionable PGx alleles in an ancestrally diverse biobank population. Methods A retrospective analysis of the Penn Medicine electronic health records (EHRs), which includes ~ 3.3 million patients between 2012 and 2020, provides a snapshot of the trends in prescriptions for drugs with genotype-based prescribing guidelines (‘CPIC level A or B’) in the Penn Medicine health system. The Penn Medicine BioBank (PMBB) consists of a diverse group of 43,359 participants whose EHRs are linked to genome-wide SNP array and whole exome sequencing (WES) data. We used the Pharmacogenomics Clinical Annotation Tool (PharmCAT), to annotate PGx alleles from PMBB variant call format (VCF) files and identify samples with actionable PGx alleles. Results We identified ~ 316.000 unique patients that were prescribed at least 2 drugs with CPIC Level A or B guidelines. Genetic analysis in PMBB identified that 98.9% of participants carry one or more PGx actionable alleles where treatment modification would be recommended. After linking the genetic data with prescription data from the EHR, 14.2% of participants (n = 6157) were prescribed medications that could be impacted by their genotype (as indicated by their PharmCAT report). For example, 856 participants received clopidogrel who carried CYP2C19 reduced function alleles, placing them at increased risk for major adverse cardiovascular events. When we stratified by genetic ancestry, we found disparities in PGx allele frequencies and clinical burden. Clopidogrel users of Asian ancestry in PMBB had significantly higher rates of CYP2C19 actionable alleles than European ancestry users of clopidrogrel (p < 0.0001, OR = 3.68). Conclusions Clinically actionable PGx alleles are highly prevalent in our health system and many patients were prescribed medications that could be affected by PGx alleles. These results illustrate the potential utility of preemptive genotyping for tailoring of medications and implementation of PGx into routine clinical care.

BackgroundFluoropyrimidines (fluorouracil [5-FU], capecitabine) and irinotecan are commonly prescribed chemotherapy agents for gastrointestinal (GI) malignancies. Pharmacogenetic (PGx) testing for germline DPYD and UGT1A1 variants associated with reduced enzyme activity holds the potential to identify patients at high risk for severe chemotherapy-induced toxicity. Slow adoption of PGx testing in routine clinical care is due to implementation barriers, including long test turnaround times, lack of integration in the electronic health record (EHR), and ambiguity in test cost coverage. We sought to establish PGx testing in our health system following the Exploration, Preparation, Implementation, Sustainment (EPIS) framework as a guide. Our implementation study aims to address barriers to PGx testing.MethodsThe Implementing Pharmacogenetic Testing in Gastrointestinal Cancers (IMPACT-GI) study is a non-randomized, pragmatic, open-label implementation study at three sites within a major academic health system. Eligible patients with a GI malignancy indicated for treatment with 5-FU, capecitabine, or irinotecan will undergo PGx testing prior to chemotherapy initiation. Specimens will be sent to an academic clinical laboratory followed by return of results in the EHR with appropriate clinical decision support for the care team. We hypothesize that the availability of a rapid turnaround PGx test with specific dosing recommendations will increase PGx test utilization to guide pharmacotherapy decisions and improve patient safety outcomes. Primary implementation endpoints are feasibility, fidelity, and penetrance. Exploratory analyses for clinical effectiveness of genotyping will include assessing grade ≥3 treatment-related toxicity using available clinical data, patient-reported outcomes, and quality of life measures.ConclusionWe describe the formative work conducted to prepare our health system for DPYD and UGT1A1 testing. Our prospective implementation study will evaluate the clinical implementation of this testing program and create the infrastructure necessary to ensure sustainability of PGx testing in our health system. The results of this study may help other institutions interested in implementing PGx testing in oncology care.Clinical Trial Registrationhttps://clinicaltrials.gov/ct2/show/NCT04736472, identifier [NCT04736472].

BackgroundPharmacogenomics (PGx) aims to utilize a patient’s genetic data to enable safer and more effective prescribing of medications. The Clinical Pharmacogenetics Implementation Consortium (CPIC) provides guidelines with strong evidence for 24 genes that affect 72 medications. Despite strong evidence linking PGx alleles to drug response, there is a large gap in the implementation and return of actionable pharmacogenetic findings to patients in standard clinical practice. In this study, we evaluated opportunities for genetically guided medication prescribing in a diverse health system and determined the frequencies of actionable PGx alleles in an ancestrally diverse biobank population.MethodsA retrospective analysis of the Penn Medicine electronic health records (EHRs), which includes ∼3.3 million patients between 2012-2020, provides a snapshot of the trends in prescriptions for drugs with genotype-based prescribing guidelines (‘CPIC level A or B’) in the Penn Medicine health system. The Penn Medicine BioBank (PMBB) consists of a diverse group of 43,359 participants whose EHRs are linked to genome-wide SNP array and whole exome sequencing (WES) data. We used the Pharmacogenomics Clinical Annotation Tool (PharmCAT), to annotate PGx alleles from PMBB variant call format (VCF) files and identify samples with actionable PGx alleles.ResultsWe identified ∼316,000 unique patients that were prescribed at least 2 drugs with CPIC Level A or B guidelines. Genetic analysis in PMBB identified that 98.9% of participants carry one or more PGx actionable alleles where treatment modification would be recommended. After linking the genetic data with prescription data from the EHR, 14.2% of participants (n=6157) were prescribed medications that could be impacted by their genotype (as indicated by their PharmCAT report). For example, 856 participants received clopidogrel who carried CYP2C19 reduced function alleles, placing them at increased risk for major adverse cardiovascular events. When we stratified by genetic ancestry, we found disparities in PGx allele frequencies and clinical burden. Clopidogrel users of Asian ancestry in PMBB had significantly higher rates of CYP2C19 actionable alleles than European ancestry users of clopidrogrel (p<0.0001, OR=3.68).ConclusionsClinically actionable PGx alleles are highly prevalent in our health system and many patients were prescribed medications that could be affected by PGx alleles. These results illustrate the potential utility of preemptive genotyping for tailoring of medications and implementation of PGx into routine clinical care.

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