Clinical Pharmacogenetics Implementation Consortium (CPIC) Guideline for Pharmacogenetics-Guided Warfarin Dosing: 2017 Update

Pharmacogenomic analysis of a genetically distinct Indigenous population

Indigenous Australians face a disproportionately severe burden of chronic disease relative to other Australians, with elevated rates of morbidity and mortality. While genomics technologies are slowly gaining momentum in personalised treatments for many, a lack of pharmacogenomic research in Indigenous peoples could delay adoption. Appropriately implementing pharmacogenomics in clinical care necessitates an understanding of the frequencies of pharmacologically relevant genetic variants within Indigenous populations. We analysed whole-genome sequence data from 187 individuals from the Tiwi Islands and characterised the pharmacogenomic landscape of this population. Specifically, we compared variant profiles and allelic distributions of previously described pharmacologically significant genes and variants with other population groups. We identified 22 translationally relevant pharmacogenomic variants and 18 clinically actionable guidelines with implications for drug dosing and treatment of conditions including heart disease, diabetes and cancer. We specifically observed increased poor and intermediate metabolizer phenotypes in the CYP2C9 (PM:19%, IM:44%) and CYP2C19 (PM:18%, IM:44%) genes.

Genetic-Guided Pharmacotherapy for Atrial Fibrillation: A Systematic and Critical Review of Economic Evaluations

OBJECTIVES

This study aimed to examine the extent and quality of evidence from economic evaluations (EEs) of genetic-guided pharmacotherapy (PGx) for atrial fibrillation (AF) and to identify variables influential in changing base-case conclusions.

METHODS

From systematic searches, we included EEs of existing PGx testing to guide pharmacotherapy for AF, without restrictions on population characteristics or language. Articles excluded were genetic tests used to guide device-based therapy or focused on animals.

RESULTS

We found 18 EEs (46 comparisons), all model-based cost-utility analysis with or without cost-effectiveness analysis mostly from health system's perspectives, of PGx testing to determine coumadin/direct-acting anticoagulant (DOAC) dosing (14 of 18), to stratify patients into coumadin/DOACs (3 of 18), or to increase patients' adherence to coumadin (1 of 18) versus non-PGx. Most PGx to determine coumadin dosing found PGx more costly and more effective than standard or clinical coumadin dosing (19 of 24 comparisons) but less costly and less effective than standard DOAC dosing (14 of 14 comparisons). The remaining comparisons were too few to observe any trend. Of 61 variables influential in changing base-case conclusions, effectiveness of PGx testing was the most common (37%), accounted for in the models using time-based or medication-based approaches or relative risk. The cost of PGx testing has decreased and plateaued over time.

CONCLUSIONS

EEs to date only partially inform decisions on selecting optimal PGx testing for AF, because most evidence focuses on PGx testing to determine coumadin dosing, but less on other purposes. Future EE may refer to the list of influential variables and the approaches used to account for the effect of PGx testing to inform data collection and study design.

Development of an interview-based warfarin nomogram predicting the time spent in the therapeutic INR range: a cost-effective, and non-invasive strategy building from a cross sectional study in a low resource setting

A cross-sectional study was conducted to predict time in therapeutic range (TTR) using clinical history, examination, and socioeconomic data. Study included warfarin-receiving patients from outpatient-clinic. In 203 patients studied, mean warfarin start-dose was 2.55 mg/day and maintenance-dose/week was 30.79 mg. Body mass index (BMI) (p = 0.03), warfarin maintenance dose/day (p = 0.02), and comorbidity presence (p = 0.04) were significantly associated with TTR. Occupation (p = 0.53), income (p = 0.83), education (p = 0.55), and socioeconomic score (p = 0.73) showed non-significant association with TTR. A TTR predicting nomogram was built from clinical history and examination findings.

Identification of pharmacogenetic variants from large scale next generation sequencing data in the Saudi population

It is well documented that drug responses are related to Absorption, Distribution, Metabolism, and Excretion (ADME) characteristics of individual patients. Several studies have identified genetic variability in pharmacogenes, that are either directly responsible for or are associated with ADME, giving rise to individualized treatments. Our objective was to provide a comprehensive overview of pharmacogenetic variation in the Saudi population. We mined next generation sequencing (NGS) data from 11,889 unrelated Saudi nationals, to determine the presence and frequencies of known functional SNP variants in 8 clinically relevant pharmacogenes (CYP2C9, CYP2C19, CYP3A5, CYP4F2, VKORC1, DPYD, TPMT and NUDT15), recommended by the Clinical Pharmacogenetics Implementation Consortium (CPIC), and collectively identified 82 such star alleles. Functionally significant pharmacogenetic variants were prevalent especially in CYP genes (excluding CYP3A5), with 10-44.4% of variants predicted to be inactive or to have decreased activity. In CYP3A5, inactive alleles (87.5%) were the most common. Only 1.8%, 0.7% and 0.7% of NUDT15, TPMT and DPYD variants respectively, were predicted to affect gene activity. In contrast, VKORC1 was found functionally, to be highly polymorphic with 53.7% of Saudi individuals harboring variants predicted to result in decreased activity and 31.3% having variants leading to increased metabolic activity. Furthermore, among the 8 pharmacogenes studied, we detected six rare variants with an aggregated frequency of 1.1%, that among several other ethnicities, were uniquely found in Saudi population. Similarly, within our cohort, the 8 pharmacogenes yielded forty-six novel variants predicted to be deleterious. Based upon our findings, 99.2% of individuals from the Saudi population carry at least one actionable pharmacogenetic variant.

Pharmacogenetics and Precision Medicine Approaches for the Improvement of COVID-19 Therapies

Many drugs are being administered to tackle coronavirus disease 2019 (COVID-19) pandemic situations without establishing clinical effectiveness or tailoring safety. A repurposing strategy might be more effective and successful if pharmacogenetic interventions are being considered in future clinical studies/trials. Although it is very unlikely that there are almost no pharmacogenetic data for COVID-19 drugs, however, from inferring the pharmacokinetic (PK)/pharmacodynamic(PD) properties and some pharmacogenetic evidence in other diseases/clinical conditions, it is highly likely that pharmacogenetic associations are also feasible in at least some COVID-19 drugs. We strongly mandate to undertake a pharmacogenetic assessment for at least these drug-gene pairs (atazanavir-UGT1A1, ABCB1, SLCO1B1, APOA5; efavirenz-CYP2B6; nevirapine-HLA, CYP2B6, ABCB1; lopinavir-SLCO1B3, ABCC2; ribavirin-SLC28A2; tocilizumab-FCGR3A; ivermectin-ABCB1; oseltamivir-CES1, ABCB1; clopidogrel-CYP2C19, ABCB1, warfarin-CYP2C9, VKORC1; non-steroidal anti-inflammatory drugs (NSAIDs)-CYP2C9) in COVID-19 patients for advancing precision medicine. Molecular docking and computational studies are promising to achieve new therapeutics against SARS-CoV-2 infection. The current situation in the discovery of anti-SARS-CoV-2 agents at four important targets from in silico studies has been described and summarized in this review. Although natural occurring compounds from different herbs against SARS-CoV-2 infection are favorable, however, accurate experimental investigation of these compounds is warranted to provide insightful information. Moreover, clinical considerations of drug-drug interactions (DDIs) and drug-herb interactions (DHIs) of the existing repurposed drugs along with pharmacogenetic (e.g., efavirenz and CYP2B6) and herbogenetic (e.g., andrographolide and CYP2C9) interventions, collectively called multifactorial drug-gene interactions (DGIs), may further accelerate the development of precision COVID-19 therapies in the real-world clinical settings.

Clinical pharmacogenetic analysis in 5,001 individuals with diagnostic Exome Sequencing data

Exome sequencing is utilized in routine clinical genetic diagnosis. The technical robustness of repurposing large-scale next-generation sequencing data for pharmacogenetics has been demonstrated, supporting the implementation of preemptive pharmacogenetic strategies based on adding clinical pharmacogenetic interpretation to exomes. However, a comprehensive study analyzing all actionable pharmacogenetic alleles contained in international guidelines and applied to diagnostic exome data has not been performed. Here, we carried out a systematic analysis based on 5001 Spanish or Latin American individuals with diagnostic exome data, either Whole Exome Sequencing (80%), or the so-called Clinical Exome Sequencing (20%) (60 Mb and 17 Mb, respectively), to provide with global and gene-specific clinical pharmacogenetic utility data. 788 pharmacogenetic alleles, distributed through 19 genes included in Clinical Pharmacogenetics Implementation Consortium guidelines were analyzed. We established that Whole Exome and Clinical Exome Sequencing performed similarly, and 280 alleles in 11 genes (CACNA1S, CYP2B6, CYP2C9, CYP4F2, DPYD, G6PD, NUDT15, RYR1, SLCO1B1, TPMT, and UGT1A1) could be used to inform of pharmacogenetic phenotypes that change drug prescription. Each individual carried in average 2.2 alleles and overall 95% (n = 4646) of the cohort could be informed of at least one actionable pharmacogenetic phenotype. Differences in variant allele frequency were observed among the populations studied and the corresponding gnomAD population for 7.9% of the variants. In addition, in the 11 selected genes we uncovered 197 novel variants, among which 27 were loss-of-function. In conclusion, we provide with the landscape of actionable pharmacogenetic information contained in diagnostic exomes, that can be used preemptively in the clinics.

A population study of clinically actionable genetic variation affecting drug response from the Middle East

Clinical implementation of pharmacogenomics will help in personalizing drug prescriptions and alleviate the personal and financial burden due to inefficacy and adverse reactions to drugs. However, such implementation is lagging in many parts of the world, including the Middle East, mainly due to the lack of data on the distribution of actionable pharmacogenomic variation in these ethnicities. We analyzed 6,045 whole genomes from the Qatari population for the distribution of allele frequencies of 2,629 variants in 1,026 genes known to affect 559 drugs or classes of drugs. We also performed a focused analysis of genotypes or diplotypes of 15 genes affecting 46 drugs, which have guidelines for clinical implementation and predicted their phenotypic impact. The allele frequencies of 1,320 variants in 703 genes affecting 299 drugs or class of drugs were significantly different between the Qatari population and other world populations. On average, Qataris carry 3.6 actionable genotypes/diplotypes, affecting 13 drugs with guidelines for clinical implementation, and 99.5% of the individuals had at least one clinically actionable genotype/diplotype. Increased risk of simvastatin-induced myopathy could be predicted in ~32% of Qataris from the diplotypes of SLCO1B1, which is higher compared to many other populations, while fewer Qataris may need tacrolimus dosage adjustments for achieving immunosuppression based on the CYP3A5 diplotypes compared to other world populations. Distinct distribution of actionable pharmacogenomic variation was also observed among the Qatari subpopulations. Our comprehensive study of the distribution of actionable genetic variation affecting drugs in a Middle Eastern population has potential implications for preemptive pharmacogenomic implementation in the region and beyond.

Clinical Opportunities for Germline Pharmacogenetics and Management of Drug-Drug Interactions in Patients With Advanced Solid Cancers

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.

Nine-gene pharmacogenomics profile service: The Mayo Clinic experience

PURPOSE

The Pharmacogenomics (PGx) Profile Service was a proof-of-concept project to implement PGx in patient care at Mayo Clinic.

METHODS

Eighty-two healthy individuals aged 18 and older underwent genotyping of CYP1A2, CYP2C9, CYP2C19, CYP2D6, CYP3A4, CYP3A5, SLCO1B1, HLA-B*58:01, and VKORC1. A PGx pharmacist was involved in ordering, meeting with patients, interpreting, reviewing, and documenting results.

RESULTS

Ninety three percent were CYP1A2 rapid metabolizers, 92% CYP3A4 normal metabolizers, and 88% CYP3A5 poor metabolizers; phenotype frequencies for CYP2C19 and CYP2D6 varied. Seventy-three percent had normal functioning SLCO1B1 transporter, 4% carried the HLA-B*58:01 risk variant, and 35% carried VKORC1 and CYP2C9 variants that increased warfarin sensitivity.

CONCLUSION

Pre-emptive PGx testing offered medication improvement opportunity in 56% of participants for commonly used medications. A collaborative approach involving a PGx pharmacist integrated within a clinical practice with regards to utility of PGx results allowed for implementation of the PGx Profile Service.

KEY POINTS

The Mayo Clinic PGx (PGx) Profile Service was a proof-of-concept project to utilize PGx testing as another clinical tool to enhance medication selection and decrease serious adverse reactions or medication failures. Over one-half of participants in the pilot using the PGx Profile Service were predicted to benefit from pre-emptive PGx testing to guide pharmacotherapy. PGx pharmacists played a crucial role in the PGx Profile Service by educating participants, identifying medication-gene interactions, and providing evidence-based (CPIC and DPWG) PGx recommendations for past, current, and future medication us.

Assessment of a Manual Method versus an Automated, Probability-Based Algorithm to Identify Patients at High Risk for Pharmacogenomic Adverse Drug Outcomes in a University-Based Health Insurance Program

We compared patient cohorts selected for pharmacogenomic testing using a manual method or automated algorithm in a university-based health insurance network. The medication list was compiled from claims data during 4th quarter 2018. The manual method selected patients by number of medications by the health system’s list of medications for pharmacogenomic testing. The automated method used YouScript’s pharmacogenetic interaction probability (PIP) algorithm to select patients based on the probability that testing would result in detection of one or more clinically significant pharmacogenetic interactions. A total of 6916 patients were included. Patient cohorts selected by each method differed substantially, including size (manual n = 218, automated n = 286) and overlap (n = 41). The automated method was over twice as likely to identify patients where testing may reveal a clinically significant pharmacogenetic interaction than the manual method (62% vs. 29%, p < 0.0001). The manual method captured more patients with significant drug–drug or multi-drug interactions (80.3% vs. 40.2%, respectively, p < 0.0001), higher average number of significant drug interactions per patient (3.3 vs. 1.1, p < 0.0001), and higher average number of unique medications per patient (9.8 vs. 7.4, p < 0.0001). It is possible to identify a cohort of patients who would likely benefit from pharmacogenomic testing using manual or automated methods.

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

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

The VKORC1 and CYP2C9 gene variants as pharmacogenetic factors in acenocoumarol therapy in Serbian patients - consideration of hypersensitivity and resistance

Introduction/Objective. Coumarin therapy represents one of the best models for applying pharmacogenetics. The contribution of factors influencing coumarin therapy can vary significantly between ethnic groups, which justifies conducting population-specific studies. The aim of this study was to analyze the influence of the most important genetic factors (VKORC1 and CYP2C9 genes) that affect coumarin therapy in patients from Serbia. Methods. A retrospective study involving 207 patients on acenocoumarol therapy was conducted. Genetic analyses were performed by direct sequencing. Influence on acenocoumarol dose of variants (VKORC1, CYP2C9*2, CYP2C9*3) causing hypersensitivity and VKORC1 variants causing resistance to acenocoumarol were analyzed. Multiple regression analysis was used to design a mathematical model for predicting individual drug dosage based on clinical-demographic and genetic data. Results. The study confirmed significant influence of the analyzed genetic factors on acenocoumarol maintenance dose. We designed mathematical model for predicting individual acenocoumarol dose and its unadjusted R2 was 61.8. In the testing cohort, our model gave R2 value of 42.6 and showed better prediction in comparison with model given by other authors. In the analyzed patients, nine different variants in the VKORC1 coding region were found. Among carriers of these variants 78% were completely resistant, and it was not possible to achieve therapeutic effect even with high doses of acenocoumarol. Conclusions. Population-specific model for prediction individual dose of acenocoumarol, may show advantages over protocols that are used in a generalized manner. Also, VKORC1 variants which cause coumarin resistance should be considered when planning therapy.

Pharmacogenomics Informs Cardiovascular Pharmacotherapy

Precision medicine exemplifies the emergence of personalized treatment options which may benefit specific patient populations based upon their genetic makeup. Application of pharmacogenomics requires an understanding of how genetic variations impact pharmacokinetic and pharmacodynamic properties. This particular approach in pharmacotherapy is helpful because it can assist in and improve clinical decisions. Application of pharmacogenomics to cardiovascular pharmacotherapy provides for the ability of the medical provider to gain critical knowledge on a patient's response to various treatment options and risk of side effects.

Direct Oral Anticoagulants (DOAC): Are We Ready for a Pharmacogenetic Approach?

Anticoagulants play an important role in reducing complications and mortality associated with thromboembolic disorders, and anticoagulant therapy has been progressively enriched over the last few years with numerous new options [...].

The Landscape of Clinical Implementation of Pharmacogenetic Testing in Central China: A Single-Center Study

Purpose

Pharmacogenetic testing is recognized as the major method for the individualized pharmacotherapy in clinical pharmacy practice, but information about the clinical implementation of pharmacogenetic testing in China is limited. The present study aimed to determine the situation of clinical implementation for pharmacogenetic testing in central China.

Methods

The study is conducted in the department of clinical pharmacy in The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China. We collected and analyzed pharmacogenetic testing results from November 1, 2013 to November 2, 2018 in our hospital, which were checked in the electronic medical record system. The main outcome measures were the number and type of pharmacogenetic testing across five years.

Results

A total of 47,265 (56.9% male, mean age = 51.5 years) pharmacogenetic testing results were obtained with an average annual rate of growth of 63.0% across five years. A 50.2% (23,748/47,265) of all the pharmacogenetic testing results were for the determination of cytochrome P450 2C19 (CYP2C19) *2, *3 genotypes, and 41.7% were for the methylene tetrahydrofolate reductase (MTHFR) C677T genotype. The number of departments performing the pharmacogenetic testing was 35, 63, 55, 52, 52 and 39 for 2013–2018, respectively, and the main top five departments were cardiology, psychiatry, ICU, cardiac surgery and intervention.

Conclusion

Clinical implementation of pharmacogenetic testing in China is growing rapidly, but the types and implementing departments of pharmacogenetic testing were limited. Our present study reported the real-world implementation modality of pharmacogenomic tests in China. It will help us to understand the testing of pharmacogenetics in China in order to promote the rational development of pharmacogenetics.

Personalized medicine in cardiovascular disease: review of literature

Purpose

Personalized medicine (PM) is the concept of managing patients based on their characteristics, including genotypes. In the field of cardiology, advantages of PM could be found in the diagnosis and treatment of several conditions such as arrhythmias and cardiomyopathies; moreover, it may be beneficial to prevent adverse drug reactions (ADR) and select the best medication. Genetic background can help us in selecting effective treatments, appropriate dose requirements, and preventive strategies in individuals with particular genotypes.

Method

In this review, we provide examples of personalized medicine based on human genetics for the most used pharmaceutics in cardiology, including warfarin, clopidogrel, and statins. We also review cardiovascular diseases, including coronary artery disease, arrhythmia, and cardiomyopathies.

Conclusion

Genetic factors are as important as environmental factors and they should be tested and evaluated more in the future by improving in genetic testing tools.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40200-021-00840-0.

Incremental Value of Genotype Bins over the HAS-BLED Score for the Prediction of Bleeding Risk in Warfarin-Treated Patients with Atrial Fibrillation

Background

This study aimed to analyse the role of the HAS-BLED score with the addition of genotype bins for bleeding risk prediction in warfarin-treated patients with atrial fibrillation (AF).

Methods and Results

Consecutive patients with AF on initial warfarin treatment were recruited. For each patient, CYP2C9 ^∗ 3 and VKORC1-1639 A/G genotyping was performed to create 3 genotype functional bins. The predictive values of the HAS-BLED score with or without the addition of genotype bins were compared. According to the carrier status of the genotype bins, the numbers of normal, sensitive, and highly sensitive responders among 526 patients were 64 (12.17%), 422 (80.23%), and 40 (7.60%), respectively. A highly sensitive response was independently associated with clinically relevant bleeding (HR: 3.85, 95% CI: 1.88-7.91, P=0.001) and major bleeding (HR:3.75, 95% CI: 1.17-11.97, P=0.03). With the addition of genotype bins, the performance of the HAS-BLED score for bleeding risk prediction was significantly improved (c-statistic from 0.60 to 0.64 for clinically relevant bleeding and from 0.64 to 0.70 for major bleeding, P < 0.01). Using the integrated discriminatory, net reclassification improvement, and decision curve analysis, the HAS-BLED score plus genotype bins could perform better in predicting any clinically relevant bleeding than the HAS-BLED score alone.

Conclusions

Genotypes have an incremental predictive value when combined with the HAS-BLED score for the prediction of clinically relevant bleeding in warfarin-treated patients with AF.

Race and Drug Toxicity: A Study of Three Cardiovascular Drugs with Strong Pharmacogenetic Recommendations

The Clinical Pharmacogenetics Implementation Consortium (CPIC^®) establishes evidence-based guidelines for utilizing pharmacogenetic information for certain priority drugs. Warfarin, clopidogrel and simvastatin are cardiovascular drugs that carry strong prescribing guidance by CPIC. The respective pharmacogenes for each of these drugs exhibit considerable variability amongst different ethnic/ancestral/racial populations. Race and ethnicity are commonly employed as surrogate biomarkers in clinical practice and can be found in many prescribing guidelines. This is controversial due to the large variability that exists amongst different racial/ethnic groups, lack of detailed ethnic information and the broad geographic categorization of racial groups. Using a retrospective analysis of electronic health records (EHR), we sought to determine the degree to which self-reported race/ethnicity contributed to the probability of adverse drug reactions for these drugs. All models used individuals self-reporting as White as the comparison group. The majority of apparent associations between different racial groups and drug toxicity observed in the "race only" model failed to remain significant when we corrected for covariates. We did observe self-identified Asian race as a significant predictor (p = 0.016) for warfarin hemorrhagic events in all models. In addition, patients identifying as either Black/African-American (p = 0.001) or Other/Multiple race (p = 0.019) had a lower probability of reporting an adverse reaction than White individuals while on simvastatin even after correcting for other covariates. In both instances where race/ethnicity was predictive of drug toxicity (i.e., warfarin, simvastatin), the findings are consistent with the known global variability in the pharmacogenes described in the CPIC guidelines for these medications. These results confirm that the reliability of using self-identified race/ethnic information extracted from EHRs as a predictor of adverse drug reactions is likely limited to situations where the genes influencing drug toxicity display large, distinct ethnogeographic variability.

Machine Learning for Prediction of Stable Warfarin Dose in US Latinos and Latin Americans

Populations used to create warfarin dose prediction algorithms largely lacked participants reporting Hispanic or Latino ethnicity. While previous research suggests nonlinear modeling improves warfarin dose prediction, this research has mainly focused on populations with primarily European ancestry. We compare the accuracy of stable warfarin dose prediction using linear and nonlinear machine learning models in a large cohort enriched for US Latinos and Latin Americans (ULLA). Each model was tested using the same variables as published by the International Warfarin Pharmacogenetics Consortium (IWPC) and using an expanded set of variables including ethnicity and warfarin indication. We utilized a multiple linear regression model and three nonlinear regression models: Bayesian Additive Regression Trees, Multivariate Adaptive Regression Splines, and Support Vector Regression. We compared each model’s ability to predict stable warfarin dose within 20% of actual stable dose, confirming trained models in a 30% testing dataset with 100 rounds of resampling. In all patients (n = 7,030), inclusion of additional predictor variables led to a small but significant improvement in prediction of dose relative to the IWPC algorithm (47.8 versus 46.7% in IWPC, p = 1.43 × 10⁻¹⁵). Nonlinear models using IWPC variables did not significantly improve prediction of dose over the linear IWPC algorithm. In ULLA patients alone (n = 1,734), IWPC performed similarly to all other linear and nonlinear pharmacogenetic algorithms. Our results reinforce the validity of IWPC in a large, ethnically diverse population and suggest that additional variables that capture warfarin dose variability may improve warfarin dose prediction algorithms.

Pharmacogenetics to Avoid Adverse Reactions in Cardiology: Ready for Implementation?

Cardiovascular Diseases (CVs) are one of the main causes of mortality and disability around the world. Advances in drug treatment have greatly improved survival and quality of life in the past decades, but associated adverse events remain a relevant problem. Pharmacogenetics can help individualize cardiovascular treatment, reducing associated toxicities and improving outcomes. Several scientific societies and working groups periodically review available studies and provide consensus recommendations for those gene-drug pairs with a sufficient level of evidence. However, these recommendations are rarely mandatory, and the indications on how to adjust treatment can vary between different guidelines, which limits their clinical applicability. The aim of this review is to compile, compare and discuss available guidelines and recommendations by the main Pharmacogenetics Consortiums (Clinical Pharmacogenetics Implementation Consortium (CPIC); Dutch Pharmacogenetics Working Group (DPWG); the French Network of Pharmacogenetics (Réseau national de pharmacogénétique (RNPGx) and The Canadian Pharmacogenomics Network for Drug Safety (CPNDS) regarding how to apply pharmacogenetic results to optimize pharmacotherapy in cardiology. Pharmacogenetic recommendations included in European or American drug labels, as well as those included in the European Society of Cardiology (ESC) and the American College of Cardiology (ACC) and the American Heart Association (AHA) treatment guidelines are also discussed.

Association between time to therapeutic INR and length of stay following mechanical heart valve surgery

BACKGROUND

Warfarin is the only oral anticoagulant approved for use following mechanical valve surgery (MeVS). Patients may experience prolonged hospital length of stay (LOS) following MeVS awaiting an appropriate warfarin effect. We aimed to determine whether an association exists between time to achieve the first therapeutic international normalized ratio (INR) and LOS following MeVS.

MATERIALS AND METHODS

Retrospective single center cohort study. We included consecutive adult patients undergoing elective MeVS from 2013 to 2018. Landmark analyses and multivariable regression with time-updated INR were used to estimate the association between time to therapeutic INR (TTI) and LOS.

RESULTS

Among 384 patients (median age: 51 years, interquartile range [IQR]: 41-57; 58.3% male), the median TTI was 4 days (IQR: 2-5). Thirty seven percent of patients were discharged with a subtherapeutic INR, many on bridging anticoagulation or with an INR close to target. Those achieving therapeutic INR had an increased rate of hospital discharge (adjusted hazard ratio: 2.17; 95% confidence interval: 1.71-2.76; p < .0001). Attainment of a therapeutic INR anytime between postoperative Days 4 and 13 was significantly associated with a shorter LOS.

CONCLUSIONS

Prolonged time to achieve a therapeutic INR was independently associated with prolonged LOS. Future strategies aimed at improving attainment of therapeutic INR following MeVS may reduce hospital LOS.

Individualized versus Standardized Risk Assessment in Patients at High Risk for Adverse Drug Reactions (The IDrug Randomized Controlled Trial)-Never Change a Running System?

The aim of this study was to compare effects of an individualized with a standardized risk assessment for adverse drug reactions to improve drug treatment with antithrombotic drugs in older adults. A randomized controlled trial was conducted in general practitioner (GP) offices. Patients aged 60 years and older, multi-morbid, taking antithrombotic drugs and at least one additional drug continuously were randomized to individualized and standardized risk assessment groups. Patients were followed up for nine months. A composite endpoint defined as at least one bleeding, thromboembolic event or death reported via a trigger list was used. Odds ratios (OR) and 95% confidence intervals (CI) were calculated. In total, N = 340 patients were enrolled from 43 GP offices. Patients in the individualized risk assessment group met the composite endpoint more often than in the standardized group (OR 1.63 [95%CI 1.02-2.63]) with multiple adjustments. The OR was higher in patients on phenprocoumon treatment (OR 1.99 [95%CI 1.05-3.76]), and not significant on DOAC treatment (OR 1.52 [95%CI 0.63-3.69]). Pharmacogenenetic variants of CYP2C9, 2C19 and VKORC1 were not observed to be associated with the composite endpoint. The results of this study may indicate that the time point for implementing individualized risk assessments is of importance.

Comprehensive analysis of important pharmacogenes in Koreans using the DMET™ platform

Genetic polymorphisms of enzymes and transporters associated with the absorption, distribution, metabolism, and elimination (ADME) of drugs are one of the major factors that contribute to interindividual variations in drug response. In the present study, we aimed to elucidate the pharmacogenetic profiles of the Korean population using the Affymetrix Drug Metabolizing Enzyme and Transporters (DMET™) platform. A total of 1,012 whole blood samples collected from Korean subjects were genotyped using the DMET™ plus microarray. In total, 1,785 single nucleotide polymorphism (SNP) markers for 231 ADME genes were identified. The genotype and phenotype of 13 clinically important ADME genes implemented in the Clinical Pharmacogenetics Implementation Consortium guidelines were compared among different ethnic groups. Overall, the genotype frequencies of the Korean population were similar to those of the East Asian population. Several genes, notably CYP2C19 and VKORC1, showed marked differences in Koreans compared to Europeans (EURs) or Africans (AFRs). The percentage of CYP2C19 poor metabolizers was 15% in Koreans and less than 3% in EURs or AFRs. The frequencies of causative SNPs of the VKORC1 gene for the low warfarin dose phenotype were 90%, 60%, and 10% in Koreans, EURs and AFRs, respectively. Our findings can be utilized for optimal pharmacotherapy in Korean patients.

Lack of Major Involvement of Common CYP2C Gene Polymorphisms in the Risk of Developing Cross-Hypersensitivity to NSAIDs

Cross-hypersensitivity to non-steroidal anti-inflammatory drugs (NSAIDs) is a relatively common, non-allergic, adverse drug event triggered by two or more chemically unrelated NSAIDs. Current evidence point to COX-1 inhibition as one of the main factors in its etiopathogenesis. Evidence also suggests that the risk is dose-dependent. Therefore it could be speculated that individuals with impaired NSAID biodisposition might be at increased risk of developing cross-hypersensitivity to NSAIDs. We analyzed common functional gene variants for CYP2C8, CYP2C9, and CYP2C19 in a large cohort composed of 499 patients with cross-hypersensitivity to NSAIDs and 624 healthy individuals who tolerated NSAIDs. Patients were analyzed as a whole group and subdivided in three groups according to the main enzymes involved in the metabolism of the culprit drugs as follows: CYP2C9, aceclofenac, indomethacin, naproxen, piroxicam, meloxicam, lornoxicam, and celecoxib; CYP2C8 plus CYP2C9, ibuprofen and diclofenac; CYP2C19 plus CYP2C9, metamizole. Genotype calls ranged from 94 to 99%. No statistically significant differences between patients and controls were identified in this study, either for allele frequencies, diplotypes, or inferred phenotypes. After patient stratification according to the enzymes involved in the metabolism of the culprit drugs, or according to the clinical presentation of the hypersensitivity reaction, we identified weak significant associations of a lower frequency (as compared to that of control subjects) of CYP2C8*3/*3 genotypes in patients receiving NSAIDs that are predominantly CYP2C9 substrates, and in patients with NSAIDs-exacerbated cutaneous disease. However, these associations lost significance after False Discovery Rate correction for multiple comparisons. Taking together these findings and the statistical power of this cohort, we conclude that there is no evidence of a major implication of the major functional CYP2C polymorphisms analyzed in this study and the risk of developing cross-hypersensitivity to NSAIDs. This argues against the hypothesis of a dose-dependent COX-1 inhibition as the main underlying mechanism for this adverse drug event and suggests that pre-emptive genotyping aiming at drug selection should have a low practical utility for cross-hypersensitivity to NSAIDs.

Retrospective pharmacogenetic analysis of a pediatric patient under anticoagulant treatment: Clinical case

We present the clinical case of a 10-year-old patient diagnosed with dilated cardiomyopathy who registered INR values above 10 upon receiving standard doses of acenocoumarol, as well as other values reported as uncoagulable, forcing the discontinuation and restart of treatment more than once. Expected and stable INR levels were achieved after more than 30 days of treatment, surprisingly with half the recommended dose for a patient of her age and weight. We decided to conduct a retrospective pharmacogenomic analysis including nucleotide genetic polymorphisms (SNPs) with different degrees of association with the dose/response to antivitamin K (AVK) drugs: rs2108622 (gene CYP4F2), rs9923231, rs7294 (gene VKORC1), rs1799853, and rs1057910 (CYP2C9 gene) using TaqMan® RT-PCR. The patient was homozygous for rs9923231 (VKORC1) and heterozygous for rs2108622 (CYP4F2),a genetic profile strongly associated with a requirement of lower AVK doses as shown by national and international evidence. In conclusion, the pharmacogenetic analysis confirmed that this patient’s genetic conditions, involving low expression of the VKA therapeutic target, required a lower dose than that established in clinical protocols as recommended by the Food and Drug Administration (FDA) and the PharmGKB® for coumarin drugs. A previous genotypic analysis of the patient would have allowed reaching the therapeutic range sooner, thus avoiding potential bleeding risks. This shows the importance of pharmacogenetic analyses for highly variable treatments with a narrow therapeutic range.

The Gene-Drug Duality: Exploring the Pharmacogenomics of Indigenous Populations

While pharmacogenomic studies have facilitated the rapid expansion of personalized medicine, the benefits of these findings have not been evenly distributed. Genomic datasets pertaining to Indigenous populations are sorely lacking, leaving members of these communities at a higher risk of adverse drug reactions (ADRs), and associated negative outcomes. Australia has one of the largest Indigenous populations in the world. Pharmacogenomic studies of these diverse Indigenous Australian populations have been hampered by a paucity of data. In this article, we discuss the history of pharmacogenomics and highlight the inequalities that must be addressed to ensure equal access to pharmacogenomic-based healthcare. We also review efforts to conduct the pharmacogenomic profiling of chronic diseases among Australian Indigenous populations and survey the impact of the lack of drug safety-related information on potential ADRs among individuals in these communities.

Required warfarin dose and time in therapeutic range in patients with diagnosed Nonalcoholic Fatty Liver Disease (NAFLD) or Nonalcoholic Steatohepatitis (NASH)

Warfarin has been widely used to treat thromboembolism. The effect of nonalcoholic fatty liver disease (NAFLD) or nonalcoholic steatohepatitis (NASH), on warfarin dosing remains unknown. This study aims to examine the effects of NAFLD/NASH on the average daily dose (ADD) of warfarin and the time in therapeutic range (TTR). This is a retrospective study utilizing an administrative data. We included patients with at least 2 months of warfarin dispensing and two subsequent consecutive INR measures. The ADD of warfarin to achieve therapeutic range INR levels, and TTR were compared between patients with and without NAFLD/NASH in four subgroups of patients accounting for the presence of obesity and diabetes. Generalized linear models (GLM) with Propensity score (PS) fine stratification were applied to evaluate the relative differences (RD) of warfarin ADD and TTR (>60%) in four subgroups. A total of 430 NAFLD/NASH patients and 38,887 patients without NAFLD/NASH were included. The ADD and TTR, were not significant in the overall cohort between those with and without NAFLD/NASH. However, GLM results in patients without diabetes or obesity (N = 26,685) showed a significantly lower warfarin ADD (RD: -0.38; 95%CI: -0.74–-0.02) and shorter TTR (OR: 0.71; 95%CI: 0.52–0.97) in patients diagnosed with NAFLD/NASH. The effects of NAFLD/NASH on warfarin dose or TTR were observed in patients without obesity and diabetes. Obesity and diabetes appear to be significant modifiers for the effects of NAFLD/NASH on warfarin dose and TTR.

Measuring Pharmacogene Variant Function at Scale Using Multiplexed Assays

As costs of next-generation sequencing decrease, identification of genetic variants has far outpaced our ability to understand their functional consequences. This lack of understanding is a central challenge to a key promise of pharmacogenomics: using genetic information to guide drug selection and dosing. Recently developed multiplexed assays of variant effect enable experimental measurement of the function of thousands of variants simultaneously. Here, we describe multiplexed assays that have been performed on nearly 25,000 variants in eight key pharmacogenes (ADRB2, CYP2C9, CYP2C19, NUDT15, SLCO1B1, TMPT, VKORC1, and the LDLR promoter), discuss advances in experimental design, and explore key challenges that must be overcome to maximize the utility of multiplexed functional data. Expected final online publication date for the Annual Review of Pharmacology and Toxicology, Volume 62 is January 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Pharmacogenetics to guide cardiovascular drug therapy

Over the past decade, pharmacogenetic testing has emerged in clinical practice to guide selected cardiovascular therapies. The most common implementation in practice is CYP2C19 genotyping to predict clopidogrel response and assist in selecting antiplatelet therapy after percutaneous coronary intervention. Additional examples include genotyping to guide warfarin dosing and statin prescribing. Increasing evidence exists on outcomes with genotype-guided cardiovascular therapies from multiple randomized controlled trials and observational studies. Pharmacogenetic evidence is accumulating for additional cardiovascular medications. However, data for many of these medications are not yet sufficient to support the use of genotyping for drug prescribing. Ultimately, pharmacogenetics might provide a means to individualize drug regimens for complex diseases such as heart failure, in which the treatment armamentarium includes a growing list of medications shown to reduce morbidity and mortality. However, sophisticated analytical approaches are likely to be necessary to dissect the genetic underpinnings of responses to drug combinations. In this Review, we examine the evidence supporting pharmacogenetic testing in cardiovascular medicine, including that available from several clinical trials. In addition, we describe guidelines that support the use of cardiovascular pharmacogenetics, provide examples of clinical implementation of genotype-guided cardiovascular therapies and discuss opportunities for future growth of the field.

PharmVar GeneFocus: CYP2C9

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.

To establish a model for the prediction of initial standard and maintenance doses of warfarin for the Han Chinese population based on gene polymorphism: a multicenter study

PURPOSE

The purpose of this paper is to study the correlation between demographic and clinical factors and warfarin dose of patients in Chinese Han population taking warfarin and study gene polymorphisms impact of related gene loci (CYP2C9*3, VKORC1-1639G > A) on warfarin doses, to establish a model to predict initial standard dose and maintenance dose based on CYP2C9*3, VKORC1-1639G > A genotype.

METHODS

The study collects the data of patients in our hospital and other subcenters which incorporates 2160 patients to establish the initial dose model and 1698 patients for the stable dose model, and sequences 26 multigene sites in 451 patients. Based on the patient's dosage, clinical data, and demographic characteristics, the genetic and non-genetic effects on the initial dose and stable dose of warfarin are calculated by using statistical methods, and the prediction model of initial standard dose and maintenance dose can be established via multiple linear regression.

RESULTS

The initial dose of warfarin (mg/day) was calculated as (1.346 + 0.350 × (VKORC1-1639G > A) - 0.273 × (CYP2C9*3) + 0.245 × (body surface area) - 0.003 × (age) - 0.036 × (amine-iodine) + 0.021 × (sex))². This model incorporated seven factors and explained 55.3% of the individualization differences of the warfarin drug dose. The maintenance dose of warfarin (mg/day) was calculated as (1.336 + 0.299 × (VKORC1-1639G > A) + 0.480 × (body surface area) - 0.214 × (CYP2C9*3) - 0.074 × (amine-iodine) - 0.003 × (age) - 0.077 × (statins) - 0.002 × (height))². This model incorporated six factors and explained 42.4% of the individualization differences in the warfarin drug dose.

CONCLUSION

The genetic and non-genetic factors affecting warfarin dose in Chinese Han population were studied systematically in this study. The pharmacogenomic dose prediction model constructed in this study can predict anticoagulant efficacy of warfarin and has potential application value in clinical practice.

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

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

Impact of genetic and non-genetic factors on hepatic CYP2C9 expression and activity in Hungarian subjects

CYP2C9, one of the most abundant hepatic cytochrome P450 enzymes, is involved in metabolism of 15–20% of clinically important drugs (warfarin, sulfonylureas, phenytoin, non-steroid anti-inflammatory drugs). To avoid adverse events and/or impaired drug-response, CYP2C9 pharmacogenetic testing is recommended. The impact of CYP2C9 polymorphic alleles (CYP2C9*2, CYP2C9*3) and phenoconverting non-genetic factors on CYP2C9 function and expression was investigated in liver tissues from Caucasian subjects (N = 164). The presence of CYP2C9*3 allele was associated with CYP2C9 functional impairment, and CYP2C9*2 influenced tolbutamide 4′-hydroxylase activity only in subjects with two polymorphic alleles, whereas the contribution of CYP2C8*3 was not confirmed. In addition to CYP2C9 genetic polymorphisms, non-genetic factors (co-medication with CYP2C9-specific inhibitors/inducers and non-specific factors including amoxicillin + clavulanic acid therapy or chronic alcohol consumption) contributed to the prediction of hepatic CYP2C9 activity; however, a CYP2C9 genotype–phenotype mismatch still existed in 32.6% of the subjects. Substantial variability in CYP2C9 mRNA levels, irrespective of CYP2C9 genotype, was demonstrated; however, CYP2C9 induction and non-specific non-genetic factors potentially resulting in liver injury appeared to modify CYP2C9 expression. In conclusion, complex implementation of CYP2C9 genotype and non-genetic factors for the most accurate estimation of hepatic CYP2C9 activity may improve efficiency and safety of medication with CYP2C9 substrate drugs in clinical practice.

Precision Medicine and Adverse Drug Reactions Related to Cardiovascular Drugs

Cardiovascular disease remains the leading global cause of death. Early intervention, with lifestyle advice alongside appropriate medical therapies, is fundamental to reduce patient mortality among high-risk individuals. For those who live with the daily challenges of cardiovascular disease, pharmacological management aims to relieve symptoms and prevent disease progression. Despite best efforts, prescription drugs are not without their adverse effects, which can cause significant patient morbidity and consequential economic burden for healthcare systems. Patients with cardiovascular diseases are often among the most vulnerable to adverse drug reactions due to multiple co-morbidities and advanced age. Examining a patient's genome to assess for variants that may alter drug efficacy and susceptibility to adverse reactions underpins pharmacogenomics. This strategy is increasingly being implemented in clinical cardiology to tailor patient therapies. The identification of specific variants associated with adverse drug effects aims to predict those at greatest risk of harm, allowing alternative therapies to be given. This review will explore current guidance available for pharmacogenomic-based prescribing as well as exploring the potential implementation of genetic risk scores to tailor treatment. The benefits of large databases and electronic health records will be discussed to help facilitate the integration of pharmacogenomics into primary care, the heartland of prescribing.

Pharmacogenomic Clinical Decision Support: A Review, How-to Guide, and Future Vision

Clinical decision support (CDS) is an essential part of any pharmacogenomics (PGx) implementation. Increasingly, institutions have implemented CDS tools in the clinical setting to bring PGx data into patient care, and several have published their experiences with these implementations. However, barriers remain that limit the ability of some programs to create CDS tools to fit their PGx needs. Therefore, the purpose of this review is to summarize the types, functions, and limitations of PGx CDS currently in practice. Then, we provide an approachable step‐by‐step how‐to guide with a case example to help implementers bring PGx to the front lines of care regardless of their setting. Particular focus is paid to the five “rights” of CDS as a core around designing PGx CDS tools. Finally, we conclude with a discussion of opportunities and areas of growth for PGx CDS.

Genetic testing in ambulatory cardiology clinics reveals high rate of findings with clinical management implications

PURPOSE

Cardiovascular disease (CVD) is the leading cause of death in adults in the United States, yet the benefits of genetic testing are not universally accepted.

METHODS

We developed the "HeartCare" panel of genes associated with CVD, evaluating high-penetrance Mendelian conditions, coronary artery disease (CAD) polygenic risk, LPA gene polymorphisms, and specific pharmacogenetic (PGx) variants. We enrolled 709 individuals from cardiology clinics at Baylor College of Medicine, and samples were analyzed in a CAP/CLIA-certified laboratory. Results were returned to the ordering physician and uploaded to the electronic medical record.

RESULTS

Notably, 32% of patients had a genetic finding with clinical management implications, even after excluding PGx results, including 9% who were molecularly diagnosed with a Mendelian condition. Among surveyed physicians, 84% reported medical management changes based on these results, including specialist referrals, cardiac tests, and medication changes. LPA polymorphisms and high polygenic risk of CAD were found in 20% and 9% of patients, respectively, leading to diet, lifestyle, and other changes. Warfarin and simvastatin pharmacogenetic variants were present in roughly half of the cohort.

CONCLUSION

Our results support the use of genetic information in routine cardiovascular health management and provide a roadmap for accompanying research.

Cardiovascular Pharmacogenomics: An Update on Clinical Studies of Antithrombotic Drugs in Brazilian Patients

Anticoagulant and antiplatelet drugs effectively prevent thrombotic events in patients with cardiovascular diseases, ischemic stroke, peripheral vascular diseases, and other thromboembolic diseases. However, genetic and non-genetic factors affect the response to antithrombotic therapy and can increase the risk of adverse events. This narrative review discusses pharmacogenomic studies on antithrombotic drugs commonly prescribed in Brazil. Multiple Brazilian studies assessed the impact of pharmacokinetic (PK) and pharmacodynamic (PD) gene variants on warfarin response. The reduced function alleles CYP2C9*2 and CYP2C9*3, and VKORC1 rs9923231 (c.-1639G>A) are associated with increased sensitivity to warfarin and a low dose requirement to prevent bleeding episodes, whereas CYP4F2 rs2108622 (p.Val433Met) carriers have higher dose requirements (warfarin resistance). These deleterious variants and non-genetic factors (age, gender, body weight, co-administered drugs, food interactions, and others) account for up to 63% of the warfarin dose variability. Few pharmacogenomics studies have explored antiplatelet drugs in Brazilian cohorts, finding associations between CYP2C19*2, PON1 rs662 and ABCC3 rs757421 genotypes and platelet responsiveness or clopidogrel PK in subjects with coronary artery disease (CAD) or acute coronary syndrome (ACS), whereas ITGB3 contributes to aspirin PK but not platelet responsiveness in diabetic patients. Brazilian guidelines on anticoagulants and antiplatelets recommend the use of a platelet aggregation test or genotyping only in selected cases of ACS subjects without ST-segment elevation taking clopidogrel, and also suggest CYP2C9 and VKORC1 genotyping before starting warfarin therapy to assess the risk of bleeding episodes or warfarin resistance.

Stroke Genetics: Turning Discoveries into Clinical Applications

The field of medical and population genetics in stroke is moving at a rapid pace and has led to unanticipated opportunities for discovery and clinical applications. Genome-wide association studies have highlighted the role of specific pathways relevant to etiologically defined subtypes of stroke and to stroke as a whole. They have further offered starting points for the exploration of novel pathways and pharmacological strategies in experimental systems. Mendelian randomization studies continue to provide insights in the causal relationships between exposures and outcomes and have become a useful tool for predicting the efficacy and side effects of drugs. Additional applications that have emerged from recent discoveries include risk prediction based on polygenic risk scores and pharmacogenomics. Among the topics currently moving into focus is the genetics of stroke outcome. While still at its infancy, this field is expected to boost the development of neuroprotective agents. We provide a brief overview on recent progress in these areas.

Genomewide Association Studies in Pharmacogenomics

The increasing availability of genotype data linked with information about drug-response phenotypes has enabled genomewide association studies (GWAS) that uncover genetic determinants of drug response. GWAS have discovered associations between genetic variants and both drug efficacy and adverse drug reactions. Despite these successes, the design of GWAS in pharmacogenomics (PGx) faces unique challenges. In this review, we analyze the last decade of GWAS in PGx. We review trends in publications over time, including the drugs and drug classes studied and the clinical phenotypes used. Several data sharing consortia have contributed substantially to the PGx GWAS literature. We anticipate increased focus on biobanks and highlight phenotypes that would best enable future PGx discoveries.

Translational Pharmacogenomics: Discovery, Evidence Synthesis and Delivery of Race-Conscious Medicine

Response to medications, the principal treatment modality for acute and chronic diseases, is highly variable, with 40-70% of patients exhibiting lack of efficacy or adverse drug reactions. With ~ 15-30% of this variability explained by genetic variants, pharmacogenomics has become a valuable tool in our armamentarium for optimizing treatments and is poised to play an increasing role in clinical care. This review presents the progress made toward elucidating genetic underpinnings of drug response including discovery of race/ancestry-specific pharmacogenetic variants and discusses the current evidence and evidence framework for actionability. The review is framed in the context of changing demographics and evolving views related to race and ancestry. Finally, it highlights the vital role played by cohort studies in elucidating genetic differences in drug response across race and ancestry and the informal collaborations that have enabled the field to bridge the "bench to bedside" translational gap.

Opportunity for Genotype-Guided Prescribing Among Adult Patients in 11 US Health Systems

The value of utilizing a multigene pharmacogenetic panel to tailor pharmacotherapy is contingent on the prevalence of prescribed medications with an actionable pharmacogenetic association. The Clinical Pharmacogenetics Implementation Consortium (CPIC) has categorized over 35 gene-drug pairs as "level A," for which there is sufficiently strong evidence to recommend that genetic information be used to guide drug prescribing. The opportunity to use genetic information to tailor pharmacotherapy among adult patients was determined by elucidating the exposure to CPIC level A drugs among 11 Implementing Genomics In Practice Network (IGNITE)-affiliated health systems across the US. Inpatient and/or outpatient electronic-prescribing data were collected between January 1, 2011 and December 31, 2016 for patients ≥ 18 years of age who had at least one medical encounter that was eligible for drug prescribing in a calendar year. A median of ~ 7.2 million adult patients was available for assessment of drug prescribing per year. From 2011 to 2016, the annual estimated prevalence of exposure to at least one CPIC level A drug prescribed to unique patients ranged between 15,719 (95% confidence interval (CI): 15,658-15,781) in 2011 to 17,335 (CI: 17,283-17,386) in 2016 per 100,000 patients. The estimated annual exposure to at least 2 drugs was above 7,200 per 100,000 patients in most years of the study, reaching an apex of 7,660 (CI: 7,632-7,687) per 100,000 patients in 2014. An estimated 4,748 per 100,000 prescribing events were potentially eligible for a genotype-guided intervention. Results from this study show that a significant portion of adults treated at medical institutions across the United States is exposed to medications for which genetic information, if available, should be used to guide prescribing.

Prevalence of five pharmacologically most important CYP2C9 and CYP2C19 allelic variants in the population from the Republic of Srpska in Bosnia and Herzegovina

The enzymes of the cytochrome P450 superfamily play a critical role in phase I drug metabolism. Among them, CYP2C9 and CYP2C19 are clinically important, as they can mediate severe toxicity, therapy failure, and increased susceptibility to cancer and other diseases caused by chemicals. The aim of this study was to determine the prevalence of pharmacologically most important allelic variants of the CYP2C9 and CYP2C19 genes in the general population of the Republic of Srpska (Bosnia and Herzegovina) and to compare them with other populations. For this purpose we determined the genotype profile and allele frequency of 216 randomly selected healthy volunteers using real-time polymerase chain reaction (RT-PCR). The prevalence of the CYP2C9 *2 and *3 alleles was 13.6 and 7.4 %, respectively. Based on these frequencies, of the 216 participants four (1.86 %) were predicted to be poor metabolisers, 78 (36.11 %) intermediate, and the remaining 134 (62.03 %) normal metabolisers. Based on the prevalence of CYP2C19 *2 and *17 variants – 16.2 and 20.4 %, respectively – nine (4.17 %) were predicted to be poor, 57 (26.39 %) rapid, and nine (4.17 %) ultra-rapid metabolisers. We found no significant differences in allele frequencies in our population and populations from other European countries. These findings suggest that genetically determined phenotypes of CYP2C9 and CYP2C19 should be taken into consideration to minimise individual risk and improve benefits of drug therapy in the Republic of Srpska.

Admixture Has Shaped Romani Genetic Diversity in Clinically Relevant Variants

Genetic patterns of inter-population variation are a result of different demographic and adaptive histories, which gradually shape the frequency distribution of the variants. However, the study of clinically relevant mutations has a Eurocentric bias. The Romani, the largest transnational minority ethnic group in Europe, originated in South Asia and received extensive gene flow from West Eurasia. Most medical genetic studies have only explored founder mutations related to Mendelian disorders in this population. Here we analyze exome sequences and genome-wide array data of 89 healthy Spanish Roma individuals to study complex traits and disease. We apply a different framework and focus on variants with both increased and decreased allele frequencies, taking into account their local ancestry. We report several OMIM traits enriched for genes with deleterious variants showing increased frequencies in Roma or in non-Roma (e.g., obesity is enriched in Roma, with an associated variant linked to South Asian ancestry; while non-insulin dependent diabetes is enriched in non-Roma Europeans). In addition, previously reported pathogenic variants also show differences among populations, where some variants segregating at low frequency in non-Roma are virtually absent in the Roma. Lastly, we describe frequency changes in drug-response variation, where many of the variants increased in Roma are clinically associated with metabolic and cardiovascular-related drugs. These results suggest that clinically relevant variation in Roma cannot only be characterized in terms of founder mutations. Instead, we observe frequency differences compared to non-Roma: some variants are absent, while other have drifted to higher frequencies. As a result of the admixture events, these clinically damaging variants can be traced back to both European and South Asian-related ancestries. This can be attributed to a different prevalence of some genetic disorders or to the fact that genetic susceptibility variants are mostly studied in populations of European descent, and can differ in individuals with different ancestries.

Evaluation of population-level pharmacogenetic actionability in Alabama

The evolution of evidence and availability of Clinical Pharmacogenetic Implementation Consortium (CPIC) guidelines have enabled assessment of pharmacogenetic (PGx) actionability and clinical implementation. However, population‐level actionability is not well‐characterized. We leveraged the Alabama Genomic Health Initiative (AGHI) to evaluate population‐level PGx actionability. Participants (>18 years), representing all 67 Alabama counties, were genotyped using the Illumina Global Screening array. Using CPIC guidelines, actionability was evaluated using (1) genotype data and genetic ancestry, (2) prescribing data, and (3) combined genotype and medication data. Of 6,331 participants, 4230 had genotype data and 3386 had genotype and prescription data (76% women; 76% White/18% Black [self‐reported]). Genetic ancestry was concordant with self‐reported race. For CPIC level A genes, 98.6% had an actionable genotype (99.4% Blacks/African; 98.5% White/European). With the exception of DPYD and CYP2C19, the prevalence of actionable genotypes by gene differed significantly by race. Based on prescribing, actionability was highest for CYP2D6 (70.9%), G6PD (54.1%), CYP2C19 (53.5%), and CYP2C9 (47.5%). Among participants prescribed atenolol, carvedilol, or metoprolol, ~ 50% had an actionable ADRB1 genotype, associated with decreased therapeutic response, with higher actionability among Blacks compared to Whites (62.5% vs. 47.4%; p < 0.0001). Based on both genotype and prescribing frequencies, no significant differences in actionability were observed between men and women. This statewide effort highlights PGx population‐level impact to help optimize pharmacotherapy. Almost all Alabamians harbor an actionable genotype, and a significant proportion are prescribed affected medications. Statewide efforts, such as AGHI, lay the foundation for translational research and evaluate “real‐world” outcomes of PGx.

Allele frequencies of single nucleotide polymorphisms of clinically important drug-metabolizing enzymes CYP2C9, CYP2C19, and CYP3A4 in a Thai population

Prior knowledge of allele frequencies of cytochrome P450 polymorphisms in a population is crucial for the revision and optimization of existing medication choices and doses. In the current study, the frequency of the CYP2C9*2, CYP2C9*3, CYP2C19*2, CYP2C19*3, CYP2C19*6, CYP2C19*17, and CYP3A4 (rs4646437) alleles in a Thai population across different regions of Thailand was examined. Tests for polymorphisms of CYP2C9 and CYP3A4 were performed using TaqMan SNP genotyping assay and CYP2C19 was performed using two different methods; TaqMan SNP genotyping assay and Luminex x Tag V3. The blood samples were collected from 1205 unrelated healthy individuals across different regions within Thailand. Polymorphisms of CYP2C9 and CYP2C19 were transformed into phenotypes, which included normal metabolizer (NM), intermediate metabolizer (IM), poor metabolizer (PM), and rapid metabolizers (RM). The CYP2C9 allele frequencies among the Thai population were 0.08% and 5.27% for the CYP2C9*2 and CYP2C9*3 alleles, respectively. The CYP2C19 allele frequencies among the Thai population were 25.60%, 2.50%, 0.10%, and 1.80% for the CYP2C19*2, CYP2C19*3, CYP2C19*6, and CYP2C19*17 alleles, respectively. The allele frequency of the CYP3A4 (rs4646437) variant allele was 28.50% in the Thai population. The frequency of the CYP2C9*3 allele was significantly lower among the Northern Thai population (P < 0.001). The frequency of the CYP2C19*17 allele was significantly higher in the Southern Thai population (P < 0.001). Our results may provide an understanding of the ethnic differences in drug responses and support for the utilization of pharmacogenomics testing in clinical practice.

Pharmacogenetic determinants of warfarin in the Indian population

BACKGROUND

Several studies optimized the warfarin dose based on CYP2C9*2, CYP2C9*3, VKORC1 -1639 G > A, CYP4F2 V433M. But, the information on the rare variants is lacking. In this study, we have explored the prevalence of common and rare pharmacogenetic determinants of warfarin and determined their damaging nature.

METHODS

We have analyzed 2000 healthy adults using the Infinium global screening array (GSA) for 15 pharmacogenetic determinants of warfarin. In addition, we have elucidated the impact of these variants on protein function, stability, dynamics, evolutionary preservation, and ligand binding propensity.

RESULTS

The GSA Analysis has revealed that CYP4F2 V433M (MAF: 39.425%), VKORC1 -1639 G > A (MAF: 20.5%), CYP2C9*3 (MAF:9.925%), and CYP2C9*2 (MAF:4.575%) are common, while CYP2C9*14 (MAF: 1.475%), CYP2C9*4 (0.175%), CYP2C9*5 (0.125%), and CYP2C9*11 (0.125%) are rare. Position-specific evolutionary preservation (PSEP) analysis has revealed that CYP2C9*4 is possibly damaging, while CYP2C9*5, CYP2C9*11, and CYP2C9*14 are probably damaging. CYP2C9*4 has high thermolability (-10.14 kcal/mol). Among the rare CYP2C9 variants, CYP2C9*4 and CYP2C9*11 exert destabilizing effects and may have increased molecular flexibility, while CYP2C9*5 and CYP2C9*14 exert stabilizing effects and may have decreased molecular flexibility. DNase I footprint analysis has revealed the loss of the E-box consensus sequence due to VKORC1 -1639 G > A polymorphism.

CONCLUSION

CYP2C9*2, CYP2C9*3, VKORC1 -1639 G > A and CYP4F2 V433M are common; CYP2C9*4, CYP2C9*5, CYP2C9*11, and CYP2C9*14 variants are rare in Indian subjects. All the CYP2C9 variants are found to be damaging. DNase I footprint analysis provided the mechanistic rationale for the association of VKORC1 -1639 G > A with warfarin sensitivity.

The Interface of Therapeutics and Genomics in Cardiovascular Medicine

Pharmacogenomics has a burgeoning role in cardiovascular medicine, from warfarin dosing to antiplatelet choice, with recent developments in sequencing bringing the promise of personalised medicine ever closer to the bedside. Further scientific evidence, real-world clinical trials, and economic modelling are needed to fully realise this potential. Additionally, tools such as polygenic risk scores, and results from Mendelian randomisation analyses, are only in the early stages of clinical translation and merit further investigation. Genetically targeted rational drug design has a strong evidence base and, due to the nature of genetic data, academia, direct-to-consumer companies, healthcare systems, and industry may meet in an unprecedented manner. Data sharing navigation may prove problematic. The present manuscript addresses these issues and concludes a need for further guidance to be provided to prescribers by professional bodies to aid in the consideration of such complexities and guide translation of scientific knowledge to personalised clinical action, thereby striving to improve patient care. Additionally, technologic infrastructure equipped to handle such large complex data must be adapted to pharmacogenomics and made user friendly for prescribers and patients alike.