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Interindividual heterogeneity in drug response is a central feature of all drug therapies. Studies in individual patients, families, and populations over the past several decades have identified variants in genes encoding drug elimination or drug target pathways that in some cases contribute substantially to variable efficacy and toxicity. Important associations of pharmacogenomics in cardiovascular medicine include clopidogrel and risk for in-stent thrombosis, steady-state warfarin dose, myotoxicity with simvastatin, and certain drug-induced arrhythmias. This review describes methods used to accumulate and validate these findings and points to approaches--now being put in place at some centers--to implementing them in clinical care.
BACKGROUND - Warfarin inhibits vitamin K-dependent coagulation factors. Being fat-soluble, the availability of vitamin K may vary according to body fat. We hypothesized that body mass index (BMI), a proxy of body fat, may interact with vitamin K intake in determining a warfarin maintenance (WM) dose.
METHODS - Patients with data on vitamin K intake, potential confounders and WM dose (n = 172) were included in linear regression models to test whether BMI modifies the relation between vitamin K intake and WM dose.
RESULTS - Warfarin loading dose correlated with the maintenance dose (r = 0.36, p < 0.0001) but was not significantly associated with WM dose in analyses adjusted for vitamin K epoxide reductase (VKORC1) and cytochrome P450 2C9 (CYP2C9) genotypes. In fully adjusted models, BMI was associated (p = 0.001) with WM dose but vitamin K was only marginally positively associated (p = 0.06) with WM dose. We found no interaction (p > 0.05) between BMI and vitamin K intake with regard to WM dose. Inclusion of vitamin K intake in the model only slightly improved the amount of variance (1.1%) explained by age, gender, BMI, race, physical activity, energy intake and VKORC1 and CYP2C9 genotypes.
CONCLUSION - Our data suggest that body fat does not affect the relation between vitamin K intake and WM dose.
Using a derivation cohort (N=349), we developed the first warfarin dosing algorithm that includes recently discovered polymorphisms in VKORC1 and CYP2C9 associated with warfarin dose requirement in African Americans (AAs). We tested our novel algorithm in an independent cohort of 129 AAs and compared the dose prediction to the International Warfarin Pharmacogenetics Consortium (IWPC) dosing algorithms. Our algorithm explains more of the phenotypic variation (R(2)=0.27) than the IWPC pharmacogenomics (R(2)=0.15) or clinical (R(2)=0.16) algorithms. Among high-dose patients, our algorithm predicted a higher proportion of patients within 20% of stable warfarin dose (45% vs 29% and 2% in the IWPC pharmacogenomics and clinical algorithms, respectively). In contrast to our novel algorithm, a significant inverse correlation between predicted dose and percent West African ancestry was observed for the IWPC pharmacogenomics algorithm among patients requiring ⩾60 mg per week (β=-2.04, P=0.02).
BACKGROUND - VKORC1 and CYP2C9 are important contributors to warfarin dose variability, but explain less variability for individuals of African descent than for those of European or Asian descent. We aimed to identify additional variants contributing to warfarin dose requirements in African Americans.
METHODS - We did a genome-wide association study of discovery and replication cohorts. Samples from African-American adults (aged ≥18 years) who were taking a stable maintenance dose of warfarin were obtained at International Warfarin Pharmacogenetics Consortium (IWPC) sites and the University of Alabama at Birmingham (Birmingham, AL, USA). Patients enrolled at IWPC sites but who were not used for discovery made up the independent replication cohort. All participants were genotyped. We did a stepwise conditional analysis, conditioning first for VKORC1 -1639G→A, followed by the composite genotype of CYP2C9*2 and CYP2C9*3. We prespecified a genome-wide significance threshold of p<5×10(-8) in the discovery cohort and p<0·0038 in the replication cohort.
FINDINGS - The discovery cohort contained 533 participants and the replication cohort 432 participants. After the prespecified conditioning in the discovery cohort, we identified an association between a novel single nucleotide polymorphism in the CYP2C cluster on chromosome 10 (rs12777823) and warfarin dose requirement that reached genome-wide significance (p=1·51×10(-8)). This association was confirmed in the replication cohort (p=5·04×10(-5)); analysis of the two cohorts together produced a p value of 4·5×10(-12). Individuals heterozygous for the rs12777823 A allele need a dose reduction of 6·92 mg/week and those homozygous 9·34 mg/week. Regression analysis showed that the inclusion of rs12777823 significantly improves warfarin dose variability explained by the IWPC dosing algorithm (21% relative improvement).
INTERPRETATION - A novel CYP2C single nucleotide polymorphism exerts a clinically relevant effect on warfarin dose in African Americans, independent of CYP2C9*2 and CYP2C9*3. Incorporation of this variant into pharmacogenetic dosing algorithms could improve warfarin dose prediction in this population.
FUNDING - National Institutes of Health, American Heart Association, Howard Hughes Medical Institute, Wisconsin Network for Health Research, and the Wellcome Trust.
Copyright © 2013 Elsevier Ltd. All rights reserved.
Variability in drug responsiveness is a sine qua non of modern therapeutics, and the contribution of genomic variation is increasingly recognized. Investigating the genomic basis for variable responses to cardiovascular therapies has been a model for pharmacogenomics in general and has established critical pathways and specific loci modulating therapeutic responses to commonly used drugs such as clopidogrel, warfarin, and statins. In addition, genomic approaches have defined mechanisms and genetic variants underlying important toxicities with these and other drugs. These findings have not only resulted in changes to the product labels but also have led to development of initial clinical guidelines that consider how to facilitate incorporating genetic information to the bedside. This review summarizes the state of knowledge in cardiovascular pharmacogenomics and considers how variants described to date might be deployed in clinical decision making.
Warfarin is the most commonly used oral anticoagulant worldwide. Warfarin has a narrow therapeutic index, requiring frequent monitoring of the INR to achieve therapeutic anticoagulation. The role of pharmacogenomics in warfarin disposition and response has been well established in adults, but remains unclear for pediatric patients. In this review, we focus on the important CYP2C9 and VKORC1 variants involved in warfarin response, our current understanding of warfarin disposition and pharmacogenomics, and recent warfarin pharmacogenetic studies in pediatric patients. Finally, we discuss the need for future pediatric studies and the clinical implications of developing pharmacogenetic-based dosing algorithms in children.
Copyright © 2013 Wiley Periodicals, Inc.
AIM - Warfarin pharmacogenomic algorithms reduce dosing error, but perform poorly in non-European-Americans. Electronic health record (EHR) systems linked to biobanks may allow for pharmacogenomic analysis, but they have not yet been used for this purpose.
PATIENTS & METHODS - We used BioVU, the Vanderbilt EHR-linked DNA repository, to identify European-Americans (n = 1022) and African-Americans (n = 145) on stable warfarin therapy and evaluated the effect of 15 pharmacogenetic variants on stable warfarin dose.
RESULTS - Associations between variants in VKORC1, CYP2C9 and CYP4F2 with weekly dose were observed in European-Americans as well as additional variants in CYP2C9 and CALU in African-Americans. Compared with traditional 5 mg/day dosing, implementing the US FDA recommendations or the International Warfarin Pharmacogenomics Consortium (IWPC) algorithm reduced error in weekly dose in European-Americans (13.5-12.4 and 9.5 mg/week, respectively) but less so in African-Americans (15.2-15.0 and 13.8 mg/week, respectively). By further incorporating associated variants specific for European-Americans and African-Americans in an expanded algorithm, dose-prediction error reduced to 9.1 mg/week (95% CI: 8.4-9.6) in European-Americans and 12.4 mg/week (95% CI: 10.0-13.2) in African-Americans. The expanded algorithm explained 41 and 53% of dose variation in African-Americans and European-Americans, respectively, compared with 29 and 50%, respectively, for the IWPC algorithm. Implementing these predictions via dispensable pill regimens similarly reduced dosing error.
CONCLUSION - These results validate EHR-linked DNA biorepositories as real-world resources for pharmacogenomic validation and discovery.
Identification of patients' drug exposure information is critical to drug-related research that is based on electronic medical records (EMRs). Drug information is often embedded in clinical narratives and drug regimens change frequently because of various reasons like intolerance or insurance issues, making accurate modeling challenging. Here, we developed an informatics framework to determine patient drug exposure histories from EMRs by combining natural language processing (NLP) and machine learning (ML) technologies. Our framework consists of three phases: 1) drug entity recognition - identifying drug mentions; 2) drug event detection - labeling drug mentions with a status (e.g., "on" or "stop"); and 3) drug exposure modeling - predicting if a patient is taking a drug at a given time using the status and temporal information associated with the mentions. We applied the framework to determine patient warfarin exposure at hospital admissions and achieved 87% precision, 79% recall, and an area under the receiver-operator characteristic curve of 0.93.
Variable warfarin response during treatment initiation poses a significant challenge to providing optimal anticoagulation therapy. We investigated the determinants of initial warfarin response in a cohort of 167 patients. During the first nine days of treatment with pharmacogenetics-guided dosing, S-warfarin plasma levels and international normalized ratio were obtained to serve as inputs to a pharmacokinetic-pharmacodynamic (PK-PD) model. Individual PK (S-warfarin clearance) and PD (I(max)) parameter values were estimated. Regression analysis demonstrated that CYP2C9 genotype, kidney function, and gender were independent determinants of S-warfarin clearance. The values for I(max) were dependent on VKORC1 and CYP4F2 genotypes, vitamin K status (as measured by plasma concentrations of proteins induced by vitamin K absence, PIVKA-II) and weight. Importantly, indication for warfarin was a major independent determinant of I(max) during initiation, where PD sensitivity was greater in atrial fibrillation than venous thromboembolism. To demonstrate the utility of the global PK-PD model, we compared the predicted initial anticoagulation responses with previously established warfarin dosing algorithms. These insights and modeling approaches have application to personalized warfarin therapy.
Single-nucleotide polymorphisms in genes that affect warfarin metabolism (cytochrome P450 2C9 gene, CYP2C9) and response (vitamin K epoxide reductase complex 1 gene, VKORC1) have an important influence on warfarin therapy, particularly during initiation; however, there is a lack of consensus regarding the optimal pharmacogenetics-based initiation strategy. We conducted a prospective cohort study in which patients requiring warfarin therapy for atrial fibrillation or venous thromboembolism were initiated with a novel pharmacogenetics-initiation protocol (WRAPID, Warfarin Regimen using A Pharmacogenetics-guided Initiation Dosing) that incorporated loading and maintenance doses based on genetics, clinical variables, and response (n = 167, followed up for 90 days), to assess the influence of genetic variations on anticoagulation responses. Application of the WRAPID algorithm resulted in a negligible influence of genetic variation in VKORC1 or CYP2C9 on time to achievement of first therapeutic response (P = .52, P = .28) and risk of overanticoagulation (P = .64, P = .96). After adjustment for covariates, time to stable anticoagulation was not influenced by VKORC1 or CYP2C9 genotype. Importantly, time spent within or above the therapeutic range did not differ among VKORC1 and CYP2C9 genotype groups. Moreover, the overall time course of the anticoagulation response among the genotype groups was similar and predictable. We demonstrate the clinical utility of genetics-guided warfarin initiation with the WRAPID protocol to provide safe and optimal anticoagulation therapy for patients with atrial fibrillation or venous thromboembolism.