Genetic warfarin dosing: tables versus algorithms

Warfarin pharmacogenetics

The cytochrome P450 (CYP) 2C9 and vitamin K epoxide reductase complex 1 (VKORC1) genotypes have been strongly and consistently associated with warfarin dose requirements, and dosing algorithms incorporating genetic and clinical information have been shown to be predictive of stable warfarin dose. However, clinical trials evaluating genotype-guided warfarin dosing produced mixed results, calling into question the utility of this approach. Recent trials used surrogate markers as endpoints rather than clinical endpoints, further complicating translation of the data to clinical practice. The present data do not support genetic testing to guide warfarin dosing, but in the setting where genotype data are available, use of such data in those of European ancestry is reasonable. Outcomes data are expected from an on-going trial, observational studies continue, and more work is needed to define dosing algorithms that incorporate appropriate variants in minority populations; all these will further shape guidelines and recommendations on the clinical utility of genotype-guided warfarin dosing.

Implementation and utilization of genetic testing in personalized medicine

Clinical genetic testing began over 30 years ago with the availability of mutation detection for sickle cell disease diagnosis. Since then, the field has dramatically transformed to include gene sequencing, high-throughput targeted genotyping, prenatal mutation detection, preimplantation genetic diagnosis, population-based carrier screening, and now genome-wide analyses using microarrays and next-generation sequencing. Despite these significant advances in molecular technologies and testing capabilities, clinical genetics laboratories historically have been centered on mutation detection for Mendelian disorders. However, the ongoing identification of deoxyribonucleic acid (DNA) sequence variants associated with common diseases prompted the availability of testing for personal disease risk estimation, and created commercial opportunities for direct-to-consumer genetic testing companies that assay these variants. This germline genetic risk, in conjunction with other clinical, family, and demographic variables, are the key components of the personalized medicine paradigm, which aims to apply personal genomic and other relevant data into a patient’s clinical assessment to more precisely guide medical management. However, genetic testing for disease risk estimation is an ongoing topic of debate, largely due to inconsistencies in the results, concerns over clinical validity and utility, and the variable mode of delivery when returning genetic results to patients in the absence of traditional counseling. A related class of genetic testing with analogous issues of clinical utility and acceptance is pharmacogenetic testing, which interrogates sequence variants implicated in interindividual drug response variability. Although clinical pharmacogenetic testing has not previously been widely adopted, advances in rapid turnaround time genetic testing technology and the recent implementation of preemptive genotyping programs at selected medical centers suggest that personalized medicine through pharmacogenetics is now a reality. This review aims to summarize the current state of implementing genetic testing for personalized medicine, with an emphasis on clinical pharmacogenetic testing.

VKORC1 and CYP2C9 genotypes in Egyptian patients with warfarin resistance

Warfarin is the most commonly prescribed anticoagulant drug; however, a narrow therapeutic range and a high risk of bleeding or stroke complicate its clinical use. Warfarin resistance was defined as prolonged warfarin requirements of more than 15 mg/day to achieve therapeutic anticoagulation or failure to achieve therapeutic anticoagulation with more than 20 mg/day. The resistance is associated with polymorphisms of the vitamin K epoxide reductase-oxidase complex (VKORC1) and cytochrome P450-2C9 (CYP2C9) genes, which affect warfarin pharmacodynamics and pharmacokinetics, respectively. Identification of the VKORC1 -1639 (A/G) and CYP2C9 (*1/*2/*3) allelic variants was performed using the PGX-Thrombo Strip in 41 patients with warfarin resistance compared with 30 patients with normal warfarin response out of 352 diagnosed cases of deep vein thrombosis. In warfarin-resistant patients, the VKORC1-1639 genotype frequencies were GG 0.756, GA 0.244 and AA 0.0, whereas in warfarin responder patients, they were: GG 0.333, GA 0.400 and AA 0.276 with P ≤ 0.001. The CYP2C9 genotype frequencies showed nonsignificant difference in both group of patients (P = 0.31). Our results suggest that the VKORC1-1639 GG and the wild type CYP2C9*1*1genotypes are associated with the high-dose requirement for warfarin therapy, and that VKORC1-1639 GG is responsible for warfarin resistance and failure in Egyptian patients.

Personalized pharmacogenomics: predicting efficacy and adverse drug reactions

Drug response varies between individuals owing to disease heterogeneity, environmental factors, and genetic factors. Genetic factors can affect both the pharmacokinetics and pharmacodynamics of a drug, leading to changes in local and systemic drug exposure and/or changes in the function of the drug target, altering drug response. Several pharmacogenetic biomarkers are already utilized in clinical practice and have been shown to improve clinical outcomes. However, a large number of other biomarkers have never made it beyond the discovery stage. Concerted effort is needed to improve the translation of pharmacogenetic biomarkers into clinical practice, and this will involve the use of standardized phenotyping and genotyping strategies, collaborative work, multidisciplinary approaches to identifying and replicating associations, and cooperation with industry to facilitate translation and commercialization. Acceptance of these approaches by clinicians, regulators, patients, and the public will be important in determining future success.

Current concepts and clinical applications of stroke genetics

Driven by innovative technologies, novel analytical methods, and collaborations unimaginable not long ago, our understanding of the role of genetic variation in stroke has advanced substantially in recent years. However, a vast amount of data have accumulated quickly, and increasingly complex methodologies used in studies make keeping up to date on relevant findings difficult. In addition to well known, highly penetrant rare mutations that cause mendelian disorders related to stroke, several common genetic variants have been associated with common stroke subtypes, some of which also affect disease severity and clinical outcome. Furthermore, common genetic variations in biological pathways that have an important role in the pathophysiology of cerebrovascular diseases-such as blood pressure and oxidative phosphorylation-have been implicated in stroke. Clinical and translational applications of these and future discoveries in stroke genetics include identification of novel targets for treatment and development of personalised approaches to stroke prevention and management.

Effect of VKORC1, CYP2C9 and CYP4F2 genetic variants in early outcomes during acenocoumarol treatment

Aim: To analyze VKORC1, CYP2C9 and CYP4F2 polymorphisms in relation to the main outcomes in the first stages of acenocoumarol therapy. Patients & methods: Nine hundred and forty one patients who had started therapy and in whom time to stable dosage, time to over-anticoagulation and adverse events occurred during 3 first months were retrospectively analyzed. Results: VKORC1 AA patients needed fewer days to reach stable dosage (p = 0.017). International normalized ratio [INR] at 72 h, and VKORC1 and CYP2C9 genotypes conditioned INR values >2.5 (p < 0.001, p = 0.002 and p < 0.001, respectively), whereas CYP4F2 T carriers had a low risk of the same outcome (p = 0.009). In regards to combined genotypes, CYP4F2 had a significant effect on over-anticoagulation at the beginning of therapy except for the VKORC1 AA and CYP2C9*3 combination. Conclusion: In addition to VKORC1 and CYP2C9, CYP4F2 gene has a slight but significant role in reaching INR >2.5 during the first weeks of acenocoumarol therapy.

Original submitted 22 July 2013; Revision submitted 14 November 2013

Disclosure of individual pharmacogenomic results in research projects: when and what kind of information to return to research participants

In the growing field of genomics, the utility of returning certain research results to participants has become a highly debated issue. Existing guidelines are not explicit as to the kind of genomic information that should be returned to research participants. Moreover, very few current recommendations and articles in the literature address the return of pharmacogenomic results. Although genetics and pharmacogenomics have many similarities, the circumstances in which disclosure could have a benefit for the participants are different. This review aims to describe the conditions in which disclosure of pharmacogenomic results is appropriate.

A randomized trial of genotype-guided dosing of warfarin

BACKGROUND

The level of anticoagulation in response to a fixed-dose regimen of warfarin is difficult to predict during the initiation of therapy. We prospectively compared the effect of genotype-guided dosing with that of standard dosing on anticoagulation control in patients starting warfarin therapy.

METHODS

We conducted a multicenter, randomized, controlled trial involving patients with atrial fibrillation or venous thromboembolism. Genotyping for CYP2C9*2, CYP2C9*3, and VKORC1 (-1639G→A) was performed with the use of a point-of-care test. For patients assigned to the genotype-guided group, warfarin doses were prescribed according to pharmacogenetic-based algorithms for the first 5 days. Patients in the control (standard dosing) group received a 3-day loading-dose regimen. After the initiation period, the treatment of all patients was managed according to routine clinical practice. The primary outcome measure was the percentage of time in the therapeutic range of 2.0 to 3.0 for the international normalized ratio (INR) during the first 12 weeks after warfarin initiation.

RESULTS

A total of 455 patients were recruited, with 227 randomly assigned to the genotype-guided group and 228 assigned to the control group. The mean percentage of time in the therapeutic range was 67.4% in the genotype-guided group as compared with 60.3% in the control group (adjusted difference, 7.0 percentage points; 95% confidence interval, 3.3 to 10.6; P<0.001). There were significantly fewer incidences of excessive anticoagulation (INR ≥4.0) in the genotype-guided group. The median time to reach a therapeutic INR was 21 days in the genotype-guided group as compared with 29 days in the control group (P<0.001).

CONCLUSIONS

Pharmacogenetic-based dosing was associated with a higher percentage of time in the therapeutic INR range than was standard dosing during the initiation of warfarin therapy. (Funded by the European Commission Seventh Framework Programme and others; ClinicalTrials.gov number, NCT01119300.).

Comparative genetics of warfarin resistance

Warfarin and other 4-hydroxycoumarin-based oral anticoagulants targeting vitamin K 2,3-epoxide reductase complex subunit 1 (VKORC1) are administered to humans, mice and rats with different purposes in mind - to act as pesticides in high-dosage baits for killing rodents, but also to save lives when administered in low dosages as antithrombotic drugs in humans. However, high-dosage warfarin used to control rodent populations has resulted in numerous mutations causing warfarin resistance. Currently, six single missense mutations in mice, 12 distinct missense mutations in rats, as well as compound heterozygous or homozygous mutations with up to six distinct missense mutations per Vkorc1 allele have been described. Warfarin resistance missense mutations for human VKORC1 have also been found world-wide, but differ characteristically from those in rodents. In humans, 26 distinct mutations have been characterized, but occur only rarely either in heterozygous or, even rarer, in homozygous form. In this review, we summarize the known VKORC1 missense mutations causing warfarin and other 4-hydroxycoumarin drug resistance, identify genomics databases as new sources of data, explore possible underlying genetic mechanisms, and summarize similarities and differences between warfarin resistant VKORC1 variants in humans and rodents.

Clopidogrel and warfarin pharmacogenetic tests: what is the evidence for use in clinical practice?

PURPOSE OF REVIEW

To review the most promising genetic markers associated with the variability in the safety or efficacy of warfarin and clopidogrel and highlight the verification and validation initiatives for translating clopidogrel and warfarin pharmacogenetic tests to clinical practice.

RECENT FINDINGS

Rapid advances in pharmacogenetics, continuous decrease in genotyping cost, development of point-of-care devices and the newly established clinical genotyping programs at several institutions hold the promise of individualizing clopidogrel and warfarin based on genotype. Guidelines have been established to assist clinicians in prescribing clopidogrel or warfarin dose based on genotype. However, the clinical utility of clopidogrel and warfarin is still limited. Accordingly, large randomized clinical trials are underway to define the role of clopidogrel and warfarin pharmacogenetics in clinical practice.

SUMMARY

Pharmacogenetics has offered compelling evidence toward the individualization of clopidogrel and warfarin therapies. The rapid advances in technology make the clinical implementation of clopidogrel and warfarin pharmacogenetics possible. The clinical genotyping programs and the ongoing clinical trials will help in overcoming some of the barriers facing the clinical implementation of clopidogrel and warfarin pharmacogenetics.

Applied pharmacogenomics in cardiovascular medicine

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.

Warfarin pharmacogenetics: A controlled dose–response study in healthy subjects

The aim of this study was to determine how genetic variants contribute to warfarin dosing variability when non-genetic factors are controlled. Thirty healthy subjects were subjected to a warfarin dosing algorithm with daily international normalized ratio (INR) measurements to INR ≥ 2.0, then off warfarin to INR ≤ 1.2. The primary outcome was the cumulative dose required to achieve INR ≥ 2.0 for 2 consecutive days. CYP2C9 ( p=0.004) and VKORC1 ( p=0.02) variant carriers required lower cumulative doses, and CYP4F2 carriers required higher doses ( p=0.04). Subjects with variants in both CYP2C9 and VKORC1 required fewer days to reach INR ≥ 2.0 than wild-type subjects or those with variants in CYP2C9 or VKORC1 ( p=0.01). Genetic contribution to dose variability (~62%) was greater than previously reported, suggesting that uncontrolled clinical variables influence the effect of these variants. In conclusion, genotype-guided warfarin-dosing algorithms may rely more on genetic variables in healthier individuals than in patients with clinical confounders. ClinicalTrials.gov Identifier: NCT01520402

Pharmacogenetics in clinical practice

Pharmacogenetics is a discipline that investigates how genetic variation relates to the drug efficacy and safety. The goal of pharmacogenetics is a personalized treatment, where according to genotype we would be able to prescribe the most effective drug at the most appropriate dose for an individual patient. The aim of this review is to summarize pharmacogenetics as a specialization with its own background, research, methods, including barriers and promises for the future.

Warfarin anticoagulant therapy: a Southern Italy pharmacogenetics-based dosing model

Background and Aim

Warfarin is the most frequently prescribed anticoagulant worldwide. However, warfarin therapy is associated with a high risk of bleeding and thromboembolic events because of a large interindividual dose-response variability. We investigated the effect of genetic and non genetic factors on warfarin dosage in a South Italian population in the attempt to setup an algorithm easily applicable in the clinical practice.

Materials and Methods

A total of 266 patients from Southern Italy affected by cardiovascular diseases were enrolled and their clinical and anamnestic data recorded. All patients were genotyped for CYP2C9*2,*3, CYP4F2*3, VKORC1 -1639 G>A by the TaqMan assay and for variants VKORC1 1173 C>T and VKORC1 3730 G>A by denaturing high performance liquid chromatography and direct sequencing. The effect of genetic and not genetic factors on warfarin dose variability was tested by multiple linear regression analysis, and an algorithm based on our data was established and then validated by the Jackknife procedure.

Results

Warfarin dose variability was influenced, in decreasing order, by VKORC1-1639 G>A (29.7%), CYP2C9*3 (11.8%), age (8.5%), CYP2C9*2 (3.5%), gender (2.0%) and lastly CYP4F2*3 (1.7%); VKORC1 1173 C>T and VKORC1 3730 G>A exerted a slight effect (<1% each). Taken together, these factors accounted for 58.4% of the warfarin dose variability in our population. Data obtained with our algorithm significantly correlated with those predicted by the two online algorithms: Warfarin dosing and Pharmgkb (p<0.001; R² = 0.805 and p<0.001; R² = 0.773, respectively).

Conclusions

Our algorithm, which is based on six polymorphisms, age and gender, is user-friendly and its application in clinical practice could improve the personalized management of patients undergoing warfarin therapy.

Feasibility of implementing a comprehensive warfarin pharmacogenetics service

STUDY OBJECTIVE

To determine the procedural feasibility of a pharmacist-led interdisciplinary service for providing genotype-guided warfarin dosing for hospitalized patients newly starting warfarin.

DESIGN

Prospective observational study.

SETTING

A 438-bed tertiary care hospital affiliated with a large academic institution.

PATIENTS

Eighty patients who started warfarin therapy and were managed by a newly implemented pharmacogenetics service.

INTERVENTION

All patients received routine warfarin genotyping and clinical pharmacogenetics consultation.

MEASUREMENTS AND MAIN RESULTS

The primary outcomes were percentage of genotype-guided dose recommendations available prior to the second warfarin dose and adherence of the medical staff to doses recommended by the pharmacogenetics service. Of 436 genotype orders placed during the first 6 months of the service, 190 (44%) were deemed appropriate. For the 80 patients on the service who consented to data collection, 76% of the genotypes were available prior to the second warfarin dose. The median (range) time from genotype order to genotype result was 26 hours (7-80 hrs), and the time to genotype-guided dose recommendation was 30 hours (7-80 hrs). A total of 73% of warfarin doses ordered by the medical staff were within 0.5 mg of the daily dose recommended by the pharmacogenetics consult service.

CONCLUSION

Providing routine genotype-guided warfarin dosing supported by a pharmacogenetics consult service is feasible from a procedural standpoint, with most genotypes available prior to the second warfarin dose and good adherence to genotype-guided dose recommendations by the medical staff.

Novel associations of VKORC1 variants with higher acenocoumarol requirements

BACKGROUND

Algorithms combining both clinical and genetic data have been developed to improve oral anticoagulant therapy. Three polymorphisms in two genes, VKORC1 and CYP2C9, are the main coumarin dose determinants and no additional polymorphisms of any relevant pharmacogenetic importance have been identified.

OBJECTIVES

To identify new genetic variations in VKORC1 with relevance for oral anticoagulant therapy.

METHODS AND RESULTS

3949 consecutive patients taking acenocoumarol were genotyped for the VKORC1 rs9923231 and CY2C9* polymorphisms. Of these, 145 patients with a dose outside the expected range for the genetic profile determined by these polymorphisms were selected. Clinical factors explained the phenotype in 88 patients. In the remaining 57 patients, all with higher doses than expected, we sequenced the VKORC1 gene and genetic changes were identified in 14 patients. Four patients carried VKORC1 variants previously related to high coumarin doses (L128R, N = 1 and D36Y, N = 3).Three polymorphisms were also detected: rs17878544 (N = 5), rs55894764 (N = 4) and rs7200749 (N = 2) which was in linkage disequilibrium with rs17878544. Finally, 2 patients had lost the rs9923231/rs9934438 linkage. The prevalence of these variations was higher in these patients than in the whole sample. Multivariate linear regression analysis revealed that only D36Y and rs55894764 variants significantly affect the dose, although the improvement in the prediction model is small (from 39% to 40%).

CONCLUSION

Our strategy identified novel associations of VKORC1 variants with higher acenocoumarol doses albeit with a low effect size. Further studies are necessary to test their influence on the VKORC1 function and the cost/benefit of their inclusion in pharmacogenetic algorithms.

Pharmacogenetics and cardiovascular disease--implications for personalized medicine

The past decade has seen tremendous advances in our understanding of the genetic factors influencing response to a variety of drugs, including those targeted at treatment of cardiovascular diseases. In the case of clopidogrel, warfarin, and statins, the literature has become sufficiently strong that guidelines are now available describing the use of genetic information to guide treatment with these therapies, and some health centers are using this information in the care of their patients. There are many challenges in moving from research data to translation to practice; we discuss some of these barriers and the approaches some health systems are taking to overcome them. The body of literature that has led to the clinical implementation of CYP2C19 genotyping for clopidogrel, VKORC1, CYP2C9; and CYP4F2 for warfarin; and SLCO1B1 for statins is comprehensively described. We also provide clarity for other genes that have been extensively studied relative to these drugs, but for which the data are conflicting. Finally, we comment briefly on pharmacogenetics of other cardiovascular drugs and highlight β-blockers as the drug class with strong data that has not yet seen clinical implementation. It is anticipated that genetic information will increasingly be available on patients, and it is important to identify those examples where the evidence is sufficiently robust and predictive to use genetic information to guide clinical decisions. The review herein provides several examples of the accumulation of evidence and eventual clinical translation in cardiovascular pharmacogenetics.

Pharmacogenetics of warfarin: challenges and opportunities

Since the introduction in the 1950s, warfarin has become the commonly used oral anticoagulant for the prevention of thromboembolism in patients with deep vein thrombosis, atrial fibrillation or prosthetic heart valve replacement. Warfarin is highly efficacious; however, achieving the desired anticoagulation is difficult because of its narrow therapeutic window and highly variable dose response among individuals. Bleeding is often associated with overdose of warfarin. There is overwhelming evidence that an individual's warfarin maintenance is associated with clinical factors and genetic variations, most notably polymorphisms in cytochrome P450 2C9 and vitamin K epoxide reductase subunit 1. Numerous dose-prediction algorithms incorporating both genetic and clinical factors have been developed and tested clinically. However, results from major clinical trials are not available yet. This review aims to provide an overview of the field of warfarin which includes information about the drug, genetics of warfarin dose requirements, dosing algorithms developed and the challenges for the clinical implementation of warfarin pharmacogenetics.

Warfarin Pharmacogenetics: New Life for an Old Drug

Warfarin was first introduced in the 1950s and quickly became the most commonly used oral anticoagulant for the prevention of thromboembolism in patients with deep vein thrombosis, atrial fibrillation, or prosthetic heart valve replacement. Warfarin is highly effective in treating these diseases; however, several factors prevent it from even wider use, especially in Asian populations. It is difficult for patients on warfarin to reach desired anticoagulation due to its narrow therapeutic index and highly variable dose response. The major adverse event is bleeding which is associated with overdose of warfarin. Clinical and genetic factors such as polymorphisms in CYP2C9 and VKORC1 associated with an individual's warfarin maintenance have been identified. More than 20 dose prediction algorithms incorporating both genetic and clinical factors have been developed, and some of them have been tested clinically. However, most of the algorithms were tested in small populations. Several major clinical trials are now underway. This review aims to provide an overview of the field of warfarin which includes information about the drug, genetics of warfarin dose requirements, dosing algorithms developed and the challenges of clinical implementation of warfarin pharmacogenetics.

KEY WORDS

CYP2C9; Pharmacogenetics; VKORC1; Warfarin.

Scientific challenges and implementation barriers to translation of pharmacogenomics in clinical practice

The mapping of the human genome and subsequent advancements in genetic technology had provided clinicians and scientists an understanding of the genetic basis of altered drug pharmacokinetics and pharmacodynamics, as well as some examples of applying genomic data in clinical practice. This has raised the public expectation that predicting patients' responses to drug therapy is now possible in every therapeutic area, and personalized drug therapy would come sooner than later. However, debate continues among most stakeholders involved in drug development and clinical decision-making on whether pharmacogenomic biomarkers should be used in patient assessment, as well as when and in whom to use the biomarker-based diagnostic tests. Currently, most would agree that achieving the goal of personalized therapy remains years, if not decades, away. Realistic application of genomic findings and technologies in clinical practice and drug development require addressing multiple logistics and challenges that go beyond discovery of gene variants and/or completion of prospective controlled clinical trials. The goal of personalized medicine can only be achieved when all stakeholders in the field work together, with willingness to accept occasional paradigm change in their current approach.

Empiric evidence for a genetic contribution to predisposition to surgical site infection

The genetics of microbial pathogens have been extensively studied, but there has been little work on human genetic susceptibility to surgical site infection (SSI). We analyzed a large genealogical population database to study the familial contribution to SSI. We analyzed 651 individuals with International Classification of Disease, Ninth Revision codes indicating the presence of SSI. Matched hospital controls were randomly selected from the database based on birth year, sex, and birthplace. The average relatedness of all possible pairs of cases and separately of controls (×1000 sets) was compared empirically. The relative risk (RR) for SSI was estimated by comparing the number of observed affected individuals among the relatives of cases to the number of affected individuals observed among relatives of matched hospital controls. The genealogical index of familiality test for patients with SSI showed significant excess relatedness (p < 0.010); this excess was still observed when close relationships were ignored (p =  0.019). The RR for third-degree relatives of cases was significantly elevated (1.62, p = 0.029). The significant excess relatedness and the significantly elevated RR to distant relatives support a genetic predisposition to acquiring SSI.

The future of warfarin pharmacogenetics in under-represented minority groups

Genotype-based dosing recommendations are provided in the US FDA-approved warfarin labeling. However, data that informed these recommendations were from predominately Caucasian populations. Studies show that variants contributing to warfarin dose requirements in Caucasians provide similar contributions to dose requirements in US Hispanics, but significantly lesser contributions in African-Americans. Further data demonstrate that variants occurring commonly in individuals of African ancestry, but rarely in other racial groups, significantly influence dose requirements in African-Americans. These data suggest that it is important to consider variants specific for African-Americans when implementing genotype-guided warfarin dosing in this population.

Omics and drug response

A new generation of technologies commonly named omics permits assessment of the entirety of the components of biological systems and produces an explosion of data and a major shift in our concepts of disease. These technologies will likely shape the future of health care. One aspect of these advances is that the data generated document the uniqueness of each human being in regard to disease risk and treatment response. These developments have reemphasized the concept of personalized medicine. Here we review the impact of omics technologies on one key aspect of personalized medicine: the individual drug response. We describe how knowledge of different omics may affect treatment decisions, namely drug choice and drug dose, and how it can be used to improve clinical outcomes.

Warfarin pharmacogenetics: does more accurate dosing benefit patients?

After a decade of clinical investigation, pharmacogenetic-guided initial dosing of warfarin is at a crossroads. Genotypes for two single nucleotide polymorphisms (SNPs) in the cytochrome P 450 2C9 gene, affecting warfarin metabolism, and one SNP in vitamin K reductase complex 1 gene, affecting warfarin sensitivity, account for approximately 30% of therapeutic warfarin dosing variability in whites and Asians. Incorporating this genetic information, along with patient's age, body size, and other clinical information improves the accuracy of initial warfarin dosing. Currently, there is insufficient evidence to support the clinical benefits and cost effectiveness of routine warfarin pharmacogenetics. Results from ongoing international randomized clinical trials should provide clarity about the place of warfarin pharmacogenetics in personalized medicine.

CYP2C9 and VKORC1 polymorphisms influence warfarin dose variability in patients on long-term anticoagulation

OBJECTIVES

The main aim of this study was to determine whether CYP2C9 and VKORC1 polymorphisms influence warfarin dose variability during initial dose-finding phase and during maintenance treatment after 360 days.

METHODS

Two hundred and six consecutive patients who were beginning warfarin therapy were selected. They were assessed for general and clinical characteristics; prescribed warfarin dose; response to therapy on days 7-10, 30, 60, 180, and 360; adverse events; and CYP2C9 2, 3, 5, 6, 8, 11, and VKORC1 1639G >A assays.

RESULTS

During the first 30 days of anticoagulation, the relative variability of warfarin dose was significantly associated with CYP2C9*2 and CYP2C9*3 polymorphisms (p = 0.02) and with VKORC1 1639G >A genotypes (p = 0.04). Warfarin variability was also statistically different according to predicted metabolic phenotype and to VKORC1 genotypes after 360 days of treatment, and in the phase between 180 and 360 days (long-term dose variability). Both CYP2C9 and VKORC1 polymorphisms were associated with the international normalized ratio (INR) made between 7 and 10 days/initial dose ratio, adjusted for covariates (p < 0.01 and p = 0.02, respectively). Patients carrying VKORC1 and CYP2C9 variants presented lower required dose (at the end of follow-up of 360 days) compared to patients carrying wild-type genotypes (p = 0.04 and p = 0.03, respectively).

CONCLUSIONS

Genetic information on CYP2C9 and VKORC1 is important both for the initial dose-finding phase and during maintenance treatment with warfarin.

Validation of pharmacogenetic algorithms and warfarin dosing table in Egyptian patients

BACKGROUND

Warfarin remains a difficult drug to use due to the large variability in dose response. Clear understanding of the accuracy of warfarin pharmacogenetic dosing methods might lead to appropriate control of anticoagulation.

OBJECTIVE

This study aims to evaluate the accuracy of warfarin dosing table and two pharmacogenetic algorithms, namely the algorithms of Gage et al. (Clin Pharmacol Ther 84:326-331, 2008), and the International Warfarin Pharmacogenetics Consortium algorithm (IWPC) in a real Egyptian clinical setting. Additionally, three non-pharmacogenetic dosing methods (the Gage, IWPC clinical algorithms and the empiric 5 mg/day dosing) were evaluated.

SETTING

Sixty-three Egyptian patients on a stable therapeutic warfarin dose were included. Patients were recruited from the outpatient clinic of the critical care medicine department.

METHODS

CYP2C9 and VKORC1 polymorphisms were genotyped by real time PCR system. Predicted doses by all dosing methods were calculated and compared with the actual therapeutic warfarin doses.

RESULTS

The Gage algorithm (adjusted R(2) = 0.421, and mean absolute error (MAE) = 3.3), and IWPC algorithm (adjusted R(2) = 0.419, MAE = 3.2) produced better accuracy than did the warfarin dosing table (adjusted R(2) = 0.246, MAE = 3.5), the two clinical algorithms (R(2) = 0.24, MAE = 3.7) and the fixed dose approach (MAE = 3.9). However, all dosing models produced comparable clinical accuracy with respect to proportion of patients within 1 mg/day of actual dose (ideal dose). Non-pharmacogenetic methods severely over-predicted dose (defined as ≥2 mg/day more than actual dose) compared to the three pharmacogenetic models. In comparison to non-pharmacogenetic methods, the three pharmacogenetic models performed better regarding the low dose group in terms of percentage of patients within ideal dose. In the high dose group, none of the dosing models predicted warfarin doses within ideal dose.

CONCLUSION

Our study showed that genotype-based dosing improved prediction of warfarin therapeutic dose beyond that available with the fixed-dose approach or the clinical algorithms, especially in the low-dose group. However, the two pharmacogenetic algorithms were the most accurate.

CYP2C9 and VKORC1 polymorphisms are differently distributed in the Brazilian population according to self-declared ethnicity or genetic ancestry

BACKGROUND

Warfarin-dosing pharmacogenetic algorithms have presented different performances across ethnicities, and the impact in admixed populations is not fully known.

AIMS

To evaluate the CYP2C9 and VKORC1 polymorphisms and warfarin-predicted metabolic phenotypes according to both self-declared ethnicity and genetic ancestry in a Brazilian general population plus Amerindian groups.

METHODS

Two hundred twenty-two Amerindians (Tupinikin and Guarani) were enrolled and 1038 individuals from the Brazilian general population who were self-declared as White, Intermediate (Brown, Pardo in Portuguese), or Black. Samples of 274 Brazilian subjects from Sao Paulo were analyzed for genetic ancestry using an Affymetrix 6.0(®) genotyping platform. The CYP2C9*2 (rs1799853), CYP2C9*3 (rs1057910), and VKORC1 g.-1639G>A (rs9923231) polymorphisms were genotyped in all studied individuals.

RESULTS

The allelic frequency for the VKORC1 polymorphism was differently distributed according to self-declared ethnicity: White (50.5%), Intermediate (46.0%), Black (39.3%), Tupinikin (40.1%), and Guarani (37.3%) (p<0.001), respectively. The frequency of intermediate plus poor metabolizers (IM+PM) was higher in White (28.3%) than in Intermediate (22.7%), Black (20.5%), Tupinikin (12.9%), and Guarani (5.3%), (p<0.001). For the samples with determined ancestry, subjects carrying the GG genotype for the VKORC1 had higher African ancestry and lower European ancestry (0.14±0.02 and 0.62±0.02) than in subjects carrying AA (0.05±0.01 and 0.73±0.03) (p=0.009 and 0.03, respectively). Subjects classified as IM+PM had lower African ancestry (0.08±0.01) than extensive metabolizers (0.12±0.01) (p=0.02).

CONCLUSIONS

The CYP2C9 and VKORC1 polymorphisms are differently distributed according to self-declared ethnicity or genetic ancestry in the Brazilian general population plus Amerindians. This information is an initial step toward clinical pharmacogenetic implementation, and it could be very useful in strategic planning aiming at an individual therapeutic approach and an adverse drug effect profile prediction in an admixed population.

Semantically enabling pharmacogenomic data for the realization of personalized medicine

Understanding how each individual's genetics and physiology influences pharmaceutical response is crucial to the realization of personalized medicine and the discovery and validation of pharmacogenomic biomarkers is key to its success. However, integration of genotype and phenotype knowledge in medical information systems remains a critical challenge. The inability to easily and accurately integrate the results of biomolecular studies with patients' medical records and clinical reports prevents us from realizing the full potential of pharmacogenomic knowledge for both drug development and clinical practice. Herein, we describe approaches using Semantic Web technologies, in which pharmacogenomic knowledge relevant to drug development and medical decision support is represented in such a way that it can be efficiently accessed both by software and human experts. We suggest that this approach increases the utility of data, and that such computational technologies will become an essential part of personalized medicine, alongside diagnostics and pharmaceutical products.

Clinical Pharmacogenomics of Warfarin and Clopidogrel

Genetic polymorphisms significantly influence responses to warfarin and clopidogrel. Polymorphisms in the cytochrome P450 (CYP) 2C9 and vitamin K epoxide reductase genes change warfarin pharmacokinetics and pharmacodynamics, respectively. Because these polymorphisms influence warfarin dose requirements, they may primarily help determine therapeutic warfarin doses in patients who newly start on the drug. To assist in estimating therapeutic warfarin doses, the warfarin label provides a pharmacogenomic dosing table and various warfarin pharmacogenomic dosing algorithms are available. On the other hand, polymorphisms in the CYP2C19 gene affect clopidogrel pharmacokinetics. These polymorphisms may be useful to identify clopidogrel nonresponders who may benefit from taking an alternative antiplatelet agent such as prasugrel and ticagrelor. Although both drugs have pharmacogenomic tests available for clinical use, their clinical utilities have not been established and are currently being actively studied. In this review, clinical application of warfarin and clopidogrel pharmacogenomics will be focused. With the current level of evidence, potential patients who may get benefit from warfarin and clopidogrel pharmacogenomic testing will be discussed. In addition, the interpretation of the warfarin and clopidogrel test results and the current barriers to widespread use of warfarin and clopidogrel pharmacogenomic testing will be discussed.

Retrospective evidence for clinical validity of expanded genetic model in warfarin dose optimization in a South Indian population

Aim: To optimize warfarin dose in patients at risk for thrombotic events, we have recently developed a pharmacogenomic algorithm, which explained 44.9% of the variability in warfarin dose requirements using age, gender, BMI, vitamin K intake, CYP2C9 (*2 and *3) and VKORC1 (*3, *4 and -1639 G>A) as predictors. The aim of the current study is to develop an expanded genetic model that can explain greater percentage of warfarin variability and that has clinical validity. Patients & methods: CYP2C9*8, CYP4F2 V433M, GGCX G8016A and thyroid status were added to an expanded genetic model (n = 243). Results: The expanded genetic model explained 61% of the variability in warfarin dose requirements, has a prediction accuracy of ±11 mg/week and can differentiate warfarin sensitive and warfarin resistant groups efficiently (areas under receiver operating characteristic curves: 0.93 and 0.998, respectively; p < 0.0001). Higher percentage of International Normalized Ratios in therapeutic range (52.68 ± 4.21 vs 43.80 ± 2.27; p = 0.04) and prolonged time in therapeutic range (61.74 ± 3.18 vs 47.75 ± 5.77; p = 0.03) were observed in subjects with a prediction accuracy of <1 mg/day compared with subjects with prediction accuracy >1 mg/day. In the warfarin-resistant group, primary hypothyroidism was found to induce more resistance while in the warfarin-sensitive group, hyperthyroidism was found to increase sensitivity. Conclusion: The expanded genetic model explains greater variability in warfarin dose requirements and it prolongs time in therapeutic range and minimizes out-of-range International Normalized Ratios. Thyroid status also influences warfarin dose adjustments.

Original submitted 21 March 2012; Revision submitted 16 April 2012

A Randomized and Clinical Effectiveness Trial Comparing Two Pharmacogenetic Algorithms and Standard Care for Individualizing Warfarin Dosing (CoumaGen-II)

Background—

Warfarin is characterized by marked variations in individual dose requirements and a narrow therapeutic window. Pharmacogenetics (PG) could improve dosing efficiency and safety, but clinical trials evidence is meager.

Methods and Results—

A Randomized and Clinical Effectiveness Trial Comparing Two Pharmacogenetic Algorithms and Standard Care for Individualizing Warfarin Dosing (CoumaGen-II) comprised 2 comparisons: (1) a blinded, randomized comparison of a modified 1-step (PG-1) with a 3-step algorithm (PG-2) (N=504), and (2) a clinical effectiveness comparison of PG guidance with use of either algorithm with standard dosing in a parallel control group (N=1866). A rapid method provided same-day CYP2C9 and VKORC1 genotyping. Primary outcomes were percentage of out-of-range international normalized ratios at 1 and 3 months and percentage of time in therapeutic range. Primary analysis was modified intention to treat. In the randomized comparison, PG-2 was noninferior but not superior to PG-1 for percentage of out-of-range international normalized ratios at 1 month and 3 months and for percentage of time in therapeutic range at 3 months. However, the combined PG cohort was superior to the parallel controls (percentage of out-of-range international normalized ratios 31% versus 42% at 1 month; 30% versus 42% at 3 months; percentage of time in therapeutic range 69% versus 58%, 71% versus 59%, respectively, all P <0.001). Differences persisted after adjustment for age, sex, and clinical indication. There were fewer percentage international normalized ratios ≥4 and ≤1.5 and serious adverse events at 3 months (4.5% versus 9.4% of patients, P <0.001) with PG guidance.

Conclusions—

These findings suggest that PG dosing should be considered for broader clinical application, a proposal that is being tested further in 3 major randomized trials. The simpler 1-step PG algorithm provided equivalent results and may be preferable for clinical application.

Clinical Trial Registration—

URL: http://www.clinicaltrials.gov . Unique identifier: NCT00927862.

Role of pharmacogenomics in the management of traditional and novel oral anticoagulants

Warfarin is the most commonly prescribed oral anticoagulant. However, it remains a difficult drug to manage mostly because of its narrow therapeutic index and wide interpatient variability in anticoagulant effects. Over the past decade, there has been substantial progress in our understanding of genetic contributions to variable warfarin response, particularly with regard to warfarin dose requirements. The genes encoding for cytochrome P450 (CYP) 2C9 (CYP2C9) and vitamin K epoxide reductase complex subunit 1 (VKORC1) are the major genetic determinants of warfarin pharmacokinetics and pharmacodynamics, respectively. Numerous studies have demonstrated significant contributions of these genes to warfarin dose requirements. The CYP2C9 gene has also been associated with bleeding risk with warfarin. The CYP4F2 gene influences vitamin K availability and makes minor contributions to warfarin dose requirements. Less is known about genes influencing warfarin response in African-American patients compared with other racial groups, but this is the focus of ongoing research. Several warfarin pharmacogenetic dosing algorithms and United States Food and Drug Administration-cleared genotyping tests are available for clinical use. Clinical trials are ongoing to determine the clinical utility and cost-effectiveness of genotypeguided warfarin dosing. Results from these trials will likely influence clinical uptake and third party payer reimbursement for genotype-guided warfarin therapy. There is still a lack of pharmacogenetic data for the newly approved oral anticoagulants, dabigatran and rivaroxaban, and with other oral anticoagulants in the research and development pipeline. These data, once known, could be of great importance as routine monitoring parameters for these agents are not available.

Prediction of warfarin dose: why, when and how?

Prediction models are the key to individualized drug therapy. Warfarin is a typical example of where pharmacogenetics could help the individual patient by modeling the dose, based on clinical factors and genetic variation in CYP2C9 and VKORC1. Clinical studies aiming to show whether pharmacogenetic warfarin dose predictions are superior to conventional initiation of warfarin are now underway. This review provides a broad view over the field of warfarin pharmacogenetics from basic knowledge about the drug, how it is monitored, factors affecting dose requirement, prediction models in general and different types of prediction models for warfarin dosing.

Predicting warfarin dosage in European-Americans and African-Americans using DNA samples linked to an electronic health record

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.

Accuracy of the pharmacogenetic dosing table in the warfarin label in predicting initial therapeutic warfarin doses in a large, racially diverse cohort

STUDY OBJECTIVES

To compare the accuracy of the pharmacogenetic dosing table included in the warfarin label with two empiric dosing strategies in predicting initial therapeutic warfarin doses, and to identify factors that influence the accuracy of the table.

DESIGN

Retrospective cohort study.

DATA SOURCE

International Warfarin Pharmacogenetic Consortium database.

PATIENTS

A total of 3727 racially diverse patients receiving stable doses of warfarin who had international normalized ratios (INRs) between 2.0 and 3.0.

MEASUREMENTS AND MAIN RESULTS

Mean absolute error (MAE) and mean percentage of patients whose predicted doses were within 20% of their actual therapeutic doses (percentage within 20%) were compared between the pharmacogenetic table and two empiric dosing strategies. In the first strategy, warfarin 5 mg/day was used, and in the second strategy, dosing varied depending on the patient's race. The mean percentage of patients whose actual doses were within the ranges of the table (percentage within range) was also calculated. Warfarin dosing using the table resulted in a lower MAE (10.9 mg/wk) and a higher percentage within 20% (41.5%) than both empiric dosing strategies (MAE 12.3-12.6 mg/wk, percentage within 20% of 31.8-32.7%). In addition, using the table showed similar MAE, mean percentage within 20%, and mean percentage within range across the different racial groups. Dosing according to the table had higher mean percentage within 20% (56.4% vs 15.4%) and higher mean percentage within range (53.3% vs 19.2%) in the intermediate-dose group (> 21 but ≤ 49 mg/wk) than in the low-dose group (≤ 21 mg/wk). Being female and taking amiodarone were identified as factors that significantly increased the likelihood that the patient's predicted dose would be outside of 20% of their actual therapeutic dose or outside the range of the pharmacogenetic table.

CONCLUSION

Using the pharmacogenetic dosing table included in the warfarin label resulted in higher accuracy of dosing prediction than two empiric dosing strategies. The table had similar accuracy across racial groups and better accuracy in patients receiving an intermediate dose of warfarin. When the table is used for warfarin dosing, women and patients receiving amiodarone may require more intensive monitoring of their warfarin therapy.

Challenge of evidence in individualized medicine

Tension between standardization and individualization has always been a characteristic of medical activity. However, whether it is better that interventions should be based on guideline recommendations on the basis of large multicenter trials, or on a genetic biomarker in individualized medicine, can be the subject of debate. With the aid of stratification, evidence-based medicine and individualized medicine could be linked. Networks of large research projects, involving clinical, biomedical, molecular and other expertises are necessary for evidence-based evaluation, standardization, and clinical validation of new methods and algorithms.

Copy number variation and warfarin dosing: evaluation of CYP2C9, VKORC1, CYP4F2, GGCX and CALU

AIM

To determine if copy number variants contribute to warfarin dose requirements, we investigated CYP2C9, VKORC1, CYP4F2, GGCX and CALU for deletions and duplications in a multiethnic patient population treated with therapeutic doses of warfarin.

PATIENTS & METHODS

DNA samples from 178 patients were subjected to copy number analyses by multiplex ligation-dependent probe amplification or quantitative PCR assays. Additionally, the CYP2C9 exon 8 insertion/deletion polymorphism (rs71668942) was examined among the patient cohort and 1750 additional multiethnic healthy individuals.

RESULTS

All patients carried two copies of CYP2C9 by multiplex ligation-dependent probe amplification and no exon 8 deletion carriers were detected. Similarly, quantitative PCR assays for VKORC1, CYP4F2, GGCX and CALU identified two copies in all populations.

CONCLUSION

These data indicate that copy number variants in the principal genes involved in warfarin dose variability (CYP2C9, VKORC1), including genes with lesser effect (CYP4F2, GGCX), and those that may be more relevant among certain racial groups (CALU), are rare in multiethnic populations, including African-Americans.