A new algorithm to predict warfarin dose from polymorphisms of CYP4F2, CYP2C9 and VKORC1 and clinical variables: Derivation in Han Chinese patients with non valvular atrial fibrillation

Association between CYP2C9 and VKORC1 genetic polymorphisms and efficacy and safety of warfarin in Chinese patients

OBJECTIVES

Genetic variation has been a major contributor to interindividual variability of warfarin dosage requirement. The specific genetic factors contributing to warfarin bleeding complications are largely unknown, particularly in Chinese patients. In this study, 896 Chinese patients were enrolled to explore the effect of CYP2C9 and VKORC1 genetic variations on both the efficacy and safety of warfarin therapy.

METHODS AND RESULTS

Univariate analyses unveiled significant associations between two specific single nucleotide polymorphisms rs1057910 in CYP2C9 and rs9923231 in VKORC1 and stable warfarin dosage ( P  < 0.001). Further, employing multivariate logistic regression analysis adjusted for age, sex and height, the investigation revealed that patients harboring at least one variant allele in CYP2C9 exhibited a heightened risk of bleeding events compared to those with the wild-type genotype (odds ratio = 2.16, P  = 0.04). Moreover, a meta-analysis conducted to consolidate findings confirmed the associations of both CYP2C9 (rs1057910) and VKORC1 (rs9923231) with stable warfarin dosage. Notably, CYP2C9 variant genotypes were significantly linked to an increased risk of hemorrhagic complications ( P  < 0.00001), VKORC1 did not demonstrate a similar association.

CONCLUSION

The associations found between specific genetic variants and both stable warfarin dosage and bleeding risk might be the potential significance of gene detection in optimizing warfarin therapy for improving patient efficacy and safety.

Genetic Factors Influencing Warfarin Dose in Han Chinese Population: A Systematic Review and Meta-Analysis of Cohort Studies

OBJECTIVE

To investigate the association of single nucleotide polymorphisms (SNPs) of various genes known to influence mean daily warfarin dose (MDWD) in the Han Chinese population.

METHODS

The study is a systematic review and meta-analysis. Selected studies retrieved by searching Pubmed, Embase (Ovid), Medline, CNKI, Wanfang data, and SinoMed (from their inception to 31 August 2022) for the cohort studies assessing genetic variations that may possibly influence MDWD in Chinese patients were included.

RESULT

A total of 46 studies including a total of 10,102 Han Chinese adult patients were finally included in the meta-analysis. The impact of 20 single nucleotide polymorphisms (SNPs) in 8 genes on MDWD was analyzed. The significant impact of some of these SNPs on MDWD requirements was demonstrated. Patients with CYP4F2 rs2108622 TT, EPHX1 rs2260863 GC, or NQO1 rs1800566 TT genotype required more than 10% higher MDWD. Furthermore, patients with ABCB1 rs2032582 GT or GG, or CALU rs2290228 TT genotype required more than 10% lower MDWD. Subgroup analysis showed that patients with EPHX1 rs2260863 GC genotype required 7% lower MDWD after heart valve replacement (HVR).

CONCLUSION

This is the first systematic review and meta-analysis assessing the association between single nucleotide polymorphisms (SNPs) of various genes known to influence MDWD besides CYP2C9 and VKORC1 in the Han Chinese population. CYP4F2 (rs2108622), GGCX (rs12714145), EPHX1 (rs2292566 and rs2260863), ABCB1 (rs2032582), NQO1 (rs1800566), and CALU (rs2290228) SNPs might be moderate factors affecting MDWD requirements.

REGISTERED INFORMATION

PROSPERO International Prospective Register of Systematic Reviews (CRD42022355130).

Developing Chinese race-specific warfarin dose prediction algorithms

BACKGROUND

Numerous genotype-guided warfarin dosing algorithms have been developed to individualize warfarin doses, but they can only explain 47-52% of the variability.

AIM

This study aimed to develop new warfarin algorithms suitable to predict the stable warfarin dose for the Chinese population and to compare their prediction performance with those of the most commonly used algorithms.

METHOD

Multiple linear regression analysis with the warfarin optimal dose (WOD), logarithm (log) WOD, 1/WOD, and [Formula: see text], respectively, as the dependent variables were performed to deduce a new warfarin algorithm (NEW-Warfarin). WOD was the stable dose that maintained the international normalized ratio (INR) within the target range (2.0-3.0). Three major genotype-guided warfarin dosing algorithms were selected and compared against NEW-Warfarin predictive performance using the mean absolute error (MAE). Furthermore, patients were divided into five groups according to warfarin indications [atrial fibrillation (AF), pulmonary embolism (PE), cardiac-related disease (CRD), deep vein thrombosis (DVT), and other diseases (OD)]. Multiple linear regression analyses were also performed for each group.

RESULTS

The regression equation with [Formula: see text] as the dependent variable had the highest coefficient of determination (R² = 0.489). The NEW-Warfarin had the best predictive accuracy compared to the three algorithms selected. Group analysis, according to indications, showed that the R² of the five groups were PE (0.902) > DVT (0.608) > CRD (0.569) > OD (0.436) > AF (0.424).

CONCLUSION

Dosing algorithms based on warfarin indications are more suitable for predicting warfarin doses. Our research provides a novel strategy to develop indication-specific warfarin dosing algorithms to improve the efficacy and safety of warfarin prescribing.

Comparison of Maintenance Dose Predictions by Warfarin Dosing Algorithms Based on Chinese and Western Patients

Warfarin has a long record of safe and effective clinical use, and it remains one of the most commonly prescribed drugs for the prevention and treatment of thromboembolic conditions even in the era of direct oral anticoagulants. To address its large interindividual variability and narrow therapeutic window, the Clinical Pharmacogenetics Implementation Consortium has recommended using pharmacogenetic dosing algorithms, such as the ones developed by the International Warfarin Pharmacogenetics Consortium (IWPC) and by Gage et al, to dose warfarin when genotype information is available. In China, dosing algorithms based on local patient populations have been developed and evaluated for predictive accuracy of warfarin maintenance doses. In this study, percentage deviations of doses predicted by 15 Chinese dosing algorithms from that by IWPC and Gage algorithms were systematically evaluated to understand the differences between Chinese and Western algorithms. In general, dose predictions by Chinese dosing algorithms tended to be lower than those predicted by IWPC or Gage algorithms for the most prevalent VKORC1 and CYP2C9 genotypes in the Chinese population. The extent of negative prediction deviation appeared to be largest in the younger age group with smaller body weight. Our findings are consistent with previous reports that Asians have a higher sensitivity to warfarin and require lower doses than Western populations.

An Adapted Neural-Fuzzy Inference System Model Using Preprocessed Balance Data to Improve the Predictive Accuracy of Warfarin Maintenance Dosing in Patients After Heart Valve Replacement

BACKGROUND

Tailoring warfarin use poses a challenge for physicians and pharmacists due to its narrow therapeutic window and substantial inter-individual variability. This study aimed to create an adapted neural-fuzzy inference system (ANFIS) model using preprocessed balance data to improve the predictive accuracy of warfarin maintenance dosing in Chinese patients undergoing heart valve replacement (HVR).

METHODS

This retrospective study enrolled patients who underwent HVR between June 1, 2012, and June 1, 2016, from 35 centers in China. The primary outcomes were the mean difference between predicted warfarin dose by ANFIS models and actual dose and the models' predictive accuracy, including the ideal predicted percentage, the mean absolute error (MAE), and the mean squared error (MSE). The eligible cases were divided into training, internal validation, and external validation groups. We explored input variables by univariate analysis of a general linear model and created two ANFIS models using imbalanced and balanced training sets. We finally compared the primary outcomes between the imbalanced and balanced ANFIS models in both internal and external validation sets. Stratified analyses were conducted across warfarin doses (low, medium, and high doses).

RESULTS

A total of 15,108 patients were included and grouped as follows: 12,086 in the imbalanced training set; 2820 in the balanced training set; 1511 in the internal validation set; and 1511 in the external validation set. Eight variables were explored as predictors related to warfarin maintenance doses, and imbalanced and balanced ANFIS models with multi-fuzzy rules were developed. The results showed a low mean difference between predicted and actual doses (< 0.3 mg/d for each model) and an accurate prediction property in both the imbalanced model (ideal prediction percentage, 74.39-78.16%; MAE, 0.37 mg/daily; MSE, 0.39 mg/daily) and the balanced model (ideal prediction percentage, 73.46-75.31%; MAE, 0.42 mg/daily; MSE, 0.43 mg/daily). Compared to the imbalanced model, the balanced model had a significantly higher prediction accuracy in the low-dose (14.46% vs. 3.01%; P < 0.001) and the high-dose warfarin groups (34.71% vs. 23.14%; P = 0.047). The results from the external validation cohort confirmed this finding.

CONCLUSIONS

The ANFIS model can accurately predict the warfarin maintenance dose in patients after HVR. Through data preprocessing, the balanced model contributed to improved prediction ability in the low- and high-dose warfarin groups.

Comparison of the prediction performance of different warfarin dosing algorithms based on Chinese patients

Aim: To compare the prediction performance of different warfarin dosing algorithms based on Chinese patients. Materials & methods: A total of 18 algorithms were tested in 325 patients. The predictive efficacy of selected algorithms was evaluated by calculating the percentage of patients whose predicted dose fell within ±20% of their actual stable warfarin dose and the mean absolute error. Results: The percentage within ± 20% and the mean absolute error of the algorithms ranged from 11.9 to 41.2% and -0.20 (-0.29 to -0.11) mg/d to -1.63 (-1.75 to -1.50) mg/d. The algorithms established by Miao et al. and Wei et al. had optimal predictive performance. Conclusion: Algorithms based on geographical populations might be more suitable for the prediction of stable warfarin doses in local patients.

Genotype-Guided Dosing of Warfarin in Chinese Adults: A Multicenter Randomized Clinical Trial

BACKGROUND

Warfarin is an effective treatment for thromboembolic disease but has a narrow therapeutic index; optimal anticoagulation dosage can differ tremendously among individuals. We aimed to evaluate whether genotype-guided warfarin dosing is superior to routine clinical dosing for the outcomes of interest in Chinese patients.

METHODS

We conducted a multicenter, randomized, single-blind, parallel-controlled trial from September 2014 to April 2017 in 15 hospitals in China. Eligible patients were ≥18 years of age, with atrial fibrillation or deep vein thrombosis without previous treatment of warfarin or a bleeding disorder. Nine follow-up visits were performed during the 12-week study period. The primary outcome measure was the percentage of time in the therapeutic range of the international normalized ratio during the first 12 weeks after starting warfarin therapy.

RESULTS

A total of 660 participants were enrolled and randomly assigned to a genotype-guided dosing group or a control group under standard dosing. The genotype-guided dosing group had a significantly higher percentage of time in the therapeutic range than the control group (58.8% versus 53.2% [95% CI of group difference, 1.1-10.2]; P=0.01). The genotype-guided dosing group also achieved the target international normalized ratio sooner than the control group. In subgroup analyses, warfarin normal sensitivity group had an even higher percentage of time in the therapeutic range during the first 12 weeks compared with the control group (60.8% versus 48.9% [95% CI, 1.1-24.4]). The incidence of adverse events was low in both groups.

CONCLUSIONS

The outcomes of genotype-guided warfarin dosing were superior to those of clinical standard dosing. These findings raise the prospect of precision warfarin treatment in China. Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT02211326.

Development and Validation of a Novel Warfarin Dosing Algorithm for Korean Patients With VKORC1 1173C

BACKGROUND

Differences in the performance of suggested warfarin dosing algorithms among different ethnicities and genotypes have been reported; this necessitates the development of an algorithm with enhanced performance for specific population groups. Previous warfarin dosing algorithms underestimated warfarin doses in VKORC1 1173C carriers. We aimed to develop and validate a new warfarin dosing algorithm for Korean patients with VKORC1 1173C.

METHODS

A total of 109 patients carrying VKORC1 1173CT (N=105) or 1173CC (N=4) were included in this study. Multiple regression analysis was performed to deduce a new dosing algorithm. Following literature searches for genotype-guided warfarin dosing algorithms, 21 algorithms were selected and evaluated using the correlation coefficient (ρ) of actual dose and estimated dose, mean error, and root mean square error.

RESULTS

The developed algorithm is as follows: maintenance dose (mg/week)=exp [3.223-0.009×(age)+0.577×(body surface area [BSA])+0.178×(sex)-0.481×(CYP2C9 genotype)+0.227×(VKORC1 genotype)]. Integrated variables explained 44% of the variance in the maintenance dose. The predicted and actual doses showed moderate correlation (ρ=0.641) with the best performance with a mean error of -1.30 mg/week. The proportion of underestimated groups was 17%, which was lower than with the other algorithms.

CONCLUSIONS

This is the first study to develop and validate a warfarin dosing algorithm based on data from VKORC1 1173C carriers; it showed superior predictive performance compared with previously published algorithms.

Efficacy and Safety of Genotype-Guided Warfarin Dosing in the Chinese Population: A Meta-analysis of Randomized Controlled Trials

AIMS

To evaluate the efficacy and safety of using genetic information to guide warfarin dosing in the Chinese population.

METHODS

This meta-analysis was conducted among the published, randomized, controlled trials (RCTs) in the Chinese population comparing genotype-guided warfarin dosing (PG group) with clinical or standard warfarin dosing (STD group). RCTs published on or before January 2018 were identified using the PubMed, Embase, Cochrane Library, CNKI, Chinese VIP database, and Chinese Wanfang database.

RESULT

Intotal, 2137 participants from 14 RCTs were included in the meta-analysis. Primary analysis showed that both bleeding events [odds ratio (OR) = 0.24; 95% confidence interval (CI), 0.11-0.52; P = 0.0003] and adverse events (OR = 0.60; 95% CI, 0.43-0.83; P = 0.002) were significantly lower in the genotype-guided group than in the clinical or standard group. The percentage of patients who received a warfarin-stable therapeutic dose during follow-up was increased in the genotype-guided group compared with the percentage in the clinical or standard group (OR = 2.68; 95% CI, 1.82-3.95; P < 0.00001). In the genotype-guided group, the time to a stable therapeutic dose (mean difference = -7.98; 95% CI, -9.08 to -6.87; P < 0.00001) and the time to the first target value (mean difference = -1.87; 95% CI, -3.41 to -0.32; P = 0.02) were shortened compared with those of the clinical or standard group, but there was no difference for international normalized ratio >4, between the 2 groups (OR = 0.42; 95% CI, 0.14-1.25; P = 0.12).

CONCLUSIONS

Genotype-guided warfarin-dosing algorithms could improve the efficacy and safety of warfarin anticoagulation in the Chinese population.

Oral Anticoagulant Therapy-When Art Meets Science

Anticoagulant treatment is extremely important and frequently encountered in the therapy of various cardiovascular diseases. Vitamin K antagonists (VKA) are in use for the prevention and treatment of arterial and venous thromboembolism, despite the introduction of new direct-acting oral anticoagulants (NOAC). The VKA still have the clear recommendation in patients with a mechanical prosthetic heart valve replacement or moderate to severe mitral stenosis of the rheumatic origin, in deep vein thrombosis associated with congenital thrombophilia, and in cases where NOAC are prohibited by social condition (financial reason) or by comorbidities (extreme weight, severe renal or liver disease). VKA dosing required to reach the targeted therapeutic range varies largely between patients (inter-individual variability). This inter-individual variability depends on multiple environmental factors such as age, mass, diet, etc. but it is also influenced by genetic determinism. About 30 genes implicated in the metabolism coumarins derivatives were identified, the most important being CYP2C9 and VKORC, each with several polymorphisms. Herein, we review the data regarding genetic alterations in general and specific populations, highlight the diagnosis options in particular cases presenting with genetic alteration causing higher sensitivity and/or resistance to VKA therapy and underline the utility of NOAC in solving such rare and difficult problems.

Pharmacogenetics in the Treatment of Cardiovascular Diseases and Its Current Progress Regarding Implementation in the Clinical Routine

There is a special interest in the implementation of pharmacogenetics in clinical practice, although there are some barriers that are preventing this integration. A large part of these pharmacogenetic tests are focused on drugs used in oncology and psychiatry fields and for antiviral drugs. However, the scientific evidence is also high for other drugs used in other medical areas, for example, in cardiology. In this article, we discuss the evidence and guidelines currently available on pharmacogenetics for clopidogrel, warfarin, acenocoumarol, and simvastatin and its implementation in daily clinical practice.

Evaluation of the predictive performance of Bayesian dosing for warfarin in Chinese patients

Aim: To evaluate the accuracy and predictive performance of Bayesian dosing for warfarin in Chinese patients. Materials & methods: Six multiple linear regression algorithms (Wei, Lou, Miao, Huang, Gage and IWPC) and a Bayesian method implemented in Warfarin Dose Calculator were compared with each other. Results: Six multiple linear regression warfarin dosing algorithms had similar predictive ability, except Miao and Lou. The mean prediction error of Bayesian priori and posteriori method were 0.01 mg/day (95% CI: -0.18 to 0.19) and 0.17 mg/day (95% CI: -0.05 to 0.29), respectively, and Bayesian posteriori method demonstrated better performance in all dose ranges. Conclusion: The Bayesian method showed a good potential for warfarin maintenance dose prediction in Chinese patients requiring less than 6 mg/day.

Impact of incorporating ABCB1 and CYP4F2 polymorphisms in a pharmacogenetics-guided warfarin dosing algorithm for the Brazilian population

PURPOSE

Interpatient variation of warfarin dose requirements may be explained by genetic variations and general and clinical factors. In this scenario, diverse population-calibrated dosing algorithms, which incorporate the main warfarin dosing influencers, have been widely proposed for predicting supposed warfarin maintenance dose, in order to prevent and reduce adverse events. The aim of the present study was to evaluate the impact of the inclusion of ABCB1 c.3435C>T and CYP4F2 c.1297G>A polymorphisms as additional covariates in a previously developed pharmacogenetic-based warfarin dosing algorithm calibrated for the Brazilian population.

METHODS

Two independent cohorts of patients treated with warfarin (n = 832 and n = 133) were included for derivation and replication of the algorithm, respectively. Genotyping of ABCB1 c.3435C>T and CYP4F2 c.1297G>A polymorphisms was performed by polymerase chain reaction followed by melting curve analysis and TaqMan® assay, respectively. A multiple linear regression was performed for the warfarin stable doses as a dependent variable, considering clinical, general, and genetic data as covariates.

RESULTS

The inclusion of ABCB1 and CYP4F2 polymorphisms was able to improve the algorithm's coefficient of determination (R²) by 2.6%. In addition, the partial determination coefficients of these variants revealed that they explained 3.6% of the warfarin dose variability. We also observed a marginal improvement of the linear correlation between observed and predicted doses (from 59.7 to 61.4%).

CONCLUSION

Although our study indicates that the contribution of the combined ABCB1 and CYP4F2 genotypes in explaining the overall variability in warfarin dose is not very large, we demonstrated that these pharmacogenomic data are statistically significant. However, the clinical relevance and cost-effective impact of incorporating additional variants in warfarin dosing algorithms should be carefully evaluated.

Warfarin: The End or the End of One Size Fits All Therapy?

Oral anticoagulants are required for both treatment and prophylaxis in many different diseases. Clinicians and patients now have a choice of oral anticoagulants, including the vitamin K antagonists (of which warfarin is the most widely used and is used as the exemplar in this paper), and direct oral anticoagulants (DOACs: dabigatran, apixaban, rivaroxaban, and edoxaban). This paper explores the recent advances and controversies in oral anticoagulation. While some commentators may favour a complete switchover to DOACs, this paper argues that warfarin still has a place in therapy, and a stratified approach that enables the correct choice of both drug and dose would improve both patient outcomes and affordability.

Pharmacogenetic studies with oral anticoagulants. Genome-wide association studies in vitamin K antagonist and direct oral anticoagulants

Oral anticoagulants (OAs) are the recommended drugs to prevent cardiovascular events and recurrence in patients with atrial fibrillation (AF) and cardioembolic stroke. We conducted a literature search to review the current state of OAs pharmacogenomics, focusing on Genome Wide Association Studies (GWAs) in patients treated with vitamin K antagonists (VKAs) and direct oral anticoagulants (DOACs).

VKAs: Warfarin, acenocoumarol, fluindione and phenprocoumon have long been used, but their interindividual variability and narrow therapeutic/safety ratio makes their dosage difficult. GWAs have been useful in finding genetic variants associated with VKAs response. The main genes involved in VKAs pharmacogenetics are: VKORC1, CYP2C19 and CYP4F2. Variants in these genes have been included in pharmacogenetic algorithms to predict the VKAs dose individually in each patient depending on their genotype and clinical variables.

DOACs: Dabigatran, apixaban, rivaroxaban and edoxaban have been approved for patients with AF. They have stable pharmacokinetics and do not require routine blood checks, thus avoiding most of the drawbacks of VKAs. Except for a GWAs performed in patients treated with dabigatran, there is no Genome Wide pharmacogenomics data for DOACs. Pharmacogenomics could be useful to predict the better clinical response and avoid adverse events in patients treated with anticoagulants, identifying the most appropriate anticoagulant drug for each patient. Current pharmacogenomics data show that the polymorphisms affecting VKAs or DOACs are different, concluding that personalized medicine based on pharmacogenomics could be possible. However, more studies are required to implement personalized medicine in clinical practice with OA and based on pharmacogenetics of DOACs.

Association Between ABCB1 Polymorphism and Stable Warfarin Dose Requirements in Brazilian Patients

The ideal dose of the oral anticoagulant warfarin varies widely among patients, mainly due to genetic factors. Genetic variations that impact warfarin pharmacokinetics and the vitamin K cycle are plausible candidates for being associated with warfarin dose requirements. Therefore, the aim of this study was to assess whether polymorphisms in the ABCB1 and CYP4F2 genes were associated with stable warfarin dose requirements in Brazilian patients. This retrospective study included samples from 309 individuals. Genotyping of ABCB1 c.3435C>T and CYP4F2 c.1297G>A were performed by polymerase chain reaction followed by melting curve analysis (HRM-PCR) and TaqMan® genotyping assay, respectively. Stable doses were adjusted in a linear multiple regression model for age, gender, body mass index, self-reported race, use of amiodarone, CYP2C9 (^*2 and ^*3), VKORC1 c.1639G>A, and ABCB1 c.3435C>T or CYP4F2 c.1297G>A. By performing a univariate analysis of variance, we found that the warfarin patients who carry ABCB1 c.3435T variant alleles (CT and TT genotypes) need fewer warfarin stable doses in comparison with the individuals that are CC wild-type: 2.5 (p = 0.003) and 4.3 (p < 0.001) mg/week less, respectively, for the overall group of patients on stable anticoagulation therapeutics (n = 309); and 5.5 (p = 0.006) and 10.2 (p < 0.001) mg/week less, respectively, for the self-declared non-white stable subgroup (n = 76). No statistically significant differences in dose requirements were observed according to CYP4F2 genotypes. In conclusion, our results suggest ABCB1 c.3435C>T variant may influence warfarin dose requirements in Brazilian patients, when associated with other genotypic, demographic and clinical factors.

Genotype-guided warfarin therapy: current status

Warfarin pharmacogenomics has been an extensively studied field in the last decades as it is focused on personalized therapy to overcome the wide interpatient warfarin response variability and decrease the risk of side effects. In this expert review, besides briefly summarizing the current knowledge about warfarin pharmacogenetics, we also present an overview of recent studies that aimed to assess the efficacy, safety and economic issues related to genotype-based dosing algorithms used to guide warfarin therapy, including randomized and controlled clinical trials, meta-analyses and cost-effectiveness studies. To date, the findings still present disparities, mostly because of standard limitations. Thus, further studies should be encouraged to try to demonstrate the benefits of the application of warfarin pharmacogenomic dosing algorithms in clinical practice.

The Influence of CYP2C9 and VKORC1 Gene Polymorphisms on the Response to Warfarin in Egyptians

Warfarin is the most commonly used drug for chronic prevention of thromboembolic events, it also ranks high among drugs that cause serious adverse events. The variability in dose requirements has been attributed to inter-individual differences in medical, personal, and genetic factor. Cytochrome P-450 2C9 is the principle enzyme that terminates the anticoagulant effect of warfarin by catalyzing the conversion of the pharmacologically more potent S-enantiomer to its inactive metabolites. Warfarin exerts its effect by inhibition of vitamin K epoxide reductase. This protein is encoded by vitamin K epoxide reductase complex subunit 1 gene (VKORC1). The current study aimed to investigate the pharmacogenetic effect of CYP2C9 and VKORC1 gene polymorphisms on the patients response to warfarin. One hundred cases starting warfarin treatment and 20 healthy controls were enrolled. The mean daily dose of warfarin was calculated from patient's medical records. For each patient, less than 10 % variability in warfarin dose and a target international normalized ratio (INR) within the therapeutic target range were required for at least 3 months for one of the following indications (deep vein thrombosis, pulmonary embolism, cerebrovascular stroke and myocardial infarction) prior to inclusion in the study. Tetraprimer amplification refractory mutation system PCR was performed to determine CYP2C9*2, CYP2C9*3, and the VKORC1 1639 G > A genetic polymorphisms. Plasma warfarin determination was performed using rapid fluorometric assay. Plasma warfarin concentration ranged from 2.19 to 10.98 μg/ml with a median 3.52 μg/ml. Supratherpeutic INR was observed in 11 % of the cases. Thromboembolic complications occurred in 7 % of the cases and 8 % of cases experienced major bleeding. High maintenance dose (>7 mg/day) was associated with the combined non VKORC1*2 and homozygous wild type CYP2C9 (CYP2C9*1*1) alleles, while low maintenance dose was associated with the Variant (AG + AA)/Wild (*1/*1). (p value <0.001). CYP2C9 variant was a risk factor for supratherapeutic INR in the multivariate logistic regression model. Thromboembolic complication and incidence of supratherapeutic INR were observed in patients carrying combined VKORC1 Variant (AG + AA) and CYP2C9 Variant (*2/*3). Data from our study suggest that together with clinical factors, VKORC1 and CYP2C9 polymorphisms are important contributors to warfarin dosing and may help predict adverse effects in Egyptian patients.

Pharmacogenomics of CYP2C9: Functional and Clinical Considerations

CYP2C9 is the most abundant CYP2C subfamily enzyme in human liver and the most important contributor from this subfamily to drug metabolism. Polymorphisms resulting in decreased enzyme activity are common in the CYP2C9 gene and this, combined with narrow therapeutic indices for several key drug substrates, results in some important issues relating to drug safety and efficacy. CYP2C9 substrate selectivity is detailed and, based on crystal structures for the enzyme, we describe how CYP2C9 catalyzes these reactions. Factors relevant to clinical response to CYP2C9 substrates including inhibition, induction and genetic polymorphism are discussed in detail. In particular, we consider the issue of ethnic variation in pattern and frequency of genetic polymorphisms and clinical implications. Warfarin is the most well studied CYP2C9 substrate; recent work on use of dosing algorithms that include CYP2C9 genotype to improve patient safety during initiation of warfarin dosing are reviewed and prospects for their clinical implementation considered. Finally, we discuss a novel approach to cataloging the functional capabilities of rare 'variants of uncertain significance', which are increasingly detected as more exome and genome sequencing of diverse populations is conducted.

Estimation of the warfarin dose with a pharmacogenetic refinement algorithm in Chinese patients mainly under low-intensity warfarin anticoagulation

Pharmacogenetic (PG) dosing algorithms have been confirmed to predict warfarin therapeutic dose more accurately;however, most of them are based on standard intensity of warfarin anticoagulation, and their utility outside this range is limited. This study was designed to develop and validate a PG refinement algorithm in Chinese patients mainly under low-intensity warfarin anticoagulation. Consented Chinese-Han patients (n=310) under stable warfarin treatment were randomly divided into a derivation (n=207) and a validation cohort (n=103), with 83% and 80% of the patients under low-intensity anticoagulation, respectively. In the derivation cohort, a PG algorithm was constructed on the basis of genotypes (CYP2C9*3 and VKORC1–1639A/G) and clinical data. After integrating additional covariates of international normalised ratio (INR) values (INR on day 4 of therapy and target INR) and genotype of CYP4F2 (rs2108622), a PG refinement algorithm was established and explained 54% of warfarin dose variability. In the validation cohort, warfarin dose prediction was more accurate (p <0.01) with the PG refinement algorithm than with the PG algorithm and the fixed dose approach (3 mg/day). In the entire cohort, the PG refinement algorithm could accurately identify larger proportions of patients with lower dose requirement (≤2 mg/day) and higher dose requirement (≥4 mg/day) than did the PG algorithm. In conclusion, PG refinement algorithm integrating early INR response and three genotypes CYP2C9*3, VKORC1–1639A/G, CYP4F2 rs2108622) improves the accuracy of warfarin dose prediction in Chinese patients mainly under low-intensity anticoagulation.

Creating a genotype-based dosing algorithm for acenocoumarol steady dose

Acenocoumarol is a commonly prescribed anticoagulant drug for the prophylaxis and treatment of venous and arterial thromboembolic disorders in several countries. In counterpart of warfarin, there is scarce information about pharmacogenetic algorithms for steady acenocoumarol dose estimation. The aim of this study was to develop an algorithm of prediction for acenocoumarol.The algorithm was created using the data from 973 retrospectively selected anticoagulated patients and was validated in a second independent cohort adding up to 2,683 patients. The best regression model to predict stable dosage in the Primary Cohort included clinical factors (age and body mass index, BSA) and genetic variants (VKORC1, CYP2C9* and CYP4F2 polymorphisms) and explained up to 50% of stable dose. In the validation study the clinical algorithm yielded an adjusted R2=0.15 (estimation´s standard error=4.5) and the genetic approach improved the dose forecast up to 30% (estimation´s standard error=4.6). Again, the best model combined clinical and genetic factors (R2= 0.48; estimation´s standard error=4) which provided the best results of doses estimates within 20% of the real dose in patients taking lower (≤7mg/week) or higher (≥25mg/week) acenocoumarol doses. In conclusion, we developed a prediction algorithm using clinical data and three polymorphisms in VKORC1, CYP2C9* and CYP4F2 genes that provided a steady acenocoumarol dose for about 50% of patients in the Validation Cohort. Such algorithm was especially useful to patients who need higher or lower acenocoumarol doses, those patients with higher time required until their stabilisation and are more prone to suffer a treatment derived complication.

Development of a novel individualized warfarin dose algorithm based on a population pharmacokinetic model with improved prediction accuracy for Chinese patients after heart valve replacement

The gene-guided dosing strategy of warfarin generally leads to over-dose in patients at doses lower than 2 mg/kg, and only 50% of individual variability in daily stable doses can be explained. In this study, we developed a novel population pharmacokinetic (PK) model based on a warfarin dose algorithm for Han Chinese patients with valve replacement for improving the dose prediction accuracy, especially in patients with low doses. The individual pharmacokinetic (PK) parameter - apparent clearance of S- and R-warfarin (CLs) was obtained after establishing and validating the population PK model from 296 recruited patients with valve replacement. Then, the individual estimation of CLs, VKORC1 genotypes, the steady-state international normalized ratio (INR) values and age were used to describe the maintenance doses by multiple linear regression for 144 steady-state patients. The newly established dosing algorithm was then validated in an independent group of 42 patients and was compared with other dosing algorithms for the accuracy and precision of prediction. The final regression model developed was as follows: Dose=-0.023×AGE+1.834×VKORC1+0.952×INR+2.156×CLs (the target INR value ranges from 1.8 to 2.5). The validation of the algorithm in another group of 42 patients showed that the individual variation rate (71.6%) was higher than in the gene-guided dosing models. The over-estimation rate in patients with low doses (<2 mg/kg) was lower than the other dosing methods. This novel dosing algorithm based on a population PK model improves the predictive performance of the maintenance dose of warfarin, especially for low dose (<2 mg/d) patients.

Clinical and genetic factors associated with warfarin maintenance dose in northern Chinese patients with mechanical heart valve replacement

The effects of genetic variants on warfarin dosing vary among different ethnic groups, especially in the Chinese population. The objective of this study was to recruit patients through a rigorous experimental design and to perform a comprehensive screen to identify gene polymorphisms that may influence warfarin dosing in northern Han Chinese patients with mechanical heart valve replacement. Consenting patients (n = 183) with a stable warfarin dose were included in this study. Ninety-six single nucleotide polymorphisms (SNPs) in 30 genes involved in warfarin pharmacological pathways were genotyped using the Illumina SNP GoldenGate Assay, and their associations with warfarin dosing were assessed using univariate regression analysis with post hoc comparison using least significant difference analysis. Multiple linear regression was performed by incorporating patients' clinical and genetic data to create a new algorithm for warfarin dosing. From the 96 SNPs analyzed, VKORC1 rs9923231, CYP1A2 rs2069514, CYP3A4 rs28371759, and APOE rs7412 were associated with higher average warfarin maintenance doses, whereas CYP2C9 rs1057910, EPHX1 rs2260863, and CYP4F2 rs2189784 were associated with lower warfarin doses (P < 0.05). Multiple linear regression analysis could estimate 44.4% of warfarin dose variability consisting of, in decreasing order, VKORC1 rs9923231 (14.2%), CYP2C9*3 (9.6%), body surface area (6.7%), CYP1A2 rs2069514 (3.7%), age (2.7%), CYP3A4 rs28371759 (2.5%), CYP4F2 rs2108622 (1.9%), APOE rs7412 (1.7%), and VKORC1 rs2884737 (1.4%). In the dosing algorithm we developed, we confirmed the strongest effects of VKORC1, CYP2C9 on warfarin dosing. In the limited sample set, we also found that novel genetic predictors (CYP1A2, CYP3A4, APOE, EPHX1, CYP4F2, and VKORC1 rs2884737) may be associated with warfarin dosing. Further validation is needed to assess our results in larger independent northern Chinese samples.

Development of neuro-fuzzy model to explore gene-nutrient interactions modulating warfarin dose requirement

AIM

To investigate the influence of alterations in vitamin K (K1, K2 and K3) in modulating warfarin dose requirement.

PATIENTS & METHODS

Reverse phase HPLC to determine the plasma vitamin K; PCR-RFLP to detect polymorphisms; and the neuro-fuzzy model to predict warfarin dose were used.

RESULTS

The developed neuro-fuzzy model showed a mean absolute error of 0.000024 mg/week. CYP2C9*2 and CYP2C9*3 mediated warfarin sensitivity was observed when vitamin K is in high and low tertiles, respectively. VKORC1-1639G>A exhibited warfarin sensitivity in all combinations. Higher vitamin K1 was observed in CYP4F2 V433M polymorphism. The requirement of warfarin is low in GGCX 8016 GG genotype compared with GA and AA genotypes.

CONCLUSION

Vitamin K profile along with genetic testing ensures precision in warfarin dose optimization.

Impact of CYP2C9, VKORC1 and CYP4F2 genetic polymorphisms on maintenance warfarin dosage in Han-Chinese patients: A systematic review and meta-analysis

Introduction

Warfarin is the most commonly used antithrombotic drug. Single nucleotide polymorphisms (SNPs) of CYP2C9, CYP4F2, VKORC1 1173 and VKORC1-1639 influence warfarin maintenance dosage. We aimed to determine the impact of SNPs of these genes on mean daily warfarin dosage (MDWD) in Han-Chinese patients.

Methods

Strict literature inclusion criteria were established, and literature searching was performed on PubMed, Embase and Cochrane Library for English articles and CNKI, CBM and Wanfang database for Chinese articles before September 2, 2014. Revman 5.3 was used to analyze the relationship between gene SNPs and MDWD in Han-Chinese subjects.

Results

We included 33 studies researching the impact of gene SNPs on MDWD in Han-Chinese subjects. CYP2C9 *3/*3, *1/*3 and *3 carriers needed a 72% (95% confidence interval [CI]: 62.0%–81.0%), 28% (22.0%–33.0%) and 26% (21.0%–32.0%) lower MDWD, respectively, than CYP2C9 *1/*1 carriers. CYP4F2 TT, CT and T carriers required a 18% (7.0%–30.0%), 7% (7.0%–7.0%) and 11% (7.0%–14.0%) higher MDWD, respectively, than CYP4F2 CC carriers. VKORC1 1173 CC, CT and C carriers required a 98% (78.0%–118.0%), 49% (37.0%–62.0%) and 56% (44.0%–67.0%) higher MDWD, respectively, than VKORC1 1173 TT carriers. VKORC1-1639 GG, GA and G carriers needed a 101% (53.0%–149.0%), 40% (36.0%–45.0%) and 38% (35.0%–42.0%) higher MDWD, respectively, than VKORC1-1639 AA carriers.

Conclusions

This meta-analysis is the first to report the relationship between genotypes and MDWD among Han-Chinese patients. The results showed that SNPs of CYP2C9, CYP4F2, VKORC1 1173 and VKORC1-1639 significantly influenced the MDWD in Han-Chinese patients.

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This meta-analysis examined the effects of genotype on mean daily warfarin dosage.

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CYP2C9, CYP4F2 and VKORC1 genotypes were studied in Han-Chinese patients.

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CYP2C9, CYP4F2, VKORC1-1173 and VKORC1-1639 polymorphisms affected warfarin dosage.

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VKORC1-1173 C and VKORC1-1639 G mutations had similar frequencies and effects.

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Either genotype can be tested for to guide drug usage and lower medical costs.

Acenocoumarol Pharmacogenetic Dosing Algorithms and Their Application in Two Bulgarian Patients with Low Anticoagulant Requirements

BACKGROUND

The anticoagulant therapy with acenocoumarol is generally associated with a high risk of bleeding and thromboembolic events.

PURPOSE

We applied eight already existing acenocoumarol dosing algorithms to Bulgarian patients with low acenocoumarol dose requirements and investigated which of these algorithms would predict most precisely the dose anticoagulant.

MATERIALS AND METHODS

Two patients with Bulgarian origin were referred to the outpatient clinical laboratory of "St. Ekaterina" University Hospital for Cardiovascular Surgery and Cardiology, Sofia, Bulgaria. After obtaining written informed consent, both patients were genotyped for polymorphisms in genes for Cytochrome P450 2C9 (CYP2C9), Vitamin K epoxide reductase (VKORC1), Apolipoprotein E (APOE), and Cytochrome P450 4F2 (CYP4F2).

RESULTS

All applied acenocoumarol dosing algorithms predicted relatively similar doses of coumarin anticoagulant in both patients. However, van Schie et al.'s algorithm allowed more accurate calculation of the optimal dose in our patients with extremely low acenocoumarol requirements. Genotyping of selected polymorphic variants in CYP2C9 and VKORC1 showed that both patients were compound heterozygotes for CYP2C9 (CYP2C9*2/*3) and homozygotes for both variants in VKORC1 (VKORC1 1173 T/T, and VKORC1-1639 A/A). This combination of genotypes suggested high sensitivity to acenocoumarol leading to the low anticoagulant dose requirements (0.25 and 1 mg/day, respectively) needed to reach the target International Normalized Ratio of 2.5-3.5.

CONCLUSIONS

The genotyping of polymorphic variants in VKORC1 and CYP2C9, together with clinical and demographic parameters, can serve for more precise definition of the individual starting and maintenance doses of coumarin derivatives in each patient.

Validation of warfarin pharmacogenetic algorithms in 586 Han Chinese patients

AIM

To compare the accuracy of the nine selected algorithms for predicting warfarin dose with 586 Han Chinese patients.

MATERIALS & METHODS

Genotyping of VKORC1 1639G>A, CYP2C9*2 and CYP2C9*3 variants was performed. Both the mean absolute error and ideal estimation value were used for comparison.

RESULTS

The top three performers were from East Asians. The algorithms from Caucasians generally performed better in the medium-dose subgroup (>3 and <7 mg/day), while the algorithms from East Asians generally performed better in the low-dose subgroup (≤ 3 mg/day). None of the algorithms performed well in the high-dose subgroup (≥ 7 mg/day).

CONCLUSION

Algorithms built for specific ethnic groups and preassigned-dose groups are suggested for better prediction.

Development of a pharmacogenetic-based warfarin dosing algorithm and its performance in Brazilian patients: highlighting the importance of population-specific calibration

BACKGROUND

The main aims of the present study were to develop a pharmacogenetic-based warfarin dosing algorithm and to validate it in a highly admixed population.

MATERIALS & METHODS

We included two patient cohorts treated with warfarin (first cohort, n = 832; and second cohort, n = 133).

RESULTS

Our algorithm achieved a determination coefficient of 40% including the variables age, gender, weight, height, self-declared race, amiodarone use, enzyme inducers use, VKORC1 genotypes and predicted phenotypes according to CYP2C9 polymorphisms.

CONCLUSION

Data suggest that our developed algorithm is more accurate than the IWPC algorithm when the application is focused on patients from the Brazilian population. Population-specific derivation and/or calibration of warfarin dosing algorithms may lead to improved performance compared with general use dosing algorithms currently available. Original submitted 26 November 2014; Revision submitted 9 April 2015.

Pharmacogenetic-guided dosing of coumarin anticoagulants: algorithms for warfarin, acenocoumarol and phenprocoumon

Coumarin derivatives, such as warfarin, acenocoumarol and phenprocoumon are frequently prescribed oral anticoagulants to treat and prevent thromboembolism. Because there is a large inter-individual and intra-individual variability in dose-response and a small therapeutic window, treatment with coumarin derivatives is challenging. Certain polymorphisms in CYP2C9 and VKORC1 are associated with lower dose requirements and a higher risk of bleeding. In this review we describe the use of different coumarin derivatives, pharmacokinetic characteristics of these drugs and differences amongst the coumarins. We also describe the current clinical challenges and the role of pharmacogenetic factors. These genetic factors are used to develop dosing algorithms and can be used to predict the right coumarin dose. The effectiveness of this new dosing strategy is currently being investigated in clinical trials.

A pharmacogenetics-based warfarin maintenance dosing algorithm from Northern Chinese patients

Inconsistent associations with warfarin dose were observed in genetic variants except VKORC1 haplotype and CYP2C9*3 in Chinese people, and few studies on warfarin dose algorithm was performed in a large Chinese Han population lived in Northern China. Of 787 consenting patients with heart-valve replacements who were receiving long-term warfarin maintenance therapy, 20 related Single nucleotide polymorphisms were genotyped. Only VKORC1 and CYP2C9 SNPs were observed to be significantly associated with warfarin dose. In the derivation cohort (n = 551), warfarin dose variability was influenced, in decreasing order, by VKORC1 rs7294 (27.3%), CYP2C9*3(7.0%), body surface area(4.2%), age(2.7%), target INR(1.4%), CYP4F2 rs2108622 (0.7%), amiodarone use(0.6%), diabetes mellitus(0.6%), and digoxin use(0.5%), which account for 45.1% of the warfarin dose variability. In the validation cohort (n = 236), the actual maintenance dose was significantly correlated with predicted dose (r = 0.609, P<0.001). Our algorithm could improve the personalized management of warfarin use in Northern Chinese patients.

Verification of pharmacogenetics-based warfarin dosing algorithms in Han-Chinese patients undertaking mechanic heart valve replacement

OBJECTIVE

To study the performance of pharmacogenetics-based warfarin dosing algorithms in the initial and the stable warfarin treatment phases in a cohort of Han-Chinese patients undertaking mechanic heart valve replacement.

METHODS

We searched PubMed, Chinese National Knowledge Infrastructure and Wanfang databases for selecting pharmacogenetics-based warfarin dosing models. Patients with mechanic heart valve replacement were consecutively recruited between March 2012 and July 2012. The predicted warfarin dose of each patient was calculated and compared with the observed initial and stable warfarin doses. The percentage of patients whose predicted dose fell within 20% of their actual therapeutic dose (percentage within 20%), and the mean absolute error (MAE) were utilized to evaluate the predictive accuracy of all the selected algorithms.

RESULTS

A total of 8 algorithms including Du, Huang, Miao, Wei, Zhang, Lou, Gage, and International Warfarin Pharmacogenetics Consortium (IWPC) model, were tested in 181 patients. The MAE of the Gage, IWPC and 6 Han-Chinese pharmacogenetics-based warfarin dosing algorithms was less than 0.6 mg/day in accuracy and the percentage within 20% exceeded 45% in all of the selected models in both the initial and the stable treatment stages. When patients were stratified according to the warfarin dose range, all of the equations demonstrated better performance in the ideal-dose range (1.88-4.38 mg/day) than the low-dose range (<1.88 mg/day). Among the 8 algorithms compared, the algorithms of Wei, Huang, and Miao showed a lower MAE and higher percentage within 20% in both the initial and the stable warfarin dose prediction and in the low-dose and the ideal-dose ranges.

CONCLUSIONS

All of the selected pharmacogenetics-based warfarin dosing regimens performed similarly in our cohort. However, the algorithms of Wei, Huang, and Miao showed a better potential for warfarin prediction in the initial and the stable treatment phases in Han-Chinese patients undertaking mechanic heart valve replacement.

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.

Optimal dosing of warfarin and other coumarin anticoagulants: the role of genetic polymorphisms

Coumarin anticoagulants, which include warfarin, acenocoumarol and phenprocoumon, are among the most widely prescribed drugs worldwide. There is now a large body of published data showing that genotype for certain common polymorphisms in the genes encoding the target vitamin K epoxide reductase (G-1639A/C1173T) and the main metabolizing enzyme CYP2C9 (CYP2C9*2 and *3 alleles) are important determinants of the individual coumarin anticoagulant dose requirement. Additional less common polymorphisms in these genes together with polymorphisms in other genes relevant to blood coagulation such as the cytochrome P450 CYP4F2, gamma-glutamyl carboxylase, calumenin and cytochrome P450 oxidoreductase may also be significant predictors of dose, especially in ethnic groups such as Africans where there have been fewer genetic studies compared with European populations. Using relevant genotypes to calculate starting dose may improve safety during the initiation period. Various algorithms for dose calculation, which also take patient age and other characteristics into consideration, have been developed for all three widely used coumarin anticoagulants and are now being tested in ongoing large randomised clinical trials. One recently completed study has provided encouraging results suggesting that calculation of warfarin dose on the basis of individual patient genotype leads to few adverse events and a higher proportion of time within the therapeutic coagulation rate window, but these findings still need confirmation.