Prospective study of warfarin dosage requirements based on CYP2C9 and VKORC1 genotypes

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.

Improved stacking ensemble learning based on feature selection to accurately predict warfarin dose

Background

With the rapid development of artificial intelligence, prediction of warfarin dose via machine learning has received more and more attention. Since the dose prediction involve both linear and nonlinear problems, traditional machine learning algorithms are ineffective to solve such problems at one time.

Objective

Based on the characteristics of clinical data of Chinese warfarin patients, an improved stacking ensemble learning can achieve higher prediction accuracy.

Methods

Information of 641 patients from southern China who had reached a steady state on warfarin was collected, including demographic information, medical history, genotype, and co-medication status. The dataset was randomly divided into a training set (90%) and a test set (10%). The predictive capability is evaluated on a new test set generated by stacking ensemble learning. Additional factors associated with warfarin dose were discovered by feature selection methods.

Results

A newly proposed heuristic-stacking ensemble learning performs better than traditional-stacking ensemble learning in key metrics such as accuracy of ideal dose (73.44%, 71.88%), mean absolute errors (0.11 mg/day, 0.13 mg/day), root mean square errors (0.18 mg/day, 0.20 mg/day) and R2 (0.87, 0.82).

Conclusions

The developed heuristic-stacking ensemble learning can satisfactorily predict warfarin dose with high accuracy. A relationship between hypertension, a history of severe preoperative embolism, and warfarin dose is found, which provides a useful reference for the warfarin dose administration in the future.

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.

Ethnic Diversity and Warfarin Pharmacogenomics

Warfarin has remained the most commonly prescribed vitamin K oral anticoagulant worldwide since its approval in 1954. Dosing challenges including having a narrow therapeutic window and a wide interpatient variability in dosing requirements have contributed to making it the most studied drug in terms of genotype-phenotype relationships. However, most of these studies have been conducted in Whites or Asians which means the current pharmacogenomics evidence-base does not reflect ethnic diversity. Due to differences in minor allele frequencies of key genetic variants, studies conducted in Whites/Asians may not be applicable to underrepresented populations such as Blacks, Hispanics/Latinos, American Indians/Alaska Natives and Native Hawaiians/other Pacific Islanders. This may exacerbate health inequalities when Whites/Asians have better anticoagulation profiles due to the existence of validated pharmacogenomic dosing algorithms which fail to perform similarly in the underrepresented populations. To examine the extent to which individual races/ethnicities are represented in the existing body of pharmacogenomic evidence, we review evidence pertaining to published pharmacogenomic dosing algorithms, including clinical utility studies, cost-effectiveness studies and clinical implementation guidelines that have been published in the warfarin field.

Predicting Range of Initial Warfarin Dose Based on Pharmacometabolomic and Genetic Inputs

Anticoagulation response to warfarin during the initial stage of therapy varies among individuals. In this study, we aimed to combine pharmacometabolomic and pharmacogenetic data to predict interindividual variation in warfarin response, and, on this basis, suggest an initial daily dose range. The baseline metabolic profiles, genotypes, and clinical information of 160 patients with heart valve disease served as the variables of the function of the last international normalized ratio measured before a patient's discharge (INR_day7 ) to screen for potential biomarkers. The partial least-squares model showed that two baseline metabolites (uridine and guanosine), one single-nucleotide variation (VKORC1), and four clinical parameters (weight, creatinine level, amiodarone usage, and initial daily dose) had good predictive power for INR_day7 (R²  = 0.753 for the training set, 0.643 for the test set). With these biomarkers, a machine learning algorithm (two-dimensional linear discriminant analysis-multinomial logit model) was used to predict the subgroups with extremely warfarin-sensitive or less warfarin-sensitive patients with a prediction accuracy of 91% for the training set and 90% for the test set, indicating that individual responses to warfarin could be effectively predicted. Based on this model, we have successfully designed an algorithm,"IniWarD," for predicting an effective dose range in the initial 7-day warfarin therapy. The results indicate that the daily dose range suggested by the IniWarD system is more appropriate than that of the conventional genotype-based method, and the risk of bleeding or thrombus due to warfarin could thus be avoided.

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

PURPOSE

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

METHODS

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

RESULTS

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

CONCLUSION

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

A post-hoc interpretable ensemble model to feature effect analysis in warfarin dose prediction for Chinese patients

To interprete the importance of clinical features and genotypes for warfarin daily dose prediction, we developed a post-hoc interpretable framework based on an ensemble predictive model. This framework includes permutation importance for global interpretation and local interpretable model-agnostic explanation (LIME) and shapley additive explanations (SHAP) for local explanation. The permutation importance globally ranks the importance of features on the whole data set. This can guide us to build a predictive model with less variables and the complexity of final predictive model can be reduced. LIME and SHAP together explain how the predictive model give the predicted dosage for specific samples. This help clinicians prescribe accurate doses to patients using more effective clinical variables. Results showed that both the permutation importance and SHAP demonstrated that VKORC1, age, serum creatinine (SCr), left atrium (LA) size, CYP2C9 and weight were the most important features on the whole data set. In specific samples, both SHAP and LIME discovered that in Chinese patients, wild-type VKORC1-AA, mutant-type CYP2C9*3, age over 60, abnormal LA size, SCr within the normal range, and using amiodarone definitely required dosage reduction, whereas mutant-type VKORC1-AG/GG, small age, SCr out of normal range, normal LA size, diabetes and heavy weight required dosage enhancement.

Competitive tight-binding inhibition of VKORC1 underlies warfarin dosage variation and antidotal efficacy

Dose control of warfarin is a major complication in anticoagulation therapy and overdose is reversed by the vitamin K antidote. Improving the dosage management and antidotal efficacy requires mechanistic understanding. Here we find that effects of the major predictor of warfarin dosage, SNP -1639 G>A, follow a general correlation that warfarin 50% inhibitory concentration decreases with cellular level of vitamin K epoxide reductase (VKORC1), suggesting stoichiometric inhibition. Characterization of the inhibition kinetics required the use of microsomal VKORC1 with a native reductant, glutathione, that enables effective warfarin inhibition in vitro. The kinetics data can be fitted with the Morrison equation, giving a nanomolar inhibition constant and demonstrating that warfarin is a tight-binding inhibitor. However, warfarin is released from purified VKORC1-warfarin complex with increasing amount of vitamin K, indicating competitive inhibition. The competition occurs also in cells, resulting in rescued VKORC1 activity that augments the antidotal effects of vitamin K. Taken together, warfarin is a competitive inhibitor that binds VKORC1 tightly and inhibits at a stoichiometric (1:1) concentration, whereas exceeding the VKORC1 level results in warfarin overdose. Thus, warfarin dosage control should use VKORC1 level as a major indicator, and improved antidotes may be designed based on their competition with warfarin.

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.

Preventing arteriovenous shunt failure in hemodialysis patients: a population-based cohort study

Essentials Uncertainty remains about antiplatelets for vascular access patency in hemodialysis patients. 95 971 people under hemodialysis were followed in a claims database in Taiwan. Aspirin reduced vascular access failure rate and did not increase major bleeding rate. Clopidogrel, Aggrenox, and warfarin might increase major bleeding rate. SUMMARY: Background Dialysis adequacy is a major determinant of survival for patients with end-stage renal disease. Good vascular access is essential to achieve adequate dialysis. Objectives This study evaluated the impacts of different drugs on the vascular access failure rate of an arteriovenous fistula or an arteriovenous graft and the rate of major bleeding in hemodialysis patients. Patients and methods We studied patients with end-stage renal disease registered in the Taiwan National Health Insurance program from 1 January 1997 to 31 December 2012. A total of 95 971 patients were enrolled in our study. Vascular access dysfunction was defined as the need for thrombectomy or percutaneous angioplasty. Major bleeding was defined as emergency department visits or hospitalization with a primary diagnosis of gastrointestinal bleeding or intracerebral hemorrhage. The adjusted odds ratios between person-quarters with or without antiplatelet or oral anticoagulant use were calculated using a generalized estimating equation. Results The odds ratio of vascular access failure was 0.21 (0.11-0.39) for aspirin, 0.76 (0.74-0.79) for clopidogrel, 0.67 (0.59-0.77) for dipyridamole, 0.67 (0.53-0.86) for Aggrenox and 0.96 (0.90-1.03) for warfarin. The highest odds ratio for intracerebral hemorrhage was 5.33 (1.25-22.72) in younger patients using Aggrenox. The highest odds ratio for gastrointestinal bleeding was 1.34 (1.10-1.64) for clopidogrel. Conclusion Antiplatelet agents, but not warfarin, might reduce the vascular access thrombosis rate. The gastrointestinal bleeding rate was increased in the group using clopidogrel. Aggrenox should be used with caution in young individuals because it might increase the rate of intracerebral hemorrhage.

Clinical and genetic factors influencing acenocoumarol dosing: a cross-sectional study

: Coumadin oral anticoagulants are widely used in multiple clinical scenarios. Their narrow therapeutic range and a dosing strategy based on 'a posteriori' algorithms, pose them as an interesting group for prediction modelling research. Extensive literature explaining the association between clinical and genetic variables with the dose of warfarin have been published. Limited information exists regarding these factors and acenocoumarol dosing. The aim of the study is to explain through clinical/genetic variables, the weekly dose of acenocoumarol necessary for achieving stable anticoagulation status. We performed a cross-sectional study enrolling adults under treatment with acenocoumarol with at least three consecutive INRs between 2 and 3. To explain the association between demographic, clinical and genotype data (VKORC1, CYP2C9 and CYP4F2) and the mean weekly dose of acenocoumarol, we performed a multiple linear regression model. In our cohort, a higher age, the presence of atrial fibrillation, chronic renal failure and VKORC1 haplotype A were associated with a lower mean weekly dose of acenocoumarol. On the other side, a higher weight was associated with a higher weekly dose. Amongst anticoagulated adult patients, VKORC1 genotype and baseline clinical factors can explain acenocoumarol dosing, and therefore, help clinicians while deciding the initial anticoagulant dose.

Effect of CYP2C9, VKORC1, CYP4F2, and GGCX gene variants and patient characteristics on acenocoumarol maintenance dose: Proposal for a dosing algorithm for Moroccan patients

We investigated the impact of non-genetics factors, and single nucleotide polymorphisms (SNPs) in VKORC1, CYP2C9, CYP4F2, and GGCX on acenocoumarol dosage in Moroccan adult's patients, in order to develop an algorithm to predict acenocoumarol dose for Moroccan patients. Our study consisted of 217 Moroccan patients taking a maintenance dose of acenocoumarol for various indications. The patients were genotyped for VKORC1 -1639 G>A, VKORC1 1173 C>T, CYP2C9*2, CYP2C9*3, CYP4F2 1347 G>A and GGCX 12970 C>G SNPs. The statistical analysis was performed using the SPSS software. The age and SNPs in VKORC1 and CYP2C9 were significantly associated with the weekly acenocoumarol dose requirement (p = 0.023, p = 0.0001 and p = 0.001 respectively). There was no association found between the weekly acenocoumarol dose and the CYP4F2 or GGCX variants (p-value > 0.05). Non-parametric analysis confirmed the accumulate effect of variant alleles at VKORC1 -1639 G>A, VKORC1 1173 C>T and CYP2C9 SNPs on the acenocoumarol dose requirement. With 90.24% less dose required for one patient carrying homozygote variant at VKORC1 -1173 (TT) and CYP2C9 *x/*x haplotype. The multiple linear regression analysis showed that mutation in VKORC1 -1639, VKORC1 1173 SNPs, or in CYP2C9 haplotype reduces the mean acenocoumarol weekly dose to 25.4%, 23.4% and 6.2%, respectively. The R2 for multiple regression analysis final model was found to be 35.9%. In this work we were able to establish the factors influencing interindividual sensitivity to the anticoagulant therapy that can help physicians to predict optimal dose requirement for long term therapy.

Effects of Ojeok-san on the Pharmacokinetics of Celecoxib at Steady-state in Healthy Volunteers

Ojeok-san is a frequently used herbal medication for the management of osteoarthritic pain. We evaluated the effect of Ojeok-san on the pharmacokinetics of celecoxib at steady-state in healthy individuals. An open-label, fixed-sequence, two-period, two-treatment cross-over study was conducted. In period I, the individuals received celecoxib capsule 200 mg once daily for 4 days. In period II, only Ojeok-san (14.47 g/pack, three times daily) was administered for 4 days, followed by co-administration with celecoxib for 4 days. On the fourth (final) day of administration, Ojeok-san was administered as a single dose. The blood samples for pharmacokinetic evaluation were collected for up to 48 hr after the administration of celecoxib in each study period. Of the 22 enrolled individuals, 20 individuals completed the study. In the presence of Ojeok-san, the systemic exposure of celecoxib was decreased. The geometric mean ratios ([celecoxib + Ojeok-san]/celecoxib) and the 90% confidence intervals for the maximum plasma concentration (C_max ) and the area under the plasma concentration-time curve during dosing interval (AUC_τ ) of celecoxib at steady-state were 0.725 (0.620-0.848) and 0.885 (0.814-0.962), respectively. The changes in the mean of the C_max and AUC_τ of celecoxib were greater in intermediate metabolizers of cytochrome 2C9 (CYP2C9) than in normal metabolizers. Our results suggested that the C_max and AUC_τ of celecoxib were reduced by Ojeok-san co-administration. This finding may be beneficial to determine the required adjustment of celecoxib dosage when co-administered with Ojeok-san.

The effect of CYP2C9*2, CYP2C9*3, and VKORC1-1639 G>A polymorphism in patients under warfarin therapy in city of Kermanshah

Polymorphism in the genes encoding CYP2C9 enzyme and VKORC1 reductase significantly influence warfarin dose requirement since patients with CYP2C9*2, CYP2C9*3 and VKORC1 mutant alleles require lower warfarin maintenance doses. Studies have reported the ethnic variations in the frequency of these genes within the various populations in Iran and other parts of the world. However, no such study has been done yet on Kurdish population in Kermanshah. From Kurdish population of Kermanshah province in Iran, a total of 110 patients who had heart surgery and taking warfarin, were genotyped for polymorphisms of VKORC1-1639 G>A, CYP2C9*2, and CYP2C9*3. Polymorphism genotyping was performed by sequencing as well as polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) using restriction enzymes of MspI, AVAII and KpnI, respectively. The frequencies of VKORC1-1639 GG, GA, and AA genotypes were 42%, 36%, and 22%, respectively and for CYP2C9 1*/1*, 1*/2*, 2*/2*, 1*/3*, 3*/3*, 2*/3* were 71%, 17%, 5.4%, 1.8%, 4.5%, and 0%, respectively. The frequency of VKORC1-1639A allele was 42.3% and the frequencies of CYP2C9*2 and *3 alleles were 14% and 5.4%, respectively. It was indicated that low warfarin dose requirements are strongly associated with the presence of CYP2C9 and VKORC1-1639 variant alleles. Our results confirmed the supply to understand the distribution of genomic biomarkers related to the drugs metabolism for future planning health programs.

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.

Verification of five pharmacogenomics-based warfarin administration models

Objective:

This study aims to screen and validate five individual warfarin dosing models (four Asian model algorithms, namely, Ohno, Wen, Miao, Huang, and the algorithm of International Warfarin Pharmacogenetic Consortium, namely IWPC algorithm) with the aim of evaluating their accuracy, practicality, and safety.

Materials and Methods:

Patients’ CYP2C9*3 and VKORC1–1639G >A genes were genotyped, and patient-related information and steady warfarin doses were recorded. The difference between the predicted dose and actual maintenance dose of each model was compared.

Results:

The prediction accuracies of the Huang and Wen models were the highest. In terms of clinical practicality, the Huang model rated the highest for the low-dose group, whereas the Ohno and IWPC models rated the highest for the middle-dose group. The models tended to markedly overpredict the doses in the low-dose group, especially the IWPC model. The Miao model tended to severely underpredict the doses in the middle-dose group, whereas no model exhibited severe overprediction.

Conclusions:

Since none of the models ranked high for all the three criteria considered, the impact of various factors should be thoroughly considered before selecting the most appropriate model for the region's population.

The Impact of Gene Polymorphisms on Anticoagulation Control With Warfarin

Differences in warfarin maintenance dosages based on the presence of polymorphisms in VKORC1, CYP2C9, CYP4F2, and ORM1 can be determined through dosage adjustment according to routine guidelines. Little is known about whether routine therapy could provide consensus anticoagulation control for patients with different genotypes. This study was carried out to compare anticoagulant control in patients with different genotypes. Six hundred seventy patients using warfarin according to Chinese guidelines were enrolled. Warfarin dosages and monitored international normalized ratios (INRs) were recorded. Genotypes of VKORC1 rs9923231, CYP4F2 rs2108622, CYP2C9 rs1057910, and ORM1 rs17650 polymorphisms were determined. Warfarin dosages and INR were compared between genotypes. Patients with the AGCC*F*F*1*1 polymorphism took longer than patients with the AACC*F*F*1*1 polymorphism (20 vs 5 days, P < .001) to achieve the targeted INR range. The INR values of patients with AACC*F*F*1*3 were unstable and did not enter the stable state control phase until after 35 days. The peak INR of patients with the AACC*F*F*1*3 polymorphism was exceedingly high, with some values exceeding the control range limit of 3.0. Patients with the AACC*F*S*1*1 or AACT*F*F*1*1 polymorphisms exhibited similar INR values as the patients with the AACC*F*F*1*1 polymorphism. This study found that routine medication with warfarin provides significantly different levels of anticoagulant control between patients with wild-type genotypes and patients with heterozygous polymorphism genotypes of VKORC1 rs9923231 or CYP2C9 rs1057910. Patients with heterozygous polymorphism genotypes of VKORC1 or CYP2C9 require genotype-directed therapy with warfarin to increase efficacy and safety in anticoagulant treatment.

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.

Pharmacogenetic dosing of warfarin in the Han-Chinese population: a randomized trial

Aim: This study aimed to determine clinical utility of genotype-guided dosing for warfarin in Han-Chinese. Methods: A total of 320 patients were randomly assigned International Warfarin Pharmacogenetic Consortium algorithm, Taiwan algorithm and optimal clinical care arms. The primary outcome of the study was the percentage of time in the therapeutic range during the first 90 days of treatment. Results: The percentage of time in the therapeutic range of the clinical care group in the first 2 weeks was significantly higher than the algorithm groups. This difference was no longer observed after 4 weeks. No difference in excessive anticoagulation (international normalized ratio ≥4.0) and adverse events was observed. Conclusion: Genotype-guided dosing did not provide significant benefit. Loading dose with frequent international normalized ratio monitoring could provide sufficient control of anticoagulation.

Warfarin Dose Model for the Prediction of Stable Maintenance Dose in Indian Patients

The main aim of this study was to screen various genetic and nongenetic factors that are known to alter warfarin response and to generate a model to predict stable warfarin maintenance dose for Indian patients. The study comprised of 300 warfarin-treated patients. Followed by extensive literature review, 10 single-nucleotide polymorphisms, that is, VKORC1-1639 G>A (rs9923231), CYP2C9*2 (rs1799853), CYP2C9*3 (rs1057910), FVII R353Q (rs6046), GGCX 12970 C>G (rs11676382), CALU c.*4A>G (rs1043550), EPHX1 c.337T>C (rs1051740), GGCX: c.214+597G>A (rs12714145), GGCX: 8016G>A (rs699664), and CYP4F2 V433M (rs2108622), and 5 nongenetic factors, that is, age, gender, smoking, alcoholism, and diet, were selected to find their association with warfarin response. The univariate analysis was carried out for 15 variables (10 genetic and 5 nongenetic). Five variables, that is, VKORC1-1639 G>A, CYP2C9*2, CYP2C9*3, age, and diet, were found to be significantly associated with warfarin response in univariate analysis. These 5 variables were entered in stepwise and multiple regression analysis to generate a prediction model for stable warfarin maintenance dose. The generated model scored R² of .67, which indicates that this model can explain 67% of warfarin dose variability. The generated model will help in prescribing more accurate warfarin maintenance dosing in Indian patients and will also help in minimizing warfarin-induced adverse drug reactions and a better quality of life in these patients.

Identification of novel variants associated with warfarin stable dosage by use of a two-stage extreme phenotype strategy

Essentials Required warfarin doses for mechanical heart valves vary greatly. A two-stage extreme phenotype design was used to identify novel warfarin dose associated mutation. We identified a group of variants significantly associated with extreme warfarin dose. Four novel identified mutations account for 2.2% of warfarin dose discrepancies.

SUMMARY

Background The variation among patients in warfarin response complicates the management of warfarin therapy, and an improper therapeutic dose usually results in serious adverse events. Objective To use a two-stage extreme phenotype strategy in order to discover novel warfarin dose-associated mutations in heart valve replacement patients. Patients/method A total of 1617 stable-dose patients were enrolled and divided randomly into two cohorts. Stage I patients were genotyped into three groups on the basis of VKORC1-1639G>A and CYP2C9*3 polymorphisms; only patients with the therapeutic dose at the upper or lower 5% of each genotype group were selected as extreme-dose patients for resequencing of the targeted regions. Evaluation of the accuracy of the sequence data and the potential value of the stage I-identified significant mutations were conducted in a validation cohort of 420 subjects. Results A group of mutations were found to be significantly associated with the extreme warfarin dose. The validation work finally identified four novel mutations, i.e. DNMT3A rs2304429 (24.74%), CYP1A1 rs3826041 (47.35%), STX1B rs72800847 (7.01%), and NQO1 rs10517 (36.11%), which independently and significantly contributed to the overall variability in the warfarin dose. After addition of these four mutations, the estimated regression equation was able to account for 56.2% (R2Adj = 0.562) of the overall variability in the warfarin maintenance dose, with a predictive accuracy of 62.4%. Conclusion Our study provides evidence linking genetic variations in STX1B, DNMT3A and CYP1A1 to warfarin maintenance dose. The newly identified mutations together account for 2.2% of warfarin dose discrepancy.

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.

Influence of VKORC1 and CYP2C9 Polymorphisms on Daily Acenocoumarol Dose Requirement in South Indian Patients With Mechanical Heart Valves

Background and Aim:

Chronic rheumatic heart disease (RHD) patients who undergo valve replacement with mechanical valves require lifelong anticoagulation. Acenocoumarol, a vitamin K antagonist has a narrow therapeutic range and wide inter-individual variability. Our aim was to investigate the influence of polymorphisms of VKORC1 and CYP2C9 genes on the mean daily dose requirement of acenocoumarol.

Methods:

205 chronic RHD patients, with mechanical heart valves and on acenocoumarol therapy, were recruited. Genotyping for VKORC1 (−1639G>A and 1173C>T) and CYP2C9 (*2 & *3 alleles) polymorphisms was done by PCR-RFLP. There was complete linkage disequilibrium between VKORC1 polymorphisms (r2 = 0.98, D′ = 1.0, LOD = 74.02). VKORC1 genotype distribution for GG/CC, GA/CT, and AA/TT were 57.6%, 36.1%, and 6.3%, respectively. CYP2C9 genotype distribution for *1/*1, *1/*3, *1/*2, *2/*2, and *2/*3 were 78.5%, 14.1%, 6.3%, 0.5%, and 0.5%, respectively. Patients with a wild type of both VKORC1 (−1639GG and 1173CC) and CYP2C9 gene variants required higher acenocoumarol dose compared to those with mutant genotype ( P = 0.023 and P = 0.008 respectively). On combined genotype analysis, patients having a combination of wild type of VKORC1 with wild type of CYP2C9 (44.4%) required higher daily dose compared to patients bearing heterozygous VKORC1 (−1639GA & 1173CT) with wild type of CYP2C9 (30.2%, P = 0.008).

Conclusion:

Presence of a mutant allele of VKORC1 (−1639A & 1173T) and CYP2C9 genes increased the odds of requiring a lower mean dosage of acenocoumarol. Studying the combination of genotypes in RHD patients could predict acenocoumarol dose requirement more accurately.

Contrasting Medical and Legal Standards of Evidence: A Precision Medicine Case Study

As the health care system transitions to a precision medicine approach that tailors clinical care to the genetic profile of the individual patient, there is a potential tension between the clinical uptake of new technologies by providers and the legal system's expectation of the standard of care in applying such technologies. We examine this tension by comparing the type of evidence that physicians and courts are likely to rely on in determining a duty to recommend pharmacogenetic testing of patients prescribed the oral anti-coagulant drug warfarin. There is a large body of inconsistent evidence and factors for and against such testing, but physicians and courts are likely to weigh this evidence differently. The potential implications for medical malpractice risk are evaluated and discussed.

The future of pharmacogenetics in the treatment of heart failure

Heart failure is a common disease with high levels of morbidity and mortality. Current treatment comprises β-blockers, ACE inhibitors, aldosterone antagonists and diuretics. Variation in clinical response seen in patients begs the question of whether there is a pharmacogenetic component yet to be identified. To date, the genes most studied involve the β-1, β-2, α-2 adrenergic receptors and the renin-angiotensin-aldosterone pathway, mainly focusing on SNPs. However results have been inconsistent. Genome-wide association studies and next-generation sequencing are seen as alternative approaches to discovering genetic variations influencing drug response. Hopefully future research will lay the foundations for genotype-led drug management in these patients with the ultimate aim of improving their clinical outcome.

Enzyme Polymorphism in Warfarin Dose Management After Pediatric Cardiac Surgery

Background:

Warfarin is an anticoagulant and is widely used for the prevention of thromboembolic events. Genetic variants of the enzymes that metabolize warfarin, i.e. cytochrome P450 2C9 (CYP2C9) and vitamin K epoxide reductase (VKORC1), contribute to differences in patients’ responses to various warfarin doses. There is, however, a dearth of data on the role of these variants during initial anticoagulation in pediatric patients.

Objectives:

We aimed to evaluate the role of genetic variants of warfarin metabolizing enzymes in anticoagulation in a pediatric population.

Patients and Methods:

In this prospective cohort study, 200 pediatric patients, who required warfarin therapy after cardiac surgery, were enrolled and divided into two groups. For 50 cases, warfarin was prescribed based on their genotyping (group 1) and for the remaining 150 cases, warfarin was prescribed based on our institute routine warfarin dosing (group 2). The study endpoints were comprised of time to reach the first therapeutic international normalization ratio (INR), time to reach a stable warfarin maintenance dose, time with over-anticoagulation, bleeding episodes, hospital stay days and stable warfarin maintenance dose.

Results:

There was no significant difference concerning the demographic data between the two groups. The time to stable warfarin maintenance dose and hospital stay days were significantly lower in group 1 (P <0.001). However, there was no statistically significant difference in time to reach the first therapeutic INR, time with over-anticoagulation and bleeding episodes, between the two groups.

Conclusions:

The determination of warfarin dose, based on genotyping, might reduce the time to achieve stable anticoagulation of warfarin dose and length of hospital stay.

Comparison of Nine Statistical Model Based Warfarin Pharmacogenetic Dosing Algorithms Using the Racially Diverse International Warfarin Pharmacogenetic Consortium Cohort Database

Objective

Multiple linear regression (MLR) and machine learning techniques in pharmacogenetic algorithm-based warfarin dosing have been reported. However, performances of these algorithms in racially diverse group have never been objectively evaluated and compared. In this literature-based study, we compared the performances of eight machine learning techniques with those of MLR in a large, racially-diverse cohort.

Methods

MLR, artificial neural network (ANN), regression tree (RT), multivariate adaptive regression splines (MARS), boosted regression tree (BRT), support vector regression (SVR), random forest regression (RFR), lasso regression (LAR) and Bayesian additive regression trees (BART) were applied in warfarin dose algorithms in a cohort from the International Warfarin Pharmacogenetics Consortium database. Covariates obtained by stepwise regression from 80% of randomly selected patients were used to develop algorithms. To compare the performances of these algorithms, the mean percentage of patients whose predicted dose fell within 20% of the actual dose (mean percentage within 20%) and the mean absolute error (MAE) were calculated in the remaining 20% of patients. The performances of these techniques in different races, as well as the dose ranges of therapeutic warfarin were compared. Robust results were obtained after 100 rounds of resampling.

Results

BART, MARS and SVR were statistically indistinguishable and significantly out performed all the other approaches in the whole cohort (MAE: 8.84–8.96 mg/week, mean percentage within 20%: 45.88%–46.35%). In the White population, MARS and BART showed higher mean percentage within 20% and lower mean MAE than those of MLR (all p values < 0.05). In the Asian population, SVR, BART, MARS and LAR performed the same as MLR. MLR and LAR optimally performed among the Black population. When patients were grouped in terms of warfarin dose range, all machine learning techniques except ANN and LAR showed significantly higher mean percentage within 20%, and lower MAE (all p values < 0.05) than MLR in the low- and high- dose ranges.

Conclusion

Overall, machine learning-based techniques, BART, MARS and SVR performed superior than MLR in warfarin pharmacogenetic dosing. Differences of algorithms’ performances exist among the races. Moreover, machine learning-based algorithms tended to perform better in the low- and high- dose ranges than MLR.

Genome-wide association study of warfarin maintenance dose in a Brazilian sample

AIM

Extreme discordant phenotype and genome-wide association (GWA) approaches were combined to explore the role of genetic variants on warfarin dose requirement in Brazilians.

METHODS

Patients receiving low (≤ 20 mg/week; n = 180) or high stable warfarin doses (≥ 42.5 mg/week; n = 187) were genotyped with Affymetrix Axiom(®) Biobank arrays. Imputation was carried out using data from the combined 1000 Genomes project.

RESULTS

Genome-wide signals (p ≤ 5 × 10(-8)) were identified in the well-known VKORC1 (lead SNP, rs749671; OR: 20.4; p = 1.08 × 10(-33)) and CYP2C9 (lead SNP, rs9332238, OR: 6.8 and p = 4.4 × 10(-13)) regions. The rs9332238 polymorphism is in virtually perfect LD with CYP2C9*2 (rs1799853) and CYP2C9*3 (rs1057910). No other genome-wide significant regions were identified in the study.

CONCLUSION

We confirmed the important role of VKORC1 and CYP2C9 polymorphisms in warfarin dose. Original submitted 14 January 2015; Revision submitted 26 May 2015.

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.

VKORC1 -1639 G>A Polymorphism in Romanian Patients With Deep Vein Thrombosis

AIM

The purpose of the research was to study the influence of several genetic factors, especially the -1693 G>A polymorphism of the VKORC1 gene, on the risk of acute unprovoked lower extremity deep vein thrombosis (DVT).

MATERIALS AND METHODS

The study included 127 patients (median age 63 [53.2; 72] years; 61 [48%] women and 66 [52%] men) who were diagnosed with acute lower extremity DVT and 114 controls (median age 62 [53; 73] years; 64 [56.1%] women and 50 [43.9%] men) without DVT. We recorded data regarding the history of DVT and the presence of varicose veins. We determined the genotypes for factor V Leiden (FVL) mutation, prothrombin G20210A mutation, VKORC1 -1639 G>A mutation, and PAI-1 -675 4G/5G polymorphism.

RESULTS AND CONCLUSION

Varicose veins were found in 67 (52.8%) patients and 29 (25.4%) controls (P < .001). FVL was present in 29 (22.8%) patients and 10 (8.8%) controls (P = .005). The VKORC1 (-1693 G>A) GG genotype was found in 42 (33.1%) patients and 41 (36%) controls, the GA genotype in 71 (55.9%) patients and 47 (41.2%) controls, and AA genotype in 14 (11%) patients and 26 (22.8%) controls (P = .020). Multivariate analysis showed that the presence of varicose veins, FVL, and VKORC1 -1639 G>A was independently associated with the risk of DVT. The VKORC1 (-1693 G>A) AA genotype was associated with fewer cases of DVT (odds ratio = 0.435; 95% confidence interval 0.205-0.991; P = .031).

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.

Prothrombotic SERPINC1 Gene Polymorphism may Affect Heparin Sensitivity Among Different Ethnicities of Chinese Patients Receiving Heart Surgery

The purpose of this study was to investigate a possible correlation between single-nucleotide polymorphisms (SNPs) of the antithrombin (gene, SERPINC1, and perioperative sensitivity to heparin in patients receiving heart surgery. The SERPINC1 genotype and allele frequency, coagulation parameters 24 hours before and after surgery, and clinical findings were compared among 3 ethnic groups, Han, Uighur, and Kazakh, patientswho received heart surgery. In Han patients, longer coagulation time as well as higher heparin and protamine dosage was observed. SERPINC1 gene sequencing identified 2 mutations in exon 5, g.981A>G (rs5877) and g.1011A>G (rs5878). The minor allele frequency of allele (A>G) for rs5877 and rs5878 was higher in the Han patients and was significantly different among the ethnic groups ( P = .004 and P = .006, respectively). The increased SERPINC1 SNP frequency among Han patients receiving heart surgery might contribute to the differences in their perioperative sensitivity to heparin.

Effect of CYP2C9-VKORC1 interaction on warfarin stable dosage and its predictive algorithm

This study aimed to identify the effect of CYP2C9-VKORC1 interaction on warfarin dosage requirement and its predictive algorithm by investigating four populations. Generalized linear model was used to evaluate the relationship between the interaction and warfarin stable dosage (WSD), whereas multiple linear regression analysis was applied to construct the WSD predictive algorithm. To evaluate the effect of CYP2C9-VKORC1 interaction on the predictive algorithms, we compared the algorithms with and without the interaction. The interaction was significantly associated with WSD in the Chinese and White cohorts (P values < 0.05). In the algorithms that considered the interaction, the predictive success rates improved by only 0.12% in the Chinese patients and by a maximum of 0.02% in the White patients under four different CYP2C9 classifications. Thus, VKORC1-CYP2C9 interaction can affect WSD. However, the discrepancy between the predictive results obtained using the predictive algorithm with and without CYP2C9-VKORC1 interaction was negligible and can therefore be disregarded.

Determinants of the over-anticoagulation response during warfarin initiation therapy in Asian patients based on population pharmacokinetic-pharmacodynamic analyses

To clarify pharmacokinetic-pharmacodynamic (PK-PD) factors associated with the over-anticoagulation response in Asians during warfarin induction therapy, population PK-PD analyses were conducted in an attempt to predict the time-courses of the plasma S-warfarin concentration, Cp(S), and coagulation and anti-coagulation (INR) responses. In 99 Chinese patients we analyzed the relationships between dose and Cp(S) to estimate the clearance of S-warfarin, CL(S), and that between Cp(S) and the normal prothrombin concentration (NPT) as a coagulation marker for estimation of IC₅₀. We also analyzed the non-linear relationship between NPT inhibition and the increase in INR to derive the non-linear index λ. Population analyses accurately predicted the time-courses of Cp(S), NPT and INR. Multivariate analysis showed that CYP2C9*3 mutation and body surface area were predictors of CL(S), that VKORC1 and CYP4F2 polymorphisms were predictors of IC₅₀, and that baseline NPT was a predictor of λ. CL(S) and λ were significantly lower in patients with INR≥4 than in those with INR<4 (190 mL/h vs 265 mL/h, P<0.01 and 3.2 vs 3.7, P<0.01, respectively). Finally, logistic regression analysis revealed that CL(S), ALT and hypertension contributed significantly to INR≥4. All these results indicate that factors associated with the reduced metabolic activity of warfarin represented by CL(S), might be critical determinants of the over-anticoagulation response during warfarin initiation in Asians.

Trial Registration

ClinicalTrials.gov NCT02065388

Pharmacogenetics role in the safety of acenocoumarol therapy

Vitamin K antagonists (VKAs) remain as the most prescribed drug for treatment and prevention of thrombotic disorders in many countries, despite the recent approval of the new oral anticoagulants (NOACs). Although effectiveness and safety of VKAs are tightly associated to maintaining the patient within the international normalised ratio (INR) therapeutic range (TWR), they have been likened to NOACs when patients are in good INR control (≥66% of TWR). Therefore, assessing the safety of patients should be a priority in the selection of the anticoagulation therapy. The aim of this study was to evaluate the association between CYP2C9*2, CYP2C9*3, VKORC1, CYP4F2*3, ABCB1 C3435T, APOE, CYP2C19*2 and CYP2C19*17 gene polymorphisms and treatment safety in 128 patients diagnosed with atrial fibrillation or venous thromboembolism during the initial first seven months of acenocoumarol therapy. After the first month, VKORC1-T-allele and APOE-E3/E3 genotype were independently associated to higher time above therapeutic range (TAR) and lower time below the therapeutic range (TBR). After seven months, VKORC1 T-allele predicted higher TAR, and was also associated to increased INR>4, particularly the TT-genotype (odds ratio [OR]: 32; 95% confidence interval [CI95%]: 6-175; p=810⁻⁵). C-alleles for CYP2C9*3 (OR: 5.5; CI95%: 1.8-17; p=0.003) and ABCB1 (OR: 8.9;CI95%: 1.1-70; p=0.039) independently influenced on INR>6 . Patients VKORC1-TT/ABCB1-C remained 26.8% [19.7-38.9] TAR, with associated relative risk (RR) for INR>4 1.8 higher (CI95%: 1.2-2.5; p=0.015). Patients VKORC1-TT also presented the highest risk of bleeding events (RR: 3.5;CI95%: 1.4-8.4; p=0,010). In conclusion, VKORC1, CYP2C9*3, APOE and ABCB1 genotypes should be considered in prevention of overanticoagulation and bleeding events in the initiation of acenocoumarol therapy.

[Cardiovascular pharmacogenomics]

Cardiovascular disease remains a major cause of morbidity and mortality worldwide. Current medical practice takes into account information based on population studies and benefits observed in large populations or cohorts. However, individual patients present great differences in both toxicity and clinical efficacy that can be explained by variations in adherence, unknown drug to drug interactions and genetic variability. The latter seems to explain from 20% up to 95% of patient to patient variability. Treating patients with cardiovascular disorders faces the clinician with the challenge to include genomic analysis into daily practice. There are several examples within cardiovascular disease of treatments that can vary in toxicity or clinical usefulness based on genetic changes. One of the main factors affecting the efficacy of Clopidogrel is the phenotype associated with polymorphisms in the gene CYP 2C9. Furthermore, regarding oral anticoagulants, changes in CYP2C9 and VKORC1 play an important role in changing the clinical response to anticoagulation. When analyzing statin treatment, one of their main toxicities (myopathy) can be predicted by the SLCO1B1 polymorphism. The potential for prediction of toxicity and clinical efficacy from the use of genetic analysis warrants further studies aiming towards its inclusion in daily clinical practice.

Analysis of CYP2C9*2, CYP2C9*3 and VKORC1 -1639 G>A polymorphisms in a population from South-Eastern Europe

The CYP2C9 enzyme metabolizes a wide range of relevant drugs, among which are oral anticoagulants. VKORC1 is the pharmacodynamic target of the oral anticoagulants. The genetic polymorphisms CYP2C9*2, CYP2C9*3 and VKORC1 -1639 G>A are the major determinants of the inter-individual variability in the dosage requirements of oral anticoagulants. This study provides a first evaluation of these 3 polymorphisms in a Romanian population. A total of 332 Romanian individuals were genotyped for the CYP2C9*2, CYP2C9*3 and VKORC1 -1639 G>A polymorphisms using the PCR-RFLP technique. Sixty-two individuals (18.7%) were heterozygous for CYP2C9*2, whereas 47 individuals (14.1%) were heterozygous for CYP2C9*3. Fourteen individuals (4.2%) had a CYP2C9*2 homozygous, CYP2C9*3 homozygous or CYP2C9*2/CYP2C9*3 compound heterozygous genotype. These individuals are predicted to have the lowest CYP2C9 enzymatic activity. The allele frequencies of the CYP2C9*2 and CYP2C9*3 polymorphisms were 11.3% and 9.3% respectively. For the VKORC1 -1639 G>A polymorphism, there were 170 heterozygotes (51.2%) and 55 (16.6%) homozygotes for the A allele. The frequency of the A allele was 42.2%. Overall, the distribution of the CYP2C9*2, CYP2C9*3 and VKORC1 -1639 G>A polymorphisms observed in our cohort is in accordance with other Caucasian populations. A large number of Romanians are expected to harbour at least one CYP2C9 variant allele and/or one VKORC1 -1639 G>A allele. This frequency has major implications in the pharmacogenomics of oral anticoagulants in Romanians.