Extrapolation of acenocoumarol pharmacogenetic algorithms

Acenocoumarol Pharmacogenetic Dosing Algorithm versus Usual Care in Patients with Venous Thromboembolism: A Randomised Clinical Trial

Patients with venous thromboembolism (VTE) require immediate treatment with anticoagulants such as acenocoumarol. This multicentre randomised clinical trial evaluated the effectiveness of a dosing pharmacogenetic algorithm versus a standard-of-care dose adjustment at the beginning of acenocoumarol treatment. We included 144 patients with VTE. On the day of recruitment, a blood sample was obtained for genotyping (CYP2C9*2, CYP2C9*3, VKORC1, CYP4F2, APOE). Dose adjustment was performed on day 3 or 4 after the start of treatment according to the assigned group and the follow-up was at 12 weeks. The principal variable was the percentage of patients with an international normalised ratio (INR) within the therapeutic range on day 7. Thirty-four (47.2%) patients had an INR within the therapeutic range at day 7 after the start of treatment in the genotype-guided group compared with 14 (21.9%) in the control group (p = 0.0023). There were no significant differences in the time to achieve a stable INR, the number of INRs within the range in the first 6 weeks and at the end of study. Our results suggest the use of a pharmacogenetic algorithm for patients with VTE could be useful in achieving target INR control in the first days of treatment.

Effect of CYP4F2, VKORC1, and CYP2C9 in Influencing Coumarin Dose: A Single-Patient Data Meta-Analysis in More Than 15,000 Individuals

The cytochrome P450 (CYP)4F2 gene is known to influence mean coumarin dose. The aim of the present study was to undertake a meta-analysis at the individual patients level to capture the possible effect of ethnicity, gene-gene interaction, or other drugs on the association and to verify if inclusion of CYP4F2*3 variant into dosing algorithms improves the prediction of mean coumarin dose. We asked the authors of our previous meta-analysis (30 articles) and of 38 new articles retrieved by a systematic review to send us individual patients' data. The final collection consists of 15,754 patients split into a derivation and validation cohort. The CYP4F2*3 polymorphism was consistently associated with an increase in mean coumarin dose (+9% (95% confidence interval (CI) 7-10%), with a higher effect in women, in patients taking acenocoumarol, and in white patients. The inclusion of the CYP4F2*3 in dosing algorithms slightly improved the prediction of stable coumarin dose. New pharmacogenetic equations potentially useful for clinical practice were derived.

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.

CYP2C9 and VKORC1 in therapeutic dosing and safety of acenocoumarol treatment: implication for clinical practice in Hungary

The purpose of this work was to investigate the contribution of CYP2C9 and VKORC1 to acenocoumarol (AC) dose variability, bleeding events in Hungary. The study recruited 117 patients on long-term AC therapy (INR 2-3), and 510 healthy individuals to model the findings. Patients were genotyped for alleles proved to affect lower AC overdose CYP2C9*2, CYP2C9*3, VKORC1*2. Additionally, we tested VKORC1*3, VKORC1*4 to examine their effect in patients with higher AC requirements. Most impact on dose reduction is accountable for CYP2C9*2/*3 (59%) and for VKORC1*2/*2 (45.5%), and on dose increase for newly evaluated VKORC1*3/*4 (22.5%) diplotypes. VKORC1*3 and *4 alleles seem to balance the dose-reducing effect of VKORC1*2 allele. Being a carrier of combination of VKORC1*2 and CYP2C9*2,*3 polymorphisms, rather than of one of these SNPs, is associated with higher risk of over-anticoagulation (up to 34.3%) in long-term AC treatment. The pharmacogenetic dosing algorithm involving VKORC1, CYP2C9 diplotypes and age explains 30.4% of AC dosing variability (p<6.10×10^-9). Correlation between the studied diplotypes and bleeding events could not be revealed.

A New Pharmacogenetic Algorithm to Predict the Most Appropriate Dosage of Acenocoumarol for Stable Anticoagulation in a Mixed Spanish Population

There is a strong association between genetic polymorphisms and the acenocoumarol dosage requirements. Genotyping the polymorphisms involved in the pharmacokinetics and pharmacodynamics of acenocoumarol before starting anticoagulant therapy would result in a better quality of life and a more efficient use of healthcare resources. The objective of this study is to develop a new algorithm that includes clinical and genetic variables to predict the most appropriate acenocoumarol dosage for stable anticoagulation in a wide range of patients. We recruited 685 patients from 2 Spanish hospitals and 1 primary healthcare center. We randomly chose 80% of the patients (n = 556), considering an equitable distribution of genotypes to form the generation cohort. The remaining 20% (n = 129) formed the validation cohort. Multiple linear regression was used to generate the algorithm using the acenocoumarol stable dosage as the dependent variable and the clinical and genotypic variables as the independent variables. The variables included in the algorithm were age, weight, amiodarone use, enzyme inducer status, international normalized ratio target range and the presence of CYP2C9*2 (rs1799853), CYP2C9*3 (rs1057910), VKORC1 (rs9923231) and CYP4F2 (rs2108622). The coefficient of determination (R2) explained by the algorithm was 52.8% in the generation cohort and 64% in the validation cohort. The following R2 values were evaluated by pathology: atrial fibrillation, 57.4%; valve replacement, 56.3%; and venous thromboembolic disease, 51.5%. When the patients were classified into 3 dosage groups according to the stable dosage (<11 mg/week, 11-21 mg/week, >21 mg/week), the percentage of correctly classified patients was higher in the intermediate group, whereas differences between pharmacogenetic and clinical algorithms increased in the extreme dosage groups. Our algorithm could improve acenocoumarol dosage selection for patients who will begin treatment with this drug, especially in extreme-dosage patients. The predictability of the pharmacogenetic algorithm did not vary significantly between diseases.