A Pharmacogenetically Guided Acenocoumarol Dosing Algorithm for Chilean Patients: A Discovery Cohort Study

Area of Science:

• Pharmacogenomics
• Clinical Pharmacology
• Cardiovascular Medicine

Background:

• Vitamin K antagonists (VKAs) like warfarin and acenocoumarol are crucial for preventing thromboembolic events in cardiovascular disease patients.
• These VKAs exhibit significant inter-individual dose variability due to clinical and genetic factors, necessitating personalized dosing strategies.
• Understanding these factors is key to optimizing VKA therapy and improving patient outcomes.

Purpose of the Study:

• To develop a predictive algorithm for acenocoumarol therapeutic dosage in Chilean patients.
• To identify and quantify the contribution of clinical and pharmacogenetic variables to acenocoumarol dose variability.
• To enhance the precision of VKA dosing through a comprehensive algorithmic approach.

Main Methods:

• A discovery cohort of 304 Chilean patients with a target INR range of 2.0-3.0 was analyzed.
• DNA was genotyped for key pharmacogenetic variants including VKORC1, CYP2C9*2, CYP2C9*3, and others.
• Demographic, clinical data (age, sex, BMI, initial INR) were collected alongside genetic data.

Main Results:

• Clinical variables (age, sex, BMI, initial INR) explained 19% of the weekly VKA dose variability.
• Significant genetic contributors to variability included VKORC1 (rs9923231), CYP2C9*2 (rs1799853), and CYP2C9*3 (rs1057910), explaining an additional 37%.
• The combined algorithm accounted for approximately 50% of the total dose variability.

Conclusions:

• An algorithm integrating clinical and genetic factors was successfully developed to explain VKA dosage variability in the studied Chilean population.
• VKORC1, CYP2C9*2, and CYP2C9*3 polymorphisms, along with age, sex, BMI, and initial INR, are significant determinants of acenocoumarol dosage.
• This algorithm offers a promising tool for personalized VKA therapy, potentially improving treatment efficacy and safety.