VKORC1 –1639G>A (rs9923231) Polymorphism and Warfarin Dose Variability in Iraqi Patients with Hematological Disorders: A Pharmacogenetic Case-Control Study
Polimorfisme VKORC1 –1639G>A (rs9923231) dan Variabilitas Dosis Warfarin pada Pasien Irak dengan Gangguan Hematologi: Sebuah Studi Kasus-Kontrol Farmakogenetik
- Authors
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Esraa S. Al-Fatlawey
Department of Pathological Analysis, Faculty of Science, University of Kufa, Najaf
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- Keywords:
- Vkorc1 Polymorphism, Warfarin Dosing, Pharmacogenetics, Hematological Disorders, Iraqi Population
- Abstract
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General Background: Warfarin therapy for thrombotic hematological disorders is complicated by substantial inter-individual dose variability. Specific Background: The VKORC1 –1639G>A polymorphism is a major genetic determinant of warfarin sensitivity, yet Middle Eastern populations remain underrepresented in pharmacogenetic research. Knowledge Gap: There is limited evidence regarding VKORC1 allele distribution and its clinical relevance in Iraqi patients with hematological conditions. Aims: This study aimed to determine VKORC1 genotype frequencies and evaluate their association with warfarin dose, therapeutic control, and predictive modeling. Results: The AA genotype was associated with significantly reduced warfarin dose requirements compared to GG carriers, and VKORC1 explained 31.2% of dose variability. A multi-locus model incorporating additional genetic and clinical variables increased predictive accuracy to 61.3%. Novelty: This study provides the first comprehensive pharmacogenetic characterization of VKORC1 in an Iraqi hematological cohort, integrating cytokine gene variants into dosing models. Implications: These findings support population-specific dosing strategies and highlight the clinical relevance of genotype-guided anticoagulation in Middle Eastern healthcare settings.
Keywords: Vkorc1 Polymorphism, Warfarin Dosing, Pharmacogenetics, Hematological Disorders, Iraqi Population
Key Findings Highlights
- Genetic variation strongly differentiates dose requirements among patient groups
- Combined genetic markers substantially improve predictive modeling accuracy
- Regional allele distribution reveals distinct population-specific patterns
- References
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