Retrospective evidence for clinical validity of expanded genetic model in warfarin dose optimization in a South Indian population.
OBJECTIVE
To optimize warfarin dose in patients at risk for thrombotic events, we have recently developed a pharmacogenomic algorithm, which explained 44.9% of the variability in warfarin dose requirements using age, gender, BMI, vitamin K intake, CYP2C9 (*2 and *3) and VKORC1 (*3, *4 and -1639 G>A) as predictors. The aim of the current study is to develop an expanded genetic model that can explain greater percentage of warfarin variability and that has clinical validity.


METHODS
CYP2C9*8, CYP4F2 V433M, GGCX G8016A and thyroid status were added to an expanded genetic model (n = 243).


RESULTS
The expanded genetic model explained 61% of the variability in warfarin dose requirements, has a prediction accuracy of ±11 mg/week and can differentiate warfarin sensitive and warfarin resistant groups efficiently (areas under receiver operating characteristic curves: 0.93 and 0.998, respectively; p < 0.0001). Higher percentage of International Normalized Ratios in therapeutic range (52.68 ± 4.21 vs 43.80 ± 2.27; p = 0.04) and prolonged time in therapeutic range (61.74 ± 3.18 vs 47.75 ± 5.77; p = 0.03) were observed in subjects with a prediction accuracy of <1 mg/day compared with subjects with prediction accuracy >1 mg/day. In the warfarin-resistant group, primary hypothyroidism was found to induce more resistance while in the warfarin-sensitive group, hyperthyroidism was found to increase sensitivity.


CONCLUSIONS
The expanded genetic model explains greater variability in warfarin dose requirements and it prolongs time in therapeutic range and minimizes out-of-range International Normalized Ratios. Thyroid status also influences warfarin dose adjustments.
Departments of Clinical Pharmacology & Therapeutics, Nizam's Institute of Medical Sciences, Hyderabad, India.
Addepalli
A
Pavani
Shaik Mohammad
SM
Naushad
Ramesh C
RC
Mishra
Amaresh Rao
AR
Malempati
Ramakrishna
R
Pinjala
Takallapally Ramesh
TR
Kumar
Vijay Kumar
VK
Kutala
D000328:Adult; D000925:Anticoagulants / Q000008:administration & dosage*; D001189:Aryl Hydrocarbon Hydroxylases / Q000097:blood / Q000235:genetics*; D054316:Biomarkers, Pharmacological / Q000097:blood; D065729:Cytochrome P-450 CYP2C9; D004305:Dose-Response Relationship, Drug; D005260:Female; D005838:Genotype; D006801:Humans; D007194:India; D019934:International Normalized Ratio; D008297:Male; D008875:Middle Aged; D006899:Mixed Function Oxygenases / Q000097:blood / Q000235:genetics*; D012372:ROC Curve; D012189:Retrospective Studies; D013923:Thromboembolism / Q000188:drug therapy* / Q000235:genetics; D014812:Vitamin K / Q000097:blood / Q000235:genetics; D064417:Vitamin K Epoxide Reductases; D014859:Warfarin / Q000008:administration & dosage*
D000925:Anticoagulants; D054316:Biomarkers, Pharmacological; D014812:Vitamin K; D014859:Warfarin; D006899:Mixed Function Oxygenases; C450260:CYP2C9 protein, human; D065729:Cytochrome P-450 CYP2C9; D001189:Aryl Hydrocarbon Hydroxylases; C578523:VKORC1 protein, human; D064417:Vitamin K Epoxide Reductases