INTRODUCTION: Warfarin is an anticoagulant that is difficult to administer because of its narrow therapeutic margin and the numerous factors that influence patient response. OBJECTIVE: Demographic, clinical and genetic variables were characterized to establish the appropriate maintenance dosages of warfarin. MATERIALS AND METHODS: The Colombian patients consisted of 145 adults of both sexes. They were in stable anticoagulation status with international normalized ratio between 2 and 3 for at least two months, and without changes in the warfarin commercial preparation or in the dosage. After signing the informed consent, the following data was recorded for each volunteer: age, gender, weight, height, smoker status, co-morbidity, co-medication, International Normalized Ratio (INR), warfarin dose, and commercial brand. Each patient was typed for genes CYP2C9, VKORC1, CYP4F2 and PROC; for 59 patients, the serum levels of warfarin were quantified. The genotyping and the blood quantification were performed by mini-sequencing and HPLC methods, respectively. RESULTS: Age, co-medication with enzymatic inhibitors (amiodarone, sertraline, fluoxetine) or inducers (phenytoin, carbamazepine), and the alleles rs1799853 (*2) and rs1057910 (*3) of the CYP2C9 gene, as well as rs9923231 of the VKORC1 gene were associated with warfarin dose required to achieve anticoagulation with INR of 2-3. These variables were included in a multiple linear regression model for predicting the optimum dose/week of warfarin. This resulted in an algorithm that explained 47.4% of the variability in the dose responses. CONCLUSION: Clinical and pharmacogenetic variables provided a basis for improving the safety and effective dosage of warfarin; however, the use of a pharmacogenetic algorithm will require patient data obtained during clinical trials.
INTRODUCTION:Warfarin is an anticoagulant that is difficult to administer because of its narrow therapeutic margin and the numerous factors that influence patient response. OBJECTIVE: Demographic, clinical and genetic variables were characterized to establish the appropriate maintenance dosages of warfarin. MATERIALS AND METHODS: The Colombian patients consisted of 145 adults of both sexes. They were in stable anticoagulation status with international normalized ratio between 2 and 3 for at least two months, and without changes in the warfarin commercial preparation or in the dosage. After signing the informed consent, the following data was recorded for each volunteer: age, gender, weight, height, smoker status, co-morbidity, co-medication, International Normalized Ratio (INR), warfarin dose, and commercial brand. Each patient was typed for genes CYP2C9, VKORC1, CYP4F2 and PROC; for 59 patients, the serum levels of warfarin were quantified. The genotyping and the blood quantification were performed by mini-sequencing and HPLC methods, respectively. RESULTS: Age, co-medication with enzymatic inhibitors (amiodarone, sertraline, fluoxetine) or inducers (phenytoin, carbamazepine), and the alleles rs1799853 (*2) and rs1057910 (*3) of the CYP2C9 gene, as well as rs9923231 of the VKORC1 gene were associated with warfarin dose required to achieve anticoagulation with INR of 2-3. These variables were included in a multiple linear regression model for predicting the optimum dose/week of warfarin. This resulted in an algorithm that explained 47.4% of the variability in the dose responses. CONCLUSION: Clinical and pharmacogenetic variables provided a basis for improving the safety and effective dosage of warfarin; however, the use of a pharmacogenetic algorithm will require patient data obtained during clinical trials.
Authors: Elisa Danese; Sara Raimondi; Martina Montagnana; Angela Tagetti; Taimour Langaee; Paola Borgiani; Cinzia Ciccacci; Antonio J Carcas; Alberto M Borobia; Hoi Y Tong; Cristina Dávila-Fajardo; Mariana Rodrigues Botton; Stephane Bourgeois; Panos Deloukas; Michael D Caldwell; Jim K Burmester; Richard L Berg; Larisa H Cavallari; Katarzyna Drozda; Min Huang; Li-Zi Zhao; Han-Jing Cen; Rocio Gonzalez-Conejero; Vanessa Roldan; Yusuke Nakamura; Taisei Mushiroda; Inna Y Gong; Richard B Kim; Keita Hirai; Kunihiko Itoh; Carlos Isaza; Leonardo Beltrán; Enrique Jiménez-Varo; Marisa Cañadas-Garre; Alice Giontella; Marianne K Kringen; Kari Bente Foss Haug; Hye Sun Gwak; Kyung Eun Lee; Pietro Minuz; Ming Ta Michael Lee; Steven A Lubitz; Stuart Scott; Cristina Mazzaccara; Lucia Sacchetti; Ece Genç; Mahmut Özer; Anil Pathare; Rajagopal Krishnamoorthy; Andras Paldi; Virginie Siguret; Marie-Anne Loriot; Vijay Kumar Kutala; Guilherme Suarez-Kurtz; Jamila Perini; Josh C Denny; Andrea H Ramirez; Balraj Mittal; Saurabh Singh Rathore; Hersh Sagreiya; Russ Altman; Mohamed Hossam A Shahin; Sherief I Khalifa; Nita A Limdi; Charles Rivers; Aditi Shendre; Chrisly Dillon; Ivet M Suriapranata; Hong-Hao Zhou; Sheng-Lan Tan; Vacis Tatarunas; Vaiva Lesauskaite; Yumao Zhang; Anke H Maitland-van der Zee; Talitha I Verhoef; Anthonius de Boer; Monica Taljaard; Carlo Federico Zambon; Vittorio Pengo; Jieying Eunice Zhang; Munir Pirmohamed; Julie A Johnson; Cristiano Fava Journal: Clin Pharmacol Ther Date: 2019-02-17 Impact factor: 6.875
Authors: E Danese; M Montagnana; J A Johnson; A E Rettie; C F Zambon; S A Lubitz; G Suarez-Kurtz; L H Cavallari; L Zhao; M Huang; Y Nakamura; T Mushiroda; M K Kringen; P Borgiani; C Ciccacci; N T Au; T Langaee; V Siguret; M A Loriot; H Sagreiya; R B Altman; M H A Shahin; S A Scott; S I Khalifa; B Chowbay; I M Suriapranata; M Teichert; B H Stricker; M Taljaard; M R Botton; J E Zhang; M Pirmohamed; X Zhang; J F Carlquist; B D Horne; M T M Lee; V Pengo; G C Guidi; P Minuz; C Fava Journal: Clin Pharmacol Ther Date: 2012-11-07 Impact factor: 6.875