Literature DB >> 30815847

Differences in Warfarin Pharmacodynamics and Predictors of Response Among Three Racial Populations.

Minami Ohara1, Yasuhiko Suzuki1, Saki Shinohara1, Inna Y Gong2, Crystal L Schmerk2, Rommel G Tirona2, Ute I Schwarz2, Ming-Shien Wen3, Ming Ta Michael Lee4, Kiyoshi Mihara5, Edith A Nutescu6, Minoli A Perera7, Larisa H Cavallari8, Richard B Kim2, Harumi Takahashi9.   

Abstract

BACKGROUND: Population differences in warfarin dosing requirement have been reported; however, unlike the pharmacokinetics (PK) of warfarin, the quantitative influences of pharmacodynamic (PD) factors on the anticoagulation response to warfarin in different ethnic populations are totally unknown.
METHODS: Using population PK/PD analysis, we attempted to identify predictors of S-warfarin clearance [CL(S)] and half maximal effective concentration (EC50) to quantify racial differences in both PK and PD parameters, and to assess the contribution of these parameters to the international normalized ratio (INR) and over-anticoagulation response (INR ≥ 4) in a cohort of 309 White, Asian and African American patients.
RESULTS: Similar to our previous findings, the median CL(S) was 30% lower in African American patients than Asian and White patients (169 vs. 243 and 234 mL/h, p < 0.01). EC50 showed a greater racial difference than CL(S) [1.03, 1.70 and 2.76 μg/mL for Asian, White and African American patients, respectively, p < 0.01). Significant predictors of INR included demographic/clinical (age, body weight, creatinine clearance and sex) and genotypic (CYP2C9*3,*8 and VKORC1 -1639G>A) factors, as well as African American ethnicity. In all three racial groups, genetic predictors of INR appeared to have greater influence than demographic/clinical predictors. Both CL(S) and EC50 contributed to the over-anticoagulation response to warfarin. Patients having VKORC1 -1639 G>A and/or factors associated with reduced CYP2C9 activity were more likely to have an INR ≥ 4.
CONCLUSIONS: Although there were contrasting racial differences in CL(S) and EC50 that impacted on the INR, the racial difference in EC50 was greater than that for CL(S), thus explaining the higher warfarin requirement for African American patients.

Entities:  

Year:  2019        PMID: 30815847     DOI: 10.1007/s40262-019-00745-5

Source DB:  PubMed          Journal:  Clin Pharmacokinet        ISSN: 0312-5963            Impact factor:   6.447


  32 in total

1.  A procedure for generating bootstrap samples for the validation of nonlinear mixed-effects population models.

Authors:  J Parke; N H Holford; B G Charles
Journal:  Comput Methods Programs Biomed       Date:  1999-04       Impact factor: 5.428

2.  Pyrosequencing method for genotyping cytochrome P450 CYP2C8 and CYP2C9 enzymes.

Authors:  Matthew W Hruska; Reginald F Frye; Taimour Y Langaee
Journal:  Clin Chem       Date:  2004-12       Impact factor: 8.327

3.  A PK-PD model for predicting the impact of age, CYP2C9, and VKORC1 genotype on individualization of warfarin therapy.

Authors:  A-K Hamberg; M-L Dahl; M Barban; M G Scordo; M Wadelius; V Pengo; R Padrini; E N Jonsson
Journal:  Clin Pharmacol Ther       Date:  2007-02-14       Impact factor: 6.875

4.  Effect of VKORC1 haplotypes on transcriptional regulation and warfarin dose.

Authors:  Mark J Rieder; Alexander P Reiner; Brian F Gage; Deborah A Nickerson; Charles S Eby; Howard L McLeod; David K Blough; Kenneth E Thummel; David L Veenstra; Allan E Rettie
Journal:  N Engl J Med       Date:  2005-06-02       Impact factor: 91.245

5.  Warfarin pharmacogenetics: a single VKORC1 polymorphism is predictive of dose across 3 racial groups.

Authors:  Nita A Limdi; Mia Wadelius; Larisa Cavallari; Niclas Eriksson; Dana C Crawford; Ming-Ta M Lee; Chien-Hsiun Chen; Alison Motsinger-Reif; Hersh Sagreiya; Nianjun Liu; Alan H B Wu; Brian F Gage; Andrea Jorgensen; Munir Pirmohamed; Jae-Gook Shin; Guilherme Suarez-Kurtz; Stephen E Kimmel; Julie A Johnson; Teri E Klein; Michael J Wagner
Journal:  Blood       Date:  2010-03-04       Impact factor: 22.113

6.  Different contributions of polymorphisms in VKORC1 and CYP2C9 to intra- and inter-population differences in maintenance dose of warfarin in Japanese, Caucasians and African-Americans.

Authors:  Harumi Takahashi; Grant R Wilkinson; Edith A Nutescu; Takashi Morita; Marylyn D Ritchie; Maria G Scordo; Vittorio Pengo; Martina Barban; Roberto Padrini; Ichiro Ieiri; Kenji Otsubo; Toshitaka Kashima; Sosuke Kimura; Shinichi Kijima; Hirotoshi Echizen
Journal:  Pharmacogenet Genomics       Date:  2006-02       Impact factor: 2.089

7.  The largest prospective warfarin-treated cohort supports genetic forecasting.

Authors:  Mia Wadelius; Leslie Y Chen; Jonatan D Lindh; Niclas Eriksson; Mohammed J R Ghori; Suzannah Bumpstead; Lennart Holm; Ralph McGinnis; Anders Rane; Panos Deloukas
Journal:  Blood       Date:  2008-06-23       Impact factor: 22.113

8.  Use of pharmacogenetic and clinical factors to predict the therapeutic dose of warfarin.

Authors:  B F Gage; C Eby; J A Johnson; E Deych; M J Rieder; P M Ridker; P E Milligan; G Grice; P Lenzini; A E Rettie; C L Aquilante; L Grosso; S Marsh; T Langaee; L E Farnett; D Voora; D L Veenstra; R J Glynn; A Barrett; H L McLeod
Journal:  Clin Pharmacol Ther       Date:  2008-02-27       Impact factor: 6.875

9.  Genetic determinants of response to warfarin during initial anticoagulation.

Authors:  Ute I Schwarz; Marylyn D Ritchie; Yuki Bradford; Chun Li; Scott M Dudek; Amy Frye-Anderson; Richard B Kim; Dan M Roden; C Michael Stein
Journal:  N Engl J Med       Date:  2008-03-06       Impact factor: 91.245

10.  Estimation of the warfarin dose with clinical and pharmacogenetic data.

Authors:  T E Klein; R B Altman; N Eriksson; B F Gage; S E Kimmel; M-T M Lee; N A Limdi; D Page; D M Roden; M J Wagner; M D Caldwell; J A Johnson
Journal:  N Engl J Med       Date:  2009-02-19       Impact factor: 91.245

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  1 in total

1.  Efficacy and safety of app-based remote warfarin management during COVID-19-related lockdown: a retrospective cohort study.

Authors:  Shaojun Jiang; Meina Lv; Zhiwei Zeng; Zongwei Fang; Mingrong Chen; Jiafen Qian; Tingting Wu; Wenjun Chen; Jinhua Zhang
Journal:  J Thromb Thrombolysis       Date:  2022-01-29       Impact factor: 2.300

  1 in total

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