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Verification of pharmacogenomics-based algorithms to predict warfarin maintenance dose using registered data of Japanese patients

  • Maki Sasano
  • Masako Ohno
  • Yuya Fukuda
  • Shinpei Nonen
  • Sachiko Hirobe
  • Shinichiro Maeda
  • Yoshihiro Miwa
  • Junya Yokoyama
  • Hiroyuki Nakayama
  • Shigeru Miyagawa
  • Yoshiki Sawa
  • Yasushi Fujio
  • Makiko MaedaEmail author
Pharmacogenetics
  • 54 Downloads

Abstract

Purpose

Large inter-individual differences in warfarin maintenance dose are mostly due to the effect of genetic polymorphisms in multiple genes, including vitamin K epoxide reductase complex 1 (VKORC1), cytochromes P450 2C9 (CYP2C9), and cytochrome P450 4F2 (CYP4F2). Thus, several algorithms for predicting the warfarin dose based on pharmacogenomics data with clinical characteristics have been proposed. Although these algorithms consider these genetic polymorphisms, the formulas have different coefficient values that are critical in this context. In this study, we assessed the mutual validity among these algorithms by specifically considering racial differences.

Methods

Clinical data including actual warfarin dose (AWD) of 125 Japanese patients from our previous study (Eur J Clin Pharmacol 65(11):1097–1103, 2009) were used as registered data that provided patient characteristics, including age, sex, height, weight, and concomitant medications, as well as the genotypes of CYP2C9 and VKORC1. Genotyping for CYP4F2*3 was performed by the PCR method. Five algorithms that included these factors were selected from peer-reviewed articles. The selection covered four populations, Japanese, Chinese, Caucasian, and African-American, and the International Warfarin Pharmacogenetics Consortium (IWPC).

Results

For each algorithm, we calculated individual warfarin doses for 125 subjects and statistically evaluated its performance. The algorithm from the IWPC had the statistically highest correlation with the AWD. Importantly, the calculated warfarin dose (CWD) using the algorithm from African-Americans was less correlated with the AWD as compared to those using the other algorithms. The integration of CYP4F2 data into the algorithm did not improve the prediction accuracy.

Conclusion

The racial difference is a critical factor for warfarin dose predictions based on pharmacogenomics.

Keywords

Warfarin Algorithm VKORC1 CYP2C9 CYP4F2 

Notes

Acknowledgments

We are grateful to all doctors, nurses, and subjects who participated in this study.

Author contributions

Conceived and designed the experiments: MO, HN, YF, MM. Performed the experiments: MS, YF, SN, MM. Analyzed the data: MO, SN, SH, SM, YF, YM, JY, YS, YF, MM. Contributed new methods or models: YF, MM. Wrote the paper: YF, MM.

Funding

This study was funded by the Management Expenses Grants from MEXT, Japan.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

This study was approved by the Ethical Review Committee of Osaka University (approval number, 766). Written informed consent was obtained from each participant to allow their samples and clinical data to be used for secondary analyses. For this type of study formal consent is not required. The study has been performed in accordance with The Code of Ethics of the 1964 Declaration of Helsinki and its later amendments. This study does not contain any studies with animals performed by any of the authors.

Supplementary material

228_2019_2656_MOESM1_ESM.pptx (120 kb)
Figure S1 Scatter Plot of the actual warfarin dose (AWD) v.s. the calculated warfarin dose (CWD) only for 51 subjects with PT-INR between 2 and 3. Scatter plots were applied to examine the correlation between the AWD and the CWD derived from each algorithm. The solid line indicates the line of equivalence, which shows that the CWD and the AWD are perfectly matched. The X-axis represents the AWD (mg/day) and the Y-axis represents the CWD (mg/day). a Original algorithm. b Algorithm I (IWPC). c Algorithm II. d Algorithm III. e Algorithm IV. f Algorithm V. (PPTX 120 kb)
228_2019_2656_MOESM2_ESM.pptx (132 kb)
Figure S2 Bland and Altman plot for the actual warfarin dose (AWD) and the calculated warfarin dose (CWD) with the representation of the limits of agreement. Bland and Altman’s plots were performed to describe the agreement between the CWD and the AWD. The Y-axis represents the difference between the CWD and the AWD (CWD-AWD) (mg/day), and the solid line indicates the mean difference. The X-axis represents the mean of the CWD and the AWD ((CWD+AWD)/2) (mg/day). The dotted lines indicate the ±1.96 SD of the mean difference (CWD - AWD) are shown a parallel to the X-axis. a Original algorithm. b Algorithm I (IWPC). c Algorithm II. d Algorithm III. e Algorithm IV. f Algorithm V. (PPTX 131 kb)
228_2019_2656_MOESM3_ESM.pptx (107 kb)
Figure S3 Scatter Plot of the calculated warfarin dose (CWD) derived from each algorithm I (IWPC) to V v.s. CWD derived from the Original algorithm only for 51 subject with PT-INR between 2 and 3. Scatter plots were applied to examine the correlation between the CWD derived from each algorithm I (IWPC) to V and the CWD derived from the Original algorithm (Original CWD). The solid line indicates the line of equivalence, which shows that the CWD and the Original CWD are perfectly matched. The X-axis designated as Original represents the Original CWD (mg/day). The Y-axis represents the CWD derived from each algorithm (mg/day). a Algorithm I (IWPC). b Algorithm II. c Algorithm III. d Algorithm IV. e Algorithm V. (PPTX 107 kb)

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Maki Sasano
    • 1
  • Masako Ohno
    • 2
  • Yuya Fukuda
    • 3
  • Shinpei Nonen
    • 2
  • Sachiko Hirobe
    • 1
    • 3
  • Shinichiro Maeda
    • 1
    • 3
  • Yoshihiro Miwa
    • 4
  • Junya Yokoyama
    • 5
  • Hiroyuki Nakayama
    • 6
  • Shigeru Miyagawa
    • 5
  • Yoshiki Sawa
    • 5
  • Yasushi Fujio
    • 1
    • 6
  • Makiko Maeda
    • 1
    • 3
    Email author
  1. 1.Clinical Pharmacology and Therapeutics Project, Graduate School of Pharmaceutical SciencesOsaka UniversityOsakaJapan
  2. 2.School of PharmacyHyogo University of Health SciencesKobeJapan
  3. 3.Advanced Research of Medical and Pharmaceutical Sciences , Graduate School of Pharmaceutical SciencesOsaka UniversityOsakaJapan
  4. 4.Department of PharmacyOsaka University HospitalOsakaJapan
  5. 5.Department of Cardiovascular Surgery, Graduate School of MedicineOsaka UniversityOsakaJapan
  6. 6.Laboratory of Clinical Science and Biomedicine, Graduate School of Pharmaceutical SciencesOsaka UniversityOsakaJapan

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