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European Journal of Clinical Pharmacology

, Volume 74, Issue 12, pp 1555–1566 | Cite as

Impact of incorporating ABCB1 and CYP4F2 polymorphisms in a pharmacogenetics-guided warfarin dosing algorithm for the Brazilian population

  • Letícia C. Tavares
  • Nubia E. Duarte
  • Leiliane R. Marcatto
  • Renata A. G. Soares
  • Jose E. Krieger
  • Alexandre C. Pereira
  • Paulo Caleb Junior Lima Santos
Pharmacogenetics
  • 115 Downloads

Abstract

Purpose

Interpatient variation of warfarin dose requirements may be explained by genetic variations and general and clinical factors. In this scenario, diverse population-calibrated dosing algorithms, which incorporate the main warfarin dosing influencers, have been widely proposed for predicting supposed warfarin maintenance dose, in order to prevent and reduce adverse events. The aim of the present study was to evaluate the impact of the inclusion of ABCB1 c.3435C>T and CYP4F2 c.1297G>A polymorphisms as additional covariates in a previously developed pharmacogenetic-based warfarin dosing algorithm calibrated for the Brazilian population.

Methods

Two independent cohorts of patients treated with warfarin (n = 832 and n = 133) were included for derivation and replication of the algorithm, respectively. Genotyping of ABCB1 c.3435C>T and CYP4F2 c.1297G>A polymorphisms was performed by polymerase chain reaction followed by melting curve analysis and TaqMan® assay, respectively. A multiple linear regression was performed for the warfarin stable doses as a dependent variable, considering clinical, general, and genetic data as covariates.

Results

The inclusion of ABCB1 and CYP4F2 polymorphisms was able to improve the algorithm’s coefficient of determination (R2) by 2.6%. In addition, the partial determination coefficients of these variants revealed that they explained 3.6% of the warfarin dose variability. We also observed a marginal improvement of the linear correlation between observed and predicted doses (from 59.7 to 61.4%).

Conclusion

Although our study indicates that the contribution of the combined ABCB1 and CYP4F2 genotypes in explaining the overall variability in warfarin dose is not very large, we demonstrated that these pharmacogenomic data are statistically significant. However, the clinical relevance and cost-effective impact of incorporating additional variants in warfarin dosing algorithms should be carefully evaluated.

Keywords

Warfarin pharmacogenetics Genetic-guided dosing algorithm ABCB1 MDR1 CYP4F2 Warfarin stable dose 

Notes

Acknowledgements

We thank the participants of the study and the technical assistance provided by the staff of the Laboratory of Genetics and Molecular Cardiology, Heart Institute (InCor).

Author contribution

All authors have contributed substantially to the conception and design of this paper. LC performed the experiments, collected and analyzed the data, and wrote the paper. LR recruited the patients, collected data, and critically revised the manuscript. RA recruited the patients. AC, JE, and PC provided the facilities, analyzed the data, and critically revised the manuscript.

Funding information

The authors declare that they have received grants for the support of this study from São Paulo Research Foundation (FAPESP), grant numbers 2013/09295-3, 2016/22507-8, and 2016/23454-5.

Compliance with ethical standards

The study protocol was approved by the Institutional Ethics Committee (Registered Number 0804/10), and written informed consent was obtained from all participants prior to entering in the study.

Conflict of interest

The authors declare that they have no competing interests.

Supplementary material

228_2018_2528_MOESM1_ESM.docx (2.7 mb)
ESM 1 (DOCX 2716 kb)

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Letícia C. Tavares
    • 1
  • Nubia E. Duarte
    • 2
  • Leiliane R. Marcatto
    • 1
  • Renata A. G. Soares
    • 1
  • Jose E. Krieger
    • 1
  • Alexandre C. Pereira
    • 1
  • Paulo Caleb Junior Lima Santos
    • 1
    • 3
  1. 1.Laboratory of Genetics and Molecular Cardiology, Heart Institute (InCor), Faculdade de Medicina FMUSPUniversidade de Sao PauloSão PauloBrazil
  2. 2.Department of Mathematic and StatisticsUniversidad Nacional de ColombiaManizalesColombia
  3. 3.Department of Pharmacology, Escola Paulista de MedicinaUniversidade Federal de Sao Paulo UNIFESPSão PauloBrazil

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