Dataset Information

The effect of the VKORC1 promoter variant on warfarin responsiveness in the Saudi WArfarin Pharmacogenetic (SWAP) cohort.

ABSTRACT: Warfarin is a frequently prescribed oral anticoagulant with a narrow therapeutic index, requiring careful dosing and monitoring. However, patients respond with significant inter-individual variability in terms of the dose and responsiveness of warfarin, attributed to genetic polymorphisms within the genes responsible for the pharmacokinetics and pharmacodynamics of warfarin. Extensive warfarin pharmacogenetic studies have been conducted, including studies resulting in genotype-guided dosing guidelines, but few large scale studies have been conducted with the Saudi population. In this study, we report the study design and baseline characteristics of the Saudi WArfarin Pharmacogenomics (SWAP) cohort, as well as the association of the VKORC1 promoter variants with the warfarin dose and the time to a stable INR. In the 936 Saudi patients recruited in the SWAP study, the minor allele C of rs9923231 was significantly associated with a 8.45 mg higher weekly warfarin dose (p value?=?4.0?×?10-46), as well as with a significant delay in achieving a stable INR level. The addition of the rs9923231 status to the model, containing all the significant clinical variables, doubled the warfarin dose explained variance to 31%. The SWAP cohort represents a valuable resource for future research with the objective of identifying rare and prevalent genetic variants, which can be incorporated in personalized anticoagulation therapy for the Saudi population.

SUBMITTER: Al Ammari M

PROVIDER: S-EPMC7363835 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

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The effect of the VKORC1 promoter variant on warfarin responsiveness in the Saudi WArfarin Pharmacogenetic (SWAP) cohort.

Al Ammari Maha M AlBalwi Mohammed M Sultana Khizra K Alabdulkareem Ibrahim B IB Almuzzaini Bader B Almakhlafi Nada S NS Aldrees Mohammed M Alghamdi Jahad J

Scientific reports 20200715 1

Warfarin is a frequently prescribed oral anticoagulant with a narrow therapeutic index, requiring careful dosing and monitoring. However, patients respond with significant inter-individual variability in terms of the dose and responsiveness of warfarin, attributed to genetic polymorphisms within the genes responsible for the pharmacokinetics and pharmacodynamics of warfarin. Extensive warfarin pharmacogenetic studies have been conducted, including studies resulting in genotype-guided dosing guid ...[more]

PMID: 32669629

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Project description:ObjectiveMultiple linear regression (MLR) and machine learning techniques in pharmacogenetic algorithm-based warfarin dosing have been reported. However, performances of these algorithms in racially diverse group have never been objectively evaluated and compared. In this literature-based study, we compared the performances of eight machine learning techniques with those of MLR in a large, racially-diverse cohort.MethodsMLR, artificial neural network (ANN), regression tree (RT), multivariate adaptive regression splines (MARS), boosted regression tree (BRT), support vector regression (SVR), random forest regression (RFR), lasso regression (LAR) and Bayesian additive regression trees (BART) were applied in warfarin dose algorithms in a cohort from the International Warfarin Pharmacogenetics Consortium database. Covariates obtained by stepwise regression from 80% of randomly selected patients were used to develop algorithms. To compare the performances of these algorithms, the mean percentage of patients whose predicted dose fell within 20% of the actual dose (mean percentage within 20%) and the mean absolute error (MAE) were calculated in the remaining 20% of patients. The performances of these techniques in different races, as well as the dose ranges of therapeutic warfarin were compared. Robust results were obtained after 100 rounds of resampling.ResultsBART, MARS and SVR were statistically indistinguishable and significantly out performed all the other approaches in the whole cohort (MAE: 8.84-8.96 mg/week, mean percentage within 20%: 45.88%-46.35%). In the White population, MARS and BART showed higher mean percentage within 20% and lower mean MAE than those of MLR (all p values < 0.05). In the Asian population, SVR, BART, MARS and LAR performed the same as MLR. MLR and LAR optimally performed among the Black population. When patients were grouped in terms of warfarin dose range, all machine learning techniques except ANN and LAR showed significantly higher mean percentage within 20%, and lower MAE (all p values < 0.05) than MLR in the low- and high- dose ranges.ConclusionOverall, machine learning-based techniques, BART, MARS and SVR performed superior than MLR in warfarin pharmacogenetic dosing. Differences of algorithms' performances exist among the races. Moreover, machine learning-based algorithms tended to perform better in the low- and high- dose ranges than MLR.

Dataset Information

The effect of the VKORC1 promoter variant on warfarin responsiveness in the Saudi WArfarin Pharmacogenetic (SWAP) cohort.

Publications

The effect of the VKORC1 promoter variant on warfarin responsiveness in the Saudi WArfarin Pharmacogenetic (SWAP) cohort.

Similar Datasets

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