Key result
Genetic variants including VKORC1 and CES1 influence patient response to oral anticoagulants.
While pharmacogenetic algorithms exist for VKAs, there is a critical lack of genome-wide association data for most DOACs to guide personalized anticoagulant therapy.
Pharmacogenetic algorithms apply mainly to VKAs; leaves open critical GWAS gaps for most DOACs to enable personalized therapy.
Variants in these genes have been included in pharmacogenetic algorithms to predict the VKAs dose individually in each patient depending on their genotype and clinical variables. DOACs: Dabigatran, apixaban, rivaroxaban and edoxaban have been approved for patients with AF. They have stable pharmacokinetics and do not require routine blood checks, thus avoiding most of the drawbacks of VKAs. Except for a GWAs performed in patients treated with dabigatran, there is no Genome Wide pharmacogenomics data for DOACs. Pharmacogenomics could be useful to predict the better clinical response and avoid adverse events in patients treated with anticoagulants, identifying the most appropriate anticoagulant drug for each patient. Current pharmacogenomics data show that the polymorphisms affecting VKAs or DOACs are different, concluding that personalized medicine based on pharmacogenomics could be possible. However, more studies are required to implement personalized medicine in clinical practice with OA and based on pharmacogenetics of DOACs.
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Cullell et al. (2018) conducted a review in Atrial fibrillation and cardioembolic stroke. Oral anticoagulants (VKAs and DOACs) was evaluated. Genome-wide association studies have identified distinct genetic variants, such as VKORC1 and CYP2C9 for vitamin K antagonists and CES1 for dabigatran, that influence oral anticoagulant response.
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