SLC4A4, FRAS1, and SULT1A1 Genetic Variations Associated With Dabigatran Metabolism in a Healthy Chinese Population

Background: The purpose of this study was to identify genetic variations associated with the metabolism of dabigatran in healthy Chinese subjects, with particular focus given to pharmacokinetics (PK) and pharmacodynamics (PD). Methods: Healthy Chinese adults aged 18–65 years with unknown genotypes from a bioequivalence trial were included according to the protocol registered at ClinicalTrial.org (NCT03161496). All subjects received a single dose (150 mg) of dabigatran etexilate. PK (main outcomes: area under the concentration-time, AUC(0-t), of total and free dabigatran) and PD (main outcomes: anti-FIIa activity, APTT, and PT) parameters were evaluated. Whole-exome sequencing and genome-wide association analyses were performed. Additionally, candidate gene association analyses related to dabigatran were conducted. Results: A total of 118 healthy Chinese subjects were enrolled in this study. According to the p-value suggestive threshold (1.0 × 10(−4)), the following three SNPs were found to be associated with the AUC(0–t) of total dabigatran: SLC4A4 SNP rs138389345 (p = 5.99 × 10(−5)), FRAS1 SNP rs6835769 (p = 6.88 × 10(−5)), and SULT1A1 SNP rs9282862 (p = 7.44 × 10(−5)). Furthermore, these SNPs were also found to have significant influences on the AUC(0–t) of free dabigatran, maximum plasma concentration, and anti-FIIa activity (p < 0.05). Moreover, we identified 30 new potential SNPs of 13 reported candidate genes (ABCB1, ABCC2, ABCG2, CYP2B6, CYP1A2, CYP2C19, CYP3A5, CES1, SLCO1B1, SLC22A1, UGT1A1, UGT1A9, and UGT2B7) that were associated with drug metabolism. Conclusion: Genetic variations were indeed found to impact dabigatran metabolism in a population of healthy Chinese subjects. Further research is needed to explore the more detailed functions of these SNPs. Additionally, our results should be verified in studies that use larger sample sizes and investigate other ethnicities.