Association between genetic polymorphisms in fibrinogen genes and bleeding risk in patients treated with direct oral anticoagulants

Introduction: This study aimed to investigate the association between polymorphisms in fibrinogen genes and bleeding risk in patients receiving direct oral anticoagulants (DOACs). Method: Patients treated with DOACs from June 2018 to December 2021 were enrolled in the study. Genotyping was done for rs2070011, rs6050, and rs2070022 in fibrinogen alpha chain (FGA); rs1800788, rs4220, and rs4463047 in fibrinogen beta chain (FGB); and rs2066865 and rs1800792 in fibrinogen gamma chain (FGG), along with F2 rs5896 and F10 rs5960. Multivariable logistic regression analysis was performed to investigate the risk factors for bleeding and to develop a risk scoring system. Results: A total of 468 patients were included in the analysis, 14 of whom experienced major bleeding and 36 experienced clinically relevant non-major bleeding. In the multivariable analysis, overdose, anaemia, F2 rs5896, and FGG rs1800792 were found to be significantly associated with bleeding risk. Specifically, patients with the TT genotype of F2 rs5896 and the CC genotype of FGG rs1800792 had 2.1 times (95% confidence interval [CI] 1.1-3.9) and 2.7 times (95% CI 1.2-5.9) higher bleeding risk than the C allele and T allele carriers, respectively. Based on the risk scoring system, patients with 0, 1, 2, 3, 4, and 5 points were predicted to have 5.2%, 10.8%, 22.4%, 32.3%, 42.3%, and 61.8% of bleeding risk, respectively. Conclusion: To our knowledge, this is the first study to investigate the effects of polymorphisms in fibrinogen genes on DOAC response. After validation, these results will be useful for personalised

Automated summary

This study investigated the association between fibrinogen gene polymorphisms and bleeding risk in patients receiving DOACs. It found that overdose, anemia, F2 rs5896, and FGG rs1800792 were significantly associated with bleeding risk. A risk scoring system was developed to predict bleeding risk based on different scores.