| Summary: | <b>Objectives</b>: The purpose of our study is to investigate the effects of apolipoprotein B (<i>APOB</i>) and <i>APOE</i> gene polymorphisms on bleeding complications in patients receiving direct oral anticoagulants (DOACs). <b>Methods</b>: A total of 16 single nucleotide polymorphisms (SNPs) in 468 patients were genotyped. Six SNPs of <i>ABCB1</i> (rs3842, rs1045642, rs2032582, rs1128503, rs3213619, and rs3747802), one SNP of <i>CYP3A5</i> (rs776746), seven SNPs of <i>APOB</i> (rs1042034, rs2163204, rs693, rs679899, rs13306194, rs13306198, and rs1367117), and two SNPs of <i>APOE</i> (rs429358 and rs7412) were analyzed by a TaqMan genotyping assay. Multivariable logistic regression analysis with selected variables was performed for the construction of a risk scoring system. Two risk scoring systems were compared (demographic factors only vs. demographic factors and genetic factors). <b>Results</b>: In the multivariable analyses, two models were constructed; only demographic factors were included in Model I and both demographic factors and genetic factors in Model II. Rivaroxaban and anemia showed significant association with bleeding in both models. Additionally, <i>ABCB1</i> rs3842 variant homozygote carriers (CC) and <i>APOB</i> rs13306198 variant allele carriers (AG, AA) had a higher risk of bleeding risk compared with that of wild-type allele carriers (TT, TC) and wild-type homozygote carriers (GG), respectively. Whereas the area under the receiver operating characteristic curve (AUROC) value using demographic factors only was 0.65 (95% confidence interval (CI): 0.56–0.74), the AUROC increased to 0.72 by adding genetic factors (95% CI: 0.65–0.80). The predicted bleeding risks of bleeding in patients with 0, 1, 2, 3, 4, 5, 6, 7 and 8 points from the logistic regression curve were 0.8%, 2.0%, 5.4%, 5.2%, 12.5%, 26.9%, 47.0%, 64.3% and 82.3%, respectively. <b>Conclusions</b>: The study results can be used for enhancing individualized treatment strategies in patients taking DOACs, helping clinicians predict the bleeding risk.
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