Premium
Genetic variation influences the risk of bleeding after cardiac surgery: novel associations and validation of previous findings
Author(s) -
GREIFF G.,
PLEYM H.,
STENSETH R.,
WAHBA A.,
VIDEM V.
Publication year - 2015
Publication title -
acta anaesthesiologica scandinavica
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.738
H-Index - 107
eISSN - 1399-6576
pISSN - 0001-5172
DOI - 10.1111/aas.12504
Subject(s) - medicine , logistic regression , single nucleotide polymorphism , odds ratio , abo blood group system , genetic variation , surgery , gene , genotype , genetics , population , biology , environmental health
Background Severe post‐operative bleeding in cardiac surgery is associated with increased morbidity and mortality. We hypothesized that variation in genetic susceptibility contributes to post‐operative bleeding in addition to clinical factors. Methods We included 1036 adults undergoing cardiac surgery with cardiopulmonary bypass. Two different endpoints for excessive post‐operative bleeding were used, either defined as blood loss exceeding 2 ml/kg/h the first 4 h post‐operatively or a composite including bleeding, transfusions, and reoperations. Twenty‐two single nucleotide polymorphisms ( SNPs ) central in the coagulation and fibrinolysis systems or in platelet membrane receptors were genotyped, focusing on replication of earlier non‐replicated findings and exploration of potential novel associations. Using logistic regression, significant SNPs were added to a model with only clinical variables to evaluate whether the genetic variables provided additional information. Results Univariate tests identified rs 1799809 (located in the promoter region of the PROC gene), rs 27646 and rs 1062535 (in the ITGA 2 gene), rs 630014 (in the ABO gene), and rs 6048 (in the F 9 gene) as significantly associated with excessive post‐operative bleeding ( P < 0.05, P ‐values confirmed by permutation). The SNPs were significant also after adjustment with clinical variables, showing almost unchanged odds ratios except for rs1799809 ( P = 0.06). Addition of the genetic covariates to a logistic regression model with clinical variables significantly improved the model ( P < 0.01). Conclusion We identified five SNPs associated with post‐operative bleeding after cardiac surgery, of which two validated previously published associations. Addition of genetic information to models with only clinical variables improved the models. Our results indicate that common genetic variations significantly influence post‐operative bleeding after cardiac surgery.