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标题： Genetic evaluation system for predicting long-term prognosis after coronary artery bypass grafting

讲者：刘汉凝

单位：中国医学科学院阜外医院

关键词：

Coronary artery bypass grafting long-term rognosis Genetic evaluation.

播放： 3166

论文摘要：

Background Both genetic and clinical factors could influent the long-term prognosis after coronary artery bypass graft (CABG) surgery. There exist clinical risk scores to predict the adverse events after CABG, the efficacy and quality of these predicting models still needs to be improved. Several genetic variants were associated with poor prognosis after CABG. This study aims to put forward a gene-based risk score system to predict long-term prognosis after CABG.

Methods A cohorts of 1547 patients undergoing CABG surgery were examined, and the adverse events after the index CABG were followed up. Patients were consecutively recruited from Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College (Beijing, China) between December 2007 and July 2010. The study protocol was approved by the Review Board of Fuwai Hospital，Peking Union Medical College (Beijing, China). We have complied with the World Medical Association Declaration of Helsinki regarding ethical conduct of research involving human subjects and/or animals. All patients were provided written informed consent to be involved in the study. The median follow-up time of these patients was 6.06 years. The adverse events (MACCE) includes all-cause death, new-onset nonfatal myocardial infarction, new-onset nonfatal stroke and repeat revascularization. For every patient, ninety-five single-nucleotide polymorphisms (SNPs) were tested. These SNPs were reported associating with coronary artery diseases in GWA studies and/or studies of candidate genes. For every SNP, a variable recording the allele count (0, 1, 2) was used to perform statistical analysis. Cox proportional hazard models were used to identify genomic predictors of MACCE. The level of significance was set to P-value < 0.05. Significant SNPs were selected as risk SNPs to further study. The sums of the allele count of all the remained risk SNPs were calculated as a risk score. The risk score were validated in Cox proportional hazard models. We also calculated Cox regression C statistics of the genetic risk score to evaluated the efficacy of this predicting model.

Results In the 6-year follow up period, there were 329 out of 1547 patients (21.27%) suffered in adverse events. Seven SNPs were selected as risk SNPs. They were IL6 rs1800796 (HR=1.268, 95% CI: 1.084-1.482, P=0.003), ITGA2 rs1126643 (HR=1.270, 95% CI: 1.075-1.500, P=0.005), THBD rs1042579 (HR=1.221, 95% CI: 1.027-1.450, P=0.023), THBD 3176123 (HR=1.207, 95% CI: 1.018-1.431, P=0.030), P2RY12 rs2046934 (HR=1.230, 95% CI: 1.017-1.487, P=0.033) and CYP2C19 rs4244285 (HR=1.179, 95% CI: 1.003-1.385, P=0.046). GenoSCORE of all patients ranged from 0 to 10. When the GenoSCORE increased for 1 unit, the risk of MACCE would increase for 1.172 times (P=1.57*10^-7). Then, the patients were divided into four groups according to GenoSCORE, namely the low risk group (GenoSCORE: 0 and 1), intermediate risk group (GenoSCORE: 2, 3 and 4), high risk group (GenoSCORE: 5, 6 and 7) and extremely high risk group (GenoSCORE: 8,9 and 10). The HR of the intermediate risk group, high risk group and extremely risk group were 1.361 (p=0.074), 2.109 (p=7.75*10^-5) and 4.212 (p=2.30*10^-5) compared to the low risk group. The Cox regression C statistics of GenoSCORE was 0.798, which means it can predict the adverse events accurately.

Conclusions We established a genetic risk score based on the association between SNPs and poor prognosis after CABG, and the GenoSCORE can predict the adverse events after CABG accurately.