Combined Effect of Genetic Factors, Age, and Smoking on the Risk of Developing Myocardial Infarction

Objective: to elaborate a complex model for myocardial infarction (MI) risk assessment considering the combined effect of genetic predisposition, age and smoking. Materials and methods. The study included two independent samples of ethnic Russians: 325 patients with MI and 185 individuals without history of cardiovascular diseases (controls) from the Moscow region, and 220 patients and 197 controls from the Republic of Bashkortostan. Genotyping of polymorphic loci of genes CRP (rs1130864), IFNG (rs2430561), TGFB1 (rs1982073), FGB (rs1800788) and PTGS1 (rs3842787) was performed. To construct the predictive models, we used logistic regression with stepwise inclusion of variables. The predictive value was evaluated by the area under the curve (AUC) in a ROC-analysis. The factor was considered as a marker at pAUC <0.05 calculated by the method of DeLong. The marker was considered effective at AUC >0.60. Results. Three separate genetic variants FGB rs1800788*T, TGFB1 rs1982073*TT, CRP rs1130864*TT, and biallelic combination IFNG rs2430561*A PTGS1 rs3842787*T whose association with MI we described earlier, were used to construct the composite genetic marker (AUC = 0.66 in the training and test samples) by the logistic regression method. Adding to the obtained composite genetic marker such parameters as age and smoking allowed to create a complex MI risk marker, which was characterized by the predictive value stability (AUC =0.77 in the training sample and 0.82 in the test sample). Conclusion. The obtained complex model for MI risk assessment was reproduced in two independent samples of Russian ethnicity individuals from different regions of Russia with different gender identities, and allowed to have a reasonable chance (about 80%) of distinguishing patients and healthy individuals.