[Age-Dependent Approach to Search for Genetic Variants Associated with Myocardial Infarction].

Myocardial infarction (MI), one of the most common manifestations of cardiovascular system aging, is often fatal. The vast majority of studies on genetic susceptibility to age-dependent diseases are carried out using the case-control study design. However, its use involves a number of difficulties, most of which arise when establishing the control group of relatively healthy individuals. In this work, survival functions were analyzed for carriers of alternative polymorphic variants of 18 genes that had been tested for association with MI using the case-control approach in our previous study, and the magnitude of the shift in the age of the disease onset depending on individual variations of the genome was estimated. The following risk variants were associated with the age of MI: rs2430561*A of IFNG (HR = 1.3, P = 0.043), rs1799889*5 of PAI-1 (HR = 1.3, P = 0.039), rs1800896*GG of IL10 (HR = 1.5, P = 0.0048), rs1800471*C of TGFB1 (HR = 1.5, P = 0.043), and rs11614913*TT of MIR196A2 (HR = 1.5, P = 0.035). In carriers of these variants, the disease developed 3-6 years earlier than in carriers of alternative variants. The results of this study were compared with data on the associations with MI previously obtained on the same sample using the case-control approach. It turned out that the estimates based on the two methods mostly disagreed. However, the age-dependent approach relies on fewer assumptions that can be additionally verified. In our opinion, it makes this approach more promising than the case-control design.

[The Myocardial Infarction Associated Variant in the MIR196A2 Gene and Presumable Signaling Pathways to Involve miR-196a2 in the Pathological Phenotype].

The heritable component of susceptibility to myocardial infraction (MI) remains unexplained, possibly due to the minor effects of genes, which are not obviously associated with the disease. These genes may be integrated in miRNA regulated networks associated with myocardial infarction. A systematic review of the literature led us to selecting rs2910164 (MIR146A), rs11614913 (MIR196A2), and rs3746444 (MIR499А) variants to study the association with the MI phenotype. In ethnic Russians, variant rs11614913*C (MIR196A2) was found to be associated with the risk of myocardial infraction (p = 0.023, OR = 1.74) for the first time; this association was validated in an independent cohort. The gene-gene interaction network for experimentally validated miR-196a2 target genes was built and analyzed. One of its four topological clusters contained the majority of miR-196a2 target genes associated with atherosclerosis, coronary artery disease or myocardial infarction and was enriched with the genes regulating the TGFß and class I MHC signaling pathways, platelet activation/aggregation, and the cell cycle control. This analysis points towards the role of miR-196a2 in the pathological coronary phenotypes and opens up an avenue for further investigations.

Multilocus Analysis of Genetic Susceptibility to Myocardial Infarction in Russians: Replication Study.

In search of genetic markers of myocardial infarction (MI) risk, which have prognostic significance for Russians, we performed a replication study of MI association with genetic variants of PCSK9 (rs562556), APOE (epsilon polymorphism, rs7412 and rs429358), LPL (rs320), MTHFR (rs1801133), eNOS (rs2070744), and the 9p21 region (rs1333049) in 405 patients with MI and 198 controls. Significant MI association was observed with variants of the lipid metabolism genes (PCSK9, APOE and LPL), and of eNOS. The SNPs in the MTHFR gene and the 9p21 region were not significantly associated with MI one by one but were included in several different MI-associated allelic combinations identified by multilocus analysis. Since we have not revealed nonlinear epistatic interactions between the components of the identified combinations, we postulate that the cumulative effect of genes that form a combination arises from the summation of their small independent contributions. The prognostic significance of the additive composite model built from the PCSK9, APOE, LPL, and eNOS genes as genetic markers was assessed using ROC analysis. After we included these markers in the previously published composite model of individual genetic risk of MI, the prognostic efficacy in our sample reached AUC = 0.676. However, the results obtained in this study certainly need to be replicated in an independent sample of Russians.

[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.