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Article Abstract

Myocardial infarction (MI) is a multifactorial polygenic disease that develops as a result of a complex interaction of numerous genetic factors and the external environment. Accordingly, the contribution of each of them separately is usually not large and may significantly depend on the state of other accompanying factors. The purpose of the study was to search for informative predictors of MI risk based on polygenic analysis of polymorphic variants of (1) the antioxidant defense enzyme genes PON1 (rs662), PON2 (rs7493), CAT (rs1001179), MSRA (rs10098474) and GSTP1 (rs1695); (2) the apoptosis genes CASP8 (rs3834129), TP53 (rs1042522) and BCL2 (rs12454712); and (3) the inflammation genes CRP (rs1205), CX3CR1 (rs3732378), IL6 (rs1800795) and CCL2 (rs1024611). 591 DNA samples were used in the study (280 patients with the onset at 30 to 60 years, with an average age of 46.02 ± 6.17, and 311 control subjects aged 30 to 62, with an average age of 44.65 ± 7.07). All the participants were male and Tatars by ethnicity. The logistic regression analysis with various models demonstrated associations with MI of polymorphic variants of the genes CX3CR1 (rs3732378) (overdominant model - G/G + A/A vs A/G P = 0.0002, OR = 1.9), MSRA (rs10098474) (dominant model - T/T vs T/C + C/C P = 0.015, OR = 1.51), CCL2 (rs1024611) (recessive model - P = 0.0007 - A/A + A/G vs G/G OR = 2.63), BCL2 (rs12454712) (log-additive model - *C allele, P = 0.005, OR = 1.38). Using the Monte Carlo method and Markov chains (APSampler), combinations of alleles/genotypes of the studied polymorphic loci associated with a high risk of MI were obtained, which, in addition to those identified during single-locus analysis, contained polymorphic variants of the genes CASP8, TP53, CAT, PON2, CRP, IL6, GSTP1. Among the combinations obtained, a pairwise analysis of possible non-linear interactions between the identified combinations of alleles/genotypes was carried out, which showed synergistic interactions of the polymorphic variants CX3CR1*A/G and CASP8*I/I, MSRA*C and CRP*C, CAT*C/T and MSRA*C, CAT*C/T and CX3CR1*A contributing to the development of MI. Based on the results obtained using multivariate logistic regression analysis, a predictive model was built to assess the risk of developing MI, the predictive ability of which reached the value AUC = 0.71 (AUC - area under the curve in ROC analysis).

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11667575PMC
http://dx.doi.org/10.18699/vjgb-24-87DOI Listing

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