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[Genetic Predisposition to Early Myocardial Infarction].
Goncharova, I A; Nazarenko, M S; Babushkina, N P; Markov, A V; Pecherina, T B; Kashtalap, V V; Tarasenko, N V; Ponasenko, A V; Barbarash, O L; Puzyrev, V P.
Affiliation
  • Goncharova IA; Research Institute for Medical Genetics, Tomsk, 634050 Russia.
  • Nazarenko MS; Research Institute for Complex Issues of Cardiovascular Diseases, Kemerovo, 650002 Russia.
  • Babushkina NP; irina.goncharova@medgenetics.ru.
  • Markov AV; Research Institute for Medical Genetics, Tomsk, 634050 Russia.
  • Pecherina TB; Research Institute for Complex Issues of Cardiovascular Diseases, Kemerovo, 650002 Russia.
  • Kashtalap VV; Siberian State Medical University, Tomsk, 634050 Russia.
  • Tarasenko NV; Research Institute for Medical Genetics, Tomsk, 634050 Russia.
  • Ponasenko AV; Research Institute for Medical Genetics, Tomsk, 634050 Russia.
  • Barbarash OL; Research Institute for Complex Issues of Cardiovascular Diseases, Kemerovo, 650002 Russia.
  • Puzyrev VP; Research Institute for Complex Issues of Cardiovascular Diseases, Kemerovo, 650002 Russia.
Mol Biol (Mosk) ; 54(2): 224-232, 2020.
Article in Ru | MEDLINE | ID: mdl-32392191
ABSTRACT
The aim of the study was to identify the features of the genetic structure of myocardial infarction (MI) susceptibility depending on age ("early MI" denoting individuals who had the first MI before the age of 60 years, and "late MI" the group of patients with the first "MI after 60 years"). A total of 355 patients were examined (n = 121 early MI and n = 234 late MI) and 285 residents of the Siberian region (as a control group). Genotyping of 58 single nucleotide variants (SNPs) was performed using mass spectrometry using the Agena (ex Sequenom) MassARRAY® System. Statistical analysis was performed using Statistica 8.0 ("StatSoft Inc.", USA), as well as the "stats" and "genetics" packages in the R environment. The regulatory potential of SNPs was evaluated using the rSNPBase online service (http//rsnp.psych.ac.cn/). eQTL loci were identified using data from the Genotype-Tissue Expression (GTEx) project (http//www.gtexportal.org/) and the Blood eQTL online service (https//genenetwork.nl/bloodeqtlbrowser/). The GG genotype of ITGA4 rs1143674, the CC genotype of CDKN2B-AS1 rs1333049, and the CC genotype of KIAA1462 rs3739998, are generally associated with MI. The AA genotype of ADAMDEC1 rs3765124 (OR = 2.03; 95% CI 1.23-3.33; p = 0.004) and the GG genotype of AQP2 rs2878771 (OR = 2.24; 95% CI 1.23-4.09; p = 0.006) are associated with the development of MI at an early age, and the TT genotype of TAS2R38 rs1726866 (OR = 1.82; 95% CI 1.11-2.89; p = 0.009) was the high-risk genotype for the late MI. Genetic variants associated with MI are regulatory SNP (rSNP) and affect the affinity of DNA binding to transcription factors, carry out post-transcriptional control of gene activity and change the level of gene expression in various tissues. Thus, early and late MI are based on both common genetic variants of ITGA4, CDKN2B-AS1, KIAA1462 genes and specific ones (ADAMDEC1 and AQP2 for early MI and TAS2R38 for late MI).
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Genetic Predisposition to Disease / Myocardial Infarction Type of study: Prognostic_studies Limits: Humans Language: Ru Journal: Mol Biol (Mosk) Year: 2020 Type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Genetic Predisposition to Disease / Myocardial Infarction Type of study: Prognostic_studies Limits: Humans Language: Ru Journal: Mol Biol (Mosk) Year: 2020 Type: Article