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Comprehensive Statistical and Bioinformatics Analysis in the Deciphering of Putative Mechanisms by Which Lipid-Associated GWAS Loci Contribute to Coronary Artery Disease

The study was designed to evaluate putative mechanisms by which lipid-associated loci identified by genome-wide association studies (GWAS) are involved in the molecular pathogenesis of coronary artery disease (CAD) using a comprehensive statistical and bioinformatics analysis. A total of 1700 unrela...

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Detalles Bibliográficos
Autores principales: Lazarenko, Victor, Churilin, Mikhail, Azarova, Iuliia, Klyosova, Elena, Bykanova, Marina, Ob’edkova, Natalia, Churnosov, Mikhail, Bushueva, Olga, Mal, Galina, Povetkin, Sergey, Kononov, Stanislav, Luneva, Yulia, Zhabin, Sergey, Polonikova, Anna, Gavrilenko, Alina, Saraev, Igor, Solodilova, Maria, Polonikov, Alexey
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8868589/
https://www.ncbi.nlm.nih.gov/pubmed/35203469
http://dx.doi.org/10.3390/biomedicines10020259
Descripción
Sumario:The study was designed to evaluate putative mechanisms by which lipid-associated loci identified by genome-wide association studies (GWAS) are involved in the molecular pathogenesis of coronary artery disease (CAD) using a comprehensive statistical and bioinformatics analysis. A total of 1700 unrelated individuals of Slavic origin from the Central Russia, including 991 CAD patients and 709 healthy controls were examined. Sixteen lipid-associated GWAS loci were selected from European studies and genotyped using the MassArray-4 system. The polymorphisms were associated with plasma lipids such as total cholesterol (rs12328675, rs4846914, rs55730499, and rs838880), LDL-cholesterol (rs3764261, rs55730499, rs1689800, and rs838880), HDL-cholesterol (rs3764261) as well as carotid intima-media thickness/CIMT (rs12328675, rs11220463, and rs1689800). Polymorphisms such as rs4420638 of APOC1 (p = 0.009), rs55730499 of LPA (p = 0.0007), rs3136441 of F2 (p < 0.0001), and rs6065906 of PLTP (p = 0.002) showed significant associations with the risk of CAD, regardless of sex, age, and body mass index. A majority of the observed associations were successfully replicated in large independent cohorts. Bioinformatics analysis allowed establishing (1) phenotype-specific and shared epistatic gene–gene and gene–smoking interactions contributing to all studied cardiovascular phenotypes; (2) lipid-associated GWAS loci might be allele-specific binding sites for transcription factors from gene regulatory networks controlling multifaceted molecular mechanisms of atherosclerosis.