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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...
Autores principales: | , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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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 |
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author | 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 |
author_facet | 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 |
author_sort | Lazarenko, Victor |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8868589 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-88685892022-02-25 Comprehensive Statistical and Bioinformatics Analysis in the Deciphering of Putative Mechanisms by Which Lipid-Associated GWAS Loci Contribute to Coronary Artery Disease 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 Biomedicines Article 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. MDPI 2022-01-25 /pmc/articles/PMC8868589/ /pubmed/35203469 http://dx.doi.org/10.3390/biomedicines10020259 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article 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 Comprehensive Statistical and Bioinformatics Analysis in the Deciphering of Putative Mechanisms by Which Lipid-Associated GWAS Loci Contribute to Coronary Artery Disease |
title | Comprehensive Statistical and Bioinformatics Analysis in the Deciphering of Putative Mechanisms by Which Lipid-Associated GWAS Loci Contribute to Coronary Artery Disease |
title_full | Comprehensive Statistical and Bioinformatics Analysis in the Deciphering of Putative Mechanisms by Which Lipid-Associated GWAS Loci Contribute to Coronary Artery Disease |
title_fullStr | Comprehensive Statistical and Bioinformatics Analysis in the Deciphering of Putative Mechanisms by Which Lipid-Associated GWAS Loci Contribute to Coronary Artery Disease |
title_full_unstemmed | Comprehensive Statistical and Bioinformatics Analysis in the Deciphering of Putative Mechanisms by Which Lipid-Associated GWAS Loci Contribute to Coronary Artery Disease |
title_short | Comprehensive Statistical and Bioinformatics Analysis in the Deciphering of Putative Mechanisms by Which Lipid-Associated GWAS Loci Contribute to Coronary Artery Disease |
title_sort | comprehensive statistical and bioinformatics analysis in the deciphering of putative mechanisms by which lipid-associated gwas loci contribute to coronary artery disease |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8868589/ https://www.ncbi.nlm.nih.gov/pubmed/35203469 http://dx.doi.org/10.3390/biomedicines10020259 |
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