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Integrating Genes Affecting Coronary Artery Disease in Functional Networks by Multi-OMICs Approach

Coronary artery disease (CAD) and myocardial infarction (MI) remain among the leading causes of mortality worldwide, urgently demanding a better understanding of disease etiology, and more efficient therapeutic strategies. Genetic predisposition as well as the environment and lifestyle are thought t...

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Autores principales: Vilne, Baiba, Schunkert, Heribert
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6056735/
https://www.ncbi.nlm.nih.gov/pubmed/30065929
http://dx.doi.org/10.3389/fcvm.2018.00089
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author Vilne, Baiba
Schunkert, Heribert
author_facet Vilne, Baiba
Schunkert, Heribert
author_sort Vilne, Baiba
collection PubMed
description Coronary artery disease (CAD) and myocardial infarction (MI) remain among the leading causes of mortality worldwide, urgently demanding a better understanding of disease etiology, and more efficient therapeutic strategies. Genetic predisposition as well as the environment and lifestyle are thought to contribute to disease risk. It is likely that non-linear and complex interactions occur between these multiple factors, involving simultaneous pathological changes in diverse cell types, tissues, and organs, at multiple molecular levels. Recent technological advances have exponentially expanded the breadth of available -omics data, from genome, epigenome, transcriptome, proteome, metabolome to even the microbiome. Integration of multiple layers of information across several -omics domains, i.e., the so-called multi-omics approach, currently holds the promise as a path toward precision medicine. Indeed, a more meaningful interpretation of genotype-phenotype relationships and the development of successful therapeutics tailored to individual patients are urgently needed. In this review, we will summarize recent findings and applications of integrative multi-omics in elucidating the etiology of CAD/MI; with a special focus on established disease susceptibility loci sequentially identified in genome-wide association studies (GWAS) over the last 10 years. Moreover, in addition to the autosomal genome, we will also consider the genetic variation in our “second genome”—the mitochondrial genome. Finally, we will summarize the current challenges in the field and point to future research directions required in order to successfully and effectively apply these approaches for precision medicine.
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spelling pubmed-60567352018-07-31 Integrating Genes Affecting Coronary Artery Disease in Functional Networks by Multi-OMICs Approach Vilne, Baiba Schunkert, Heribert Front Cardiovasc Med Cardiovascular Medicine Coronary artery disease (CAD) and myocardial infarction (MI) remain among the leading causes of mortality worldwide, urgently demanding a better understanding of disease etiology, and more efficient therapeutic strategies. Genetic predisposition as well as the environment and lifestyle are thought to contribute to disease risk. It is likely that non-linear and complex interactions occur between these multiple factors, involving simultaneous pathological changes in diverse cell types, tissues, and organs, at multiple molecular levels. Recent technological advances have exponentially expanded the breadth of available -omics data, from genome, epigenome, transcriptome, proteome, metabolome to even the microbiome. Integration of multiple layers of information across several -omics domains, i.e., the so-called multi-omics approach, currently holds the promise as a path toward precision medicine. Indeed, a more meaningful interpretation of genotype-phenotype relationships and the development of successful therapeutics tailored to individual patients are urgently needed. In this review, we will summarize recent findings and applications of integrative multi-omics in elucidating the etiology of CAD/MI; with a special focus on established disease susceptibility loci sequentially identified in genome-wide association studies (GWAS) over the last 10 years. Moreover, in addition to the autosomal genome, we will also consider the genetic variation in our “second genome”—the mitochondrial genome. Finally, we will summarize the current challenges in the field and point to future research directions required in order to successfully and effectively apply these approaches for precision medicine. Frontiers Media S.A. 2018-07-17 /pmc/articles/PMC6056735/ /pubmed/30065929 http://dx.doi.org/10.3389/fcvm.2018.00089 Text en Copyright © 2018 Vilne and Schunkert. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Cardiovascular Medicine
Vilne, Baiba
Schunkert, Heribert
Integrating Genes Affecting Coronary Artery Disease in Functional Networks by Multi-OMICs Approach
title Integrating Genes Affecting Coronary Artery Disease in Functional Networks by Multi-OMICs Approach
title_full Integrating Genes Affecting Coronary Artery Disease in Functional Networks by Multi-OMICs Approach
title_fullStr Integrating Genes Affecting Coronary Artery Disease in Functional Networks by Multi-OMICs Approach
title_full_unstemmed Integrating Genes Affecting Coronary Artery Disease in Functional Networks by Multi-OMICs Approach
title_short Integrating Genes Affecting Coronary Artery Disease in Functional Networks by Multi-OMICs Approach
title_sort integrating genes affecting coronary artery disease in functional networks by multi-omics approach
topic Cardiovascular Medicine
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6056735/
https://www.ncbi.nlm.nih.gov/pubmed/30065929
http://dx.doi.org/10.3389/fcvm.2018.00089
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