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Identification of Risk Genes Associated with Myocardial Infarction—Big Data Analysis and Literature Review

Acute myocardial infarction occurs when blood supply to a particular coronary artery is cut off, causing ischemia or hypoxia and subsequent heart muscle destruction in the vascularized area. With a mortality rate of 17% per year, myocardial infarction (MI) is still one of the top causes of death glo...

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Autores principales: Tirdea, Cosmin, Hostiuc, Sorin, Moldovan, Horatiu, Scafa-Udriste, Alexandru
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9738549/
https://www.ncbi.nlm.nih.gov/pubmed/36499335
http://dx.doi.org/10.3390/ijms232315008
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author Tirdea, Cosmin
Hostiuc, Sorin
Moldovan, Horatiu
Scafa-Udriste, Alexandru
author_facet Tirdea, Cosmin
Hostiuc, Sorin
Moldovan, Horatiu
Scafa-Udriste, Alexandru
author_sort Tirdea, Cosmin
collection PubMed
description Acute myocardial infarction occurs when blood supply to a particular coronary artery is cut off, causing ischemia or hypoxia and subsequent heart muscle destruction in the vascularized area. With a mortality rate of 17% per year, myocardial infarction (MI) is still one of the top causes of death globally. Numerous studies have been done to identify the genetic risk factors for myocardial infarction, as a positive family history of heart disease is one of the most potent cardiovascular risk factors. The goal of this review is to compile all the information currently accessible in the literature on the genes associated with AMI. We performed a big data analysis of genes associated with acute myocardial infarction, using the following keywords: “myocardial infarction”, “genes”, “involvement”, “association”, and “risk”. The analysis was done using PubMed, Scopus, and Web of Science. Data from the title, abstract, and keywords were exported as text files and imported into an Excel spreadsheet. Its analysis was carried out using the VOSviewer v. 1.6.18 software. Our analysis found 28 genes which are mostly likely associated with an increased risk for AMI, including: PAI-1, CX37, IL18, and others. Also, a correlation was made between the results obtained in the big data analysis and the results of the review. The most important genes increasing the risk for AMI are lymphotoxin-a gene (LTA), LGALS2, LDLR, and APOA5. A deeper understanding of the underlying functional genomic circuits may present new opportunities for research in the future.
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spelling pubmed-97385492022-12-11 Identification of Risk Genes Associated with Myocardial Infarction—Big Data Analysis and Literature Review Tirdea, Cosmin Hostiuc, Sorin Moldovan, Horatiu Scafa-Udriste, Alexandru Int J Mol Sci Review Acute myocardial infarction occurs when blood supply to a particular coronary artery is cut off, causing ischemia or hypoxia and subsequent heart muscle destruction in the vascularized area. With a mortality rate of 17% per year, myocardial infarction (MI) is still one of the top causes of death globally. Numerous studies have been done to identify the genetic risk factors for myocardial infarction, as a positive family history of heart disease is one of the most potent cardiovascular risk factors. The goal of this review is to compile all the information currently accessible in the literature on the genes associated with AMI. We performed a big data analysis of genes associated with acute myocardial infarction, using the following keywords: “myocardial infarction”, “genes”, “involvement”, “association”, and “risk”. The analysis was done using PubMed, Scopus, and Web of Science. Data from the title, abstract, and keywords were exported as text files and imported into an Excel spreadsheet. Its analysis was carried out using the VOSviewer v. 1.6.18 software. Our analysis found 28 genes which are mostly likely associated with an increased risk for AMI, including: PAI-1, CX37, IL18, and others. Also, a correlation was made between the results obtained in the big data analysis and the results of the review. The most important genes increasing the risk for AMI are lymphotoxin-a gene (LTA), LGALS2, LDLR, and APOA5. A deeper understanding of the underlying functional genomic circuits may present new opportunities for research in the future. MDPI 2022-11-30 /pmc/articles/PMC9738549/ /pubmed/36499335 http://dx.doi.org/10.3390/ijms232315008 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 Review
Tirdea, Cosmin
Hostiuc, Sorin
Moldovan, Horatiu
Scafa-Udriste, Alexandru
Identification of Risk Genes Associated with Myocardial Infarction—Big Data Analysis and Literature Review
title Identification of Risk Genes Associated with Myocardial Infarction—Big Data Analysis and Literature Review
title_full Identification of Risk Genes Associated with Myocardial Infarction—Big Data Analysis and Literature Review
title_fullStr Identification of Risk Genes Associated with Myocardial Infarction—Big Data Analysis and Literature Review
title_full_unstemmed Identification of Risk Genes Associated with Myocardial Infarction—Big Data Analysis and Literature Review
title_short Identification of Risk Genes Associated with Myocardial Infarction—Big Data Analysis and Literature Review
title_sort identification of risk genes associated with myocardial infarction—big data analysis and literature review
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9738549/
https://www.ncbi.nlm.nih.gov/pubmed/36499335
http://dx.doi.org/10.3390/ijms232315008
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