ReviewInternational journal of molecular sciences2022
Identification of Risk Genes Associated with Myocardial Infarction-Big Data Analysis and Literature Review.
Review in International journal of molecular sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed, 24 citations in OpenAlex.
- Accelerated Biological Aging, Neurodegenerative Disease, and Mortality in Cardiovascular Disease Patients: Mediation and Modification Analysis.CNS neuroscience & therapeutics · 2026Article
- Chronic β-Blockade and Systemic Homeostasis: Molecular Integration of Cardiorenal and Immune Pathways, a Narrative Review.Biomolecules · 2025Review
- Transcription Factor SOX10 Improves Migration and Homing of MSCs After Myocardial Infarction by Upregulating CXCR4.Stem cells international · 2025Article
- Molecular Study of Sudden Cardiac Death.International journal of molecular sciences · 2024Article
- Association ofGenetic testing and molecular biomarkers · 2024Article
- A Mass Spectrometry-Based Proteome Study of Twin Pairs Discordant for Incident Acute Myocardial Infarction within Three Years after Blood Sampling Suggests Novel Biomarkers.International journal of molecular sciences · 2024Article
- CYP2C19 Poor Metabolizer Status and High System Inflammation Response Index are Independent Risk Factors for Premature Myocardial Infarction: A Hospital-Based Retrospective Study.International journal of general medicine · 2024Article
- Integrative Genetic Approach Facilitates Precision Strategies for Acute Myocardial Infarction.Genes · 2023Review
- Identification of shared fatty acid metabolism related signatures in dilated cardiomyopathy and myocardial infarction.Future science OA · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.