ArticleFrontiers in cardiovascular medicine2022
Integrated Bioinformatics-Based Analysis of Hub Genes and the Mechanism of Immune Infiltration Associated With Acute Myocardial Infarction.
Article in Frontiers in cardiovascular medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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Who cites it
21 citing papers in PubMed, 45 citations in OpenAlex.
- Rosa davurica Pall. as a Functional Food in Ameliorating Acute Myocardial Ischemia: An Integrated Multi-Omics Study on TNF-α and Oxidative Stress.Chemistry & biodiversity · 2026Article
- Integrated transcriptomic and functional analysis reveals overlapping pathways in lung adenocarcinoma and chronic obstructive pulmonary disease.Hereditas · 2025Article
- Integration of Single Cell and Bulk RNA-Sequencing Reveals Key Genes and Immune Cell Infiltration to Construct a Predictive Model and Identify Drug Targets in Endometriosis.Journal of inflammation research · 2025Article
- Exploring the Potential Regulatory Mechanisms of Mitophagy in Ischemic Cardiomyopathy.International journal of general medicine · 2025Article
- Neutrophil-related IL1R2 gene predicts the occurrence and early progression of myocardial infarction.Frontiers in cardiovascular medicine · 2025Article
- Identification and validation of key genes associated with cell senescence in acute myocardial infarction.Frontiers in cardiovascular medicine · 2025Article
- Integrating machine learning and single-cell transcriptomic analysis to identify potential biomarkers and analyze immune features of ischemic stroke.Scientific reports · 2024Article
- FASLG as a Key Member of Necroptosis Participats in Acute Myocardial Infarction by Regulating Immune Infiltration.Cardiology research · 2024Article
- Unraveling shared molecular signatures and potential therapeutic targets linking psoriasis and acute myocardial infarction.Scientific reports · 2024Article
- Leveraging a neutrophil-derived PCD signature to predict and stratify patients with acute myocardial infarction: from AI prediction to biological interpretation.Journal of translational medicine · 2024Article
- Exploring T-cell exhaustion features in Acute myocardial infarction for a Novel Diagnostic model and new therapeutic targets by bio-informatics and machine learning.BMC cardiovascular disorders · 2024Article
- Comprehensive bioinformatics analytics andAging · 2024Article
- Article
- Identification of key genes associated with acute myocardial infarction using WGCNA and two-sample mendelian randomization study.PloS one · 2024Article
- Identification of the feature genes involved in cytokine release syndrome in COVID-19.PloS one · 2024Article
- Identification and immunoinfiltration analysis of key genes in ulcerative colitis using WGCNA.PeerJ · 2024Article
- Neutrophil extracellular trap is an important connection between hemodialysis and acute myocardial infarction.Renal failure · 2023Article
- M6A regulator methylation patterns and characteristics of immunity in acute ST-segment elevation myocardial infarction.Scientific reports · 2023Article
- Machine learning-based mRNA signature in early acute myocardial infarction patients: the perspective toward immunological, predictive, and personalized.Functional & integrative genomics · 2023Article
- Construction of the ceRNA network in the progression of acute myocardial infarction.American journal of cardiovascular disease · 2022Article
Corrections and comments
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Authors and funding
8 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Acute myocardial infarction (AMI) is a fatal disease that causes high morbidity and mortality. It has been reported that AMI is associated with immune cell infiltration. Now, we aimed to identify the potential diagnostic biomarkers of AMI and uncover the immune cell infiltration profile of AMI. Methods: From the Gene Expression Omnibus (GEO) data set, three data sets (GSE48060, GSE60993, and GSE66360) were downloaded. Differentially expressed genes (DEGs) from AMI and healthy control samples were screened. Furthermore, DEGs were performed Results: A total of 71 DEGs were identified. These DEGs were mainly enriched in immune response and immune-related pathways. Toll-like receptor 2 (TLR2), interleukin-1B (IL1B), leukocyte immunoglobulin-like receptor subfamily B2 (LILRB2), Fc fragment of IgE receptor Ig (FCER1G), formyl peptide receptor 1 (FPR1), and matrix metalloproteinase 9 (MMP9) were identified as diagnostic markers with the value of Conclusion: TLR2, IL1B, LILRB2, FCER1G, FPR1, and MMP9 are involved in the process of AMI, which can be used as molecular biomarkers for the screening and diagnosis of AMI. In addition, the immune system plays a vital role in the occurrence and progression of AMI.
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