ArticleMedicine2017
Biomarkers identification for acute myocardial infarction detection via weighted gene co-expression network analysis.
Article in Medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed, 25 citations in OpenAlex.
- Guanylate-binding protein 5: a promising biomarker and therapeutic target.Infection and immunity · 2025Review
- Expression characteristics of lipid metabolism-related genes and correlative immune infiltration landscape in acute myocardial infarction.Scientific reports · 2024Article
- Identifying Genes Related to Acute Myocardial Infarction Based on Network Control Capability.Genes · 2022Article
- Annexin-A1: The culprit or the solution?Immunology · 2022Review
- Potential biomarkers of acute myocardial infarction based on co-expression network analysis.Experimental and therapeutic medicine · 2022Article
- Construction of the ceRNA network in the progression of acute myocardial infarction.American journal of cardiovascular disease · 2022Article
- Systematic Bioinformatics Analysis Based on Public and Second-Generation Sequencing Transcriptome Data: A Study on the Diagnostic Value and Potential Mechanisms of Immune-Related Genes in Acute Myocardial Infarction.Frontiers in cardiovascular medicine · 2022Article
- Integrated Bioinformatics-Based Analysis of Hub Genes and the Mechanism of Immune Infiltration Associated With Acute Myocardial Infarction.Frontiers in cardiovascular medicine · 2022Article
- Screening for Regulatory Network of miRNA-Inflammation, Oxidative Stress and Prognosis-Related mRNA in Acute Myocardial Infarction: An in silico and Validation Study.International journal of general medicine · 2022Article
- Dietary switch to Western diet induces hypothalamic adaptation associated with gut microbiota dysbiosis in rats.International journal of obesity (2005) · 2021Article
- Regulation of Inflammation and Oxidative Stress by Formyl Peptide Receptors in Cardiovascular Disease Progression.Life (Basel, Switzerland) · 2021Review
- Identification of key gene modules and pathways of human platelet transcriptome in acute myocardial infarction patients through co-expression network.American journal of translational research · 2021Article
- Uncovering potential differentially expressed miRNAs and targeted mRNAs in myocardial infarction based on integrating analysis.Molecular medicine reports · 2020Article
- Key miRNAs associated with memory and learning disorder upon exposure to sevoflurane determined by RNA sequencing.Molecular medicine reports · 2020Article
- Identification of Post-myocardial Infarction Blood Expression Signatures Using Multiple Feature Selection Strategies.Frontiers in physiology · 2020Article
- Identification of key genes involved in myocardial infarction.European journal of medical research · 2019Article
- Weighted Gene Co-Expression Network Analysis Identifies Critical Genes in the Development of Heart Failure After Acute Myocardial Infarction.Frontiers in genetics · 2019Article
Corrections and comments
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Authors and funding
5 authors at 1 institution in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The study aimed to seek potential biomarkers for acute myocardial infarction (AMI) detection and treatment.The dataset GSE48060 was used, consisting of 52 peripheral blood samples (31 AMI samples and 21 normal controls). By limma package, differentially expressed genes (DEGs) between 2 kinds of samples were identified, followed by enrichment analysis, subpathway analysis, protein-protein interaction (PPI) network analysis, and transcription factor network (TFN) analysis. Weighted gene co-expression network analysis was used to further extract key modules relating to AMI, followed by enrichment and TFN analyses. Expression validation was performed via meta-analysis of 2 datasets, GSE22229 and GSE29111.A set of 428 DEGs in AMI were screened out, and the upregulated toll-like receptor (TLR) family genes (TLR1, TLR2, and TLR10) were enriched in wound response, immune response and inflammatory response functions, and downregulated genes (GBP5, CXCL5, GZMA, CCL5, and CCL4) were correlated with immune response. CCL5, GZMA, GZMB, TLR2, and formyl peptide receptor 1 (FPR1) were predicted as crucial nodes in the PPI network. Signal transducer and activator of transcription 1 (STAT1) was the key transcription factor (TF) with multiple targets. The grey module was highly related to AMI. Genes in this module were closely related to regulation of macrophage activation, and spermatogenic leucine zipper 1 (SPZ1) was identified as a TF. Expressions of TLR2 and FPR1 were confirmed via the integrated matrix.Several potential biomarkers for AMI detection were identified, such as GZMB, GBP5, FPR1, TLR2, STAT1, and SPZ1. They might exert their functions via regulation of immune and inflammation responses. Genes in grey module play significant roles in AMI via regulation of macrophage activation.
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