ArticleFrontiers in public health2022
Identification of Five Hub Genes Based on Single-Cell RNA Sequencing Data and Network Pharmacology in Patients With Acute Myocardial Infarction.
Article in Frontiers in public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.
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Who cites it
24 citing papers in PubMed, 1 synthesis or guideline pooled it, 27 citations in OpenAlex.
- Bioinformatics Analysis Reveals HIST1H2BH as a Novel Diagnostic Biomarker for Atrial Fibrillation-Related Cardiogenic Thromboembolic Stroke.Molecular biotechnology · 2025Pooled it
- Multi target effects of Allium macrostemon against myocardial infarction: an integrated network pharmacology, molecular docking, and experimental study.Journal of thrombosis and thrombolysis · 2026Article
- Prognostic and therapeutic implications of PSMD14 in hepatocellular carcinoma: an integrative analysis of transcriptomic and single-cell profiles.Translational cancer research · 2026Article
- Identification of PANoptosis-related hub genes in acute myocardial infarction: diagnostic potential, immune correlates, and therapeutic insights.Journal of cardiothoracic surgery · 2026Article
- Cell-Type-Resolved Acetylation Regulator Atlas Defines Immune Endotypes and Druggable Vulnerabilities in Psoriasis.Biomedicines · 2026Article
- Exploration of SOCS3 and HSPA1A in PANoptosis during acute myocardial infarction and chronic kidney disease.Frontiers in cellular and infection microbiology · 2026Article
- Identification and Analysis of PANoptosis Associated with Coronary Artery Disease Using Integrated Bioinformatics Methods.Iranian journal of biotechnology · 2026Article
- Identification of key genes associated with cellular aging and mitochondria in acute myocardial infarction.Scientific reports · 2025Article
- Identification of cell specific biomarkers for intellectual disability via single cell RNA sequencing and transcriptomic bioinformatics approaches.Scientific reports · 2025Article
- Single-cell Analysis Highlights Anti-apoptotic Subpopulation Promoting Malignant Progression and Predicting Prognosis in Bladder Cancer.Cancer informatics · 2025Article
- Peripheral blood memory T cells and follicular helper T cells as potential biomarkers for assessing disease severity and in-hospital outcomes in acute myocardial infarction patients.American journal of translational research · 2025Article
- Neutrophil-related IL1R2 gene predicts the occurrence and early progression of myocardial infarction.Frontiers in cardiovascular medicine · 2025Article
- The immune-inflammation factor is associated with diabetic nephropathy: evidence from NHANES 2013-2018 and GEO database.Scientific reports · 2024Article
- Article
- Single-cell RNA sequencing reveals hub genes of myocardial infarction-associated endothelial cells.BMC cardiovascular disorders · 2024Article
- Exploring the pathogenesis and key genes associated of acute myocardial infarction complicated with Alzheimer's disease.Scientific reports · 2024Article
- Identification of key genes associated with acute myocardial infarction using WGCNA and two-sample mendelian randomization study.PloS one · 2024Article
- Identifying potential drug targets for myocardial infarction through Mendelian randomization.PloS one · 2024Article
- Role of Pericytes in Cardiomyopathy-Associated Myocardial Infarction Revealed by Multiple Single-Cell Sequencing Analysis.Biomedicines · 2023Article
- New discoveries in the field of metabolism by applying single-cell and spatial omics.Journal of pharmaceutical analysis · 2023Review
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Authors and funding
6 authors at 3 institutions in 1 country.
Funding
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Abstract
Acute myocardial infarction (AMI) has a high mortality. The single-cell RNA sequencing (scRNA-seq) method was used to analyze disease heterogeneity at the single-cell level. From the Gene Expression Omnibus (GEO) database (GSE180678), AMI scRNA-seq were downloaded and preprocessed by the Seurat package. Gene expression data came from GSE182923. Cell cluster analysis was conducted. Cell types were identified. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analyses were performed on hub genes. Drugs were predicted by protein-protein interaction (PPI) and molecular docking. In total, 7 cell clusters were defined based on the scRNA-seq dataset, and the clusters were labeled as 5 cell types by marker genes. Hematopoietic stem cell types as a differential subgroups were higher in AMI than in healthy tissues. From available databases and PPI analysis, 52 common genets were identified. Based on 52 genes, 5 clusters were obtained using the MCODE algorithm, and genes in these 5 clusters involved in immune and inflammatory pathways were determined. Correlation analysis showed that hematopoietic stem cell types were negatively correlated with ATM, CARM1, and CASP8 but positively correlated with CASP3 and PPARG. This was reversed with immune cells. Molecular docking analysis showed that DB05490 had the lowest docking score with PPARG. We identified 5 hub genes (ATM, CARM1, CASP8, CASP3, and PPARG) involved in AMI progression. Compound DB05490 was a potential inhibitor of PPAG.
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