ArticleBiomedical engineering online2019
Potential biomarkers of acute myocardial infarction based on weighted gene co-expression network analysis.
Article in Biomedical engineering online, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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Who cites it
23 citing papers in PubMed.
- Molecular mechanisms of suxiao jiuxin pills in ameliorating post-acute myocardial infarction inflammatory response: a combined network pharmacology, Mendelian randomization, and experimental validation study.Frontiers in cardiovascular medicine · 2026Article
- Single-cell RNA sequencing pseudobulk analysis and machine learning identify candidate biomarkers for ischemic cardiomyopathy.Frontiers in cardiovascular medicine · 2026Article
- GFOD1 expression in clear cell renal cell carcinoma and its role in cancer cell proliferation, migration, and invasion.Discover oncology · 2025Article
- Molecular insight into the potential functional role of pseudoenzyme GFOD1 via interaction with NKIRAS2.Acta biochimica et biophysica Sinica · 2024Article
- Propofol regulates the progression of hepatocellular carcinoma via the POLR2L/TGF-β signaling pathway.Translational cancer research · 2024Article
- Explainable coronary artery disease prediction model based on AutoGluon from AutoML framework.Frontiers in cardiovascular medicine · 2024Article
- Differentially expressed platelet activation-related genes in dogs with stage B2 myxomatous mitral valve disease.BMC veterinary research · 2023Article
- Biomarkers: Promising and valuable tools towards diagnosis, prognosis and treatment of Covid-19 and other diseases.Heliyon · 2023Review
- Clinical value of combined plasma brain natriuretic peptide and serum cystatin C measurement on the prediction of heart failure in patients after acute myocardial infarction.Brazilian journal of medical and biological research = Revista brasileira de pesquisas medicas e biologica · 2023Article
- Article
- Transcription factor JDP2 activates PDE4B to participate in hypoxia/reoxygenation-induced H9c2 cell injury.Experimental and therapeutic medicine · 2022Article
- Potential biomarkers of acute myocardial infarction based on co-expression network analysis.Experimental and therapeutic medicine · 2022Article
- The Identification and Validation of Hub Genes Associated with Acute Myocardial Infarction Using Weighted Gene Co-Expression Network Analysis.Journal of cardiovascular development and disease · 2022Article
- Weighted Gene Coexpression Network Analysis Identifies Crucial Genes Involved in Coronary Atherosclerotic Heart Disease.Disease markers · 2022Article
- Analysis of Time Series Gene Expression and DNA Methylation Reveals the Molecular Features of Myocardial Infarction Progression.Frontiers in cardiovascular medicine · 2022Article
- Article
- Identification of key molecular markers of acute coronary syndrome using peripheral blood transcriptome sequencing analysis and mRNA-lncRNA co-expression network construction.Bioengineered · 2021Article
- Study on the interaction mechanism betweenAnnals of translational medicine · 2021Article
- HEMGN and SLC2A1 might be potential diagnostic biomarkers of steroid-induced osteonecrosis of femoral head: study based on WGCNA and DEGs screening.BMC musculoskeletal disorders · 2021Article
- 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
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Abstract
backgroundAcute myocardial infarction (AMI) is the common cause of mortality in developed countries. The feasibility of whole-genome gene expression analysis to identify outcome-related genes and dysregulated pathways remains unknown. Molecular marker such as BNP, CRP and other serum inflammatory markers have got the notice at this point. However, these biomarkers exhibit elevated levels in patients with thyroid disease, renal failure and congestive heart failure. In this study, three groups of microarray data sets (GES66360, GSE48060, GSE29532) were collected from GEO, a total of 99, 52 and 55 samples, respectively. Weighted gene co-expression network analysis (WGCNA) was performed to obtain a classifier which composed of related genes that best characterize the AMI.
resultsHere, this study obtained three groups of microarray data sets (GES66360, GSE48060, GSE29532) on AMI blood samples, a total of 99, 52 and 24 samples, respectively. In all, 4672 genes, 3185 genes, 3660 genes were identified in GSE66360, GSE48060, GSE60993 modules, respectively. We preformed WGCNA, GO and KEGG pathway enrichment analysis on these three data sets, finding function enrichment of the differential expression gene on inflammation and immune response. Transcriptome analysis were performed in AMI patients at four time points compared to CAD patients with no history of MI, to determine gene expression profiles and their possible changes during the recovery from myocardial infarction.
conclusionsThe results suggested that three overlapping genes (FGFBP2, GFOD1 and MLC1) between two modules could be a potential use of gene biomarkers for the diagnose of AMI.
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