ArticleFrontiers in neurology2020
Identification of Co-expressed Genes Between Atrial Fibrillation and Stroke.
Article in Frontiers in neurology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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The trial behind it
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Who cites it
11 citing papers in PubMed, 20 citations in OpenAlex.
- Article
- GAS6-AS1, a long noncoding RNA, functions as a key candidate gene in atrial fibrillation related stroke determined by ceRNA network analysis and WGCNA.BMC medical genomics · 2023Article
- Article
- iTRAQ-Based Proteomic Analysis of APP Transgenic Mouse Urine Exosomes.International journal of molecular sciences · 2022Article
- Identification of genes and key pathways underlying the pathophysiological association between nonalcoholic fatty liver disease and atrial fibrillation.BMC medical genomics · 2022Article
- Analysis of expression profiles and bioinformatics suggests that plasma exosomal circular RNAs may be involved in ischemic stroke in the Chinese Han population.Metabolic brain disease · 2022Article
- Integrative identification of immune-related key genes in atrial fibrillation using weighted gene coexpression network analysis and machine learning.Frontiers in cardiovascular medicine · 2022Article
- Identification of Potential Key Biomarkers of Atrial Fibrillation and Their Correlation with Immune Infiltration in Atrial Tissue.Computational and mathematical methods in medicine · 2022Article
- TMAO Aggregates Neurological Damage Following Ischemic Stroke by Promoting Reactive Astrocytosis and Glial Scar FormationFrontiers in cellular neuroscience · 2021Article
- A Review of Biomarkers for Ischemic Stroke Evaluation in Patients With Non-valvular Atrial Fibrillation.Frontiers in cardiovascular medicine · 2021Review
- Patterns of Immune Infiltration and the Key Immune-Related Genes in Acute Type A Aortic Dissection in Bioinformatics Analyses.International journal of general medicine · 2021Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Atrial fibrillation (AF) increases the risk of ischemic stroke and systemic arterial embolism. However, the risk factors or predictors of stroke in AF patients have not been clarified. Therefore, it is necessary to find effective diagnostic and therapeutic targets. Two datasets were downloaded from the Gene Expression Omnibus (GEO) database. Differently expressed genes (DEGs) were identified between samples of atrial fibrillation without stroke and atrial fibrillation with stroke. Enrichment analysis of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) by Gene Set Enrichment Analysis (GSEA), construction and analysis of protein-protein interaction (PPI) network and significant module, and the receiver operator characteristic (ROC) curve analysis were performed. A total of 524 DEGs were common to both datasets. Analysis of KEGG pathways indicated that the top canonical pathways associated with DEGs were ubiquitin-mediated proteolysis, endocytosis, spliceosome, and so on. Ten hub genes (SMURF2, CDC42, UBE3A, RBBP6, CDC5L, NEDD4L, UBE2D2, UBE2B, UBE2I, and MAPK1) were identified from the PPI network and were significantly associated with a diagnosis of atrial fibrillation and stroke (AFST). In summary, a total of 524 DEGs and 10 hub genes were identified between samples of atrial fibrillation without stroke and atrial fibrillation with stroke. These genes may serve as the target of early diagnosis or treatment of AF complicated by stroke.
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