ArticleJournal of thoracic disease2020
Bioinformatics analysis of key genes and miRNAs associated with Stanford type A aortic dissection.
Article in Journal of thoracic disease, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
7 citing papers in PubMed, 11 citations in OpenAlex.
- Article
- Progression of Thoracic Aortic Dissection Is Aggravated by the hsa_circ_0007386/miR-1271-5P/IGF1R/AKT Axis via Induction of Arterial Smooth Muscle Cell Apoptosis.Biomedicines · 2023Article
- MicroRNA-126-3p/5p and Aortic Stiffness in Patients with Turner Syndrome.Children (Basel, Switzerland) · 2022Article
- Identification of novel potential biomarkers in infantile hemangioma via weighted gene co-expression network analysis.BMC pediatrics · 2022Article
- Bioinformatics Analysis Reveals Cell Cycle-Related Gene Upregulation in Ascending Aortic Tissues From Murine Models.Frontiers in genetics · 2022Article
- Crucial Genes in Aortic Dissection Identified by Weighted Gene Coexpression Network Analysis.Journal of immunology research · 2022Article
- Analysis of Hub Genes and the Mechanism of Immune Infiltration in Stanford Type a Aortic Dissection.Frontiers in cardiovascular medicine · 2021Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAortic dissection is one of the most detrimental cardiovascular diseases with a high risk of mortality and morbidity. This study aimed to examine the key genes and microRNAs associated with Stanford type A aortic dissection (AAD).
methodsThe expression data of AAD and healthy samples were downloaded from two microarray datasets in the Gene Expression Omnibus (GEO) database to identify highly preserved modules by weighted gene co-expression network analysis (WGCNA). Differentially expressed genes (DEGs) and differentially expressed miRNAs (DEmiRNAs) were selected and functionally annotated. The predicted interactions between the DEGs and DEmiRNAs were further illustrated.
resultsIn two highly preserved modules, 459 DEGs were identified. These DEGs were functionally enriched in the HIF1, Notch, and PI3K/Akt pathways. Furthermore, 6 DEmiRNAs that were enriched in the regulation of vasculature development and HIF1 pathway, were predicted to target 23 DEGs.
conclusionsOur study presented several promising modulators, both DEGs and DEmiRNAs, as well as possible pathological pathways for AAD, which narrows the scope for further fundamental research.
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