ArticlePloS one2020
Weighted gene co-expression network analysis identified six hub genes associated with rupture of intracranial aneurysms.
Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- WTAP-mediated m6A modification on BASP1 mRNA contributes to ferroptosis in AAA.General thoracic and cardiovascular surgery · 2025Article
- Familial Hyperkalemic Hypertension.Comprehensive Physiology · 2024Review
- Hub genes and pathways related to caries-free dental biofilm: clinical metatranscriptomic study.Clinical oral investigations · 2023Article
- Review
- Identification of hub genes significantly linked to subarachnoid hemorrhage and epilepsyFrontiers in neurology · 2023Article
- microRNAs in Subarachnoid Hemorrhage (Review of Literature).Journal of clinical medicine · 2022Review
- A two-stage hybrid gene selection algorithm combined with machine learning models to predict the rupture status in intracranial aneurysms.Frontiers in neuroscience · 2022Article
- Identification of upregulated NF-κB inhibitor alpha and IRAK3 targeting lncRNA following intracranial aneurysm rupture-induced subarachnoid hemorrhage.BMC neurology · 2021Article
- Investigation of molecular regulation mechanism under the pathophysiology of subarachnoid hemorrhage.Open life sciences · 2021Article
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Authors and funding
8 authors.
Funding
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Abstract
Intracranial aneurysms (IAs) are characterized by localized dilation or ballooning of a cerebral artery. When IAs rupture, blood leaks into the space around the brain to create a subarachnoid hemorrhage. The latter is associated with a higher risk of disability and mortality. The aims of this study were to gain greater insight into the pathogenesis of ruptured IAs, and to clarify whether identified hub genes represent potential biological markers for assessing the likelihood of IA progression and rupture. Briefly, the GSE36791 and GSE73378 datasets from the National Center of Biotechnology Information Gene Expression Omnibus database were reanalyzed and subjected to a weighted gene co-expression network analysis to test the association between gene sets and clinical features. The clinical significance of these genes as potential biomarkers was also examined, with their expression validated by quantitative real-time PCR. A total of 14 co-expression modules and 238 hub genes were identified. In particular, three modules (labeled turquoise, blue, and brown) were found to highly correlate with IA rupture events. Additionally, six potential biomarkers were identified (BASP1, CEBPB, ECHDC2, GZMK, KLHL3, and SLC2A3), which are strongly associated with the progression and rupture of IAs. Taken together, these findings provide novel insights into potential molecular mechanisms responsible for IAs and they highlight the potential for these particular genes to serve as biomarkers for monitoring IA rupture.
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