ArticleCancer gene therapy2015
Identification of crucial genes in intracranial aneurysm based on weighted gene coexpression network analysis.
Article in Cancer gene therapy, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 24 citations in OpenAlex.
- A Transcriptomic Comparative Study of Cranial Vasculature.Translational stroke research · 2024Article
- Comprehensive analysis of mitochondrial dysfunction and necroptosis in intracranial aneurysms from the perspective of predictive, preventative, and personalized medicine.Apoptosis : an international journal on programmed cell death · 2023Article
- Review
- High-ThroughputFrontiers in oncology · 2021Article
- Weighted Co-Expression Network Analysis Identifies RNF181 as a Causal Gene of Coronary Artery Disease.Frontiers in genetics · 2021Article
- Identification and validation of key genes mediating intracranial aneurysm rupture by weighted correlation network analysis.Annals of translational medicine · 2020Article
- Weighted gene co-expression network analysis revealed key biomarkers associated with the diagnosis of hypertrophic cardiomyopathy.Hereditas · 2020Article
- Identification of Four Potential Biomarkers Associated With Coronary Artery Disease in Non-diabetic Patients by Gene Co-expression Network Analysis.Frontiers in genetics · 2020Article
- Identification of key gene modules for human osteosarcoma by co-expression analysis.World journal of surgical oncology · 2018Article
- Weighted Gene Co-expression Network Analysis Identifies FKBP11 as a Key Regulator in Acute Aortic Dissection through a NF-kB Dependent Pathway.Frontiers in physiology · 2017Article
Corrections and comments
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Authors and funding
6 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The rupture of intracranial aneurysm (IA) is the leading cause for devastating subarachnoid hemorrhage. This study aimed to investigate genes related to IA and potential diagnosis targets. Two data sets (GSE15629 and GSE54083) were downloaded from Gene Expression Omnibus database. GSE15629 contained eight RI (ruptured IA), six UI (unruptured IA) and five control IA samples. GSE54083 included 8 RI, 5 UI and 10 superficial temporal artery samples. In total, 452 differentially expressed genes (DEGs) between RI and control, and 570 DEGs between UI and control, were identified. Protein-protein interaction networks for two kinds of DEGs related to RI and UI were constructed, respectively. Module networks were searched for DEGs related to RI or UI based on WGCNA (weighted gene coexpression network analysis). In the significant modules, FOS, CCL2, COL4A2 and CXCL5 were screened as crucial nodes with high degrees. Among them, FOS and CCL2 were enriched in immune response and COL4A2 was involved in the ECM (extracellular matrix) pathway, whereas CXCL5 was related to cytokine-cytokine receptor pathway. Taken together, FOS, CCL2, COL4A2 and CXCL5 might participate in the pathogenesis of RI or UI, and could serve as potential diagnosis targets.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.