Dataset Information

Integrated analysis of microarray data to identify the genes critical for the rupture of intracranial aneurysm.

ABSTRACT: Intracranial aneurysm (IA) is a localized dilation of the blood vessel. The present study was designed to explore the mechanisms of rupture of IA. GSE13353 (including 11 ruptured and 8 unruptured IA samples) and GSE15629 (including 8 ruptured and 6 unruptured IA samples) were downloaded from the Gene Expression Omnibus database. The differentially expressed genes (DEGs) identified using limma and MetaDE packages were merged, and a protein-protein interaction (PPI) network analysis was performed using Cytoscape software. Pathway enrichment analysis was performed for the nodes of the PPI network using the fisher algorithm. The 100 most prominent genes in the network were designated candidate genes and a hierarchical clustering analysis was performed. The tune.svm function of e1071 package was used to construct a support vector machine (SVM) classifier, and the Candidate Cancer Gene Database was applied to analyze the characterization of gene-associated cancer. Furthermore, the genes involved in the SVM classifier were assessed via principal component analysis (PCA). In the ruptured samples, 1,292 DEGs and 1,029 DEGs separately were identified by limma and MetaDE packages. The 100 most prominent genes in the network included fibronectin 1 (FN1), amyloid ? (A4) precursor protein (APP), nuclear RNA export factor 1 (NXF1) and signal transducer and activator of transcription 3 (STAT3). Pathway enrichment analysis identified that toll-like receptor 3 (TLR3) was enriched in the Toll-like receptor signaling pathway. A total of 15 genes (including FN1) were used to construct the SVM classifier. NXF1 was identified to be associated with Nervous System Cancer. PCA revealed that APP, NXF1 and STAT3 were the 3 principal components. TLR3, FN1, APP, NXF1 and STAT3 may affect the rupture of IA.

SUBMITTER: Wei L

PROVIDER: S-EPMC5840557 | biostudies-literature | 2018 Apr

REPOSITORIES: biostudies-literature

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Integrated analysis of microarray data to identify the genes critical for the rupture of intracranial aneurysm.

Wei Liang L Wang Qi Q Zhang Yanfei Y Yang Cheng C Guan Hongxin H Jiang Jianxin J Sun Zhiyang Z

Oncology letters 20180202 4

Intracranial aneurysm (IA) is a localized dilation of the blood vessel. The present study was designed to explore the mechanisms of rupture of IA. GSE13353 (including 11 ruptured and 8 unruptured IA samples) and GSE15629 (including 8 ruptured and 6 unruptured IA samples) were downloaded from the Gene Expression Omnibus database. The differentially expressed genes (DEGs) identified using limma and MetaDE packages were merged, and a protein-protein interaction (PPI) network analysis was performed ...[more]

PMID: 29552131

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Project description:Intracranial aneurysms (IAs) may cause lethal subarachnoid hemorrhage upon rupture, but the molecular mechanisms are poorly understood. The aims of this study were to analyze the transcriptional profiles to explore the functions and regulatory networks of differentially expressed genes (DEGs) in IA rupture by bioinformatics methods and to identify the underlying mechanisms. In this study, 1,471 DEGs were obtained, of which 619 were upregulated and 852 were downregulated. Gene enrichment analysis showed that the DEGs were mainly enriched in the inflammatory response, immune response, neutrophil chemotaxis, and macrophage differentiation. Related pathways include the regulation of actin cytoskeleton, leukocyte transendothelial migration, nuclear factor κB signaling pathway, Toll-like receptor signaling pathway, tumor necrosis factor signaling pathway, and chemokine signaling pathway. The enrichment analysis of 20 hub genes, subnetworks, and significant enrichment modules of weighted gene coexpression network analysis showed that the inflammatory response and immune response had a causal relationship with the rupture of unruptured IAs (UIAs). Next, the CIBERSORT method was used to analyze immune cell infiltration into ruptured IAs (RIAs) and UIAs. Macrophage infiltration into RIAs increased significantly compared with that into UIAs. The result of principal component analysis revealed that there was a difference between RIAs and UIAs in immune cell infiltration. A 4-gene immune-related risk model for IA rupture (IRMIR), containing CXCR4, CXCL3, CX3CL1, and CXCL16, was established using the glmnet package in R software. The receiver operating characteristic value revealed that the model represented an excellent clinical situation for potential application. Enzyme-linked immunosorbent assay was performed and showed that the concentrations of CXCR4 and CXCL3 in serum from RIA patients were significantly higher than those in serum from UIA patients. Finally, a competing endogenous RNA network was constructed to provide a potential explanation for the mechanism of immune cell infiltration into IAs. Our findings highlighted the importance of immune cell infiltration into RIAs, providing a direction for further research.

Project description:BackgroundRupture of intracranial aneurysm (IA) is the leading cause of subarachnoid hemorrhage. However, there are few pharmacological therapies available for the prevention of IA rupture. Therefore, exploring the molecular mechanisms which underlie IA rupture and identifying the potential molecular targets for preventing the rupture of IA is of vital importance.MethodsWe used the Gene Expression Omnibus (GEO) datasets GSE13353, GSE15629, and GSE54083 in our study. The 3 datasets were merged and normalized. Differentially expressed gene (DEG) screening and weighted correlation network analysis (WGCNA) were conducted. The co-expression patterns between ruptured IA samples and unruptured IA samples were compared. Then, the DEGs were mapped into the whole co-expression network of ruptured IA samples, and a DEG co-expression network was generated. Molecular Complex Detection (MCODE) (http://baderlab.org/Software/MCODE) was used to identify key genes based on the DEG co-expression network. Finally, key genes were validated using another GEO dataset (GSE122897), and their potential diagnostic values were shown using receiver operating characteristic (ROC) analysis.ResultsIn our study, 49 DEGs were screened while 8 and 6 gene modules were detected based on ruptured IA samples and unruptured IA samples, respectively. Pathways associated with inflammation and immune response were clustered in the salmon module of ruptured IA samples. The DEG co-expression network with 35 nodes and 168 edges was generated, and 14 key genes were identified based on this DEG co-expression network. The gene with the highest degree in the key gene cluster was CXCR4. All key genes were validated using GSE122897, and they all showed the potential diagnostic value in predicting IA rupture.ConclusionsUsing a weighted gene co-expression network approach, we identified 8 and 6 modules for ruptured IA and unruptured IA, respectively. After that, we identified the hub genes for each module and key genes based on the DEG co-expression network. All these key genes were validated by another GEO dataset and might serve as potential targets for pharmacological therapies and diagnostic markers in predicting IA rupture. Further studies are needed to elucidate the detailed molecular mechanisms and biological functions of these key genes which underlie the rupture of IA.

Project description:ImportanceUnruptured intracranial aneurysms not undergoing preventive endovascular or neurosurgical treatment are often monitored radiologically to detect aneurysm growth, which is associated with an increase in risk of rupture. However, the absolute risk of aneurysm rupture after detection of growth remains unclear.ObjectiveTo determine the absolute risk of rupture of an aneurysm after detection of growth during follow-up and to develop a prediction model for rupture.Design, setting, and participantsIndividual patient data were obtained from 15 international cohorts. Patients 18 years and older who had follow-up imaging for at least 1 untreated unruptured intracranial aneurysm with growth detected at follow-up imaging and with 1 day or longer of follow-up after growth were included. Fusiform or arteriovenous malformation-related aneurysms were excluded. Of the 5166 eligible patients who had follow-up imaging for intracranial aneurysms, 4827 were excluded because no aneurysm growth was detected, and 27 were excluded because they had less than 1 day follow-up after detection of growth.ExposuresAll included aneurysms had growth, defined as 1 mm or greater increase in 1 direction at follow-up imaging.Main outcomes and measuresThe primary outcome was aneurysm rupture. The absolute risk of rupture was measured with the Kaplan-Meier estimate at 3 time points (6 months, 1 year, and 2 years) after initial growth. Cox proportional hazards regression was used to identify predictors of rupture after growth detection.ResultsA total of 312 patients were included (223 [71%] were women; mean [SD] age, 61 [12] years) with 329 aneurysms with growth. During 864 aneurysm-years of follow-up, 25 (7.6%) of these aneurysms ruptured. The absolute risk of rupture after growth was 2.9% (95% CI, 0.9-4.9) at 6 months, 4.3% (95% CI, 1.9-6.7) at 1 year, and 6.0% (95% CI, 2.9-9.1) at 2 years. In multivariable analyses, predictors of rupture were size (7 mm or larger hazard ratio, 3.1; 95% CI, 1.4-7.2), shape (irregular hazard ratio, 2.9; 95% CI, 1.3-6.5), and site (middle cerebral artery hazard ratio, 3.6; 95% CI, 0.8-16.3; anterior cerebral artery, posterior communicating artery, or posterior circulation hazard ratio, 2.8; 95% CI, 0.6-13.0). In the triple-S (size, site, shape) prediction model, the 1-year risk of rupture ranged from 2.1% to 10.6%.Conclusion and relevanceWithin 1 year after growth detection, rupture occurred in approximately 1 of 25 aneurysms. The triple-S risk prediction model can be used to estimate absolute risk of rupture for the initial period after detection of growth.

Project description:Background and objectiveThe rupture risk of intracranial aneurysms (IAs) is related to their arterial origin, but whether the different segments of the artery have different risks and act as independent risk factors is still unknown. Our study aimed to investigate the rupture risk of IAs in different arterial segments in a large Chinese cohort.MethodsImaging and clinical data of consecutive patients with IAs diagnosed by Computed Tomography angiography (CTA) from January 2013 to December 2022 were collected. Two neuroradiologists independently identified ruptured and unruptured IAs based on imaging and medical records. The internal carotid artery (ICA), middle cerebral artery (MCA), anterior cerebral artery (ACA), vertebral artery (VA), and posterior cerebral artery (PCA) were segmented according to the Bouthillier and Fischer segmentation methods. Stenoses of the proximal parent vessel were evaluated and documented. The Institutional Review Board (IRB) at Beijing Tiantan Hospital approved this retrospective study.ResultsA total of 3,837 aneurysms {median size 3.5 mm [interquartile range (IQR) 2.6-5.1 mm]; 532 ruptured} were included in this study from 2,968 patients [mean age: 57 years (IQR 50-64); male patients: 1,153]. Ruptured aneurysms were most commonly located in the posterior inferior cerebellar artery (PICA) (52.9%), anterior communicating artery (ACoA) (33.8%), other locations (33.3%), ACA (22.4%), and basilar artery (BA) (21.4%). The locations with the highest likelihood of rupture were the C7 ICA (21.3%), M2 MCA (24.0%), distal MCA (25.0%), and A2 ACA (28.1%). IAs originating from the C7 (p < 0.001), dM1 (p = 0.022), and dA1 (p = 0.021) segments were independent risk factors for rupture. IAs without stenosis of the proximal parent vessel were associated with a higher risk of rupture (p = 0.023).ConclusionThere are unique associations between the origins of aneurysms from various arterial segments. Aneurysms originating from the anterior communicating artery (ACoA), BA, PICA, A2, dA, C7, and M2 indicate a higher risk of rupture. Aneurysms originating from C4, C5, and C6 indicate a lower risk of rupture. C7 IAs, ACoA IAs, and PICA IAs seem to be independent risk factors.

Dataset Information

Integrated analysis of microarray data to identify the genes critical for the rupture of intracranial aneurysm.

Publications

Integrated analysis of microarray data to identify the genes critical for the rupture of intracranial aneurysm.

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