Identifying and validating key genes mediating intracranial aneurysm rupture using weighted correlation network analysis and exploration of personalized treatment.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36330394", "kind": "science-record", "revision": 5, "content_hash": "sha256:e6e596314910dee8685039880260c4d3825bcf3703d9b215943a7847db074c7a", "created_at": "2026-11-01T18:15:45Z", "updated_at": "2026-11-01T22:50:31Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identifying and validating key genes mediating intracranial aneurysm rupture using weighted correlation network analysis and exploration of personalized treatment.", "doi": "10.21037/atm-22-4068", "pmid": "36330394", "authors": ["Ji Wu", "Zhi-Jun Chen", "Jing Liang", "Chang-Sheng Lai", "Xue-Yu Li", "Zhao-Jian Yang"], "journal": "Annals of translational medicine", "year": 2022, "abstract": "Background: Intracranial aneurysmal subarachnoid hemorrhage (aSAH) is a dangerous and highly fatal condition if ruptured. Significant advances have been made in the treatment of unruptured intracranial aneurysms (UIAs), but risk assessment methods for early diagnosis of intracranial aneurysm (IA) rupture remain limited.\nMethods: The datasets of IA GSE13353, GSE15629, and GSE54083 were downloaded through the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) in unruptured and ruptured aneurysms were identified by R software using methods such as gene set enrichment analysis (GSEA) and weighted gene co-expression network analysis (WGCNA). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were performed on the DEGs, and logistic regression models were used to construct a prediction model to discriminate UIA from healthy samples. We then performed GSEA on the genes in the model, followed by model validation using the GSE54083 dataset. Finally, we used the single-sample (ss)GSEA method to investigate the relationship between the diagnostic model genes and immune cells and immune function.\nResults: A total of 79 DEGs were obtained in patients with IA rupture compared to unruptured controls. The results of KEGG and GO enrichment analysis showed that neutrophil activation is involved in immune response, neutrophil mediated immunity, and positive regulation of angiogenesis. Interestingly, the results of immunoassays demonstrated that the break in IA may be associated with immune T cells. We used DEGs and WGCNA to determine common genes. The logistic regression model was trained based on 24 intersecting genes, and eventually retained 2 genes, KIAA0226L and UPP1, which we found to be reliable using the validation set, and GSEA revealed that the diagnostic model was associated with the Hippo signaling pathway and vascular smooth muscle contraction, and viral protein interaction with cytokine and cytokine were also associated. Finally explored using the CMap database, Tivozanib could be a potential small molecule drug for the treatment of ruptured intracranial aneurysms (RIAs).\nConclusions: We identified new diagnostic genes associated with IA rupture, which may provide a new way of aneurysm diagnosis.", "claims": [{"id": "claim-method", "statement": "We first annotated the above downloaded data using perl, then normalized and merged the annotated GSE13353 and GSE15629 data using the limma and sva packages of R software (The R Foundation For Statistical Computing, Vienna, Austria), and finally used the limma package for screening of differentially expressed genes (DEGs) in ruptured aneurysms with the following screening criteria: log fold change (FC) ≥1, adjusted P value <0.05.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36330394", "locator": "sections[4] \"Data processing and DEG screening\" paragraph 2", "quote": "We first annotated the above downloaded data using perl, then normalized and merged the annotated GSE13353 and GSE15629 data using the limma and sva packages of R software (The R Foundation For Statistical Computing, Vienna, Austria), and finally used the limma package for screening of differentially expressed genes (DEGs) in ruptured aneurysms with the following screening criteria: log fold change (FC) ≥1, adjusted P value <0.05."}], "state": "complete"}, {"id": "claim-data-access", "statement": "We performed a search for IAs through the GEO database and selected data on RIAs and UIAs by filtering and downloading GSE13353 (containing a total of 11 RIA and 8 UIA specimens), GSE15629 (which contained 8 ruptured and 6 human UIAs and 5 RIAs), and GSE54083 (gene expression levels were determined in 8 RIAs, 5 UIAs, and 10 superficial temporal arteries), and downloaded the relevant platform data separately for subsequent analysis.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36330394", "locator": "sections[3] \"Data download\" paragraph 2", "quote": "We performed a search for IAs through the GEO database and selected data on RIAs and UIAs by filtering and downloading GSE13353 (containing a total of 11 RIA and 8 UIA specimens), GSE15629 (which contained 8 ruptured and 6 human UIAs and 5 RIAs), and GSE54083 (gene expression levels were determined in 8 RIAs, 5 UIAs, and 10 superficial temporal arteries), and downloaded the relevant platform data separately for subsequent analysis."}], "state": "complete"}, {"id": "claim-target-result", "statement": "A total of 79 differentially expressed genes were identified in ruptured intracranial aneurysms compared with unruptured controls.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:36330394", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "A total of 79 DEGs were obtained in patients with IA rupture compared to unruptured controls."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "A total of 79 differentially expressed genes were identified in ruptured intracranial aneurysms compared with unruptured controls.", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:36330394"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE13353"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {"fold_change": "limma package using log fold change ≥1 and adjusted P value"}, "inputs": ["data:geo:GSE13353"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:36330394", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": 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