Evidence map›Paper›PMID 41487007›Full record

ArticleEndocrine, metabolic & immune disorders drug targets2026

Identification of Senescence- and Inflammation-Related Genes and Immune Microenvironment Characterization in Intracranial Aneurysms

Xiaoyan Li, Yingying Li, Le Zhang, Jie Mao, Bin Li

Abstract read
In one paragraph

Article in Endocrine, metabolic & immune disorders drug targets, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Xiaoyan LiDepartment of Neurology, Anhui No.2 Provincial People's Hospital, Hefei, 230041, China.
Yingying LiGraduate School, Bengbu Medical University, Bengbu, 233000, China.
Le ZhangDepartment of Neurology, Anhui No.2 Provincial People's Hospital, Hefei, 230041, China.
Jie MaoDepartment of Neurosurgery, Longgang Central Hospital of Shenzhen, Shenzhen, 518035, China.
Bin LiDepartment of Neurology, Anhui No.2 Provincial People's Hospital, Hefei, 230041, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionIntracranial aneurysm (IA) is a cerebrovascular disease that lacks effective methods for early diagnosis and risk prediction. Considering the pivotal roles of senescence and inflammation in many diseases, this study aimed to identify related biomarkers for IA and explore their underlying mechanisms.

methodsThe GSE122897 and GSE75436 datasets were obtained from the Gene Expression Omnibus (GEO) database. Senescence and inflammation scores were calculated using single-sample GSEA (ssGSEA), and weighted gene co-expression network analysis (WGCNA) was performed to identify relevant modules and hub genes. Differentially expressed genes (DEGs) were determined with the DESeq2 package, followed by conducting LASSO regression and support vector machine-recursive feature elimination (SVM-RFE) to screen key genes. Immune infiltration was analyzed using CIBERSORT and ESTIMATE algoritms, and correlations between key genes and immune cells were assessed. Finally, transcription factor (TF)-miRNA regulatory networks were constructed using the JASPAR package and ENCORI database.

resultsIA samples exhibited significantly higher senescence and inflammation scores in comparison to the controls. A total of 858 hub genes identified by WGCNA were intersected with the DEGs for further refinement by LASSO and SVM-RFE, ultimately yielding DISCUSSION: These findings indicated that senescence and inflammation contributed to IA pathogenesis and may regulate disease progression by modulating the immune microenvironment, highlighting their dual role in IA.

conclusion

Indexed as

AgingCellular MicroenvironmentCellular SenescenceInflammationIntracranial AneurysmDatabases, GeneticGene Expression ProfilingGene Regulatory NetworksHumansimmune infiltration.inflammationIntracranial aneurysmsenescencetranscription factor-miRNA regulatory networkWGCNA

Identifiers

PMID41487007
PMCPMC13334262

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