Identification of key genes in intracranial aneurysm via WGCNA: insights into immune microenvironment and therapeutic targets.
Journal:
Neurological research
Published Date:
Aug 25, 2025
Abstract
BACKGROUND: Intracranial aneurysms (IA) are prevalent vascular lesions whose rupture causes subarachnoid hemorrhage with high disability and mortality. Although cell adhesion molecules help maintain vascular integrity, their roles in IA pathogenesis remain incompletely defined. High-throughput bioinformatics offers a means to elucidate these mechanisms. METHODS: Transcriptomic datasets of IA tissues and peripheral blood were retrieved from GEO. Differential expression analysis and weighted gene co-expression network analysis (WGCNA) identified IA-related genes. Functional enrichment, immune-cell infiltration profiling, consensus clustering, competing endogenous RNA (ceRNA) network construction, and in silico drug prediction were performed. Experimental validation used qRT-PCR in vascular smooth muscle cells. RESULTS: We identified 2,052 differentially expressed genes (DEGs), of which 54 were linked to cell adhesion and immune functions. Integrating LASSO and random forest yielded three hub genes-SLC7A11, FAP, and COL1A1-that were validated as diagnostic biomarkers with high accuracy; notably, two of the three high-AUC genes were strongly correlated. These genes were enriched in immune-regulatory pathways, including Toll-like receptor signaling and cytokine-cytokine receptor interactions. Immune infiltration analysis showed altered levels of seven immune cell types in IA tissues, with a particularly strong association between hub genes and activated mast cells. The ceRNA network suggested potential post-transcriptional regulators, and drug prediction identified several FDA-approved agents targeting the hub genes. Consensus clustering separated IA patients into two molecular subtypes with distinct immune landscapes. CONCLUSION: This study delineates the molecular and immunological landscape of IA from the perspective of cell adhesion molecules. The identified biomarkers enhance diagnostic precision and provide mechanistic insights and potential therapeutic avenues.
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