BACKGROUND: Research on driver genes that can be used to diagnose and control the formation and development of intracranial aneurysms (IAs) is still limited, and bioinformatics and machine learning approaches are implemented in the study in an aim to identify and validate them. METHODS: By applying datasets from the Gene Expression Omnibus database for human cerebrovascular tissue, 47 cases of ruptured IA, 71 cases of ruptured IA, and 64 cases of normal control intracranial vessels were analyzed. Apply bioinformatics and machine learning methods to screen for the driver genes that contribute to the occurrence and development of IAs. Construct animal models to verify them. RESULTS: STX17 was identified as a key driver gene for the occurrence and development of IAs (AUC: 0.724). The animal model of IA was successfully constructed. Immunohistochemistry: The average optical density values of vascular smooth muscle and STX17 antibodies in the model group were significantly decreased compared with those in the normal group (P <
0.002). reverse transcription - polymerase chain reaction: The mRNA expression level of the STX17 gene in the model group was significantly lower than that in the normal group (P <
0.002). Western blot: The protein expression level of the STX17 gene in the model group was significantly decreased compared with that in the normal group (P <
0.002). CONCLUSIONS: STX17-mediated changes in the smooth muscle cell phenotype are new driver genes for IA formation and progression, providing a new approach for the early screening, diagnosis, and treatment of IA.