Unveiling m7G modification patterns and causal drivers governing intracranial aneurysm rupture risk through...

Area of Science:

• Molecular Biology
• Genetics
• Medical Science

Background:

• Intracranial aneurysm (IA) rupture leads to severe brain hemorrhage and high mortality.
• The molecular mechanisms underlying IA rupture are not fully understood.
• Improved risk prediction for IA rupture is clinically essential.

Purpose of the Study:

• To investigate the role of N7-methylguanosine (m7G) RNA modifications in intracranial aneurysms.
• To develop a predictive model for IA rupture risk based on m7G patterns.
• To identify genetic factors associated with m7G modifications in IA.

Main Methods:

• Transcriptomic analysis
• Single-cell analysis
• Genetic data analysis
• Machine learning model development
• Validation in independent patient cohorts

Main Results:

• Distinct m7G modification patterns were identified in IA.
• These m7G patterns significantly improved the accuracy of a machine learning-based rupture prediction model (AUC 0.91-0.95).
• Three causal m7G-related genes (NSUN2, IFIT5, SNUPN) were identified, with altered expression and methylation in ruptured aneurysms.

Conclusions:

• m7G RNA modifications play a critical role in the rupture of intracranial aneurysms.
• The developed prediction model shows strong clinical potential for assessing IA rupture risk.
• The identified genes (NSUN2, IFIT5, SNUPN) are potential therapeutic targets for IA.