Synaptic dysfunction-related gene expression spatially correlates with widespread cortical network atrophy in...

Area of Science:

• Neuroscience
• Epilepsy Research
• Brain Imaging

Background:

• Temporal lobe epilepsy (TLE) shows lateralized gray matter changes, but whole-brain network vulnerability independent of seizure side is unclear.
• Understanding the link between brain structure changes and molecular underpinnings is crucial for TLE mechanisms.

Purpose of the Study:

• To identify brain networks vulnerable in TLE regardless of seizure laterality.
• To explore the spatial relationship between brain atrophy and gene expression in TLE.
• To establish a structural-molecular framework for TLE pathology.

Main Methods:

• Voxel-based morphometry (VBM) and surface-based morphometry (SBM) for gray matter analysis in 69 TLE patients and 47 controls.
• Multivariate machine learning to validate structural features.
• Imaging-transcriptomics using the Allen Human Brain Atlas to correlate morphology with gene expression.

Main Results:

• Identified bilateral somatomotor and default mode networks, and the right ventral attention network as vulnerable, independent of seizure origin.
• Machine learning confirmed right somatomotor network atrophy as a key TLE signature.
• Found spatial correlations between cortical atrophy and synaptic genes (CTNNB1, NLGN1, GRM5 positively; SNAP25 inversely).

Conclusions:

• Delineated lateralization-independent vulnerability networks in TLE.
• Characterized the spatial-molecular architecture of these networks.
• Linked macroscopic atrophy to microscopic synaptic gene expression, suggesting targets for precision therapies.