Transcriptional signatures and topological reorganization of morphometric similarity networks in temporal lobe epilepsy with unilateral hippocampal sclerosis.
Authors
Affiliations (7)
Affiliations (7)
- Department of Radiology, Huaxi MR Research Center (HMRRC), Institute of Radiology and Medical Imaging, West China Hospital of Sichuan University, Chengdu, Sichuan, China.
- Psychoradiology Key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Chengdu, Sichuan, China.
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, Sichuan, China.
- Department of Anesthesiology, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China.
- Department of Neurology, West China Hospital of Sichuan University, Chengdu, Sichuan, China.
- Department of Science and Technology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
- Department of Anesthesiology, National-Local Joint Engineering Research Centre of Translational Medicine of Anesthesiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China.
Abstract
To delineate morphometric similarity network (MSN) topological abnormalities and their underlying spatial transcriptomics in the normal-appearing cortex of unilateral mesial temporal lobe epilepsy with hippocampal sclerosis (mTLE-HS). High-resolution T1-weighted magnetic resonance imaging (MRI) from 109 unilateral mTLE-HS patients (64 left, 45 right) and 90 matched controls were analyzed to construct individual-level MSNs by integrating five cortical morphometric features. Graph-theoretical analysis quantified global and local network topology, and machine-learning models assessed their values in patient identification and epileptogenic lateralization, with performance further evaluated in an independent validation dataset. Further connectome-transcriptome association analyses linked these macroscale topological abnormalities to the microscale substrates in specific gene expressions, biological pathways, cellular compositions, and neurodevelopmental windows. Patients exhibited global small-worldness increase and local nodal reorganizations, with hyper-connectivity in default mode and limbic networks and hypo-connectivity in temporo-occipital cortex. These MSN-topology abnormalities enabled accurate patient classification (77.4%) and epileptogenic lateralization (83.2%), driven predominantly by features from limbic network (40.0% and 41.1%, respectively). These performances were reproducible in an independent validation dataset (classification accuracy = 75.4%, lateralization accuracy = 77.1%). Spatial transcriptomics mapped the MSN-topology alterations to expression of genes enriched in RNA processing and mitochondrial energy metabolism, including key epilepsy risk genes such as DNM1 and PPFIA3. These genes showed enriched expression in excitatory neurons, astrocytes, and oligodendrocytes, peaking during neurodevelopment in early-fetal striatum and neonatal-to-childhood cortex. MSN topology delineates the pattern of cortical network reorganization in mTLE-HS, aiding in patient identification and lateralization. The convergence of these macroscale connectomic alterations with microscale transcriptomic profiles points to an RNA-metabolic interplay that shapes cortical vulnerability of mTLE-HS in a progressive way.