ArticleScientific reports2025
Alterations of multilayer network correlated with cognitive impairment and gene expression profiles in children with idiopathic generalized epilepsy.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Transcriptional signatures of the cortical morphometric similarity network gradient in left temporal lobe epilepsy with different seizure symptoms.Frontiers in neuroscience · 2026Article
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10 authors.
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Abstract
This study investigated dynamic brain network changes and their genetic correlations in children with idiopathic generalized epilepsy (IGE). We included 26 children with IGE and 35 healthy controls, all participants underwent resting-state functional magnetic resonance imaging and cognitive assessments. Modular variability (MV) in time-varying networks was compared, and correlations with cognition and clinical variables were analyzed, we also explored classification problems using machine learning. Gene sets associated with IGE-related network remodeling were identified using the Allen Human Brain Atlas and gene enrichment analysis tools. The results showed that children with IGE exhibited reduced MV in sensorimotor and frontoparietal networks and increased MV in the default mode network (DMN). MV changes in the left prefrontal and right orbitofrontal cortices correlated with verbal and full-scale IQ scores, respectively. MV changes in the left precuneus/posterior cingulate cortex correlated with performance IQ scores. Transcriptomic analysis revealed 985 genes (FDR < 0.05) whose spatial expression patterns covaried with network alterations, prominently enriched for synaptic signaling and neuroactive ligand-receptor interactions, including GABA receptor subunits (GABRE) and neurodevelopmental regulators (BCL11A). Machine learning confirmed MV as a significant predictor of verbal IQ (permutation P = 0.041), with DMN and frontoparietal regions contributing most to prediction. Dynamic brain network abnormalities in children with IGE were significantly associated with cognitive function and gene expression, providing new insights into the neural mechanisms underlying network dysfunction and cognitive impairment in epilepsy.
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