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Updated: May 23, 2025
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Studying Metabolic Brain Connectivity Using 2-Deoxy-2-[18F]Fluoro-D-Glucose Dynamic Positron Emission Tomography at the Single-subject Level
Published on: January 24, 2025
Transcriptomic and glucose metabolism of connectome dynamics variability in temporal lobe epilepsy revealed by
Jie Hu1, Bixiao Cui1, Zhenming Wang1
1Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China.
Abstract:
Temporal lobe epilepsy (TLE) is associated to genetic predisposition, metabolic abnormalities, and disruptions in brain connectivity. However, the relationships between genetic factors, metabolic processes, and brain network dynamics are not yet fully understood. Simultaneous positron emission tomography and function magnetic resonance imaging (PET/fMRI) data were collected from 66 patients with TLE and 38 healthy controls (HCs). We compared differences in brain network dynamics between TLE patients and HCs using the multilayer network model constructed from extensive temporal features extracted from fMRI. Postmortem whole brain gene expression data were then utilized to identify genes associated with alterations in TLE connectome dynamics, with subsequent enrichment analysis for functional annotation, cellular, and disease associations. Mediation analysis further explored the interrelations among gene expression, glucose metabolism as measured by PET, and brain network dynamics as measured by fMRI. Compared with HCs, individuals with TLE exhibited increased module variability primarily in the default mode network and reduced module variability in the attention network. These case-control differences were validated through split-half analyses and remained unaffected by medication or lateralization. These aberrant module variability patterns were associated with gene expression profiles predominantly related to inhibitory neurons, postsynaptic cell components, MAPK signaling pathway, and these genes were significantly enriched relative to established epilepsy-related gene sets. Moreover, we observed that the effect of gene expression profile on the alterations in TLE connectome dynamics was significantly mediated by changes in glucose metabolism. These findings highlight that alterations in brain network dynamics in TLE are associated with transcriptomic signatures, and that glucose metabolic changes partially mediate this relationship, furthering insights into the biological basis of the disorder.

