Transcriptionally Downregulated GABAergic Genes Associated with Synaptic Density Network Dysfunction in Temporal Lobe Epilepsy

Neurology Life Sciences Biochemistry Genetics Medical Imaging Medicine
Temporal Lobe Epilepsy Synaptic Density Network SV2A PET Gene Expression GABAergic Inhibition

Revealing Gene Expression Patterns Associated with Synaptic Density Network Dysfunction in Temporal Lobe Epilepsy

Background

Temporal Lobe Epilepsy (TLE) is the most common form of focal epilepsy, and its pathological features and mechanisms have long drawn extensive attention in the field of neuroscience. This disorder involves not only a single brain region (e.g., epileptogenic focus) but is also considered a condition that impacts widespread brain network functions. The core pathological mechanism of TLE primarily encompasses the imbalance between excitatory and inhibitory synaptic transmission, with synaptic loss being a key factor. These macroscopic synaptic network changes may further lead to brain functional network dysfunction, potentially driven by genetic dysregulation underlying these synaptic remodeling processes. However, direct in vivo studies exploring whole-brain synaptic density networks (SDSN) and their associated gene expression mechanisms in TLE patients remain sparse.

To address these issues, the authors of this paper employed a multi-modal approach combining neuroimaging and transcriptomics. For the first time, they investigated the relationship between in vivo SDSN macroscopic changes and gene expression patterns in TLE. This study carries significant implications for uncovering the molecular and genetic network mechanisms of TLE and provides novel directions and possibilities for developing network-based treatments for epilepsy.

Paper and Study Source

The paper, titled “Transcriptionally downregulated GABAergic genes associated with synaptic density network dysfunction in Temporal Lobe Epilepsy,” was authored by Rong Li, Ling Xiao, and others. The research team includes members from various institutions, such as Xiangya Hospital, Central South University, Axel Rominger, and Kuangyu Shi’s academic units. The paper was published in the European Journal of Nuclear Medicine and Molecular Imaging in 2024.

Study Design and Experimental Workflow

This study integrated Positron Emission Tomography (PET) with transcriptomic data to analyze SDSN dysfunction in TLE patients and explore related mechanisms of gene dysregulation.

Overall Experimental Design

The research was divided into two main parts: 1) utilizing the novel radiotracer [18F]Synvest-1 in PET scans to evaluate whole-brain SDSN in TLE patients and healthy controls (HC); and 2) integrating two independent transcriptomic datasets to investigate the association between SDSN topological changes and TLE-risk genes. The experimental workflow is as follows:

  • Participant Selection and Grouping: The PET cohort consisted of 24 TLE patients and 17 age- and gender-matched healthy controls (HC). The location and diagnosis of epileptogenic foci were determined by two experienced epileptologists using multi-modal evaluations, including neurological history, video EEG, and structural MRI. Transcriptomic analysis included hippocampal samples from six TLE patients and six autopsy controls. Additionally, to cover the entire brain region, the study incorporated publicly available transcriptomic data from Guelfi et al., which included 161 TLE patients’ temporal neocortex samples.

  • [18F]Synvest-1 PET Imaging Acquisition: Participants underwent static PET after [18F]Synvest-1 injection, enabling quantitative analysis of synaptic density. Images were co-registered to MRI and normalized to MNI space. Using Kernel Density Estimation (KDE), probability distributions of voxel intensities in each brain region were calculated. A Kullback-Leibler divergence method was then used to construct a 246×246 adjacency matrix of the whole-brain SDSN.

  • Transcriptome Sequencing: RNA extracted from hippocampal samples was sequenced using the Illumina HiSeq X Ten platform. Data were analyzed using HISAT2 alignment and Differential Gene Expression (DGE) analysis to identify significantly dysregulated genes. In addition, full-brain spatial expression data for 15,633 genes were obtained from the publicly available Allen Human Brain Atlas (AHBA).

  • Statistical Models and Network Analysis: Based on SDSN derived from PET, graph measures such as Weighted Strength, Weighted Clustering Coefficient, and Weighted Path Length were calculated. The relationship between SDSN changes and TLE-risk gene expression profiles was modeled using Partial Least Squares (PLS) regression.

Results

Whole-Brain and Topological Alterations in SDSN

  • Global Level: TLE patients exhibited significantly lower SDSN connectivity strength and clustering coefficients compared to healthy controls, alongside longer network path lengths. These findings indicate a reduction in global connectivity and local information processing efficiency in TLE.

  • Regional Node Level: Dysfunction in synaptic networks was predominantly localized to the frontal and parietal cortical regions, temporal lobe, limbic systems (e.g., amygdala), as well as the basal ganglia and thalamus. These regions are crucial for memory integration, epilepsy propagation, and regulation of conscious states during seizures.

Mapping Transcriptomics to SDSN Nodes

  • TLE-Associated Gene Expression Patterns: A cross-analysis of multiple datasets identified 5,451 TLE-risk genes, with 2,908 genes significantly upregulated and 3,250 downregulated. The study revealed that these gene expression patterns were significantly correlated with changes in PET-derived SDSN node strength, explaining 13% of the variance across the brain.

  • Key Genes: Imaging-transcriptomic association analyses identified GABAergic regulatory genes SLITRK3 and RBFOX1 as significantly downregulated in TLE patients. SLITRK3, critical for the formation of inhibitory synapses, was associated with increased seizure susceptibility. RBFOX1 downregulation, on the other hand, was linked to reduced inhibitory synaptic transmission, triggering hyperexcitability.

Functional Enrichment and Genetic Interaction Networks

Through Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses, notable effects on GABAergic synapse regulation, long-term potentiation (LTP), and calcium signaling pathways were observed. These biological processes likely contribute to synaptic dysfunction in TLE. Genetic interaction analyses further highlighted RBFOX1 as a central hub gene, interacting with SLITRK3 and ROCK2, among others.

Significance and Implications

This study, by integrating SDSN neuroimaging with transcriptomics, has for the first time elucidated the gene expression basis of synaptic network dysfunction in TLE. It underscores the significant impact of GABAergic gene downregulation on synaptic structure and function in this condition. Moreover, the study provides novel molecular and genetic targets for therapeutic strategies, such as gene therapy or molecular drug development.

Additionally, this research introduced the novel PET radiotracer [18F]Synvest-1 and an individualized Kullback-Leibler divergence-based SDSN analysis framework. These methodological innovations pave the way for capturing complex brain networks, expanding the toolkit for epilepsy and brain network studies.

Key Highlights

  • The first integration of in vivo molecular imaging with transcriptomic data, systematically analyzing synaptic density network dysfunction and associated gene expression in TLE.
  • Identification of SLITRK3 and RBFOX1 as key genes mediating synaptic network dysfunction, highlighting their value as potential therapeutic targets.
  • Pioneering the use of [18F]Synvest-1 and personalized SDSN analysis frameworks, further advancing tools for epilepsy and brain network research.