Dataset Information

Genetic epilepsy syndromes without structural brain abnormalities: clinical features and experimental models.

ABSTRACT: Research in genetics of epilepsy represents an area of great interest both for clinical purposes and for understanding the basic mechanisms of epilepsy. Most mutations in epilepsies without structural brain abnormalities have been identified in ion channel genes, but an increasing number of genes involved in a diversity of functional and developmental processes are being recognized through whole exome or genome sequencing. Targeted molecular diagnosis is now available for different forms of epilepsy. The identification of epileptogenic mutations in patients before epilepsy onset and the possibility of developing therapeutic strategies tested in experimental models may facilitate experimental approaches that prevent epilepsy or decrease its severity. Functional analysis is essential for better understanding pathogenic mechanisms and gene interactions. In vitro experimental systems are either cells that usually do not express the protein of interest or neurons in primary cultures. In vivo/ex vivo systems are organisms or preparations obtained from them (e.g., brain slices), which should better model the complexity of brain circuits and actual pathophysiological conditions. Neurons differentiated from induced pluripotent stem cells generated from the skin fibroblasts of patients have recently allowed the study of mutations in human neurons having the genetic background of a given patient. However, there is remarkable complexity underlying epileptogenesis in the clinical dimension, as reflected by the fact that experimental models have not provided yet results having clinical translation and that, with a few exceptions concerning rare conditions, no new curative treatment has emerged from any genetic finding in epilepsy.

SUBMITTER: Guerrini R

PROVIDER: S-EPMC3996114 | biostudies-literature | 2014 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Genetic epilepsy syndromes without structural brain abnormalities: clinical features and experimental models.

Guerrini Renzo R Marini Carla C Mantegazza Massimo M

Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics 20140401 2

Research in genetics of epilepsy represents an area of great interest both for clinical purposes and for understanding the basic mechanisms of epilepsy. Most mutations in epilepsies without structural brain abnormalities have been identified in ion channel genes, but an increasing number of genes involved in a diversity of functional and developmental processes are being recognized through whole exome or genome sequencing. Targeted molecular diagnosis is now available for different forms of epil ...[more]

PMID: 24664660

Similar Datasets

Project description:The epilepsies are commonly accompanied by widespread abnormalities in cerebral white matter. ENIGMA-Epilepsy is a large quantitative brain imaging consortium, aggregating data to investigate patterns of neuroimaging abnormalities in common epilepsy syndromes, including temporal lobe epilepsy, extratemporal epilepsy, and genetic generalized epilepsy. Our goal was to rank the most robust white matter microstructural differences across and within syndromes in a multicentre sample of adult epilepsy patients. Diffusion-weighted MRI data were analysed from 1069 healthy controls and 1249 patients: temporal lobe epilepsy with hippocampal sclerosis (n = 599), temporal lobe epilepsy with normal MRI (n = 275), genetic generalized epilepsy (n = 182) and non-lesional extratemporal epilepsy (n = 193). A harmonized protocol using tract-based spatial statistics was used to derive skeletonized maps of fractional anisotropy and mean diffusivity for each participant, and fibre tracts were segmented using a diffusion MRI atlas. Data were harmonized to correct for scanner-specific variations in diffusion measures using a batch-effect correction tool (ComBat). Analyses of covariance, adjusting for age and sex, examined differences between each epilepsy syndrome and controls for each white matter tract (Bonferroni corrected at P < 0.001). Across 'all epilepsies' lower fractional anisotropy was observed in most fibre tracts with small to medium effect sizes, especially in the corpus callosum, cingulum and external capsule. There were also less robust increases in mean diffusivity. Syndrome-specific fractional anisotropy and mean diffusivity differences were most pronounced in patients with hippocampal sclerosis in the ipsilateral parahippocampal cingulum and external capsule, with smaller effects across most other tracts. Individuals with temporal lobe epilepsy and normal MRI showed a similar pattern of greater ipsilateral than contralateral abnormalities, but less marked than those in patients with hippocampal sclerosis. Patients with generalized and extratemporal epilepsies had pronounced reductions in fractional anisotropy in the corpus callosum, corona radiata and external capsule, and increased mean diffusivity of the anterior corona radiata. Earlier age of seizure onset and longer disease duration were associated with a greater extent of diffusion abnormalities in patients with hippocampal sclerosis. We demonstrate microstructural abnormalities across major association, commissural, and projection fibres in a large multicentre study of epilepsy. Overall, patients with epilepsy showed white matter abnormalities in the corpus callosum, cingulum and external capsule, with differing severity across epilepsy syndromes. These data further define the spectrum of white matter abnormalities in common epilepsy syndromes, yielding more detailed insights into pathological substrates that may explain cognitive and psychiatric co-morbidities and be used to guide biomarker studies of treatment outcomes and/or genetic research.

Project description:ObjectiveWe assessed preoperative structural brain networks and clinical characteristics of patients with drug-resistant temporal lobe epilepsy (TLE) to identify correlates of postsurgical seizure recurrences.MethodsWe examined data from 51 patients with TLE who underwent anterior temporal lobe resection (ATLR) and 29 healthy controls. For each patient, using the preoperative structural, diffusion, and postoperative structural MRI, we generated 2 networks: presurgery network and surgically spared network. Standardizing these networks with respect to controls, we determined the number of abnormal nodes before surgery and expected to be spared by surgery. We incorporated these 2 abnormality measures and 13 commonly acquired clinical data from each patient into a robust machine learning framework to estimate patient-specific chances of seizures persisting after surgery.ResultsPatients with more abnormal nodes had a lower chance of complete seizure freedom at 1 year and, even if seizure-free at 1 year, were more likely to relapse within 5 years. The number of abnormal nodes was greater and their locations more widespread in the surgically spared networks of patients with poor outcome than in patients with good outcome. We achieved an area under the curve of 0.84 ± 0.06 and specificity of 0.89 ± 0.09 in predicting unsuccessful seizure outcomes (International League Against Epilepsy [ILAE] 3-5) as opposed to complete seizure freedom (ILAE 1) at 1 year. Moreover, the model-predicted likelihood of seizure relapse was significantly correlated with the grade of surgical outcome at year 1 and associated with relapses up to 5 years after surgery.ConclusionNode abnormality offers a personalized, noninvasive marker that can be combined with clinical data to better estimate the chances of seizure freedom at 1 year and subsequent relapse up to 5 years after ATLR.Classification of evidenceThis study provides Class II evidence that node abnormality predicts postsurgical seizure recurrence.

Project description:ObjectiveTo explore the structural brain abnormality and its relationship with neuropsychological disorders and electroclinical characteristics in juvenile myoclonic epilepsy (JME) patients.MethodsSixty-seven patients diagnosed with JME and 56 healthy controls were enrolled. All subjects underwent MRI using T1-weighted 3D brain structural images with 1 mm thickness. Voxel-based morphometry (VBM) and surface-based morphometry (SBM) analyses were performed. They also underwent a series of neuropsychological tests to assess cognitive function. The correlation analyses were conducted between structural changes, neuropsychological outcomes, and electroclinical features.ResultsThe gray matter concentration (GMC) was decreased in the bilateral pre-central and post-central gyrus, right anterior cingulate gyrus, left posterior orbital region, bilateral occipital regions, bilateral hippocampus and bilateral caudate nucleus in the JME groups (corrected P < 0.05). The evaluation of gray matter volume (GMV) showed significant decrease respectively in bilateral pre-central and post-central gyrus, left paracentral lobule, left orbital gyrus, left amygdala, left basal ganglia and left thalamus of JME patients (P < 0.05). The cortex thicknesses of the right inferior temporal gyrus, right insular gyrus, and right cingulate gyrus had negative correlations with the disease duration significantly. At the same time, the whole-brain white matter volume was positively associated with the course of the disease (P < 0.05). Patients with persistent abnormal EEG discharges had significantly less whole-brain gray matter volume than JME patients with normal EEG (P = 0.03). Correlation analyses and linear regression analyses showed that, in addition to the gray matter volumes of frontal and parietal lobe, the temporal lobe, as well as the basal ganglia and thalamus, were also significantly correlated with neuropsychological tests' results (P < 0.05).ConclusionThe JME patients showed subtle structural abnormalities in multiple brain regions that were not only limited to the frontal lobe but also included the thalamus, basal ganglia, parietal lobe, temporal lobe and some occipital cortex, with significant involvement of the primary somatosensory cortex and primary motor cortex. And we significantly demonstrated a correlation between structural abnormalities and cognitive impairment. In addition, the course of disease and abnormal discharges had a specific negative correlation with the structural changes.

Dataset Information

Genetic epilepsy syndromes without structural brain abnormalities: clinical features and experimental models.

Publications

Genetic epilepsy syndromes without structural brain abnormalities: clinical features and experimental models.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets