Grey and White Matter Alterations in Juvenile Myoclonic Epilepsy: A Comprehensive Review

The co-activation patterns of multiple brain regions in Juvenile Myoclonic Epilepsy

Juvenile myoclonic epilepsy (JME) as an idiopathic generalized epilepsy has been studied by many advanced neuroimaging techniques to elucidate its neuroanatomical basis and pathophysiological mechanisms. In this paper, we used co-activation patterns (CAPs) to explore the differences of dynamic brain activity changes in resting state between JME patients and healthy controls. 27 cases JME patients and 27 cases healthy of fMRI data were collected. The structural image data of the subjects were analyzed by voxel-based morphological analysis, and the regions with gray matter volume atrophy and high voxel were selected as the regions of interest. Further, the mean disease duration was used as boundary to divide the patients' data into the below-average time and the above-average time groups, which were defined as patient disease duration groups. And these data were used to construct CAPs and to compare changes in brain dynamics. It was found that the number of patterns occurrences and the possibility of switching between patterns were smaller than those in the healthy control, which indicated patients with damage to brain regions. For the patient time control group, the number of patterns occurrences and the possibility of switching between patterns were similar, while there was linear regression between the three values and disease duration. Collectively, this study provides important evidence for revealing the key brain regions of JME by studying the transformation between CAPs. Future studies could investigate the effects of receiving treatment on patient dynamic brain activity.

Increased Thalamic Connectivity in Juvenile Myoclonic Epilepsy Based on Electroencephalography Source-Level Analysis

Background: This study investigated alterations in the intrinsic thalamic network of patients with juvenile myoclonic epilepsy (JME) based on an electroencephalography (EEG) source-level analysis. Materials and Methods: We enrolled patients newly diagnosed with JME as well as healthy controls. The assessments were conducted in the resting state. We computed sources based on the scalp electrical potentials using a minimum-norm imaging method and a standardized, low-resolution, brain electromagnetic tomography approach. To create a functional connectivity matrix, we used the Talairach atlas to define thalamic nodes and applied the coherence method to measure brain synchronization as edges. We then calculated the intrinsic thalamic network using graph theory. We compared the intrinsic thalamic network of patients with JME with those of healthy controls. Results: This study included 67 patients with JME and 66 healthy controls. EEG source-level analysis revealed significant differences in the intrinsic thalamic networks between patients with JME and healthy controls. The measures of functional connectivity (radius, diameter, and characteristic path length) were significantly lower in patients with JME than in healthy controls (radius: 2.769 vs. 3.544, p = 0.015; diameter: 4.464 vs. 5.443, p = 0.024; and characteristic path length: 2.248 vs. 2.616, p = 0.046). Conclusions: We demonstrated alterations in the intrinsic thalamic network in patients with JME compared with those in healthy controls based on the EEG source-level analysis. These findings indicated increased thalamic connectivity in the JME group. These intrinsic thalamic network changes may be related to the pathophysiology of JME.

Heterozygous RELN missense variants associated with genetic generalized epilepsy

PURPOSE

The RELN gene encodes the secreted glycoprotein Reelin and has important functions in both developing and adult brains. In this study, we aimed to explore the association between the RELN and genetic generalized epilepsy (GGE).

METHODS

We performed whole-exome sequencing on a cohort of 92 patients with GGE. Based on amino acid sequence alignments, allele frequency, pedigree validation and computational modeling, the RELN variants were identified and clinical features of cases were summarized. Cell-based Reelin secretion assays were examined by Western blotting. Alterations of mutant Reelin transport through the secretion pathway were detected by immunofluorescence staining.

RESULTS

Three novel pathogenic RELN variants (3.26%; c.2260C>T/p.R754W, c.2914C>G/p.P972A and c.3029G>A/p.R1010H) were identified. All probands showed adolescence-onset generalized seizures characterized by generalized epileptiform discharges with normal EEG backgrounds, no or mild cognitive impairment, and responded well to anti-seizure medications. All these variants were located in the central regions from 1B to 2A consecutive repeats, and protein modeling demonstrated structural alterations in Reelin. Moreover, we found that these heterozygous missense variants significantly decreased the secretion of mutant proteins in HEK-293T cells, and this impairment was due to the altered transport of mutant Reelin in the secretion pathway.

CONCLUSION

These results suggest that RELN is potentially associated with GGE. The phenotype of GGE caused by RELN variants is relatively mild, and the pathogenic mechanism may involve a loss-of-function.

Multi-spectral diffusion MRI mega-analysis in genetic generalized epilepsy: Relation to outcomes

BACKGROUND AND OBJECTIVES

Genetic generalized epilepsy (GGE) is the most common form of generalized epilepsy. Although individual patients with GGE typically present without structural alterations, group differences have been demonstrated in GGE and some GGE subtypes like juvenile myoclonic epilepsy (GGE-JME). Previous studies usually involved only small cohorts from single centers and therefore could not assess imaging markers of multiple GGE subtypes.

METHODS

We performed a diffusion MRI mega-analysis in 192 participants consisting of 126 controls and 66 patients with GGE from four different cohorts and two different epilepsy centers. We applied whole-brain multi-site harmonization and analyzed fractional anisotropy (FA), as well as mean, radial and axial diffusivity (MD/RD/AD) to assess differences between controls, patients with GGE and the common GGE subtypes, i.e. GGE with generalized tonic-clonic seizures only (GGE-GTCS), GGE-JME and absence epilepsy (GGE-AE). We also analyzed relationships with patients' response to anti-seizure-medication (ASM).

RESULTS

Relative to controls, we identified decreased anisotropy and increased RD in patients with GGE. We found no significant effects of disease duration, age of onset or seizure frequency on diffusion metrics. Patients with JME had increased MD and RD when compared to controls, while patients with GGE-GTCS showed decreased MD/AD when compared to controls. Compared to patients with GGE-AE, patients with GGE-GTCS had lower AD/MD. Compared to patients with GGE-GTCS, patients with GGE-JME had higher MD/RD and AD. Moreover, we found lower FA in patients with refractory when compared to patients with non-refractory GGE in the right cortico-spinal tract, but no significant differences in patients with active versus controlled epilepsy.

DISCUSSION

We provide evidence that clinically defined GGE as a whole and GGE-subtypes harbor marked microstructural differences detectable with diffusion MRI. Moreover, we found an association between microstructural changes and treatment resistance. Our findings have important implications for future full-resolution multi-site studies when assessing GGE, its subtypes and ASM refractoriness.

Understanding frontal lobe function in epilepsy: Juvenile myoclonic epilepsy vs. frontal lobe epilepsy

AIM

To compare neuropsychological function in juvenile myoclonic epilepsy (JME) and frontal lobe epilepsy (FLE) since frontal circuitry is involved in both conditions. By drawing on previously theory-guided hypotheses and findings, a particular emphasis is placed on the way different cognitive-pathophysiological mechanisms act upon to produce frontal dysfunction in JME (frontal-executive and attention-related problems: vigilance, reaction times, processing speed, and response inhibition) and in FLE (reflecting the coproduct of the functional deficit zone), respectively.

METHODS

A total of 16 patients with JME, 34 patients with FLE, and 48 normal controls, all matched for age and education, were administered a comprehensive battery of tests to assess frontal-executive functions, as well as attention, memory, and learning domains. Participants did not take medications other than antiepileptics or have a psychiatric history.

RESULTS

Patients with FLE overall showed worse neuropsychological performance compared to both JME and HCs. With respect to JME, patients with FLE did significantly worse in measures of verbal and nonverbal executive function, short-term-, and long-term- auditory-verbal memory and learning, immediate and delayed episodic recall, visual attention and motor function, visuo-motor coordination and psychomotor speed, speed of visual information processing, and vocabulary. Patients with JME performed significantly worse compared to FLE only in associative semantic processing, while the former outperformed all groups in vocabulary, visuomotor coordination, and psychomotor speed.

CONCLUSION

We suggest that selective impairments of visual- and mostly auditory-speed of information processing, vigilance, and response inhibition may represent a salient neuropsychological feature in JME. These findings suggest the existence of an aberrantly working executive-attention system, secondary to pathological reticulo-thalamo-cortical dynamics. Contrariwise, cortically (frontal and extra-frontal) and subcortically induced malfunction in FLE is determined by the functional deficit zone i.e., the ensemble of cortical and subcortical areas that are functionally abnormal between seizures.

Can Disruption of Basal Ganglia-Thalamocortical Circuit in Wilson Disease Be Associated with Juvenile Myoclonic Epilepsy Phenotype?

In this paper, we describe the multimodal MRI findings in a patient with Wilson disease and a seizure disorder, characterized by an electroclinical picture resembling juvenile myoclonic epilepsy. The brain structural MRI showed a deposition of ferromagnetic materials in the basal ganglia, with marked hypointensities in T2-weighted images of globus pallidus internus bilaterally. A resting-state fMRI study revealed increased functional connectivity in the patient, compared to control subjects, in the following networks: (1) between the primary motor cortex and several cortical regions, including the secondary somatosensory cortex and (2) between the globus pallidus and the thalamo-frontal network. These findings suggest that globus pallidus alterations, due to metal accumulation, can lead to a reduction in the normal globus pallidus inhibitory tone on the thalamo-(motor)-cortical pathway. This, in turn, can result in hyperconnectivity in the motor cortex circuitry, leading to myoclonus and tonic-clonic seizures. We suppose that, in this patient, Wilson disease generated a ‘lesion model’ of myoclonic epilepsy.

A systematic review of resting-state and task-based fmri in juvenile myoclonic epilepsy

Functional neuroimaging modalities have enhanced our understanding of juvenile myoclonic epilepsy (JME) underlying neural mechanisms. Due to its non-invasive, sensitive and analytical nature, functional magnetic resonance imaging (fMRI) provides valuable insights into relevant functional brain networks and their segregation and integration properties. We systematically reviewed the contribution of resting-state and task-based fMRI to the current understanding of the pathophysiology and the patterns of seizure propagation in JME Altogether, despite some discrepancies, functional findings suggest that corticothalamo-striato-cerebellar network along with default-mode network and salience network are the most affected networks in patients with JME. However, further studies are required to investigate the association between JME's main deficiencies, e.g., motor and cognitive deficiencies and fMRI findings. Moreover, simultaneous electroencephalography-fMRI (EEG-fMRI) studies indicate that alterations of these networks play a role in seizure modulation but fall short of identifying a causal relationship between altered functional properties and seizure propagation. This review highlights the complex pathophysiology of JME, which necessitates the design of more personalized diagnostic and therapeutic strategies in this group.

Identifying juvenile myoclonic epilepsy via diffusion tensor imaging using machine learning analysis

The aim of this study was to evaluate the feasibility of using a machine learning approach based on diffusion tensor imaging (DTI) to identify patients with juvenile myoclonic epilepsy. We analyzed the usefulness of combining conventional DTI measures and structural connectomic profiles. This retrospective study was conducted at a tertiary hospital. We enrolled 55 patients with juvenile myoclonic epilepsy. All of the subjects underwent DTI from January 2017 to March 2020. We also enrolled 58 healthy subjects as a normal control group. We extracted conventional DTI measures and structural connectomic DTI profiles. We employed the support vector machines (SVM) algorithm to classify patients with juvenile myoclonic epilepsy and healthy subjects based on the conventional DTI measures and structural connectomic profiles. The SVM classifier based on conventional DTI measures had an accuracy of 68.1% and an area under the curve (AUC) of 0.682. Another SVM classifier based on the structural connectomic profiles demonstrated an accuracy of 72.7% and an AUC of 0.727. The SVM classifier based on combining the conventional DTI measures and structural connectomic profiles had an accuracy of 81.8% and an AUC of 0.818. DTI using machine learning is useful for classifying patients with juvenile myoclonic epilepsy and healthy subjects. Combining both the conventional DTI measures and structural connectomic profiles results in a better classification performance than using conventional DTI measures or the structural connectomic profiles alone to identify juvenile myoclonic epilepsy.

Alterations of the intrinsic amygdala-hippocampal network in juvenile myoclonic epilepsy

INTRODUCTION

Several lines of evidence suggest that the amygdala-hippocampus is involved in the epileptogenic network of juvenile myoclonic epilepsy (JME). The aim of this study was to investigate the alterations in the individual nuclei of the amygdala and hippocampal subfields, and the intrinsic amygdala-hippocampal network of patients with JME compared to healthy controls.

METHODS

This retrospective study conducted at a single tertiary hospital involved 35 patients with newly diagnosed JME, and 34 healthy subjects. We calculated the individual structural volumes of 18 nuclei in the amygdala, and 38 hippocampal subfields using three-dimensional volumetric T1-weighted imaging and FreeSurfer program. We also performed an analysis of the intrinsic amygdala-hippocampal global and local network based on these volumes using a graph theory and Brain Analysis using Graph Theory (BRAPH) program. We investigated the differences in these volumes and network measures between patients with JME and healthy controls.

RESULTS

There were no significant volume differences in the nuclei of the amygdala and hippocampal subfields between patients with JME and healthy controls. However, we found significant differences in the global network between patients with JME and healthy controls. The mean clustering coefficient was significantly decreased in patients with JME compared to healthy controls (0.473 vs. 0.653, p = .047). In addition, specific regions in the hippocampal subfields showed significant differences in the local network between the two groups. The betweenness centrality of the right CA1-head, right hippocampus-amygdala-transition area, left hippocampal fissure, left fimbria, and left CA3-head, was increased in patients with JME compared to healthy controls.

CONCLUSION

The intrinsic amygdala-hippocampal global and local networks differed in patients with JME compared to healthy controls, which may be related to the pathogenesis of JME, and memory dysfunction in patients with JME.

Trait impulsivity correlates with active myoclonic seizures in genetic generalized epilepsy

BACKGROUND

Juvenile myoclonic epilepsy (JME) is a common subtype of genetic generalized epilepsy (GGE) arising in adolescence and is often associated with executive function (EF) deficits. Some EF components like response inhibition have been extensively evaluated in JME, but few studies have focused upon trait impulsivity or compared between GGE subtypes. The aim of the present study was to compare the association of trait impulsivity in JME with other GGE subtypes.

METHODS

Patients with GGE aged between 14 and 40 years (n = 137) were divided into those with JME (n = 92) and those with other GGEs (n = 45: 8 childhood absence epilepsy (CAE), 22 juvenile absence epilepsy (JAE), and 15 epilepsy with generalized tonic-clonic seizures only (EGTCS)). The study participants were recruited through medical records of the general population of Buskerud County and the neighboring municipalities, covering 477,000 people or 9.1% of Norway's total population. All participants underwent a clinical interview including the Barratt Impulsiveness Scale (BIS), an established measure of trait impulsivity. We controlled for other potential predictors of BIS score using analysis of covariance (ANCOVA).

RESULTS

There were no differences between JME and other types of GGE for BIS scores, but the presence of myoclonic seizures within the last year, irrespective of GGE subtype, was independently associated with significantly increased behavioral impulsivity.

CONCLUSIONS

This study demonstrates that trait impulsivity in GGE is most strongly related to the recent occurrence of myoclonic seizures rather than GGE subtype.

LncRNA ILF3-AS1 mediated the occurrence of epilepsy through suppressing hippocampal miR-212 expression

Increased expression of some matrix metalloproteinases (MMPs) is closely associated with epilepsy. However, factors that promote their expression have not been clarified. Long noncoding RNAs (lncRNAs) play crucial roles in the development of human diseases, including various cancers, but its potential function in temporal lobe epilepsy (TLE) has remained unexplored. In this study, we showed that hippocampal and serum ILF3-AS1 levels are higher in TLE patients than in matched controls. Interleukin (IL)-1β and tumor necrosis factor (TNF)-α induced ILF3-AS1 expression in astrocytes, while ectopic expression of ILF3-AS1 enhanced IL-6 and TNF-α expression. Ectopic ILF3-AS1 in astrocytes also increased expression of MMP2, MMP3, MMP9 and MMP14, but suppressed expression of miR-212. Consistent with that finding, miR-212 levels were lower in the hippocampus and serum of TLE patients than their controls. This suggests that ILF3-AS1 promotes expression of inflammatory cytokines and MMPs by targeting miR-212 and that ILF3-AS1 plays a crucial role in the development of TLE.

Alteration of cerebello-thalamocortical spontaneous low-frequency oscillations in juvenile myoclonic epilepsy

OBJECTIVE

Altered thalamocortical network has been proposed to play a pivotal role in the principal pathophysiology underlying juvenile myoclonic epilepsy (JME). Recently, resting-state fMRI studies have provided converging evidence for thalamocortical dysconnectivity in patients with JME. Herein, we investigated the amplitude and spatial distribution of spontaneous low-frequency oscillations using analysis of fractional amplitude of low-frequency fluctuation (fALFF) in a large group of JME patients in comparison with controls.

METHODS

Volumetric MRI and resting-state fMRI were acquired in 75 patients with JME and 62 matched controls. After preprocessing of MRI data, fALFF was computed and then Z-transformed for standardization. fALFF was compared between controls and patients, and correlation analysis between regional fALFF and clinical parameters were performed in patients.

RESULTS

Compared with controls, JME patients revealed significant fALFF increases in the bilateral medial thalamus, insular cortex/inferior frontal gyrus, and cerebellum vermis (false discovery rate-corrected P < 0.05). There was no region of fALFF reduction in JME patients relative to controls. No significant correlation was observed between regional fALFF and disease duration or cumulative number of generalized tonic-clonic seizures.

CONCLUSIONS

We have shown alterations of low-frequency oscillations in the thalamus, insular cortex/inferior frontal gyrus, and cerebellum in patients with JME, implicating cerebello-thalamocortical network abnormality in the pathophysiology underlying JME. Our results could further support the recent concept that JME is a network epilepsy involving specific cortical and subcortical structures, especially the cerebello-thalamocortical network.

Subtle Brain Developmental Abnormalities in the Pathogenesis of Juvenile Myoclonic Epilepsy

Juvenile myoclonic epilepsy (JME), a lifelong disorder that starts during adolescence, is the most common of genetic generalized epilepsy syndromes. JME is characterized by awakening myoclonic jerks and myoclonic-tonic-clonic (m-t-c) grand mal convulsions. Unfortunately, one third of JME patients have drug refractory m-t-c convulsions and these recur in 70-80% who attempt to stop antiepileptic drugs (AEDs). Behavioral studies documented impulsivity, but also impairment of executive functions relying on organization and feedback, which points to prefrontal lobe dysfunction. Quantitative voxel-based morphometry (VBM) revealed abnormalities of gray matter (GM) volumes in cortical (frontal and parietal) and subcortical structures (thalamus, putamen, and hippocampus). Proton magnetic resonance spectroscopy (MRS) found evidence of dysfunction of thalamic neurons. White matter (WM) integrity was disrupted in corpus callosum and frontal WM tracts. Magnetic resonance imaging (MRI) further unveiled anomalies in both GM and WM structures that were already present at the time of seizure onset. Aberrant growth trajectories of brain development occurred during the first 2 years of JME diagnosis. Because of genetic origin, disease causing variants were sought, first by positional cloning, and most recently, by next generation sequencing. To date, only six genes harboring pathogenic variants (GABRA1, GABRD, EFHC1, BRD2, CASR, and ICK) with Mendelian and complex inheritance and covering a limited proportion of the world population, are considered as major susceptibility alleles for JME. Evidence on the cellular role, developmental and cell-type expression profiles of these six diverse JME genes, point to their pathogenic variants driving the first steps of brain development when cell division, expansion, axial, and tangential migration of progenitor cells (including interneuron cortical progenitors) sculpture subtle alterations in brain networks and microcircuits during development. These alterations may explain "microdysgenesis" neuropathology, impulsivity, executive dysfunctions, EEG polyspike waves, and awakening m-t-c convulsions observed in JME patients.

Progress in the molecular mechanisms of genetic epilepsies using patient-induced pluripotent stem cells

Research findings on the molecular mechanisms of epilepsy almost always originate from animal experiments, and the development of induced pluripotent stem cell (iPSC) technology allows the use of human cells with genetic defects for studying the molecular mechanisms of genetic epilepsy (GE) for the first time. With iPSC technology, terminally differentiated cells collected from GE patients with specific genetic etiologies can be differentiated into many relevant cell subtypes that carry all of the GE patient's genetic information. iPSCs have opened up a new research field involving the pathogenesis of GE. Using this approach, studies have found that gene mutations induce GE by altering the balance between neuronal excitation and inhibition, which is associated. among other factors, with neuronal developmental disturbances, ion channel abnormalities, and synaptic dysfunction. Simultaneously, astrocyte activation, mitochondrial dysfunction, and abnormal signaling pathway activity are also important factors in the molecular mechanisms of GE.