Missense variants in ANO4 cause sporadic encephalopathic or familial epilepsy with evidence for a dominant-negative effect.

Anoctamins are a family of Ca2+-activated proteins that may act as ion channels and/or phospholipid scramblases with limited understanding of function and disease association. Here, we identified five de novo and two inherited missense variants in ANO4 (alias TMEM16D) as a cause of fever-sensitive developmental and epileptic or epileptic encephalopathy (DEE/EE) and generalized epilepsy with febrile seizures plus (GEFS+) or temporal lobe epilepsy. In silico modeling of the ANO4 structure predicted that all identified variants lead to destabilization of the ANO4 structure. Four variants are localized close to the Ca2+ binding sites of ANO4, suggesting impaired protein function. Variant mapping to the protein topology suggests a preliminary genotype-phenotype correlation. Moreover, the observation of a heterozygous ANO4 deletion in a healthy individual suggests a dysfunctional protein as disease mechanism rather than haploinsufficiency. To test this hypothesis, we examined mutant ANO4 functional properties in a heterologous expression system by patch-clamp recordings, immunocytochemistry, and surface expression of annexin A5 as a measure of phosphatidylserine scramblase activity. All ANO4 variants showed severe loss of ion channel function and DEE/EE associated variants presented mild loss of surface expression due to impaired plasma membrane trafficking. Increased levels of Ca2+-independent annexin A5 at the cell surface suggested an increased apoptosis rate in DEE-mutant expressing cells, but no changes in Ca2+-dependent scramblase activity were observed. Co-transfection with ANO4 wild-type suggested a dominant-negative effect. In summary, we expand the genetic base for both encephalopathic sporadic and inherited fever-sensitive epilepsies and link germline variants in ANO4 to a hereditary disease.

Late-onset temporal lobe epilepsy: insights from brain atrophy and Alzheimer's disease biomarkers.

Considering the growing age of the world population, the incidence of epilepsy in older adults is expected to increase significantly. It has been suggested that late-onset temporal lobe epilepsy (LO-TLE) may be neurodegenerative in origin and overlap with Alzheimer's Disease (AD). Herein, we aimed to characterize the pattern of cortical atrophy and cerebrospinal fluid (CSF) biomarkers of AD (total and phosphorylated tau, and ß-amyloid) in a selected population of LO-TLE of unknown origin. We prospectively enrolled individuals with temporal lobe epilepsy onset after the age of 50 and no cognitive impairment. They underwent a structural MRI scan and CSF biomarkers measurement. Imaging and biomarkers data were compared to three retrospectively collected groups: (i) age-sex-matched healthy controls, (ii) patients with Mild Cognitive Impairment (MCI) and abnormal CSF AD biomarkers (MCI-AD), and (iii) patients with MCI and normal CSF AD biomarkers (MCI-noAD). From a pool of 52 patients, twenty consecutive eligible LO-TLE patients with a mean disease duration of 1.8 years were recruited. As control populations, 25 patients with MCI-AD, 25 patients with MCI-noAD, and 25 healthy controls were enrolled. CSF biomarkers returned normal values in LO-TLE, significantly different from patients with MCI due to AD. There were no differences in cortico-subcortical atrophy between epilepsy patients and healthy controls, while patients with MCI demonstrated widespread injuries of cortico-subcortical structures. Individuals with a late-onset form of temporal lobe epilepsy, characterized by short disease duration and normal CSF ß-amyloid and tau protein levels, showed patterns of cortical thickness and subcortical volumes not significantly different from healthy controls, but highly different from patients with MCI, either due to Alzheimer's Disease or not.

Microstate-based brain network dynamics distinguishing temporal lobe epilepsy patients: A machine learning approach.

Temporal lobe epilepsy (TLE) stands as the predominant adult focal epilepsy syndrome, characterized by dysfunctional intrinsic brain dynamics. However, the precise mechanisms underlying seizures in these patients remain elusive. Our study encompassed 116 TLE patients compared with 51 healthy controls. Employing microstate analysis, we assessed brain dynamic disparities between TLE patients and healthy controls, as well as between drug-resistant epilepsy (DRE) and drug-sensitive epilepsy (DSE) patients. We constructed dynamic functional connectivity networks based on microstates and quantified their spatial and temporal variability. Utilizing these brain network features, we developed machine learning models to discriminate between TLE patients and healthy controls, and between DRE and DSE patients. Temporal dynamics in TLE patients exhibited significant acceleration compared to healthy controls, along with heightened synchronization and instability in brain networks. Moreover, DRE patients displayed notably lower spatial variability in certain parts of microstate B, E and F dynamic functional connectivity networks, while temporal variability in certain parts of microstate E and G dynamic functional connectivity networks was markedly higher in DRE patients compared to DSE patients. The machine learning model based on these spatiotemporal metrics effectively differentiated TLE patients from healthy controls and discerned DRE from DSE patients. The accelerated microstate dynamics and disrupted microstate sequences observed in TLE patients mirror highly unstable intrinsic brain dynamics, potentially underlying abnormal discharges. Additionally, the presence of highly synchronized and unstable activities in brain networks of DRE patients signifies the establishment of stable epileptogenic networks, contributing to the poor responsiveness to antiseizure medications. The model based on spatiotemporal metrics demonstrated robust predictive performance, accurately distinguishing both TLE patients from healthy controls and DRE patients from DSE patients.

Reproducible network changes occur in a mouse model of temporal lobe epilepsy but do not correlate with disease severity.

Studying the development of brain network disruptions in epilepsy is challenged by the paucity of data before epilepsy onset. Here, we used the unilateral, kainate mouse model of hippocampal epilepsy to investigate brain network changes before and after epilepsy onset and their stability across time. Using 32 epicranial electrodes distributed over the mouse hemispheres, we analyzed EEG epochs free from epileptic activity in 15 animals before and 28 days after hippocampal injection (group 1) and in 20 animals on two consecutive days (d28 and d29, group 2). Statistical dependencies between electrodes were characterized with the debiased-weighted phase lag index. We analyzed: a) graph metric changes from baseline to chronic stage (d28) in group 1; b) their reliability across d28 and d29, in group 2; c) their correlation with epileptic activity (EA: seizure, spike and fast-ripple rates), averaged over d28 and d29, in group 2. During the chronic stage, intra-hemispheric connections of the non-injected hemisphere strengthened, yielding an asymmetrical network in low (4-8 Hz) and high theta (8-12 Hz) bands. The contralateral hemisphere also became more integrated and segregated within the high theta band. Both network topology and EEG markers of EA were stable over consecutive days but not correlated with each other. Altogether, we show reproducible large-scale network modifications after the development of focal epilepsy. These modifications are mostly specific to the non-injected hemisphere. The absence of correlation with epileptic activity does not allow to specifically ascribe these network changes to mechanisms supporting EA or rather compensatory inhibition but supports the notion that epilepsy extends beyond the sole repetition of EA and impacts network that might not be involved in EA generation.

Parvalbumin neurons in the nucleus accumbens shell modulate seizure in temporal lobe epilepsy.

A growing number of clinical and animal studies suggest that the nucleus accumbens (NAc), especially the shell, is involved in the pathogenesis of temporal lobe epilepsy (TLE). However, the role of parvalbumin (PV) GABAergic neurons in the NAc shell involved in TLE is still unclear. In this study, we induced a spontaneous TLE model by intrahippocampal administration of kainic acid (KA), which generally induce acute seizures in first 2 h (acute phase) and then lead to spontaneous recurrent seizures after two months (chronic phase). We found that chemogenetic activation of NAc shell PV neurons could alleviate TLE seizures by reducing the number and period of focal seizures (FSs) and secondary generalized seizures (sGSs), while selective inhibition of PV exacerbated seizure activity. Ruby-virus mapping results identified that the hippocampus (ventral and dorsal) is one of the projection targets of NAc shell PV neurons. Chemogenetic activation of the NAc-Hip PV projection fibers can mitigate seizures while inhibition has no effect on seizure ictogenesis. In summary, our findings reveal that PV neurons in the NAc shell could modulate the seizures in TLE via a long-range NAc-Hip circuit. All of these results enriched the investigation between NAc and epilepsy, offering new targets for future epileptogenesis research and precision therapy.

The downregulation of Kv1 channels in Lgi1-/-mice is accompanied by a profound modification of its interactome and a parallel decrease in Kv2 channels.

In animal models of LGI1-dependent autosomal dominant lateral temporal lobe epilepsy, Kv1 channels are downregulated, suggesting their crucial involvement in epileptogenesis. The molecular basis of Kv1 channel-downregulation in LGI1 knock-out mice has not been elucidated and how the absence of this extracellular protein induces an important modification in the expression of Kv1 remains unknown. In this study we analyse by immunofluorescence the modifications in neuronal Kv1.1 and Kv1.2 distribution throughout the hippocampal formation of LGI1 knock-out mice. We show that Kv1 downregulation is not restricted to the axonal compartment, but also takes place in the somatodendritic region and is accompanied by a drastic decrease in Kv2 expression levels. Moreover, we find that the downregulation of these Kv channels is associated with a marked increase in bursting patterns. Finally, mass spectrometry uncovered key modifications in the Kv1 interactome that highlight the epileptogenic implication of Kv1 downregulation in LGI1 knock-out animals.

Impacted spike frequency adaptation associated with reduction of KCNQ2/3 exacerbates seizure activity in temporal lobe epilepsy.

Numerous epilepsy-related genes have been identified in recent decades by unbiased genome-wide screens. However, the available druggable targets for temporal lobe epilepsy (TLE) remain limited. Furthermore, a substantial pool of candidate genes potentially applicable to TLE therapy awaits further validation. In this study, we reveal the significant role of KCNQ2 and KCNQ3, two M-type potassium channel genes, in the onset of seizures in TLE. Our investigation began with a quantitative analysis of two publicly available TLE patient databases to establish a correlation between seizure onset and the downregulated expression of KCNQ2/3. We then replicated these pathological changes in a pilocarpine seizure mouse model and observed a decrease in spike frequency adaptation due to the affected M-currents in dentate gyrus granule neurons. In addition, we performed a small-scale simulation of the dentate gyrus network and confirmed that the impaired spike frequency adaptation of granule cells facilitated epileptiform activity throughout the network. This, in turn, resulted in prolonged seizure duration and reduced interictal intervals. Our findings shed light on an underlying mechanism contributing to ictogenesis in the TLE hippocampus and suggest a promising target for the development of antiepileptic drugs.

Simultaneous high-resolution whole-brain MR spectroscopy and [18F]FDG PET for temporal lobe epilepsy.

PURPOSE: Precise lateralizing the epileptogenic zone in patients with drug-resistant mesial temporal lobe epilepsy (mTLE) remains challenging, particularly when routine MRI scans are inconclusive (MRI-negative). This study aimed to investigate the synergy of fast, high-resolution, whole-brain MRSI in conjunction with simultaneous [18F]FDG PET for the lateralization of mTLE. METHODS: Forty-eight drug-resistant mTLE patients (M/F 31/17, age 12-58) underwent MRSI and [18F]FDG PET on a hybrid PET/MR scanner. Lateralization of mTLE was evaluated by visual inspection and statistical classifiers of metabolic mappings against routine MRI. Additionally, this study explored how disease status influences the associations between altered N-acetyl aspartate (NAA) and FDG uptake using hierarchical moderated multiple regression. RESULTS: The high-resolution whole-brain MRSI data offers metabolite maps at comparable resolution to [18F]FDG PET. Visual examinations of combined MRSI and [18F]FDG PET showed an mTLE lateralization accuracy rate of 91.7% in a 48-patient cohort, surpassing routine MRI (52.1%). Notably, out of 23 MRI-negative mTLE, combined MRSI and [18F]FDG PET helped detect 19 cases. Logistical regression models combining hippocampal NAA level and FDG uptake improved lateralization performance (AUC=0.856), while further incorporating extrahippocampal regions such as amygdala, thalamus, and superior temporal gyrus increased the AUC to 0.939. Concurrent MRSI/PET revealed a moderating influence of disease duration and hippocampal atrophy on the association between hippocampal NAA and glucose uptake, providing significant new insights into the disease's trajectory. CONCLUSION: This paper reports the first metabolic imaging study using simultaneous high-resolution MRSI and [18F]FDG PET, which help visualize MRI-unidentifiable lesions and may thus advance diagnostic tools and management strategies for drug-resistant mTLE.

EANM practice guidelines for an appropriate use of PET and SPECT for patients with epilepsy.

Epilepsy is one of the most frequent neurological conditions with an estimated prevalence of more than 50 million people worldwide and an annual incidence of two million. Although pharmacotherapy with anti-seizure medication (ASM) is the treatment of choice, ~30% of patients with epilepsy do not respond to ASM and become drug resistant. Focal epilepsy is the most frequent form of epilepsy. In patients with drug-resistant focal epilepsy, epilepsy surgery is a treatment option depending on the localisation of the seizure focus for seizure relief or seizure freedom with consecutive improvement in quality of life. Beside examinations such as scalp video/electroencephalography (EEG) telemetry, structural, and functional magnetic resonance imaging (MRI), which are primary standard tools for the diagnostic work-up and therapy management of epilepsy patients, molecular neuroimaging using different radiopharmaceuticals with single-photon emission computed tomography (SPECT) and positron emission tomography (PET) influences and impacts on therapy decisions. To date, there are no literature-based praxis recommendations for the use of Nuclear Medicine (NM) imaging procedures in epilepsy. The aims of these guidelines are to assist in understanding the role and challenges of radiotracer imaging for epilepsy; to provide practical information for performing different molecular imaging procedures for epilepsy; and to provide an algorithm for selecting the most appropriate imaging procedures in specific clinical situations based on current literature. These guidelines are written and authorized by the European Association of Nuclear Medicine (EANM) to promote optimal epilepsy imaging, especially in the presurgical setting in children, adolescents, and adults with focal epilepsy. They will assist NM healthcare professionals and also specialists such as Neurologists, Neurophysiologists, Neurosurgeons, Psychiatrists, Psychologists, and others involved in epilepsy management in the detection and interpretation of epileptic seizure onset zone (SOZ) for further treatment decision. The information provided should be applied according to local laws and regulations as well as the availability of various radiopharmaceuticals and imaging modalities.

The use of automated and AI-driven algorithms for the detection of hippocampal sclerosis and focal cortical dysplasia.

In drug-resistant epilepsy, magnetic resonance imaging (MRI) plays a central role in detecting lesions as it offers unmatched spatial resolution and whole-brain coverage. In addition, the last decade has witnessed continued developments in MRI-based computer-aided machine-learning techniques for improved diagnosis and prognosis. In this review, we focus on automated algorithms for the detection of hippocampal sclerosis and focal cortical dysplasia, particularly in cases deemed as MRI negative, with an emphasis on studies with histologically validated data. In addition, we discuss imaging-derived prognostic markers, including response to anti-seizure medication, post-surgical seizure outcome, and cognitive reserves. We also highlight the advantages and limitations of these approaches and discuss future directions toward person-centered care.

Amygdala enlargement in temporal lobe epilepsy: Histopathology and surgical outcomes.

OBJECTIVES: Amygdala enlargement is detected on magnetic resonance imaging (MRI) in some patients with drug-resistant temporal lobe epilepsy (TLE), but its clinical significance remains uncertain We aimed to assess if the presence of amygdala enlargement (1) predicted seizure outcome following anterior temporal lobectomy with amygdalohippocampectomy (ATL-AH) and (2) was associated with specific histopathological changes. METHODS: This was a case-control study. We included patients with drug-resistant TLE who underwent ATL-AH with and without amygdala enlargement detected on pre-operative MRI. Amygdala volumetry was done using FreeSurfer for patients who had high-resolution T1-weighted images. Mann-Whitney U test was used to compare pre-operative clinical characteristics between the two groups. The amygdala volume on the epileptogenic side was compared to the amygdala volume on the contralateral side among cases and controls. Then, we used a two-sample, independent t test to compare the means of amygdala volume differences between cases and controls. The chi-square test was used to assess the correlation of amygdala enlargement with (1) post-surgical seizure outcomes and (2) histopathological changes. RESULTS: Nineteen patients with and 19 patients without amygdala enlargement were studied. Their median age at surgery was 38 years for cases and 39 years for controls, and 52.6% were male. There were no statistically significant differences between the two groups in their pre-operative clinical characteristics. There were significant differences in the means of volume difference between cases and controls (Diff = 457.2 mm3, 95% confidence interval [CI] 289.6-624.8; p < .001) and in the means of percentage difference (p < .001). However, there was no significant association between amygdala enlargement and surgical outcome (p = .72) or histopathological changes (p = .63). SIGNIFICANCE: The presence of amygdala enlargement on the pre-operative brain MRI in patients with TLE does not affect the surgical outcome following ATL-AH, and it does not necessarily suggest abnormal histopathology. These findings suggest that amygdala enlargement might reflect a secondary reactive process to seizures in the epileptogenic temporal lobe.

Statistical learning in epilepsy: Behavioral and anatomical mechanisms in the human brain.

OBJECTIVE: Statistical learning, the fundamental cognitive ability of humans to extract regularities across experiences over time, engages the medial temporal lobe (MTL) in the healthy brain. This leads to the hypothesis that statistical learning (SL) may be impaired in patients with epilepsy (PWE) involving the temporal lobe, and that this impairment could contribute to their varied memory deficits. In turn, studies done in collaboration with PWE, that evaluate the necessity of MTL circuitry through disease and causal perturbations, provide an opportunity to advance basic understanding of SL. METHODS: We implemented behavioral testing, volumetric analysis of the MTL substructures, and direct electrical brain stimulation to examine SL across a cohort of 61 PWE and 28 healthy controls. RESULTS: We found that behavioral performance in an SL task was negatively associated with seizure frequency irrespective of seizure origin. The volume of hippocampal subfields CA1 and CA2/3 correlated with SL performance, suggesting a more specific role of the hippocampus. Transient direct electrical stimulation of the hippocampus disrupted SL. Furthermore, the relationship between SL and seizure frequency was selective, as behavioral performance in an episodic memory task was not impacted by seizure frequency. SIGNIFICANCE: Overall, these results suggest that SL may be hippocampally dependent and that the SL task could serve as a clinically useful behavioral assay of seizure frequency that may complement existing approaches such as seizure diaries. Simple and short SL tasks may thus provide patient-centered endpoints for evaluating the efficacy of novel treatments in epilepsy.

Semiautomated electric source imaging determines epileptogenicity of encephaloceles in temporal lobe epilepsy.

OBJECTIVE: We aimed to assess the ability of semiautomated electric source imaging (ESI) from long-term video-electroencephalographic (EEG) monitoring (LTM) to determine the epileptogenicity of temporopolar encephaloceles (TEs) in patients with temporal lobe epilepsy. METHODS: We conducted a retrospective study involving 32 temporal lobe epilepsy patients with TEs as potentially epileptogenic lesions in structural magnetic resonance imaging scans. Findings were validated through invasive intracerebral stereo-EEG in six of 32 patients and postsurgical outcome after tailored resection of the TE in 17 of 32 patients. LTM (mean duration = 6 days) was performed using the 10/20 system with additional T1/T2 for all patients and sphenoidal electrodes in 23 of 32 patients. Semiautomated detection and clustering of interictal epileptiform discharges (IEDs) were carried out to create IED types. ESI was performed on the averages of the two most frequent IED types per patient, utilizing individual head models, and two independent inverse methods (sLORETA [standardized low-resolution brain electromagnetic tomography], MUSIC [multiple signal classification]). ESI maxima concordance and propagation in spatial relation to TEs were quantified for sources with good signal quality (signal-to-noise ratio > 2, explained signal > 60%). RESULTS: ESI maxima correctly colocalized with a TE in 20 of 32 patients (62.5%) either at the onset or half-rising flank of at least one IED type per patient. ESI maxima showed propagation from the temporal pole to other temporal or extratemporal regions in 14 of 32 patients (44%), confirming propagation originating in the area of the TE. The findings from both inverse methods validated each other in 14 of 20 patients (70%), and sphenoidal electrodes exhibited the highest signal amplitudes in 17 of 23 patients (74%). The concordance of ESI with the TE predicted a seizure-free postsurgical outcome (Engel I vs. >I) with a diagnostic odds ratio of 2.1. SIGNIFICANCE: Semiautomated ESI from LTM often successfully identifies the epileptogenicity of TEs and the IED onset zone within the area of the TEs. Additionally, it shows potential predictive power for postsurgical outcomes in these patients.

Preoperative structural-functional coupling at the default mode network predicts surgical outcomes of temporal lobe epilepsy.

OBJECTIVE: Structural-functional coupling (SFC) has shown great promise in predicting postsurgical seizure recurrence in patients with temporal lobe epilepsy (TLE). In this study, we aimed to clarify the global alterations in SFC in TLE patients and predict their surgical outcomes using SFC features. METHODS: This study analyzed presurgical diffusion and functional magnetic resonance imaging data from 71 TLE patients and 48 healthy controls (HCs). TLE patients were categorized into seizure-free (SF) and non-seizure-free (nSF) groups based on postsurgical recurrence. Individual functional connectivity (FC), structural connectivity (SC), and SFC were quantified at the regional and modular levels. The data were compared between the TLE and HC groups as well as among the TLE, SF, and nSF groups. The features of SFC, SC, and FC were categorized into three datasets: the modular SFC dataset, regional SFC dataset, and SC/FC dataset. Each dataset was independently integrated into a cross-validated machine learning model to classify surgical outcomes. RESULTS: Compared with HCs, the visual and subcortical modules exhibited decoupling in TLE patients (p < .05). Multiple default mode network (DMN)-related SFCs were significantly higher in the nSF group than in the SF group (p < .05). Models trained using the modular SFC dataset demonstrated the highest predictive performance. The final prediction model achieved an area under the receiver operating characteristic curve of .893 with an overall accuracy of .887. SIGNIFICANCE: Presurgical hyper-SFC in the DMN was strongly associated with postoperative seizure recurrence. Furthermore, our results introduce a novel SFC-based machine learning model to precisely classify the surgical outcomes of TLE.

Acetazolamide as an effective treatment for pilomotor seizures in autoimmune encephalitis.

Pilomotor seizures are strongly associated with autoimmune encephalitis (AE), particularly anti-LGI1 encephalitis. The carbonic anhydrase inhibitor acetazolamide may have special efficacy for treating AE-associated pilomotor seizures. Six patients with AE (five anti-LGI1, one seronegative) and temporal lobe pilomotor seizures (five with seizures inducible by hyperventilation) were treated with acetazolamide, administered in a cycling (2-days-ON, 4-days-OFF) regimen to offset tolerance. Seizures were assessed during epilepsy monitoring unit (EMU) recordings in four inpatients (one of whom also maintained an outpatient seizure diary chronicling 1203 seizures over 1079 days); two outpatients self-reported seizure frequencies. The extended diary revealed an inverse correlation between acetazolamide and proportion of seizures/day: 6%, 2% (days 1, 2 ON); 3%, 13%, 31%, 45% (days 1, 2, 3, 4 OFF). This patient later developed focal status epilepticus upon wean of antiseizure medications during a seropositive AE relapse that was remarkably aborted with acetazolamide monotherapy. The other three EMU patients averaged .56 seizures/day ON, and 3.81 seizures/day OFF (p = .004). The two outpatients reported seizure reductions from 3-5/day to 2/week, and 15-20/day to none, respectively, after initiation of cycling acetazolamide. Likely related to cerebral CO2/pH sensitivity, acetazolamide can be unusually effective in controlling pilomotor seizures in AE, chronically or in acute settings.

Mesial temporal lobe spiking reveals distinct patterns of blood oxygen level-dependent functional magnetic resonance imaging activation using simultaneous intracranial electroencephalography-functional magnetic resonance imaging.

OBJECTIVE: Temporal lobe epilepsy (TLE) has a high probability of becoming drug resistant and is frequently considered for surgical intervention. However, 30% of TLE cases have nonlesional magnetic resonance imaging (MRI) scans, which is associated with worse surgical outcomes. Characterizing interactions between temporal and extratemporal structures in these patients may help understand these poor outcomes. Simultaneous intracranial electroencephalography-functional MRI (iEEG-fMRI) can measure the hemodynamic changes associated with interictal epileptiform discharges (IEDs) recorded directly from the brain. This study was designed to characterize the whole brain patterns of IED-associated fMRI activation recorded exclusively from the mesial temporal lobes of patients with nonlesional TLE. METHODS: Eighteen patients with nonlesional TLE undergoing iEEG monitoring with mesial temporal IEDs underwent simultaneous iEEG-fMRI at 3 T. IEDs were marked, and statistically significant clusters of fMRI activation were identified. The locations of IED-associated fMRI activation for each patient were determined, and patients were grouped based on the location and pattern of fMRI activation. RESULTS: Two patterns of IED-associated fMRI activation emerged: primarily localized (n = 7), where activation was primarily located within the ipsilateral temporal lobe, and primarily diffuse (n = 11), where widespread bilateral extratemporal activation was detected. The primarily diffuse group reported significantly fewer focal to bilateral tonic-clonic seizures and had better postsurgical outcomes. SIGNIFICANCE: Simultaneous iEEG-fMRI can measure the hemodynamic changes associated with focal IEDs not visible on scalp EEG, such as those arising from the mesial temporal lobe. Significant fMRI activation associated with these IEDs was observed in all patients. Two distinct patterns of IED-associated activation were seen: primarily localized to the ipsilateral temporal lobe and more widespread, bilateral activation. Patients with widespread IED associated-activation had fewer focal to bilateral tonic-clonic seizures and better postsurgical outcome, which may suggest a neuroprotective mechanism limiting the spread of ictal events.

Somatic variants as a cause of drug-resistant epilepsy including mesial temporal lobe epilepsy with hippocampal sclerosis.

OBJECTIVE: The contribution of somatic variants to epilepsy has recently been demonstrated, particularly in the etiology of malformations of cortical development. The aim of this study was to determine the diagnostic yield of somatic variants in genes that have been previously associated with a somatic or germline epilepsy model, ascertained from resected brain tissue from patients with multidrug-resistant focal epilepsy. METHODS: Forty-two patients were recruited across three categories: (1) malformations of cortical development, (2) mesial temporal lobe epilepsy with hippocampal sclerosis, and (3) nonlesional focal epilepsy. Participants were subdivided based on histopathology of the resected brain. Paired blood- and brain-derived DNA samples were sequenced using high-coverage targeted next generation sequencing to high depth (585× and 1360×, respectively). Variants were identified using Genome Analysis ToolKit (GATK4) MuTect-2 and confirmed using high-coverage Amplicon-EZ sequencing. RESULTS: Sequence data on 41 patients passed quality control. Four somatic variants were validated following amplicon sequencing: within CBL, ALG13, MTOR, and FLNA. The diagnostic yield across 41 patients was 10%, 9% in mesial temporal lobe epilepsy with hippocampal sclerosis and 20% in malformations of cortical development. SIGNIFICANCE: This study provides novel insights into the etiology of mesial temporal lobe epilepsy with hippocampal sclerosis, highlighting a potential pathogenic role of somatic variants in CBL and ALG13. We also report candidate diagnostic somatic variants in FLNA in focal cortical dysplasia, while providing further insight into the importance of MTOR and related genes in focal cortical dysplasia. This work demonstrates the potential molecular diagnostic value of variants in both germline and somatic epilepsy genes.

Ketogenic Diets Alter the Gut Microbiome, Resulting in Decreased Susceptibility to and Cognitive Impairment in Rats with Pilocarpine-Induced Status Epilepticus.

A ketogenic diet (KD) is a high-fat, low-carbohydrate, and low-protein diet that exerts antiepileptic effects by attenuating spontaneous recurrent seizures, ameliorating learning and memory impairments, and modulating the gut microbiota composition. However, the role of the gut microbiome in the antiepileptic effects of a KD on temporal lobe epilepsy (TLE) induced by lithium-pilocarpine in adult rats is still unknown. Our study provides evidence demonstrating that a KD effectively mitigates seizure behavior and reduces acute-phase epileptic brain activity and that KD treatment alleviates hippocampal neuronal damage and improves cognitive impairment induced by TLE. We also observed that the beneficial effects of a KD are compromised when the gut microbiota is disrupted through antibiotic administration. Analysis of gut microbiota components via 16S rRNA gene sequencing in fecal samples collected from TLE rats fed either a KD or a normal diet. The Chao1 and ACE indices showed decreased species variety in KD-fed rats compared to TLE rats fed a normal diet. A KD increased the levels of Actinobacteriota, Verrucomicrobiota and Proteobacteria and decreased the level of Bacteroidetes. Interestingly, the abundances of Actinobacteriota and Verrucomicrobiota were positively correlated with learning and memory ability, and the abundance of Proteobacteria was positively correlated with seizure susceptibility. In conclusion, our study revealed the significant antiepileptic and neuroprotective effects of a KD on pilocarpine-induced epilepsy in rats, primarily mediated through the modulation of the gut microbiota. However, whether the gut microbiota mediates the antiseizure effects of a KD still needs to be better elucidated.

Leukocyte differential gene expression prognostic value for high versus low seizure frequency in temporal lobe epilepsy.

BACKGROUND: This study was performed to test the hypothesis that systemic leukocyte gene expression has prognostic value differentiating low from high seizure frequency refractory temporal lobe epilepsy (TLE). METHODS: A consecutive series of patients with refractory temporal lobe epilepsy was studied. Based on a median baseline seizure frequency of 2.0 seizures per month, low versus high seizure frequency was defined as ≤ 2 seizures/month and > 2 seizures/month, respectively. Systemic leukocyte gene expression was analyzed for prognostic value for TLE seizure frequency. All differentially expressed genes were analyzed, with Ingenuity® Pathway Analysis (IPA®) and Reactome, to identify leukocyte gene expression and biological pathways with prognostic value for seizure frequency. RESULTS: There were ten males and six females with a mean age of 39.4 years (range: 16 to 62 years, standard error of mean: 3.6 years). There were five patients in the high and eleven patients in the low seizure frequency cohorts, respectively. Based on a threshold of twofold change (p < 0.001, FC > 2.0, FDR < 0.05) and expression within at least two pathways from both Reactome and Ingenuity® Pathway Analysis (IPA®), 13 differentially expressed leukocyte genes were identified which were all over-expressed in the low when compared to the high seizure frequency groups, including NCF2, HMOX1, RHOB, FCGR2A, PRKCD, RAC2, TLR1, CHP1, TNFRSF1A, IFNGR1, LYN, MYD88, and CASP1. Similar analysis identified four differentially expressed genes which were all over-expressed in the high when compared to the low seizure frequency groups, including AK1, F2R, GNB5, and TYMS. CONCLUSIONS: Low and high seizure frequency TLE are predicted by the respective upregulation and downregulation of specific leukocyte genes involved in canonical pathways of neuroinflammation, oxidative stress and lipid peroxidation, GABA (γ-aminobutyric acid) inhibition, and AMPA and NMDA receptor signaling. Furthermore, high seizure frequency-TLE is distinguished prognostically from low seizure frequency-TLE by differentially increased specific leukocyte gene expression involved in GABA inhibition and NMDA receptor signaling. High and low seizure frequency patients appear to represent two mechanistically different forms of temporal lobe epilepsy based on leukocyte gene expression.

Disorganization of language and working memory systems in frontal versus temporal lobe epilepsy.

Cognitive impairment is a common comorbidity of epilepsy and adversely impacts people with both frontal lobe (FLE) and temporal lobe (TLE) epilepsy. While its neural substrates have been investigated extensively in TLE, functional imaging studies in FLE are scarce. In this study, we profiled the neural processes underlying cognitive impairment in FLE and directly compared FLE and TLE to establish commonalities and differences. We investigated 172 adult participants (56 with FLE, 64 with TLE and 52 controls) using neuropsychological tests and four functional MRI tasks probing expressive language (verbal fluency, verb generation) and working memory (verbal and visuo-spatial). Patient groups were comparable in disease duration and anti-seizure medication load. We devised a multiscale approach to map brain activation and deactivation during cognition and track reorganization in FLE and TLE. Voxel-based analyses were complemented with profiling of task effects across established motifs of functional brain organization: (i) canonical resting-state functional systems; and (ii) the principal functional connectivity gradient, which encodes a continuous transition of regional connectivity profiles, anchoring lower-level sensory and transmodal brain areas at the opposite ends of a spectrum. We show that cognitive impairment in FLE is associated with reduced activation across attentional and executive systems, as well as reduced deactivation of the default mode system, indicative of a large-scale disorganization of task-related recruitment. The imaging signatures of dysfunction in FLE are broadly similar to those in TLE, but some patterns are syndrome-specific: altered default-mode deactivation is more prominent in FLE, while impaired recruitment of posterior language areas during a task with semantic demands is more marked in TLE. Functional abnormalities in FLE and TLE appear overall modulated by disease load. On balance, our study elucidates neural processes underlying language and working memory impairment in FLE, identifies shared and syndrome-specific alterations in the two most common focal epilepsies and sheds light on system behaviour that may be amenable to future remediation strategies.