Etiology and management of refractory epilepsies

Emerging Trends in Neuromodulation for Treatment of Drug-Resistant Epilepsy

Epilepsy is a neurological disorder that affects more than 70 million people globally. A considerable proportion of epilepsy is resistant to anti-epileptic drugs (AED). For patients with drug-resistant epilepsy (DRE), who are not eligible for resective or ablative surgery, neuromodulation has been a palliative option. Since the approval of vagus nerve stimulation (VNS) in 1997, expansion to include other modalities, such as deep brain stimulation (DBS) and responsive neurostimulation (RNS), has led to improved seizure control in this population. In this article, we discuss the current updates and emerging trends on neuromodulation for epilepsy.

Integrating old and new complexity measures toward automated seizure detection from long-term video EEG recordings

Automated seizure detection in long-term video-EEG recordings is far from being integrated into common clinical practice. Here, we leverage classical and state-of-the-art complexity measures to robustly and automatically detect seizures from scalp recordings. Brain activity is scored through eight features, encompassing traditional time domain and novel measures of recurrence. A binary classification algorithm tailored to treat unbalanced dataset is used to determine whether a time window is ictal or non-ictal from its features. The application of the algorithm on a cohort of ten adult patients with focal refractory epilepsy indicates sensitivity, specificity, and accuracy of 90%, along with a true alarm rate of 95% and less than four false alarms per day. The proposed approach emphasizes ictal patterns against noisy background without the need of data preprocessing. Finally, we benchmark our approach against previous studies on two publicly available datasets, demonstrating the good performance of our algorithm.

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Complexity measures are formulated to enhance classical time-domain statistics of EEG

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The detection algorithm does not need ad-hoc data preprocessing to address artifacts

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Focal seizures are detected 95% of the time with less than four false alarms per day

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The approach offers a visual representation of a seizure as a time-evolving network

Anticonvulsant mechanisms of the ketogenic diet and caloric restriction

Many treatments have been proposed to control epileptic seizures, such as the ketogenic diet and caloric restriction. However, seizure control has not yet been improved completely in all patients. Probably, due to the lack of understanding regarding this neurological disorder pathogenesis or pathophysiology, including its molecular approach. Currently, there is not much information about the molecular processes and genes involved, and their relation to the possible beneficial effects of diet therapy on epilepsy. The ketogenic diet and caloric restriction are implicated in potential anti-seizure mechanisms related to the gut microbiome, metabolic pathways, hormones and neurotransmitters, mitochondria improvement, a role in inflammation, and oxidative stress, among others. In this review, we pretend to describe the molecular mechanism and the possible genes involved in the different ketogenic diet and caloric restriction mechanisms of action described to decrease neural excitability and, therefore, epileptic seizures, especially when conventional treatment is not enough to achieve control of epilepsy.

Determination of valproic acid and 3-heptanone in plasma using air-assisted liquid-liquid microextraction with the assistance of vortex: Application in the real samples

Introduction: Valproic acid (VPA) is an antiepileptic drug used to treat epilepsy and bipolar disorder. Adverse effects of VPA were studied in many reports, however, a dose-response relationship between VPA and its metabolites in epilepsy patients are extremely limited. In this paper, a high efficient method was developed for the preconcentration and determination of VPA and its main metabolite in plasma. Methods: For the extraction and preconcentration of the selected analytes, a volume of an extractant was placed at the bottom of the microtube containing pretreated plasma. The mixture was repeatedly withdrawn from the microtube and pushed-out into it using a 1.0-mL glass syringe and resulted in a cloudy mixture. For further turbidity, the mixture was shaken on a vortex agitator. This procedure was used to analyze the plasma samples of patients with epilepsy (n = 70). Results: The results revealed that in most patients with a low level of VPA relative to its expected level, 3-heptanone concentrations were high. The limits of quantification of 3-heptanone and VPA were 0.04 mg L-1 and 0.2 mg L-1, respectively. A suitable precision at a concentration of 2 mg L-1 for each analyte was obtained (relative standard deviation ≤ 9%). Conclusion: The obtained results indicated that this procedure is easy, sensitive, and reliable, and can be used for the analysis of the selected analytes in the plasma samples of patients with epilepsy.

Medication adherence and adverse effect profile of antiepileptic drugs in Nigerian patients with epilepsy

Aim: Medication adherence remains a major challenge among patients with epilepsy (PWE) with the adverse effect profile of antiepileptic drugs (AEDs) as one of its main drivers. Methods: This was a cross-sectional questionnaire-based study among PWE in selected Nigerian tertiary healthcare facilities using the Morisky Medication Adherence Scale and the Liverpool Adverse Effect Profile (LAEP). Results: 126 PWE from four tertiary healthcare facilities were included in this study comprising of 59 (46.8%) males and 67 (53.2%) females. Carbamazepine (104/70.7%), sodium valproate (23/15.6%) and phenytoin (11/7.5%) were the most commonly prescribed AEDs. Using the Morisky Medication Adherence Scale, 17.2, 38.3 and 44.5% of patients were classified as having high, medium and low adherence, respectively. The mean LAEP score was 23.69 ± 6.07. The most common reported adverse effects among respondents were tiredness (30.4%) and headache (22.5%). Conclusion: Medication adherence to AED was poor among patients in this study.

Drug-Resistant Epilepsy: Multiple Hypotheses, Few Answers

Epilepsy is a common neurological disorder that affects over 70 million people worldwide. Despite the recent introduction of new antiseizure drugs (ASDs), about one-third of patients with epilepsy have seizures refractory to pharmacotherapy. Early identification of patients who will become refractory to ASDs could help direct such patients to appropriate non-pharmacological treatment, but the complexity in the temporal patterns of epilepsy could make such identification difficult. The target hypothesis and transporter hypothesis are the most cited theories trying to explain refractory epilepsy, but neither theory alone fully explains the neurobiological basis of pharmacoresistance. This review summarizes evidence for and against several major theories, including the pharmacokinetic hypothesis, neural network hypothesis, intrinsic severity hypothesis, gene variant hypothesis, target hypothesis, and transporter hypothesis. The discussion is mainly focused on the transporter hypothesis, where clinical and experimental data are discussed on multidrug transporter overexpression, substrate profiles of ASDs, mechanism of transporter upregulation, polymorphisms of transporters, and the use of transporter inhibitors. Finally, future perspectives are presented for the improvement of current hypotheses and the development of treatment strategies as guided by the current understanding of refractory epilepsy.

SOX11 identified by target gene evaluation of miRNAs differentially expressed in focal and non-focal brain tissue of therapy-resistant epilepsy patients

MicroRNAs (miRNAs) are small non-coding RNAs that post-transcriptionally control the expression of their target genes via RNA interference. There is increasing evidence that expression of miRNAs is dysregulated in neuronal disorders, including epilepsy, a chronic neurological disorder characterized by spontaneous recurrent seizures. Mesial temporal lobe epilepsy (MTLE) is a common type of focal epilepsy in which disease-induced abnormalities of hippocampal neurogenesis in the subgranular zone as well as gliosis and neuronal cell loss in the cornu ammonis area are reported. We hypothesized that in MTLE altered miRNA-mediated regulation of target genes could be involved in hippocampal cell remodeling. A miRNA screen was performed in hippocampal focal and non-focal brain tissue samples obtained from the temporal neocortex (both n=8) of MTLE patients. Out of 215 detected miRNAs, two were differentially expressed (hsa-miR-34c-5p: mean increase of 5.7 fold (p=0.014), hsa-miR-212-3p: mean decrease of 76.9% (p=0.0014)). After in-silico target gene analysis and filtering, reporter gene assays confirmed RNA interference for hsa-miR-34c-5p with 3'-UTR sequences of GABRA3, GRM7 and GABBR2 and for hsa-miR-212-3p with 3'-UTR sequences of SOX11, MECP2, ADCY1 and ABCG2. Reporter gene assays with mutated 3'-UTR sequences of the transcription factor SOX11 identified two different binding sites for hsa-miR-212-3p and its primary transcript partner hsa-miR-132-3p. Additionally, there was an inverse time-dependent expression of Sox11 and miR-212-3p as well as miR-132-3p in rat neonatal cortical neurons. Transfection of neurons with anti-miRs for miR-212-3p and miR-132-3p suggest that both miRNAs work synergistically to control Sox11 expression. Taken together, these results suggest that differential miRNA expression in neurons could contribute to an altered function of the transcription factor SOX11 and other genes in the setting of epilepsy, resulting not only in impaired neural differentiation, but also in imbalanced neuronal excitability and accelerated drug export.

Neuronal calcium signaling pathways are associated with the development of epilepsy

Epilepsy is the most common serious neurological disorder worldwide, however, the specific causative factors and mechanisms underlying epilepsy remain unclear. The current study aimed to study the potential genes or pathways associated with epilepsy, based on rat miRNA expression profiles. The microarray dataset GSE49850 was downloaded and analyzed with the TimeCourse R software package, which was used to generate comparisons between the control and electrically-stimulated groups. The target genes of differentially expressed miRNAs were queried in the miRWalk database and functional enrichment was conducted using the Database for Annotation, Visualization and Integrated Discovery software tools. The interaction network of the target genes was constructed based on the Biomolecular Interaction Network Database and clustered using ClusterONE. In total, 152 differentially expressed miRNAs were identified, with rno-miR-21-5p being the most significantly differentially expressed. A total of 526 target genes of the differentially expressed miRNAs were obtained. Functional analysis indicated that these genes were predominantly involved in responses to stimuli. The interaction network showed that the GRIN and STX gene family, which are involved in synaptic signal transmission, were significant. In conclusion, the present study identified that the development of epilepsy was closely associated with neuronal calcium signaling pathways.

Refractory epilepsy in children

Refractory epilepsy, estimated to affect 10-20% children with epilepsy, can have profound effect on the education, social and cognitive functioning and recreational activities of the child. The definitions are still evolving. A detailed clinical evaluation may reveal an accurate syndromic and etiological diagnosis. The recent advances in neuroimaging and electrophysiology have revolutionized the management of children with refractory epilepsy and supplement the clinical evaluation. Genetic and metabolic evaluation may be indicated in selected cases. The rational use of anti-epileptic drugs, epilepsy surgery and dietary therapies are the mainstay in the management. Various experimental treatment options and pharmacogenetics offer hope for future.

Performance-power consumption tradeoff in wearable epilepsy monitoring systems

Automated seizure detection methods can be used to reduce time and costs associated with analyzing large volumes of ambulatory EEG recordings. These methods however have to rely on very complex, power hungry algorithms, implemented on the system backend, in order to achieve acceptable levels of accuracy. In size, and therefore power-constrained EEG systems, an alternative approach to the problem of data reduction is online data selection, in which simpler algorithms select potential epileptiform activity for discontinuous recording but accurate analysis is still left to a medical practitioner. Such a diagnostic decision support system would still provide doctors with information relevant for diagnosis while reducing the time taken to analyze the EEG. For wearable systems with limited power budgets, data selection algorithm must be of sufficiently low complexity in order to reduce the amount of data transmitted and the overall power consumption. In this paper, we present a low-power hardware implementation of an online epileptic seizure data selection algorithm with encryption and data transmission and demonstrate the tradeoffs between its accuracy and the overall system power consumption. We demonstrate that overall power savings by data selection can be achieved by transmitting less than 40% of the data. We also show a 29% power reduction when selecting and transmitting 94% of all seizure events and only 10% of background EEG.

The frequency and precipitating factors for breakthrough seizures among patients with epilepsy in Uganda

Background

Epilepsy is one of the major brain disorders worldwide. Breakthrough seizures carry a heavy burden of epilepsy, with increased morbidity and risk of premature mortality. Several factors have been suggested to precipitate break through seizures but these have not been studied in our setting. The study sought to determine the prevalence of breakthrough seizures, as well as precipitating factors in adults with epilepsy attending Mulago hospital.

Methods

This study was conducted in Mulago Hospital, using a cross sectional study design between August and December 2009. Subjects with epilepsy and had been receiving anti-epileptics treatment for at least 6 months prior to the study were consecutively enrolled.

Results

A total of 256 patients with epilepsy were recruited. Prevalence of breakthrough seizures among epilepsy patients attending Mulago hospital was 75.3%. Factors found to be significantly associated with breakthrough seizures were non compliance to anti-epileptic therapy (p < 0.0001); duration of treatment (p < 0.0001); infections (p < 0.044) and menses among female study participants (p < 0.0001). The level of education, sleep deprivation, alcohol and substance abuse, and flickering lights were not associated with breakthrough seizures.

Conclusions

Breakthrough seizures are high in Mulago National referral hospital, with drug non-compliance the commonest cause. The attending physicians need to identify precipitating factors among patients attending Mulago hospital and have them addressed appropriately during patient care.

Alterations in miRNA levels in the dentate gyrus in epileptic rats

The aim of this study was to characterize changes in miRNA expression in the epileptic dentate gyrus. Status epilepticus evoked by amygdala stimulation was used to induce epilepsy in rats. The dentate gyri were isolated at 7 d, 14 d, 30 d and 90 d after stimulation (n=5). Sham-operated time-matched controls were prepared for each time point (n=5). The miRNA expression was evaluated using Exiqon microarrays. Additionally, mRNA from the same animals was profiled using Affymetrix microarrays. We detected miRNA expression signatures that differentiate between control and epileptic animals. Significant changes in miRNA expression between stimulated and sham operated animals were observed at 7 and 30 d following stimulation. Moreover, we found that there are ensembles of miRNAs that change expression levels over time. Analysis of the mRNA expression from the same animals revealed that the expression of several mRNAs that are potential targets for miRNA with altered expression level is regulated in the expected direction. The functional characterization of miRNAs and their potential mRNA targets indicate that miRNA can participate in several molecular events that occur in epileptic tissue, including immune response and neuronal plasticity. This is the first report on changes in the expression of miRNA and the potential functional impact of these changes in the dentate gyrus of epileptic animals. Complex changes in the expression of miRNAs suggest an important role for miRNA in the molecular mechanisms of epilepsy.

Improving seizure detection performance reporting: analysing the duration needed for a detection

Improving seizure detection performance relies not only on novel signal processing approaches but also on new accurate, reliable and comparable performance reporting to give researchers better and fairer tools for understanding the true algorithm operation. This paper investigates the sensitivity of current performance metrics to the duration of data that must be marked as candidate seizure activity before a seizure detection is made. The results demonstrate that not all metrics are insensitive to this high level choice in the algorithm design, and provide new approaches for comparing between reported algorithm performances in a robust and reliable manner.

Optimal features for online seizure detection

This study identifies characteristic features in scalp EEG that simultaneously give the best discrimination between epileptic seizures and background EEG in minimally pre-processed scalp data; and have minimal computational complexity to be suitable for online, real-time analysis. The discriminative performance of 65 previously reported features has been evaluated in terms of sensitivity, specificity, area under the sensitivity-specificity curve (AUC), and relative computational complexity, on 47 seizures (split in 2,698 2 s sections) in over 172 h of scalp EEG from 24 adults. The best performing features are line length and relative power in the 12.5-25 Hz band. Relative power has a better seizure detection performance (AUC = 0.83; line length AUC = 0.77), but is calculated after the discrete wavelet transform and is thus more computationally complex. Hence, relative power achieves the best performance for offline detection, whilst line length would be preferable for online low complexity detection. These results, from the largest systematic study of seizure detection features, aid future researchers in selecting an optimal set of features when designing algorithms for both standard offline detection and new online low computational complexity detectors.

Adenosine dysfunction in astrogliosis: cause for seizure generation?

Epilepsy is characterized by both neuronal and astroglial dysfunction. The endogenous anticonvulsant adenosine, the level of which is largely controlled by astrocytes, might provide a crucial link between astrocyte and neuron dysfunction in epilepsy. Here we have studied astrogliosis, a hallmark of the epileptic brain, adenosine dysfunction and the emergence of spontaneous seizures in a comprehensive approach that includes a new mouse model of focal epileptogenesis, mutant mice with altered brain levels of adenosine, and mice lacking adenosine A1 receptors. In wild-type mice, following a focal epileptogenesis-precipitating injury, astrogliosis, upregulation of the adenosine-removing astrocytic enzyme adenosine kinase (ADK), and spontaneous seizures coincide in a spatio-temporally restricted manner. Importantly, these spontaneous seizures are mimicked by untreated transgenic mice that either overexpress ADK in brain or lack A1 receptors. Conversely, mice with reduced ADK in the forebrain do not develop either astrogliosis or spontaneous seizures. Our studies define ADK as a crucial upstream regulator of A1 receptor-mediated modulation of neuronal excitability, and support the ADK hypothesis of epileptogenesis in which upregulation of ADK during astrogliosis provides a crucial link between astrocyte and neuron dysfunction in epilepsy. These findings define ADK as rational target for therapeutic intervention.