Classifying epilepsy pragmatically: Past, present, and future

Nanotechnological advances in the treatment of epilepsy: a comprehensive review

Epilepsy is one of the most prevalent chronic neurological disorders characterized by frequent unprovoked epileptic seizures. Epileptic seizures can develop from a broad range of underlying abnormalities such as tumours, strokes, infections, traumatic brain injury, developmental abnormalities, autoimmune diseases, and genetic predispositions. Sometimes epilepsy is not easily diagnosed and treated due to the large diversity of symptoms. Undiagnosed and untreated seizures deteriorate over time, impair cognition, lead to injuries, and can sometimes result in death. This review gives details about epilepsy, its classification on the basis of International League Against Epilepsy, current therapeutics which are presently offered for the treatment of epilepsy. Despite of the fact that more than 30 different anti-epileptic medication and antiseizure drugs are available, large number of epileptic patients fail to attain prolonged seizure independence. Poor onsite bioavailability of drugs due to blood brain barrier poses a major challenge in drug delivery to brain. The present review covers the limitations with the state-of-the-art strategies for managing seizures and emphasizes the role of nanotechnology in overcoming these issues. Various nano-carriers like polymeric nanoparticles, dendrimers, lipidic nanoparticles such as solid lipid nanoparticles, nano-lipid carriers, have been explored for the delivery of anti-epileptic drugs to brain using oral and intranasal routes. Nano-carries protect the encapsulated drugs from degradation and provide a platform to deliver controlled release over prolonged periods, improved permeability and bioavailability at the site of action. The review also emphasises in details about the role of neuropeptides for the treatment of epilepsy.

Quantitative serum proteome analysis using tandem mass tags in dogs with epilepsy

This study included four groups of dogs (group A: healthy controls, group B: idiopathic epilepsy receiving antiepileptic medication (AEM), group C: idiopathic epilepsy without AEM, group D: structural epilepsy). Comparative quantitative proteomic analysis of serum samples among the groups was the main target of the study. Samples were analyzed by a quantitative Tandem-Mass-Tags approach on the Q-Exactive-Plus Hybrid Quadrupole-Orbitrap mass-spectrometer. Identification and relative quantification were performed in Proteome Discoverer. Data were analyzed using R. Gene ontology terms were analyzed based on Canis lupus familiaris database. Data are available via ProteomeXchange with identifier PXD041129. Eighty-one proteins with different relative adundance were identified in the four groups and 25 were master proteins (p < 0.05). Clusterin (CLU), and apolipoprotein A1 (APOA1) had higher abundance in the three groups of dogs (groups B, C, D) compared to controls. Amine oxidase (AOC3) was higher in abundance in group B compared to groups C and D, and lower in group A. Adiponectin (ADIPOQ) had higher abundance in groups C compared to group A. ADIPOQ and fibronectin (FN1) had higher abundance in group B compared to group C and D. Peroxidase activity assay was used to quantify HP abundance change, validating and correlating with proteomic analysis (r = 0.8796). SIGNIFICANCE: The proteomic analysis of serum samples from epileptic dogs indicated potential markers of epilepsy (CLU), proteins that may contribute to nerve tissue regeneration (APOA1), and contributing factors to epileptogenesis (AOC3). AEM could alter extracellular matrix proteins (FN1). Illness (epilepsy) severity could influence ADIPOQ abundance.

Variation in prognosis and treatment outcome in juvenile myoclonic epilepsy: a Biology of Juvenile Myoclonic Epilepsy Consortium proposal for a practical definition and stratified medicine classifications

Reliable definitions, classifications and prognostic models are the cornerstones of stratified medicine, but none of the current classifications systems in epilepsy address prognostic or outcome issues. Although heterogeneity is widely acknowledged within epilepsy syndromes, the significance of variation in electroclinical features, comorbidities and treatment response, as they relate to diagnostic and prognostic purposes, has not been explored. In this paper, we aim to provide an evidence-based definition of juvenile myoclonic epilepsy showing that with a predefined and limited set of mandatory features, variation in juvenile myoclonic epilepsy phenotype can be exploited for prognostic purposes. Our study is based on clinical data collected by the Biology of Juvenile Myoclonic Epilepsy Consortium augmented by literature data. We review prognosis research on mortality and seizure remission, predictors of antiseizure medication resistance and selected adverse drug events to valproate, levetiracetam and lamotrigine. Based on our analysis, a simplified set of diagnostic criteria for juvenile myoclonic epilepsy includes the following: (i) myoclonic jerks as mandatory seizure type; (ii) a circadian timing for myoclonia not mandatory for the diagnosis of juvenile myoclonic epilepsy; (iii) age of onset ranging from 6 to 40 years; (iv) generalized EEG abnormalities; and (v) intelligence conforming to population distribution. We find sufficient evidence to propose a predictive model of antiseizure medication resistance that emphasises (i) absence seizures as the strongest stratifying factor with regard to antiseizure medication resistance or seizure freedom for both sexes and (ii) sex as a major stratifying factor, revealing elevated odds of antiseizure medication resistance that correlates to self-report of catamenial and stress-related factors including sleep deprivation. In women, there are reduced odds of antiseizure medication resistance associated with EEG-measured or self-reported photosensitivity. In conclusion, by applying a simplified set of criteria to define phenotypic variations of juvenile myoclonic epilepsy, our paper proposes an evidence-based definition and prognostic stratification of juvenile myoclonic epilepsy. Further studies in existing data sets of individual patient data would be helpful to replicate our findings, and prospective studies in inception cohorts will contribute to validate them in real-world practice for juvenile myoclonic epilepsy management.

Ontology-based feature engineering in machine learning workflows for heterogeneous epilepsy patient records

Biomedical ontologies are widely used to harmonize heterogeneous data and integrate large volumes of clinical data from multiple sources. This study analyzed the utility of ontologies beyond their traditional roles, that is, in addressing a challenging and currently underserved field of feature engineering in machine learning workflows. Machine learning workflows are being increasingly used to analyze medical records with heterogeneous phenotypic, genotypic, and related medical terms to improve patient care. We performed a retrospective study using neuropathology reports from the German Neuropathology Reference Center for Epilepsy Surgery at Erlangen, Germany. This cohort included 312 patients who underwent epilepsy surgery and were labeled with one or more diagnoses, including dual pathology, hippocampal sclerosis, malformation of cortical dysplasia, tumor, encephalitis, and gliosis. We modeled the diagnosis terms together with their microscopy, immunohistochemistry, anatomy, etiologies, and imaging findings using the description logic-based Web Ontology Language (OWL) in the Epilepsy and Seizure Ontology (EpSO). Three tree-based machine learning models were used to classify the neuropathology reports into one or more diagnosis classes with and without ontology-based feature engineering. We used five-fold cross validation to avoid overfitting with a fixed number of repetitions while leaving out one subset of data for testing, and we used recall, balanced accuracy, and hamming loss as performance metrics for the multi-label classification task. The epilepsy ontology-based feature engineering approach improved the performance of all the three learning models with an improvement of 35.7%, 54.5%, and 33.3% in logistics regression, random forest, and gradient tree boosting models respectively. The run time performance of all three models improved significantly with ontology-based feature engineering with gradient tree boosting model showing a 93.8% reduction in the time required for training and testing of the model. Although, all three models showed an overall improved performance across the three-performance metrics using ontology-based feature engineering, the rate of improvement was not consistent across all input features. To analyze this variation in performance, we computed feature importance scores and found that microscopy had the highest importance score across the three models, followed by imaging, immunohistochemistry, and anatomy in a decreasing order of importance scores. This study showed that ontologies have an important role in feature engineering to make heterogeneous clinical data accessible to machine learning models and also improve the performance of machine learning models in multilabel multiclass classification tasks.

Dogs as a Natural Animal Model of Epilepsy

Epilepsy is a common neurological disease in both humans and domestic dogs, making dogs an ideal translational model of epilepsy. In both species, epilepsy is a complex brain disease characterized by an enduring predisposition to generate spontaneous recurrent epileptic seizures. Furthermore, as in humans, status epilepticus is one of the more common neurological emergencies in dogs with epilepsy. In both species, epilepsy is not a single disease but a group of disorders characterized by a broad array of clinical signs, age of onset, and underlying causes. Brain imaging suggests that the limbic system, including the hippocampus and cingulate gyrus, is often affected in canine epilepsy, which could explain the high incidence of comorbid behavioral problems such as anxiety and cognitive alterations. Resistance to antiseizure medications is a significant problem in both canine and human epilepsy, so dogs can be used to study mechanisms of drug resistance and develop novel therapeutic strategies to benefit both species. Importantly, dogs are large enough to accommodate intracranial EEG and responsive neurostimulation devices designed for humans. Studies in epileptic dogs with such devices have reported ictal and interictal events that are remarkably similar to those occurring in human epilepsy. Continuous (24/7) EEG recordings in a select group of epileptic dogs for >1 year have provided a rich dataset of unprecedented length for studying seizure periodicities and developing new methods for seizure forecasting. The data presented in this review substantiate that canine epilepsy is an excellent translational model for several facets of epilepsy research. Furthermore, several techniques of inducing seizures in laboratory dogs are discussed as related to therapeutic advances. Importantly, the development of vagus nerve stimulation as a novel therapy for drug-resistant epilepsy in people was based on a series of studies in dogs with induced seizures. Dogs with naturally occurring or induced seizures provide excellent large-animal models to bridge the translational gap between rodents and humans in the development of novel therapies. Furthermore, because the dog is not only a preclinical species for human medicine but also a potential patient and pet, research on this species serves both veterinary and human medicine.

Neuroimaging at 7 Tesla: a pictorial narrative review

Neuroimaging using the 7-Tesla (7T) human magnetic resonance (MR) system is rapidly gaining popularity after being approved for clinical use in the European Union and the USA. This trend is the same for functional MR imaging (MRI). The primary advantages of 7T over lower magnetic fields are its higher signal-to-noise and contrast-to-noise ratios, which provide high-resolution acquisitions and better contrast, making it easier to detect lesions and structural changes in brain disorders. Another advantage is the capability to measure a greater number of neurochemicals by virtue of the increased spectral resolution. Many structural and functional studies using 7T have been conducted to visualize details in the white matter and layers of the cortex and hippocampus, the subnucleus or regions of the putamen, the globus pallidus, thalamus and substantia nigra, and in small structures, such as the subthalamic nucleus, habenula, perforating arteries, and the perivascular space, that are difficult to observe at lower magnetic field strengths. The target disorders for 7T neuroimaging range from tumoral diseases to vascular, neurodegenerative, and psychiatric disorders, including Alzheimer's disease, Parkinson's disease, multiple sclerosis, epilepsy, major depressive disorder, and schizophrenia. MR spectroscopy has also been used for research because of its increased chemical shift that separates overlapping peaks and resolves neurochemicals more effectively at 7T than a lower magnetic field. This paper presents a narrative review of these topics and an illustrative presentation of images obtained at 7T. We expect 7T neuroimaging to provide a new imaging biomarker of various brain disorders.

Learning from the comorbidities of epilepsy

PURPOSE OF REVIEW

Comorbidities are a common feature in epilepsy, but neither the entire spectrum nor the significance of such comorbidities has been fully explored. We review comorbidities associated with epilepsy and their associated burden, provide an overview of relationships, and discuss a new conceptualization of the comorbidities.

RECENT FINDINGS

The epidemiology of the comorbidities of epilepsy and effects on health outcomes, healthcare use, and healthcare expenditures have been partly delineated. Distinct mechanisms of the associations have been suggested but not entirely ascertained. Movement from conceptualizing epilepsy as a condition to a symptom-complex has occurred.

SUMMARY

Comorbidities are common among people with epilepsy and are associated with poorer clinical outcomes and quality of life, greater use of health resources, and increased expenditure. Becoming aware of the associated mechanisms and their uncertainty is central to understanding the relationships between epilepsy and comorbid health conditions, which have implications for diagnosis and screening, medical management, and surgical management. Conceptualizing comorbidities of epilepsy as precipitating factors and epilepsy as the symptom will improve the understanding of epilepsy and catalyze research and improvements in clinical practice.

Late-life terminal seizure freedom in drug-resistant epilepsy: "Burned-out epilepsy"

The course of established epilepsy in late life is not fully known. One key question is whether the resolution of an epileptic diathesis is a natural outcome in some people with long-standing epilepsy. We investigated this with a view to generating a hypothesis. We retrospectively explored whether terminal seizure-freedom occurs in older people with previous drug-resistant epilepsy at the Chalfont Centre for Epilepsy over twenty years. Of the 226 people followed for a median period of 52 years, 39 (17%) achieved late-life terminal seizure-freedom of at least two years before death, which occurred at a median age of 68 years with a median duration of 7 years. Multivariate analysis suggests that a high initial seizure frequency was a negative predictor (p < 0.0005). Our findings indicate that the 'natural' course of long-standing epilepsy in some people is one of terminal seizure freedom. We also consider the concept of "remission" in epilepsy, its definition challenges, and the evolving terminology used to describe the state of seizure freedom. The intersection of ageing and seizure freedom is an essential avenue of future investigation, especially in light of current demographic trends. Gaining mechanistic insights into this phenomenon may help broaden our understanding of the neurobiology of epilepsy and potentially provide targets for therapeutic intervention.