From precision diagnosis to precision treatment in epilepsy

Visual detection of seizures in mice using supervised machine learning

Seizures are caused by abnormally synchronous brain activity that can result in changes in muscle tone, such as twitching, stiffness, limpness, or rhythmic jerking. These behavioral manifestations are clear on visual inspection and the most widely used seizure scoring systems in preclinical models, such as the Racine scale in rodents, use these behavioral patterns in semiquantitative seizure intensity scores. However, visual inspection is time-consuming, low-throughput, and partially subjective, and there is a need for rigorously quantitative approaches that are scalable. In this study, we used supervised machine learning approaches to develop automated classifiers to predict seizure severity directly from noninvasive video data. Using the PTZ-induced seizure model in mice, we trained video-only classifiers to predict ictal events, combined these events to predict an univariate seizure intensity for a recording session, as well as time-varying seizure intensity scores. Our results show, for the first time, that seizure events and overall intensity can be rigorously quantified directly from overhead video of mice in a standard open field using supervised approaches. These results enable high-throughput, noninvasive, and standardized seizure scoring for downstream applications such as neurogenetics and therapeutic discovery.

Epilepsy: Mitochondrial connections to the 'Sacred' disease

Over 65 million people suffer from recurrent, unprovoked seizures. The lack of validated biomarkers specific for myriad forms of epilepsy makes diagnosis challenging. Diagnosis and monitoring of childhood epilepsy add to the need for non-invasive biomarkers, especially when evaluating antiseizure medications. Although underlying mechanisms of epileptogenesis are not fully understood, evidence for mitochondrial involvement is substantial. Seizures affect 35%-60% of patients diagnosed with mitochondrial diseases. Mitochondrial dysfunction is pathophysiological in various epilepsies, including those of non-mitochondrial origin. Decreased ATP production caused by malfunctioning brain cell mitochondria leads to altered neuronal bioenergetics, metabolism and neurological complications, including seizures. Iron-dependent lipid peroxidation initiates ferroptosis, a cell death pathway that aligns with altered mitochondrial bioenergetics, metabolism and morphology found in neurodegenerative diseases (NDDs). Studies in mouse genetic models with seizure phenotypes where the function of an essential selenoprotein (GPX4) is targeted suggest roles for ferroptosis in epilepsy. GPX4 is pivotal in NDDs, where selenium protects interneurons from ferroptosis. Selenium is an essential central nervous system micronutrient and trace element. Low serum concentrations of selenium and other trace elements and minerals, including iron, are noted in diagnosing childhood epilepsy. Selenium supplements alleviate intractable seizures in children with reduced GPX activity. Copper and cuproptosis, like iron and ferroptosis, link to mitochondria and NDDs. Connecting these mechanistic pathways to selenoproteins provides new insights into treating seizures, pointing to using medicines including prodrugs of lipoic acid to treat epilepsy and to potential alternative therapeutic approaches including transcranial magnetic stimulation (transcranial), photobiomodulation and vagus nerve stimulation.

How have the recent updated epilepsy classifications impacted on diagnosis and treatment?

INTRODUCTION

Epilepsies are a diverse group of disorders which differ regarding prognosis for seizure control and associated comorbidities. Accurate classification is critical to choose the highest yield investigations and best therapeutic options and to provide the most accurate prognoses regarding the expected degree of seizure control, possible remission, and risk of associated comorbidities to patients and their families. This article reviews the recent updates in epilepsy classification to illustrate how accurate classification impacts care for persons with epilepsy.

AREAS COVERED

The authors discuss the ILAE 2017 Classification of the Epilepsies along with the modification of the classification for neonatal seizures and epilepsies. They also discuss the ILAE position papers on Epilepsy syndromes in neonates and infants and children of variable age and the Idiopathic Generalized Epilepsies.

EXPERT OPINION

Accurate epilepsy classification allows selection of the highest yield investigations, choice of optimal therapies, and accurate prognostication of seizures (likelihood of response to antiseizure treatments and likelihood of remission with age), as well as comorbidities (likelihood, type, and severity). As we move into the era of disease modifying therapy, early accurate identification of underlying causes with timely introduction of specific treatments will be crucial to lessen the severity of epilepsy, with improved seizure control and attenuation of associated comorbidities.