Paroxysmal slow wave events predict epilepsy following a first seizure.

OBJECTIVE: Management of a patient presenting with a first seizure depends on the risk of additional seizures. In clinical practice, the recurrence risk is estimated by the treating physician using the neurological examination, brain imaging, a thorough history for risk factors, and routine scalp electroencephalogram (EEG) to detect abnormal epileptiform activity. The decision to use antiseizure medication can be challenging when objective findings are missing. There is a need for new biomarkers to better diagnose epilepsy following a first seizure. Recently, an EEG-based novel analytical method was reported to detect paroxysmal slowing in the cortical network of patients with epilepsy. The aim of our study is to test this method's sensitivity and specificity to predict epilepsy following a first seizure. METHODS: We analyzed interictal EEGs of 70 patients admitted to the emergency department of a tertiary referral center after a first seizure. Clinical data from a follow-up period of at least 18 months were available. EEGs of 30 healthy controls were also analyzed and included. For each EEG, we applied an automated algorithm to detect paroxysmal slow wave events (PSWEs). RESULTS: Of patients presenting with a first seizure, 40% had at least one additional recurring seizure and were diagnosed with epilepsy. Sixty percent did not report additional seizures. A significantly higher occurrence of PSWEs was detected in the first interictal EEG test of those patients who were eventually diagnosed with epilepsy. Conducting the EEG test within 72 h after the first seizure significantly increased the likelihood of detecting PSWEs and the predictive value for epilepsy up to 82%. SIGNIFICANCE: The quantification of PSWEs by an automated algorithm can predict epilepsy and help the neurologist in evaluating a patient with a first seizure.

Dual-Targeted Autoimmune Sword in Fatal Epilepsy: Patient's glutamate receptor AMPA GluR3B peptide autoimmune antibodies bind, induce Reactive Oxygen Species (ROS) in, and kill both human neural cells and T cells.

Nodding Syndrome (NS) is a fatal pediatric epilepsy of unknown etiology, accompanied by multiple neurological impairments, and associated with Onchocerca volvulus (Ov), malnutrition, war-induced trauma, and other insults. NS patients have neuroinflammation, and ~50% have cross-reactive Ov/Leiomodin-1 neurotoxic autoimmune antibodies. RESULTS: Studying 30 South Sudanese NS patients and a similar number of healthy subjects from the same geographical region, revealed autoimmune antibodies to 3 extracellular peptides of ionotropic glutamate receptors in NS patients: AMPA-GluR3B peptide antibodies (86%), NMDA-NR1 peptide antibodies (77%) and NMDA-NR2 peptide antibodies (87%) (in either 1:10, 1:100 or 1:1000 serum dilution). In contrast, NS patients did not have 26 other well-known autoantibodies that target the nervous system in several autoimmune-mediated neurological diseases. We demonstrated high expression of both AMPA-GluR3 and NMDA-NR1 in human neural cells, and also in normal human CD3+ T cells of both helper CD4+ and cytotoxic CD8+ types. Patient's GluR3B peptide antibodies were affinity-purified, and by themselves precipitated short 70 kDa neuronal GluR3. NS patient's affinity-purified GluR3B peptide antibodies also bound to, induced Reactive Oxygen Species (ROS) in, and killed both human neural cells and T cells within 1-2 hours only. NS patient's purified IgGs, or serum (1:10 or 1:30), induced similar effects. In vivo video EEG experiments in normal mice, revealed that when NS patient's purified IgGs were released continuously (24/7 for 1 week) in normal mouse brain, they induced all the following: 1.Seizures, 2. Cerebellar Purkinje cell loss, 3. Degeneration in the hippocampus and cerebral cortex, and 4. Elevation of CD3+ T cells, and of activated Mac-2+microglia and GFAP+astrocytes in both the gray and white matter of the cerebral cortex, hippocampus, corpus calossum and cerebellum of mice. NS patient's serum cytokines: IL-1ß, IL-2, IL-6, IL-8, TNFα, IFNγ, are reduced by 85-99% compared to healthy subjects, suggesting severe immunodeficiency in NS patients. This suspected immunodeficiency could be caused by combined effects of the: 1. Chronic Ov infection, 2. Malnutrition, 3. Killing of NS patient's T cells by patient's own GluR3B peptide autoimmune antibodies (alike the killing of normal human T cells by the NS patient's GluR3B peptide antibodies found herein in vitro). CONCLUSIONS: Regardless of NS etiology, NS patients suffer from 'Dual-targeted Autoimmune Sword': autoimmune AMPA GluR3B peptide antibodies that bind, induce ROS in, and kill both neural cells and T cells. These neurotoxic and immunotoxic GluR3B peptide autoimmune antibodies, and also NS patient's NMDA-NR1/NR2A and Ov/Leiomodin-1 autoimmune antibodies, must be silenced or removed. Moreover, the findings of this study are relevant not only to NS, but also to many more patients with other types of epilepsy, which have GluR3B peptide antibodies in serum and/or CSF. This claim is based on the following facts: 1. The GluR3 subunit is expressed in neural cells in crucial brains regions, in motor neurons in the spinal cord, and also in other cells in the body, among them T cells of the immune system, 2. The GluR3 subunit has diverse neurophysiological role, and its deletion or abnormal function can: disrupt oscillatory networks of both sleep and breathing, impair motor coordination and exploratory activity, and increase the susceptibility to generate seizures, 3. GluR3B peptide antibodies were found so far in ~27% of >300 epilepsy patients worldwide, which suffer from various other types of severe, intractable and enigmatic epilepsy, and which turned out to be 'Autoimmune Epilepsy'. Furthermore, the findings of this study could be relevant to different neurological diseases besides epilepsy, since other neurotransmitter-receptors autoantibodies are present in other neurological and psychiatric diseases, e.g. autoimmune antibodies against other GluRs, Dopamine receptors, GABA receptors, Acetylcholine receptors and others. These neurotransmitter-receptors autoimmune autoantibodies might also act as 'Dual-targeted Autoimmune Sword' and damage both neural cells and T cells (as the AMPA-GluR3B peptide antibodies induced in the present study), since T cells, alike neural cells, express most if not all these neurotransmitter receptors, and respond functionally to the respective neurotransmitters - a scientific and clinical topic we coined 'Nerve-Driven Immunity'.

Paroxysmal slow cortical activity in Alzheimer's disease and epilepsy is associated with blood-brain barrier dysfunction.

A growing body of evidence shows that epileptic activity is frequent but often undiagnosed in patients with Alzheimer's disease (AD) and has major therapeutic implications. Here, we analyzed electroencephalogram (EEG) data from patients with AD and found an EEG signature of transient slowing of the cortical network that we termed paroxysmal slow wave events (PSWEs). The occurrence per minute of the PSWEs was correlated with level of cognitive impairment. Interictal (between seizures) PSWEs were also found in patients with epilepsy, localized to cortical regions displaying blood-brain barrier (BBB) dysfunction, and in three rodent models with BBB pathology: aged mice, young 5x familial AD model, and status epilepticus-induced epilepsy in young rats. To investigate the potential causative role of BBB dysfunction in network modifications underlying PSWEs, we infused the serum protein albumin directly into the cerebral ventricles of naïve young rats. Infusion of albumin, but not artificial cerebrospinal fluid control, resulted in high incidence of PSWEs. Our results identify PSWEs as an EEG manifestation of nonconvulsive seizures in patients with AD and suggest BBB pathology as an underlying mechanism and as a promising therapeutic target.

Dynamic changes in murine forebrain miR-211 expression associate with cholinergic imbalances and epileptiform activity.

Epilepsy is a common neurological disease, manifested in unprovoked recurrent seizures. Epileptogenesis may develop due to genetic or pharmacological origins or following injury, but it remains unclear how the unaffected brain escapes this susceptibility to seizures. Here, we report that dynamic changes in forebrain microRNA (miR)-211 in the mouse brain shift the threshold for spontaneous and pharmacologically induced seizures alongside changes in the cholinergic pathway genes, implicating this miR in the avoidance of seizures. We identified miR-211 as a putative attenuator of cholinergic-mediated seizures by intersecting forebrain miR profiles that were Argonaute precipitated, synaptic vesicle target enriched, or differentially expressed under pilocarpine-induced seizures, and validated TGFBR2 and the nicotinic antiinflammatory acetylcholine receptor nAChRa7 as murine and human miR-211 targets, respectively. To explore the link between miR-211 and epilepsy, we engineered dTg-211 mice with doxycycline-suppressible forebrain overexpression of miR-211. These mice reacted to doxycycline exposure by spontaneous electrocorticography-documented nonconvulsive seizures, accompanied by forebrain accumulation of the convulsive seizures mediating miR-134. RNA sequencing demonstrated in doxycycline-treated dTg-211 cortices overrepresentation of synaptic activity, Ca2+ transmembrane transport, TGFBR2 signaling, and cholinergic synapse pathways. Additionally, a cholinergic dysregulated mouse model overexpressing a miR refractory acetylcholinesterase-R splice variant showed a parallel propensity for convulsions, miR-211 decreases, and miR-134 elevation. Our findings demonstrate that in mice, dynamic miR-211 decreases induce hypersynchronization and nonconvulsive and convulsive seizures, accompanied by expression changes in cholinergic and TGFBR2 pathways as well as in miR-134. Realizing the importance of miR-211 dynamics opens new venues for translational diagnosis of and interference with epilepsy.

Electrocorticographic Dynamics as a Novel Biomarker in Five Models of Epileptogenesis.

Postinjury epilepsy (PIE) is a devastating sequela of various brain insults. While recent studies offer novel insights into the mechanisms underlying epileptogenesis and discover potential preventive treatments, the lack of PIE biomarkers hinders the clinical implementation of such treatments. Here we explored the biomarker potential of different electrographic features in five models of PIE. Electrocorticographic or intrahippocampal recordings of epileptogenesis (from the insult to the first spontaneous seizure) from two laboratories were analyzed in three mouse and two rat PIE models. Time, frequency, and fractal and nonlinear properties of the signals were examined, in addition to the daily rate of epileptiform spikes, the relative power of five frequency bands (theta, alpha, beta, low gamma, and high gamma) and the dynamics of these features over time. During the latent pre-seizure period, epileptiform spikes were more frequent in epileptic compared with nonepileptic rodents; however, this feature showed limited predictive power due to high inter- and intra-animal variability. While nondynamic rhythmic representation failed to predict epilepsy, the dynamics of the theta band were found to predict PIE with a sensitivity and specificity of >90%. Moreover, theta dynamics were found to be inversely correlated with the latency period (and thus predict the onset of seizures) and with the power change of the high-gamma rhythm. In addition, changes in theta band power during epileptogenesis were associated with altered locomotor activity and distorted circadian rhythm. These results suggest that changes in theta band during the epileptogenic period may serve as a diagnostic biomarker for epileptogenesis, able to predict the future onset of spontaneous seizures.SIGNIFICANCE STATEMENT Postinjury epilepsy is an unpreventable and devastating disorder that develops following brain injuries, such as traumatic brain injury and stroke, and is often associated with neuropsychiatric comorbidities. As PIE affects as many as 20% of brain-injured patients, reliable biomarkers are imperative before any preclinical therapeutics can find clinical translation. We demonstrate the capacity to predict the epileptic outcome in five different models of PIE, highlighting theta rhythm dynamics as a promising biomarker for epilepsy. Our findings prompt the exploration of theta dynamics (using repeated electroencephalographic recordings) as an epilepsy biomarker in brain injury patients.