Structural and Functional Alterations at Pre-Epileptic Stage Are Closely Associated with Epileptogenesis in Pilocarpine-induced Epilepsy Model

Progressive alterations in electrophysiological and epileptic network properties during the development of temporal lobe epilepsy in rats

OBJECTIVE

Refractory temporal lobe epilepsy (TLE) with recurring seizures causing continuing pathological changes in neural reorganization. There is an incomplete understanding of how spatiotemporal electrophysiological characteristics changes during the development of TLE. Long-term multi-site epilepsy patients' data is hard to obtain. Thus, our study relied on animal models to reveal the changes in electrophysiological and epileptic network characteristics systematically.

METHODS

Long-term local field potentials (LFPs) were recorded over a period of 1 to 4 months from 6 pilocarpine-treated TLE rats. We compared variations of seizure onset zone (SOZ), seizure onset pattern (SOP), the latency of seizure onsets, and functional connectivity network from 10-channel LFPs between the early and late stages. Moreover, three machine learning classifiers trained by early-stage data were used to test seizure detection performance in the late stage.

RESULTS

Compared to the early stage, the earliest seizure onset was more frequently detected in hippocampus areas in the late stage. The latency of seizure onsets between electrodes became shorter. Low-voltage fast activity (LVFA) was the most common SOP and the proportion of it increased in the late stage. Different brain states were observed during seizures using Granger causality (GC). Moreover, seizure detection classifiers trained by early-stage data were less accurate when tested in late-stage data.

SIGNIFICANCE

Neuromodulation especially closed-loop deep brain stimulation (DBS) is effective in the treatment of refractory TLE. Although the frequency or amplitude of the stimulation is generally adjusted in existing closed-loop DBS devices in clinical usage, the adjustment rarely considers the pathological progression of chronic TLE. This suggests that an important factor affecting the therapeutic effect of neuromodulation may have been overlooked. The present study reveals time-varying electrophysiological and epileptic network properties in chronic TLE rats and indicates that classifiers of seizure detection and neuromodulation parameters might be designed to adapt to the current state dynamically with the progression of epilepsy.

Stage- and Subfield-Associated Hippocampal miRNA Expression Patterns after Pilocarpine-Induced Status Epilepticus

OBJECTIVE

To investigate microRNA (miRNA) expression profiles before and after pilocarpine-induced status epilepticus (SE) in the cornu ammonis (CA) and dentated gyrus (DG) areas of the mouse hippocampus, and to predict the downstream proteins and related pathways based on bioinformatic analysis.

METHODS

An epileptic mouse model was established using a pilocarpine injection. Brain tissues from the CA and DG were collected separately for miRNA analysis. The miRNAs were extracted using a kit, and the expression profiles were generated using the SurePrint G3 Mouse miRNA microarray and validated. The intersecting genes of TargetScan and miRanda were selected to predict the target genes of each miRNA. For gene ontology (GO) studies, the parent-child-intersection (pci) method was used for enrichment analysis, and Benjamini-Hochberg was used for multiple test correction. The Kyoto Encyclopedia of Genes and Genomes (KEGG) was used to detect disease-related pathways among the large list of miRNA-targeted genes. All analyses mentioned above were performed at the time points of control, days 3, 14, and 60 post-SE.

RESULTS

Control versus days 3, 14, and 60 post-SE: in the CA area, a total of 131 miRNAs were differentially expressed; 53, 49, and 26 miRNAs were upregulated and 54, 10, and 22 were downregulated, respectively. In the DG area, a total of 171 miRNAs were differentially expressed; furthermore, 36, 32, and 28 miRNAs were upregulated and 78, 58, and 44 were downregulated, respectively. Of these, 92 changed in both the CA and DG, 39 only in the CA, and 79 only in the DG area. The differentially expressed miRNAs target 11-1630 genes. Most of these proteins have multiple functions in epileptogenesis. There were 15 common pathways related to altered miRNAs: nine different pathways in the CA and seven in the DG area.

CONCLUSIONS

Stage- and subfield-associated hippocampal miRNA expression patterns are closely related to epileptogenesis, although the detailed mechanisms need to be explored in the future.

A mathematical model of neuroimmune interactions in epileptogenesis for discovering treatment strategies

The development of epilepsy (epileptogenesis) involves a complex interplay of neuronal and immune processes. Here, we present a first-of-its-kind mathematical model to better understand the relationships among these processes. Our model describes the interaction between neuroinflammation, blood-brain barrier disruption, neuronal loss, circuit remodeling, and seizures. Formulated as a system of nonlinear differential equations, the model reproduces the available data from three animal models. The model successfully describes characteristic features of epileptogenesis such as its paradoxically long timescales (up to decades) despite short and transient injuries or the existence of qualitatively different outcomes for varying injury intensity. In line with the concept of degeneracy, our simulations reveal multiple routes toward epilepsy with neuronal loss as a sufficient but non-necessary component. Finally, we show that our model allows for in silico predictions of therapeutic strategies, revealing injury-specific therapeutic targets and optimal time windows for intervention.

•

A dynamical systems model describes the development of epilepsy after different injuries

•

Simulation results are in agreement with data from three animal models

•

Model shows degeneracy: multiple distinct but linked mechanisms cause epileptogenesis

•

Framework permits studying the effects of therapeutic interventions in silico

Choice of anesthesia and data analysis method strongly increases sensitivity of 18F-FDG PET imaging during experimental epileptogenesis

Purpose

Alterations in brain glucose metabolism detected by 2-deoxy-2-[¹⁸F]-fluoro-D-glucose (¹⁸F-FDG) positron emission tomography (PET) may serve as an early predictive biomarker and treatment target for epileptogenesis. Here, we aimed to investigate changes in cerebral glucose metabolism before induction of epileptogenesis, during epileptogenesis as well as during chronic epilepsy. As anesthesia is usually unavoidable for preclinical PET imaging and influences the distribution of the radiotracer, four different protocols were compared.

Procedures

We investigated ¹⁸F-FDG uptake phase in conscious rats followed by a static scan as well as dynamic scans under continuous isoflurane, medetomidine-midazolam-fentanyl (MMF), or propofol anesthesia. Furthermore, we applied different analysis approaches: atlas-based regional analysis, statistical parametric mapping, and kinetic analysis.

Results

At baseline and compared to uptake in conscious rats, isoflurane and propofol anesthesia resulted in decreased cortical ¹⁸F-FDG uptake while MMF anesthesia led to a globally decreased tracer uptake. During epileptogenesis, MMF anesthesia was clearly best distinctive for visualization of prominently increased glucometabolism in epilepsy-related brain areas. Kinetic modeling further increased sensitivity, particularly for continuous isoflurane anesthesia. During chronic epilepsy, hypometabolism affecting more or less the whole brain was detectable with all protocols.

Conclusion

This study reveals evaluation of anesthesia protocols for preclinical ¹⁸F-FDG PET imaging as a critical step in the study design. Together with an appropriate data analysis workflow, the chosen anesthesia protocol may uncover otherwise concealed disease-associated regional glucometabolic changes.

Inhibition of Glutamate Release, but Not of Glutamine Recycling to Glutamate, Is Involved in Delaying the Onset of Initial Lithium-Pilocarpine-Induced Seizures in Young Rats by a Non-Convulsive MSO Dose

Initial seizures observed in young rats during the 60 min after administration of pilocarpine (Pilo) were delayed and attenuated by pretreatment with a non-convulsive dose of methionine sulfoximine (MSO). We hypothesized that the effect of MSO results from a) glutamine synthetase block-mediated inhibition of conversion of Glu/Gln precursors to neurotransmitter Glu, and/or from b) altered synaptic Glu release. Pilo was administered 60 min prior to sacrifice, MSO at 75 mg/kg, i.p., 2.5 h earlier. [1,2-¹³C]acetate and [U-¹³C]glucose were i.p.-injected either together with Pilo (short period) or 15 min before sacrifice (long period). Their conversion to Glu and Gln in the hippocampus and entorhinal cortex was followed using [¹³C] gas chromatography-mass spectrometry. Release of in vitro loaded Glu surrogate, [³H]d-Asp from ex vivo brain slices was monitored in continuously collected superfusates. [³H]d-Asp uptake was tested in freshly isolated brain slices. At no time point nor brain region did MSO modify incorporation of [¹³C] to Glu or Gln in Pilo-treated rats. MSO pretreatment decreased by ~37% high potassium-induced [³H]d-Asp release, but did not affect [³H]d-Asp uptake. The results indicate that MSO at a non-convulsive dose delays the initial Pilo-induced seizures by interfering with synaptic Glu-release but not with neurotransmitter Glu recycling.

Identification of Brain Damage after Seizures Using an MR-Based Electrical Conductivity Imaging Method

Previous imaging studies have shown the morphological malformation and the alterations of ionic mobility, water contents, electrical properties, or metabolites in seizure brains. Magnetic resonance electrical properties tomography (MREPT) is a recently developed technique for the measurement of electrical tissue properties with a high frequency that provides cellular information regardless of the cell membrane. In this study, we examined the possibility of MREPT as an applicable technique to detect seizure-induced functional changes in the brain of rats. Ultra-high field (9.4 T) magnetic resonance imaging (MRI) was performed, 2 h, 2 days, and 1 week after the injection of N-methyl-D-aspartate (NMDA; 75 mg/kg). The conductivity images were reconstructed from B1 phase images using a magnetic resonance conductivity imaging (MRCI) toolbox. The high-frequency conductivity was significantly decreased in the hippocampus among various brain regions of NMDA-treated rats. Nissl staining showed shrunken cell bodies and condensed cytoplasm potently at 2 h after NMDA treatment, and neuronal cell loss at all time points in the hippocampus. These results suggest that the reduced electrical conductivity may be associated with seizure-induced neuronal loss in the hippocampus. Magnetic resonance (MR)-based electrical conductivity imaging may be an applicable technique to non-invasively identify brain damage after a seizure.

DNA methylation: A mechanism for sustained alteration of KIR4.1 expression following central nervous system insult

Kir4.1, a glial-specific inwardly rectifying potassium channel, is implicated in astrocytic maintenance of K+ homeostasis. Underscoring the role of Kir4.1 in central nervous system (CNS) functioning, genetic mutations in KCNJ10, the gene which encodes Kir4.1, causes seizures, ataxia and developmental disability in humans. Kir4.1 protein and mRNA loss are consistently observed in CNS injury and neurological diseases linked to hyperexcitability and neuronal dysfunction, leading to the notion that Kir4.1 represents an attractive therapeutic target. Despite this, little is understood regarding the mechanisms that underpin this downregulation. Previous work by our lab revealed that DNA hypomethylation of the Kcnj10 gene functions to regulate mRNA levels during astrocyte maturation whereas hypermethylation in vitro led to decreased promoter activity. In the present study, we utilized two vastly different injury models with known acute and chronic loss of Kir4.1 protein and mRNA to evaluate the methylation status of Kcnj10 as a candidate molecular mechanism for reduced transcription and subsequent protein loss. Examining whole hippocampal tissue and isolated astrocytes, in a lithium-pilocarpine model of epilepsy, we consistently identified hypermethylation of CpG island two, which resides in the large intronic region spanning the Kcnj10 gene. Strikingly similar results were observed using the second injury paradigm, a fifth cervical (C5) vertebral hemi-contusion model of spinal cord injury. Our previous work indicates the same gene region is significantly hypomethylated when transcription increases during astrocyte maturation. Our results suggest that DNA methylation can bidirectionally modulate Kcnj10 transcription and may represent a targetable molecular mechanism for the restoring astroglial Kir4.1 expression following CNS insult.

Artificial Intelligence and Computational Approaches for Epilepsy

Studies on treatment of epilepsy have been actively conducted in multiple avenues, but there are limitations in improving its efficacy due to between-subject variability in which treatment outcomes vary from patient to patient. Accordingly, there is a growing interest in precision medicine that provides accurate diagnosis for seizure types and optimal treatment for an individual epilepsy patient. Among these approaches, computational studies making this feasible are rapidly progressing in particular and have been widely applied in epilepsy. These computational studies are being conducted in two main streams: 1) artificial intelligence-based studies implementing computational machines with specific functions, such as automatic diagnosis and prognosis prediction for an individual patient, using machine learning techniques based on large amounts of data obtained from multiple patients and 2) patient-specific modeling-based studies implementing biophysical in-silico platforms to understand pathological mechanisms and derive the optimal treatment for each patient by reproducing the brain network dynamics of the particular patient per se based on individual patient's data. These computational approaches are important as it can integrate multiple types of data acquired from patients and analysis results into a single platform. If these kinds of methods are efficiently operated, it would suggest a novel paradigm for precision medicine.

Enzymatic Digestion of Hyaluronan-Based Brain Extracellular Matrix in vivo Can Induce Seizures in Neonatal Mice

It is well-known that hyaluronic acid (HA) as a component of brain extracellular matrix (ECM) plays a pivotal role in the nervous system and is involved in synaptic plasticity changes in vascular cognitive impairment and dementia. HA breakdown is a feature of the acute stage of stroke injury and may be detrimental through enhancement of the inflammatory response. Recent studies have shown that knockout mice lacking hyaluronic acid synthetase demonstrates epileptic phenotype in vivo and removal of HA leads to delayed development of epileptiform activity in cultured hippocampal neurons in vitro. Here, we studied whether digestion of hyaluronic acid in the hippocampus in early postnatal period can trigger seizures. Hyaluronidase (Hyal) (5 U/μl) was bilaterally injected into C57BL/6j mice (P17) CA1 field of hippocampus using the stereotaxic method to remove hyaluronan-based ECM. Transcriptome analysis of hippocampal tissue 2 h after enzymatic digestion of hyaluronan-based brain ECM revealed increased gene expression of proteins involved in inflammation reactions (TLR2, CCL2,3,5), neuroinflammation, axonal guidance and ephrin receptor signaling, versus the vehicle group. Mice injected with hyaluronidase exhibited delayed audiogenic seizures and improvement in working memory 72 h after injection, while there were no changes in locomotor activity, anxious level and exploratory behavior due to the open field test. The obtained results point to a link between the activation of neuroinflammation by enzymatic digestion of hyaluronan-based brain ECM during the neonatal period and their subsequent reactivity to seizures, which may play an important role in the functional features of the developing brain, including its seizure propensity.