No abstract

There remains an urgent need for new therapies for drug-resistant epilepsy (DRE). Sodium channel blockers are effective for seizure control in common forms of epilepsy, but loss of sodium channel function underlies some genetic forms of epilepsy. Approaches that provide bi-directional control of sodium channel expression are needed. MicroRNAs (miRNA) are small non-coding RNAs which negatively regulate gene expression. Here, we show that genome-wide miRNA screening of hippocampal tissue from a rat epilepsy model, mice treated with the novel anti-seizure medicine cannabidiol (CBD) and plasma from patients with DRE, converge on a single target, miR-335-5p. Pathway analysis on predicted and validated miR-335-5p targets identified multiple voltage-gated sodium channels (VGSCs). Intracerebroventricular injection of antisense oligonucleotides against miR-335-5p resulted in upregulation of Scn1a, Scn2a and Scn3a in the mouse brain and an increased action potential rising phase and greater excitability of hippocampal pyramidal neurons in brain slice recordings, consistent with VGSCs as functional targets of miR-335-5p. Blocking of miR-335-5p also increased voltage-gated sodium currents in human iPSC-derived neurons. Inhibition of miR-335-5p increased susceptibility to tonic-clonic seizures in the pentylenetetrazole seizure model, whereas AAV9-mediated overexpression of miR-335-5p reduced seizure severity and improved survival. These studies suggest modulation of miR-335-5p may be a means to regulate VGSCs and affect brain excitability and seizures. Changes to miR-335-5p may reflect compensatory mechanisms to control excitability and could provide new biomarker or therapeutic strategies for different types of drug-resistant epilepsy.

The smooth conduct of movements requires simultaneous motor planning and execution according to internal goals. So far it remains unknown how such movement plans are modified without interfering with ongoing movements. Previous studies have isolated planning and execution-related neuronal activity by separating behavioral planning and movement periods in time by sensory cues. Here, we separate continuous self-paced motor planning from motor execution statistically, by experimentally minimizing the repetitiveness of the movements. This approach shows that, in the rat sensorimotor cortex, neuronal motor planning processes evolve with slower dynamics than movement-related responses. Fast-evolving neuronal activity precees skilled forelimb movements and is nested within slower dynamics. We capture this effect via high-pass filtering and confirm the results with optogenetic stimulations. The various dynamics combined with adaptation-based high-pass filtering provide a simple principle for separating concurrent motor planning and execution.

There remains an urgent need for new therapies for treatment-resistant epilepsy. Sodium channel blockers are effective for seizure control in common forms of epilepsy, but loss of sodium channel function underlies some genetic forms of epilepsy. Approaches that provide bidirectional control of sodium channel expression are needed. MicroRNAs (miRNA) are small noncoding RNAs which negatively regulate gene expression. Here we show that genome-wide miRNA screening of hippocampal tissue from a rat epilepsy model, mice treated with the antiseizure medicine cannabidiol, and plasma from patients with treatment-resistant epilepsy, converge on a single target—miR-335-5p. Pathway analysis on predicted and validated miR-335-5p targets identified multiple voltage-gated sodium channels (VGSCs). Intracerebroventricular injection of antisense oligonucleotides against miR-335-5p resulted in upregulation of Scn1a , Scn2a , and Scn3a in the mouse brain and an increased action potential rising phase and greater excitability of hippocampal pyramidal neurons in brain slice recordings, consistent with VGSCs as functional targets of miR-335-5p. Blocking miR-335-5p also increased voltage-gated sodium currents and SCN1A, SCN2A , and SCN3A expression in human induced pluripotent stem cell-derived neurons. Inhibition of miR-335-5p increased susceptibility to tonic-clonic seizures in the pentylenetetrazol seizure model, whereas adeno-associated virus 9-mediated overexpression of miR-335-5p reduced seizure severity and improved survival. These studies suggest modulation of miR-335-5p may be a means to regulate VGSCs and affect neuronal excitability and seizures. Changes to miR-335-5p may reflect compensatory mechanisms to control excitability and could provide biomarker or therapeutic strategies for different types of treatment-resistant epilepsy.

Objective. Electroencephalography (EEG) is a key tool for non-invasive recording of brain activity and the diagnosis of epilepsy. EEG monitoring is also widely employed in rodent models to track epilepsy development and evaluate experimental therapies and interventions. Whereas automated seizure detection algorithms have been developed for clinical EEG, preclinical versions face challenges of inter-model differences and lack of EEG standardization, leaving researchers relying on time-consuming visual annotation of signals. Approach. In this study, a machine learning-based seizure detection approach, ‘Epi-AI’, which can semi-automate EEG analysis in multiple mouse models of epilepsy was developed. Twenty-six mice with a total EEG recording duration of 6451 h were used to develop and test the Epi-AI approach. EEG recordings were obtained from two mouse models of kainic acid-induced epilepsy (Models I and III), a genetic model of Dravet syndrome (Model II) and a pilocarpine mouse model of epilepsy (Model IV). The Epi-AI algorithm was compared against two threshold-based approaches for seizure detection, a local Teager-Kaiser energy operator (TKEO) approach and a global Teager-Kaiser energy operator-discrete wavelet transform (TKEO-DWT) combination approach. Main results. Epi-AI demonstrated a superior sensitivity, 91.4%–98.8%, and specificity, 93.1%–98.8%, in Models I–III, to both of the threshold-based approaches which performed well on individual mouse models but did not generalise well across models. The performance of the TKEO approach in Models I–III ranged from 66.9%–91.3% sensitivity and 60.8%–97.5% specificity to detect spontaneous seizures when compared with expert annotations. The sensitivity and specificity of the TKEO-DWT approach were marginally better than the TKEO approach in Models I–III at 73.2%–80.1% and 75.8%–98.1%, respectively. When tested on EEG from Model IV which was not used in developing the Epi-AI approach, Epi-AI was able to identify seizures with 76.3% sensitivity and 98.1% specificity. Significance. Epi-AI has the potential to provide fast, objective and reproducible semi-automated analysis of multiple types of seizure in long-duration EEG recordings in rodents.

Drug-resistant epilepsy remains a significant clinical and societal burden, with one third of people with epilepsy continuing to experience seizures despite the availability of around 30 anti-seizure drugs (ASDs). Further, ASDs often have substantial adverse effects, including impacts on learning and memory. Therefore, it is important to develop new ASDs, which may be more potent or better tolerated. Here, we report the preliminary preclinical evaluation of BICS01, a synthetic product based on a natural compound, as a potential ASD. To model seizure-like activity in vitro, we prepared hippocampal slices from adult male Sprague Dawley rats, and elicited epileptiform bursting using high extracellular potassium. BICS01 (200 μM) rapidly and reversibly reduced the frequency of epileptiform bursting but did not change broad measures of network excitability or affect short-term synaptic facilitation. BICS01 was well tolerated following systemic injection at up to 1,000 mg/kg. However, we did not observe any protective effect of systemic BICS01 injection against acute seizures evoked by pentylenetetrazol. These results indicate that BICS01 is able to acutely reduce epileptiform activity in hippocampal networks. Further preclinical development studies to enhance pharmacokinetics and accumulation in the brain, as well as studies to understand the mechanism of action, are now required.

The diagnosis of epilepsy is complex and challenging and would benefit from the availability of molecular biomarkers, ideally measurable in a biofluid such as blood. Experimental and human epilepsy are associated with altered brain and blood levels of various microRNAs (miRNAs). Evidence is lacking, however, as to whether any of the circulating pool of miRNAs originates from the brain. To explore the link between circulating miRNAs and the pathophysiology of epilepsy, we first sequenced Ago2-bound miRNAs in plasma samples collected from mice subject to status epilepticus (SE) induced by intraamygdala microinjection of kainic acid. This identified time-dependent changes in plasma levels of miRNAs with known neuronal and microglial-cell origins. To explore whether the circulating miRNAs had originated from the brain, we generated mice expressing FLAG-Ago2 in neurons or microglia using tamoxifen-inducible Thy1 or Cx3cr1 promoters, respectively. FLAG immunoprecipitates from the plasma of these mice after seizures contained miRNAs, including let-7i-5p and miR-19b-3p. Taken together, these studies confirm that a portion of the circulating pool of miRNAs in experimental epilepsy originates from the brain, increasing support for miRNAs as mechanistic biomarkers of epilepsy.

The smooth conduction of movements requires simultaneous motor planning and execution according to internal goals. So far it is not known how such movement plans can be modified without being distorted by ongoing movements. Previous studies have isolated planning and execution related neuronal activity by separating behavioral planning and movement periods in time by sensory cues1–7. Here, we introduced two novel tasks in which motor planning developed intrinsically. We separated this continuous self-paced motor planning statistically from motor execution by experimentally minimizing the repetitiveness of the movements. Thereby, we found that in the rat sensorimotor cortex, neuronal motor planning processes evolved with slower dynamics than movement related responses both on a sorted unit and population level. The fast evolving neuronal activity preceded skilled forelimb movements while it coincided with movements in a locomotor task. We captured this fast evolving movement related activity via a high-pass filter approach and confirmed the results with optogenetic stimulations. As biological mechanism underlying such a high pass filtering we suggest neuronal adaption. The differences in dynamics combined with a high pass filtering mechanism represents a simple principle for concurrent motor planning and execution in which planning will result in relatively slow dynamics that will not produce movements.