Modeling pathogenesis and treatment response in childhood absence epilepsy

Modelling the effect of allopregnanolone on the resolution of spike-wave discharges

Childhood absence epilepsy (CAE) is a paediatric generalized epilepsy disorder with a confounding feature of resolving in adolescence in a majority of cases. In this study, we modelled how the small-scale (synapse-level) effect of progesterone metabolite allopregnanolone induces a large-scale (network-level) effect on a thalamocortical circuit associated with this disorder. In particular, our goal was to understand the role of sex steroid hormones in the spontaneous remission of CAE. The conductance-based computational model consisted of single-compartment cortical pyramidal, cortical interneurons, thalamic reticular and thalamocortical relay neurons, each described by a set of ordinary differential equations. Excitatory and inhibitory synapses were mediated by AMPA, GABAa and GABAb receptors. The model was implemented using the NetPyne modelling tool and the NEURON simulator. It was found that the action of allopregnanolone (ALLO) on individual GABAa-receptor mediated synapses can have an ameliorating effect on spike-wave discharges (SWDs) associated with absence seizures. This effect is region-specific and most significant in the thalamus, particularly the synapses between thalamic reticular neurons. The remedying effect of allopregnanolone on SWDs may possibly be true only for individuals that are predisposed to remission due to intrinsic connectivity differences or differences in tonic inhibition. These results are a useful first-step and prescribe directions for further investigation into the role of ALLO together with these differences to distinguish between models for CAE-remitting and non-remitting individuals.

Genotype-function-phenotype correlations for SCN1A variants identified by clinical genetic testing

OBJECTIVE

Interpretation of clinical genetic testing, which identifies a potential genetic etiology in 25% of children with epilepsy, is limited by variants of uncertain significance. Understanding functional consequences of variants can help distinguish pathogenic from benign alleles. We combined automated patch clamp recording with neurophysiological simulations to discern genotype-function-phenotype correlations in a real-world cohort of children with SCN1A-associated epilepsy.

METHODS

Clinical data were extracted for children with SCN1A variants identified by clinical genetic testing. Functional properties of non-truncating NaV1.1 variant channels were determined using automated patch clamp recording. Functional data were incorporated into a parvalbumin-positive (PV+) interneuron computer model to predict variant effects on neuron firing and were compared with longitudinal clinical data describing epilepsy types, neurocognitive outcomes, and medication response.

RESULTS

Twelve SCN1A variants were identified (nine non-truncating). Six non-truncating variants exhibited no measurable sodium current in heterologous cells consistent with complete loss of function (LoF). Two variants caused either partial LoF (L479P) or a mixture of gain and loss of function (I1356M). The remaining non-truncating variant (T1250M) exhibited normal function. Functional data changed classification of pathogenicity for six variants. Complete LoF variants were universally associated with seizure onset before one year of age and febrile seizures, and were often associated with drug resistant epilepsy and below average cognitive outcomes. Simulations demonstrated abnormal firing in heterozygous model neurons containing dysfunctional variants.

INTERPRETATION

In SCN1A-associated epilepsy, functional analysis and neuron simulation studies resolved variants of uncertain significance and correlated with aspects of phenotype and medication response.

Similar excitability through different sodium channels and implications for the analgesic efficacy of selective drugs

Nociceptive sensory neurons convey pain-related signals to the CNS using action potentials. Loss-of-function mutations in the voltage-gated sodium channel NaV1.7 cause insensitivity to pain (presumably by reducing nociceptor excitability) but clinical trials seeking to treat pain by inhibiting NaV1.7 pharmacologically have struggled. This may reflect the variable contribution of NaV1.7 to nociceptor excitability. Contrary to claims that NaV1.7 is necessary for nociceptors to initiate action potentials, we show that nociceptors can achieve similar excitability using different combinations of NaV1.3, NaV1.7, and NaV1.8. Selectively blocking one of those NaV subtypes reduces nociceptor excitability only if the other subtypes are weakly expressed. For example, excitability relies on NaV1.8 in acutely dissociated nociceptors but responsibility shifts to NaV1.7 and NaV1.3 by the fourth day in culture. A similar shift in NaV dependence occurs in vivo after inflammation, impacting ability of the NaV1.7-selective inhibitor PF-05089771 to reduce pain in behavioral tests. Flexible use of different NaV subtypes exemplifies degeneracy - achieving similar function using different components - and compromises reliable modulation of nociceptor excitability by subtype-selective inhibitors. Identifying the dominant NaV subtype to predict drug efficacy is not trivial. Degeneracy at the cellular level must be considered when choosing drug targets at the molecular level.

Modelling novelty detection in the thalamocortical loop

In complex natural environments, sensory systems are constantly exposed to a large stream of inputs. Novel or rare stimuli, which are often associated with behaviorally important events, are typically processed differently than the steady sensory background, which has less relevance. Neural signatures of such differential processing, commonly referred to as novelty detection, have been identified on the level of EEG recordings as mismatch negativity (MMN) and on the level of single neurons as stimulus-specific adaptation (SSA). Here, we propose a multi-scale recurrent network with synaptic depression to explain how novelty detection can arise in the whisker-related part of the somatosensory thalamocortical loop. The "minimalistic" architecture and dynamics of the model presume that neurons in cortical layer 6 adapt, via synaptic depression, specifically to a frequently presented stimulus, resulting in reduced population activity in the corresponding cortical column when compared with the population activity evoked by a rare stimulus. This difference in population activity is then projected from the cortex to the thalamus and amplified through the interaction between neurons of the primary and reticular nuclei of the thalamus, resulting in rhythmic oscillations. These differentially activated thalamic oscillations are forwarded to cortical layer 4 as a late secondary response that is specific to rare stimuli that violate a particular stimulus pattern. Model results show a strong analogy between this late single neuron activity and EEG-based mismatch negativity in terms of their common sensitivity to presentation context and timescales of response latency, as observed experimentally. Our results indicate that adaptation in L6 can establish the thalamocortical dynamics that produce signatures of SSA and MMN and suggest a mechanistic model of novelty detection that could generalize to other sensory modalities.

Degeneracy in epilepsy: multiple routes to hyperexcitable brain circuits and their repair

Due to its complex and multifaceted nature, developing effective treatments for epilepsy is still a major challenge. To deal with this complexity we introduce the concept of degeneracy to the field of epilepsy research: the ability of disparate elements to cause an analogous function or malfunction. Here, we review examples of epilepsy-related degeneracy at multiple levels of brain organisation, ranging from the cellular to the network and systems level. Based on these insights, we outline new multiscale and population modelling approaches to disentangle the complex web of interactions underlying epilepsy and to design personalised multitarget therapies.

Childhood absence epilepsy patients with cognitive impairment have decreased sleep spindle density

OBJECTIVE

To explore the differences in sleep spindle (SS) characteristics during stage N2 sleep between children with childhood absence epilepsy and healthy controls, and between children with childhood absence epilepsy with or without cognitive impairment.

METHODS

We recruited 29 children (14 females, 15 males, mean age: 8 (2.5) years) with childhood absence epilepsy who did not undergone antiseizure treatments previously and 30 age-matched controls (14 females, 16 males, mean age: 9 (3.0) years). For all patients, data on medical history were collected. Each child was monitored overnight by long-term video electroencephalography and was evaluated by the Wechsler Intelligence Scale for Children-Fourth Edition. Next, we compared anterior SS characteristics, including density, frequency, cycle length, duration, amplitude, and percentage of sleep stages.

RESULTS

The childhood absence epilepsy group exhibited lower spindle density and duration in the first 37.5 min of stage N2 sleep than the control group (P < 0.01). A decrease in spindle density could be observed in the childhood absence epilepsy group with aggravated cognition impairment. The spindle density was substantially lower in the cognitively impaired group than in the cognitively unimpaired group (P < 0.01). No significant differences were observed in SS amplitude, SS frequency, SS cycle length, and the distribution of sleep stages.

CONCLUSIONS

Reduction in spindle density and duration is associated with the mechanisms underlying childhood absence epilepsy. The deficit in SS density is related with impaired cognition. This deficiency in SSs may be a useful predictive indicator of cognitive impairment in children with absence epilepsy, indicating that SSs may become a useful biomarker and potential adjuvant anti-seizure target for cognitive impairment caused by childhood absence epilepsy.

Two cases of childhood absence epilepsy who showed seizure disappearance after ethosuximide drug eruption

Background

Recent studies suggest potential roles of immune response in the pathophysiology of epilepsy. Anti-seizure medications (ASMs) are known to have side effects of drug eruption caused by immune responses. A few reports in adults have demonstrated disappearance of seizures after an ASM drug eruption episode. In this paper, we described 2 cases of childhood absence epilepsy (CAE) who showed seizure disappearance after ethosuximide (ESM) drug eruption, suggesting the possibility that the epilepsy disappears due to immune responses to ASM.

Case presentation

Case 1 was an 8-year-old girl diagnosed with CAE. She was treated with valproate acid (VPA) initially, and then ESM was administered as an additional treatment. Her epileptic seizure disappeared 4 days after initiation of ESM. However, drug eruption appeared 1 week after the administration of ESM. Even after discontinuation of ESM administration, she maintains no seizure after the drug eruption. Case 2 was a 5-year-old boy diagnosed as CAE. He was treated with VPA initially, and ESM was administered additionally. Drug eruption appeared 1 month after the administration of ESM. Even after ESM was terminated, he maintained seizure freedom after the appearance of eruption.

Conclusions

Epileptic seizures may have been suppressed due to the immune responses caused by ASM eruption. Further studies are needed to elucidate the pathophysiologic effects of drug eruption on epilepsy through immune responses.

Pareto optimality, economy-effectiveness trade-offs and ion channel degeneracy: improving population modelling for single neurons

Neurons encounter unavoidable evolutionary trade-offs between multiple tasks. They must consume as little energy as possible while effectively fulfilling their functions. Cells displaying the best performance for such multi-task trade-offs are said to be Pareto optimal, with their ion channel configurations underpinning their functionality. Ion channel degeneracy, however, implies that multiple ion channel configurations can lead to functionally similar behaviour. Therefore, instead of a single model, neuroscientists often use populations of models with distinct combinations of ionic conductances. This approach is called population (database or ensemble) modelling. It remains unclear, which ion channel parameters in the vast population of functional models are more likely to be found in the brain. Here we argue that Pareto optimality can serve as a guiding principle for addressing this issue by helping to identify the subpopulations of conductance-based models that perform best for the trade-off between economy and functionality. In this way, the high-dimensional parameter space of neuronal models might be reduced to geometrically simple low-dimensional manifolds, potentially explaining experimentally observed ion channel correlations. Conversely, Pareto inference might also help deduce neuronal functions from high-dimensional Patch-seq data. In summary, Pareto optimality is a promising framework for improving population modelling of neurons and their circuits.

Topological Organization Alterations of Whole-Brain Functional Networks in Patients with Childhood Absence Epilepsy: Associations with Treatment Effects

PURPOSE

The purpose of the current study is to detect changes of topological organization of whole-brain functional networks and their relationship with the clinical treatment effects of antiepileptic drugs (AEDs) for patients with childhood absence epilepsy (CAE) using resting-state functional MRI (RS-fMRI). Patients and Methods. RS-fMRI data from 30 CAE patients were collected and compared with findings from 30 age- and gender-matched healthy controls (HCs). The patients were treated with first-line AEDs for 46.03 months before undergoing a second RS-fMRI scan.

RESULTS

CAE children at baseline showed a reduced clustering coefficient (Cp) and local efficiency (El) than the HC group, implying the reduction of functional segregation. CAE children at baseline also showed smaller characteristic path length (Lp) and higher global efficiency (Eg) compared with the HC group, implying the impairment of functional segregation. However, those metrics showed no significant differences between CAE children at follow-up and the HC group which indicated a clear renormalization of topological organization after AED treatments. CAE at follow-up also showed significantly decreased connectivity between several network regions, with which the thalamus is mainly involved. Furthermore, the reduced connectivity change between the left superior parietal gyrus and the left thalamus is positively correlated with the symptom improvements after AED treatment.

CONCLUSION

We highlighted the convergence and divergence of brain functional network dysfunctions in CAE patients and provided crucial insights into pathophysiological mechanisms and the AED effects.

Altered spontaneous brain activity in patients with childhood absence epilepsy: associations with treatment effects

The study aims to detect resting-state functional MRI (RS-fMRI) changes and their relationships with the clinical treatment effects of anti-epileptic drugs (AEDs) for patients with childhood absence epilepsy (CAE) using the fractional amplitude of low-frequency fluctuation (fALFF). RS-fMRI data from 30 CAE patients were collected and compared with findings from 30 healthy controls (HCs) with matched sex and age. Patients were treated with first-line AEDs for 46.2 months before undergoing a second RS-fMRI scan. fALFF data were processed using DPABI and SPM12 software. Compared with the HCs, CAE patients at baseline showed increased fALFF in anterior cingulate cortex, inferior parietal lobule, inferior frontal lobule, supplementary motor area and reduced fALFF in putamen and thalamus. At follow-up, the fALFF showed a clear rebound which indicated a normalization of spontaneous brain activities in these regions. In addition, the fALFF changes within thalamus showed significant positive correlation with the seizure frequency improvements. Our results suggest that specific cortical and subcortical regions are involved in seizure generation and the neurological impairments found in CAE children and might shed new light about the AEDs effects on CAE patients.

Computational Evidence for a Competitive Thalamocortical Model of Spikes and Spindle Activity in Rolandic Epilepsy

Rolandic epilepsy (RE) is the most common idiopathic focal childhood epilepsy syndrome, characterized by sleep-activated epileptiform spikes and seizures and cognitive deficits in school age children. Recent evidence suggests that this disease may be caused by disruptions to the Rolandic thalamocortical circuit, resulting in both an abundance of epileptiform spikes and a paucity of sleep spindles in the Rolandic cortex during non-rapid eye movement sleep (NREM); electrographic features linked to seizures and cognitive symptoms, respectively. The neuronal mechanisms that support the competitive shared thalamocortical circuitry between pathological epileptiform spikes and physiological sleep spindles are not well-understood. In this study we introduce a computational thalamocortical model for the sleep-activated epileptiform spikes observed in RE. The cellular and neuronal circuits of this model incorporate recent experimental observations in RE, and replicate the electrophysiological features of RE. Using this model, we demonstrate that: (1) epileptiform spikes can be triggered and promoted by either a reduced NMDA current or h-type current; and (2) changes in inhibitory transmission in the thalamic reticular nucleus mediates an antagonistic dynamic between epileptiform spikes and spindles. This work provides the first computational model that both recapitulates electrophysiological features and provides a mechanistic explanation for the thalamocortical switch between the pathological and physiological electrophysiological rhythms observed during NREM sleep in this common epileptic encephalopathy.

The Transcription Factor Shox2 Shapes Neuron Firing Properties and Suppresses Seizures by Regulation of Key Ion Channels in Thalamocortical Neurons

Thalamocortical neurons (TCNs) play a critical role in the maintenance of thalamocortical oscillations, dysregulation of which can result in certain types of seizures. Precise control over firing rates of TCNs is foundational to these oscillations, yet the transcriptional mechanisms that constrain these firing rates remain elusive. We hypothesized that Shox2 is a transcriptional regulator of ion channels important for TCN function and that loss of Shox2 alters firing frequency and activity, ultimately perturbing thalamocortical oscillations into an epilepsy-prone state. In this study, we used RNA sequencing and quantitative PCR of control and Shox2 knockout mice to determine Shox2-affected genes and revealed a network of ion channel genes important for neuronal firing properties. Protein regulation was confirmed by Western blotting, and electrophysiological recordings showed that Shox2 KO impacted the firing properties of a subpopulation of TCNs. Computational modeling showed that disruption of these conductances in a manner similar to Shox2's effects modulated frequency of oscillations and could convert sleep spindles to near spike and wave activity, which are a hallmark for absence epilepsy. Finally, Shox2 KO mice were more susceptible to pilocarpine-induced seizures. Overall, these results reveal Shox2 as a transcription factor important for TCN function in adult mouse thalamus.

Estimating neuronal conductance model parameters using dynamic action potential clamp

BACKGROUND

Parameterization of neuronal membrane conductance models relies on data acquired from current clamp (CC) or voltage clamp (VC) recordings. Although the CC approach provides key information on a neuron's firing properties, it is often difficult to disentangle the influence of multiple conductances that contribute to the excitation properties of a real neuron. Isolation of a single conductance using pharmacological agents or heterologous expression simplifies analysis but requires extensive VC evaluation to explore the complete state behavior of the channel of interest.

NEW METHOD

We present an improved parameterization approach that uses data derived from dynamic action potential clamp (DAPC) recordings to extract conductance equation parameters. We demonstrate the utility of the approach by applying it to the standard Hodgkin-Huxley conductance model although other conductance models could be easily incorporated as well.

RESULTS

Using a fully simulated setup we show that, with as few as five action potentials previously recorded in DAPC mode, sodium conductance equation parameters can be determined with average parameter errors of less than 4% while action potential firing accuracy approaches 100%. In real DAPC experiments, we show that by "training" our model with five or fewer action potentials, subsequent firing lasting for several seconds could be predicted with ˜96% mean firing rate accuracy and 94% temporal overlap accuracy.

COMPARISON WITH EXISTING METHODS

Our DAPC-based approach surpasses the accuracy of VC-based approaches for extracting conductance equation parameters with a significantly reduced temporal overhead.

CONCLUSION

DAPC-based approach will facilitate the rapid and systematic characterization of neuronal channelopathies.

NetPyNE, a tool for data-driven multiscale modeling of brain circuits

Biophysical modeling of neuronal networks helps to integrate and interpret rapidly growing and disparate experimental datasets at multiple scales. The NetPyNE tool (www.netpyne.org) provides both programmatic and graphical interfaces to develop data-driven multiscale network models in NEURON. NetPyNE clearly separates model parameters from implementation code. Users provide specifications at a high level via a standardized declarative language, for example connectivity rules, to create millions of cell-to-cell connections. NetPyNE then enables users to generate the NEURON network, run efficiently parallelized simulations, optimize and explore network parameters through automated batch runs, and use built-in functions for visualization and analysis - connectivity matrices, voltage traces, spike raster plots, local field potentials, and information theoretic measures. NetPyNE also facilitates model sharing by exporting and importing standardized formats (NeuroML and SONATA). NetPyNE is already being used to teach computational neuroscience students and by modelers to investigate brain regions and phenomena.

The absence of NIPA2 enhances neural excitability through BK (big potassium) channels

AIM

To reveal the pathogenesis and find the precision treatment for the childhood absence epilepsy (CAE) patients with NIPA2 mutations.

METHODS

We performed whole-cell patch-clamp recordings to measure the electrophysiological properties of layer V neocortical somatosensory pyramidal neurons in wild-type (WT) and NIPA2-knockout mice.

RESULTS

We identified that layer V neocortical somatosensory pyramidal neurons isolated from the NIPA2-knockout mice displayed higher frequency of spontaneous and evoked action potential, broader half-width of evoked action potential, and smaller currents of BK channels than those from the WT mice. NS11021, a specific BK channel opener, reduced neuronal excitability in the NIPA2-knockout mice. Paxilline, a selective BK channel blocker, treated WT neurons and could simulate the situation of NIPA2-knockout group, thereby suggesting that the absence of NIPA2 enhanced the excitability of neocortical somatosensory pyramidal neurons by decreasing the currents of BK channels. Zonisamide, an anti-epilepsy drug, reduced action potential firing in NIPA2-knockout mice through increasing BK channel currents.

CONCLUSION

The results indicate that the absence of NIPA2 enhances neural excitability through BK channels. Zonisamide is probably a potential treatment for NIPA2 mutation-induced epilepsy, which may provide a basis for the development of new treatment strategies for epilepsy.