Reduced GABAergic Neuron Excitability, Altered Synaptic Connectivity, and Seizures in a KCNT1 Gain-of-Function Mouse Model of Childhood Epilepsy

Shore, Amy N.; Colombo, Sophie; Tobin, William F.; Petri, Sabrina; Cullen, Erin R; Domínguez, Soledad; Bostick, Christopher D.; Beaumont, Michael; Williams, Damian J.; Khodagholy, Dion; Yang, Mu; Lutz, Cathleen; Peng, Yueqing; Gelinas, Jennifer N.; Goldstein, David B.; Boland, Michael J.; Frankel, Wayne N.; Weston, Matthew C.

doi:10.1016/j.celrep.2020.108303

Cited by 55 publications

(107 citation statements)

References 83 publications

(113 reference statements)

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“…This results in a strong increase of the excitation‐to‐inhibition ratio, thereby increasing excitability and synchrony at the network level. One preprint and one recent study seemed to validate the localization of slack in both glutamatergic and GABAergic neurons 47,48 . Predictions of our model seemed in phase with the report of Shore et al showing similar firing curves in the different subtypes of neurons, with a predominant impact on GABAergic neurons (Figure ) 47 …”

Section: Discussionsupporting

confidence: 80%

“…One preprint and one recent study seemed to validate the localization of slack in both glutamatergic and GABAergic neurons. 47,48 Predictions of our model seemed in phase with the report of Shore et al showing similar firing curves in the different subtypes of neurons, with a predominant impact on GABAergic neurons ( Figure S2). 47 In our study, we moved from a microscopic to a macroscopic model by adapting the wave-to-pulse functions of the different subpopulations according to frequency-intensity curves for each neuronal type.…”

Section: F I G U R Esupporting

confidence: 87%

“…47,48 Predictions of our model seemed in phase with the report of Shore et al showing similar firing curves in the different subtypes of neurons, with a predominant impact on GABAergic neurons ( Figure S2). 47 In our study, we moved from a microscopic to a macroscopic model by adapting the wave-to-pulse functions of the different subpopulations according to frequency-intensity curves for each neuronal type. This modification, in addition to the adaptation of parameters to simulate immature brain, allowed us to reproduce the interictal EEG pattern of patients with slack GOF.…”

Section: F I G U R Esupporting

confidence: 87%

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In silico model reveals the key role of GABA in KCNT1‐epilepsy in infancy with migrating focal seizures

et al. 2021

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Objective This study was undertaken to investigate how gain of function (GOF) of slack channel due to a KCNT1 pathogenic variant induces abnormal neuronal cortical network activity and generates specific electroencephalographic (EEG) patterns of epilepsy in infancy with migrating focal seizures. Methods We used detailed microscopic computational models of neurons to explore the impact of GOF of slack channel (explicitly coded) on each subtype of neurons and on a cortical micronetwork. Then, we adapted a thalamocortical macroscopic model considering results obtained in detailed models and immature properties related to epileptic brain in infancy. Finally, we compared simulated EEGs resulting from the macroscopic model with interictal and ictal patterns of affected individuals using our previously reported EEG markers. Results The pathogenic variants of KCNT1 strongly decreased the firing rate properties of γ‐aminobutyric acidergic (GABAergic) interneurons and, to a lesser extent, those of pyramidal cells. This change led to hyperexcitability with increased synchronization in a cortical micronetwork. At the macroscopic scale, introducing slack GOF effect resulted in epilepsy of infancy with migrating focal seizures (EIMFS) EEG interictal patterns. Increased excitation‐to‐inhibition ratio triggered seizure, but we had to add dynamic depolarizing GABA between somatostatin‐positive interneurons and pyramidal cells to obtain migrating seizure. The simulated migrating seizures were close to EIMFS seizures, with similar values regarding the delay between the different ictal activities (one of the specific EEG markers of migrating focal seizures due to KCNT1 pathogenic variants). Significance This study illustrates the interest of biomathematical models to explore pathophysiological mechanisms bridging the gap between the functional effect of gene pathogenic variants and specific EEG phenotype. Such models can be complementary to in vitro cellular and animal models. This multiscale approach provides an in silico framework that can be further used to identify candidate innovative therapies.

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Section: Discussionsupporting

confidence: 80%

Section: F I G U R Esupporting

confidence: 87%

Section: F I G U R Esupporting

confidence: 87%

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In silico model reveals the key role of GABA in KCNT1‐epilepsy in infancy with migrating focal seizures

et al. 2021

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“…However, isolated LOF or GOF effects on K v 1.2 both lead to epileptic encephalopathy as well. Recently, Shore et al (2020) provided data, showing how GOF variants can lead to epilepsy [ 55 ]. By expressing known epilepsy-causing KCNT1 -gain-of-function variants in excitatory and inhibitory neurons, they were able to demonstrate specific mutational effects affecting inhibitory neurons only, especially interneurons with fast-spiking activity, promoting network hyperexcitability and hypersynchronicity.…”

Section: Discussionmentioning

confidence: 99%

Refining Genotypes and Phenotypes in KCNA2-Related Neurological Disorders

Döring

Schröter

Jüngling

et al. 2021

IJMS

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Pathogenic variants in KCNA2, encoding for the voltage-gated potassium channel Kv1.2, have been identified as the cause for an evolving spectrum of neurological disorders. Affected individuals show early-onset developmental and epileptic encephalopathy, intellectual disability, and movement disorders resulting from cerebellar dysfunction. In addition, individuals with a milder course of epilepsy, complicated hereditary spastic paraplegia, and episodic ataxia have been reported. By analyzing phenotypic, functional, and genetic data from published reports and novel cases, we refine and further delineate phenotypic as well as functional subgroups of KCNA2-associated disorders. Carriers of variants, leading to complex and mixed channel dysfunction that are associated with a gain- and loss-of-potassium conductance, more often show early developmental abnormalities and an earlier onset of epilepsy compared to individuals with variants resulting in loss- or gain-of-function. We describe seven additional individuals harboring three known and the novel KCNA2 variants p.(Pro407Ala) and p.(Tyr417Cys). The location of variants reported here highlights the importance of the proline(405)–valine(406)–proline(407) (PVP) motif in transmembrane domain S6 as a mutational hotspot. A novel case of self-limited infantile seizures suggests a continuous clinical spectrum of KCNA2-related disorders. Our study provides further insights into the clinical spectrum, genotype–phenotype correlation, variability, and predicted functional impact of KCNA2 variants.

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“…The manuscript by Shore et al is an excellent example of the necessity of modeling human mutations in preclinical models, demonstrating the ability to recapitulate the human condition and elucidate the complex mechanisms contributing to the phenotype. 1 The study underscores the fact that it is difficult to predict the consequences of a known human mutation without assessing the impact in an intact network, which may not produce the anticipated results via the presumed mechanism when examined in vivo. Thus, this study highlights the utility of animal models for studying human diseases, including epilepsy—a topic which was controversially debated at the 73rd Annual American Epilepsy Society meeting held in 2019 2 ( https://www.pathlms.com/aes/courses/17742 ).…”

Section: Commentarymentioning

confidence: 98%