Page 104 - Read Online

Mohammadi et al. J Transl Genet Genom 2020;4:238-50 I https://doi.org/10.20517/jtgg.2020.29 Page 241

been used to study the electrophysiological consequences of genetic variants but also to investigate their
pharmacological characteristics [13,25] . Xenopus oocyte models have, for instance, been used to study the effect
[13]
of the potassium channel blocker quinidine on GoF of KCNT1 channels , and neuroblastoma ND7/23 cells
[25]
have been used to study the effect of the sodium channel blocker phenytoin on GoF of SCN8A channels .
Both studies have successfully shown that the investigated drugs could reverse the variant specific GoF,
which indicates that these conditions may respond to the targeted therapies. Although these cellular
expression systems are extremely valuable, a clear drawback is that they only allow theoretical predictions as
[26]
to how neuronal behavior might be changed by the variants . It is therefore crucial to test the dysfunctional
proteins in a human neuronal specific context, which can mimic human physiological conditions to a better
extent.

hiPSC models in epilepsy disorders
Patient hiPSCs have successfully been used to model several different monogenic epilepsies including
[28]
[29]
[27]
epilepsy in infancy with migrating focal seizures , tuberous sclerosis , PCDH19 girls clustering epilepsy ,
Dravet syndrome [30,31] and Angelman syndrome [32,33] . On the one hand, these studies have provided novel
mechanistic insights and served as proof of principle platforms for using hiPSCs to study epilepsy, but on the
other hand, they have also highlighted the potential limitations. In the following, we will discuss the hiPSC
models of Dravet syndrome as an example.

Dravet syndrome
Dravet syndrome is a severe developmental and epileptic encephalopathy (DEE) caused by LoF variants in
SCN1A, encoding the voltage-gated sodium channel Nav1.1. The syndrome is characterized by prolonged
fever-induced hemi-clonic or generalized tonic-clonic seizures (GTCS) with onset at around 6 months of
age [7,34] . Over time, the patients also develop afebrile seizures including GTCS, atypical absences, and focal
and myoclonic seizures. Development is often normal at onset; however, during the course of the disease,
most patients develop moderate-to-severe intellectual disability, behavioral problems, sleep disturbances, and
both gross and fine motor impairment [7,34] . To understand the physiopathology of Dravet syndrome, hiPSC
models were generated [30,31] . In one of these studies, patient-derived neurons could not respond adequately
to high-intensity stimulation, which suggested an impairment in the function of GABAergic neurons and
[30]
would explain the epileptogenesis in the syndrome . In another study neurons derived from patient hiPSCs
displayed increased sodium currents in both bipolar- and pyramidal-shaped neurons, accompanied by
[31]
spontaneous bursting and other evidence of hyperexcitability . In addition, in hiPSC-derived neurons, the
expression of tyrosine hydroxylase mRNA and subsequent protein abundance was increased, which might
[35]
indicate that pathogenic variants in SCN1A could change the dopamine system and responses .

Measuring electrophysiological properties of neurons and cellular networks
The electrophysiological properties of differentiated neurons can be measured to clarify the impact of the
genetic variant on the function of the protein/channel and the properties of the neural network in a disease
and species-specific context using different systems. Furthermore, these systems can be used in drug
screening to assess which drug(s) can reverse the electrophysiological imbalance of a differentiated neuron
with a given pathogenic variant.

Voltage clamping allows monitoring of minute changes in the electric currents across membranes. 2D
cellular models of excitatory/glutamatergic and inhibitory/GABAergic neurons are ideal for functional
readouts. Two techniques commonly used to assess the electrophysiological properties of model systems are
(1) single-cell patch-clamp electrophysiological recordings; and (2) multielectrode array (MEA) which is
described below. The main difference between these techniques is that the former method measures synaptic
activity of single neurons, while MEA measures electrophysological activity of neuronal networks. MEA uses
several microelectrodes embedded in the surface of neuron cultures and allows the targeting of several sites