Temperature-dependent changes in neuronal dynamics in a patient with an SCN1A mutation and hyperthermia induced seizures

Abstract

Dravet syndrome is the prototype of SCN1A-mutation associated epilepsies. It is characterised by prolonged seizures, typically provoked by fever. We describe the evaluation of an SCN1A mutation in a child with early-onset temperature-sensitive seizures. The patient carries a heterozygous missense variant (c3818C > T; pAla1273Val) in the NaV1.1 brain sodium channel. We compared the functional effects of the variant vs. wild type NaV1.1 using patch clamp recordings from channels expressed in Chinese Hamster Ovary Cells at different temperatures (32, 37, and 40 °C). The variant channels produced a temperature-dependent destabilization of activation and fast inactivation. Implementing these empirical abnormalities in a computational model predicts a higher threshold for depolarization block in the variant, particularly at 40 °C, suggesting a failure to autoregulate at high-input states. These results reveal direct effects of abnormalities in NaV1.1 biophysical properties on neuronal dynamics. They illustrate the value of combining cellular measurements with computational models to integrate different observational scales (gene/channel to patient).

Figure 1. Schematic Sodium Channel Topology.

Schematic showing the membrane structure of mammalian voltage-gated sodium channels. The pore-forming regions of each domain are shown in blue while the positively charged S4 voltage-sensing segments are shown in yellow. The locations of the fast inactivation particle (h gate) and the A1273V mutant are also shown.

Figure 2. Macroscopic Na_V1.1 Currents.

Sample WT (a) and A1273V (b) currents elicited at potentials between −100 mV and +60 mV at 40 °C. Time to 50% maximal current is plotted versus voltage for WT and A1273V Na_V1.1 channels at 37 °C (c) and 40 °C (d). Source data for time to 50% maximal current can be found in Supplementary Table S2.

Figure 3. Voltage Dependence of NaV1.1 Conductance and Fast Inactivation.

Normalized Conductance curves for WT and A1273V Na_V1.1 channels at 37 °C (a) and 40 °C (b). Conductance was determined from macroscopic current recordings using Ohm’s law corrected for the experimentally observed equilibrium potential. Normalized current during a test pulse following a 200 ms pre-pulse is plotted versus pre-pulse potential for WT and A1273V Na_V1.1 channels at 37 °C (c) and 40 °C (d). Pulse protocols used to elicit macroscopic current and to determine the voltage-dependence of fast inactivation are shown in the insets of a and c, respectively. Source data for the voltage dependence of activation and fast inactivation can be found in Supplementary Table S3.

Figure 4. Time Course of Fast Inactivation.

Open-state fast inactivation time constants are plotted versus voltage for WT and A1273V Na_V1.1 at 37 °C (a) and 40 °C (b). The time course of fast inactivation recovery versus recovery is plotted for WT and A1273V Na_V1.1 at 37 °C (c) and 40 °C (d). The double-pulse protocol used to measure fast inactivation recovery is shown in the inset of a. Source data for fast inactivation time constants can be found in Supplementary Tables S4 and S5.

Figure 5. Computational Model Fits to Experimental Data.

Steady state values for different voltages were estimated for both the m and the h parameters based on values from cortical Hodgkin-Huxley-type neuronal simulations. A Boltzmann formulation of the steady state equation was then fitted to the estimates to derive baseline parameter values for the slopes (s_m and s_h) and half-peak voltages (V_2m, V_2h). Experimental results from voltage clamp experiments were then translated into changes from these baseline parameters to produce steady state curves for (a) the WT, and (b) the mutation gating parameters at different temperatures. Forward and reverse rates of the fast inactivation gate (α_h(V) and β_h(V)) were shifted along the voltage axis to correspond to the shifts in half-peak voltage of steady-state fast inactivation. The resultant recovery time courses for fast inactivation are shown for WT and the mutant at 37 °C (c) and 40 °C (d).

Figure 6. Computational Modelling of Membrane Dynamics.

Experimental voltage clamp measurements for four experimental conditions (WT and A1273V at 37 °C and 40 °C) were integrated into a Hodgkin-Huxley model of cortical neurons and normalised to the WT measurements at 37 °C. (a) Simulations of the membrane response at different input current levels revealed absent action potential generation in the WT at high currents, even when A1273V neurons continue to fire. (b) Bifurcation analysis shows differences in the transition from oscillation to fixed steady states at high input currents (i.e. depolarisation block), both qualitatively in terms of the bifurcation type, and quantitatively in terms of the input currents required to achieve depolarisation block. Of all experimental conditions modelled, A1273V neurons permit the highest input currents to elicit continuous action potentials. Model parameters: g_L = 2.5  *  10⁻⁵ S/cm², E_L = −70.3, g_Na = 0.056 S/cm², E_Na = 50–mV, g_K = 0.005 S/cm², E_K = −90 mV, V_t = −60 mV, C_m = 0.01 μF/mm² ; high input current I_stim = 45 μA/mm², low input current I_stim = 0.2 μA/mm². Remaining parameters were condition specific and defined as described in the Methods section.