Abstract
Background: The Nav 1.8 sodium channel has a key role in generating repetitive action potentials in nociceptive human dorsal root ganglion neurons. Nav 1.8 is differentiated from other voltage-gated sodium channels by its unusually slow inactivation kinetics and depolarised voltage-dependence of activation. These features are particularly pronounced in the human Nav 1.8 channel and allow the channel to remain active during repolarisation. Gain-of-function mutations in Nav 1.8 have been linked to neuropathic pain and selective blockers of Nav 1.8 have been developed as potential new analgesics. However, it is not well understood how modulating the Nav 1.8 conductance alters neuronal excitability and how this depends on the balance of other ion channels expressed by nociceptive neurons. Methods: To investigate this, we developed a novel computational model of the human dorsal root ganglion neuron and used it to construct a population of models that mimicked inter-neuronal heterogeneity in ionic conductances and action potential morphology Results: By simulating changes to the Nav 1.8 conductance in the population of models, we found that moderately increasing the Nav 1.8 conductance led to increased firing rate, as expected, but increasing Nav 1.8 conductance beyond an inflection point caused firing rate to decrease. We found that the delayed rectifier and M-type potassium conductances were also critical for determining neuronal excitability. In particular, altering the delayed rectifier potassium conductance shifted the position of the Nav 1.8 inflection point and therefore the relationship between Nav 1.8 conductance and firing rate. Conclusions: Our results suggest that the effects of modulating Nav 1.8 in a nociceptive neuron can depend significantly on other conductances, particularly potassium conductances.
Highlights
The sodium channel Nav 1.8 is selectively expressed in small diameter dorsal root ganglion (DRG) neurons and has an important and unique role in pain signalling, due to its slow and depolarised kinetics of inactivation [Akopian et al, 1996; Sangameswaran et al, 1996] and fast recovery from inactivation [Dib-Hajj et al, 1997] compared with other voltagegated sodium channels
All models in the population had substantially different combinations of conductances, but all of them produced action potential (AP) biomarkers at rheobase that were within 1.5 standard deviations of the mean values of each parameter, based on data recorded from ex vivo human DRG (hDRG) neurons [Davidson et al, 2014]
Voltages traces from the population of models (Figure 1A) show they reproduce key characteristics of the hDRG neuron AP, including its characteristic broad shoulder [Davidson et al 2014, Han et al, 2015], the slow rise to threshold followed by a rapid upstroke, and the presence of an after-hyperpolarization following repolarization
Summary
The sodium channel Nav 1.8 is selectively expressed in small diameter dorsal root ganglion (DRG) neurons and has an important and unique role in pain signalling, due to its slow and depolarised kinetics of inactivation [Akopian et al, 1996; Sangameswaran et al, 1996] and fast recovery from inactivation [Dib-Hajj et al, 1997] compared with other voltagegated sodium channels. Understanding how variation in multiple ionic currents will interact with each other, not just on a qualitative level (whether a channel is expressed or not) but on a quantitative level (the level of expression of each channel), is challenging This is an important consideration though, as ion channel densities have been shown to have high inter-neuronal variability [Schulz et al, 2006]. Gain-of-function mutations in Nav 1.8 have been linked to neuropathic pain and selective blockers of Nav 1.8 have been developed as potential new analgesics It is not well understood how modulating the Nav 1.8 conductance alters neuronal excitability and how this depends on the balance of other ion channels expressed by nociceptive neurons. Conclusions: Our results suggest that the effects of modulating Nav 1.8 in a nociceptive neuron can depend significantly on other conductances, potassium conductances
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