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References for manuscript.tex
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## g_table.tex
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Latex file for table of conductance values in models
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## gating_table.tex
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Latex file for table of gating values fit
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## eNeuro_title_page.docx
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Required word title page file
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manuscript.pdf
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% pandoc export with references: pandoc manuscript.tex --citeproc --bibliography=ref.bib -o manuscript.docx
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\documentclass[11pt]{article}
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\usepackage[utf8]{inputenc}
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@ -106,33 +107,33 @@ Using a diverse collection of neuronal models, the effects of changes in ion cur
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Ion channels determine neuronal excitability and mutations that alter ion channel properties result in neurological disorders called channelopathies. Although the genetic nature of such mutations as well as their effects on the ion channel's biophysical properties are routinely assessed experimentally, determination of the role in altering neuronal firing is more difficult. Computational modelling bridges this gap and demonstrates that the cell type in which a mutation occurs is an important determinant in the effects of firing. As a result, classification of ion channel mutations as loss or gain of function is useful to describe the ionic current but care should be taken when applying this classification on the level of neuronal firing.
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\par\null
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\section*{Introduction (750 Words Maximum - Currently 673)}
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\section*{Introduction (750 Words Maximum - Currently \textcolor{red}{837})}
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%\textit{The Introduction should briefly indicate the objectives of the study and provide enough background information to clarify why the study was undertaken and what hypotheses were tested.}
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Neuronal ion channels are vital in determining neuronal excitability, action potential generation and firing patterns \citep{bernard_channelopathies_2008, carbone_ion_2020}. In particular, the properties and combinations of ion channels and their resulting currents determine the firing properties of the neuron \citep{rutecki_neuronal_1992, pospischil_minimal_2008}. However, ion channel function can be disturbed, resulting in altered ionic current properties and altered neuronal firing behaviour \citep{carbone_ion_2020}. Ion channel mutations are a common cause of such channelopathies and are often associated with hereditary clinical disorders \citep{bernard_channelopathies_2008, carbone_ion_2020}.
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\textcolor{red}{what effect does the mutation have on firing behaviour? - first motivation, about where this should lead}
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Neuronal ion channels are vital in determining neuronal excitability, action potential generation and firing patterns \citep{bernard_channelopathies_2008, carbone_ion_2020}. In particular, the properties and combinations of ion channels and their resulting currents determine the firing properties of the neuron \citep{rutecki_neuronal_1992, pospischil_minimal_2008}. However, ion channel function can be disturbed resulting in altered ionic current properties and altered neuronal firing behaviour \citep{carbone_ion_2020}. Ion channel mutations are a common cause of such channelopathies and are often associated with hereditary clinical disorders \citep{bernard_channelopathies_2008, carbone_ion_2020}. The effects of these mutations are frequently presumed \cite{Balestrini1044} or determined at a biophysical level, however assessment of the impact of these mutations on neuronal firing and excitability is more difficult.
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The effects of these mutations are frequently determined at a biophysical level in heterologous expression systems that contain no endogenous ionic currents. \textcolor{red}{(why?)} These experiments can determine how the voltage dependent kinetics have changed, but only allow for rough predictions about how the firing rate of a neuron is affected.
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Experimentally, these mutations are frequently determined at a biophysical level in heterologous expression systems that contain no endogenous ionic currents. These experiments can determine how the voltage dependent kinetics have changed, but only allow for rough predictions about how the firing rate of a neuron is affected.
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Transfection of primary neuron cultures can overcome some of these limitations and changes in firing behaviour can more readily be assessed \cite{Scalmani2006, Liu2019}. However, the relative expression and conductance of the transfected ion channel in relation to endogenous currents can be variable. As the firing behaviour and dynamics of neuronal models can be dramatically altered by altering relative current amplitudes \citep{rutecki_neuronal_1992, pospischil_minimal_2008,Kispersky2012, golowasch_failure_2002, barreiro_-current_2012}, primary neuronal do probably not provide definitive insight into the effects of a channelopathy on \textit{in vivo} firing.
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Transfection of primary neuron cultures can overcome these limitations and changes in firing behaviour can more readily be assessed \cite{Scalmani2006, Liu2019}. However, the relative expression and conductance of the transfected ion channel in relation to endogenous currents can be variable. As the firing behaviour and dynamics of neuronal models can be dramatically altered by altering relative current amplitudes \citep{rutecki_neuronal_1992, pospischil_minimal_2008,Kispersky2012, golowasch_failure_2002, barreiro_-current_2012}, primary neuronal cultures do probably not provide definitive insight into the effects of a channelopathy on \textit{in vivo} firing.
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One of the most realistic methods, but also the most time extensive and expensive, is the generation of a mouse line with the prefered mutation.
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%One of the most realistic methods, but also the most time extensive and expensive, is the generation of a mouse line with the prefered mutation.
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%The effects of these mutations are frequently determined at a biophysical level, however assessment of the impact of mutations on neuronal firing and excitability is more difficult. Experimentally, transfection of cell cultures or the generation of mutant mice lines are common approaches. Cell culture transfection does not replicate the exact interplay of endogenous currents nor does it take into account the complexity of the nervous system including factors such as expression patterns, intracellular regulation and modulation of ion channels as well as network effects. Transfected currents are characterized in isolation and the role of these isolated currents in the context of other currents in a neuron cannot be definitively inferred. The effects of individual currents \textit{in vivo} also depend on the neuron type they are expressed in and which roles these neurons have in specific circuits. Complex interactions between different cell types \textit{in vivo} are neglected in transfected cell culture. Additionally, transfected currents are not present with the neuron-type specific cellular machinery present \textit{in vivo} and are even transfected in cells of different species. Furthermore, culture conditions can shape ion channel expression \citep{ponce_expression_2018}.
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%Ion channel transfection of primary neuronal cultures can overcome some of the limitations of cell culture expression. In transfected neuronal cell cultures firing can more readily be assessed as endogenous currents are present, however the expressed and endogenous versions of the same ion channel are present in the cell \cite{Scalmani2006, Smith2018}. To avoid the confound of both expressed and endogenous current contributing to firing, a drug resistance can be introduced into the ion channel that is transfected and the drug is used to silence the endogenous version of this current \cite{Liu2019}. Although addition of TTX-resistance to \(\textrm{Na}_{\textrm{V}}\) does not alter the gating properties of these channels \cite{Leffler2005}, the relative expression and conductance of the transfected ion channel in relation to endogenous currents can be variable and non-specific blocking of ion channels not affected by the channelopathy may occur. As the firing behaviour and dynamics of neuronal models can be dramatically altered by altering relative current amplitudes \citep{rutecki_neuronal_1992, pospischil_minimal_2008,Kispersky2012, golowasch_failure_2002, barreiro_-current_2012}, primary neuronal cultures provide a useful general indication as to the effects of ion channel mutations but do not provide definitive insight into the effects of a channelopathy on \textit{in vivo} firing.
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%Neuronal ion channels are vital in determining neuronal excitability, action potential generation and firing patterns \citep{bernard_channelopathies_2008, carbone_ion_2020}. In particular, the properties and combinations of ion channels and their resulting currents determine the firing properties of the neuron \citep{rutecki_neuronal_1992, pospischil_minimal_2008}. However, ion channel function can be disturbed resulting in altered ionic current properties and altered neuronal firing behaviour \citep{carbone_ion_2020}. Ion channel mutations are a common cause of such channelopathies and are often associated with hereditary clinical disorders \citep{bernard_channelopathies_2008, carbone_ion_2020}. The effects of these mutations are frequently presumed \cite{Balestrini1044} or determined at a biophysical level, however assessment of the impact of mutations on neuronal firing and excitability is more difficult. Experimentally, cell culture transfection does not replicate the exact interplay of endogenous currents nor does it take into account the complexity of the nervous system including factors such as expression patterns, intracellular regulation and modulation of ion channels as well as network effects \cite{Balestrini1044, Noebels2017}. Transfected currents are characterized in isolation and the role of these isolated currents in the context of other currents in a neuron cannot be definitively inferred \cite{Dunlop2008, Noebels2017}. Additionally, transfected currents are not expressed in the presence of physiologically present auxillary proteins and are even transfected in cells of different species. Furthermore, culture conditions can shape ion channel expression \citep{ponce_expression_2018}.
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% Complex interactions between different cell types and circuit level effects \textit{in vivo} are neglected in transfected cell culture.
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%Ion channel transfection of primary neuronal cultures can overcome some of the limitations of cell culture expression. In transfected neuronal cell cultures firing can more readily be assessed as endogenous currents are present, however the expressed and endogenous versions of the same ion channel are present in the cell \cite{Scalmani2006, Smith2018}. To avoid the confound of both expressed and endogenous current contributing to firing, a drug resistance can be introduced to the transfected ion channel and the endogenous version of this current can be pharmacologically silenced \cite{Liu2019}. Although addition of TTX-resistance to \(\textrm{Na}_{\textrm{V}}\) does not alter the gating properties of these channels \cite{Leffler2005}, the relative expression of the transfected ion channel in relation to endogenous currents can be variable and non-specific blocking of ion channels not affected by the channelopathy may occur. As the firing behaviour and dynamics of neuronal models can be dramatically altered by altering relative current amplitudes \citep{rutecki_neuronal_1992, pospischil_minimal_2008,Kispersky2012, golowasch_failure_2002, barreiro_-current_2012, Noebels2017}, primary neuronal cultures provide a useful general indication as to the effects of ion channel mutations but do not provide definitive insight into the effects of a channelopathy on \textit{in vivo} firing.
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The generation of mice lines is costly and behavioural characterization of new mice lines is required to assess similarities to patient symptoms. Although the generation of mouse lines is desirable for a clinical disorder characterized by a specific ion channel mutation, this approach becomes impractical for disorders associated with a collection of distinct mutations in a single ion channel. Because of the lack of adequate experimental approaches, a great need is present for the ability to assess the impacts of ion channel mutations on neuronal firing. A more general understanding of the effects of changes in current properties on neuronal firing may help to understand the impacts of ion channel mutations. Specifically, modelling approaches can be used to assess the impacts of current property changes on firing behaviour, bridging the gap between changes in the biophysical properties induced by mutations and clinical symptoms. Conductance-based neuronal models enable insight into the effects of ion channel mutations with specific effects of the resulting ionic current as well as enabling \textit{in silico} assessment of the relative effects of changes in biophysical properties of ionic currents on neuronal firing . The effects of altered voltage-gated potassium channel \Kv function is of particular interest in this study as it gives rise to the \IKv current and is associated with episodic ataxia type 1. Furthermore, modelling approaches enable predictions of the effects of specific mutation and drug induced biophysical property changes.
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The generation of mice lines is costly and behavioural characterization of new mice lines is required to assess similarities to patient symptoms. Although the generation of mouse lines is desirable for a clinical disorder characterized by a specific ion channel mutation, this approach becomes impractical for
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personalized treatment for large numbers of distinct mutations. General understanding of the effects of changes in current properties on neuronal firing may help to fill the need to understand the impacts of ion channel mutations on neuronal firing. Specifically, modelling approaches can be used to assess the impacts of current property changes on firing behaviour, bridging the gap between changes in the biophysical properties induced by mutations and clinical symptoms. Conductance-based neuronal models enable insight into the effects of ion channel mutations with specific effects of the resulting ionic current as well as enabling \textit{in silico} assessment of the relative effects of changes in biophysical properties of ionic currents on neuronal firing. The effects of altered voltage-gated potassium channel \Kv function is of particular interest in this study as it gives rise to the \IKv current and is associated with episodic ataxia type 1. Furthermore, modelling approaches enable predictions of the effects of specific mutation and drug induced biophysical property changes.
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\Kv channels, encoded by the KCNA1 gene, play a role in repolarizing the action potential, neuronal firing patterns, neurotransmitter release, and saltatory conduction \citep{dadamo_episodic_1998} and are expressed throughout the CNS \citep{tsaur_differential_1992, wang_localization_1994, veh_immunohistochemical_1995}.
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Altered \Kv channel function as a result of KCNA1 mutations in humans is associated with episodic ataxia type 1 (EA1) which is characterized by period attacks of ataxia and persistent myokymia \citep{parker_periodic_1946, van_dyke_hereditary_1975}.
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Onset of EA1 is before 20 years of age \citep{brunt_familial_1990,rajakulendran_episodic_2007,van_dyke_hereditary_1975, jen_primary_2007} and is associated with a 10 times higher prevalence of epileptic seizures\citep{zuberi_novel_1999}. EA1 significantly impacts patient quality of life \citep{graves_episodic_2014}.
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\Kv null mice have spontaneous seizures without ataxia starting in the third postnatal week although impaired balance has been reported \citep{smart_deletion_1998, zhang_specific_1999} and neuronal hyperexcitability has been demonstrated in these mice \citep{smart_deletion_1998, brew_hyperexcitability_2003}. However, the lack of ataxia in \Kv null mice raises the question if the hyperexcitability seen is representative of the effects of EA1 associated \Kv mutations.
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Onset of EA1 is before 20 years of age \citep{brunt_familial_1990,rajakulendran_episodic_2007,van_dyke_hereditary_1975, jen_primary_2007}, is associated with a 10 times higher prevalence of epileptic seizures\citep{zuberi_novel_1999} and significantly impacts patient quality of life \citep{graves_episodic_2014}.
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%\Kv null mice have spontaneous seizures without ataxia starting in the third postnatal week although impaired balance has been reported \citep{smart_deletion_1998, zhang_specific_1999} and neuronal hyperexcitability has been demonstrated in these mice \citep{smart_deletion_1998, brew_hyperexcitability_2003}. However, the lack of ataxia in \Kv null mice raises the question if the hyperexcitability seen is representative of the effects of EA1 associated \Kv mutations.
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Using a diverse set of conductance-based neuronal models we examine the role of current environment on the impact of alterations in channels properties on firing behavior generally and for EA1 associated \Kv mutations.
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Using a diverse set of conductance-based neuronal models we examine the role of current environment on the impact of alterations in channels properties on firing behavior generally and for EA1 associated \Kv mutations.
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\par\null
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@ -213,7 +214,7 @@ Changes in firing as characterized by \(\Delta\)AUC and \(\Delta\)rheobase occup
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\end{figure}
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Neuronal firing is a complex phenomenon and classification of firing is needed for comparability across cell types. Here we focus on the classification of two aspects of firing: rheobase (smallest injected current at which the cell fires an action potential) and the initial shape of the frequency-current (fI) curve. The quantification of the inital shape of the fI curve using by computing the area under the curve (AUC) is a measure of the initial firing at currents above rheobase (\Cref{fig:firing_characterizaton}A). The characterization of firing with AUC and rheobase enables determination of general increases or decreases in firing based on current-firing relationships, with the upper left quadrant (+\(\Delta\)AUC and -\(\Delta\)rheobase) indicate an increase in firing, whereas the bottom right quadrant (-\(\Delta\)AUC and +\(\Delta\)rheobase) is indicative of decreased firing (\Cref{fig:firing_characterizaton}B). In the lower left and upper right quadrants, the effects on firing are more nuance and cannot easily be described as a gain or loss of excitability.
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Neuronal firing is a complex phenomenon and classification of firing is required for comparisons of firing across cell types and between conditions. Here we focus on the classification of two aspects of firing: rheobase (smallest injected current at which the cell fires an action potential) and the initial shape of the frequency-current (fI) curve. The quantification of the inital shape of the fI curve using by computing the area under the curve (AUC) is a measure of the initial firing at currents above rheobase (\Cref{fig:firing_characterizaton}A). The characterization of firing with AUC and rheobase enables determination of general increases or decreases in firing based on current-firing relationships, with the upper left quadrant (+\(\Delta\)AUC and -\(\Delta\)rheobase) indicate an increase in firing, whereas the bottom right quadrant (-\(\Delta\)AUC and +\(\Delta\)rheobase) is indicative of decreased firing (\Cref{fig:firing_characterizaton}B). In the lower left and upper right quadrants, the effects on firing are more nuance and cannot easily be described as a gain or loss of excitability.
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\begin{figure}[ht!]
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\centering
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@ -224,10 +225,10 @@ Neuronal firing is a complex phenomenon and classification of firing is needed f
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\end{figure}
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Considerable diversity is present in the set of neuronal models used as evident in the variability seen across neuronal models both in representative spike trains and their fI curves (\Cref{fig:diversity_in_firing}). The models chosen all fire repetitively and do not exhibit bursting. Some models, such as Cb stellate and RS inhibitory models, display type I firing whereas others such as Cb stellate \(\Delta\)\Kvnospace and STN models have type II firing. Type I firing is characterized by continuous fI curve (i.e. firing rate is continuous) generated through a saddle-node on invariant cycle bifurcation and type II firing is characterized by a discontinuity in the fI curve (i.e. a jump occurs from no firing to firing at a certain frequency) due to a Hopf bifurcation \cite{ERMENTROUT2002, ermentrout_type_1996}. Other models lie on a continuum between these prototypical firing classifications. Most neuronal models exhibit hysteresis with ascending and descending ramps eliciting spikes with different thresholds, however STN +\Kv, STN \(\Delta\)\Kv, Cb stellate \(\Delta\)\Kv have large hysteresis (\Cref{fig:diversity_in_firing}).
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Neuronal firing is heterogenous across the CNS and a set of neuronal models with heterogenous firing due to different ion currents is desirable to reflect this heterogeneity. The set of neuronal models used here has considerable diversity as evident in the variability seen across neuronal models both in representative spike trains and their fI curves (\Cref{fig:diversity_in_firing}). The models chosen all fire repetitively and do not exhibit bursting. Some models, such as Cb stellate and RS inhibitory models, display type I firing whereas others such as Cb stellate \(\Delta\)\Kvnospace and STN models have type II firing. Type I firing is characterized by continuous fI curve (i.e. firing rate is continuous) generated through a saddle-node on invariant cycle bifurcation and type II firing is characterized by a discontinuity in the fI curve (i.e. a jump occurs from no firing to firing at a certain frequency) due to a Hopf bifurcation \cite{ERMENTROUT2002, ermentrout_type_1996}. Other models lie on a continuum between these prototypical firing classifications. Most neuronal models exhibit hysteresis with ascending and descending ramps eliciting spikes with different thresholds, however STN +\Kv, STN \(\Delta\)\Kv, Cb stellate \(\Delta\)\Kv have large hysteresis (\Cref{fig:diversity_in_firing}).
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\subsection*{Sensitivity analysis}
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A one-factor-a-time sensitivity analysis enables the comparison of a given alteration in current parameters across models. Changes in gating \(V_{1/2}\) and slope factor k as well as the current conductance affect AUC (\Cref{fig:AUC_correlation} A, B and C). Heterogeneity in the correlation between gating and conductance changes and AUC occurs across models for most currents. In these cases some of the models display non-monotonic relationships \\(i.e. \( |\)Kendall \(\tau | \neq\) 1). However, shifts in A current activation \(V_{1/2}\), changes in \Kv activation \(V_{1/2}\) and slope, and changes in A current conductance display consistent monotonic relationships across models.
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Sensitivity analyses are used to understand how input model parameters contribute to the output of a model \citep{Saltelli2002}. In other words, sensitivity analyses are used to understand how sensitive the output of a model is to a change in input or model parameters. One-factor-a-time sensitivity analysis involve altering one parameter at a time and enable the comparison of a given alteration in current parameters across models. Changes in gating \(V_{1/2}\) and slope factor k as well as the current conductance affect AUC (\Cref{fig:AUC_correlation} A, B and C). Heterogeneity in the correlation between gating and conductance changes and AUC occurs across models for most currents. In these cases some of the models display non-monotonic relationships (i.e. \( |\)Kendall \(\tau | \neq\) ). However, shifts in A current activation \(V_{1/2}\), changes in \Kv activation \(V_{1/2}\) and slope, and changes in A current conductance display consistent monotonic relationships across models.
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\begin{figure}[ht!]
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@ -238,9 +239,6 @@ A one-factor-a-time sensitivity analysis enables the comparison of a given alter
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\label{fig:AUC_correlation}
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\end{figure}
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Alterations in gating \(V_{1/2}\) and slope factor k as well as the current conductance also play a role in determining rheobase (\Cref{fig:rheobase_correlation} A, B and C). Shifts in half activation of gating properties are similarly correlated with rheobase across models, however Kendall \(\tau\) values departing from -1 indicate non-monotonic relationships between K current \(V_{1/2}\) and rheobase in some models (\Cref{fig:rheobase_correlation}A). Changes in Na current inactivation, \Kv current inactivation and A current activation have affect rheobase with positive and negative correlations in different models (\Cref{fig:rheobase_correlation}B). Departures from monotonic relationships occur in some models as a result of K current activation, \Kv current inactivation and A current activation in some models. Current conductance magnitude alterations affect rheobase similarly across models (\Cref{fig:rheobase_correlation}C).
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\begin{figure}[ht!]
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@ -252,7 +250,7 @@ Alterations in gating \(V_{1/2}\) and slope factor k as well as the current cond
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\end{figure}
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\subsection*{\Kv}
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The changes in AUC and rheobase from wild-type values for reported episodic ataxia type 1 (EA1) associated \Kv mutations are heterogenous across models containing \Kv, but generally show decreases in rheobase (\Cref{fig:simulation_model_comparision}A-I). Pairwise non-parametric Kendall \(\tau\) rank correlations between the simulated effects of these \Kv mutations on rheobase are highly correlated across models (\Cref{fig:simulation_model_comparision}J). However, the effects of the \Kv mutations on AUC are more heterogenous as reflected by both weak and strong positive and negative pairwise correlations between models (\Cref{fig:simulation_model_comparision}K).
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Mutations in \Kv are associated with episodic ataxia type 1 (EA1) have been characterized biophysically and are used here as a case study in the effects of current environment on the outcomes of channelopathies on firing. The changes in AUC and rheobase from wild-type values for reported EA1 associated \Kv mutations are heterogenous across models containing \Kv, but generally show decreases in rheobase (\Cref{fig:simulation_model_comparision}A-I). Pairwise non-parametric Kendall \(\tau\) rank correlations between the simulated effects of these \Kv mutations on rheobase are highly correlated across models (\Cref{fig:simulation_model_comparision}J). However, the effects of the \Kv mutations on AUC are more heterogenous as reflected by both weak and strong positive and negative pairwise correlations between models (\Cref{fig:simulation_model_comparision}K).
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\begin{figure}[ht!]
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\centering
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\includegraphics[width=\linewidth]{Figures/simulation_model_comparison.pdf}
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@ -262,7 +260,7 @@ The changes in AUC and rheobase from wild-type values for reported episodic atax
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\end{figure}
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\section*{Discussion (3000 Words Maximum - Currently 1780)}
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\section*{Discussion (3000 Words Maximum - Currently 2010)}
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% \textit{The discussion section should include a brief statement of the principal findings, a discussion of the validity of the observations, a discussion of the findings in light of other published work dealing with the same or closely related subjects, and a statement of the possible significance of the work. Extensive discussion of the literature is discouraged.}\\
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Using a set of diverse conductance-based neuronal models, the effects of changes to current properties and conductances on firing were determined to be heterogenous for the AUC of the steady state fI curve but more homogenous for rheobase. For a known channelopathy, episodic ataxia type 1 associated \Kv mutations, the effects on rheobase is consistent across cell types, whereas the effect on AUC is cell type dependent.
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@ -289,7 +287,7 @@ Moderate changes in delayed rectifier potassium currents change the bifurcation
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Different current properties, such as the difference in \(\textrm{I}_\textrm{A}\) and \IKv in the Cb stellate and STN model families alter the impact of KCNA1 mutations on firing highlighting that knowledge of the biophysical properties of a current and its neuronal expression is vital for holistic understanding of the effects of a given ion channel mutation both at a single cell and network level.
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\subsection*{Loss or Gain of Function Characterizations Do Not Fully Capture Ion Channel Mutation Effects on Firing}
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The effects of changes in current properties depend in part on the neuronal model in which they occur and can be seen in the variance of correlations (especially in AUC) across models for a given current property change. Therefore, relative conductances and gating properties of currents in the current environment in which an alteration in current properties occurs plays an important role in determining the outcome on firing. The use of loss of function (LOF) and gain of function (GOF) is useful at the level of ion channels and whether a mutation results in more or less ionic current, however the extension of this thinking onto whether mutations induce LOF or GOF at the level of neuronal firing based on the ionic current LOF/GOF is problematic due to the dependency of neuronal firing changes on the current environment. Thus the direct leap from current level LOF/GOF characterizations to effects on firing without experimental or modelling-based evidence, although tempting, should be refrained from and viewed with caution when reported. This is especially relevant in the recent development of personalized medicine for channelopathies, where a patients specific channelopathy is identified and used to tailor treatments \citep{Weber2017, Ackerman2013, Helbig2020, Gnecchi2021}. However, the effects of specific ion channel mutations are often characterized in expression systems and classified as LOF or GOF to aid in treatment decisions \citep{johannesen_genotype-phenotype_2021, Brunklaus2022, Musto2020}. Interestingly, both LOF and GOF \(\textrm{Na}_{\textrm{V}}\textrm{1.1}\) mutations can benefit from treatment with sodium channel blockers \citep{johannesen_genotype-phenotype_2021}, suggesting that the relationship between effects at the level of ion channels and effects at the level of firing and therapeutics is not linear or evident without further contextual information. Therefore, this approach must be used with caution and the cell type which expressed the mutant ion channel must be taken into account. Experimental assessment of the effects of a patients specific ion channel mutation \textit{in vivo} is not feasible at a large scale due to time and cost constraints, modelling of the effects of patient specific channelopathies is a desirable approach.
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The effects of changes in current properties depend in part on the neuronal model in which they occur and can be seen in the variance of correlations (especially in AUC) across models for a given current property change. Therefore, relative conductances and gating properties of currents in the current environment in which an alteration in current properties occurs plays an important role in determining the outcome on firing. The use of loss of function (LOF) and gain of function (GOF) is useful at the level of ion channels and whether a mutation results in more or less ionic current, however the extension of this thinking onto whether mutations induce LOF or GOF at the level of neuronal firing based on the ionic current LOF/GOF is problematic due to the dependency of neuronal firing changes on the current environment. Thus the direct leap from current level LOF/GOF characterizations to effects on firing without experimental or modelling-based evidence, although tempting, should be refrained from and viewed with caution when reported. This is especially relevant in the recent development of personalized medicine for channelopathies, where a patients specific channelopathy is identified and used to tailor treatments \citep{Weber2017, Ackerman2013, Helbig2020, Gnecchi2021, Musto2020, Brunklaus2022}. However, the effects of specific ion channel mutations are often characterized in expression systems and classified as LOF or GOF to aid in treatment decisions \citep{johannesen_genotype-phenotype_2021, Brunklaus2022, Musto2020}. Interestingly, both LOF and GOF \(\textrm{Na}_{\textrm{V}}\textrm{1.1}\) mutations can benefit from treatment with sodium channel blockers \citep{johannesen_genotype-phenotype_2021}, suggesting that the relationship between effects at the level of ion channels and effects at the level of firing and therapeutics is not linear or evident without further contextual information. Therefore, this approach must be used with caution and the cell type which expressed the mutant ion channel must be taken into account. Experimental assessment of the effects of a patients specific ion channel mutation \textit{in vivo} is not feasible at a large scale due to time and cost constraints, modelling of the effects of patient specific channelopathies is a desirable approach.
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Accordingly, for accurate modelling and predictions of the effects of mutations on neuronal firing, information as to the type of neurons containing the affected channel, and the properties of the affected and all currents in the affected neuronal type is needed. When modelling approaches are sought out to overcome the limitations of experimental approaches, care must be taken to account for model dependency and the generation of relevant cell-type or cell specific populations of models should be standard in assessing the effects of mutations in specific neurons.
|
||||
\par\null
|
||||
|
||||
|
||||
80
ref.bib
80
ref.bib
@ -1,3 +1,62 @@
|
||||
|
||||
@Article{Noebels2017,
|
||||
author = {Noebels, Jeffrey},
|
||||
journal = {The Journal of General Physiology},
|
||||
title = {Precision physiology and rescue of brain ion channel disorders},
|
||||
year = {2017},
|
||||
issn = {0022-1295},
|
||||
month = may,
|
||||
number = {5},
|
||||
pages = {533--546},
|
||||
volume = {149},
|
||||
abstract = {Noebels highlights the importance of cellular and circuit-level context for understanding channelopathies of the brain., Ion channel genes, originally implicated in inherited excitability disorders of muscle and heart, have captured a major role in the molecular diagnosis of central nervous system disease. Their arrival is heralded by neurologists confounded by a broad phenotypic spectrum of early-onset epilepsy, autism, and cognitive impairment with few effective treatments. As detection of rare structural variants in channel subunit proteins becomes routine, it is apparent that primary sequence alone cannot reliably predict clinical severity or pinpoint a therapeutic solution. Future gains in the clinical utility of variants as biomarkers integral to clinical decision making and drug discovery depend on our ability to unravel complex developmental relationships bridging single ion channel structure and human physiology.},
|
||||
doi = {10.1085/jgp.201711759},
|
||||
file = {PubMed Central Link:https\://www.ncbi.nlm.nih.gov/pmc/articles/PMC5412535/:text/html},
|
||||
pmcid = {PMC5412535},
|
||||
pmid = {28428202},
|
||||
url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5412535/},
|
||||
urldate = {2022-04-13},
|
||||
}
|
||||
|
||||
|
||||
@Article{Dunlop2008,
|
||||
author = {Dunlop, John and Bowlby, Mark and Peri, Ravikumar and Vasilyev, Dmytro and Arias, Robert},
|
||||
journal = {Nature Reviews Drug Discovery},
|
||||
title = {High-throughput electrophysiology: an emerging paradigm for ion-channel screening and physiology},
|
||||
year = {2008},
|
||||
issn = {1474-1784},
|
||||
month = apr,
|
||||
number = {4},
|
||||
pages = {358--368},
|
||||
volume = {7},
|
||||
abstract = {Ion channels represent an important class of druggable targets; however, it is generally appreciated in the field that ion-channel targeted drug discovery has been hampered by the unavailability of high-throughput platforms that use electrophysiological techniques for the characterization of compound activity. To address this bottleneck, in the past 5 years, several companies have developed and introduced automated platforms for performing electrophysiological studies.This recent explosion includes different approaches taken to carry out multi-channel planar-array based patch-clamp recordings of mammalian cells, resulting in the commercialization of four systems — IonWorks, PatchXpress, Patchliner and CytoPatch. Complementary to these technologies has been the development of lower capacity systems that fully automate conventional manual patch-clamp recordings including the Flyscreen, AutoPatch and RoboPatch for mammalian cells, and the Robocyte and OpusXpress 6000A for Xenopus oocytes.Despite the sophisticated technologies that are now available, automating patch-clamp electrophysiology often presents underestimated challenges regarding reproducibility with the cells being used; this needs to be fully appreciated when embarking on the implementation of any of these approaches.The need to assess the potential of drug candidates to inhibit cardiac ion-channels, particularly hERG, has greatly contributed to the development of these technologies. Although higher throughput non-electrophysiological assays have a reasonable predictive potential, they have several limitations that might be technically or chemically limiting. Consequently, the desire to use electrophysiological assays early on to assess ion-channel liabilities has been one of the key drivers for implementation of automated electrophysiology.Compound screening against molecularly isolated, heterologously expressed ion channels, will often identify drug candidates whose higher-order impact on networked neuronal systems are not necessarily inferable from their effects on individual conductances. Raising the throughput of pharmacological evaluation in such higher-order systems presents a distinct set of challenges. However, recent progress has been made in the development of automated systems for performing electrophysiogical studies in brain slices and other intact biological preparations.The availability of these technologies has re-energized ion-channel targeted drug discovery by allowing the development of screening paradigms that were not feasible in the pre-automation era. In our opinion this holds much promise for the discovery and development of innovative new ion-channel targeted drugs. Tractability of ion channels as drug targets coupled with future advances in technology platforms and decreased cost of consumables are expected to support an even wider implementation of these automated systems.},
|
||||
copyright = {2008 Nature Publishing Group},
|
||||
doi = {10.1038/nrd2552},
|
||||
file = {Full Text PDF:https\://www.nature.com/articles/nrd2552.pdf:application/pdf},
|
||||
keywords = {Biomedicine, general, Pharmacology/Toxicology, Biotechnology, Medicinal Chemistry, Molecular Medicine, Cancer Research},
|
||||
language = {en},
|
||||
publisher = {Nature Publishing Group},
|
||||
shorttitle = {High-throughput electrophysiology},
|
||||
url = {https://www.nature.com/articles/nrd2552},
|
||||
urldate = {2022-04-13},
|
||||
}
|
||||
|
||||
@Article{Balestrini1044,
|
||||
author = {Balestrini, Simona and Chiarello, Daniela and Gogou, Maria and Silvennoinen, Katri and Puvirajasinghe, Clinda and Jones, Wendy D and Reif, Philipp and Klein, Karl Martin and Rosenow, Felix and Weber, Yvonne G and Lerche, Holger and Schubert-Bast, Susanne and Borggraefe, Ingo and Coppola, Antonietta and Troisi, Serena and M{\o}ller, Rikke S and Riva, Antonella and Striano, Pasquale and Zara, Federico and Hemingway, Cheryl and Marini, Carla and Rosati, Anna and Mei, Davide and Montomoli, Martino and Guerrini, Renzo and Cross, J Helen and Sisodiya, Sanjay M},
|
||||
title = {Real-life survey of pitfalls and successes of precision medicine in genetic epilepsies},
|
||||
volume = {92},
|
||||
number = {10},
|
||||
pages = {1044--1052},
|
||||
year = {2021},
|
||||
doi = {10.1136/jnnp-2020-325932},
|
||||
publisher = {BMJ Publishing Group Ltd},
|
||||
abstract = {Objective The term {\textquoteleft}precision medicine{\textquoteright} describes a rational treatment strategy tailored to one person that reverses or modifies the disease pathophysiology. In epilepsy, single case and small cohort reports document nascent precision medicine strategies in specific genetic epilepsies. The aim of this multicentre observational study was to investigate the deeper complexity of precision medicine in epilepsy.Methods A systematic survey of patients with epilepsy with a molecular genetic diagnosis was conducted in six tertiary epilepsy centres including children and adults. A standardised questionnaire was used for data collection, including genetic findings and impact on clinical and therapeutic management.Results We included 293 patients with genetic epilepsies, 137 children and 156 adults, 162 females and 131 males. Treatment changes were undertaken because of the genetic findings in 94 patients (32\%), including rational precision medicine treatment and/or a treatment change prompted by the genetic diagnosis, but not directly related to known pathophysiological mechanisms. There was a rational precision medicine treatment for 56 patients (19\%), and this was tried in 33/56 (59\%) and was successful (ie, \>50\% seizure reduction) in 10/33 (30\%) patients. In 73/293 (25\%) patients there was a treatment change prompted by the genetic diagnosis, but not directly related to known pathophysiological mechanisms, and this was successful in 24/73 (33\%).Significance Our survey of clinical practice in specialised epilepsy centres shows high variability of clinical outcomes following the identification of a genetic cause for an epilepsy. Meaningful change in the treatment paradigm after genetic testing is not yet possible for many people with epilepsy. This systematic survey provides an overview of the current application of precision medicine in the epilepsies, and suggests the adoption of a more considered approach.Data are available on reasonable request. The authors confirm that the data supporting the findings of this study are available from the corresponding author, on reasonable request and subject to protocol approvals at each contributing site.},
|
||||
issn = {0022-3050},
|
||||
URL = {https://jnnp.bmj.com/content/92/10/1044},
|
||||
eprint = {https://jnnp.bmj.com/content/92/10/1044.full.pdf},
|
||||
journal = {Journal of Neurology, Neurosurgery \& Psychiatry}
|
||||
}
|
||||
|
||||
@Article{chi_manipulation_2007,
|
||||
author = {Chi, Xian Xuan and Nicol, G. D.},
|
||||
title = {Manipulation of the {Potassium} {Channel} {Kv1}.1 and {Its} {Effect} on {Neuronal} {Excitability} in {Rat} {Sensory} {Neurons}},
|
||||
@ -1298,3 +1357,24 @@ SIGNIFICANCE: Bromide is most effective and is a well-tolerated drug among DS pa
|
||||
month = nov,
|
||||
year = {2001},
|
||||
}
|
||||
|
||||
|
||||
@Article{Saltelli2002,
|
||||
author = {Saltelli, Andrea},
|
||||
journal = {Risk Analysis},
|
||||
title = {Sensitivity {Analysis} for {Importance} {Assessment}},
|
||||
year = {2002},
|
||||
issn = {1539-6924},
|
||||
number = {3},
|
||||
pages = {579--590},
|
||||
volume = {22},
|
||||
abstract = {We review briefly some examples that would support an extended role for quantitative sensitivity analysis in the context of model-based analysis (Section 1). We then review what features a quantitative sensitivity analysis needs to have to play such a role (Section 2). The methods that meet these requirements are described in Section 3; an example is provided in Section 4. Some pointers to further research are set out in Section 5.},
|
||||
doi = {10.1111/0272-4332.00040},
|
||||
file = {Full Text PDF:https\://onlinelibrary.wiley.com/doi/pdfdirect/10.1111/0272-4332.00040:application/pdf},
|
||||
keywords = {Uncertainty analysis, quantitative sensitivity analysis, computational models, assessment of importance, risk analysis},
|
||||
language = {en},
|
||||
url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/0272-4332.00040},
|
||||
urldate = {2022-04-12},
|
||||
}
|
||||
|
||||
@Comment{jabref-meta: databaseType:bibtex;}
|
||||
|
||||
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