Abstract:The voltage-gated sodium channel Nav1.7 is encoded by SCN9A gene and plays a critical role in pain sensitivity. Several SCN9A gain-of-function (GOF) mutations have been found in patients with small fiber neuropathy (SFN) having chronic pain, including the R185H mutation. However, for most of these variants, their involvement in pain phenotype still needs to be experimentally elucidated. In order to delineate the impact of R185H mutation on pain sensitivity, we have established the Scn9aR185H mutant mouse model… Show more
“…Given the role of Na v 1.7 in sympathetic neurons in heat pain in mice 11 , it is possible that hyperactive Na v 1.7 channels in sympathetic neurons play a significant role in the very rare cases of Primary Erythermalgia linked to Na v 1.7 mutations (OMIM 133020). However, mouse models of gain-of-function human Na v 1.7 mutants do not show an erythermalgia phenotype, whilst a human mutation linked to painful small fiber neuropathy does exhibit enhanced pain, interestingly in mice in a sex dependent manner 12 . This fits with the observations of diminished C-fiber peripheral terminals in some human Na v 1.7 pain free nulls 13 .…”
Genetic deletion and pharmacological inhibition are distinct approaches to unravelling pain mechanisms, identifying targets and developing new analgesics. Both approaches have been applied to the voltage-gated sodium channels Nav1.7 and Nav1.8. Genetic deletion of Nav1.8 in mice leads to a loss of pain, and antagonists are effective human analgesics. Complete embryonic loss of Nav1.7 in humans or in mouse sensory neurons leads to profound analgesia substantially mediated by endogenous opioid signaling, and anosmia that is opioid independent. Autonomic function appears to be normal. Adult deletion of Nav1.7 in sensory neurons also leads to analgesia with diminished sensory neuron excitability but there is no opioid component of analgesia. Pharmacological inhibition of Nav1.7 leads to dramatic side-effects on the autonomic nervous system. Here we compare and contrast the distinct embryonic and adult null mechanisms of Nav1.7 loss-of-function analgesia. We describe an endogenous opioid mechanism of analgesia that provides new opportunities for therapeutic intervention and pain relief.
“…Given the role of Na v 1.7 in sympathetic neurons in heat pain in mice 11 , it is possible that hyperactive Na v 1.7 channels in sympathetic neurons play a significant role in the very rare cases of Primary Erythermalgia linked to Na v 1.7 mutations (OMIM 133020). However, mouse models of gain-of-function human Na v 1.7 mutants do not show an erythermalgia phenotype, whilst a human mutation linked to painful small fiber neuropathy does exhibit enhanced pain, interestingly in mice in a sex dependent manner 12 . This fits with the observations of diminished C-fiber peripheral terminals in some human Na v 1.7 pain free nulls 13 .…”
Genetic deletion and pharmacological inhibition are distinct approaches to unravelling pain mechanisms, identifying targets and developing new analgesics. Both approaches have been applied to the voltage-gated sodium channels Nav1.7 and Nav1.8. Genetic deletion of Nav1.8 in mice leads to a loss of pain, and antagonists are effective human analgesics. Complete embryonic loss of Nav1.7 in humans or in mouse sensory neurons leads to profound analgesia substantially mediated by endogenous opioid signaling, and anosmia that is opioid independent. Autonomic function appears to be normal. Adult deletion of Nav1.7 in sensory neurons also leads to analgesia with diminished sensory neuron excitability but there is no opioid component of analgesia. Pharmacological inhibition of Nav1.7 leads to dramatic side-effects on the autonomic nervous system. Here we compare and contrast the distinct embryonic and adult null mechanisms of Nav1.7 loss-of-function analgesia. We describe an endogenous opioid mechanism of analgesia that provides new opportunities for therapeutic intervention and pain relief.
“…A part of the analysis performed on the mouse models for Scn10a [ 25 ] and Scn9a [ 26 ] genes is already available in the publications containing the molecular and phenotypic characterization of these models. For the Scn10a G1662S murine model, 112 animals including males and females (57 females and 55 males) and a total of 36 wild-type, 39 heterozygous, 37 homozygous animals were challenged in a phenotypic pipeline and the data from 14 variables was collected for the analysis.…”
Section: Resultsmentioning
confidence: 99%
“…1 ; Table 1 ) and show two examples of the application of Gdaphen to phenotypic datasets of mouse models of neuropathic pain. The datasets show increased complexity and some results of the application of GDAPHEN are published as part of the deep statistical analyses performed over the phenotypic characterization of these models [ 25 , 26 ]. Fig.…”
Background
In individuals or animals suffering from genetic or acquired diseases, it is important to identify which clinical or phenotypic variables can be used to discriminate between disease and non-disease states, the response to treatments or sexual dimorphism. However, the data often suffers from low number of samples, high number of variables or unbalanced experimental designs. Moreover, several parameters can be recorded in the same test. Thus, correlations should be assessed, and a more complex statistical framework is necessary for the analysis. Packages already exist that provide analysis tools, but they are not found together, rendering the decision method and implementation difficult for non-statisticians.
Result
We present Gdaphen, a fast joint-pipeline allowing the identification of most important qualitative and quantitative predictor variables to discriminate between genotypes, treatments, or sex. Gdaphen takes as input behavioral/clinical data and uses a Multiple Factor Analysis (MFA) to deal with groups of variables recorded from the same individuals or anonymize genotype-based recordings. Gdaphen uses as optimized input the non-correlated variables with 30% correlation or higher on the MFA-Principal Component Analysis (PCA), increasing the discriminative power and the classifier’s predictive model efficiency. Gdaphen can determine the strongest variables that predict gene dosage effects thanks to the General Linear Model (GLM)-based classifiers or determine the most discriminative not linear distributed variables thanks to Random Forest (RF) implementation. Moreover, Gdaphen provides the efficacy of each classifier and several visualization options to fully understand and support the results as easily readable plots ready to be included in publications. We demonstrate Gdaphen capabilities on several datasets and provide easily followable vignettes.
Conclusions
Gdaphen makes the analysis of phenotypic data much easier for medical or preclinical behavioral researchers, providing an integrated framework to perform: (1) pre-processing steps as data imputation or anonymization; (2) a full statistical assessment to identify which variables are the most important discriminators; and (3) state of the art visualizations ready for publication to support the conclusions of the analyses. Gdaphen is open-source and freely available at https://github.com/munizmom/gdaphen, together with vignettes, documentation for the functions and examples to guide you in each own implementation.
“…Small fiber neuropathy is one of the other syndromes that is worth mentioning that is associated with a mutation of the SCN9A gene. 52 The disease sequence consists of an attack of severe pain beginning at the feet and the hand. 53 Even though the pain attack begins with the hand and feet as the person ages and in the more severe disease areas affected include the arm, ear, face, legs and legs.…”
Introduction
There is a great need to find alternative treatments for chronic pain which have become a healthcare problem. We discuss current therapeutic targeting Nav1.7.
Areas Covered
Nav1.7 is a sodium ion channel protein that is associated with several human pain genetic syndromes. It has been found that mutations associated with Nav1.7 lead to the loss of the ability to perceive pain in individuals that are otherwise normal. Several therapeutic interventions are presently undergoing preclinical and research using the methodology of damping Nav1.7 expressions as a methodology to decrease the sensation of pain leading to analgesia.
Expert Opinion
It is our strong belief that there is a viable future in the targeting of protein of Nav1.7 for the relief of chronic pain in humans. The review will look at the genomics associated with SCN1A and proteomic of Nav1.7 as a foundation to explain the mechanism of the therapeutic interventions targeting Nav1.7, the human disease that are associated with Nav1.7, and the current development of treatment for chronic pain whether in preclinical or clinical trials targeting Nav1.7 expressions. The development of therapeutic antagonists targeting Nav1.7 could be a viable alternative to the current treatments which have led to the opioid crisis. Therefore, Nav1.7 targeted treatment has a major clinical significance that will have positive consequences as it relates to chronic pain interventions.
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