Pain-Associated Neuronal Hyperexcitability and Intracellular Calcium Signaling

Va Connecticut Healthcare System, West Haven CT

Investigators

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Abstract

DESCRIPTION (provided by applicant): Better treatments for pain are urgently needed both within the VA and globally. The objective of this proposal is to validate improved assays that measure nociceptor excitability toward the rapid development of more effective treatments for pain. Our laboratory has demonstrated that gain-of-function variants of the voltage- gated sodium channel Nav1.7 known to cause human pain syndromes respond more strongly to stimuli. We have shown that when these channel variants were heterologously expressed in rodent DRG neurons they elicit neuronal hyperexcitability. In addition, we have shown that variants of voltage-gated sodium channels Nav1.8 and Nav1.9 associated with painful peripheral neuropathies also elicit hyperexcitability when expressed in rodent DRG neurons. The approach of expressing sodium channel variants in rodent DRG neurons provides a useful in vitro model toward identifying variants that cause, or increase the susceptibility of carriers to developing, pain syndromes. Our studies using whole-cell patch-clamp electrophysiology have shown that drugs that are clinically effective in mitigating pain also reduce electrical excitability in this model, making this in vitro system suitable for testing novel pharmacological agents that are being developed for clinical testing in humans. However, measurement of electrical excitability using whole-cell patch-clamp electrophysiology, although powerful and quantitative, is low-throughput, less physiological (requiring manipulations that disrupt cell integrity), and does not permit repeated exposures of the same cell to different treatments. In this project we propose to develop an improved assay system that would provide a unique platform for: a) rapid testing of ion channel variants from patients with chronic pain to determine their effect on neuronal excitability; and b) high-throughput identification of pain therapeutics that would be most effective in the context of the patient's own genetic profile.