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The genetics of neuropathic pain from model organisms to clinical application

Authors :
Michael Costigan
Margarita Calvo
Greg A. Weir
G. Gregory Neely
Harry L. Hébert
Blair H. Smith
Alexander J. Davies
David L.H. Bennett
Nanna B. Finnerup
Roy C. Levitt
Elissa J. Chesler
Source :
Neuron, Calvo, M, Davies, A J, Hébert, H L, Weir, G A, Chesler, E J, Finnerup, N B, Levitt, R C, Smith, B H, Neely, G G, Costigan, M & Bennett, D L 2019, ' The Genetics of Neuropathic Pain from Model Organisms to Clinical Application ', Neuron, vol. 104, no. 4, pp. 637-653 . https://doi.org/10.1016/j.neuron.2019.09.018
Publication Year :
2019

Abstract

Neuropathic pain (NeuP) arises due to injury of the somatosensory nervous system and is both common and disabling, rendering an urgent need for non-addictive, effective new therapies. Given the high evolutionary conservation of pain, investigative approaches from Drosophila mutagenesis to human Mendelian genetics have aided our understanding of the maladaptive plasticity underlying NeuP. Successes include the identification of ion channel variants causing hyper-excitability and the importance of neuro-immune signaling. Recent developments encompass improved sensory phenotyping in animal models and patients, brain imaging, and electrophysiology-based pain biomarkers, the collection of large well-phenotyped population cohorts, neurons derived from patient stem cells, and high-precision CRISPR generated genetic editing. We will discuss how to harness these resources to understand the pathophysiological drivers of NeuP, define its relationship with comorbidities such as anxiety, depression, and sleep disorders, and explore how to apply these findings to the prediction, diagnosis, and treatment of NeuP in the clinic.<br />Calvo et al. discuss how applying genetic techniques, from model organisms to human populations, can help us understand the pathophysiology of neuropathic pain. These strategies could soon reveal novel analgesic drug targets and aid both personalized risk prediction and treatment.

Details

ISSN :
10974199 and 08966273
Volume :
104
Issue :
4
Database :
OpenAIRE
Journal :
Neuron
Accession number :
edsair.doi.dedup.....3ebb7c6071bad2b10d64735a8805bc85