4.6 Review

Multiple sclerosis-induced neuropathic pain: pharmacological management and pathophysiological insights from rodent EAE models

Journal

INFLAMMOPHARMACOLOGY
Volume 22, Issue 1, Pages 1-22

Publisher

SPRINGER BASEL AG
DOI: 10.1007/s10787-013-0195-3

Keywords

Experimental autoimmune encephalomyelitis; Multiple sclerosis; Neuropathic pain; Allodynia; Neuroinflammation; Pharmacological management

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In patients with multiple sclerosis (MS), pain is a frequent and disabling symptom. The prevalence is in the range 29-86 % depending upon the assessment protocols utilised and the definition of pain applied. Neuropathic pain that develops secondary to demyelination, neuroinflammation and axonal damage in the central nervous system is the most distressing and difficult type of pain to treat. Although dysaesthetic extremity pain, L'hermitte's sign and trigeminal neuralgia are the most common neuropathic pain conditions reported by patients with MS, research directed at gaining insight into the complex mechanisms underpinning the pathobiology of MS-associated neuropathic pain is in its relative infancy. By contrast, there is a wealth of knowledge on the neurobiology of neuropathic pain induced by peripheral nerve injury. To date, the majority of research in the MS field has used rodent models of experimental autoimmune encephalomyelitis (EAE) as these models have many clinical and neuropathological features in common with those observed in patients with MS. However, it is only relatively recently that EAE-rodents have been utilised to investigate the mechanisms contributing to the development and maintenance of MS-associated central neuropathic pain. Importantly, EAE-rodent models exhibit pro-nociceptive behaviours predominantly in the lower extremities (tail and hindlimbs) as seen clinically in patients with MS-neuropathic pain. Herein, we review research to date on the pathophysiological mechanisms underpinning MS-associated neuropathic pain as well as the pharmacological management of this condition. We also identify knowledge gaps to guide future research in this important field.

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