A pain-mediated neural signal induces relapse in murine autoimmune encephalomyelitis, a multiple sclerosis model
- Hokkaido University, Japan
- Tsurumi University, Japan
- University of Freiburg, Germany
- Wakayama Medical University, Japan
- Osaka University, Japan
- National Hospital Organization Toneyama Hospital, Japan
- University of Tokyo, Japan
Abstract
Although pain is a common symptom of various diseases and disorders, its contribution to disease pathogenesis is not well understood. Here we show using murine experimental autoimmune encephalomyelitis (EAE), a model for multiple sclerosis (MS), that pain induces EAE relapse. Mechanistic analysis showed that pain induction activates a sensory-sympathetic signal followed by a chemokine-mediated accumulation of MHC class II+CD11b+ cells that showed antigen-presentation activity at specific ventral vessels in the fifth lumbar cord of EAE-recovered mice. Following this accumulation, various immune cells including pathogenic CD4+ T cells recruited in the spinal cord in a manner dependent on a local chemokine inducer in endothelial cells, resulting in EAE relapse. Our results demonstrate that a pain-mediated neural signal can be transformed into an inflammation reaction at specific vessels to induce disease relapse, thus making this signal a potential therapeutic target.
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Animal experimentation: All animal experiments were performed following the guidelines of the Institutional Animal Care and Use Committees of the Institute for Genetic Medicine, the Graduate School of Medicine, Hokkaido University and the Graduate School of Frontier Bioscience and Graduate School of Medicine, Osaka University with protocol numbers 2014-0083 and 2014-0026.
Copyright
© 2015, Arima et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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A pain-mediated neural signal induces relapse in murine autoimmune encephalomyelitis, a multiple sclerosis model
eLife 4:e08733.
https://doi.org/10.7554/eLife.08733
