Modulating skin innervation to treat cutaneous inflammation

ended

Skin disease is one of the most common human illnesses. At any given time, approximately one out of three individuals is affected by skin disease and it is the 18th leading cause of health burden worldwide. Despite this profound impact, skin disease continues to receive relatively little attention in global health forums, and the etiology of most of these conditions is unclear. The skin is our major interface with the external world, densely innervated with sensory and autonomic nerve fibers. Thus, neuromodulators are involved during all phases of skin damage and healing. Nevertheless, we do not fully understand the interaction between skin innervation and skin pathologies. More importantly, the therapeutic potential contained in cutaneous innervation has not been exploited. NEUROSKIN will determine how different skin innervations affect psoriasis, a major skin disease, representing the largest class of skin conditions, those that are mediated by inflammation. We will utilize a transgenic mouse model that enables optogenetic control of local peripheral innervations using light. This model was developed as part of our ERC STG to characterize the involvement of peripheral innervation on gut inflammation. In NEUROSKIN, we will extend this tool to develop additional transgenic mice relevant to cutaneous neuronal subpopulations. In these mice, we will control the activity of neurons innervating the psoriatic plaques at different stages of the disease. This will allow us to map potential of targeted neuronal interventions to treat inflammatory skin conditions. Such characterization is expected to introduce an entire set of therapeutic tools based on neurological manipulations, and allow us to repurpose drugs and other technologies (e.g electrical and magnetic simulation) for the potential treatment of skin disorders. Moreover, NEUROSKIN will introduce a new toolbox that will enable the entire community to study the involvement of skin innervation in skin functions.