Refined biomimetic model of chronic pain healed with erythropoietin

Abstract

Humans suffering with chronic pain may have no evidence of a lesion or disease. They are managed with a morass of drugs and invasive procedures. In many, their persistent pain occurs after the healing of a soft tissue injury, with a neural source hypothesized. Opiates, commonly used to mitigate their symptoms, can cause an increase in neuropathic pain over time. Current animal models of neuropathic pain commonly create direct neural damage with open surgeries using ligatures, neurectomies, chemicals or other forms of intentional trauma. However, we have observed clinically that after an injury in humans, the naturally occurring process of tissue repair can cause chronic neural pain. We show here how the refined biomimetic NeuroDigm GELTM Model, in the mature male rat, gradually induces neuropathic pain behavior with a nonsurgical percutaneous injection of tissue-derived hydrogel in the tunnel of the distal tibial nerve. This perineural model creates a mononeuritis with the biogenic matrix induction of tissue remodeling, the last stage of tissue repair. Repeated behavioral analgesic testing over 5 months in the model implied a unique predictive validity for all analgesics tested. Morphine, initially effective, had an increase in pain behavior over time, suggesting an opioid-induced hyperalgesia, as seen in humans. Celecoxib produced no analgesia, while gabapentin and duloxetine at low doses had profound analgesia. Histology reveals focal neural remodeling, with neural regeneration, as in human biopsies. For the first time, targeted erythropoietin appears to heal neural pain, by extinguishing bilateral pain behavior present for over 4 months.\n\ntranslational model, neuropathic pain, erythropoietin, neural regeneration, soft tissue injuries, neuritis, tissue repair, hydrogel, animal model of disease, neural remodeling, age, opioid-induced hyperalgesia, morphine resistance, analgesics, refined pain model, matrix remodeling, neuroinflammation, predictive validity, habituation, estrogen