Neuropathic vs. inflammatory pain in chronic pancreatitis: can unique biomarkers be identified to guide mechanistic approaches to pain treatment?

摘要 慢性胰腺炎（CP）通常伴有严重的衰弱性疼痛，这是非常难以治疗的。 临床上没有可用的工具来正确地表征患者正在经历的疼痛的亚型， 选择一种最有可能对患者的疼痛症状有益的治疗方法。有两种外围机制， 炎症性疼痛（IP）和神经性疼痛（NP）。IP的一个主要驱动因素是神经性的 炎症，由增加的神经活动引起的炎症，其驱动神经肽的释放， 招募/激活免疫细胞。NP由直接神经损伤（压迫或损伤）引起。重要的是，两者 不同类型的疼痛伴随着细胞因子表达的独特变化， 导致患者疼痛的机制（IP和/或NP）。开发区分IP和NP的工具 在临床上可以最终简化CP疼痛管理，因为有证据表明， 对一种疼痛比另一种更有效。例如，阿片类药物对IP更有效 而加巴喷丁类化合物对NP更有用。该提议旨在比较一种新的动物模型， 其中胰腺炎疼痛纯粹由IP（光遗传学）和常用的CP动物模型诱导 （慢性雨蛙素），其中疼痛是IP和NP两者的结果。目的是确定与细胞因子相关的细胞因子谱， 与特定疼痛表型进行比较，并与来自一个充分表征的临床队列的遗留样本进行比较。 CP患者我们还将测试患者是否表现出细胞因子谱和疼痛之间的相关性 特色长期计划是使用迭代方法，使用患者数据来优化动物模型。 CP的模型，然后可以用来开发疼痛类型的特定疗法。 除了将新技术（光遗传学）纳入CP的研究之外，本项目还将提供深入的 处理和分析人类数据的培训，并将为未来的人类提供基础。 研究将包括专门设计用于诊断炎症性和神经性疼痛的调查工具， 人类CP

Abstract Chronic pancreatitis (CP) is often accompanied by profoundly debilitating pain that is quite difficult to treat. There are no tools available in clinics to properly characterize the subtype of pain a patient is experiencing to choose a therapy most likely to benefit a patient’s pain symptoms. There are two peripheral mechanisms that could contribute, inflammatory pain (IP) and neuropathic pain (NP). A major driver of IP is neurogenic inflammation, inflammation resulting from increased neural activity that drives release of neuropeptides that recruit/activate immune cells. NP results from direct nerve injury (compression or lesion). Importantly, both types of pain are accompanied by unique changes in cytokine expression that can be used to identify mechanisms (IP and/or NP) contributing to a patient’s pain. The development of tools to differentiate IP and NP in the clinic could ultimately streamline CP pain management because there is evidence that certain therapies are far more efficacious for one type of pain versus the other. For example, opioids are more effective for IP while gabapentinoids are more useful for NP. This proposal is designed to compare a novel animal model in which pancreatitis pain is induced purely by IP (optogenetic) and a commonly used animal model of CP (chronic cerulein) in which pain is a result of both IP and NP. The goal is to identify cytokine profiles associated with the specific pain phenotypes and compare to legacy samples from a well-characterized clinical cohort of CP patients. We will also test whether patients show correlations between cytokine profiles and pain characteristics. The long-term plan is to use an iterative approach that uses patient data to refine animal models of CP that can then be used to develop pain-type specific therapies. In addition to incorporating new technologies (optogenetic) to the study of CP, this project will provide in depth training in handling and analyzing human data and will provide a foundation for future prospective human studies that will include survey tools specifically designed for diagnosis of inflammatory and neuropathic pain in humans with CP.