MICA: Exploiting specialised pro-resolution molecule mediated analgesia to identify novel targets for the treatment of chronic pain

骨关节炎（OA）和糖尿病性神经病变通常与慢性疼痛有关，正如我们的PPIE代表所强调的那样，慢性疼痛对日常生活产生了巨大的影响。并不是每个患有这些疾病的人都会经历慢性疼痛，了解这些差异可能会为新的治疗方法提供见解。在动物疼痛模型中，人体产生的一类天然分子（specialized pro-resolution molecules, SPMs）具有强大的镇痛作用，而SPMs水平较低的健康志愿者对疼痛更敏感。至关重要的是，我们发现患有OA的人，SPMs水平较低的人会经历更多的疼痛。SPMs通过干扰多种信号通路来减轻疼痛，从而产生强烈的镇痛作用。尽管SPMs很快被分解成无活性的产物，但它们具有持久的效果——这一过程可能是由于已知的在基因表达水平上驱动疼痛反应的分子的调节。我们已经确定了与SPMs对OA疼痛的影响有关的基因通路。目的：确定导致SPMs产生强效和持久镇痛的细胞和分子过程，并利用这些信息确定新的治疗方法来改善慢性疼痛的治疗。团队：这项新研究由我们的PPIE指导小组指导，并由一个在慢性疼痛机制，疼痛遗传学和实验性疼痛方面具有优势的团队领导。制药公司礼来（Eli Lilly）带来了分析和整合大规模数据集的专业知识，以最大限度地利用这些有价值的临床数据集。该项目还支持共同研究员P Gowler博士的职业发展。实验计划：我们将使用内部生物信息学方法来分析我们现有的和新获得的数据，以预测可能调节与SPMs高低水平相关的基因表达变化及其与慢性疼痛的关系的特定分子（称为microrna）。首先，我们将收集患有OA疼痛的人的血液（并控制非OA组），对预测调节OA疼痛相关基因水平和特定稳定分子水平的microrna进行详细分析，该分子是许多SPMs的前体，称为17-HDHA。利用现有的计算工具，我们将确定与17-HDHA高水平和低水平相关的microrna，以及这与OA疼痛的关系。我们将在患有不同类型慢性疼痛的患者（糖尿病神经性疼痛伴痛和无痛）中验证这些发现，以确定这两种类型慢性疼痛的共同点和差异，从而确定特定于疾病的靶点，以及它们之间的共同点。为了关注这些途径在驱动疼痛中的潜在作用，对已经从OA患者（由我们的合作者）收集的关节组织和滑液中现有的microRNA数据集进行计算分析，将确定我们已经确定的哪些microRNA也存在于疾病部位和疼痛源。使用实验模型和工具，我们将确定哪些临床鉴定的microrna被17-HDHA治疗小鼠改变，支持哪些途径可能成为新疗法的候选者。专门开发用于操纵这些microrna功能的分子工具将用于鉴定介导17-HDHA对驱动疼痛反应的兴奋性感觉神经活动的影响的microrna。这种方法将优先考虑临床鉴定的microrna，这些microrna对慢性OA疼痛患者的治疗发展最有潜力。这一结果的重要性得到了我们的PPIE代表的支持，因为患有疼痛的人希望开发新的治疗方法来减少他们现有的疼痛，让他们有一个更充实、更快乐的生活体验。

Osteoarthritis (OA) and diabetic neuropathy are often associated with chronic pain which, as highlighted by our PPIE representatives, hugely impacts upon daily life. Not everybody with these diseases experiences chronic pain, and understanding these differences may offer insight into new treatments. A family of natural molecules produced by the body (specialised pro-resolution molecules (SPMs)) have robust analgesic effects in animal models of pain, while healthy volunteers with lower levels of SPMs are more sensitive to pain. Crucially, we showed that people with OA who have lower levels of SPMs experience significantly more pain. The SPMs reduce pain by interfering with multiple signalling pathways, leading to strong analgesic effects. Although SPMs are quickly broken-down into inactive products, they have long-lasting effects - a process likely to be due to the modulation of molecules known to drive pain responses at the gene expression level. We have already identified gene pathways implicated in the effects of the SPMs on OA pain in people.Aim: To identify the cellular and molecular processes that lead to the powerful and long-lasting analgesia produced by the SPMs and to use this information to identify new therapeutic approaches to improve the treatment of chronic pain. Team: This new research is guided by our PPIE steering group, and is lead by a team which brings strength in chronic pain mechanisms, genetics of pain and experimental pain. The pharmaceutical company Eli Lilly brings expertise in analysing and integrating large-scale datasets to maximise the benefits of these valuable clinical datasets. The project also supports the career development of researcher co-investigator Dr P Gowler.Experimental Plan: We will use in-house bioinformatic approaches to analyse our existing and newly acquired data to predict the specific molecules (known as microRNAs) which may regulate changes in gene expression associated with high versus low levels of SPMs and their relationships with chronic pain. First we will collect blood from people with OA pain (and control non-OA group) to undertake a detailed analysis of microRNAs that are predicted to regulate the levels of genes associated with OA pain and levels of a specific stable molecule which is a precursor for many SPMs, known as 17-HDHA. Using existing computational tools we will identify the microRNAs associated with having high versus low levels of 17-HDHA and how this relates to the OA pain experienced. We will validate these findings in patients with a different type of chronic pain (diabetic neuropathic pain with and without pain) to identify commonality and differences between these two types of chronic pain, thus identifying targets that are specific to the diseases, and those shared between them. To focus on potential roles of these pathways in driving pain, computational analysis of existing microRNA datasets from joint tissue and synovial fluid already collected from people with OA (by our collaborator) will identify which microRNAs that we have identified are also present at the site of disease and the source of the pain. Using experimental models and tools we will identify which of the clinically identified microRNAs are altered by 17-HDHA treatment in mice, supporting which pathways are likely candidates for novel therapeutics. Molecular tools specifically developed to manipulate the function of those microRNAs will be used to identify the miRNAs that mediate the effects of the 17-HDHA on excitatory sensory nerve activity that drives pain responses. This approach will prioritise the clinically identified microRNAs to those with the most potential for therapeutic development for people with chronic OA pain. The importance of this outcome was supported by our PPIE representatives, as people living with pain want the development of new treatments which reduce their existing pain and allows them to have a fuller and happier life experience.