Using Mouse Pain Scales to Discover Unusual Pain Sensitivity and New Pain Targets

使用小鼠疼痛量表发现异常的疼痛敏感性和新的疼痛目标

• 批准号: 10842053
• 负责人: Ishmail John Abdus-Saboor
• 金额: $ 6.25万
• 依托单位: COLUMBIA UNIV NEW YORK MORNINGSIDE
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-07-01 至 2024-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10842053
• 关键词: Ablation; Acute Pain; Animals; Atlases; Award; Behavior assessment; Behavioral; Biological; Candidate Disease Gene; Communities; Computer software; Custom; Dimensions; Esthesia; Genes; Genetic; Genetic Variation; Goals; Human; Human Genome; Hypersensitivity; Individual; Machine Learning; Maps; Measures; Mechanics; Mission; Mus; Neurons; Nociceptors; Pain; Pain Measurement; Pathologic; Persons; Population; Positioning Attribute; Public Health; Publications; Publishing; Research; Resources; Risk; Role; Route; Sensory; Shapes; Speed; Testing; Therapeutic; United States National Institutes of Health; Wild Type Mouse; chronic pain; chronic pain management; genetic architecture; human RNA sequencing; inter-individual variation; mouse genetics; mouse model; non-verbal; pain behavior; pain chronification; pain model; pain reduction; pain scale; pain sensation; pain sensitivity; pre-clinical; preclinical study; programs; response; single-cell RNA sequencing; spontaneous pain; therapeutic target; tool; trait; translational potential; unsupervised learning

Project Summary There is vast inter-individual variability to acute and chronic pain, and genetic architecture is one of the major factors that shape our unique responses to pain. The misexpression of genes in nociceptors can facilitate the transition from acute to chronic pain, and thus targeting nociceptor genes in the periphery is an important route towards non-addictive pain therapeutics. If we seek to uncover how diverse human genomes may give rise to pathological pain sensation, a narrow focus in our preclinical studies on one canonical wildtype mouse line, C57BL/6J, is insufficient. Moreover, to harness the full translational potential of mouse models of pain, a prerequisite is being able to accurately measure pain, which is an inherently subjective sensation that becomes even harder to score in nonverbal animals. In recent publications from my lab, we have developed automated mouse “pain scales” using high-speed videography, machine learning, and custom software, to capture the sensory-reflexive dimensions of pain in a quantitative manner. In ongoing studies, we use unsupervised learning platforms to automatically capture spontaneous signatures of pain. Therefore, we are now well-positioned to use our automated pain behavior assessment platforms to test new pain target genes and identify genetically divergent mice with atypical pain sensitivity. We have three major goals in this New Innovator Award program. First, we aim to identify genetically unique mouse lines that have unusual responses to acute and chronic pain, using evoked and spontaneous pain measurements, testing hundreds of mice. The mouse lines tested in this application that fail to respond normally to pain, or have heightened pain responses, may hold the keys to uncovering how populations of people have pathological pain sensitivity. This is significant because individuals with hypersensitivity to pain, appear to have an increased risk of developing chronic pain. The genetic construction of these mouse lines also facilitates mapping analyses to connect genes to pain traits, thus identifying potential new pain targets. Second, we will investigate the biological basis of pain sensitivity in a mouse line that my lab already published on, as having mechanical pain hypersensitivity. We aim to identify causative changes that permit this hypersensitivity, and thus unlock a new pain target. Finally, we will use mouse genetic targeting to ablate a candidate pain target in mouse nociceptors and test functional consequences with our automated behavioral pipelines. This new candidate gene recently emerged from single-cell RNA sequencing of human nociceptors. Taken together, we are levering the tools my lab developed and resources made available to the entire community, to produce an atlas of pain hyper- and hypo-sensitive mouse lines, as well as functionally identifying new pain therapeutic targets.

项目概要 急性和慢性疼痛存在巨大的个体差异，遗传结构是其​​中之一 塑造我们对疼痛独特反应的主要因素。伤害感受器中基因的错误表达可以促进 从急性疼痛到慢性疼痛的转变，因此针对外周伤害感受器基因是一个重要的 通往非成瘾性疼痛治疗的途径。如果我们试图揭示多样化的人类基因组如何产生 病理性疼痛感觉，这是我们对一种典型野生型小鼠品系的临床前研究的一个狭窄焦点， C57BL/6J，不足。此外，为了充分利用小鼠疼痛模型的转化潜力， 前提是能够准确测量疼痛，这是一种固有的主观感觉， 在非语言动物中得分就更难了。在我的实验室最近发表的出版物中，我们开发了自动化 使用高速摄像、机器学习和定制软件来捕获小鼠“疼痛量表” 以定量方式描述疼痛的感觉反射维度。在正在进行的研究中，我们使用无监督学习 自动捕捉自发疼痛特征的平台。因此，我们现在可以很好地使用 我们的自动化疼痛行为评估平台可测试新的疼痛目标基因并识别基因 具有非典型疼痛敏感性的不同小鼠。 我们的新创新者奖计划有三个主要目标。首先，我们的目标是从基因上鉴定 独特的小鼠品系，利用诱发和自发疼痛，对急性和慢性疼痛有不寻常的反应 测量，测试了数百只老鼠。本应用中测试的鼠标线无法正常响应 疼痛或疼痛反应加剧可能是揭示人们如何进行疼痛的关键 病理性疼痛敏感性。这很重要，因为对疼痛过敏的人似乎有 发生慢性疼痛的风险增加。这些小鼠品系的基因构建也有利于 绘图分析将基因与疼痛特征联系起来，从而识别潜在的新疼痛目标。其次，我们将 研究我的实验室已经发表的小鼠品系疼痛敏感性的生物学基础，因为 机械性疼痛过敏。我们的目标是找出导致这种超敏反应的原因变化，从而 解锁新的疼痛目标。最后，我们将使用小鼠基因靶向消除小鼠的候选疼痛靶点 伤害感受器并通过我们的自动化行为管道测试功能后果。这个新的候选基因 最近从人类伤害感受器的单细胞 RNA 测序中发现。总的来说，我们正在利用 我的实验室开发的工具和向整个社区提供的资源，以制作一份超级疼痛图谱 和低敏感性小鼠系，以及功能性识别新的疼痛治疗靶点。