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: 10581160
• 负责人: Ishmail John Abdus-Saboor
• 金额: $ 246.75万
• 依托单位: COLUMBIA UNIV NEW YORK MORNINGSIDE
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-21 至 2025-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10581160
• 关键词: 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; Measures; Mechanics; Mission; Mus; Neurons; Nociceptors; Pain; Pain Measurement; Pathologic; Persons; Population; Positioning Attribute; Public Health; Publications; Publishing; Reflex action; 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; innovation; inter-individual variation; mouse genetics; mouse model; 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.

项目摘要 急性和慢性疼痛存在巨大的个体间差异，遗传结构是其中之一。 影响我们对疼痛的独特反应的主要因素。伤害感受器中基因的错误表达 从急性疼痛到慢性疼痛的转变，因此靶向外周的伤害感受器基因是重要的 走向非成瘾性疼痛治疗的途径。如果我们试图揭示人类基因组的多样性 病理性疼痛感觉，我们在一个典型的野生型小鼠系的临床前研究中的一个狭窄的焦点， C57 BL/6 J是不够的。此外，为了利用小鼠疼痛模型的全部转化潜力， 先决条件是能够准确地测量疼痛，这是一种固有的主观感觉， 在不会说话的动物身上更难得分。在我的实验室最近的出版物中，我们开发了自动化的 使用高速摄像、机器学习和定制软件， 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， 平台来自动捕捉疼痛的自发信号。因此，我们现在可以利用 我们的自动疼痛行为评估平台，以测试新的疼痛靶基因， 具有非典型疼痛敏感性的分歧小鼠。 我们在这个创新奖计划中有三个主要目标。首先，我们的目标是从基因上识别 独特的小鼠品系，对急性和慢性疼痛有不寻常的反应，使用诱发和自发疼痛 测量，测试数百只老鼠。此应用程序中测试的鼠标线无法正常响应 疼痛，或有更高的疼痛反应，可能是揭示人群如何 病理性疼痛敏感性这一点很重要，因为对疼痛过敏的人似乎 患慢性疼痛的风险增加。这些小鼠品系的遗传构建也有助于 映射分析，将基因与疼痛特征联系起来，从而确定潜在的新疼痛靶点。二是 在我的实验室已经发表的小鼠品系中研究疼痛敏感性的生物学基础， 机械性疼痛过敏我们的目标是确定允许这种超敏反应的病因变化， 解锁一个新的痛苦目标最后，我们将使用小鼠遗传靶向来消融小鼠中的候选疼痛靶标， 伤害感受器和测试功能后果与我们的自动化行为管道。这个新的候选基因 最近从人类伤害感受器的单细胞RNA测序中出现。总之，我们正在勒韦林 我的实验室开发的工具和资源提供给整个社区，以产生一个地图集的疼痛超， 和低敏感小鼠系，以及功能性鉴定新的疼痛治疗靶点。