Computational investigation of neuropathic changes in primary afferent excitabili

描述(申请人提供)：神经性疼痛由神经系统的损伤或功能障碍引起。它是无法估量的痛苦的来源，尽管基础研究取得了进展，但众所周知，它仍然很难治疗。初级传入神经元的异位峰电位通过驱动中枢敏感化和向中枢神经系统提供异常感觉输入，直接导致神经病理性疼痛。因此，研究人员花费了相当大的努力试图了解异位尖峰现象，事实上，现在已经知道哪些离子通道在不同的初级传入神经元中表达，以及这些通道在神经病变条件下是如何改变的。然而，离子通道表达或性质的变化并不总是对细胞的兴奋性产生直接的影响；例如，Nav1.7通道的一个单一突变已被证明对兴奋性具有相反的影响，这取决于细胞中存在的其他通道(Rush等人。2006；PNAS 103：8245-50)。这说明细胞兴奋性是一种依赖于膜电流之间复杂相互作用的紧急性质。因此，我们认为，成功开发新的止痛药需要一种专门处理和解释膜电流相互作用的复杂方式的方法。复杂的(即非线性的)相互作用意味着膜电流彼此竞争、合作或干扰。破译这些相互作用需要对疼痛研究来说是陌生的计算工具。我们建议从动力系统理论中引入工具，更重要的是，建立将这些工具与实验方法相结合的概念框架。我们将通过使用我们的综合方法来解释损伤诱导的神经元兴奋性(明显与神经病理性疼痛有关)的定性变化模式是如何由定量改变的膜电流之间的异常非线性相互作用产生的，从而证明我们的综合方法的有效性。我们的方法是一种多学科的方法，协同结合了计算机建模、数学分析和实验。自上而下的模型将被用来在最小的计算机模型中复制细胞兴奋性的变化，以便动态系统分析可以用来解释基于改变的非线性相互作用的兴奋性变化。在自上而下建模和分析所获得的理论知识的指导下，自下而上的建模将被用来识别哪些损伤诱导的特定膜电流的变化足以解释细胞的超兴奋性模式。此外，为了建立自上而下和自下而上模型预测的变化之间的因果联系，我们将在NAVE和神经损伤动物的真实神经元中进行动态钳制实验，以确定哪些分子(通道)变化是必要的，并且足以解释大直径背根节(DRG)神经元的超兴奋性。总之，我们对膜电流之间的非线性相互作用的关注是新颖的。我们提出的使用计算工具来研究这些相互作用的解决方案(到目前为止，疼痛研究中还没有计算工具)作为综合的多学科方法的一部分，同样具有创新性和潜在的变革性。 公共卫生相关性：神经性疼痛是无法估量的痛苦的来源，仍然是出了名的难以治疗。考虑到它的流行率约为每15人中就有一人，以及它给照顾者和医疗系统带来的负担，总成本是巨大的。开发对神经性疼痛更有效的新镇痛剂的困难突显了对基础研究的新的创新路线的需要，例如计算建模和动态分析，这些研究将促进对现有数据的解释，并最终导致临床翻译。

DESCRIPTION (provided by applicant): Neuropathic pain results from damage to or dysfunction of the nervous system. It is a source of incalculable suffering and remains notoriously difficult to treat despite advances in basic research. Ectopic spiking in primary afferents contributes directly to neuropathic pain by driving central sensitization and by providing abnormal sensory input to the CNS. Accordingly, researchers have spent considerable effort trying to understand ectopic spiking, and indeed, much is now known about which ion channels are expressed in different primary afferents and how those channels are altered under neuropathic conditions. However, changes in ion channel expression or properties do not always have straightforward effects on cellular excitability; for example, a single mutation in Nav1.7 channels has been shown to have opposite effects on excitability depending on the other channels present in the cell (Rush et al. 2006; PNAS 103: 8245-50). This illustrates that cellular excitability is an emergent property that depends on the complex interaction between membrane currents. We argue, therefore, that successful development of new analgesics requires an approach that specifically addresses and accounts for the complex ways in which membrane currents interact. Complex (i.e. nonlinear) inter- actions imply that membrane currents compete, cooperate, or interfere with one another. Deciphering those inter- actions requires computational tools that are foreign to pain research. We propose to import tools from dynamical systems theory and, more importantly, to establish the conceptual framework by which to integrate those tools with experimental approaches. We will demonstrate the utility of our integrated approach by using it to explain how patterns of qualitative, injury-induced changes in neuronal excitability (that are clearly linked with neuropathic pain) arise from aberrant nonlinear interactions between quantitatively altered membrane currents. Our approach is a multidisciplinary one that synergistically combines computer modeling, mathematical analysis, and experiments. Top-down modeling will be used to replicate cellular excitability changes in minimal computer models so that dynamical systems analysis can be used to explain excitability changes on the basis of altered nonlinear interactions. Guided by the theoretical knowledge gained through top-down modeling and analysis, bottom-up modeling will be used to identify which injury-induced changes in specific membrane currents are sufficient to explain cellular hyperexcitability patterns. Furthermore, to establish causal links between the changes predicted by top-down and bottom-up modeling, we will conduct dynamic clamp experi- ments in real neurons from naove and nerve-injured animals to determine which molecular (channel) changes are necessary and sufficient to explain hyperexcitability in large diameter dorsal root ganglion (DRG) neurons. In summary, our focus on nonlinear interactions between membrane currents is novel. Our proposed solution for investigating those interactions using computational tools (which have heretofore been missing from pain research) as part of an integrative, multidisciplinary approach is equally innovative and potentially transformative. PUBLIC HEALTH RELEVANCE: Neuropathic pain is a source of incalculable suffering that remains notoriously difficult to treat. Given its prevalence of approximately one in 15 people and its burden on caregivers and the healthcare system, the total costs are enormous. The difficulty developing new analgesics with greater efficacy against neuropathic pain highlights the need for new and innovative lines of basic research, such as computational modeling and dynamical analysis, that will facilitate interpretation of existing data and, ultimately, lead to clinical translation.