Inter-neuronal variability in human nociceptor electrophysiology: experimentally-driven computational study of response to drugs and channelopathies

慢性疼痛影响着全世界数百万人，但目前缺乏有效的治疗方法。缓解慢性疼痛的新疗法的一个潜在目标是我们体内数百万专门的感觉神经元，称为伤害感受器，它们检测有害刺激并将此信息传递到大脑，在那里它可以被感知为疼痛。伤害感受器通常为我们提供保护性的疼痛感，帮助我们避免伤害。最近，患有慢性神经性疼痛（由于神经系统损伤引起的不必要的疼痛）和对疼痛完全不敏感的患者的疼痛状态与特定离子通道中的基因突变有关，这些离子通道最常见于伤害感受器中。这些离子通道是在神经细胞的外膜中发现的蛋白质，其打开和关闭以控制带电离子（如钠和钾）流入和流出细胞。每个伤害感受器都包含许多不同的离子通道，当我们遇到无害和有害的刺激时，通过这些通道的电流组合决定了它的反应。这些发现表明，有一些特定的离子通道在决定哪些刺激导致我们每个人经历疼痛方面发挥着至关重要的作用。关于这些离子通道突变如何影响疼痛信号的研究，以及通过靶向伤害感受器离子通道治疗慢性疼痛的新药的研究正在进行中。目前，这些研究使用来自动物，特别是大鼠和小鼠的伤害感受器。这是因为器官捐赠者捐赠给研究的人类伤害感受器非常稀少，我们对它们的数据也很有限。不幸的是，在动物和人类的伤害感受器和离子通道之间并没有完美的匹配。因此，使用动物模型的发现可能无法转化为人类生物学。伤害感受器本身也是高度多样的，因为它们被分为不同的亚型，对不同的刺激敏感，如热或冷，并显示个体之间的行为差异。为了解决这些问题，这个项目的目标是开发人类伤害感受器的计算机模型，这些模型代表了我们在伤害感受器亚型之间以及不同个体的伤害感受器之间看到的广泛的变异性。伤害感受器电活动的计算模型在数学上描述了人类伤害感受器中的不同离子通道如何打开和关闭，以及这如何影响伤害感受器的信号传导特性。这些模型中的方程太复杂，无法用手工求解，必须在计算机上求解。通常这些模型只描述伤害感受器的平均行为，但我们开发了一种方法来构建伤害感受器模型的群体，由数千个不同的模型组成，其中每个模型产生的行为都在实验中观察到的生物变异性范围内，但每个模型都有稍微不同的组成，例如在其膜中具有不同密度的每种类型的离子通道。因此，每个模型的行为不同，对药物的模拟应用或离子通道突变的插入的反应也不同。突变和其他因素，如神经损伤和炎症，可以使伤害感受器过度兴奋。这意味着它们可以发射更长时间的信号，或者以更低的阈值发射信号，导致不必要的、非保护性的疼痛。阻断特定离子通道的药物可以使这些伤害感受器恢复正常的兴奋性，但这种有效的治疗方法还有待开发。目前的研究结果表明，单独的药物可能不足以实现这一目标，药物组合可能更有效。我们将使用计算机模拟来筛选各种不同的药物组合，以预测哪些组合可以恢复暴露于炎症介质的伤害感受器的正常兴奋性，以及恢复与神经性疼痛发展相关的离子通道突变的伤害感受器的正常兴奋性。

Chronic pain affects millions of people worldwide, but currently lacks effective treatments. A potential target for new therapies to relieve chronic pain are the millions of specialised sensory neurons in our bodies, called nociceptors, that detect harmful stimuli and transmit this information to the brain, where it can be perceived as pain. Nociceptors normally provide us with a protective sense of pain that helps us to avoid harm. Recently, patients with chronic neuropathic pain (unwanted pain due to damage to the nervous system) and with complete insensitivity to pain have had their pain states linked to genetic mutations in specific ion channels that are found most commonly in nociceptors. These ion channels are proteins found in the outer membranes of nerve cells, that open and close to control the flow of electrically charged ions, such as sodium and potassium, into and out of the cell. Each nociceptor contains many different ion channels, and the combined flow of electrical current through these channels determines how it responds when we encounter both harmless and harmful stimuli. These findings have shown that there are particular ion channels that play a vital role in determining which stimuli cause each of us to experience pain. Studies into how these ion channel mutations affect pain signalling, and the search for new drugs that could treat chronic pain by targeting nociceptor ion channels are ongoing. Currently these studies use nociceptors from animals, particularly rats and mice. This is because human nociceptors, donated to research by organ donors, are scarce and we have limited data from them. Unfortunately there is not a perfect match between animal and human nociceptors and ion channels. Therefore findings made using animal models may not translate to human biology. Nociceptors themselves are also highly varied, as they are divided up into different sub-types, sensitive to different stimuli such as heat or cold, and show differences in behaviour between individuals. To address these problems, the goal of this project is to develop computer models of human nociceptors that are representative of the wide range of variability we see between nociceptor sub-types, and between nociceptors from different individuals. Computational models of nociceptor electrical activity mathematically describe how the different ion channels in a human nociceptor open and close, and how this affects the signalling properties of the nociceptor. The equations in these models are too complex to solve by hand, and must be solved on computers. Usually these models only describe the average behaviour of nociceptors, but instead we have developed a method to construct population of nociceptor models, consisting of thousands of different models, where every model produces behaviours that are within the range of biological variability observed in experiments, but where every model has a slightly different makeup, such as having different densities of each type of ion channel in its membrane. Therefore, each model behaves differently, and responds differently to simulated application of drugs or the insertion of an ion channel mutation.Mutations and other factors such as nerve injury and inflammation can make nociceptors hyper excitable. This means they can fire signals for longer, or at lower thresholds, leading to unwanted, non-protective pain. Drugs that block particular ion channels could return these nociceptors back to normal excitability, but effective therapies of this kind have yet to be developed. Current findings suggest individual drugs alone may not be sufficient to achieve this, and combinations of drugs might be more effective. We will use computer simulations to screen a wide range of different drug combinations to predict which combinations restore normal excitability to nociceptors exposed to inflammatory agents, and to nociceptors with ion channel mutations linked to the development of neuropathic pain.