Mouse, Man, and Machine: Combining Model Systems to Develop a Biomarker for Cochlear Deafferentation in Humans (Administrative Supplement)

小鼠、人和机器：结合模型系统开发人类耳蜗传入神经阻滞的生物标志物（行政补充）

• 批准号: 10681110
• 负责人: Naomi Bramhall
• 金额: $ 1.48万
• 依托单位: OREGON HEALTH & SCIENCE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-07-15 至 2023-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10681110
• 关键词: Administrative Supplement; Affect; Aging; Animal Model; Auditory; Auditory Brainstem Responses; Biological Markers; Biological Models; Cochlea; Computer Models; Data; Deafferentation procedure; Development; Diagnosis; Diagnostic tests; Hearing Tests; Hearing problem; Histologic; Human; Hyperacusis; Individual; Inner Hair Cells; Knowledge; Lead; Measurement; Measures; Methods; Mission; Mus; Outer Hair Cells; Peripheral; Persons; Pharmacotherapy; Physiological; Prevalence; Prevention; Public Health; Reflex action; Research; Risk Factors; Speech Perception; Synapses; Testing; Tinnitus; Translations; United States National Institutes of Health; Work; base; cell injury; disability; ear muscle; ganglion cell; human model; human subject; individual patient; innovation; man; middle ear; noise exposure; otoacoustic emission; prevent; research clinical testing; response; spiral ganglion

Project Summary Clinical testing for peripheral auditory dysfunction focuses on the audiogram. However, many auditory perceptual deficits, such as tinnitus, hyperacusis, and difficulty with speech perception, cannot be fully explained by the audiogram. Cochlear deafferentation (i.e., loss of inner hair cells, spiral ganglion cells, or cochlear synapses), may contribute to these perceptual problems. However, there is currently no method for diagnosing deafferentation in living humans. This prevents us from determining the prevalence of deafferentation in humans, identifying deafferentation risk factors and perceptual consequences, or testing potential drug treatments. Several non-invasive physiological measures are sensitive to loss of cochlear synapses (a form of deafferentation) in animal models, including the auditory brainstem response (ABR), the envelope following response (EFR), and the middle ear muscle reflex (MEMR). However, it is unclear how cochlear gain loss (e.g., due to outer hair cell damage) impacts the relationship between deafferentation and these physiological measures, hindering translation to a diagnostic test for deafferentation. The overall objective of this proposal is to develop a computational model that can estimate deafferentation from non-invasive physiological measurements in humans with varying degrees of cochlear gain loss. The central hypothesis is that cochlear gain loss can be predicted from distortion product otoacoustic emissions (DPOAEs) and deafferentation can be predicted from a combination of ABR, EFR, and MEMR measurements. This hypothesis will be tested by pursuing four specific aims: 1) Expand a computational model of the auditory periphery (CMAP) to predict ABR, EFR, MEMR, and DPOAE responses in mice and humans based on both cochlear gain and afferent function, 2) Validate and refine the CMAP by collecting physiological and histological data from mouse, 3) Predict deafferentation in individual human subjects from physiological measurements by fitting the CMAP using Bayesian regression, and 4) Evaluate deafferentation predictions for their relationship with risk factors and predicted perceptual consequences of deafferentation. This approach is innovative because it extends prior work to animal and human models with both cochlear gain loss and deafferentation, uses computational modeling to bridge the gap between model systems, and combines multiple physiological measurements to predict deafferentation in individual human subjects. The proposed research is significant because we currently have no means of diagnosing deafferentation. Thus, the prevalence, associated risk factors, and perceptual impacts of this condition are unclear. This project is expected to result in a biomarker of deafferentation for individual patients that is based on their physiological measurements. This will enable us to identify peripheral auditory damage that is independent of cochlear gain loss. If the biomarker is correlated with risk factors such as noise exposure and auditory perceptual deficits such as speech perception difficulty, it will allow for the development of targeted treatments for auditory perceptual deficits and strategies for damage prevention.

项目概要 周围听觉功能障碍的临床测试重点是听力图。然而，许多听觉感知 诸如耳鸣、听觉过敏和言语感知困难等缺陷不能完全用 听力图。耳蜗传入神经阻滞（即内毛细胞、螺旋神经节细胞或耳蜗突触丧失）， 可能会导致这些知觉问题。但目前尚无诊断方法 活人的传入神经阻滞。这使我们无法确定人类传入神经阻滞的患病率， 识别传入神经阻滞的风险因素和感知后果，或测试潜在的药物治疗。 几种非侵入性生理测量对耳蜗突触（耳蜗突触的一种形式）的丧失很敏感。 动物模型中的传入神经阻滞），包括听觉脑干反应（ABR），包络跟随 反应（EFR）和中耳肌肉反射（MEMR）。然而，目前尚不清楚耳蜗增益如何损失（例如， 由于外毛细胞损伤）影响传入神经阻滞和这些生理学之间的关系 措施，阻碍转化为传入神经阻滞的诊断测试。该提案的总体目标是 开发一种计算模型，可以估计非侵入性生理传入传入神经阻滞 对具有不同程度耳蜗增益损失的人类进行测量。中心假设是耳蜗 增益损失可以通过失真产物耳声发射 (DPOAE) 进行预测，并且传入传入神经阻滞可以通过 根据 ABR、EFR 和 MEMR 测量值的组合进行预测。这个假设将被检验 追求四个具体目标：1）扩展听觉外围（CMAP）的计算模型来预测 ABR， 小鼠和人类基于耳蜗增益和传入功能的 EFR、MEMR 和 DPOAE 反应，2) 通过收集小鼠的生理和组织学数据来验证和完善 CMAP，3) 预测 通过使用 CMAP 拟合，从生理测量中得出个体人类受试者的传入阻滞 贝叶斯回归，以及 4) 评估传入阻滞预测与风险因素的关系，以及 预测传入神经阻滞的知觉后果。这种方法是创新的，因为它扩展了之前的工作 对于具有耳蜗增益损失和传入神经阻滞的动物和人类模型，使用计算模型 弥合模型系统之间的差距，并结合多种生理测量来预测 个别人类受试者的传入神经阻滞。拟议的研究意义重大，因为我们目前有 没有方法诊断传入神经阻滞。因此，患病率、相关风险因素和感知影响 这种情况的情况尚不清楚。该项目预计将产生个人传入神经阻滞的生物标志物 患者是基于他们的生理测量。这将使我们能够识别外周听觉 与耳蜗增益损失无关的损伤。如果生物标志物与噪音等风险因素相关 暴露和听觉感知缺陷，例如言语感知困难，这将有助于发展 听觉感知缺陷的针对性治疗和损害预防策略。