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.

项目摘要 外围听觉功能障碍的临床测试集中在听力图上。但是，许多听觉感知 缺陷，例如耳鸣，超声波和语音感知的困难，无法完全解释 听力图。人工耳蜗（即，内毛细胞，螺旋神经节细胞或耳蜗突触的丧失）， 可能会导致这些感知问题。但是，目前尚无诊断的方法 在活人中脱颖而出。这样可以防止我们确定人类剥夺的盛行率， 识别脱离危险因素和感知后果，或测试潜在的药物治疗。 几种非侵入性生理指标对人工耳蜗突触的丧失敏感（一种形式（一种形式） 在动物模型中，包括听觉的脑干响应（ABR），信封遵循的动物模型）。 反应（EFR）和中耳肌肉反射（MEMR）。但是，目前尚不清楚耳蜗增益损失如何（例如， 由于外毛细胞的损伤）会影响脱毛和这些生理的关系 措施，阻碍翻译为诊断测试的脱落测试。该提议的总体目标是 开发一个计算模型，该模型可以估计非侵入性生理学 人工收益损失程度不同的人类的测量。中心假设是人工耳蜗 可以通过失真产物的耳声发射（DPOAE）预测增益损失 通过ABR，EFR和MEMR测量的组合预测。该假设将通过 追求四个具体目标：1）扩展一个听觉外围（CMAP）的计算模型，以预测ABR， 基于耳蜗增益和传入功能，小鼠和人类的EFR，MEMR和DPOAE反应，2） 通过从小鼠那里收集生理和组织学数据来验证和完善CMAP，3）预测 通过使用使用CMAP拟合CMAP的人类受试者对个别人类受试者的脱俗 贝叶斯回归，4）评估其与风险因素和风险因素的关系 预测的脱落后果。这种方法具有创新性，因为它扩展了先前的工作 对于具有人工耳蜗增益损失和剥夺的动物和人类模型，使用计算建模来 弥合模型系统之间的差距，并结合多个生理测量以预测 在个别人类受试者中脱颖而出。拟议的研究很重要，因为我们目前有 无法诊断出脱落的手段。因此，患病率，相关的风险因素和感知影响 这种情况尚不清楚。预计该项目将导致个人剥离的生物标志物 基于其生理测量的患者。这将使我们能够识别外围听觉 与人工耳蜗损失无关的损害。如果生物标志物与噪声等风险因素相关 曝光和听觉感知缺陷，例如语音感知难度，它将允许发展 有针对性治疗的听觉感知缺陷和预防损害的策略。