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 外周听觉功能障碍的临床测试集中在听力图上。然而，许多听觉感知 缺陷，如耳鸣，听觉过敏，和言语知觉困难，不能完全解释的， 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的丧失）， 可能会导致这些感知问题。然而，目前还没有诊断方法 在活人身上的感觉缺失这使我们无法确定人类中传入神经阻滞的患病率， 识别传入神经阻滞的风险因素和知觉后果，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）的丧失敏感。 在动物模型中，包括听觉脑干反应（ABR）， 中耳反射（MEMR）。然而，尚不清楚耳蜗增益损失（例如， 由于外毛细胞损伤）影响传入神经阻滞和这些生理 措施，阻碍翻译为一个诊断测试的传入神经阻滞。本建议的总体目标是 开发一个计算模型，可以估计来自非侵入性生理的传入神经阻滞， 在具有不同程度的耳蜗增益损失的人类中的测量。核心假设是耳蜗 增益损失可以从失真产物耳声发射（DPOAE）中预测，并且传入神经阻滞可以通过 根据ABR、EFR和MEMR测量的组合预测。这一假设将由以下人员进行检验： 追求四个具体目标：1）扩展听觉外周（CMAP）的计算模型以预测ABR， 基于耳蜗增益和传入功能的小鼠和人类EFR、MEMR和DPOAE反应，2） 通过收集小鼠的生理和组织学数据，对CMAP进行了验证和改进， 通过使用以下方法拟合CMAP，从生理测量中获得个体人类受试者的传入阻滞 贝叶斯回归，以及4）评估传入神经阻滞预测与风险因素的关系，以及 预测了传入神经阻滞的感知后果。这种方法是创新的，因为它扩展了以前的工作 动物和人类模型与耳蜗增益损失和deafferentation，使用计算建模， 弥合模型系统之间的差距，并结合多种生理测量来预测 个体受试者的传入神经阻滞。这项研究意义重大，因为我们目前有 无法诊断出是否有传入神经阻滞因此，患病率，相关的风险因素和感知影响 这种情况还不清楚。该项目预计将导致个体的传入神经阻滞的生物标志物 这是基于患者的生理测量。这将使我们能够识别周边听觉 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， 暴露和听觉知觉缺陷，如言语知觉困难，它将允许发展 听觉感知缺陷的靶向治疗和损伤预防策略。