Cochlear synaptopathy and audiometric measures from human temporal-bone cases of sensorineural hearing loss

人类感音神经性听力损失颞骨病例的耳蜗突触病和听力测量

基本信息

批准号：
10641760
负责人：
M. Charles Liberman
金额：
$ 57.52万
依托单位：
MASSACHUSETTS EYE AND EAR INFIRMARY
依托单位国家：
美国
项目类别：
财政年份：
2017
资助国家：
美国
起止时间：
2017-08-02 至 2027-07-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10641760
关键词：
Acceleration Acoustic Nerve Acquired Deafness Age Aminoglycosides Animal Model Antibiotics Archives Atrophic Audiology Auditory Threshold Autopsy Axon Big Data Biopsy Case Study Cells Cisplatin Clinical Clinical Trials Cochlea Cochlear Implants Collection Complex Data Databases Derivation procedure Diagnosis Ear Etiology Evaluation Eye Formulation Foundations Generations Grant Hair Cells Hearing Tests Histologic Human Hyperacusis Image Inner Hair Cells K ATPase Labyrinth Left Literature Location Machine Learning Measures Meniere&apos s Disease Microscopic Modeling Nerve Degeneration Nerve Fibers Nerve Regeneration Neurons Pathology Patients Pattern Peripheral Platinum Presbycusis Prevalence Publishing Recording of previous events Records Resolution Retrospective Studies Risk Factors Role Sampling Sensorineural Hearing Loss Sensory Specimen Speech Speech Discrimination Speed Statistical Models Stimulus Subjects Selections Synapses Temporal bone structure Testing Therapeutic Tinnitus Toxic effect Typology Work age related animal data cell injury cell type chemotherapy clinical imaging cochlear synaptopathy data acquisition deafness ganglion cell hearing impairment inclusion criteria insight neural noise exposure normal aging novel ototoxicity public health relevance rat Pres protein repaired sex spiral ganglion tissue resource

项目摘要

Project 2 Summary - Abstract Since the inner ear cannot be biopsied, and clinical imaging cannot produce cellular-level resolution, the only way to uncover the functionally important structural changes underlying sensorineural hearing loss is the microscopic examination of post-mortem human temporal bones. This P50 Center focuses on primary neural degeneration in the inner ear (i.e. the loss of synaptic connections between surviving sensory cells and auditory nerve cells), and its hypothesized role in limiting the ability to understand complex stimuli like speech and as a key elicitor of tinnitus and hyperacusis. Over the past 5 years, Project 2 showed, as predicted from animal models, that the rate of auditory nerve loss in normal-aging human ears out-paced the rate of hair cell loss by 2:1, and that this neural loss was further accelerated in those with a history of noise exposure. A rigorous statistical model showed that while the audiometric thresholds were well predicted by the patterns of hair cell loss, the neural loss did not affect threshold but contributed to the differences in word identification abilities among those with similar audiograms. Over the next 5 years, Project 2 builds on this foundation to explore a wider range of acquired hearing loss etiologies, i.e. ototoxic antibiotics and chemotherapeutics, sudden sensorineural hearing loss and Ménière’s disease. We choose this because they are common, well represented in our temporal bone archives, and are often associated with tinnitus and difficulties in speech discrimination. We are developing machine-learning approaches to automate the acquisition of quantitative histopathological data, because we aim to grow the number of cases analyzed as rapidly as possible. As we have now entered the era of clinical trials for deafness therapeutics, there is a critical need for robust statistical models to accurately predict the degree and pattern of cellular loss from the audiogram, word score, hearing loss etiology, age and sex of a candidate patient.

项目 2 摘要 - 摘要由于内耳无法进行活检，临床成像无法产生细胞水平分辨率，揭示潜在的功能上重要的结构变化的唯一方法感音神经性听力损失是对死后人类颞叶的显微镜检查该 P50 中心专注于内耳的原发性神经变性（即丧失听力）。幸存的感觉细胞和听觉神经细胞之间的突触连接）及其在限制理解复杂刺激（如言语）的能力方面发挥了重要作用，并将其作为关键耳鸣和听觉过敏的诱发因素。在过去 5 年里，项目 2 显示，正如动物模型预测的那样，正常衰老的人耳中听神经损失的速度比毛细胞损失的速度快 2:1，并且对于那些有噪音暴露史的人来说，这种神经损失会进一步加速。统计模型表明，虽然听力阈值可以很好地预测毛细胞损失的模式，神经损失不会影响阈值，但会导致具有相似听力图的人之间的单词识别能力存在差异。未来 5 年，项目 2 在此基础上探索更广泛的领域获得性听力损失的病因，即耳毒性抗生素和化疗药物、突发性听力损失我们选择这个是因为它们很常见，在我们的颞骨档案中得到了很好的体现，并且通常与耳鸣和我们正在开发机器学习方法来解决语音歧视问题。自动获取定量组织病理学数据，因为我们的目标是增长由于我们现在已经进入临床时代，因此需要尽快分析病例数。耳聋治疗试验中，迫切需要稳健的统计模型来准确地从听力图、单词评分、听力损失预测细胞损失的程度和模式候选患者的病因、年龄和性别。