Phase 2 Development of a Spoken Language Biomarker of Cognitive Impairment in Parkinson's Disease

项目总结/摘要 目前，对于40-80%的帕金森病（PD）患者， 患痴呆症的风险。难以在诊所外监测早期认知障碍，以及 伴随的治疗开始的延迟，是准确诊断和治疗的主要障碍。 开发PD认知障碍的干预措施。生物标志物是可以被识别的任何特征。 客观测量并指示致病过程和/或治疗反应。生物标志物可以采取 包括可观察到的行为的形式的数量。口语对早期认知变化很敏感， 痴呆症，使其成为合适的生物标志物靶标。然而，到目前为止，还没有研究利用口语的敏感性， 用于开发PD认知障碍生物标志物的论文。这项研究的长期目标是 为了提高早期和准确的诊断个人与PD发展为痴呆症的风险，使用 口语话语生物标志物。一旦生物标志物被系统地验证，计算方法可以 用于自动化生物标志物分析。那里 的 缺乏 认知 和 目的 阶段目标1将严格描述口语话语，认知， 129名健康成年人和PD患者（有和无认知障碍）的运动语言特征 使用话语生产的理论基础模型。使用我们试点中改进的方法 目标2将开发和评估最佳加权话语的分类准确性 分类功能目标2将产生一个单一的话语措施，由多个，最佳 加权个别措施。个人话语测量值可以“插入”到分类中 函数产生一个分数，当与截止值比较时，将确定话语样本是否 实现这一目标有两个主要障碍：1） 一个严格的，有说服力的，手工编码的PD口语数据集（有和没有 障碍）和2）缺乏已严格开发的口语话语生物标志物 在健康成年人和PD患者的一组特征明确的队列中进行了测试。使用适合- 生物标志物框架，拟议研究的目标是通过完成一个 2口语话语生物标志物研究。 是由一个有认知障碍的PD患者产生的。的 使用 临床基础， 发达 纵向 和 表型 发展中 建议的研究是创新的， 一个循证生物标志物框架，利用口头话语的敏感性， PD中认知障碍的生物标志物。所得生物标志物将进一步 在未来的3期研究中，生物标志物的预测准确性将在 数据集。立即，拟议的项目显着推进PD的研究和临床护理， 神经退行性疾病更广泛，通过：1）扩大我们对认知语言的理解 2）提供一个严格的，基础的，话语数据集， 自动分析生物标志物，监测真实的世界环境中的认知。 不

PROJECT SUMMARY/ABSTRACT Currently, there are limited dementia treatments for the 40-80% of individuals with Parkinson's disease (PD) at risk for developing dementia. Difficulties monitoring early cognitive impairments outside of the clinic, and concomitant delays in treatment initiation, are major barriers to both the accurate diagnosis of and the development of interventions for cognitive impairments in PD. A biomarker is any characteristic that can be measured objectively and indicates pathogenic processes and/or treatment responses. Biomarkers can take a number of forms including observable behaviors. Spoken discourse is sensitive to early cognitive changes in dementia, making it a suitable biomarker target. Yet, to date no study has leveraged the sensitivity of spoken discourse for developing a biomarker of cognitive impairment in PD. The long-term objective of this research is to improve the early and accurate diagnosis of individuals with PD at risk for developing dementia, using a spoken discourse biomarker. Once the biomarker is systematically validated, computational approaches can be used to automate the biomarker analysis. There the lack cognitive and Purpose Phase Aim 1 will rigorously characterize the spoken discourse, cognitive, and motor speech profiles of 129 healthy adults and individuals with PD (with and without cognitive impairment) using a theoretically-grounded model of discourse production. Using methods refined in our pilot studies, Aim 2 will develop and evaluate the classification accuracy of an optimally weighted discourse classification function. Aim 2 will yield a single discourse measure that is comprised of multiple, optimally weighted individual measures. Individual discourse measure values can be `plugged' into the classification function to yield a score, which when compared to a cut-off value, will determine whether the discourse sample are two major barriers toward achieving this objective: 1) of a rigorous, sufficiently-powered, hand-coded dataset of PD spoken discourse (with and without impairment) and 2) the absence of a spoken discourse biomarker that has been rigorously developed tested on a meticulously-characterized cohort of healthy adults and individuals with PD. Using the Fit-for- biomarker framework, the goal of the proposed research is to eliminate these barriers by completing a 2 spoken discourse biomarker study. was produced by a person with PD who has cognitive impairment. The use clinically-grounded, developed longitudinal and phenotypes developing proposed research is innovative in its of an evidence-informed biomarker framework to leverage the sensitivity of spoken discourse to develop a robust biomarker of cognitive impairmen in PD. The resultant biomarker will be further in a future Phase 3 study where the predictive accuracy of the biomarker will be tested in a dataset. Immediately, the proposed project significantly advances research and clinical care in PD, neurodegenerative disorders more broadly, by: 1) expanding our understanding of cognitive-linguistic across the spectrum of PD and 2) providing a rigorous, foundational, discourse dataset for automated analyses of biomarkers that monitor cognition in real world environments. t