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
The proposed project is a Fit-for-Purpose Phase 2 study for developing a spoken language biomarker of cognitive impairment in Parkinson's disease. This research will advance the development of treatments for Parkinson's disease dementia by developing a clinical tool to support the accurate and early detection of cognitive impairment in Parkinson's disease. The proposed research will have a significant and immediate impact on the health of individuals with Parkinson's disease (and neurodegenerative diseases broadly) by advancing the characterization of non-motor diagnostic profiles in Parkinson's disease; by leveraging the sensitivity of spoken discourse for biomarker development; and by generating a rigorous , foundational, discourse dataset for developing automated analyses of biomarkers that monitor cognition in real world environments.
