# Brain Drivers, Cognition, and Parkinson's Disease: A Psychometric Approach > **NIH NIH F31** · UNIVERSITY OF FLORIDA · 2024 · $19,678 ## Abstract PROJECT SUMMARY/ABSTRACT Parkinson’s disease (PD) is one of the fastest-growing neurodegenerative disorders in the United States, with cognitive decline being among its most debilitating non-motor symptoms. With disease progression, most individuals eventually develop dementia. However, the trajectory of cognitive decline varies between individuals—leading to a search for risk factors of impending decline. In 2019, Ryan and colleagues proposed a precision aging model and suggested that typical age-related cognitive decline was influenced by three broad categories of “brain drivers”: neuropathology (e.g., alpha-synuclein, tau), neuroinflammation (e.g., cytokines), and cerebrovascular dysfunction (e.g., white matter hyperintensities). Past research has consistently measured these brain driver factors in isolation, despite these factors all belonging to an interconnected, neurobiological system. Thus, the goal of the proposed study is to determine whether cognitive variation in PD is better explained by a combination of these neurobiological risk factors, relative to isolated factors. The central hypothesis is that each category of brain drivers (i.e., neuropathology, neuroinflammation, cerebrovascular dysfunction) will uniquely relate to cognitive performance (specifically executive function and memory), such that adding in each category will better explain changes in each cognitive domain. The proposed study will examine data from an existing, well-characterized cohort of individuals with idiopathic PD without dementia (N=112) to determine the association between brain driver factors and cognitive performance cross-sectionally and longitudinally (at a 2- year follow-up). To do so, brain driver relationships with cognition will be assessed in isolation (using correlations) and in combination (using hierarchical linear regressions, adding in factors from each brain driver category sequentially). Overall, this method shifts the focus towards a precision medicine approach—whereby examining multiple brain drivers may allow for greater understanding of individualized risk of cognitive decline in individuals with PD. Improving the assessment of cognitive risk could inform both clinical prognosis for patients with PD and allow for a more targeted selection of participants into experimental trials aiming to slow impending cognitive decline. The proposed training plan will provide the applicant with additional training experiences beyond that of her Ph.D. program. Specific training goals include (1) gaining expertise in the methodologies measuring neuroinflammatory and neuropathology biomarkers and their interpretation, (2) gaining proficiency with structural magnetic resonance imaging (acquisition, processing, and interpretation) to measure white matter hyperintensities (a metric of cerebrovascular dysfunction), (3) advancing statistical competencies and experimental rigor, and (4) professional and career skills development. The proposed project and traini... ## Key facts - **NIH application ID:** 10806970 - **Project number:** 5F31AG081047-02 - **Recipient organization:** UNIVERSITY OF FLORIDA - **Principal Investigator:** Lauren Kenney - **Activity code:** F31 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2024 - **Award amount:** $19,678 - **Award type:** 5 - **Project period:** 2023-05-16 → 2024-08-15 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10806970 ## Citation > US National Institutes of Health, RePORTER application 10806970, Brain Drivers, Cognition, and Parkinson's Disease: A Psychometric Approach (5F31AG081047-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10806970. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*