54 Broad and shallow, deep and narrow, data track health’s causal arrow

Objectives/Goals: Broad and shallow data from large national cohorts provide generalizable real-world insights, while deep and narrow data from smaller cohorts capture detailed multimodal measures. This project integrates both approaches to study cognitive decline in Parkinson’s disease, which affects up to 50% of patients. Methods/Study Population: This longitudinal study includes validated digital biomarkers of motor, non-motor, sleep, and driving activity in 150 participants, plus novel social connectedness measures in 150 PD – partner dyads. PD and cognitive status are assessed annually; 4 weeks of continuous real-world behavior via actigraphy, social connectedness, and driving sensors are collected biannually. Anchor variables from pilot PD, PPMI, and LongROAD enable harmonization and cross-cohort modeling. Model development focuses on generative time series models that can capture the joint distribution of multimodal time series data for predicting values for future time steps. Together combined with genetics, plasma, and neuroimaging, they enable digital twins to predict decline and identify modifiable risks. Results/Anticipated Results: This project is designed to make impactful contributions to scientific knowledge, technical capability, clinical practice, and healthcare equity. Addressing key gaps in understanding PD cognitive decline, developing clinically validated digital biomarkers, and advancing data modeling for public health and precision medicine, including the creation of Digital Twin models. By integrating real-world data and social context into PD research, we will enhance clinical trials, improve patient outcomes, and provide clinicians with valuable tools, leading to a deeper understanding of PD and ADRDs. The data generated will be mined and shared with colleagues for years, driving new research and insights. Discussion/Significance of Impact: This project enhances monitoring and prediction of cognitive decline in PD, developing clinically valid, interpretable tools for real-world health. This generalizable platform unifies digital, imaging, and biomarker data as a model for translational research, advancing trial readiness across neurological and chronic diseases.