Parkinson's disease (PD) is a progressive disease with decline in motor function and, over time, an accumulation of considerable non-motor symptoms that strongly contribute to disability and a diminished quality of life. Progression and phenotype of individual patients over the course of disease are unpredictable. Some patients become wheelchair bound, demented, severely depressed, and/or experience many other non- motor symptoms early while others are spared major disabilities until later.[4] Current treatments address symptoms and do not prevent disease progression; few address non-motor function. There is a notable knowledge gap regarding factors that contribute to or modify the phenotype/progression of PD. This is concerning as newly diagnosed patients most fear the cumulative loss of function and treatment trials in heterogeneous patient samples may fail. We aim to address this critical need by exploring contributions of environmental and genetic factor and how together they modify the complex progression phenotype in PD. We propose to study whether chemicals/pesticides, behavioral (e.g. physical activity, stress, social support, smoking and caffeine use,), medical (e.g. medications, head injuries, co-morbidities), and occupational factors together with genetic predispositions affect PD progression by leveraging the PEG study (NIEHS ES010544). This resource for Parkinson?s research, developed over 15 years, is unique in having assembled patients in a population-based manner -other US PD progression cohorts are greatly selected for biomarker discovery- with existing environmental and phenotypic data (motor and cognitive function, depressive and non-motor symptoms) at baseline early in disease for over 840 PD patients and ? soon ? GWAS data. We previously collected rich clinical data longitudinally for 248 PD patients. Here, we propose to follow 425 new patients to create a total cohort of 675. Specifically, in Aim 1, we will expand our progression cohort by following 425 PEG PD patients longitudinally for motor and non-motor progression; and collect additional environmental data and biologic samples. In Aim 2 and 3, we will explore environmental and genetic predictors of progression. For environmental predictors, we will analyze pesticides, behavioral, medical and occupational determinants of PD progression using marginal structural models and structural nested means models. We propose to identify genetic contributions in targeted (candidates from PD GWAS analyses, pathways such as inflammation, or neurodegenerative diseases such as synucleinopathies or Alzheimer) and untargeted (GWAS) approaches. We will conduct first gene-environment interaction analyses concentrating on common environmental factors and genes with common variants in relevant pathways (Sub-Aim1). Finally, we will engage in replication analyses with data from international collaborator who follow ~6000 PD patients for progression. New insights into PD progression may help facilitate more efficient treatment trials and lead to interventions that slow disease progression; possibly even during the extended pre-motor phase if biomarkers become available.