Plasma Metabolomics Profiles in Prodromal and Clinical Parkinson's Disease.

Abstract

BACKGROUND The long prodromal phase of Parkinson's disease (PD) and the link the disease has with metabolic factors suggest that metabolomics could help identify affected individuals at early stages. OBJECTIVE The goal was to examine whether plasma metabolomic profiles could identify individuals in the prodromal and clinical phase of PD. METHODS We quantified and compared the plasma metabolomic profiles of 922 individuals with PD who provided blood samples at a median of 11 years before (n = 809) or 2 years after (n = 113) disease diagnosis to that of matched controls, all selected from three established cohort studies (Nurses' Health Study, Health Professionals Follow-up Study, and Cancer Prevention Study II). We used conditional logistic regression models and machine learning techniques to identify metabolites predicting prodromal and clinically manifest PD. RESULTS Several metabolites, especially amino acids, acyl-carnitines, and other lipids were nominally associated with PD since the years leading to disease diagnosis. Metabolites proposed as biomarkers of foods or care products tended to be associated with a higher PD risk closer to disease diagnosis. Metabolites reflecting higher intake of coffee, smoking, and acetaminophen tended to be associated with a lower PD risk over the course of the disease. Metabolomic profiles in prodromal samples were unable to accurately predict future clinical PD. CONCLUSIONS Metabolic pathways related to the metabolism of amino acids and lipids may be involved in PD progression. Metabolomic differences may also result from behavioral changes and medical management, emphasizing the need to consider prodromal and clinical data in future studies. © 2025 International Parkinson and Movement Disorder Society.