Njideka U. Okubadejo, Eva Schaeffer, Alastair J. Noyce, Sebastian Heinzel, David J. Burn, Victor S. Fung, Ron B. Postuma, Daniela Berg
Parkinson's disease (PD) risk and progression are influenced by a complex interplay of genetic, environmental, and internal factors. Environmental exposures have been understudied, primarily because of the associated complexity and inherent measurement challenges. The exposome framework, encompassing lifetime environmental exposures and biological responses, offers a way to better characterize these influences. The exposome embraces the "biography-to-biology" transition, encompassing general and specific external and internal exposures accumulating over the lifespan, and interacting with genetic factors. In other fields, machine learning has been applied to develop polyexposure scores to quantify cumulative environmental risks, although challenges remain in exposure measurement, latency, and disease heterogeneity. Advancing PD research requires refined exposome definitions, systematic data integration, validation, and collaboration to improve prediction, prevention, and personalized therapies. © 2026 International Parkinson and Movement Disorder Society.