Addressing Gaps in Parkinson's Disease Etiology: The Need for a Polyexposure Score

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.

Authors

Institutions

Publication Details

Journal
Movement Disorders
Published
2026-02-17
DOI
https://doi.org/10.1002/mds.70231
Primary Topic
Health, Environment, Cognitive Aging
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Addressing Gaps in Parkinson's Disease Etiology: The Need for a Polyexposure Score

David J. Burn, Eva Schaeffer, Ron B. Postuma, Victor S. Fung et al.
Movement Disorders
Health, Environment, Cognitive Aging
article

Addressing Gaps in Parkinson's Disease Etiology: The Need for a Polyexposure Score

David J. Burn, Eva Schaeffer, Ron B. Postuma, Victor S. Fung, Daniela Berg, Alastair J. Noyce, Sebastian Heinzel, Njideka U. Okubadejo
article en

Abstract

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.

Movement Disorders
Montreal Neurological Institute and Hospital (CA), Queen Mary University of London (GB), Ollscoil na Gaillimhe – University of Galway (IE), University of Lagos (NG), Barts Health NHS Trust (GB), Sydney Hospital (AU), Westmead Hospital (AU), Christian-Albrechts-Universität zu Kiel (DE)
Openalex Percentile: Top 54%
Health, Environment, Cognitive Aging
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.