Objective: This study aims to comprehensively explore the gene-environment interactions in PD using the large-scale UK Biobank dataset.

Background: Parkinson’s disease (PD) is a neurodegenerative disorder with a complex etiology, influenced by genetic and environmental risk factors.

Method: A total of 3,932 PD patients and 433,784 non-PD control participants were included. Using polygenic risk scores (PRS) for PD, logistic regression models were constructed to investigate the multiplicative and additive interactions between genetic susceptibility and 24 environmental risk factors of PD, including body mass index (BMI), physical activity, caffeine intake, tea consumption, tobacco exposure, alcohol consumption, agricultural exposure, medication history, and past medical history.

Results: In the interaction analysis, we observed statistically significant interactions between PRS and BMI (p = 0.002), a history of depression (p = 0.027), a history of hypertension (p < 0.001), a history of type 2 diabetes mellitus (T2DM) (p < 0.001), and a history of head injury (p = 0.003). Marginal effect plots indicated that, regardless of an individual’s genetic susceptibility, depression, hypertension, and head injury were positively correlated with PD risk, although the association weakened at higher PRS levels. The direction of the association between BMI and T2DM history with PD varied depending on the PRS level.

Conclusion: Our findings highlight the important role of genetic susceptibility in PD pathogenesis. Environmental risk factors can be classified as either genetic susceptibility-modifying or genetic-independent. These classifications provide a framework for personalized prevention strategies, aiding in PD risk factor analysis and early intervention.

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MDS Abstracts - https://www.mdsabstracts.org/abstract/comprehensive-large-scale-analysis-of-gene-environment-interactions-in-parkinsons-disease/