Agricultural Copper Pesticide Exposure and Metabolic Profiles among Parkinson's Disease Cases and Community Controls in California.

Copper-based pesticide exposures have been linked to increased Parkinson's disease (PD) risk through oxidative stress, mitochondrial dysfunction, and neuroinflammation, yet their metabolic effects in PD remain poorly understood. Using high-resolution metabolomics (HRM) data from 642 PD patients and 277 controls from the Parkinson's Environment and Gene (PEG) study, we evaluated alterations associated with chronic copper pesticide exposure. Composite and individual copper pesticide estimates were derived within a 500-m buffer around residential and workplace addresses over 5 years prior to the blood draw. Metabolome-wide association studies (MWAS) using partial least-squares (PLS) and empirical Bayes linear models were conducted to identify copper-associated metabolites, and pathway enrichment was performed using the Mummichog algorithm with 100 permutations to identify enriched metabolic pathways. In the primary analysis of the composite copper metric, we detected 215 copper-associated metabolite features, 88 of which were annotated, while none of them survived the FDR < 0.05 threshold. In individual-pesticide analyses, only copper sulfate (pentahydrate) yielded significant results: 57 metabolite features passed the FDR < 0.05 threshold (51 in PD patients, 4 in controls, and 2 in the full sample). The strongest metabolite association was with a phosphatidylcholine, PC(22:2(13Z,16Z)/16:1(9Z)) (β = 0.07, p = 1.51 × 10-05). Pathway enrichment supported involvement of inflammation metabolism, lipid metabolism, amino acid metabolism, etc. These findings suggest that chronic copper pesticide exposure is linked to serum metabolic changes, particularly in inflammation-related metabolism pathways. Given the cross-sectional study design, these associations should be interpreted cautiously, as they do not establish causality.