Exploratory Metabolomic and Lipidomic Profiling in a Manganese-Exposed Parkinsonism-Affected Population in Northern...

Chronic manganese (Mn) exposure is a recognized environmental contributor to Parkinsonian syndromes, including Mn-induced Parkinsonism (MnIP). This study aimed to evaluate whole-blood Mn levels and investigate disease/exposure-status-related alterations in metabolomic and lipidomic profiles.

A case-control study (N = 97) was conducted in Brescia, Italy, stratifying participants by Parkinsonism diagnosis and residential Mn exposure. Whole-blood Mn was quantified using ICP-MS. Untargeted metabolomic and lipidomic profiling was conducted using LC-MS. Statistical analyses included Mann-Whitney U tests, conditional logistic regression, ANCOVA, and pathway analysis.

Whole-blood Mn levels were significantly elevated in Parkinsonism cases vs. controls (median: 1.55 µg/dL [IQR: 0.75] vs. 1.02 µg/dL [IQR: 0.37]; p = 0.001), with Mn associated with increased odds of Parkinsonism (OR = 2.42, 95% CI: 1.13-5.17; p = 0.022). The disease effect metabolites included 3-sulfoxy-L-tyrosine (β = 1.12), formiminoglutamic acid (β = 0.99), and glyoxylic acid (β = 0.83); all FDR p < 0.001. The exposure effect was associated with elevated glycocholic acid (β = 0.51; FDR p = 0.006) and disrupted butanoate (Impact = 0.03; p = 0.004) and glutamate metabolism (p = 0.03). Additionally, SLC-mediated transmembrane transport was enriched (p = 0.003). The interaction effect identified palmitelaidic acid (β = 0.30; FDR p < 0.001), vitamin B6 metabolism (Impact = 0.08; p = 0.03), and glucose homeostasis pathways. In lipidomics, triacylglycerols and phosphatidylethanolamines were associated with the disease effect (e.g., TG(16:0_10:0_18:1), β = 0.79; FDR p < 0.01). Ferroptosis and endocannabinoid signaling were enriched in both disease and interaction effects, while sphingolipid metabolism was specific to the interaction effect.

Mn exposure and Parkinsonism are associated with distinct metabolic and lipidomic perturbations. These findings support the utility of omics in identifying environmentally linked Parkinsonism biomarkers and mechanisms.