Effects of mixed metal exposures on MRI diffusion features in the medial temporal lobe.

Abstract

Background: Environmental exposure to metal mixtures is common and may be associated with increased risk for neurodegenerative disorders including Alzheimer's disease.

Objective: This study examined associations of mixed metal exposures with medial temporal lobe (MTL) MRI structural metrics and neuropsychological performance.

Methods: Metal exposure history, whole blood metal, and neuropsychological tests were obtained from subjects with/without a history of mixed metal exposure from welding fumes (42 exposed subjects; 31 controls). MTL structures (hippocampus, entorhinal and parahippocampal cortices) were assessed by morphologic (volume, cortical thickness) and diffusion tensor imaging [mean (MD), axial (AD), radial diffusivity (RD), and fractional anisotropy (FA)] metrics. In exposed subjects, correlation, multiple linear, Bayesian kernel machine regression, and mediation analyses were employed to examine effects of single- or mixed-metal predictor(s) and their interactions on MTL structural and neuropsychological metrics; and on the path from metal exposure to neuropsychological consequences.

Results: Compared to controls, exposed subjects had higher blood Cu, Fe, K, Mn, Pb, Se, and Zn levels (p's<0.026) and poorer performance in processing/psychomotor speed, executive, and visuospatial domains (p's<0.046). Exposed subjects displayed higher MD, AD, and RD in all MTL ROIs (p's<0.040) and lower FA in entorhinal and parahippocampal cortices (p's<0.033), but not morphological differences. Long-term mixed-metal exposure history indirectly predicted lower processing speed performance via lower parahippocampal FA (p=0.023). Higher whole blood Mn and Cu predicted higher entorhinal diffusivity (p's<0.043) and lower Delayed Story Recall performance (p=0.007) without overall metal mixture or interaction effects.

Discussion: Mixed metal exposure predicted MTL structural and neuropsychological features that are similar to Alzheimer's disease at-risk populations. These data warrant follow-up as they may illuminate the path for environmental exposure to Alzheimer's disease-related health outcomes.