Decabromodiphenyl ethane as a neurotoxicant in Alzheimer’s disease: unraveling its mechanisms through the integration of multiple computational toxicology methods

The role of environmental pollutants as risk factors for Alzheimer's disease (AD) and related neurodegenerative pathologies necessitates mechanistic investigation. Evidence implicates brominated flame retardants (BFRs)-decabromodiphenyl ethane (DBDPE)-in AD pathogenesis, though their molecular mechanisms remain inadequately elucidated. To address this challenge, we combined multiple cross-disciplinary methods (network toxicology, machine learning [ML], molecular docking, molecular dynamics [MD] simulations, and Mendelian randomization [MR] analysis) to systematically delineate DBDPE-induced AD pathogenesis. Initial screening of the SwissTargetPrediction database and GSE132903 dataset identified 47 overlapping DBDPE-AD targets. Subsequent protein-protein interaction (PPI) network analysis refined these to 42 high-confidence targets. Subsequently, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses revealed association of core targets with metabolic pathways and neuroactive ligand-receptor interactions. Three core targets were prioritized using ML framework. Molecular docking confirmed strong binding affinities between DBDPE and the core targets. Given PLAU's exceptional binding energy, we conducted MD simulations to validate complex stability and characterize binding-site interactions. Finally, MR analysis established causal links between PLAU and AD susceptibility. In summary, this study establishes a comprehensive theoretical framework for understanding the molecular mechanisms of DBDPE-induced AD and provides valuable insights for developing preventive and therapeutic strategies targeting AD associated with DBDPE exposure.