Underlying mechanisms of PPCPs on sleep disorders in the elderly: An integrated epidemiology and network toxicology study

This study aims to investigate the association between urinary exposure to emerging contaminants, pharmaceuticals and personal care products (PPCPs), and sleep disorders, while concurrently delineating the underlying mechanism. Levels of PPCPs were biomonitored in urine samples from 3,096 older adults. Logistic quantile regression, weighted quantile sum (WQS) regression, and bayesian kernel machine regression (BKMR) models were subsequently employed to investigate the associations between urinary PPCPs with detection rates ≥ 30% and sleep disorders. Potential targets linking PPCPs to sleep disorders were identified by screening databases such as PubChem, Swiss Target Prediction, PharmMapper, GeneCards, and OMIM. The STRING database, and Cytoscape software were used to identify the core targets that exhibited the most significant associations with sleep disorders. Functional enrichment analysis, specifically Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, was performed on these core targets using the DAVID database. Finally, molecular docking simulations were conducted using the CB-Dock2 platform to calculate binding energy, and promising complexes were further subjected to molecular dynamics simulations. After covariate adjustment, diethyltoluamide, sulfamonomethoxine, clindamycin, tetracycline, and azithromycin significantly weighted the overall mixture effect. Urinary coexposure to these five PPCPs was positively associated with sleep disorders and interacted with hub targets including caspase-3 (CASP3), akt serine/threonine kinase 1 (AKT1), peroxisome proliferator activated receptor gamma (PPARG), heat shock protein 90 alpha family class a member 1 (HSP90AA1) and heat shock protein 90 alpha family class b member 1 (HSP90AB1), thus influencing the progression of sleep disorders. • Biomonitoring + WQS + BKMR > traditional approaches for PPCP–sleep associations; • Network toxicology reveals multi-target mechanisms underlying PPCP-induced toxicity; • Integration of epidemiology and network toxicology provides mechanistic insights for PPCPs.