Association between urinary polycyclic aromatic hydrocarbon metabolites and sleep disturbances: A cross-sectional study integrating machine learning and network toxicology

Abstract

Objective: Although humans are widely exposed to polycyclic aromatic hydrocarbons, current evidence on the association between urinary polycyclic aromatic hydrocarbon metabolites and sleeping troubles remains limited. Herein, we aimed to investigate the effects of urinary polycyclic aromatic hydrocarbon metabolites on sleep-related issues. Methods: This retrospective cross-sectional study analyzed data from 3262 adults (≥20 years) enrolled in the National Health and Nutrition Examination Survey cycles (2005–2006, 2007–2008, and 2011–2012). The association between urinary polycyclic aromatic hydrocarbon metabolites and sleeping troubles was assessed using 11 distinct machine learning algorithms. Subsequently, network toxicology was conducted to identify critical protein targets, which were subsequently validated through molecular docking analyses. Results: Both the Random Forest and CatBoost algorithms exhibited superior performance, identifying four key pollutants: 1-hydroxypyrene, 2-hydroxyfluorene, 3-hydroxyfluorene, and 3-hydroxyphenanthrene. Molecular docking analysis further revealed that the critical targets through which polycyclic aromatic hydrocarbons influence sleep include androgen receptor, B-cell lymphoma, nuclear receptor subfamily 3 group C member 1, and transient receptor potential vanilloid 1. Conclusions: Our findings revealed an association between environmentally relevant polycyclic aromatic hydrocarbon metabolites and sleep disturbances. We also explored the underlying mechanisms using network toxicology. Our findings provide a foundation for in vivo validation in preclinical animal models and the development of sleep interventions targeting polycyclic aromatic hydrocarbons.