2025/10/21 by Xiaotu Liu, Xinyu Zhu, Shuyue Wang +8 · 1 voice
Environmental Science · Biochemistry, Genetics and Molecular Biology · Medicine · #Health, Environment, Cognitive Aging #Metabolomics and Mass Spectrometry Studies #Nutritional Studies and Diet
paper · doi:10.1021/acs.est.5c07728
openalex created_date 2025/10/21 · openalex publication_date 2025/10/21 · openalex updated_date 2026/06/15
Urinary exposome analysis faces analytical challenges due to the lack of reference standards for biotransformed products and the wide structural diversity of metabolites. This study developed a chemically labeled exposome analysis (CLEAN) strategy for nontargeted identification of urinary metabolites. The strategy uses dansyl chloride (DnsCl) and N -methylphenylethylamine (MPEA) to label exogenous and endogenous molecules with phenolic hydroxyl, primary amine, and carboxyl groups and develops an integrated screening workflow based on diagnostic fragment ion filtering and machine learning-assisted retention time prediction and structure annotation. We applied the CLEAN strategy to screen for key environmental chemicals in pregnant women associated with small vulnerable newborns (SVN) in a nested case-control study of 80 SVN cases and 160 matched controls. Among 97 identified exogenous substances, 29 were detected in more than 70% samples. The BKMR analysis revealed a significant and positive association between mixed exposure and the SVN risk and identified 1-hydroxypyrene, monoisopropyl phthalate and pentabromophenol as the key exposure markers. Among the identified endogenous metabolites, four amino acids exhibited the strongest mediation effects on the environmental exposure–SVN associations. Collectively, our work demonstrates the ability of CLEAN to achieve high-throughput and accurate urinary exposome characterization, supporting large-scale human biomonitoring and epidemiological studies.