Multiomics elucidation of triclosan-induced gestational diabetes mellitus: Identification of key targets and molecular mechanisms

Gestational diabetes mellitus (GDM) is an increasingly prevalent pregnancy complication with significant maternal-fetal health impacts. Triclosan (TCS), a ubiquitous environmental endocrine disruptor, has been epidemiologically linked to GDM risk, yet its molecular mechanisms remain poorly understood. We employed an integrated bioinformatics approach combining network toxicology, transcriptomics, and machine learning to identify potential molecular targets connecting TCS exposure with GDM. Common target genes were identified by intersecting TCS-related targets from multiple databases with GDM-associated genes, followed by core target screening through differential expression analysis of GDM placental tissue (GSE70493) and feature selection using machine learning algorithms. Target validation was conducted via immune cell infiltration analysis, single-cell expression profiling, Western blot and molecular docking. We identified 210 shared TCS-GDM target genes significantly enriched in metabolic, inflammatory, and hormonal pathways. Five core genes (CXCL12, FABP4, HSD11B1, SDHA, and PRKAG2) emerged as critical molecular links, validated through protein-level expression analysis. These targets demonstrated significant associations with diverse immune cell populations and exhibited pronounced expression alterations in GDM placentas with high collective diagnostic performance. Molecular docking confirmed favorable TCS binding affinities with all core target proteins. This study systematically revealed the potential molecular mechanisms underlying TCS influence on GDM through core targets regulating lipid metabolism, glucocorticoid signaling, energy homeostasis, and immune responses, providing new insights for understanding environmental endocrine disruptor health risks and offering potential biomarkers for early GDM diagnosis and intervention.