<p>Bisphenol A (BPA) exposure is associated with gestational diabetes mellitus (GDM); however, the underlying molecular mechanisms remain elusive. This study aimed to identify key genes mediating BPA exposure-related GDM through integrative bioinformatics analysis. We integrated BPA-related targets from multiple databases with GDM-associated genes derived from GeneCards and the GSE103552 dataset. Functional enrichment analysis was performed on the intersecting genes. A protein-protein interaction (PPI) network was constructed, and hub genes were identified using four topological algorithms. Machine learning approaches were employed for feature selection. Immune infiltration was assessed, and core gene expression was validated via reverse transcription quantitative polymerase chain reaction (RT-qPCR), additional GEO datasets, and single-cell RNA sequencing data. Thirty-four overlapping genes were identified and found to be enriched in the insulin signaling pathway, the AMPK pathway, and inflammatory responses. Following further screening, five core genes—HSPA8, NR3C1, ITGB1, NOTCH2, and POU5F1—were selected, demonstrating robust diagnostic performance. Immune analysis revealed significant correlations between hub genes and the infiltration levels of immune cells. Consistent expression patterns of ITGB1 and NOTCH2 were validated across additional GEO datasets. RT-qPCR confirmed the downregulation of HSPA8 and the upregulation of NR3C1 and NOTCH2 in GDM. Single-cell analysis corroborated cell-type-specific expression within the placenta. This study elucidates potential molecular links between BPA exposure and GDM, highlighting immune-metabolic dysregulation. The identified core genes may serve as biomarkers or therapeutic targets, thereby advancing precision environmental health strategies for pregnancy.</p>

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Integrative Multi-Omics Analysis Identifies Key Molecular Targets Linking Bisphenol A Exposure to Gestational Diabetes Mellitus

  • Lu Zheng,
  • Xinying Song,
  • Huiyan Wang,
  • Wenbo Zhou

摘要

Bisphenol A (BPA) exposure is associated with gestational diabetes mellitus (GDM); however, the underlying molecular mechanisms remain elusive. This study aimed to identify key genes mediating BPA exposure-related GDM through integrative bioinformatics analysis. We integrated BPA-related targets from multiple databases with GDM-associated genes derived from GeneCards and the GSE103552 dataset. Functional enrichment analysis was performed on the intersecting genes. A protein-protein interaction (PPI) network was constructed, and hub genes were identified using four topological algorithms. Machine learning approaches were employed for feature selection. Immune infiltration was assessed, and core gene expression was validated via reverse transcription quantitative polymerase chain reaction (RT-qPCR), additional GEO datasets, and single-cell RNA sequencing data. Thirty-four overlapping genes were identified and found to be enriched in the insulin signaling pathway, the AMPK pathway, and inflammatory responses. Following further screening, five core genes—HSPA8, NR3C1, ITGB1, NOTCH2, and POU5F1—were selected, demonstrating robust diagnostic performance. Immune analysis revealed significant correlations between hub genes and the infiltration levels of immune cells. Consistent expression patterns of ITGB1 and NOTCH2 were validated across additional GEO datasets. RT-qPCR confirmed the downregulation of HSPA8 and the upregulation of NR3C1 and NOTCH2 in GDM. Single-cell analysis corroborated cell-type-specific expression within the placenta. This study elucidates potential molecular links between BPA exposure and GDM, highlighting immune-metabolic dysregulation. The identified core genes may serve as biomarkers or therapeutic targets, thereby advancing precision environmental health strategies for pregnancy.