Bioinformatics Prediction and Experimental Validation of the Role of Macrophage Polarization and Ferroptosis in Gestational Diabetes Mellitus.

Purpose: Gestational diabetes mellitus (GDM) is a common metabolic disorder during pregnancy that is associated with placental inflammation and adverse pregnancy outcomes. However, the mechanisms of inflammation in GDM are still unclear.

Methods: Bulk transcriptome, single-cell transcriptome, clinical information, and samples were collected from GSE154414, GSE70493, GSE173193 and a retrospective cohort. Bioinformatics prediction was used to explore the mechanisms of placental inflammation, and multiplex immunofluorescence was used to validate the results.

Results: First, we found that GDM is characterized by low-grade inflammation and is linked to several adverse pregnancy outcomes, as supported by our collected clinical data. Additionally, we identified ten hub genes (, and ) as potential therapy targets and confirmed the binding of corresponding predictive therapeutic agents by molecular docking. Transcriptome sequencing analysis has shown that macrophages are primarily responsible for the emergence of placental inflammation, and that M1 macrophage polarization increased while M2 macrophage polarization decreased in GDM when compared to the control sample. Multiplex immunofluorescence staining of CD68, CD80, and ACSL4 was performed and suggested that ferroptosis of macrophages may contribute to placental inflammation in GDM.

Conclusion: In conclusion, our findings provide a better understanding of the mechanisms of inflammation in GDM and suggest potential therapeutic targets for this condition.