Identification and validation of PANX1 as an inflammasome-related biomarker in gestational diabetes mellitus: insights from machine learning and experimental approaches.

Gestational diabetes mellitus (GDM) is characterized by glucose intolerance during pregnancy, resulting from insulin resistance, and is associated with increased maternal and neonatal risks. Inflammasomes play a critical role in GDM pathophysiology by driving immune dysregulation and chronic inflammation. This study aimed to identify inflammasome-related genes, which may serve as potential diagnostic markers and contribute to GDM pathogenesis. RNA sequencing datasets from the GEO were merged and analysed to identify differentially expressed genes (DEGs). The key genes identified by LASSO logistic regression, random forest, Boruta, and SVM-RFE algorithms were superimposed with genes related to inflammasomes. In addition, the CIBERSORT algorithm was used to analyse the immune characteristics of GDM. The expression of inflammasome-related genes was validated in the clinical samples by qPCR and correlated with clinical parameters. PANX1 was identified as a key inflammasome-associated gene, with its diagnostic potential confirmed by ROC curve analysis with an AUC of 93.75%. CIBERSORT and correlation analyses confirmed a significant association between PANX1 expression and immune cell infiltration. qPCR validation using placental samples from GDM and control subjects revealed elevated PANX1 expression in GDM. Furthermore, a significant correlation was observed between PANX1 expression and levels of glucose, HbA1c, and HOMA-IR, suggesting that elevated PANX1 may be associated with metabolic dysregulation in GDM. This study highlights PANX1 as a novel diagnostic biomarker and a therapeutic target in GDM pathophysiology.