Current diagnostic methods for Gestational Diabetes Mellitus (GDM) inadequately reflect early placental pathophysiology. Accelerated cellular senescence in trophoblasts has been reported as a pathological feature associated with the GDM placenta. However, the potential of senescence-related genes (SRGs) as candidate biomarkers or molecular indicators for GDM has not been systematically investigated. Placental transcriptomic data from GDM and control samples were obtained from the Gene Expression Omnibus (GEO) database, and differentially expressed senescence-related genes (DE-SRGs) were identified. A classification model was built using an integrative machine learning framework, and RT-qPCR validated model gene expression in placental tissues. In parallel, a prospective nested case-control study (30 GDM cases and 30 controls) was conducted, with peripheral blood collected in the first trimester, second trimester, and at delivery. Plasma Angiopoietin-like 4 (ANGPTL4) levels were measured by ELISA to determine the key gene for downstream investigation. Single-cell RNA sequencing (scRNA-seq) was then used to resolve the cellular expression patterns and cell-cell communication networks of the key gene. (Chinese Clinical Trial Registration No. ChiCTR2400091955; Registration Date: 2024-11-06). The classification model integrating ANGPTL4 and DST demonstrated favorable retrospective discriminatory performance (training set AUC = 0.95; validation set AUC = 0.87). This model served as a discovery tool rather than a clinical predictor. RT-qPCR indicated upregulation of ANGPTL4 in GDM placentas (P < 0.05), ANGPTL4 was significantly elevated in the first trimester of women who later developed GDM (P_adj = 0.038); this difference was no longer significant in the second trimester. Accordingly, ANGPTL4 was prioritized for further study, ANGPTL4 was predominantly expressed in extravillous trophoblasts (EVTs), where its expression positively correlated with cellular senescence. Cell communication analysis predicted potential ligand-receptor interactions between ANGPTL4 and ITGA5/ITGB1/SDC4 in EVTs. DE-SRGs in GDM placentas were highly enriched in lipid metabolism pathways, aligning with ANGPTL4's known function. Integrating machine learning with single-cell transcriptomics, we identified placental senescence-related gene candidates associated with GDM. ANGPTL4 is elevated in first‑trimester plasma and enriched in extravillous trophoblasts, where its expression correlates with lipid metabolism and cellular senescence signatures. These correlative findings generate testable hypotheses linking ANGPTL4‑mediated signaling to placental senescence. ANGPTL4 emerges as a candidate biomarker whose clinical potential warrants further evaluation in prospective cohorts.
