The Role of Slit-2 in Gestational Diabetes Mellitus and Its Effect on Pregnancy Outcome

The integrated bioinformatic analysis identifies immune microenvironment-related potential biomarkers for patients with gestational diabetes mellitus

Background

Gestational diabetes mellitus (GDM), a transient disease, may lead to short- or long-term adverse influences on maternal and fetal health. Therefore, its potential functions, mechanisms and related molecular biomarkers must be comprehended for the control, diagnosis and treatment of GDM.

Methods

The differentially expressed genes (DEGs) were identified using GSE49524 and GSE87295 associated with GDM from the Gene Expression Omnibus database, followed by function enrichment analysis, protein-protein interactions network construction, hub DEGs mining, diagnostic value evaluation and immune infiltration analysis. Finally, hub DEGs, the strongest related to immune infiltration, were screened as immune-related biomarkers.

Results

A hundred and seven DEGs were identified between patients with GDM and healthy individuals. Six hub genes with high diagnostic values, including ALDH1A1, BMP4, EFNB2, MME, PLAUR and SLIT2, were identified. Among these, two immune-related genes (PLAUR and SLIT2) with the highest absolute correlation coefficient were considered immune-related biomarkers in GDM.

Conclusion

Our study provides a comprehensive analysis of GDM, which would provide a foundation for the development of diagnosis and treatment of GDM.

Umbilical artery cord blood glucose predicted hypoglycemia in gestational diabetes mellitus and other at-risk newborns

BACKGROUND

To explore the value of umbilical artery cord blood glucose (UACBG) in predicting hypoglycemia in gestational diabetes mellitus (GDM) and other at-risk newborns, and to provide a cut-off UACBG value for predicting hypoglycemia occurrence.

METHODS

In this prospective study, we enrolled at-risk infants delivered vaginally, including neonates born to mothers with GDM, premature, macrosomic, and low birth weight. We separated the infants into GDM group and other at-risk group. All subjects underwent UACBG measurement during delivery. Neonatal peripheral blood glucose measurement was performed at 0.5 and 2 h after birth. The predictive performance of UACBG for neonatal hypoglycemia was assessed using receiver operating characteristic curve (ROC), area under curve (AUC), sensitivity, specificity, negative predictive value (NPV) and positive predictive value (PPV).

RESULTS

916 newborns were included, with 538 in GDM group and 378 in other at-risk group. 85 neonates were diagnosed hypoglycemia within 2 h after birth, including 36 belonging to GDM group and 49 to other at-risk group. For hypoglycemia prediction within 2 h, the best cut-off of UACBG was 4.150 mmol/L, yielding an AUC of 0.688 (95% CI 0.625-0.751) and a NPV of 0.933. In detail, the AUC was 0.680 in GDM group (95% CI 0.589-0.771), with the optimal cut-off of 4.150 mmol/L and a NPV of 0.950. In other at-risk group, the AUC was 0.678(95% CI 0.586-0.771), the best threshold was 3.950 mmol/L and the NPV was 0.908. No significant differences were observed between GDM group and other at-risk group in AUC at 0.5 h, 2 h and within 2 h.

CONCLUSIONS

UACBG has a high NPV for predicting neonatal hypoglycemia within 2 h after birth. It was implied that individuals with cord blood glucose levels above the threshold were at lower risk for hypoglycemia. UACBG monitoring provides evidence for subsequent classified management of hypoglycemia.

Elevated galectin-3 levels detected in women with hyperglycemia during early and mid-pregnancy antagonizes high glucose - induced trophoblast cells apoptosis via galectin-3/foxc1 pathway

OBJECTIVE

This study was to evaluate plasma galectin-3 levels from early pregnancy to delivery and explore the effects of galectin-3 on the function of trophoblast cells under high glucose exposure.

METHODS

The plasma galectin-3 levels were quantified by enzyme-linked immunosorbent assay (ELISA) in the China National Birth Cohort (CNBC) at Peking University First Hospital, and the underlying signaling pathway was identified by protein-protein interaction (PPI) analysis, gene set enrichment analysis (GSEA), quantitative PCR (qPCR), western blotting, small interfering RNA (siRNA) transfections, and flow cytometry.

RESULTS

Significantly higher galectin-3 levels were found in patients with gestational diabetes mellitus (GDM group; n = 77) during the first and second trimesters than that in healthy pregnant women (HP group; n = 113) (P < 0.05). No significant differences in plasma galectin-3 levels were detected between GDM and HP groups in maternal third-trimester blood and cord blood. PPI analysis suggested potential interactions between galectin-3 and foxc1. The findings of GSEA showed that galectin-3 was involved in the cytochrome P450-related and complement-related pathways, and foxc1 was associated with type I diabetes mellitus. Additionally, high glucose (25 mM) significantly increased the expression levels of galectin-3 and foxc1 and induced apoptosis in HTR-8/SVneo cells. Further in vitro experiments showed that galectin-3/foxc1 pathway could protect HTR-8/SVneo cells against high glucose - induced apoptosis.

CONCLUSION

Future studies were required to validate whether plasma galectin-3 might become a potential biomarker for hyperglycemia during pregnancy. Elevated galectin-3 levels might be a vital protective mechanism among those exposed to hyperglycemia during pregnancy.