Metabolic profiles in gestational diabetes mellitus can reveal novel biomarkers for prediction of adverse neonatal outcomes.

Background: Gestational diabetes mellitus (GDM) significantly affects the fetal metabolic environment, elevating risks of neonatal hypoglycemia and macrosomia. Metabolomics offers promising avenues for early prediction and diagnosis of GDM and associated adverse offspring outcomes. Methods: This study analyzed serum samples from pregnant women diagnosed with GDM at 24 to 28 weeks of gestation using untargeted metabolomics. We monitored the health outcomes of their offspring to explore the correlation between initial serum metabolite profiles and subsequent health outcomes, to uncover the predictive markers for hypoglycemia and macrosomia in these offspring. Results: Out of 200 participants, 154 had normal newborns, 33 had offspring with hypoglycemia, and 19 had offspring with macrosomia. From 448 identified metabolites, 66 showed significant differences in cases of hypoglycemia, and 45 in macrosomia. A panel of serum metabolite biomarkers achieved Area Under the Curve (AUC) values of 0.8712 for predicting hypoglycemia and 0.9434 for macrosomia. Conclusion: The study delineated metabolic disruptions in GDM during 24-28 weeks of gestation and pinpointed biomarkers capable of forecasting adverse neonatal outcomes. These findings could inform GDM management strategies and minimize the incidence of such outcomes.

Influence of gestational diabetes mellitus on lipid signatures in breast milk and association with fetal physical development.

Gestational diabetes mellitus (GDM) commonly leads to adverse pregnancy outcomes and long-term metabolic complications in offspring. Breastfeeding has been shown to rewrite the fetal "metabolic programming" resulting from maternal diabetes and finally lead to a lower risk of future metabolic disease. Lipids in breast milk act like hormones to promote infant growth and development, but there is minimal information invested thus far in constitution changes of lipids in breast milk, especially in the context of GDM. In the present study, we performed a lipidomics analysis to compare the lipid composition in breast milk collected from women with or without GDM. We further revealed the correlations of dysregulated lipids in breast milk with maternal glucose and infant physical development. A total of 833 lipid species from 15 classes were identified, 60 of which were found to be significantly altered in response to the high glucose, suggesting a remarkable lipid profiling change in breast milk induced by GDM. Our results showed significant associations between dysregulated lipids (e.g., neutral lipids, phospholipids, sphingolipids) and maternal glucose. Furthermore, correction analysis demonstrated that GDM related lipids were also associated with indicators of infant physical development, including body weight, length, and head circumference. These findings may help to understand the protective effects of breastfeeding especially during GDM pregnancy.

Src family kinases involved in the differentiation of human preadipocytes.

BACKGROUND: Obesity is characterized by the excess accumulation of white adipose tissue (WAT). Src family kinases (SFKs) are non-receptor tyrosine kinases consisting of eight members (SRC, FYN, YES1, HCK, LCK, LYN, FGR and BLK) that have been studied extensively in mammalian cells. Although individual members in murine cells provide some clues that are associated with the regulation of adipogenesis, the specific role of this family in adipocyte differentiation has rarely been assessed, especially in human adipocytes. METHODS: Herein, we first explored the expression profiles of SFKs during human preadipocyte differentiation. Then, we used the pyrazolo-pyrimidinyl-amine compound PP1, a potent SFK inhibitor, to evaluate the function of SFKs during adipocyte differentiation. Furthermore, we adopted a loss-of-function strategy with siRNAs to determine the role of FGR in adipocyte differentiation. RESULTS: Here, we found that SRC, FYN, YES1, LYN and FGR were expressed in human preadipocytes and induced after the initiation of differentiation. Furthermore, the SFK inhibitor PP1 suppressed adipocyte differentiation. We also found that PP1 significantly suppressed the SFK activity in preadipocytes and decreased the expression of adipogenic genes in early and late differentiation. Given that FGR exhibited the most expression enhancement in mature adipocytes, we focused on FGR and found that its knockdown reduced lipid accumulation and adipogenic gene expression. CONCLUSIONS: Collectively, these findings suggest that SFKs, especially FGR, are involved in the differentiation of human preadipocytes. Our results lay a foundation for further understanding the role of SFKs in adipocyte differentiation and provide new clues for anti-obesity therapies.