Neonatal amygdala microstructure mediates the relationship between gestational glycemia and offspring adiposity

Mutual effects of gestational diabetes and schizophrenia: how can one promote the other?: A review

Although the physical complications of gestational diabetes mellitus (GDM) are well known, emerging evidence suggests a significant link with psychiatric conditions such as schizophrenia (SCZ). This review aimed to explore the extent, nature, and implications of the association between GDM and SCZ, exploring how the 2 conditions may reciprocally influence each other. We conducted a comprehensive literature review and, analyzed clinical and mechanistic evidence supporting the mutual effects of GDM and SCZ. This review examined factors such as neurodevelopment and the impact of antipsychotics. The study found that Maternal GDM increases the risk of SCZ in offspring. Conversely, women with SCZ were more prone to hyperglycemic pregnancies. The research highlights significant regional variations in GDM prevalence, with the highest rate in the Middle East, North Africa, and South-East Asia regions. These regional variations may have an impact on the epidemiology of SCZ. Furthermore, this review identifies the potential biological and environmental mechanisms underlying these associations. There is a bidirectional relationship between GDM and SCZ, with each disorder potentially exacerbating the others. This relationship has significant implications for maternal and offspring health, particularly in regions with high GDM prevalence. These findings underline the need for integrated care approaches for women with SCZ during pregnancy and the importance of monitoring and managing GDM to mitigate the risk of SCZ in the offspring. Notably, this study recognizes the need for further research to fully understand these complex interactions and their implications for healthcare.

Abnormal neonatal brain microstructure in gestational diabetes mellitus revealed by MRI texture analysis

To investigate the value of MRI texture analysis in evaluating the effect of gestational diabetes mellitus (GDM) on neonatal brain microstructure development, we retrospectively collected images of neonates undergoing head MRI scans, including a GDM group (N1 = 37) and a healthy control group (N2 = 34). MaZda texture analysis software was used to extract the texture features from different sequence images and perform dimensionality reduction, and then the texture features selected by the lowest misjudgement rate method were imported into SPSS software for statistical analysis. In our study, we found that GDM affects the development of the microstructure of the neonatal brain, and different combinations of texture features have different recognition performances, such as different sequences and different brain regions. As a consequence, texture analysis combining multiple conventional MRI sequences has a high recognition performance in revealing the abnormal development of the brain microstructure of neonates born of mothers with GDM.