Fluctuation trend of inflammatory indices associated with gestational diabetes mellitus from second to third trimester of pregnancy | BMC Pregnancy and Birth

Although there is currently no foolproof way to prevent or cure gestational diabetes mellitus (GDM), the current approach focuses on reducing known risk factors [5] and maintaining tight control of blood sugar levels [6]. This study found that women with GDM had a higher body mass index (BMI) before pregnancy than women without GDM. Research shows that the incidence of GDM in Asian women is 13.78% with a pre-pregnancy BMI over 30, 10.22% with a BMI over 25, and 6.09% with a BMI over 20 [5]. In addition, gestational hypertension is considered a major risk factor for GDM. Previous research has shown that a key pathophysiological feature of gestational hypertension is increased oxidative stress, characterized by excessive production of reactive oxygen species (ROS). [7]. Recently, the role of placental oxidative stress in the pathology of GDM has gained attention, mainly due to mitochondrial fragmentation and damage caused by high blood glucose, which leads to an excessive oxidative stress response [8]. Therefore, pregnant women with gestational hypertension are more susceptible to developing GDM.

This study also examined the effects of GDM on perinatal infant weight and found that newborns in the GDM group were significantly heavier than those in the normal group. This could be directly related to the hyperglycemic intrauterine environment that fetuses of mothers with GDM experience. In a high glucose state, fetal growth can be accelerated, increasing the risk of macrosomia and potentially leading to preterm birth [9]. This highlights the importance of GDM management not only for the mother’s health but also for the health and development of the newborn.

In addition, the study examined the roles and interrelationships of IL-1Ra, NLRP3 and TBP-2 in GDM. IL-1Ra, an important regulator of the inflammatory response, has been identified as an important early diagnostic marker for type 2 diabetes mellitus (T2DM), along with other markers such as leptin and renin [10]. Importantly, IL-1Ra plays a critical role in balancing immune responses and controlling excessive inflammation [11] by inhibiting the IL-1-induced inflammatory process. Inflammation plays a leading role in the pathology of GDM. Our research found that IL-1Ra levels in pregnant women with GDM tend to increase during pregnancy but decrease after birth as disorders of glucose metabolism and inflammatory conditions subside. NLRP3, a cytoplasmic complex that regulates inflammation by activating caspase-1 and promoting the conversion of pro-IL-1β to mature IL-1β[12, 13]showed a downward trend during pregnancy, which may be related to the blocking effect of IL-1Ra and improvements in inflammatory responses through other mechanisms. Meanwhile, TBP-2, an important regulator of redox reactions, is involved in oxidative stress responses and interacts with NLRP3 [14, 15]. TBP-2 also showed a downward trend during pregnancy. At 36 weeks of gestation, the positive correlation between IL-1Ra, NLRP3 and TBP-2 demonstrates their interactive roles and pathways in inflammation. This interaction could involve the involvement of IL-1 in the NLRP3 activation process and a complex network in which IL-1β activity is regulated by IL-1Ra [16, 17]. While NLRP3, IL-1Ra, and TBP-2 each play distinct roles in regulating inflammation, their mutual influence highlights the role of a broader inflammatory response network in the initiation and development of GDM. Particularly in the late stages of pregnancy, the relationships between these markers could be influenced by physiological changes during pregnancy and changes in gene expression regulation, such that a positive correlation is present at 36 weeks.

This study particularly focused on the relationship between serum levels of NLRP3, IL-1Ra and TBP-2 at 24 weeks of gestation and neonatal weight. Correlation analysis revealed a positive correlation between increased NLRP3 and TBP-2 levels and higher neonatal weight, while an increase in IL-1Ra levels was inversely related to neonatal weight. Based on these findings, a regression equation was formulated: newborn weight = 3300.08 − 0.03 * IL-1Ra + 4.15 * NLRP3 + 0.05 * TBP-2. However, the explanatory power of this model (R²=0.062) suggests that it only accounts for 6.2% of the weight variation, which may be due to the small sample size of this study. Therefore, to improve the accuracy of neonatal weight prediction and the detection rate of macrosomia, future studies need to expand the sample size and further refine the linear regression analysis. This would not only allow a more detailed study of the associations between these biomarkers and newborn weight, but also provide greater support in the prevention and treatment of GDM and its associated complications.

In this study, binary logistic regression analysis was used to investigate whether the levels of NLRP3, IL-1Ra and TBP-2 at 24 weeks could serve as risk factors for the occurrence of GDM. The results showed that NLRP3 alone had good sensitivity as a predictor of GDM, but had relatively low specificity with an AUC of 0.720. In combination with IL-1Ra, specificity improved, but sensitivity decreased. In contrast, the combined prediction of TBP-2 and IL-1Ra showed the lowest sensitivity for GDM, and the combination of TBP-2 and NLRP3 was not ideal in terms of both sensitivity and specificity. When all three markers were used together to predict GDM, no significant improvement in sensitivity and specificity was observed. These results highlight the potential value of NLRP3 in predicting GDM, although its specificity is low and needs to be used in conjunction with other markers such as IL-1Ra to improve prediction accuracy. Although IL-1Ra has higher specificity, its sensitivity alone is not enough. Therefore, to improve the detection rate of GDM, physicians should consider the combined use of these biomarkers to select the best prediction strategy. This study further confirms the value of IL-1Ra in predicting GDM and suggests the potential to improve GDM detection rates by optimizing biomarker combinations.