The association of maternal fat-soluble antioxidants in early pregnancy with gestational diabetes mellitus: a prospective cohort study

Gestational diabetes mellitus (GDM), a glucose intolerance developing during pregnancy, affects 5-17% of pregnancies globally and is linked to adverse maternal and offspring outcomes. While the exact pathophysiology remains unclear, particularly in early pregnancy, oxidative stress is implicated. Antioxidant vitamins, such as A and E, play crucial roles in mitigating oxidative stress and supporting maternal and fetal health. This study hypothesized that insufficient antioxidant defenses in early pregnancy increase GDM risk. The researchers aimed to determine the association between maternal vitamins A and E levels in early pregnancy and GDM occurrence, exploring their potential as predictive biomarkers.

Existing literature presents inconsistent findings on the relationship between antioxidant vitamin levels and GDM, primarily due to variations in the timing of antioxidant measurement (mid- to late pregnancy). Some studies reported lower antioxidant levels in women with GDM, while others found no association. The lack of research examining early pregnancy antioxidant levels and their predictive value for GDM motivated this study.

A prospective cohort study was conducted in Beijing, enrolling 667 pregnant women. Vitamin A and E levels were measured at 9 weeks of gestation, and GDM was diagnosed between 24 and 28 weeks using a 75-g oral glucose tolerance test (OGTT). Data on maternal age, family history of diabetes, pre-pregnancy BMI, gestational weight gain (GWG), and fasting blood glucose (FBG) were collected. Statistical analyses included χ² tests, t-tests, Wilcoxon tests, logistic regression (adjusted for age, family history of diabetes, GWG, FBG, and pre-pregnancy BMI), and ROC analysis to assess predictive capabilities. Vitamin A and E levels were analyzed as continuous variables (z-scores) and categorized into quartiles. The vitamin E/cholesterol ratio was also examined.

Higher vitamin A levels in early pregnancy were significantly associated with increased GDM risk (OR, 1.46; 95% CI: 1.14–1.88; p = 0.0032) after adjusting for confounders. A significant trend of increased risk across vitamin A quartiles was observed (Ptrend = 0.016). Vitamin A levels correlated positively with FBG in early pregnancy and OGTT glucose levels. Vitamin E levels showed no significant association with GDM overall, though a trend of reduced risk was observed across quartiles of the vitamin E/cholesterol ratio (Ptrend = 0.043). ROC analysis indicated that vitamin A had significant discriminatory ability to predict GDM (AUC 0.653, p<0.001). A multivariate model incorporating vitamin A, maternal age, family history of diabetes, GWG, FBG, and pre-pregnancy BMI showed improved predictive performance (AUC 0.760; 95% CI: 0.705–0.815; p < 0.001).

This study provides novel evidence of a positive association between higher vitamin A levels in early pregnancy and increased GDM risk. The positive correlation between vitamin A and glucose levels supports this finding. While the mechanisms remain unclear, the role of retinol and its transport protein, RBP4, warrants further investigation. The lack of association for vitamin E contrasts with some previous studies, highlighting the need for further research exploring the vitamin E/cholesterol ratio as a potential protective factor. The study’s findings suggest vitamin A could be a useful biomarker for early GDM identification, although further validation is needed. The multivariate model combining vitamin A with other clinical factors improved GDM prediction.

Higher vitamin A levels in early pregnancy are significantly associated with increased GDM risk. Vitamin E showed no clear association, but the vitamin E/cholesterol ratio warrants further investigation. Vitamin A shows promise as an early biomarker for GDM risk. Future research should focus on elucidating the underlying mechanisms and validating these findings in larger, more diverse populations.

The study's limitations include the lack of RBP4 and TTR measurements, limited dietary and physical activity data, and potential limitations in generalizability due to the study's location and population. The sample size may also affect some study conclusions.