Gestational diabetes mellitus (GDM) is a metabolic disorder that poses substantial risks to both maternal and fetal health. Early intervention has been shown to effectively reduce various complications. Gut microbiota dysbiosis is strongly linked to the onset and progression of GDM and may serve as a critical early-warning biomarker. In this study, we systematically analyzed the fecal microbiota of 61 pregnant women during the first trimester using 16S rRNA sequencing. These microbial profiles were correlated with oral glucose tolerance test (OGTT) results at 24-28 weeks of gestation and clinical delivery outcomes. Our analysis identified significant differences in gut microbiota composition between GDM and healthy pregnancies, observed at both the phylum and genus levels early in gestation. Leveraging these microbial distinctions, we developed an early diagnostic model based on genus-level markers, achieving an area under the curve (AUC) of 98.23, indicating high diagnostic precision. This study highlights early-pregnancy microbiota signatures associated with GDM and provides a robust scientific basis for developing microbiota-based diagnostic tools, offering new avenues for GDM prevention and management.
Importance: Gestational diabetes mellitus (GDM) poses significant risks to both maternal and fetal health, but early intervention can reduce complications. This study identifies gut microbiota signatures associated with GDM in the first trimester, providing a potential early diagnostic biomarker. By analyzing fecal microbiota profiles, we developed a diagnostic model with high accuracy (AUC = 98.23). These findings suggest that microbiota-based tools could enable early, non-invasive detection of GDM, offering new opportunities for prevention and personalized management. This research highlights the role of the gut microbiome in pregnancy and has important implications for improving maternal and fetal health outcomes.
Keywords: biomarkers; early diagnostic model; gestational diabetes mellitus; gut microbiota.