A recent study found that gut microbiota composition in early pregnancy may predict later development of gestational diabetes mellitus, suggesting a potential tool for earlier diagnosis and intervention.
Researchers prospectively analyzed fecal samples from 61 pregnant women between 11 and 13 weeks of gestation. Using 16S rRNA gene sequencing, they assessed gut microbial composition and correlated the results with oral glucose tolerance test (OGTT) outcomes obtained at 24 to 28 weeks. Participants were recruited from a single city—Zhangzhou, China—to minimize dietary heterogeneity.
Women who developed gestational diabetes mellitus (GDM) demonstrated distinct gut microbiota profiles compared with those who did not. These differences, most evident at the genus level, were present weeks before clinical onset. At the phylum level, Proteobacteria and Actinobacteriota were elevated, while Bacteroidota was reduced in the GDM group. Firmicutes was slightly lower in women with GDM. Although alpha and beta diversity metrics did not show statistically significant global differences in richness or structure, compositional shifts were evident.
At the genus level, GDM was associated with higher relative abundances of potentially pathogenic bacteria such as Escherichia-Shigella, Klebsiella, and Finegoldia. In contrast, beneficial genera including Bacteroides, Faecalibacterium, and Akkermansia were reduced. These taxa are known to influence metabolic and immune regulation and to support intestinal barrier integrity.
To evaluate the predictive value of these microbial features, the investigators developed early diagnostic models based on taxa with significant between-group differences. A phylum-level model that included Firmicutes, Proteobacteria, Bacteroidota, Actinobacteriota, Verrucomicrobiota, and Cyanobacteria achieved an area under the curve (AUC) of 0.799. A genus-level model, incorporating Porphyromonas, Fenollaria, Klebsiella, Prevotella, and Corynebacterium, demonstrated high discriminative power with an AUC of 0.982.
Functional prediction based on 16S rRNA data further revealed that microbial genes associated with carbohydrate metabolism and inflammatory responses were enriched in the GDM group. Notably, higher levels of domains related to the Toxin ToxN family, B12-binding proteins, and trehalose-phosphatase enzymes were observed. These may influence host glucose metabolism and insulin sensitivity. Conversely, GDM patients exhibited reduced abundance of functional markers involved in microbial stress adaptation and vitamin B₁₂ biosynthesis, such as cobalamin 5′-phosphate synthase and RecQ helicase.
The authors proposed that gut microbiota screening in the first trimester may offer a noninvasive method for identifying individuals at risk of GDM earlier than the current OGTT protocol, which is typically performed between 24 and 28 weeks. Early identification could allow for timely interventions to reduce complications for both mother and infant.
Limitations of the study included the relatively small sample size (n = 61), restriction to a single geographic area, and reliance on predictive functional analysis rather than direct metabolomic validation. Additionally, the observational design did not permit causal inference. The authors called for future research involving larger, multicenter cohorts and integration of metabolomic and proteomic data to validate these findings.
Despite these limitations, the study provides additional evidence linking gut microbiota composition to maternal metabolic health. The genus-level microbial signatures identified may serve as sensitive and specific biomarkers for early GDM detection.
The authors reported no conflicts of interest.
Source: Microbiology Spectrum