BACKGROUND Gestational diabetes mellitus (GDM) places both the mother and offspring at high risk of complications. Increasing evidence suggests that the gut microbiota plays a role in the pathogenesis of GDM. However, it is still unclear whether the gut microbiota is related to blood biochemical traits, particularly glucagon-like peptide-1 (GLP-1), in GDM patients. AIM To explore the correlation between the gut microbiota and blood biochemical traits, particularly GLP-1, in GDM patients. METHODS The V4 region of the 16S ribosomal ribonucleic acid (rRNA) gene was sequenced based on the fecal samples of 35 pregnant women with GDM and was compared to that of 25 pregnant women with normal glucose tolerance (NGT). RESULTS The results showed that Ruminococcaceae_UCG-002, Ruminococcaceae_UCG-005, Clostri-dium_sensu_stricto_1, and Streptococcus were more abundant in the NGT group than in the GDM group. Bacteroides and Lachnoclostridium were more abundant in the GDM group than in the NGT group. Spearman's correlation analysis was performed to identify the relationships between microbiota genera and blood biochemical traits. Paraprevotella, Roseburia, Faecalibacterium, and Ruminococcaceae_UCG-002 were significantly negatively correlated with glucose. Ruminococcaceae_UCG-002 was significantly negatively correlated with hemoglobin A1c. Bacteroides was significantly positively correlated with glucose. Sutterella, Oscillibacter, and Bifidobacterium were significantly positively correlated with GLP-1. A random forest model showed that 20 specific genera plus glucose provided the best discriminatory power, as indicated by the area under the receiver operating characteristic curve (0.94). CONCLUSION The results of this study reveal novel relationships between the gut microbiome, blood bio-chemical traits, particularly GLP-1, and GDM status. These findings suggest that some genera are crucial for controlling blood glucose-related indices and may be beneficial for GDM treatment. Alteration in the microbial composition of the gut may potentially serve as a marker for identifying individuals at risk of GDM.