Amino Acid Dysregulation in the Mother–Fetus Unit: Multi-Compartment Metabolomic Signatures of Gestational Diabetes Mellitus and Fetal Macrosomia

The role of amino acid disturbances in the mother–fetus system remains poorly understood, despite their critical involvement in gestational diabetes mellitus (GDM), fetal macrosomia (FM) and offspring metabolic programming. This study included 62 mother–newborn dyads stratified by GDM and FM status. An analysis of the association of amino acids with clinical parameters was performed using the Spearman test. Amino acid markers of GDM were identified using the mutual information index and the Mann–Whitney test. A random forest method was used to identify amino acid markers, with the SHAP value used to estimate the contribution of each amino acid. In maternal serum, GDM was associated with significantly lower levels of glycine, 1-methylhistidine, γ-aminobutyric acid, lysine, and tryptophan. Umbilical cord serum from GDM pregnancies showed reduced concentrations of glutamine, glycine, asparagine, methionine, and proline. In amniotic fluid, GDM with FM was characterized by elevated lysine and 1-methylhistidine. Cord blood exhibited increased lysine, proline, leucine, and allo-isoleucine, while amniotic fluid showed low homocitrulline, asparagine, and lysine, together with high histidine. Fetal weight correlated directory with lysine and isoleucine and inversely with homocitrulline. Pathway analysis linked maternal serum markers to disturbances in biotin, glutamate, and carnitine metabolism, whereas cord blood markers involved broader alterations in amino acid, purine, and amino sugar metabolism. In amniotic fluid from GDM with FM, the methylhistidine pathway was specifically enriched, suggesting changes in neonatal muscle protein turnover. GDM induces distinct alterations in the amino acid profiles of all three compartments, and the combination with FM yields unique metabolic signatures. These findings identify candidate biomarkers for prediction of GDM and its complications and point to potential targets for metabolic intervention.