Gestational diabetes mellitus (GDM) is a growing global health concern, driving the need for novel diagnostic and prognostic approaches. The aim of this study was to analyze the amino acid profile in the mother–fetus system (maternal venous blood, umbilical cord blood, and amniotic fluid) and to identify specific biological markers of GDM and macrosomia. Using HPLC-MS/MS, we analyzed serum from maternal venous and umbilical cord blood, along with amniotic fluid, across 94 mother–fetus pairs (53 GDM, 41 controls). Machine learning and metabolic pathway analysis revealed significant alterations in 19 amino acids. In GDM, maternal serum showed elevated 5-OH-lysine and homocitrulline, while cord blood had higher isoleucine, serine, and threonine. Amniotic fluid exhibited increased leucine, isoleucine, threonine, serine, arginine, and ornithine. Conversely, histidine, glutamine, alanine, asparagine, β-/γ-aminobutyric acids, phenylalanine, ornithine, and citrulline were reduced. Histidine, glutamine, and asparagine inversely correlated with blood glucose (r = −0.26, r = −0.33, r = −0.30) and were lower in GDM. These findings highlight three key metabolic loci in GDM pathogenesis, with glutamine, histidine, and asparagine emerging as potential maternal blood biomarkers for early macrosomia prediction. However, given confounding factors in metabolomic studies, further large-scale validation is essential.

: Gestational diabetes mellitus (GDM) is a growing global health concern, driving the need for novel diagnostic and prognostic approaches. This non-targeted metabolomic study investigated amino acid profiles in the mother-fetus system to identify biomarkers linked to GDM and fetal macrosomia. Using HPLC-MS/MS, we analyzed serum from maternal venous and umbilical cord blood, along with amniotic fluid, across 94 mother-fetus pairs (53 GDM, 41 controls). Machine learning and metabolic pathway analysis revealed significant alterations in 19 amino acids. In GDM, maternal serum showed elevated 5-OH-lysine and homocitrulline, while cord blood had higher isoleucine, serine, and threonine. Amniotic fluid exhibited increased leucine, isoleucine, threonine, serine, arginine, and ornithine. Conversely, histidine, glutamine, alanine, asparagine, β-/γ-aminobutyric acids, phenylalanine, ornithine, and citrulline were reduced. Histidine, glutamine, and asparagine inversely correlated with blood glucose (|R| < 0.4, *p* < 0.05) and were lower in GDM. These findings highlight three key metabolic loci in GDM pathogenesis, with glutamine, histidine, and asparagine emerging as potential maternal blood biomarkers for early macrosomia prediction. However, given confounding factors in metabolomic studies, further large-scale validation is essential.

Aim. To identify new markers using omics technologies for use as predictors of fetal growth and developmental abnormalities in gesta­tio­nal diabetes (GD). Material and methods . The long-term goal of this study is to create a unique biological sample collection that can be used to assess the risk of diabetic fetopathy (DF) and other adverse perinatal outcomes by identifying early preclinical markers. To achieve this goal, the following studies were planned for the first stage: the formation of a reference collection of biomaterial from women with a known perinatal outcome and its subsequent comprehensive analysis to identify key markers. Conducting complex experiments using genetic, immunological, and mass spectrometric approaches allows for a comprehensive assessment of molecular GD pathogenesis and the identification of complementary biomarkers. For this study, a collection of plasma samples from pregnant women in the first trimester, women in labor, amniotic fluid, and umbilical cord plasma was compiled. The resulting biomaterial samples were frozen and stored at a temperature not exceeding -80 оC. A sample of 100 women aged 18-45 years, at 34 weeks 1 day to 41 weeks 6 days of gestation, from both groups with and without GD, was included in the current study. Enzyme-­linked immunosorbent assay (ELISA) was performed on samples for a number of regulatory proteins and embryotropic antibodies, molecular genetic analysis of hemostasis gene polymorphisms, and mass spectrometric analysis of amino acids. Results . A comparative analysis revealed that pregnant women with GD were more likely to have the FGB 455 G/A fibrinogen gene poly­mor­phism (p=0,008), and their autoimmune antibody profile was altered, consistent with supraphysiological apoptosis and insulin resistance. In the absence of fetal macrosomia, maternal plasma levels of tissue plasminogen activator were lower (p=0,001). The main findings of mass spectrometry of amino acids in the blood of women with GD were lower concentrations of tryptophan (p=0,025) and γ-aminobutyric acid (p=0,023). In amniotic fluid and cord blood in GD, decreased concentrations of amino acids responsible for protein synthesis (lysine and methionine) and increased concentrations of amino acids associated with macrosomia were detected. Conclusion . The study results confirm metabolic, immune, and hemo­rheo­logical disturbances in maternal GD, associated with abnormal ami­no acid composition in cord blood and amniotic fluid in neonates with macrosomia. The identified differences in the metabolome can be con­si­dered potential markers for identifying the risk of unfavorable peri­natal outcomes.

Aim. To study the role of metabolic disorders in the development of perinatal complications of the novel coronavirus infection.Materials and methods. The analysis of the course of pregnancy and childbirth in pregnant women who had a novel coronavirus infection (170) and without it (100), and their newborns (270).Results. A novel coronavirus infection (NCI) during pregnancy leads to the development of complications: preeclampsia (p = 0.012), premature birth (p = 0.038), premature detachment of the normally located placenta (p = 0.05), fetal growth retardation (p = 0.028), gestational diabetes mellitus (GDM) (p = 0.023), intrauterine infection (p = 0.048) and asphyxia of the newborn (p = 0.04). Gestational diabetes mellitus is 2 times more likely to accompany a moderate form of NCI, as opposed to a mild one (p = 0.001). Infection with the SARS-CoV2 virus on the background of previous GDM contributes to the development of moderate NCI (p = 0.005). Hyperglycemia in GDM after moderate NCI more often than after mild requires the appointment of insulin (p = 0.03). The combination of NCI and GDM is characterized by the development of polyhydramnios (p = 0.02), the risk of which increases in the presence of hereditary thrombophilia. The neonatal period is more often complicated by intrauterine pneumonia if the mother has a combination of NCI and GDM.Conclusion. The risk of developing metabolic disorders and perinatal complications in pregnant women who had a novel coronavirus infection is significantly higher than in pregnant women without a novel coronavirus infection.