3.1 Characteristics of study participants:
The clinical characteristics of participants were shown in Table 1. There was no statistical difference in maternal age, gestational age, gravidity, systolic blood pressure(sBP), diastolic blood pressure(dBP), parity, educational level, body mass index (BMI), family income, and delivery modes between GDM and non-GDM groups, whilst fasting blood glucose, 60/120 minutes postprandial blood glucose after 75 g oral glucose differed significantly. Newborn characteristics, including birth weight and birth length were not significantly different between groups.
Table 1. Characteristics of study participants
Abbreviations: sBP, systolic blood pressure; dBP, diastolic blood pressure; LSCS, lower segment cesarean section
Values are means±SD, median (IQR) or n (%)
aP value from Mann–Whitney test
bP value from Student t-test
cP value from Chi square test
3.2 Metabolite profiling of plasma and urine
A total of 192 and 165 metabolites were profiled in maternal urine and plasma samples respectively. In 3rd trimester samples, one and 39 metabolites were significantly different between GDM and control groups in urine and plasma respectively (Table 1, Fig. 1, Table S2). In the urine, nicotinic acid was the only metabolite significantly lower in GDM when compared with control groups. In plasma, 25 metabolites where higher in GDM pregnancies, including the majority of amino acids, amino acid derivatives, and tricarboxylic acid (TCA) cycle intermediates, hexanoic acid and myristoleic acid, while 14 were lower in GDM pregnancies relative to controls. This included three saturated fatty acids (2-methyloctadecanoic acid, arachidic acid, stearic acid), six unsaturated fatty acids (adrenic acid, gondoic acid, bishomo-gamma-linolenic acid, 11,14-eicosadienoic acid, cis-vaccenic acid, trans-vaccenic acid), three amino acids derivatives (cysteine, N-(Carboxymethyl)-L-alanine, beta-methylamino-alanine) and two organic acids (malonic acid, benzoic acid). The greatest fold differences between the two groups in the first trimester were higher methionine and beta-alanine, and lower cysteine and arachidic acid in GDM pregnancies.
In the first trimester pregnancy samples, no differences between groups were seen in urine, while 14 metabolites were found to be significantly different in GDM plasma samples. This included 5 metabolites (lysine, N-alpha-acetyllysine, citric acid, beta-alanine, methionine) that with higher levels in GDM pregnancies relative to non-GDM, and 9 with lower levels in GDM relative to non-GDM pregnancies. The direction and magnitude of differences between GDM and non-GDM in first trimester were also seen in the 3rd trimester comparisons.
3.3 Receiver operating characteristic (ROC) curve analysis for plasma and urine
With regard to plasma ROC analysis, seven and four metabolites were shortlisted in the first and third trimester respectively with an AUC above 0.75. These included four fatty acids (arachidic acid, stearic acid, 2-methyloctadecanoic acid, and 11,14-eicosadienoic acid), two amino acid (alanine and cysteine), and one organic acid (malonic acid) in the first trimester (Fig. 2a). Meanwhile, three organic acids (2-aminobutyric acid, 2-hydroxybutyric acid, and benzoic acid) and one unsaturated fatty acid (11,14-Eicosadienoic acid) were found in the third trimester (Fig. 2b). By combining seven and four shortlisted metabolites for the first and third trimester via multivariant ROC models, we were capable of discriminating GDM from healthy pregnancies with an AUC of 0.928 and 0.898 respectively. In terms of urine profiles, only three significant metabolites (nicotinic acid, glutamic acid, and ornithine) were identified with an AUC above 0.75 in the third trimester (Fig. 3). A multivariant ROC model combining these three metabolites was established to differentiate GDM from healthy pregnancies with an AUC of 0. 838.
3.4 Longitudinal metabolite profiles of plasma and urine between first and third trimesters
To investigate how advanced pregnancy outcomes are changed over the first and third trimester periods, the interactions between GDM outcomes and time were analyzed. Figure 4a-c illustrated that 13 plasma metabolites between pregnancy outcomes were changed across trimester periods (p < 0.05, repeated measurement analysis of variance (ANOVA)). Among them, five metabolites displayed the opposite trend between first and third trimesters (L-alanine, 2-oxybutyric acid, hippuric acid, oleic acid and EDTA, Fig. 4a); four metabolites only displayed disparity in the first trimester (dimethyltetrdecanoic acid, glutamine, palmitic acid, lactic acid, Fig. 4b); three metabolites only showed discrimination in the third trimester (2-aminobutyric acid, 2-hydroxybutyric acid, citraconic acid, Fig. 4C). In comparison, there were only two urine metabolites (benzoic acid and 2-hydroxycinnamic acid) were found to interact between GDM outcomes and gestation progress (Fig. 4d). An increasing difference between GDM and healthy pregnancies for benzoic acid was observed over time. Conversely, there was a reduced difference for 2-hydroxycinnamic acid across trimesters.
3.5 Metabolic pathway enrichment analysis
The identified metabolites were performed enrichment analysis using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database to further characterize into functional pathway categories. The predicated outcome demonstrated that only nine metabolic pathways appeared to be significantly altered between GDM and control groups in the first trimester (Fig. 5a). The metabolism of carbohydrate, nucleotide, and amino acid were upregulated, whilst all metabolic pathways classified into lipid metabolism were downregulated in GDM group, besides, the ATP-binding cassette (ABC) transporters pathway shown the similar trend with lipid metabolism. Especially, metabolism of amino acid and fatty acid, as well as membrane transport mainly ABC transporters involving methionine, lysine and cysteine might play an important role in the pathogenesis of GDM (Fig. 5b).