Metabolic profiling of pre-gestational and gestational diabetes mellitus identifies novel predictors of pre-term delivery

Abstract

Background Pregnant women with gestational diabetes mellitus (GDM) or type 2 diabetes mellitus (T2DM) are at increased risks of pre-term labor, hypertension and preeclampsia. In this study, metabolic profiling of blood samples collected from GDM, T2DM and control pregnant women was undertaken to identify potential diagnostic biomarkers in GDM/T2DM and compared to pregnancy outcome. Methods Sixty-seven pregnant women (21 controls, 32 GDM, 14 T2DM) in their second trimester underwent targeted metabolomics of plasma samples using tandem mass spectrometry with the Biocrates MxP® Quant 500 Kit. Linear regression models were used to identify the metabolic signature of GDM and T2DM, followed by generalized linear model (GLMNET) and Receiver Operating Characteristic (ROC) analysis to determine best predictors of GDM, T2DM and pre-term labor. Results The gestational age at delivery was 2 weeks earlier in T2DM compared to GDM and controls and correlated negatively with maternal HbA1C and systolic blood pressure and positively with serum albumin. Linear regression models revealed elevated glutamate and branched chain amino acids in GDM + T2DM group compared to controls. Regression models also revealed association of lower levels of triacylglycerols and diacylglycerols containing oleic and linoleic fatty acids with pre-term delivery. A generalized linear model ROC analyses revealed that that glutamate is the best predictors of GDM compared to controls (area under curve; AUC = 0.81). The model also revealed that phosphatidylcholine diacyl C40:2, arachidonic acid, glycochenodeoxycholic acid, and phosphatidylcholine acyl-alkyl C34:3 are the best predictors of GDM + T2DM compared to controls (AUC = 0.90). The model also revealed that the triacylglycerols C17:2/36:4 and C18:1/34:1 are the best predictors of pre-term delivery (≤ 37 weeks) (AUC = 0.84). Conclusions This study highlights the metabolite alterations in women in their second trimester with diabetes mellitus and identifies predictive indicators of pre-term delivery. Future studies to confirm these associations in other cohorts and investigate their functional relevance and potential utilization for targeted therapies are warranted.

Placental metabolic profiling in gestational diabetes mellitus: An important role of fatty acids

“…Insulin resistance, low‐grade inflammation, and endothelial cell dysfunction are considered its characteristic features. Increasing studies highlight the importance of metabolite alterations in GDM, and most efforts are focused on investigating biomarkers that could facilitate prediction and diagnosis 17–19 . These studies suggested that changes in maternal metabolic status tend to affect the levels of various metabolites and metabolic homeostasis in the fetus and subsequently lead to an increased complication of pregnancy, such as macrosomia.…”

“…Increasing studies highlight the importance of metabolite alterations in GDM, and most efforts are focused on investigating biomarkers that could facilitate prediction and diagnosis. 17 , 18 , 19 These studies suggested that changes in maternal metabolic status tend to affect the levels of various metabolites and metabolic homeostasis in the fetus and subsequently lead to an increased complication of pregnancy, such as macrosomia. However, the characteristics and molecular mechanism of metabolites in the maternal‐fetal microenvironment of GDM are still unclear.…”

Differential analysis of the bacterial community in colostrum samples from women with gestational diabetes mellitus and obesity

“…5 ). Higher levels of branched-chain amino acids (BCAA) valine, leucine and isoleucine have been detected in blood from women with GDM and are linked to an increased risk of glucose intolerance, early pathogenesis of type 2 diabetes and a high relative abundance of intestinal pro-inflammatory species of Prevotella 67 – 70 . The role of Prevotella spp.…”

Analysis of specific lipid metabolites in cord blood of patients with gestational diabetes mellitus

“…Metabonomic is a powerful tool for elucidating the mechanism of metabolic abnormalities in susceptible individuals by systematically studying low molecular weight compounds in biological tissues and body fluids (Ceja-Gálvez et al, 2020;Perng et al, 2017). Metabonomic has been used to find biomarkers to predict, diagnose and monitor a variety of metabolic diseases, such as GDM (Diboun et al, 2020;Fanos et al, 2013).…”