Metabolic profiling of pre-gestational and gestational diabetes mellitus identifies novel predictors of pre-term delivery.pdf (1.1 MB)

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

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posted on 02.02.2021, 09:23 by Ilhame Diboun, Manjunath Ramanjaneya, Yasser Majeed, Lina Ahmed, Mohammed Bashir, Alexandra E Butler, Abdul Badi Abou-Samra, Stephen L. Atkin, Nayef A. Mazloum, Mohamed A. Elrayess

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.

Funding

QNRF, Grant no. NPRP10-1205-160010 (NAM)

History

Comments

The original article is available at https://translational-medicine.biomedcentral.com/

Published Citation

Diboun I, Ramanjaneya M, Majeed Y, Ahmed L, Bashir M, Butler AE, Abou-Samra AB, Atkin SL, Mazloum NA, Elrayess MA. Metabolic profiling of pre-gestational and gestational diabetes mellitus identifies novel predictors of pre-term delivery. Journal of Translational Medicine. 2020;18(1):366.

Publication Date

24 September 2020

PubMed ID

32972433

Department/Unit

  • RCSI Bahrain

Publisher

Springer Nature

Version

  • Published Version (Version of Record)

Licence

Exports

Royal College of Surgeons in Ireland

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Exports