4.7 Article

Metabolomic profiling in the prediction of gestational diabetes mellitus

Journal

DIABETOLOGIA
Volume 58, Issue 6, Pages 1329-1332

Publisher

SPRINGER
DOI: 10.1007/s00125-015-3553-4

Keywords

Amino acids; Gestational diabetes mellitus; Metabolite profiling; Metabolites; Metabolomics

Funding

  1. National Institutes of Health [R03 DK096152, K24 DK094872]
  2. Robert Wood Johnson Foundation Harold Amos Medical Faculty Development Program
  3. Massachusetts General Hospital Executive Committee on Research/Multicultural Affairs Office Physician Scientist Development Award

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Aims/hypothesis Metabolomic profiling in populations with impaired glucose tolerance has revealed that branched chain and aromatic amino acids (BCAAs) are predictive of type 2 diabetes. Because gestational diabetes mellitus (GDM) shares pathophysiological similarities with type 2 diabetes, the metabolite profile predictive of type 2 diabetes could potentially identify women who will develop GDM. Methods We conducted a nested case-control study of 18- to 40-year-old women who participated in the Massachusetts General Hospital Obstetrical Maternal Study between 1998 and 2007. Participants were enrolled during their first trimester of a singleton pregnancy and fasting serum samples were collected. The women were followed throughout pregnancy and identified as having GDM or normal glucose tolerance (NGT) in the third trimester. Women with GDM (n = 96) were matched to women with NGT (n = 96) by age, BMI, gravidity and parity. Liquid chromatography-mass spectrometry was used to measure the levels of 91 metabolites. Results Data analyses revealed the following characteristics (mean +/- SD): age 32.8 +/- 4.4 years, BMI 28.3 +/- 5.6 kg/m(2), gravidity 2 +/- 1 and parity 1 +/- 1. Six metabolites (anthranilic acid, alanine, glutamate, creatinine, allantoin and serine) were identified as having significantly different levels between the two groups in conditional logistic regression analyses (p < 0.05). The levels of the BCAAs did not differ significantly between GDM and NGT. Conclusions/interpretation Metabolic markers identified as being predictive of type 2 diabetes may not have the same predictive power for GDM. However, further study in a racially/ethnically diverse population-based cohort is necessary.

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