Metabolic fingerprint of Gestational Diabetes Mellitus

J Proteomics. 2014 May 30;103:57-71. doi: 10.1016/j.jprot.2014.03.025. Epub 2014 Mar 31.


Gestational Diabetes (GDM) is causing severe short- and long-term complications for mother, fetus or neonate. As yet, the metabolic alterations that are specific for the development of GDM have not been fully determined, which also precludes the early diagnosis and prognosis of this pathology. In this pilot study, we determine the metabolic fingerprint, using a multiplatform LC-QTOF/MS, GC-Q/MS and CE-TOF/MS system, of plasma and urine samples of 20 women with GDM and 20 with normal glucose tolerance in the second trimester of pregnancy. Plasma fingerprints allowed for the discrimination of GDM pregnant women from controls. In particular, lysoglycerophospholipids showed a close association with the glycemic state of the women. In addition, we identified some metabolites with a strong discriminative power, such as LPE(20:1), (20:2), (22:4); LPC(18:2), (20:4), (20:5); LPI(18:2), (20:4); LPS(20:0) and LPA(18:2), as well as taurine-bile acids and long-chain polyunsaturated fatty acid derivatives. Finally, we provide evidence for the implication of these compounds in metabolic routes, indicative of low-grade inflammation and altered redox-balance, that may be related with the specific pathophysiological context of the genesis of GDM. This highlights their potential use as prognostic markers for the identification of women at risk to develop severe glucose intolerance during pregnancy.

Biological significance: Gestational Diabetes Mellitus (GDM) is increasing worldwide and, although diabetes usually remits after pregnancy, women with GDM have a high risk of developing postpartum type 2-diabetes, particularly when accompanied by obesity. Therefore, understanding the pathophysiology of GDM, as well as the identification of potentially modifiable risk factors and early diagnostic markers for GDM are relevant issues. In the present study, we devised a multiplatform metabolic fingerprinting approach to obtain a comprehensive picture of the early metabolic alternations that occur in GDM, and may reflect on the specific pathophysiological context of the disease. Future studies at later stages of gestation will allow us to validate the discriminant power of the identified metabolites.

Keywords: Gestational Diabetes Mellitus; Maternal metabolism; Metabolic fingerprinting.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Biomarkers / metabolism
  • Blood Glucose / metabolism
  • Diabetes, Gestational / blood
  • Diabetes, Gestational / physiopathology*
  • Diabetes, Gestational / urine
  • Female
  • Glucose Intolerance / etiology
  • Humans
  • Phospholipids / blood
  • Pilot Projects
  • Pregnancy
  • Pregnancy Trimester, Second
  • Prognosis
  • Proteomics


  • Biomarkers
  • Blood Glucose
  • Phospholipids