First-trimester proteomic profiling identifies novel predictors of gestational diabetes mellitus

PLoS One. 2019 Mar 27;14(3):e0214457. doi: 10.1371/journal.pone.0214457. eCollection 2019.

Abstract

Background: Gestational diabetes mellitus (GDM) is a common pregnancy complication associated with adverse outcomes including preeclampsia, caesarean section, macrosomia, neonatal morbidity and future development of type 2 diabetes in both mother and child. Current selective screening strategies rely on clinical risk factors such as age, family history of diabetes, macrosomia or GDM in a previous pregnancy, and they possess a relatively low specificity. Here we hypothesize that novel first trimester protein predictors of GDM can contribute to the current selective screening strategies for early and accurate prediction of GDM, thus allowing for timely interventions.

Methods: A proteomics discovery approach was applied to first trimester sera from obese (BMI ≥27 kg/m2) women (n = 60) in a nested case-control study design, utilizing tandem mass tag labelling and tandem mass spectrometry. A subset of the identified protein markers was further validated in a second set of serum samples (n = 210) and evaluated for their contribution as predictors of GDM in relation to the maternal risk factors, by use of logistic regression and receiver operating characteristic analysis.

Results: Serum proteomic profiling identified 25 proteins with significantly different levels between cases and controls. Three proteins; afamin, serum amyloid P-component and vitronectin could be further confirmed as predictors of GDM in a validation set. Vitronectin was shown to contribute significantly to the predictive power of the maternal risk factors, indicating it as a novel independent predictor of GDM.

Conclusions: Current selective screening strategies can potentially be improved by addition of protein predictors.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Biomarkers / blood
  • Diabetes, Gestational / blood
  • Diabetes, Gestational / diagnosis*
  • Diabetes, Gestational / metabolism*
  • Female
  • Humans
  • Pregnancy
  • Pregnancy Trimester, First / blood
  • Pregnancy Trimester, First / metabolism*
  • Prognosis
  • Proteomics*
  • Reproducibility of Results

Substances

  • Biomarkers

Grants and funding

This work was supported by a post doc grant (PO0113) from the Danish Diabetes Academy (https://www.danishdiabetesacademy.dk/) supported by the Novo Nordisk Foundation to TR and DMJ and by a research grant (7-A212) from Odense University Hospital Research Foundation (http://www.ouh.dk/wm379761) to MO. The Villum Center for Bioanalytical Sciences at University of Southern Denmark is acknowledged for access to advanced LC-MS/MS instrumentation. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.