Related Experiment Video
Updated: Mar 26, 2026

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
Published on: June 21, 2018
First-trimester multimarker prediction of gestational diabetes mellitus using targeted mass spectrometry
Tina Ravnsborg1,2, Lise Lotte T Andersen3, Natacha D Trabjerg4
1Department of Clinical Biochemistry and Pharmacology, Odense University Hospital, Sdr. Boulevard 29, 5000, Odense C, Denmark.
Insights
Predicting gestational diabetes mellitus (GDM) early is crucial. Multimarker panels of serum proteins show promise for improving first-trimester GDM prediction in pregnant women.
Area of Science:
- Biochemistry
- Clinical Chemistry
- Reproductive Medicine
Background:
- Gestational diabetes mellitus (GDM) poses risks like pre-eclampsia and future type 2 diabetes for mother and child.
- Accurate early GDM prediction is vital for timely intervention and improved perinatal outcomes.
- Current single protein biomarkers lack sufficient predictive power for GDM.
Purpose of the Study:
- To investigate if multimarker panels of serum proteins enhance first-trimester GDM prediction.
- To compare the predictive performance of single markers versus multimarker panels in obese and non-obese women.
- To identify potential protein biomarkers for early GDM detection.
Main Methods:
- A nested case-control study utilized first-trimester serum samples from GDM cases and controls.
- Serum protein analysis was performed using targeted nano-flow liquid chromatography (LC) MS.
- A 25-plex multiple reaction monitoring (MRM) MS assay was developed and validated.
Main Results:
- Six proteins, including adiponectin, apolipoprotein M, and apolipoprotein D, were significantly different between obese GDM patients and controls.
- Multimarker models combining protein levels and clinical data demonstrated improved predictive accuracy (AUC) compared to adiponectin alone.
- These models showed enhanced prediction for obese, non-obese, and overall GDM groups.
Conclusions:
- Multimarker models integrating protein markers and clinical data hold potential for predicting high-risk GDM pregnancies.
- This approach may facilitate earlier identification of women susceptible to GDM.
- Further validation is needed to establish these panels for routine clinical use.
Aims/Hypothesis:
Gestational diabetes mellitus (GDM) is associated with an increased risk of pre-eclampsia, macrosomia and the future development of type 2 diabetes mellitus in both mother and child. Although an early and accurate prediction of GDM is needed to allow intervention and improve perinatal outcome, no single protein biomarker has yet proven useful for this purpose. In the present study, we hypothesised that multimarker panels of serum proteins can improve first-trimester prediction of GDM among obese and non-obese women compared with single markers.
Methods:
A nested case-control study was performed on first-trimester serum samples from 199 GDM cases and 208 controls, each divided into an obese group (BMI ≥27 kg/m(2)) and a non-obese group (BMI <27 kg/m(2)). Based on their biological relevance to GDM or type 2 diabetes mellitus or on their previously reported potential as biomarkers for these diseases, a number of proteins were selected for targeted nano-flow liquid chromatography (LC) MS analysis. This resulted in the development and validation of a 25-plex multiple reaction monitoring (MRM) MS assay.
Results:
After false discovery rate correction, six proteins remained significantly different (p<0.05) between obese GDM patients (n=135) and BMI-matched controls (n=139). These included adiponectin, apolipoprotein M and apolipoprotein D. Multimarker models combining protein levels and clinical data were then constructed and evaluated by receiver operating characteristic (ROC) analysis. For the obese, non-obese and all GDM groups, these models achieved marginally higher AUCs compared with adiponectin alone.
Conclusions/Interpretation:
Multimarker models combining protein markers and clinical data have the potential to predict women at a high risk of developing GDM.
More Related Videos
Related Concept Videos
Peptide Identification Using Tandem Mass Spectrometry
This technique helps gather information regarding the protein from which the peptide was obtained and to study the peptides’ amino acid sequence. Identifying peptides from a complex mixture is an important component of the growing field of...
MALDI-TOF Mass Spectrometry
Diabetes Mellitus: Type 2 and Gestational

