Researchers find potential diagnostic tool to help pregnant women at risk

Collaborative effort between the University of Lethbridge and other Alberta universities has identified a new technique to help identify women at risk of metabolic disorders

Between three and 20 per cent of pregnant women in Canada develop gestational diabetes mellitus, or GDM, and the health of both the mother and her developing child can be negatively affected if left untreated.

A study by researchers at the University of Lethbridge, in collaboration with the University of Calgary and the University of Alberta, has identified a technique that may one day help health-care professionals identify women at risk of developing GDM early in their pregnancy. Their study, Metabolic dysfunction in pregnancy, was recently published by Wiley.

Hannah Scott (BSc ’17), a master’s student at the U of L’s Canadian Centre for Behavioural Neuroscience, wanted to know if specific biomarkers could identify a pregnant woman’s risk for obesity and GDM. She and her team obtained urine samples collected through the Alberta Pregnancy Outcomes and Nutrition (APrON) study. This long-term study, directed by researchers at the University of Calgary, involves thousands of women from Calgary and Edmonton and is designed to analyze the relationship between pregnant women’s nutrition, their mental health and the health and development of their children.

Dr. Brenda Leung, a U of L associate professor in the Faculty of Health Sciences, was involved in starting APrON 10 years ago as a doctoral student at the U of C and she continues to be involved as an investigator. Leung facilitated the collaboration between APrON and the U of L research team.

“We examined these samples for biomarkers of risk using proton nuclear magnetic resonance (NMR) spectroscopy,” says Scott. “What we were looking for was a profile, or you can think of it as a metabolite fingerprint, associated with the diseases or the later development of the diseases.”

The urine samples were taken before the development of GDM. By using NMR, the researchers could identify the women who were obese, those who later developed GDM and those who were part of the control group. This study shows it’s possible to predict if a woman will develop GDM based on a urine sample taken before any symptoms appear.

“We’ve established that those groups have unique urinary fingerprints or profiles that distinguish them,” says Tony Montina (BSc ’08, MSc ’10), NMR facility manager. “Something chemically or biochemically is different between them and we can accurately detect these differences.”

Using urine analysis for metabolomics is a relatively new field of research; most previous studies have used blood samples.