Metabolic dysfunction in pregnancy: Fingerprinting the maternal metabolome using proton nuclear magnetic resonance spectroscopy

• Published in: Endocrinology, diabetes & metabolism diabetes & metabolism, 2021-01, Vol.4 (1), p.e00201-n/a
• Main Authors: Scott, Hannah D., Buchan, Marrissa, Chadwick, Caylin, Field, Catherine J., Letourneau, Nicole, Montina, Tony, Leung, Brenda M. Y., Metz, Gerlinde A. S.
• Format: Article
• Language: English
• Subjects: Adult; APrON study; biomarker; Biomarkers; body mass index; Diabetes, Gestational - diagnosis; Diabetes, Gestational - etiology; Diabetes, Gestational - prevention & control; Female; gestational diabetes mellitus; Humans; maternal health; Metabolic Syndrome - diagnosis; Metabolic Syndrome - etiology; Metabolic Syndrome - metabolism; Metabolome; metabolomics; Metabolomics - methods; NMR; nmr spectroscopy; Nuclear magnetic resonance; Nutrition; Obesity; Obesity - etiology; Original; Original s; pathway analysis; personalized medicine; pregnancy; Pregnancy - metabolism; Pregnancy Complications - diagnosis; Pregnancy Complications - etiology; Pregnancy Complications - metabolism; Pregnancy Outcome; preterm birth; Proton Magnetic Resonance Spectroscopy; Risk; Spectrum analysis; urine; Womens health
• ISSN: 2398-9238; 2398-9238
• DOI: 10.1002/edm2.201

Aims Maternal metabolic disorders place the mother at risk for negative pregnancy outcomes with potentially long‐term health impacts for the child. Metabolic syndrome, a cluster of features associated with increased risk of metabolic disorders, such as cardiovascular disease, diabetes and stroke, affects roughly one in five Canadians. Metabolomics is a relatively new technique that may be a useful tool to identify women at risk of metabolic disorders. This study set out to characterize urinary metabolic biomarkers of pregnant women with obesity and of pregnant women who later developed gestational diabetes mellitus (pre‐GDM), compared to controls. Methods and Materials Second trimester urine samples were collected through the Alberta Pregnancy Outcomes and Nutrition (APrON) cohort and examined with 1H nuclear magnetic resonance (NMR) spectroscopy. Multivariate analysis was used to examine group differences, and machine learning feature selection tools identified the metabolites contributing to separation. Results Obesity and pre‐GDM metabolomes were distinct from controls and from each other. In each comparison, the glycine, serine and threonine pathways were the most impacted. Pantothenate, formic acid and glycine were downregulated by obesity, while formic acid, dimethylamine and galactose were downregulated in pre‐GDM. The three most impacted metabolites for the comparison of obesity versus pre‐GDM groups were upregulated creatine/caffeine, downregulated sarcosine/dimethylamine and upregulated maltose/sucrose in individuals who later developed GDM. Conclusion These findings suggest a role for urinary metabolomics in the prediction of GDM and metabolic marker identification for potential diagnostics and prognostics in women at risk. Urinary metabolomics can provide diagnostic signatures of obesity in pregnant mothers. The urine metabolome can predict the risk of gestational diabetes mellitus. Proton nuclear magnetic resonance spectroscopy is able to identify metabolic markers for diagnostics and prognostics in women at risk.