Clinical metabolomics and insights into gestational diabetes: emerging translational opportunities

Gokulakrishnan Kuppan, PhD
National Institute of Mental Health and Neurological Disorders (NIMHANS),
Chennai | India
Part of the Symposium:
Metabolomics India - Entering the next level of population health
Gestational Diabetes Mellitus (GDM), defined as diabetes diagnosed for the first-time during pregnancy, affects 5-25% of all pregnant women, depending on the population studied, the definitions, and the screening/diagnostic methods used. GDM is also associated with a nearly tenfold increased risk for future type 2 diabetes mellitus (T2DM) and a higher incidence of cardiovascular diseases. While GDM is typically diagnosed in the late stages of pregnancy (24-28 weeks), earlier detection of women at high risk for subsequent GDM, can enable the initiation of therapeutic/lifestyle change management. Efforts in the past to identify early trimester biomarkers and risk predictions for GDM diagnosis have yielded limited results. While these models have variable degrees of predictive power depending on the choice of clinical parameters or biochemical surrogates of adiposity, it is also an issue that none have explored first-trimester-based metabolites to identify women at risk of GDM. Therefore, detecting women at higher risk of GDM early in pregnancy by appropriate biomarkers is a demanding clinical need and is expected to prevent the onset of GDM and the future development of T2DM.
Metabolomics, the systematic study of small molecule products of biochemical pathways, has shown promise in identifying biomarkers predictive of metabolic diseases. Prior metabolomic analysis in a prediabetic population identified specific amino acid clusters as predictive of T2DM. There is an unmet need for an effective technology (such as metabolomic profiling) that has the potential to identify an early diagnosis of GDM. The majority of current metabolomic studies on GDM are conducted during the third trimester or after delivery, and lack of data on metabolomic profiling in the 1st trimester of pregnancy to predict women who would subsequently develop GDM. Thus, enhanced identification of maternal metabolites in the prediction of GDM necessitates further studies in larger, more racially/ethnically diverse populations for a better understanding of the biochemical and molecular basis of GDM in pregnant women. Thus, the outcome is expected to unravel novel mechanisms that could have profound clinical and translational implications.
Based on recent technological developments and studies, it is now becoming potentially possible that clinically useful antenatal screening test(s) can be developed using metabolomics. The development of such test(s) will provide data that better informs clinical decision-making and patient management for GDM that will not only directly benefit the immediate pregnancy, but will also help mitigate the longer-term ramifications of these conditions for both the mother and the offspring.
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