Researchers led by Ellen C. Francis, an assistant professor at Rutgers School of Public Health, have conducted a comprehensive systematic review and meta-analysis to evaluate the potential of precision diagnostics in gestational diabetes mellitus (GDM).
Their study, published in Communications Medicine, offers new insights into diagnosing and managing GDM, a form of diabetes that occurs during pregnancy.
High blood sugar levels characterize GDM and is the most prevalent metabolic condition in pregnant women, posing significant risks to both mother and child.
The standard treatments for GDM vary in effectiveness, pointing to a need for more personalized approaches. Francis and her team’s research indicates that pregnancy weight and certain biochemical markers in blood may be crucial in predicting the risk of adverse pregnancy outcomes.
Francis emphasizes that obesity is not just a risk factor for larger offspring, but also the metabolic changes accompanying obesity can increase the risk of negative outcomes. This finding suggests the importance of looking beyond just blood sugar levels in GDM diagnosis.
The study is the first to systematically assess the potential of subtypes in GDM and explore whether nonglycemic markers, such as insulin profiles and triglyceride levels, can refine risk stratification.
This approach could lead to more nuanced diagnostic methods, improving mothers’ and babies’ outcomes.
However, Francis notes that there is still much to learn. The team must understand if insulin resistance or higher triglycerides are causally linked to adverse outcomes and if these factors can be safely targeted during pregnancy.
The research revealed a significant gap in existing literature, with most studies not focusing on the clinical, biochemical, or sociocultural differences among women with GDM.
Only a few recent studies have begun to examine these factors, which could improve risk assessment and differentiate clinical outcomes between GDM subtypes.
Looking forward, Francis advocates for more research into precision biomarkers, diverse population studies for replication, and multinational studies considering environmental and behavioral factors.
Additionally, exploring genetic and multi-omics data using advanced analytical methods could provide deeper insights into the causal pathways and heterogeneity within GDM and its outcomes.
This study involved collaboration with researchers from institutions across the United States, the United Kingdom, Singapore, South Korea, and Australia, highlighting its global relevance and the widespread interest in improving GDM diagnosis and treatment.
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The research findings can be found in Communications Medicine.
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