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Emerging biomarkers for gestational diabetes mellitus and related pediatric outcomes
Tanu Gautam1, Amreen Shamsad1, Renu Singh2
1Molecular and Human Genetics Laboratory, Department of Zoology, University of Lucknow, Lucknow 226007, Uttar Pradesh, India.
Insights
Gestational diabetes mellitus (GDM) diagnosis is improving with novel biomarkers like microRNAs and gut microbiota. These advancements aid in early prediction and personalized management, enhancing feto-maternal health outcomes.
Area of Science:
- Reproductive Medicine
- Metabolic Disorders
- Biomarker Discovery
Background:
- Gestational diabetes mellitus (GDM) is a pregnancy complication linked to maternal and infant metabolic health issues.
- Current GDM diagnostic methods have limitations, necessitating improved early detection strategies.
- Adverse feto-maternal outcomes are associated with GDM, highlighting the need for timely intervention.
Purpose of the Study:
- To review emerging biomarkers for gestational diabetes mellitus (GDM) diagnosis and prediction.
- To evaluate the diagnostic accuracy and predictive value of novel GDM biomarkers.
- To explore the clinical applications of these biomarkers for personalized medicine approaches in GDM management.
Main Methods:
- Literature review of recent research on GDM biomarkers.
- Analysis of emerging biomarkers including microRNAs, cell-free DNA, exosomes, and gut microbiota.
- Examination of advanced technologies like next-generation sequencing, metabolomics, and proteomics in biomarker discovery.
Main Results:
- Novel biomarkers such as microRNAs, cell-free DNA, and gut microbiota show promise for GDM diagnosis.
- Emerging biomarkers offer potential for earlier prediction of GDM and associated pediatric outcomes.
- Advanced omics technologies facilitate the identification and validation of new GDM biomarkers.
Conclusions:
- Emerging biomarkers represent a significant advancement in GDM diagnostics and prediction.
- Personalized medicine approaches utilizing novel biomarkers can improve feto-maternal outcomes.
- Further research is warranted to translate these biomarkers into clinical practice for GDM management.
Abstract:
Gestational diabetes mellitus (GDM) is a metabolic condition caused by chronic insulin resistance during pregnancy, affecting millions of women globally and causing significant health concerns. Its consequences are far-reaching, associated with poor feto-maternal outcomes. GDM has serious implications on metabolic health in both mother and child. Early diagnosis and management of GDM are crucial to prevent related consequences. Traditional diagnostic and predictive biomarkers for GDM, including oral glucose tolerance test, adiponectin, resistin, etc., have limitations. Recent advances in research have identified novel biomarkers for GDM, offering promising alternatives for early diagnosis and prediction to prevent the associated adverse pediatric outcomes. Emerging biomarkers include microRNAs, cell-free DNA, exosomes, glycolytic intermediates, inflammatory biomarkers (C-reactive protein and interleukin-6), metabolic biomarkers (Betatrophin, fetuin-A, etc.), etc. Emerging bidirectional communication pathway (gut microbiota gut-brain-axis) plays a crucial role in GDM pathophysiology, and could be a promising biomarker. Emerging technologies such as next-generation sequencing, metabolomics, and proteomics have enabled the discovery of novel biomarkers for GDM and related pediatric outcomes. This review aims to summarize the current state of knowledge on emerging biomarkers for GDM, including their diagnostic accuracy, predictive value, and potential clinical applications to improve feto-maternal outcomes by personalized medicine approaches.
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