ArticleDiabetes/metabolism research and reviews2025
Early Postpartum Metabolic Heterogeneity Among Women Who Progressed to Type 2 Diabetes After Gestational Diabetes: A Prospective Cohort.
Article in Diabetes/metabolism research and reviews, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Who cites it
1 citing paper in PubMed.
- PREGNANCY DISORDERS AND MATERNAL CONSEQUENCES: Maternal pre-pregnancy risks and postpartum consequences of gestational diabetes.Reproduction (Cambridge, England) · 2025Review
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7 authors.
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Abstract
aimsGestational diabetes mellitus (GDM) poses a significant risk for developing type 2 diabetes mellitus (T2D) and exhibits heterogeneity. However, understanding the link between different types of post-GDM individuals without diabetes and their progression to T2D is crucial to advance personalised medicine approaches. MATERIALS AND
methodsWe employed a discovery-based unsupervised machine learning clustering method to generate clustering models for analysing metabolomics, clinical, and biochemical datasets. For this analysis, we selected 225 women who later developed T2D during the 12-year follow-up period from the cohort of 1010 women who returned to a non-diabetic state at 6-9 weeks (study baseline) after a GDM pregnancy based on 2-h 75 g research OGTTs. The optimal model was selected by assessing Bayesian Information Criterion values, class separation performance, and the potential for clinically distinguishable clusters, accounting for participant prenatal and early postpartum characteristics.
resultsThe selected model comprises three clusters: pancreatic beta cell dysfunction (cluster-β: median HOMA-B 161.3 and median HOMA-IR 3.8), insulin-resistance (cluster-IR: median HOMA-B 630.5 and median HOMA-IR 16.8), and a mixed cluster (cluster-mixed: median HOMA-B 307.2 and median HOMA-IR 8.6). These clusters are distinguishable based on postpartum blood test parameters such as glucose tolerance, HOMA indices, and fasting lipid profiles including triglycerides, leptin, HDL-c, and adiponectin, as well as participant age and BMI. Metabolomic analysis identified unique molecular signatures for each cluster. However, the time to T2D onset was not statistically significant among the three clusters (p = 0.22).
conclusionThis study enhances our understanding of the heterogeneity of early postpartum metabolic profiles that characterise the future onset of T2D diabetes in a diverse cohort of women with GDM, revealing insights into distinct mechanisms and personalised intervention strategies for the prevention of T2D.
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