Postpartum circulating microRNA enhances prediction of future type 2 diabetes in women with previous gestational diabetes

Mugdha V. Joglekar, Wilson K.M. Wong, Fahmida K. Ema, Harry M. Georgiou, Alexis Shub, Anandwardhan A. Hardikar*, Martha Lappas

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review


Aims/hypothesis: Type 2 diabetes mellitus is a major cause of morbidity and death worldwide. Women with gestational diabetes mellitus (GDM) have greater than a sevenfold higher risk of developing type 2 diabetes in later life. Accurate methods for postpartum type 2 diabetes risk stratification are lacking. Circulating microRNAs (miRNAs) are well recognised as biomarkers/mediators of metabolic disease. We aimed to determine whether postpartum circulating miRNAs can predict the development of type 2 diabetes in women with previous GDM. Methods: In an observational study, plasma samples were collected at 12 weeks postpartum from 103 women following GDM pregnancy. Utilising a discovery approach, we measured 754 miRNAs in plasma from type 2 diabetes non-progressors (n = 11) and type 2 diabetes progressors (n = 10) using TaqMan-based real-time PCR on an OpenArray platform. Machine learning algorithms involving penalised logistic regression followed by bootstrapping were implemented. Results: Fifteen miRNAs were selected based on their importance in discriminating type 2 diabetes progressors from non-progressors in our discovery cohort. The levels of miRNA miR-369-3p remained significantly different (p < 0.05) between progressors and non-progressors in the validation sample set (n = 82; 71 non-progressors, 11 progressors) after adjusting for age and correcting for multiple comparisons. In a clinical model of prediction of type 2 diabetes that included six traditional risk factors (age, BMI, pregnancy fasting glucose, postpartum fasting glucose, cholesterol and triacylglycerols), the addition of the circulating miR-369-3p measured at 12 weeks postpartum improved the prediction of future type 2 diabetes from traditional AUC 0.83 (95% CI 0.68, 0.97) to an AUC 0.92 (95% CI 0.84, 1.00). Conclusions: This is the first demonstration of miRNA-based type 2 diabetes prediction in women with previous GDM. Improved prediction will facilitate early lifestyle/drug intervention for type 2 diabetes prevention. Graphical abstract: [Figure not available: see fulltext.].

Original languageEnglish
Issue number7
Pages (from-to)1516-1526
Number of pages11
Publication statusPublished - Jul 2021


  • Circulating biomarkers
  • Gestational diabetes
  • Machine learning
  • microRNAs
  • Observational cohort
  • OGTT
  • Postpartum
  • Real-time PCR
  • Receiver operating characteristic (ROC) curve
  • Risk prediction
  • Type 2 diabetes

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