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

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 la...

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Bibliographic Details
Published in:Diabetologia 2021-07, Vol.64 (7), p.1516-1526
Main Authors: Joglekar, Mugdha V., Wong, Wilson K. M., Ema, Fahmida K., Georgiou, Harry M., Shub, Alexis, Hardikar, Anandwardhan A., Lappas, Martha
Format: Article
Language:English
Subjects:
Adolescent
Adult
Australia
Biomarkers - blood
Cholesterol
Circulating MicroRNA - analysis
Circulating MicroRNA - blood
Cohort Studies
Diabetes
Diabetes mellitus (non-insulin dependent)
Diabetes Mellitus, Type 2 - blood
Diabetes Mellitus, Type 2 - diagnosis
Diabetes, Gestational - blood
Diabetes, Gestational - genetics
Fasting
Female
Follow-Up Studies
Gestational diabetes
Human Physiology
Humans
Infant, Newborn
Internal Medicine
Learning algorithms
Machine learning
Medicine
Medicine & Public Health
Metabolic Diseases
Metabolic disorders
MicroRNAs
miRNA
Morbidity
Observational studies
Postpartum
Postpartum Period - blood
Predictions
Pregnancy
Prognosis
Risk Factors
Womens health
Young Adult
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Summary: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  
ISSN:0012-186X
1432-0428
DOI:10.1007/s00125-021-05429-z