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Postpartum circulating microRNA enhances prediction of future type 2 diabetes in women with previous gestational diabetes.
Joglekar, Mugdha V; Wong, Wilson K M; Ema, Fahmida K; Georgiou, Harry M; Shub, Alexis; Hardikar, Anandwardhan A; Lappas, Martha.
Afiliação
  • Joglekar MV; Diabetes and Islet Biology Group, School of Medicine, Western Sydney University, Campbelltown, NSW, Australia.
  • Wong WKM; Diabetes and Islet Biology Group, Faculty of Medicine and Health, University of Sydney, Camperdown, NSW, Australia.
  • Ema FK; Diabetes and Islet Biology Group, School of Medicine, Western Sydney University, Campbelltown, NSW, Australia.
  • Georgiou HM; Diabetes and Islet Biology Group, Faculty of Medicine and Health, University of Sydney, Camperdown, NSW, Australia.
  • Shub A; Diabetes and Islet Biology Group, Faculty of Medicine and Health, University of Sydney, Camperdown, NSW, Australia.
  • Hardikar AA; Department of Obstetrics and Gynaecology, University of Melbourne, Mercy Hospital for Women, Heidelberg, VIC, Australia.
  • Lappas M; Department of Obstetrics and Gynaecology, University of Melbourne, Mercy Hospital for Women, Heidelberg, VIC, Australia.
Diabetologia ; 64(7): 1516-1526, 2021 07.
Article em En | MEDLINE | ID: mdl-33755745
ABSTRACT
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.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Diabetes Gestacional / Diabetes Mellitus Tipo 2 / MicroRNA Circulante Tipo de estudo: Etiology_studies / Incidence_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Adolescent / Adult / Female / Humans / Newborn / Pregnancy País/Região como assunto: Oceania Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Diabetes Gestacional / Diabetes Mellitus Tipo 2 / MicroRNA Circulante Tipo de estudo: Etiology_studies / Incidence_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Adolescent / Adult / Female / Humans / Newborn / Pregnancy País/Região como assunto: Oceania Idioma: En Ano de publicação: 2021 Tipo de documento: Article