The Predictive Value of miR-16, -29a and -134 for Early Identification of Gestational Diabetes: A Nested Analysis of the DALI Cohort

Abstract

Early identification of gestational diabetes mellitus (GDM) aims to reduce the risk of adverse maternal and perinatal outcomes. Currently, no circulating biomarker has proven clinically useful for accurate prediction of GDM. In this study, we tested if a panel of small non-coding circulating RNAs could improve early prediction of GDM. We performed a nested case-control study of participants from the European multicenter 'Vitamin D and lifestyle intervention for GDM prevention (DALI)' trial using serum samples from obese pregnant women (BMI ≥ 29 kg/m²) entailing 82 GDM cases (early- and late- GDM), and 41 age- and BMI-matched women with normal glucose tolerance (NGT) throughout pregnancy (controls). Anthropometric, clinical and biochemical characteristics were obtained at baseline (<20 weeks of gestation) and throughout gestation. Baseline serum microRNAs (miRNAs) were measured using quantitative real time PCR (qPCR). Elevated miR-16-5p, -29a-3p, and -134-5p levels were observed in women, who were NGT at baseline and later developed GDM, compared with controls who remained NGT. A combination of the three miRNAs could distinguish later GDM from NGT cases (AUC 0.717, p = 0.001, compared with fasting plasma glucose (AUC 0.687, p = 0.004)) as evaluated by area under the curves (AUCs) using Receiver Operator Characteristics (ROC) analysis. Elevated levels of individual miRNAs or a combination hereof were associated with higher odds ratios of GDM. Conclusively, circulating miRNAs early in pregnancy could serve as valuable predictive biomarkers of GDM.

Keywords: Gestational diabetes mellitus; circulating microRNA; miR-122-5p; miR-134-5p; miR-16-5p; miR-29a-3p; microRNAs; obesity; predictive biomarker; pregnancy; randomized control trial; serum.

Figure 1

Circulating miRNAs are elevated in late GDM cases. Relative mean quantities with standard deviations of serum microRNAs expressed in the three groups (A–D). Data were normalized against the geometric mean of snRNA U6, ath-miR-159 and c.el.miR-39. All indicated p-values were determined by independent t-test on logarithmic transformed data with Bonferroni correction for multiple comparisons.

Figure 2

Predictive capabilities of circulating miRNAs. ROC curves based on miRNA levels. Shown are the three miRNAs distinguishing between GDM cases diagnosed later in pregnancy and NGT cases (A–C) as well as a combination of these miRNAs ((D) 3-miRNA signature, miR-16-5p, -29a-3p and -134-5p, AUC = 0.717, 95% CI 0.60–0.83). Fasting plasma glucose (FPG, AUC = 0.687, 95% CI 0.57–0.80) and 2-h glucose value (2h glucose, AUC = 0.681, 95% CI 0.57–0.80) were evaluated alone or in combination with the 3-miRNA signature.

Figure 3

Odds ratios for the association of miRNAs with GDM. Odds ratio plot showing the predictive effects of either a single miRNA, a combination of these, or miRNAs after adjustment for confounding variables such as maternal age and BMI and offspring sex on GDM diagnosis. Normal glucose tolerant women were compared to women who were diagnosed with GDM later in pregnancy (N = 77–81). BMI: Body mass index.

Figure 4

Predicted targets and pathway enrichment analysis. Predicted targets of the four differentially expressed miRNAs associated with GDM. (A) Venn diagram of predicted targets identified through TargetScan v.7.2. (human). (B) Enrichment analysis of predicted targets common to two or more miRNAs. The size and the color of the circle corresponds to the fold enrichment.