Key result
First-trimester panel of 11 cardiovascular microRNAs predicts gestational diabetes with ~48% sensitivity.
Why the study?
Do cardiovascular disease-associated microRNAs predict the development of Gestational Diabetes Mellitus in first-trimester pregnancies?
Case-Control (n=201)
No
Do cardiovascular disease-associated microRNAs predict the development of Gestational Diabetes Mellitus in first-trimester pregnancies?
Effect estimate: AUC 0.742
p-value: p=<0.001
First-trimester profiling of cardiovascular disease-associated microRNAs, especially when combined with clinical characteristics, offers a promising early screening tool for gestational diabetes mellitus.
Hypothesis-generating for first-trimester miRNA GDM screening; leaves open prospective validation before any clinical use.
= 121) and 80 normal term pregnancies selected with regard to equality of sample storage time. Gene expression of 29 microRNAs was assessed using real-time RT-PCR. Upregulation of 11 microRNAs (miR-1-3p, miR-20a-5p, miR-20b-5p, miR-23a-3p, miR-100-5p, miR-125b-5p, miR-126-3p, miR-181a-5p, miR-195-5p, miR-499a-5p, and miR-574-3p) was observed in pregnancies destinated to develop GDM. Combined screening of all 11 dysregulated microRNAs showed the highest accuracy for the early identification of pregnancies destinated to develop GDM. This screening identified 47.93% of GDM pregnancies at a 10.0% false positive rate (FPR). The predictive model for GDM based on aberrant microRNA expression profile was further improved via the implementation of clinical characteristics (maternal age and BMI at early stages of gestation and an infertility treatment by assisted reproductive technology). Following this, 69.17% of GDM pregnancies were identified at a 10.0% FPR. The effective prediction model specifically for severe GDM requiring administration of therapy involved using a combination of these three clinical characteristics and three microRNA biomarkers (miR-20a-5p, miR-20b-5p, and miR-195-5p). This model identified 78.95% of cases at a 10.0% FPR. The effective prediction model for GDM managed by diet only required the involvement of these three clinical characteristics and eight microRNA biomarkers (miR-1-3p, miR-20a-5p, miR-20b-5p, miR-100-5p, miR-125b-5p, miR-195-5p, miR-499a-5p, and miR-574-3p). With this, the model identified 50.50% of GDM pregnancies managed by diet only at a 10.0% FPR. When other clinical variables such as history of miscarriage, the presence of trombophilic gene mutations, positive first-trimester screening for preeclampsia and/or fetal growth restriction by the Fetal Medicine Foundation algorithm, and family history of diabetes mellitus in first-degree relatives were included in the GDM prediction model, the predictive power was further increased at a 10.0% FPR (72.50% GDM in total, 89.47% GDM requiring therapy, and 56.44% GDM managed by diet only). Cardiovascular disease-associated microRNAs represent promising early biomarkers to be implemented into routine first-trimester screening programs with a very good predictive potential for GDM.
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Hromadníková et al. (2022) conducted a case-control in Gestational Diabetes Mellitus (GDM) (n=201). Dysregulated cardiovascular disease-associated microRNAs vs. Normal term pregnancies (normal expression profile) was evaluated on Early prediction of gestational diabetes mellitus (AUC 0.742, p=<0.001). Combined screening of 11 dysregulated cardiovascular disease-associated microRNAs in the first trimester identified 47.93% of pregnancies destined to develop GDM at a 10.0% false positive rate (AUC 0.742, p<0.001).
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