Design
Gestational diabetes mellitus (GDM) is one of the most common pregnancy complications and its prevalence is constantly rising worldwide. Diagnosis is commonly in the late second or early third trimester of pregnancy, though the development of GDM starts early; hence, first-trimester diagnosis is feasible.
Objective
Our objective was to identify microRNAs that best distinguish GDM samples from those of healthy pregnant women and to evaluate the predictive value of microRNAs for GDM detection in the first trimester.
Methods
We investigated the abundance of circulating microRNAs in the plasma of pregnant women in their first trimester. Two populations were included in the study to enable population-specific as well as cross-population inspection of expression profiles. Each microRNA was tested for differential expression in GDM vs control samples, and their efficiency for GDM detection was evaluated using machine-learning models.
Results
Two upregulated microRNAs (miR-223 and miR-23a) were identified in GDM vs the control set, and validated on a new cohort of women. Using both microRNAs in a logistic-regression model, we achieved an AUC value of 0.91. We further demonstrated the overall predictive value of microRNAs using several types of multivariable machine-learning models that included the entire set of expressed microRNAs. All models achieved high accuracy when applied on the dataset (mean AUC = 0.77). The significance of the classification results was established via permutation tests.
Conclusions
Our findings suggest that circulating microRNAs are potential biomarkers for GDM in the first trimester. This warrants further examination and lays the foundation for producing a novel early non-invasive diagnostic tool for GDM.
Data availabilitySummary statistics generated by COVID-19 Host Genetics Initiative are available online (https://www.covid19hg.org/results/r6/). The analyses described here use the freeze 6 data. The COVID-19 Host Genetics Initiative continues to regularly release new data freezes. Summary statistics for samples from individuals of non-European ancestry are not currently available owing to the small individual sample sizes of these groups, but the results for 23 loci lead variants are reported in Supplementary Table 3. Individual-level data can be requested directly from the authors of the contributing studies, listed in Supplementary Table 1.
Highlights
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