Fetal growth disorders detection during first trimester gestation through comprehensive maternal circulating DNA profiling.

BACKGROUND

Early diagnosis, close follow-up and timely delivery constitute the main elements for appropriate detection and management of Fetal Growth Disorders (FGD). We hypothesized that fetoplacental FGD-associated alterations can be detected in circulating DNA (cirDNA) samples isolated from maternal blood, as early as the first gestational trimester.

METHODS

Plasma cirDNA was isolated from samples prospectively collected during first trimester gestation (n = 56). Small, Large and Appropriate for Gestational Age (SGA n = 11, LGA n = 18, and AGA n = 29, respectively) status was determined at birth according to weight and gestational age. cirDNA amount, fragmentation, mitochondrial/nuclear ratio and cirDNA methylation profiles were quantified using qPCR-based assays. Machine learning approaches were applied to build a molecular signature for prediction of LGA and SGA. Prediction accuracy was assessed by Receiver-Operating Curve (ROC) analysis, and Positive and Negative Predictive values (PPV and NPV, respectively) were calculated.

RESULTS

Total concentration of plasma cirDNA, cirDNA fragmentation and ratio of mitochondrial/nuclear cirDNA were increased in SGA and LGA compared to AGA pregnancies. Out of the 10 selected loci, we detected 5 genes (HSD2, RASSF1, CYP19A1, IL10, and LEP) showing significant differential methylation differences (p < 0.05) across the SGA, AGA and LGA samples at first trimester. cirDNA marker signature discriminated between FGD and AGA pregnancies with high accuracy (AUC > 0.95), achieving 88.8% PPV and 85.7% NPV.

CONCLUSIONS

Maternal blood cirDNA profiles accurately detects early gestation FGD. The proposed novel marker panel hold great potential for implementation of low invasive approaches for reliable prediction of FGDs, enabling a disruptive path toward precision medicine in FGD.