Metabolomic prediction of fetal congenital heart defect in the first trimester

Objective: The objective of the study was to identify metabolomic markers in maternal first-trimester serum for the detection of fetal congenital heart defects (CHDs).

Study design: Mass spectrometry (direct injection/liquid chromatography and tandem mass spectrometry) and nuclear magnetic resonance spectrometry-based metabolomic analyses were performed between 11 weeks' and 13 weeks 6 days' gestation on maternal serum. A total of 27 CHD cases and 59 controls were compared. There were no known or suspected chromosomal or syndromic abnormalities indicated.

Results: A total of 174 metabolites were identified and quantified using the 2 analytical methods. There were 14 overlapping metabolites between platforms. We identified 123 metabolites that demonstrated significant differences on a univariate analysis in maternal first-trimester serum in CHD vs normal cases. There was a significant disturbance in acylcarnitine, sphingomyelin, and other metabolite levels in CHD pregnancies. Predictive algorithms were developed for CHD detection. High sensitivity (0.929; 95% confidence interval [CI], 0.92-1.00) and specificity (0.932; 95% CI, 0.78-1.00) for CHD detection were achieved (area under the curve, 0.992; 95% CI, 0.973-1.0).

Conclusion: In the first such report, we demonstrated the feasibility of the use of metabolomic developing biomarkers for the first-trimester prediction of CHD. Abnormal lipid metabolism appeared to be a significant feature of CHD pregnancies.