Congenital heart defects (CHDs) are the most important category of congenital anomalies, based on their frequency, potential severity, and health care costs. No screening policy for prenatal CHD is currently in place, and ultrasound is still the most widely used prenatal tool for detecting these abnormalities. Metabolomics is a branch of the “-omics” sciences in which high-throughput techniques are used to identify and quantify small molecules that constitute the metabolome. This prospective study was performed to determine the differences, if any, in the first-trimester maternal metabolomic profile in pregnancies with a chromosomally normal fetus compared with those affected with a CHD and to evaluate metabolite biomarker algorithms for first-trimester prediction of fetal CHD.
Patients were prospectively recruited during 2006 to 2009. Crown-rump length was used to estimate gestational age. Nuchal translucency (NT) thickness was measured for aneuploidy risk estimation. Karyotype examinations were performed to assess chromosomal status. Congenital heart defect status was determined by prenatal or postnatal imaging and based on physical examination. Singleton pregnancies were identified in which the fetus was diagnosed antenatally with an isolated major CHD with available maternal blood samples stored at 11 to 13 weeks’ gestation. The study population included 30 cases with major cardiac defects, and each case was matched with 2 control subjects with no complications. A nuclear magnetic resonance (NMR) platform was used for metabolomic analysis of the serum. A targeted quantitative metabolomics approach was used to analyze the serum samples using a combination of direct injection (DI) mass spectrometry with a reverse-phase liquid chromatography and tandem mass spectrometry (LC-MS/MS) kit. Metabolite concentrations in CHD patients and control subjects were compared.
Metabolomic analyses using NMR and DI/LC-MS/MS were performed for 27 cases of CHD and 59 normal matched control subjects. No significant differences were observed between maternal pregnancy and other demographic characteristics between study and control groups. Neither case nor control fetuses had any known or suspected chromosomal or syndromic abnormalities. A total of 150 metabolites were identified and quantified. Thirty-eight metabolites were quantified by NMR spectroscopy, with 174 distinct metabolites measured by the 2 platforms. On univariate analysis, 118 metabolites from the DI/LC-MS/MS assay showed significant concentration differences in maternal serum in CHD versus control subjects. A similar comparison of metabolite concentrations was performed for only NMR-based metabolomics and found significant differences for 5 metabolites. A clear separation between control and CHD groups was demonstrated (P < 0.0005). When the metabolites were ranked by their contribution to distinguishing CHD and control groups, several acylcarnitines, such as hydroxypropionylcarnitine and sphingomyelin, were the most discriminating metabolites for separating CHD cases from control subjects; these metabolites were reduced in CHD cases compared with the control subjects. Acetone, ethanol, acetate, and pyruvate were the most discriminating metabolites using NMR analysis. 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).
Using DI/LC-MS/MS and NMR metabolomic platforms, numerous metabolites in maternal serum distinguished chromosomally normal versus first-trimester CHD cases. The principal metabolite group was the acylcarnitines, which represent intermediates involved in the transport and metabolism of fatty acids in the mitochondria. C3-OH, C5:1-DC, and C14:2OH were highly accurate predictors of CHD status. Metabolites identified by the NMR platform alone provided only limited diagnostic accuracy. The combination of metabolite markers with NT measurement for the detection of CHD did not add any benefit above metabolites alone. A limited number of metabolites appear to have significant diagnostic accuracy for the biochemical prediction of CHD in the first-trimester fetus.