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Updated: Aug 20, 2025
Biochemical Measurement of Neonatal Hypoxia
Published on: August 24, 2011
Biomarkers for isolated congenital heart disease based on maternal amniotic fluid metabolomics analysis
Xuelian Yuan1,2, Lu Li1,2, Hong Kang1,2
1National Center for Birth Defect Monitoring, Key Laboratory of Birth Defects and Related Diseases of Women and Children, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China.
Insights
Metabolomics analysis of amniotic fluid identified 118 differential metabolites in fetuses with congenital heart disease (CHD). These findings offer potential biomarkers for early detection and understanding of CHD pathogenesis.
Area of Science:
- Biochemistry
- Genetics
- Pediatrics
Background:
- Congenital heart disease (CHD) is a common global birth defect with complex, poorly understood causes.
- Metabolomics offers a promising approach to uncover potential etiological clues and identify diagnostic biomarkers for CHD during pregnancy.
Purpose of the Study:
- To investigate metabolic variations in amniotic fluid of fetuses with CHD compared to controls.
- To identify potential metabolic biomarkers for CHD using untargeted metabolomics.
Main Methods:
- Analyzed 65 amniotic fluid samples (28 CHD cases, 37 controls) from the second and third trimesters.
- Employed untargeted metabolomics technology for comprehensive metabolite profiling.
- Utilized differential comparison and random forest analysis to screen for significant metabolic biomarkers.
Main Results:
- Detected 2472 metabolites, with 118 identified as differentially abundant between CHD cases and controls (FC ≥ 2, P < 0.01, VIP ≥ 1.5).
- Identified PE(MonoMe(11,5)/MonoMe(13,5)), N-feruloylserotonin, and 2,6-di-tert-butylbenzoquinone as potential predictive biomarkers.
- Associated differential metabolites with pathways including aldosterone synthesis, drug metabolism, and nicotinate/nicotinamide metabolism.
Conclusions:
- This study establishes a novel database of metabolic biomarkers for CHD.
- The findings provide mechanistic insights into CHD development.
- Further validation in larger cohorts is recommended to confirm these results.
Introduction:
Congenital heart disease (CHD) is one of the most prevalent birth defects in the world. The pathogenesis of CHD is complex and unclear. With the development of metabolomics technology, variations in metabolites may provide new clues about the causes of CHD and may serve as a biomarker during pregnancy.
Methods:
Sixty-five amniotic fluid samples (28 cases and 37 controls) during the second and third trimesters were utilized in this study. The metabolomics of CHD and normal fetuses were analyzed by untargeted metabolomics technology. Differential comparison and randomForest were used to screen metabolic biomarkers.
Results:
A total of 2472 metabolites were detected, and they were distributed differentially between the cases and controls. Setting the selection criteria of fold change (FC) ≥ 2, P value < 0.01 and variable importance for the projection (VIP) ≥ 1.5, we screened 118 differential metabolites. Within the prediction model by random forest, PE(MonoMe(11,5)/MonoMe(13,5)), N-feruloylserotonin and 2,6-di-tert-butylbenzoquinone showed good prediction effects. Differential metabolites were mainly concentrated in aldosterone synthesis and secretion, drug metabolism, nicotinate and nicotinamide metabolism pathways, which may be related to the occurrence and development of CHD.
Conclusion:
This study provides a new database of CHD metabolic biomarkers and mechanistic research. These results need to be further verified in larger samples.
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