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Updated: Nov 21, 2025
One-step Metabolomics: Carbohydrates, Organic and Amino Acids Quantified in a Single Procedure
Published on: June 25, 2010
Noninvasive screening for congenital heart defects using a serum metabolomics approach
Jacopo Troisi1,2,3, Pierpaolo Cavallo4,5, Sean Richards6,7
1Department of Medicine and Surgery and Dentistry, Scuola Medica Salernitana, University of Salerno, Salerno, Italy.
Insights
Maternal serum metabolomics can identify fetal heart anomalies with high accuracy. This blood test offers a promising, operator-independent screening tool for congenital heart defects.
Area of Science:
- Biochemistry
- Genetics
- Medical Diagnostics
Background:
- Congenital heart anomalies account for nearly one-third of all congenital defects.
- Current diagnostic methods like ultrasound are operator-dependent, highlighting the need for improved screening.
- Metabolomics offers a potential avenue for developing more accurate and objective diagnostic tools.
Purpose of the Study:
- To characterize the metabolomic fingerprint of maternal serum in pregnancies with fetal heart anomalies.
- To develop and validate a machine learning model for identifying these anomalies.
- To identify key metabolites associated with fetal heart anomalies.
Main Methods:
- Obtained metabolomic profiles from maternal serum of 350 mothers (280 controls, 70 cases).
- Built and optimized nine individual classification models.
- Developed an ensemble machine learning model based on individual model performance.
Main Results:
- The ensemble model achieved perfect classification for both cases and controls.
- Identified key metabolites including malonic acid, 3-hydroxybutyric acid, methyl glutaric acid, urea, androstenedione, fructose, tocopherol, leucine, and putrescine.
- These metabolites were crucial for distinguishing between affected and unaffected pregnancies.
Conclusions:
- Maternal serum metabolomics reveals a distinct biochemical signature in pregnancies with fetal heart anomalies.
- This approach shows promise as an accurate and sensitive screening tool for congenital heart defects.
- Understanding the associated metabolites and pathways enhances comprehension of the pathophysiology of affected pregnancies.
Objective:
Heart anomalies represent nearly one-third of all congenital anomalies. They are currently diagnosed using ultrasound. However, there is a strong need for a more accurate and less operator-dependent screening method. Here we report a metabolomics characterization of maternal serum in order to describe a metabolomic fingerprint representative of heart congenital anomalies.
Methods:
Metabolomic profiles were obtained from serum of 350 mothers (280 controls and 70 cases). Nine classification models were built and optimized. An ensemble model was built based on the results from the individual models.
Results:
The ensemble machine learning model correctly classified all cases and controls. Malonic, 3-hydroxybutyric and methyl glutaric acid, urea, androstenedione, fructose, tocopherol, leucine, and putrescine were determined as the most relevant metabolites in class separation.
Conclusion:
The metabolomic signature of second trimester maternal serum from pregnancies affected by a fetal heart anomaly is quantifiably different from that of a normal pregnancy. Maternal serum metabolomics is a promising tool for the accurate and sensitive screening of such congenital defects. Moreover, the revelation of the associated metabolites and their respective biochemical pathways allows a better understanding of the overall pathophysiology of affected pregnancies.
