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Published on: June 25, 2010
Prenatal Diagnosis of Isovaleric Acidemia From Amniotic Fluid Using Genetic and Biochemical Approaches
Si Ding1, Lili Liang1, Wenjuan Qiu1
1Department of Pediatric Endocrinology and Genetic Metabolism, Xinhua Hospital, Shanghai Institute of Pediatric Research, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Abstract:
Background: Isovaleric acidemia (IVA) is an inborn error of leucine metabolism and different approaches have been applied to its prenatal diagnosis. However, systemic application of a biochemical strategy is rare. To evaluate its reliability and validity, we conducted a retrospective study of our experience with metabolite measurement together with genetic analysis in IVA prenatal diagnosis at a single center. Methods: A total of eight pregnancies whose probands were diagnosed as IVA were referred to our center for prenatal diagnosis. Prenatal data of genetic analysis and metabolite measurement using tandem mass spectrometry (MS/MS) and gas chromatography/mass spectrometry (GC/MS) in amniotic fluid (AF) samples were retrospectively reviewed. Results: Genetic and biochemical results were both available in these eight at-risk fetuses. Among them, two fetuses had higher levels of isovalerylcarnitine (C5) and C5/acetylcarnitine (C2) in AF compared with normal reference range and, thus, were determined to be affected, both of whom were found to carry compound heterogeneous mutations according to genetic analysis. The remaining six fetuses were determined to be unaffected based on a normal AF metabolite profile, except one showed slightly elevated C5 and they were found to be carriers according to genetic analysis. However, the level of isovalerylglycine (IVG) could not be detected at all in both groups. Conclusion: The biochemical analysis, as a quick and convenient method, could be an additional reliable option for the prenatal diagnosis of IVA, especially in families with inconclusive genetic results, and can achieve a more precise diagnosis in conjunction with mutation analysis.
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