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Updated: Jan 30, 2026

Genotyping Single Nucleotide Polymorphisms in the Mitochondrial Genome by Pyrosequencing
Published on: February 10, 2023
Single-nucleotide polymorphism-based chromosomal microarray analysis provides clues and insights into disease
Objective:
Chromosomal microarray analysis (CMA) is the modality of choice for prenatal diagnosis in pregnancy with fetal malformation, as it has a high diagnostic yield for microdeletion/duplication syndromes. The aim of this study was to demonstrate the additional utility of single-nucleotide polymorphism (SNP)-based CMA in diagnosing monogenic diseases, imprinting disorders and uniparental disomy (UPD).
Methods:
CMA was performed using Affymetrix CytoScan array, for all indications in 6995 pregnancies, at a tertiary referral hospital from November 2013 to June 2018. We describe four cases that had a CMA result that provided a more comprehensive understanding of the complex genetic mechanisms underlying the clinical presentation.
Results:
In the first fetus, CMA was performed due to intrauterine growth restriction and revealed a 75 kbp maternally inherited microdeletion encompassing the Bloom syndrome gene (BLM). A diagnosis of Bloom syndrome was made upon identifying a paternally inherited common Ashkenazi founder mutation. In the second case, CMA was performed due to severely abnormal maternal serum analytes and revealed a deletion in 14q32.2q32.31 on the maternally inherited copy, leading to a diagnosis of Kagami-Ogata syndrome, which is an imprinting disorder. In the third case, amniocentesis was performed because of late-onset fetal macrosomia and mild polyhydramnios. CMA detected a deletion encompassing the locus of Prader-Willi/Angelman syndrome. In the fourth case, amniocentesis was performed due to maternal cytomegalovirus seroconversion. Maternal UPD of the entire long arm of chromosome 11 was detected.
Conclusion:
Prenatal CMA, based on oligo and SNP platforms, increases the diagnostic yield and enables a wider spectrum of disorders to be detected through the identification of complex genetic etiologies beyond only copy number variants. Copyright © 2019 ISUOG. Published by John Wiley & Sons Ltd.
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