Optimizing the Diagnostic Strategy to Identify Genetic Abnormalities in Miscarriage

Introduction The single most common cause of miscarriage is genetic abnormality. Objective We conducted a prospective cohort study to compare the performance of conventional karyotyping and chromosomal microarray analysis (CMA) using array comparative genomic hybridization (array-CGH) and single nuc...

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Veröffentlicht in:Molecular diagnosis & therapy 2021-05, Vol.25 (3), p.351-359
Hauptverfasser: Lee, Jong-Mi, Shin, So Young, Kim, Guk Won, Kim, Woo Jeng, Wie, Jeong Ha, Hong, Subeen, Kang, Dain, Choi, Hayoung, Yim, Jisook, Kim, Yonggoo, Kim, Myungshin, Park, In Yang
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Sprache:eng
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Zusammenfassung:Introduction The single most common cause of miscarriage is genetic abnormality. Objective We conducted a prospective cohort study to compare the performance of conventional karyotyping and chromosomal microarray analysis (CMA) using array comparative genomic hybridization (array-CGH) and single nucleotide polymorphism array (SNP-array) to identify genetic abnormalities in miscarriage specimens. Methods A total of 63 miscarriage specimens were included. Conventional karyotyping, array-CGH, and SNP-array were performed and the results compared. Results Genetic abnormalities were detected in 31 cases (49.2%) by at least one testing modality. Single autosomal trisomy was the most common defect (71.0%), followed by polyploidy (16.1%), multiple aneuploidy (9.7%), and monosomy X (3.2%). Mosaicisms were identified in four cases and confirmed by fluorescence in situ hybridization (FISH) using appropriate probes. SNP-array had a higher detection rate of genetic abnormalities than array-CGH (93.5 vs. 77.4%), and conventional karyotyping had the lowest detection rate (76.0%). SNP-array enabled the detection of all types of genetic abnormalities, including polyploidy. Conclusions Although conventional karyotyping and FISH are still needed, SNP-array represents the first choice for miscarriage because the technique showed excellent performance in the detection of genetic abnormalities and minimized the probability of testing failure as well as time, costs, and labor.
ISSN:1177-1062
1179-2000
DOI:10.1007/s40291-021-00523-9