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Application of chromosomal microarray analysis in prenatal diagnosis for fetal abnormalities detected by ultrasonography / 中华医学遗传学杂志
Article in Zh | WPRIM | ID: wpr-335135
Responsible library: WPRO
ABSTRACT
<p><b>OBJECTIVE</b>To analyze the outcome of chromosomal microarray analysis (CMA) in prenatal diagnosis for fetal abnormalities detected by ultrasonography.</p><p><b>METHODS</b>Amniotic fluid samples from 477 pregnancies with abnormal ultrasound findings but without common aneuploidies were detected by CMA with Affymetrix CytoScan 750K arrays. The results were analyzed with ChAS v3.0 software.</p><p><b>RESULTS</b>Among the 477 samples, 24 (5.03%) were detected with pathogenic copy number variations (pCNVs) by CMA. Six (9.68%) among 62 cases with structural fetal abnormalities in multiple organ systems were detected with pCNVs, 11 (7.48%) among 147 cases with a single structural anomaly were detected with pCNVs, and 7 (2.61%) among 268 cases with a soft marker were detected with pCNVs.</p><p><b>CONCLUSION</b>CMA has offered a clear advantage over conventional karyotyping for the detection of fetal chromosomal abnormalities, and can provide an effective diagnostic tool for those with one or more structural abnormalities detected by ultrasound.</p>
Subject(s)
Full text: 1 Database: WPRIM Main subject: Prenatal Diagnosis / Diagnostic Imaging / Embryology / Ultrasonography, Prenatal / Chromosome Aberrations / Chromosome Disorders / Microarray Analysis / Diagnosis / DNA Copy Number Variations / Fetal Diseases Type of study: Diagnostic_studies Limits: Adolescent / Female / Humans / Male / Pregnancy Language: Zh Journal: Chinese Journal of Medical Genetics Year: 2017 Document type: Article
Full text: 1 Database: WPRIM Main subject: Prenatal Diagnosis / Diagnostic Imaging / Embryology / Ultrasonography, Prenatal / Chromosome Aberrations / Chromosome Disorders / Microarray Analysis / Diagnosis / DNA Copy Number Variations / Fetal Diseases Type of study: Diagnostic_studies Limits: Adolescent / Female / Humans / Male / Pregnancy Language: Zh Journal: Chinese Journal of Medical Genetics Year: 2017 Document type: Article