Yan Wang1, Li Cao2, Dong Liang1, Lulu Meng1, Yun Wu2, Fengchang Qiao1, Xiuqing Ji1, Chunyu Luo1, Jingjing Zhang1, Tianhui Xu1, Bin Yu3, Leilei Wang4, Ting Wang5, Qiong Pan6, Dingyuan Ma1, Ping Hu1, Zhengfeng Xu7. 1. Department of Prenatal Diagnosis, State Key Laboratory of Reproductive Medicine, Obstetrics and Gynecology Hospital affiliated to Nanjing Medical University, Nanjing, China. 2. Department of Ultrasound, State Key Laboratory of Reproductive Medicine, Obstetrics and Gynecology Hospital affiliated to Nanjing Medical University, Nanjing, China. 3. Department of Prenatal Diagnosis at Changzhou Woman and Children Health Hospital affiliated to Nanjing Medical University, Changzhou, China. 4. Department of Lianyungang Maternal and Child Health Hospital, Lianyungang, China. 5. Center for Reproduction and Genetics, Suzhou Hospital affiliated to Nanjing Medical University, Suzhou, China. 6. Laboratory of Clinical Genetics, Department of Prenatal Diagnosis, Huaian Maternal and Child Health Care Hospital, Huaian, China. 7. Department of Prenatal Diagnosis, State Key Laboratory of Reproductive Medicine, Obstetrics and Gynecology Hospital affiliated to Nanjing Medical University, Nanjing, China. Electronic address: zhengfeng_xu_nj@163.com.
Abstract
BACKGROUND: Currently, chromosomal microarray analysis is considered the first-tier test in pediatric care and prenatal diagnosis. However, the diagnostic yield of chromosomal microarray analysis for prenatal diagnosis of congenital heart disease has not been evaluated based on a large cohort. OBJECTIVE: Our aim was to evaluate the clinical utility of chromosomal microarray as the first-tier test for chromosomal abnormalities in fetuses with congenital heart disease. STUDY DESIGN: In this prospective study, 602 prenatal cases of congenital heart disease were investigated using single nucleotide polymorphism array over a 5-year period. RESULTS: Overall, pathogenic chromosomal abnormalities were identified in 125 (20.8%) of 602 prenatal cases of congenital heart disease, with 52.0% of them being numerical chromosomal abnormalities. The detection rates of likely pathogenic copy number variations and variants of uncertain significance were 1.3% and 6.0%, respectively. The detection rate of pathogenic chromosomal abnormalities in congenital heart disease plus additional structural anomalies (48.9% vs 14.3%, P < .0001) or intrauterine growth retardation group (50.0% vs 14.3%, P = .044) was significantly higher than that in isolated congenital heart disease group. Additionally, the detection rate in congenital heart disease with additional structural anomalies group was significantly higher than that in congenital heart disease with soft markers group (48.9% vs 19.8%, P < .0001). No significant difference was observed in the detection rates between congenital heart disease with additional structural anomalies and congenital heart disease with intrauterine growth retardation groups (48.9% vs 50.0%), congenital heart disease with soft markers and congenital heart disease with intrauterine growth retardation groups (19.8% vs 50.0%), or congenital heart disease with soft markers and isolated congenital heart disease groups (19.8% vs 14.3%). The detection rate in fetuses with congenital heart disease plus mild ventriculomegaly was significantly higher than in those with other types of soft markers (50.0% vs 15.6%, P < .05). CONCLUSION: Our study suggests chromosomal microarray analysis is a reliable and high-resolution technology and should be used as the first-tier test for prenatal diagnosis of congenital heart disease in clinical practice.
BACKGROUND: Currently, chromosomal microarray analysis is considered the first-tier test in pediatric care and prenatal diagnosis. However, the diagnostic yield of chromosomal microarray analysis for prenatal diagnosis of congenital heart disease has not been evaluated based on a large cohort. OBJECTIVE: Our aim was to evaluate the clinical utility of chromosomal microarray as the first-tier test for chromosomal abnormalities in fetuses with congenital heart disease. STUDY DESIGN: In this prospective study, 602 prenatal cases of congenital heart disease were investigated using single nucleotide polymorphism array over a 5-year period. RESULTS: Overall, pathogenic chromosomal abnormalities were identified in 125 (20.8%) of 602 prenatal cases of congenital heart disease, with 52.0% of them being numerical chromosomal abnormalities. The detection rates of likely pathogenic copy number variations and variants of uncertain significance were 1.3% and 6.0%, respectively. The detection rate of pathogenic chromosomal abnormalities in congenital heart disease plus additional structural anomalies (48.9% vs 14.3%, P < .0001) or intrauterine growth retardation group (50.0% vs 14.3%, P = .044) was significantly higher than that in isolated congenital heart disease group. Additionally, the detection rate in congenital heart disease with additional structural anomalies group was significantly higher than that in congenital heart disease with soft markers group (48.9% vs 19.8%, P < .0001). No significant difference was observed in the detection rates between congenital heart disease with additional structural anomalies and congenital heart disease with intrauterine growth retardation groups (48.9% vs 50.0%), congenital heart disease with soft markers and congenital heart disease with intrauterine growth retardation groups (19.8% vs 50.0%), or congenital heart disease with soft markers and isolated congenital heart disease groups (19.8% vs 14.3%). The detection rate in fetuses with congenital heart disease plus mild ventriculomegaly was significantly higher than in those with other types of soft markers (50.0% vs 15.6%, P < .05). CONCLUSION: Our study suggests chromosomal microarray analysis is a reliable and high-resolution technology and should be used as the first-tier test for prenatal diagnosis of congenital heart disease in clinical practice.
Authors: Andrew L Dailey-Schwartz; Hanna J Tadros; Mahshid Sababi Azamian; Seema R Lalani; Shaine A Morris; Hugh D Allen; Jeffrey J Kim; Andrew P Landstrom Journal: J Pediatr Date: 2018-08-29 Impact factor: 4.406
Authors: E Bevilacqua; J C Jani; R Chaoui; E-K A Suk; R Palma-Dias; T-M Ko; S Warsof; R Stokowski; K J Jones; F R Grati; M Schmid Journal: Ultrasound Obstet Gynecol Date: 2021-10 Impact factor: 7.299