Assessment of Combined Karyotype Analysis and Chromosome Microarray Analysis in Prenatal Diagnosis: A Cohort Study of 3710 Pregnancies.

IF 1.4 4区生物学 Q4 GENETICS & HEREDITY

Genetics research Pub Date : 2022-01-01 DOI:10.1155/2022/6791439

Jin Wang, Danni Wang, Yan Yin, Yi Deng, Mengling Ye, Ping Wei, Zhuo Zhang, Chun Chen, Shengfang Qin, Xueyan Wang

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引用次数: 1

Abstract

Objective: The current study aimed to compare the characteristics of chromosome abnormalities detected by conventional G-banding karyotyping, chromosome microarray analysis (CMA), or fluorescence in situ hybridization (FISH)/CNVplex analysis and further explore the application value of combined karyotype analysis and CMA in prenatal diagnosis with a larger sample size.

Methods: From March 2019 to March 2021, 3710 amniocentesis samples were retrospectively collected from women who accepted prenatal diagnosis at 16 to 22 + 6 weeks of pregnancy. The pregnant women underwent karyotype analysis and CMA. In the case of fetal chromosomal mosaicism, FISH or CNVplex analysis was utilized for validation.

Results: In total, 3710 G-banding karyotype results and CMA results from invasive prenatal diagnosis were collected. Of these, 201 (5.41%) fetuses with an abnormal karyotype were observed. The CMA analysis showed that the abnormality rate was 9.14% (340/3710). The detection rate of CMA combined with karyotype analysis was 0.35% higher than that of CMA alone and 4.08% higher than that of karyotyping alone. Additionally, 12 cases had abnormal karyotype analysis, despite normal CMA results. To further detect the chromosome mosaicism, we used FISH analysis to correct the karyotype results of case 1. Correspondingly, a total of 157 cases showed abnormal CMA results but normal karyotype analysis. We also found chromosomal mosaicism in 4 cases using CMA. Moreover, CNVplex and CMA demonstrated that representative case 15 was mosaicism for trisomy 2.

Conclusions: Conventional G-banding karyotyping and CMA have their own advantages and limitations. A combination of karyotype analysis and CMA can increase the detection rate of chromosome abnormalities and make up for the limitation of signal detection.

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联合核型分析和染色体微阵列分析在产前诊断中的评估:一项3710例妊娠的队列研究。

目的:本研究旨在比较常规g带核型分析、染色体微阵列分析(CMA)、荧光原位杂交(FISH)/CNVplex分析检测的染色体异常特征，进一步探讨核型分析与CMA联合应用在大样本量产前诊断中的应用价值。方法:2019年3月至2021年3月，回顾性收集妊娠16 ~ 22 + 6周接受产前诊断的孕妇羊膜穿刺术标本3710份。对孕妇进行核型分析和CMA。在胎儿染色体嵌合体的情况下，使用FISH或CNVplex分析进行验证。结果:共收集3710例g带核型结果和有创产前诊断CMA结果。其中，201例(5.41%)胎儿核型异常。CMA分析显示异常率为9.14%(340/3710)。CMA联合核型分析的检出率比单独使用CMA高0.35%，比单独使用核型分析高4.08%。此外，12例患者核型分析异常，尽管CMA结果正常。为了进一步检测染色体嵌合现象，我们使用FISH分析对病例1的核型结果进行校正。157例CMA结果异常，核型分析正常。我们还在4例CMA病例中发现了染色体镶嵌现象。此外，CNVplex和CMA表明代表性病例15是2三体的嵌合。结论:常规g带核型和CMA有各自的优势和局限性。核型分析与CMA相结合可以提高染色体异常的检出率，弥补信号检测的局限性。

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来源期刊

Genetics research 生物-遗传学

自引率

6.70%

发文量

审稿时长

>12 weeks

期刊介绍： Genetics Research is a key forum for original research on all aspects of human and animal genetics, reporting key findings on genomes, genes, mutations and molecular interactions, extending out to developmental, evolutionary, and population genetics as well as ethical, legal and social aspects. Our aim is to lead to a better understanding of genetic processes in health and disease. The journal focuses on the use of new technologies, such as next generation sequencing together with bioinformatics analysis, to produce increasingly detailed views of how genes function in tissues and how these genes perform, individually or collectively, in normal development and disease aetiology. The journal publishes original work, review articles, short papers, computational studies, and novel methods and techniques in research covering humans and well-established genetic organisms. Key subject areas include medical genetics, genomics, human evolutionary and population genetics, bioinformatics, genetics of complex traits, molecular and developmental genetics, Evo-Devo, quantitative and statistical genetics, behavioural genetics and environmental genetics. The breadth and quality of research make the journal an invaluable resource for medical geneticists, molecular biologists, bioinformaticians and researchers involved in genetic basis of diseases, evolutionary and developmental studies.