Prenatal diagnosis and molecular cytogenetic characterization of fetuses with central nervous system anomalies using chromosomal microarray analysis: a seven-year single-center retrospective study

Abstract Few existing reports have investigated the copy number variants (CNVs) in fetuses with central nervous system (CNS) anomalies. To gain further insights into the genotype–phenotype relationship, we conducted chromosomal microarray analysis (CMA) to reveal the pathogenic CNVs (pCNVs) that were associated with fetal CNS anomalies. We enrolled 5,460 pregnant women with different high-risk factors who had undergone CMA. Among them, 57 subjects with fetal CNS anomalies were recruited. Of the subjects with fetal CNS anomalies, 23 were given amniocentesis, which involved karyotype analysis and CMA to detect chromosomal abnormalities. The other 34 cases only underwent CMA detection using fetal abortive tissue. In this study, we identified five cases of chromosome aneuploid and nine cases of pCNVs in the fetuses, with a chromosomal aberration detection rate of 24.56% (14/57). In the 23 cases that were given both karyotype and CMA analysis, one case with trisomy 18 was detected by karyotyping. Moreover, CMA revealed a further three cases of pCNVs, including the 1p36.33p36.31, 7q11.23, and 1q21.1q21.2 microdeletions, with a 13.04% (3/23) increase in CMA yield over the karyotype analysis. Additionally, three cases of trisomy 13, one case of trisomy 21, and six cases of pCNVs were detected in the other 34 fetuses where only CMA was performed. Furthermore, a higher chromosomal aberration detection rate was observed in the extra CNS anomaly group than in the isolated CNS anomaly group (40.91% vs 14.29%). In conclude, several pathogenic CNVs were identified in the fetuses with CNS anomalies using CMA. Among the detected CNVs, ZIC2, GNB1 , and NSUN5 may be the candidate genes that responsible for fetal CNS anomalies. Our findings provides an additional reference for genetic counseling regarding fetal CNS anomalies and offers further insight into the genotype–phenotype relationship.