Work

Combined Karyotyping, Copy Number Variation Sequencing, and Whole Exome Sequencing in the Prenatal Diagnosis of Congenital Heart Disease: Detection Rates and Phenotypic Associations

Year: 2026

Type: article

Abstract: OBJECTIVE: This study aimed to assess the value of genetic testing in the prenatal congenital heart disease (CHD) diagnosis and evaluate the relationship between genetic variants and prenatal phenotypes. METHODS: A total of 235 fetuses with CHD were classified into three groups: A: isolated simple CHD, B: isolated complex CHD, and C: non-isolated CHD. All patients underwent karyotyping and copy number variation sequencing (CNV-seq), with whole-exome sequencing (WES) performed when indicated. Statistical analyses conducted using IBM SPSS assessed the diagnostic performance of the genetic testing and detection rates across CHD subtypes. RESULTS: Karyotyping and CNV-seq revealed that chromosomal abnormality detection, particularly numerical abnormalities, was significantly associated with extracardiac anomalies (p < 0.05). In contrast, the detection rates of pathogenic/likely pathogenic (P/LP) CNVs (CNV-seq, p = 0.384) and pathogenic gene variants (WES, p = 0.624) did not differ significantly among the three groups. The severity of intracardiac abnormalities, the presence of extracardiac anomalies, and the detection of genetic abnormalities significantly influenced parental decisions regarding pregnancy termination (p < 0.05). The combination of karyotyping and CNV-seq increased the detection rate by 5.11%. In karyotyping/CNV-seq-negative fetuses who underwent WES, WES increased the detection rate by 37.21% (16/43). CONCLUSION: Combined genetic testing significantly improved the detection rate and the detection of chromosomal numerical abnormalities was strongly associated with the presence of extracardiac anomalies. Parental decisions regarding pregnancy continuation were significantly influenced by the severity of intracardiac abnormalities, the presence of extracardiac anomalies, and the identification of genetic abnormalities.

Source: Journal of Clinical Laboratory Analysis

DOI: 10.1002/jcla.70382