Understanding Pathogenic Detection Rates of CNVs in Prenatal Diagnosis: Insights from a Cohort Study

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Abstract

The current study aimed to explore the clinical utility of CNV-seq in prenatal diagnosis by comparing the pathogenic detection rates of copy number variants (CNVs) in pregnant women who underwent amniocentesis for various indications and across different CNV fragment sizes. A total of 1,118 pregnant women who received CNV-seq testing were included in the cohort and categorized into eight groups (Groups A to H) based on their testing indications, with the mixed group (Group H) serving as the reference. The top three groups with the highest pathogenic detection rates were high-risk NIPT (Group A), parental chromosomal abnormalities (Group D), and high-risk trisomy 18 (Group F), with detection rates of 92.16% (141/153), 80% (4/5), and 70% (14/20), respectively. The pathogenic CNV detection rate in our reference group (Group H) was 69.02% (127/184). A binary logistic regression analysis comparing the other seven groups against Group H showed that the detection rate in Group A was significantly higher than that in Group H (P < 0.05), while Groups B, C, E, and G had significantly lower detection rates. Furthermore, based on CNV fragment size, cutoffs were established at 1 Mb and 5 Mb, and the study cohort was further divided into four groups (Groups I to IV). Using the group with multiple CNVs (Group IV) as the reference, the pathogenic detection rates for each group were calculated. Binary logistic regression analysis revealed that Group I had a significantly lower detection rate than Group IV (P < 0.05), while Group III exhibited a significantly higher detection rate (P < 0.05). These findings suggest that abnormal NIPT results are often associated with a higher pathogenic detection rate, and larger CNV fragments exceeding 5 Mb are more likely to be pathogenic. This study provides crucial insights into the clinical application of CNV-seq in prenatal diagnosis, emphasizing the importance of abnormal NIPT results and CNV fragment size in clinical interpretation, thereby facilitating more accurate prenatal risk assessment.

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