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Objective <p>To evaluate the diagnostic yield and clinical value of a phenotype-driven genomic testing strategy in fetuses with central nervous system (CNS) abnormalities.</p> Methods <p>In this retrospective single-center study, 966 fetuses with CNS abnormalities detected by prenatal ultrasound and/or fetal magnetic resonance imaging were included. All cases underwent copy number variation sequencing (CNV-seq), while karyotyping and trio exome sequencing (trio-ES) were performed based on clinical indications and parental preference. Fetuses were stratified into isolated-single, isolated-complex, and non-isolated subgroups according to CNS involvement and extracranial abnormalities. Diagnostic yields were compared across phenotypic subgroups and common CNS phenotypes.</p> Results <p>Among 966 fetuses with prenatal CNS abnormalities, pathogenic or likely pathogenic (P/LP) variants were identified in 12.63% of cases. CNV-seq had a diagnostic yield of 8.07% (78/966), while trio-ES had a diagnostic yield of 16.32% (70/429) and provided an additional 10.92% yield (44/403) following negative CNV-seq results. Diagnostic yield varied significantly across phenotypic subgroups, with a higher CNV-seq yield in non-isolated cases than in isolated cases (15.41% vs. 4.25%, <i>P</i> &lt; 0.001), and a higher ES yield in isolated-complex cases than in isolated-single cases (32.56% vs. 9.20%, <i>P</i> &lt; 0.001). After excluding mild isolated CNS anomalies, diagnostic yields increased to 15.60% for CNV-seq and 26.67% for ES. In the adjusted cohort, differences among the three subgroups remained significant for CNV-seq (<i>P</i> &lt; 0.001) but not for ES (<i>P</i> = 0.156). Across phenotypes, major structural abnormalities demonstrated substantially higher diagnostic yields than mild or soft markers, with a clear severity-dependent increase observed in ventriculomegaly and head circumference reduction.</p> Conclusion <p>Fetal CNS abnormalities show substantial genetic heterogeneity, and diagnostic yield is closely associated with prenatal imaging phenotypes. A phenotype-driven testing strategy may help prioritize genetic evaluation and improve prenatal counseling for fetuses with CNS abnormalities.</p>

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Genetic diagnostic yield of prenatal testing for fetal central nervous system abnormalities: a phenotype-driven study in a large single-center cohort

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年8月3日

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  • Xinyu Fu,
  • Wei Zhong,
  • Zhengyang Yao,
  • Huimin Gao,
  • Fang Wang,
  • Yan Liu,
  • Yifan Liu,
  • Kai Yang,
  • Yousheng Yan,
  • Chenghong Yin

摘要

Objective

To evaluate the diagnostic yield and clinical value of a phenotype-driven genomic testing strategy in fetuses with central nervous system (CNS) abnormalities.

Methods

In this retrospective single-center study, 966 fetuses with CNS abnormalities detected by prenatal ultrasound and/or fetal magnetic resonance imaging were included. All cases underwent copy number variation sequencing (CNV-seq), while karyotyping and trio exome sequencing (trio-ES) were performed based on clinical indications and parental preference. Fetuses were stratified into isolated-single, isolated-complex, and non-isolated subgroups according to CNS involvement and extracranial abnormalities. Diagnostic yields were compared across phenotypic subgroups and common CNS phenotypes.

Results

Among 966 fetuses with prenatal CNS abnormalities, pathogenic or likely pathogenic (P/LP) variants were identified in 12.63% of cases. CNV-seq had a diagnostic yield of 8.07% (78/966), while trio-ES had a diagnostic yield of 16.32% (70/429) and provided an additional 10.92% yield (44/403) following negative CNV-seq results. Diagnostic yield varied significantly across phenotypic subgroups, with a higher CNV-seq yield in non-isolated cases than in isolated cases (15.41% vs. 4.25%, P < 0.001), and a higher ES yield in isolated-complex cases than in isolated-single cases (32.56% vs. 9.20%, P < 0.001). After excluding mild isolated CNS anomalies, diagnostic yields increased to 15.60% for CNV-seq and 26.67% for ES. In the adjusted cohort, differences among the three subgroups remained significant for CNV-seq (P < 0.001) but not for ES (P = 0.156). Across phenotypes, major structural abnormalities demonstrated substantially higher diagnostic yields than mild or soft markers, with a clear severity-dependent increase observed in ventriculomegaly and head circumference reduction.

Conclusion

Fetal CNS abnormalities show substantial genetic heterogeneity, and diagnostic yield is closely associated with prenatal imaging phenotypes. A phenotype-driven testing strategy may help prioritize genetic evaluation and improve prenatal counseling for fetuses with CNS abnormalities.