Advancing Prenatal Diagnosis: From Conventional Karyotyping to Genome-Wide CNV Analysis

Advances in genome-wide DNA-based technologies have fundamentally transformed prenatal genetic diagnostics, enabling detection of clinically significant submicroscopic chromosomal abnormalities that are not identifiable by conventional cytogenetic methods. These developments have important implications for the diagnosis and management of pregnancies complicated by fetal structural abnormalities, as they enable more accurate etiological diagnosis, improved prognostic assessment, and more informed clinical decision-making and reproductive counselling.

This narrative review synthesizes contemporary international evidence on prenatal genetic diagnostic approaches, including conventional karyotyping, chromosomal microarray analysis (CMA), and genome-wide sequencing technologies. The review focuses on diagnostic performance, clinical utility, ethical considerations, and implementation within diverse healthcare systems.

Accumulating evidence demonstrates that genome-wide approaches-particularly CMA and sequencing-based methods-provide a higher diagnostic yield in fetuses with structural anomalies, with an incremental yield of approximately 3-5% over conventional karyotyping. This is mainly due to their ability to detect pathogenic copy number variants below the cytogenetic resolution of karyotyping. These technologies improve etiological insight, enhance genotype-phenotype correlation, and support more precise prognostication and reproductive counselling, especially in pregnancies with fetal structural anomalies. Emerging sequencing platforms further expand the diagnostic spectrum by integrating copy number and sequence-level variant detection.

Genome-wide Copy Number Variation (CNV) analysis represents a critical component of contemporary prenatal diagnostics and should be integrated into invasive prenatal testing pathways in accordance with international recommendations. Genome-wide approaches need robust counselling frameworks and equitable health policy implementation to spread. The expense, lack of required experience, and variation in healthcare infrastructure across locations make widespread deployment difficult.