Validation of low‐pass genome sequencing for prenatal diagnosis

Abstract

ObjectiveChromosomal microarray (CMA), while considered the gold standard for detecting copy number variants (CNVs) in prenatal diagnostics, has its limitations, including the necessity to replace aging microarray equipment, low throughput, a static design, and an inefficient multi‐day workflow. This study evaluates the feasibility of low‐pass genome sequencing (LP‐GS) as a potential replacement for CMA in prenatal diagnostics.MethodsWe comprehensively compared LP‐GS at 10x and 5x average depths with CMA in a prenatal laboratory. We examined parameters, including concordance, sensitivity, specificity, workflow efficiency, and cost‐effectiveness.ResultsWe found a high degree of agreement between LP‐GS and CMA for detecting CNVs and absence of heterozygosity. Furthermore, compared to CMA, LP‐GS increased workflow efficiency and proved to be cost‐neutral at 10x and cost‐effective at 5x.ConclusionOur study suggests that LP‐GS is a promising alternative to CMA in prenatal diagnostics, offering advantages, including a more efficient workflow and scalability for larger testing volumes. Importantly, for clinical laboratories that have adopted next‐generation sequencing in a separate capacity, LP‐GS facilitates a unified NGS‐centric approach, enabling workflow consolidation. By offering a single, streamlined platform for detecting a broad range of genetic variants, LP‐GS may represent a critical step toward enhancing the diagnostic capabilities of prenatal laboratories.

Highlights of the 27th ISPD annual conference hosted in the historic and atmospheric city of Edinburgh

“…7 Another paper highlights the improvements in the detection of metabolic conditions when sequencing fetuses with abnormalities, 8 and a second study considers whether low pass sequencing should replace microarray testing. 9 It is heartening to see that the large amounts of data being generated by carefully curated mother, father and fetal trios in the prenatal space is driving improvements in phenotype-driven tools such as expansion of the Human Phenotype Ontology for example,. 10 As many jurisdictions implement sequencing services it is important that we consider the patient experience and learn from their feedback to appropriately improve care delivery.…”