The efficacy of genomic sequencing as a first trimester screening for neurodevelopmental disorders

by time news

Genome sequencing (GS) is a method capable of identifying new diagnoses for patients who remain undiagnosed after routine diagnostic procedures. As part of a study whose findings were recently published in the European journal of human genetics, the researchers wanted to investigate whether GS is a better genetic test as a diagnostic tool in the first trimester screening, compared to the standard diagnostic methods (standard of care – SOC).

More on a similar matter

In this study, the researchers sought to evaluate the technical and clinical validity of GS, in patients with neurodevelopmental disorders (NDD). The researchers were based on both GS and exome sequencing. The current study included 150 patient-parent triplets. The primary outcome of this study was diagnostic yield calculated based on disease-causing variants affecting the exonic sequence of known NDD genes.

Results from the study demonstrated that GSJ(30%, n = 45) and to SOCJ(28.7%, n = 43) had a similar diagnostic yield. All 43 diagnoses obtained by the SOC test were also identified by GS. However, SOC required multiple tests to arrive at these diagnoses. GS yielded 2 more definitive and 4 possible diagnoses than SOC (35 vs. 31, respectively). We note that these 6 variations, which were identified with the help of GS and not with the help of SOC, were copy number variants (CNV).

The results of this study show that GS has technical and clinical validity as a routine genetic test as part of a first trimester screening and to diagnose patients with NDD. Although the additional diagnostic yield obtained from performing GS is limited, GS comprehensively identified all diagnoses in a single trial, suggesting that GS is a more convenient genetic diagnostic tool.

source:

van der Sanden, B.P.G.H., Schobers, G., Corominas Galbany, J. et al. The performance of genome sequencing as a first-tier test for neurodevelopmental disorders. Eur J Hum Genet 31, 81–88 (2023). https://doi.org/10.1038/s41431-022-01185-9

You may also like

Leave a Comment