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Diagnostic yield of next-generation sequencing in 87 families with neurodevelopmental disorders

BACKGROUND: Neurodevelopmental disorders (NDDs) are a group of heterogeneous conditions, which include mainly intellectual disability, developmental delay (DD) and autism spectrum disorder (ASD), among others. These diseases are highly heterogeneous and both genetic and environmental factors play an...

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Detalles Bibliográficos
Autores principales: Álvarez-Mora, María Isabel, Sánchez, Aurora, Rodríguez-Revenga, Laia, Corominas, Jordi, Rabionet, Raquel, Puig, Susana, Madrigal, Irene
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8858550/
https://www.ncbi.nlm.nih.gov/pubmed/35183220
http://dx.doi.org/10.1186/s13023-022-02213-z
Descripción
Sumario:BACKGROUND: Neurodevelopmental disorders (NDDs) are a group of heterogeneous conditions, which include mainly intellectual disability, developmental delay (DD) and autism spectrum disorder (ASD), among others. These diseases are highly heterogeneous and both genetic and environmental factors play an important role in many of them. The introduction of next generation sequencing (NGS) has lead to the detection of genetic variants in several genetic diseases. The main aim of this report is to discuss the impact and advantages of the implementation of NGS in the diagnosis of NDDs. Herein, we report diagnostic yields of applying whole exome sequencing in 87 families affected by NDDs and additional data of whole genome sequencing (WGS) from 12 of these families. RESULTS: The use of NGS technologies allowed identifying the causative gene alteration in approximately 36% (31/87) of the families. Among them, de novo mutation represented the most common cause of genetic alteration found in 48% (15/31) of the patients with diagnostic mutations. The majority of variants were located in known neurodevelopmental disorders genes. Nevertheless, some of the diagnoses were made after the use of GeneMatcher tools which allow the identification of additional patients carrying mutations in THOC2, SETD1B and CHD9 genes. Finally the use of WGS only allowed the identification of disease causing variants in 8% (1/12) of the patients in which previous WES failed to identify a genetic aetiology. CONCLUSION: NGS is more powerful in identifying causative pathogenic variant than conventional algorithms based on chromosomal microarray as first-tier test. Our results reinforce the implementation of NGS as a first-test in genetic diagnosis of NDDs.