4.5 Article

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

期刊

ORPHANET JOURNAL OF RARE DISEASES
卷 17, 期 1, 页码 -

出版社

BMC
DOI: 10.1186/s13023-022-02213-z

关键词

Neurodevelopmental disorders; Whole exome sequencing; Whole genome sequencing; Genetic diagnostic; Genetic diagnostic yield

资金

  1. Instituto de Salud Carlos III (COHORTES/Programa de Enfermedades Raras, ENOD)
  2. PERIS-Departament de Salut, Fondo Europeo de Desarrollo Regional (FEDER) una manera de hacer Europa
  3. Agencia de Gestio d'Ajuts Universitaris i de Recerca from the Autonomous Catalan Government [2017 SGR1134]
  4. Fundacion Mutua Madrilena (FundMM_2019)
  5. Fundacion Alicia Koplowitz [AKOPLOWITZ18_001]
  6. CERCA Programme/Generalitat de Catalunya

向作者/读者索取更多资源

This study aims to discuss the impact and advantages of implementing NGS in the diagnosis of NDDs. The results show that NGS technology can better identify pathogenic gene mutations and suggest that NGS should be used as the first-choice diagnostic method for NDDs.
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.

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