Diagnostic yield and treatment impact of whole-genome sequencing in paediatric neurological disorders
- PMID: 33244750
- DOI: 10.1111/dmcn.14722
Diagnostic yield and treatment impact of whole-genome sequencing in paediatric neurological disorders
Abstract
Aim: To investigate the diagnostic yield and treatment impact of whole-genome sequencing (WGS) in patients with paediatric neurological disorders.
Method: From January 2016 to December 2019, paediatric patients who had suspected genetic neurological disorders were assessed using WGS. The phenotypes of eligible patients were divided into four groups: patients with neurodevelopmental disorders; patients with epilepsy; patients with neuromuscular disorders; and patients with movement disorders.
Results: A total of 214 consecutive patients (128 males, 86 females) underwent WGS. The mean (SD) age of disease onset was 13.8 (27.6) months (range 1d-15y 5mo). The mean (SD) age at which WGS was performed was 71.7 (58.9) months (range 8d-18y). A molecular diagnosis was reported in 43.9% of patients. The highest diagnostic rate was achieved in 62.5% of patients with neuromuscular disorders, 47.5% of patients with epilepsy, 41.1% of patients with neurodevelopment disorders, and 15.4% of patients with movement disorders. All 94 patients with a WGS diagnosis were given access to genetic counselling and 23.4% of patients had immediate changes in treatment strategies after undergoing WGS.
Interpretation: WGS allows paediatric neurologists to integrate genomic data into their diagnosis and adjust management strategies for a range of clinical and genetically heterogeneous disease entities to improve the clinical outcomes of patients. In our cohort, the diagnosis of a significant proportion of patients was reached through WGS (43.9%). Clinicians could use these results to directly guide the management of their patients and improve their clinical outcomes (23.4%). What this paper adds For selected children in our cohort, the diagnostic yield of whole-genome sequencing (WGS) was 43.9%. WGS can be used to expand our knowledge of phenotype-genotype variations.
© 2020 Mac Keith Press.
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