Exome sequencing has higher diagnostic yield compared to simulated disease-specific panels in children with suspected monogenic disorders

Autor: Susan M. White, Natalie P. Thorne, Sebastian Lunke, Clara Gaff, Alison Yeung, Tiong Yang Tan, Oliver James Dillon, Zornitza Stark
Rok vydání: 2018
Předmět:
Zdroj: European Journal of Human Genetics. 26:644-651
ISSN: 1476-5438
1018-4813
Popis: As test costs decline, whole-exome sequencing (WES) has become increasingly used for clinical diagnosis, and now represents the primary alternative to gene panel testing for patients with a suspected genetic disorder. We sought to compare the diagnostic yield of singleton-WES with simulated application of commercial gene panels in children suspected of having a genetically heterogeneous condition. Recruitment, singleton-WES and phenotype-driven variant analysis was completed for 145 paediatric patients. At recruitment, clinicians were required to propose commercial gene panel tests as an alternative to WES and nominate a phenotype-driven candidate gene list. In WES-diagnosed children, three commercial options for each proposed panel were identified and evaluated for hypothetical diagnostic yield assuming 100% analytical sensitivity and specificity. We compared the price of WES with the least costly panel in WES-diagnosed children. In WES-undiagnosed children, we evaluated the exonic coverage of their phenotype-driven gene list using aggregate data. WES diagnoses were made in genes not included in at least one-of-three commercial panels in 42% of cases. Had a panel been selected instead, 23% of WES-diagnosed children would not have been diagnosed. In 26% of cases, the least costly panel option would have been more expensive than WES. Evaluation of WES coverage found that at the most stringent level of 20× coverage, the likelihood of missing a clinically relevant variant in a candidate gene list was maximally 8%. The broader coverage of WES makes it a superior alternative to gene panel testing at similar financial cost for children with suspected complex monogenic phenotypes.
Databáze: OpenAIRE