Identification of clinically actionable variants from genome sequencing of families with congenital heart disease View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2018-10-08

AUTHORS

Dimuthu Alankarage, Eddie Ip, Justin O. Szot, Jacob Munro, Gillian M. Blue, Katrina Harrison, Hartmut Cuny, Annabelle Enriquez, Michael Troup, David T. Humphreys, Meredith Wilson, Richard P. Harvey, Gary F. Sholler, Robert M. Graham, Joshua W. K. Ho, Edwin P. Kirk, Nicholas Pachter, Gavin Chapman, David S. Winlaw, Eleni Giannoulatou, Sally L. Dunwoodie

ABSTRACT

PURPOSE: Congenital heart disease (CHD) affects up to 1% of live births. However, a genetic diagnosis is not made in most cases. The purpose of this study was to assess the outcomes of genome sequencing (GS) of a heterogeneous cohort of CHD patients. METHODS: Ninety-seven families with probands born with CHD requiring surgical correction were recruited for genome sequencing. At minimum, a proband-parents trio was sequenced per family. GS data were analyzed via a two-tiered method: application of a high-confidence gene screen (hcCHD), and comprehensive analysis. Identified variants were assessed for pathogenicity using the American College of Medical Genetics and Genomics-Association for Molecular Pathology (ACMG-AMP) guidelines. RESULTS: Clinically relevant genetic variants in known and emerging CHD genes were identified. The hcCHD screen identified a clinically actionable variant in 22% of families. Subsequent comprehensive analysis identified a clinically actionable variant in an additional 9% of families in genes with recent disease associations. Overall, this two-tiered approach provided a clinically relevant variant for 31% of families. CONCLUSIONS: Interrogating GS data using our two-tiered method allowed identification of variants with high clinical utility in a third of our heterogeneous cohort. However, association of emerging genes with CHD etiology, and development of novel technologies for variant assessment and interpretation, will increase diagnostic yield during future reassessment of our GS data. More... »

PAGES

1-10

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/s41436-018-0296-x

DOI

http://dx.doi.org/10.1038/s41436-018-0296-x

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1107377847

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/30293987


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