Details

Autor(en) / Beteiligte

• Thomson, Kate L.
• Ormondroyd, Elizabeth
• Harper, Andrew R.
• Dent, Tim
• McGuire, Karen
• Baksi, John
• Blair, Edward
• Brennan, Paul
• Buchan, Rachel
• Bueser, Teofila
• Campbell, Carolyn
• Carr-White, Gerald
• Cook, Stuart
• Daniels, Matthew
• Deevi, Sri V.V.
• Goodship, Judith
• Hayesmoore, Jesse B.G.
• Henderson, Alex
• Lamb, Teresa
• Prasad, Sanjay
• Rayner-Matthews, Paula
• Robert, Leema
• Sneddon, Linda
• Stark, Hannah
• Walsh, Roddy
• Ware, James S.
• Farrall, Martin
• Watkins, Hugh C.

Titel

Analysis of 51 proposed hypertrophic cardiomyopathy genes from genome sequencing data in sarcomere negative cases has negligible diagnostic yield

Ist Teil von

• Genetics in medicine, 2019-07, Vol.21 (7), p.1576-1584

Ort / Verlag

United States: Elsevier Inc

Erscheinungsjahr

2019

Quelle

MEDLINE

Beschreibungen/Notizen

• Increasing numbers of genes are being implicated in Mendelian disorders and incorporated into clinical test panels. However, lack of evidence supporting the gene-disease relationship can hinder interpretation. We explored the utility of testing 51 additional genes for hypertrophic cardiomyopathy (HCM), one of the most commonly tested Mendelian disorders. Using genome sequencing data from 240 sarcomere gene negative HCM cases and 6229 controls, we undertook case-control and individual variant analyses to assess 51 genes that have been proposed for HCM testing. We found no evidence to suggest that rare variants in these genes are prevalent causes of HCM. One variant, in a single case, was categorized as likely to be pathogenic. Over 99% of variants were classified as a variant of uncertain significance (VUS) and 54% of cases had one or more VUS. For almost all genes, the gene-disease relationship could not be validated and lack of evidence precluded variant interpretation. Thus, the incremental diagnostic yield of extending testing was negligible, and would, we propose, be outweighed by problems that arise with a high rate of uninterpretable findings. These findings highlight the need for rigorous, evidence-based selection of genes for clinical test panels.