Actionable Genes, Core Databases, and Locus‐Specific Databases. Issue 12 (26th September 2016)

• Record Type: Journal Article
• Authors: Pinard, Amélie; Miltgen, Morgane; Blanchard, Arnaud; Mathieu, Hélène; Desvignes, Jean‐Pierre; Salgado, David; Fabre, Aurélie; Arnaud, Pauline; Barré, Laura; Krahn, Martin; Grandval, Philippe; Olschwang, Sylviane; Zaffran, Stéphane; Boileau, Catherine; Béroud, Christophe; Collod‐Béroud, Gwenaëlle
• Is Part Of: Human mutation. Volume 37:Issue 12(2016)
• Page Start: 1299
• Page End: 1307
• Publication Date: 2016-09-26
• Subjects: secondary variant -- actionable genes -- LSDB -- databases -- NGS; Human chromosome abnormalities -- Periodicals; Mutation (Biology) -- Periodicals; 616.04205
• DOI: 10.1002/humu.23112
• Languages: English
• ISSNs: 1059-7794

Abstract

Abstract : Adoption of next generation sequencing in a diagnostic context raise numerous questions regarding identification and reporting of secondary variants (SVs) in actionable genes. Here, we wondered if Locus Specific databases (LSDBs) could advance the interpretation of missense variants as they can provide a wealth of information and enable classifying variants. Thanks to a use case, we demonstrated LSDBs' benefits to annotate SVs and minimize over interpretation of mutations because of their efficient curation process and collection of unpublished data. ABSTRACT: Adoption of next‐generation sequencing (NGS) in a diagnostic context raises numerous questions with regard to identification and reports of secondary variants (SVs) in actionable genes. To better understand the whys and wherefores of these questioning, it is necessary to understand how they are selected during the filtering process and how their proportion can be estimated. It is likely that SVs are underestimated and that our capacity to label all true SVs can be improved. In this context, Locus‐specific databases (LSDBs) can be key by providing a wealth of information and enabling classifying variants. We illustrate this issue by analyzing 318 SVs in 23 actionable genes involved in cancer susceptibility syndromes identified through sequencing of 572 participants selected for a range of atherosclerosis phenotypes. Among these 318 SVs, only 43.4% are reported in Human Gene Mutation Database (HGMD) Professional versus 71.4% in LSDB. In addition, 23.9% of HGMD Professional variants are reported as pathogenic versus 4.8% for LSDB. These data underline the benefits of LSDBs to annotate SVs and minimize overinterpretation of mutations thanks to their efficient curation process and collection of unpublished data.