Functional Assessment of Genetic Variants with Outcomes Adapted to Clinical Decision-Making
AuthorThouvenot, P; Ben Yamin, B; Fourriere, L; Lescure, A; Boudier, T; Del Nery, E; Chauchereau, A; Goldgar, DE; Houdayer, C; Stoppa-Lyonnet, D; ...
Source TitlePLoS Genetics
PublisherPUBLIC LIBRARY SCIENCE
University of Melbourne Author/sFourriere-Chea, Lou
AffiliationBiochemistry and Molecular Biology
Document TypeJournal Article
CitationsThouvenot, P., Ben Yamin, B., Fourriere, L., Lescure, A., Boudier, T., Del Nery, E., Chauchereau, A., Goldgar, D. E., Houdayer, C., Stoppa-Lyonnet, D., Nicolas, A. & Millot, G. A. (2016). Functional Assessment of Genetic Variants with Outcomes Adapted to Clinical Decision-Making. PLOS GENETICS, 12 (6), https://doi.org/10.1371/journal.pgen.1006096.
Access StatusOpen Access
Understanding the medical effect of an ever-growing number of human variants detected is a long term challenge in genetic counseling. Functional assays, based on in vitro or in vivo evaluations of the variant effects, provide essential information, but they require robust statistical validation, as well as adapted outputs, to be implemented in the clinical decision-making process. Here, we assessed 25 pathogenic and 15 neutral missense variants of the BRCA1 breast/ovarian cancer susceptibility gene in four BRCA1 functional assays. Next, we developed a novel approach that refines the variant ranking in these functional assays. Lastly, we developed a computational system that provides a probabilistic classification of variants, adapted to clinical interpretation. Using this system, the best functional assay exhibits a variant classification accuracy estimated at 93%. Additional theoretical simulations highlight the benefit of this ready-to-use system in the classification of variants after functional assessment, which should facilitate the consideration of functional evidences in the decision-making process after genetic testing. Finally, we demonstrate the versatility of the system with the classification of siRNAs tested for human cell growth inhibition in high throughput screening.
- Click on "Export Reference in RIS Format" and choose "open with... Endnote".
- Click on "Export Reference in RIS Format". Login to Refworks, go to References => Import References