| Literature DB >> 33111339 |
Oriane Marmontel1,2, Pierre Antoine Rollat-Farnier3, Anne-Sophie Wozny4, Sybil Charrière2,5, Xavier Vanhoye1, Thomas Simonet3, Nicolas Chatron6, Delphine Collin-Chavagnac4, Séverine Nony1, Sabrina Dumont1, Muriel Mahl4, Chantal Jacobs1, Alexandre Janin1, Cyrielle Caussy2,7, Pierre Poinsot8, Igor Tauveron9, Claire Bardel3, Gilles Millat1, Noël Peretti2,8, Philippe Moulin2,5, Christophe Marçais4, Mathilde Di Filippo1,2.
Abstract
The aim of this study was to provide an efficient tool: reliable, able to increase the molecular diagnosis performance, to facilitate the detection of copy number variants (CNV), to assess genetic risk scores (wGRS) and to offer the opportunity to explore candidate genes. Custom SeqCap EZ libraries, NextSeq500 sequencing and a homemade pipeline enable the analysis of 311 dyslipidemia-related genes. In the training group (48 DNA from patients with a well-established molecular diagnosis), this next-generation sequencing (NGS) workflow showed an analytical sensitivity >99% (n = 532 variants) without any false negative including a partial deletion of one exon. In the prospective group, from 25 DNA from patients without prior molecular analyses, 18 rare variants were identified in the first intention panel genes, allowing the diagnosis of monogenic dyslipidemia in 11 patients. In six other patients, the analysis of minor genes and wGRS determination provided a hypothesis to explain the dyslipidemia. Remaining data from the whole NGS workflow identified four patients with potentially deleterious variants. This NGS process gives a major opportunity to accede to an enhanced understanding of the genetic of dyslipidemia by simultaneous assessment of multiple genetic determinants.Entities:
Keywords: copy number variant; dyslipidemia; genetic risk score; hypercholesterolemia; hypobetalipoproteinemia; molecular diagnosis; targeted next generation sequencing
Year: 2020 PMID: 33111339 DOI: 10.1111/cge.13832
Source DB: PubMed Journal: Clin Genet ISSN: 0009-9163 Impact factor: 4.438