| Literature DB >> 32581362 |
Ernest Turro1,2,3, William J Astle4,5, Karyn Megy6,7, Stefan Gräf6,7,8, Daniel Greene6,4, Olga Shamardina6,7, Hana Lango Allen6,7, Alba Sanchis-Juan6,7, Mattia Frontini6,5,9, Chantal Thys10, Jonathan Stephens6,7, Rutendo Mapeta6,7, Oliver S Burren8,11, Kate Downes6,7, Matthias Haimel6,7,8, Salih Tuna6,7, Sri V V Deevi6,7, Timothy J Aitman12,13, David L Bennett14,15, Paul Calleja16, Keren Carss6,7, Mark J Caulfield17,18, Patrick F Chinnery7,19,20, Peter H Dixon21, Daniel P Gale22,23, Roger James6,7, Ania Koziell24,25, Michael A Laffan26,27, Adam P Levine22, Eamonn R Maher28,29,30, Hugh S Markus31, Joannella Morales32, Nicholas W Morrell7,8, Andrew D Mumford33,34, Elizabeth Ormondroyd15,35, Stuart Rankin16, Augusto Rendon6,17, Sylvia Richardson4, Irene Roberts15,36,37, Noemi B A Roy15,36,38, Moin A Saleem39,40, Kenneth G C Smith8,11, Hannah Stark7,41, Rhea Y Y Tan31, Andreas C Themistocleous14, Adrian J Thrasher42, Hugh Watkins35,38,43, Andrew R Webster44,45, Martin R Wilkins46, Catherine Williamson21,47, James Whitworth28,29,30, Sean Humphray48, David R Bentley48, Nathalie Kingston6,7, Neil Walker6,7, John R Bradley7,8,29,49,50, Sofie Ashford7,41, Christopher J Penkett6,7, Kathleen Freson10, Kathleen E Stirrups6,7, F Lucy Raymond51,52, Willem H Ouwehand53,54,55,56,57.
Abstract
Most patients with rare diseases do not receive a molecular diagnosis and the aetiological variants and causative genes for more than half such disorders remain to be discovered1. Here we used whole-genome sequencing (WGS) in a national health system to streamline diagnosis and to discover unknown aetiological variants in the coding and non-coding regions of the genome. We generated WGS data for 13,037 participants, of whom 9,802 had a rare disease, and provided a genetic diagnosis to 1,138 of the 7,065 extensively phenotyped participants. We identified 95 Mendelian associations between genes and rare diseases, of which 11 have been discovered since 2015 and at least 79 are confirmed to be aetiological. By generating WGS data of UK Biobank participants2, we found that rare alleles can explain the presence of some individuals in the tails of a quantitative trait for red blood cells. Finally, we identified four novel non-coding variants that cause disease through the disruption of transcription of ARPC1B, GATA1, LRBA and MPL. Our study demonstrates a synergy by using WGS for diagnosis and aetiological discovery in routine healthcare.Entities:
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Year: 2020 PMID: 32581362 PMCID: PMC7610553 DOI: 10.1038/s41586-020-2434-2
Source DB: PubMed Journal: Nature ISSN: 0028-0836 Impact factor: 49.962