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Whole-genome sequencing of patients with rare diseases in a national health system

Authors :
Turro, Ernest
Astle, William J.
Megy, Karyn
Gräf, Stefan
Greene, Daniel
Shamardina, Olga
Allen, Hana Lango
Sanchis-Juan, Alba
Frontini, Mattia
Thys, Chantal
Stephens, Jonathan
Mapeta, Rutendo
Burren, Oliver S.
Downes, Kate
Haimel, Matthias
Tuna, Salih
Deevi, Sri V. V.
Aitman, Timothy J.
Bennett, David L.
Calleja, Paul
Carss, Keren
Caulfield, Mark J.
Chinnery, Patrick F.
Dixon, Peter H.
Gale, Daniel P.
James, Roger
Koziell, Ania
Laffan, Michael A.
Levine, Adam P.
Maher, Eamonn R.
Markus, Hugh S.
Morales, Joannella
Morrell, Nicholas W.
Mumford, Andrew D.
Ormondroyd, Elizabeth
Rankin, Stuart
Rendon, Augusto
Richardson, Sylvia
Roberts, Irene
Roy, Noemi B. A.
Saleem, Moin A.
Smith, Kenneth G. C.
Stark, Hannah
Tan, Rhea Y. Y.
Themistocleous, Andreas C.
Thrasher, Adrian J.
Watkins, Hugh
Webster, Andrew R.
Wilkins, Martin R.
Williamson, Catherine
Whitworth, James
Humphray, Sean
Bentley, David R.
Kingston, Nathalie
Walker, Neil
Bradley, John R.
Ashford, Sofie
Penkett, Christopher J.
Freson, Kathleen
Stirrups, Kathleen E.
Raymond, F. Lucy
Ouwehand, Willem H.
Peacock, Andrew
Hague, Rosie
Maxwell, Heather
Muir, Keith W.
Tait, R. Campbell
Thomas, Moira J.
Publication Year :
2020
Publisher :
Nature Research, 2020.

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.

Details

Language :
English
ISSN :
00280836
Database :
OpenAIRE
Accession number :
edsair.core.ac.uk....35e481d94ae2b10c2fa5731f96f98110