TY - JOUR
T1 - Whole-genome sequencing of patients with rare diseases in a national health system
AU - NIHR BioResource for the 100,000 Genomes Project
AU - Turro, Ernest
AU - Astle, William J.
AU - Megy, Karyn
AU - Gräf, Stefan
AU - Greene, Daniel
AU - Shamardina, Olga
AU - Allen, Hana Lango
AU - Sanchis-Juan, Alba
AU - Frontini, Mattia
AU - Thys, Chantal
AU - Stephens, Jonathan
AU - Mapeta, Rutendo
AU - Burren, Oliver S.
AU - Downes, Kate
AU - Haimel, Matthias
AU - Tuna, Salih
AU - Deevi, Sri V.V.
AU - Aitman, Timothy J.
AU - Bennett, David L.
AU - Calleja, Paul
AU - Carss, Keren
AU - Caulfield, Mark J.
AU - Chinnery, Patrick F.
AU - Dixon, Peter H.
AU - Gale, Daniel P.
AU - James, Roger
AU - Koziell, Ania
AU - Laffan, Michael A.
AU - Levine, Adam P.
AU - Maher, Eamonn R.
AU - Markus, Hugh S.
AU - Morales, Joannella
AU - Morrell, Nicholas W.
AU - Mumford, Andrew D.
AU - Ormondroyd, Elizabeth
AU - Rankin, Stuart
AU - Rendon, Augusto
AU - Richardson, Sylvia
AU - Bennett, David L.
AU - Bueser, Teofila
AU - Carr-White, Gerald
AU - Flinter, Frances A.
AU - Irving, Melita
AU - Josifova, Dragana
AU - Koziell, Ania
AU - Mohammed, Shehla N.
AU - Thomas, Ellen
AU - Traylor, Matthew
AU - Trembath, Richard
AU - Williamson, Catherine
PY - 2020/7/2
Y1 - 2020/7/2
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85086777024&partnerID=8YFLogxK
U2 - 10.1038/s41586-020-2434-2
DO - 10.1038/s41586-020-2434-2
M3 - Article
C2 - 32581362
AN - SCOPUS:85086777024
SN - 0028-0836
VL - 583
SP - 96
EP - 102
JO - Nature
JF - Nature
IS - 7814
ER -