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Whole-genome sequencing of patients with rare diseases in a national health system
Nature ( IF 50.5 ) Pub Date : 2020-06-24 , DOI: 10.1038/s41586-020-2434-2
Ernest Turro 1, 2, 3 , William J Astle 3, 4 , Karyn Megy 1, 2 , Stefan Gräf 1, 2, 5 , Daniel Greene 1, 3 , Olga Shamardina 1, 2 , Hana Lango Allen 1, 2 , Alba Sanchis-Juan 1, 2 , Mattia Frontini 1, 4, 6 , Chantal Thys 7 , Jonathan Stephens 1, 2 , Rutendo Mapeta 1, 2 , Oliver S Burren 5, 8 , Kate Downes 1, 2 , Matthias Haimel 1, 2, 5 , Salih Tuna 1, 2 , Sri V V Deevi 1, 2 , Timothy J Aitman 9, 10 , David L Bennett 11, 12 , Paul Calleja 13 , Keren Carss 1, 2 , Mark J Caulfield 14, 15 , Patrick F Chinnery 2, 16, 17 , Peter H Dixon 18 , Daniel P Gale 19, 20 , Roger James 1, 2 , Ania Koziell 21, 22 , Michael A Laffan 23, 24 , Adam P Levine 19 , Eamonn R Maher 25, 26, 27 , Hugh S Markus 28 , Joannella Morales 29 , Nicholas W Morrell 2, 5 , Andrew D Mumford 30, 31 , Elizabeth Ormondroyd 12, 32 , Stuart Rankin 13 , Augusto Rendon 1, 14 , Sylvia Richardson 3 , Irene Roberts 12, 33, 34 , Noemi B A Roy 12, 33, 35 , Moin A Saleem 36, 37 , Kenneth G C Smith 5, 8 , Hannah Stark 2, 38 , Rhea Y Y Tan 28 , Andreas C Themistocleous 11 , Adrian J Thrasher 39 , Hugh Watkins 32, 35, 40 , Andrew R Webster 41, 42 , Martin R Wilkins 43 , Catherine Williamson 18, 44 , James Whitworth 25, 26, 27 , Sean Humphray 45 , David R Bentley 45 , , Nathalie Kingston 1, 2 , Neil Walker 1, 2 , John R Bradley 2, 5, 26, 46, 47 , Sofie Ashford 2, 38 , Christopher J Penkett 1, 2 , Kathleen Freson 7 , Kathleen E Stirrups 1, 2 , F Lucy Raymond 2, 25 , Willem H Ouwehand 1, 2, 4, 6, 48
Affiliation  

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 discovered 1 . 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 participants 2 , 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. Whole-genome sequencing and phenotype data sharing are introduced in a national health system to streamline diagnosis and to discover coding and non-coding variants that cause rare diseases.

中文翻译:


国家卫生系统罕见病患者的全基因组测序



大多数罕见病患者没有接受分子诊断,并且一半以上此类疾病的病因变异和致病基因仍有待发现 1 。在这里,我们在国家卫生系统中使用全基因组测序(WGS)来简化诊断并发现基因组编码和非编码区域中未知的病因变异。我们为 13,037 名参与者生成了 WGS 数据,其中 9,802 名参与者患有罕见疾病,并为 7,065 名广泛表型参与者中的 1,138 名提供了基因诊断。我们确定了基因与罕见疾病之间的 95 种孟德尔关联,其中 11 种是自 2015 年以来发现的,至少 79 种被确认为病因学关联。通过生成英国生物银行参与者的全基因组测序数据 2 ,我们发现稀有等位基因可以解释某些个体在红细胞数量性状尾部的存在。最后,我们发现了四种新的非编码变异,它们通过破坏 ARPC1B、GATA1、LRBA 和 MPL 的转录而导致疾病。我们的研究证明了在常规医疗保健中使用 WGS 进行诊断和病因发现的协同作用。国家卫生系统引入全基因组测序和表型数据共享,以简化诊断并发现导致罕见疾病的编码和非编码变异。
更新日期:2020-06-24
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