Greene, D;
Genomics England Research Consortium, ;
Pirri, D;
Frudd, K;
Sackey, E;
Al-Owain, M;
Giese, APJ;
Ramzan, K;
Riaz, S;
Yamanaka, I;
et al.
Greene, D; Genomics England Research Consortium; Pirri, D; Frudd, K; Sackey, E; Al-Owain, M; Giese, APJ; Ramzan, K; Riaz, S; Yamanaka, I; Boeckx, N; Thys, C; Gelb, BD; Brennan, P; Hartill, V; Harvengt, J; Kosho, T; Mansour, S; Masuno, M; Ohata, T; Stewart, H; Taibah, K; Turner, CLS; Imtiaz, F; Riazuddin, S; Morisaki, T; Ostergaard, P; Loeys, BL; Morisaki, H; Ahmed, ZM; Birdsey, GM; Freson, K; Mumford, A; Turro, E
(2023)
Genetic association analysis of 77,539 genomes reveals rare disease etiologies.
Nat Med, 29 (3).
pp. 679-688.
ISSN 1546-170X
https://doi.org/10.1038/s41591-023-02211-z
SGUL Authors: Ostergaard, Pia
Abstract
The genetic etiologies of more than half of rare diseases remain unknown. Standardized genome sequencing and phenotyping of large patient cohorts provide an opportunity for discovering the unknown etiologies, but this depends on efficient and powerful analytical methods. We built a compact database, the 'Rareservoir', containing the rare variant genotypes and phenotypes of 77,539 participants sequenced by the 100,000 Genomes Project. We then used the Bayesian genetic association method BeviMed to infer associations between genes and each of 269 rare disease classes assigned by clinicians to the participants. We identified 241 known and 19 previously unidentified associations. We validated associations with ERG, PMEPA1 and GPR156 by searching for pedigrees in other cohorts and using bioinformatic and experimental approaches. We provide evidence that (1) loss-of-function variants in the Erythroblast Transformation Specific (ETS)-family transcription factor encoding gene ERG lead to primary lymphoedema, (2) truncating variants in the last exon of transforming growth factor-β regulator PMEPA1 result in Loeys-Dietz syndrome and (3) loss-of-function variants in GPR156 give rise to recessive congenital hearing impairment. The Rareservoir provides a lightweight, flexible and portable system for synthesizing the genetic and phenotypic data required to study rare disease cohorts with tens of thousands of participants.
Item Type: |
Article
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Additional Information: |
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
© The Author(s) 2023 |
Keywords: |
Humans, Rare Diseases, Bayes Theorem, Genotype, Genome-Wide Association Study, Phenotype, Membrane Proteins, 11 Medical and Health Sciences, Immunology |
SGUL Research Institute / Research Centre: |
Academic Structure > Molecular and Clinical Sciences Research Institute (MCS) |
Journal or Publication Title: |
Nat Med |
ISSN: |
1546-170X |
Language: |
eng |
Dates: |
Date | Event |
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16 March 2023 | Published | 6 January 2023 | Accepted |
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Publisher License: |
Creative Commons: Attribution 4.0 |
Projects: |
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PubMed ID: |
36928819 |
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Go to PubMed abstract |
URI: |
https://openaccess.sgul.ac.uk/id/eprint/115131 |
Publisher's version: |
https://doi.org/10.1038/s41591-023-02211-z |
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