Rare disease gene association discovery in the 100,000 Genomes Project

Abstract

Up to 80% of rare disease patients remain undiagnosed after genomic sequencing1, with many probably involving pathogenic variants in yet to be discovered disease–gene associations. To search for such associations, we developed a rare variant gene burden analytical framework for Mendelian diseases, and applied it to protein-coding variants from whole-genome sequencing of 34,851 cases and their family members recruited to the 100,000 Genomes Project2. A total of 141 new associations were identified, including five for which independent disease–gene evidence was recently published. Following in silico triaging and clinical expert review, 69 associations were prioritized, of which 30 could be linked to existing experimental evidence. The five associations with strongest overall genetic and experimental evidence were monogenic diabetes with the known β cell regulator3,4 UNC13A, schizophrenia with GPR17, epilepsy with RBFOX3, Charcot–Marie–Tooth disease with ARPC3 and anterior segment ocular abnormalities with POMK. Further confirmation of these and other associations could lead to numerous diagnoses, highlighting the clinical impact of large-scale statistical approaches to rare disease–gene association discovery.

Metadata

Item Type:	Article
Authors/Creators:	Cipriani, V. https://orcid.org/0000-0002-0839-9955 Vestito, L. https://orcid.org/0000-0003-0008-936X Magavern, E.F. https://orcid.org/0000-0003-0699-6411 Jacobsen, J.O.B. https://orcid.org/0000-0002-3265-1591 Arno, G. Behr, E.R. https://orcid.org/0000-0002-8731-2853 Benson, K.A. Bertoli, M. Bockenhauer, D. https://orcid.org/0000-0001-5878-941X Bowl, M.R. https://orcid.org/0000-0001-7971-445X Burley, K. https://orcid.org/0000-0002-1569-5007 Chan, L.F. Chinnery, P. Conlon, P.J. Costa, M.A. https://orcid.org/0009-0008-5699-1567 Davidson, A.E. Dawson, S.J. https://orcid.org/0000-0002-4421-2043 Elhassan, E.A.E. Flanagan, S.E. https://orcid.org/0000-0002-8670-6340 Futema, M. https://orcid.org/0000-0002-2120-2088 Gale, D.P. https://orcid.org/0000-0002-9170-1579 García-Ruiz, S. Corcia, C.G. https://orcid.org/0000-0002-4289-049X Griffin, H.R. https://orcid.org/0000-0002-5288-3322 Hambleton, S. Hicks, A.R. https://orcid.org/0000-0002-3965-5253 Houlden, H. https://orcid.org/0000-0002-2866-7777 Houlston, R.S. https://orcid.org/0000-0002-5268-0242 Howles, S.A. Kleta, R. https://orcid.org/0000-0002-0228-8656 Lekkerkerker, I. Lin, S. https://orcid.org/0000-0003-1122-8396 Liskova, P. https://orcid.org/0000-0001-7834-8486 Mitchison, H.H. https://orcid.org/0000-0002-3163-6293 Morsy, H. https://orcid.org/0000-0002-9047-0959 Mumford, A.D. Newman, W.G. https://orcid.org/0000-0002-6382-4678 Neatu, R. O’Toole, E.A. https://orcid.org/0000-0002-4084-4836 Ong, A.C.M. https://orcid.org/0000-0002-7211-5400 Pagnamenta, A.T. Rahman, S. https://orcid.org/0000-0003-2088-730X Rajan, N. https://orcid.org/0000-0002-5850-5680 Robinson, P.N. https://orcid.org/0000-0002-0736-9199 Ryten, M. https://orcid.org/0000-0001-9520-6957 Sadeghi-Alavijeh, O. Sayer, J.A. https://orcid.org/0000-0003-1881-3782 Shovlin, C.L. https://orcid.org/0000-0001-9007-5775 Taylor, J.C. https://orcid.org/0000-0003-3602-5704 Teltsh, O. Tomlinson, I. https://orcid.org/0000-0003-3037-1470 Tucci, A. https://orcid.org/0000-0001-5644-0070 Turnbull, C. https://orcid.org/0000-0002-1734-5772 van Eerde, A.M. Ware, J.S. https://orcid.org/0000-0002-6110-5880 Watts, L.M. https://orcid.org/0000-0003-3391-4389 Webster, A.R. Westbury, S.K. Zheng, S.L. https://orcid.org/0000-0002-5762-6392 Caulfield, M. https://orcid.org/0000-0001-9295-3594 Smedley, D. https://orcid.org/0000-0002-5836-9850
Copyright, Publisher and Additional Information:	© The Author(s) 2025. 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/.
Keywords:	Genetic association study; Genetic variation; Genetics research; Medical genetics; Statistical methods
Dates:	Published: 26 February 2025 Published (online): 26 February 2025 Accepted: 10 January 2025 Submitted: 19 December 2023
Institution:	The University of Sheffield
Academic Units:	The University of Sheffield > Faculty of Medicine, Dentistry and Health (Sheffield) > School of Medicine and Population Health
Depositing User:	Symplectic Sheffield
Date Deposited:	05 Mar 2025 16:57
Last Modified:	05 Mar 2025 16:57
Status:	Published online
Publisher:	Springer Science and Business Media LLC
Refereed:	Yes
Identification Number:	10.1038/s41586-025-08623-w
Sustainable Development Goals:
Open Archives Initiative ID (OAI ID):	oai:eprints.whiterose.ac.uk:224016

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Rare disease gene association discovery in the 100,000 Genomes Project

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