Rare disease gene association discovery in the 100,000 GenomesProject

Up to 80% of rare disease patients remain undiagnosed after genomic sequencing<sup>1</sup>, 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 Project<sup>2</sup>. 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 regulator<sup>3,4</sup> 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.

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Journal
Nature
Published
2025-02-26
DOI
https://doi.org/10.1038/s41586-025-08623-w
Citations
13
Primary Topic
Genomics and Rare Diseases
Type
article
Field-Weighted Citation Impact
23.62

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article

Rare disease gene association discovery in the 100,000 GenomesProject

Heba Morsy, Amy R. Hicks, Omri Teltsh, Jenny C. Taylor et al.
13 citations
Nature
Genomics and Rare Diseases
23.62
article

Rare disease gene association discovery in the 100,000 GenomesProject

Heba Morsy, Amy R. Hicks, Omri Teltsh, Jenny C. Taylor, Michael R. Bowl, Damian Smedley, Claire L. Shovlin, Elijah R. Behr, Marta Futema, Hannah M. Mitchison, Patrick Francis Chinnery, Iris Lekkerkerker, M. Cecilia Gonzalez Corcia, Albert Ong, Sarah Elizabeth Flanagan, Kate Burley, James S. Ware, Detlef Böckenhauer, Siying Lin, Richard S. Houlston, Clare Turnbull, Petra Lišková, Andrew Mumford, Sally J. Dawson, Elhussein A. Elhassan, Sean L. Zheng, Peter N. Robinson, Sonia García-Ruiz, Sophie Hambleton, Emma Forton Magavern, John Andrew Sayer, Ian Tomlinson, Mina Ryten, Robert Kleta, Laura Watts, Li F. Chan, Shamima Rahman, Katherine A. Benson, Alice E. Davidson, Ruxandra Neatu, Helen Griffin, Sarah K. Westbury, Neil Rajan, Daniel P. Gale, Letizia Vestito, Albertien M. van Eerde, William G. Newman, Mark J. Caulfield, Peter J. Conlon, Gavin Arno, Julius O.B. Jacobsen, Henry Houlden, Sarah Howles, Omid Sadeghi‐Alavijeh, Arianna Tucci, Edel A. O’Toole, Andrew R. Webster, Valentina Cipriani, Marcos Abreu Costa, Marta Bértoli, Alistair T. Pagnamenta
article en
13 citations

Abstract

Up to 80% of rare disease patients remain undiagnosed after genomic sequencing<sup>1</sup>, 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 Project<sup>2</sup>. 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 regulator<sup>3,4</sup> 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.

Nature
Centre for Human Genetics (GB), Royal College of Surgeons in Ireland (IE), Institute of Cancer Research (GB), St George's, University of London (GB), Queen Mary University of London (GB), Charles University (CZ), University of Exeter (GB), University of Cambridge (GB), Great Ormond Street Hospital (GB), Royal Victoria Infirmary (GB), St George’s University Hospitals NHS Foundation Trust (GB), Newcastle upon Tyne Hospitals NHS Foundation Trust (GB), Beaumont Hospital (IE), Oxford Health NHS Foundation Trust (GB), Centre Hospitalier Universitaire Sainte-Justine (CA), University of Manchester (GB), University Medical Center Utrecht (NL), University of Bristol (GB), University of Oxford (GB), Manchester University NHS Foundation Trust (GB), Sheffield Teaching Hospitals NHS Foundation Trust (GB), Jackson Laboratory (US), UK Dementia Research Institute (GB), Sheffield Kidney Institute (GB), NIHR Newcastle Biomedical Research Centre (GB), Great North Children's Hospital (GB), Berlin Institute of Health at Charité - Universitätsmedizin Berlin (DE), Oxford BioMedica (United Kingdom) (GB), William Harvey Research Institute (GB), Moorfields Eye Hospital (GB), National Hospital for Neurology and Neurosurgery (GB), Genomics (United Kingdom) (GB), Research Network (United States) (US), MRC London Institute of Medical Sciences (GB), General University Hospital in Prague (CZ), University College London (GB), Imperial College London (GB), McGill University (CA), Université de Montréal (CA), MRC Mitochondrial Biology Unit (GB), Newcastle University (GB), Medical Research Council (GB), University of Sheffield (GB), KU Leuven (BE)
Medical Research Council
Good health and well-being
Openalex Percentile: Top 0%
Genomics and Rare Diseases
23.62
DOIOpen Access PDFOpenAlex
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