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

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

Research output: Contribution to journalArticle (Academic Journal)peer-review

18 Citations (Scopus)

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.

Original languageEnglish
Article numbere13761
Number of pages17
JournalNature
Early online date26 Feb 2025
DOIs
Publication statusE-pub ahead of print - 26 Feb 2025

Bibliographical note

© 2025. The Author(s).

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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