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

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

Abstract

Abstract Up to 80% of rare disease patients remain undiagnosed after genomic sequencing 1 , 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 2 . 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 3,4 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.

Article Details

Journal Nature
Volume / Issue Vol. 1, Issue 1
Published February 26, 2025
ISSN 0028-0836
Publisher Nature Portfolio

Journal Info

Nature

Nature Portfolio

ISSN: 0028-0836 Health Sciences

Authors (61)

V

Valentina Cipriani

L

Letizia Vestito

E

Emma F. Magavern

J

Julius O. B. Jacobsen

G

Gavin Arno

E

Elijah R. Behr

K

Katherine A. Benson

M

Marta Bertoli

D

Detlef Bockenhauer

M

Michael R. Bowl

K

Kate Burley

L

Li F. Chan

P

Patrick Chinnery

P

Peter J. Conlon

M

Marcos A. Costa

A

Alice E. Davidson

S

Sally J. Dawson

E

Elhussein A. E. Elhassan

S

Sarah E. Flanagan

M

Marta Futema

D

Daniel P. Gale

S

Sonia García-Ruiz

C

Cecilia Gonzalez Corcia

H

Helen R. Griffin

S

Sophie Hambleton

A

Amy R. Hicks

H

Henry Houlden

R

Richard S. Houlston

S

Sarah A. Howles

R

Robert Kleta

I

Iris Lekkerkerker

S

Siying Lin

P

Petra Liskova

H

Hannah H. Mitchison

H

Heba Morsy

A

Andrew D. Mumford

W

William G. Newman

R

Ruxandra Neatu

E

Edel A. O’Toole

A

Albert C. M. Ong

A

Alistair T. Pagnamenta

S

Shamima Rahman

N

Neil Rajan

P

Peter N. Robinson

M

Mina Ryten

O

Omid Sadeghi-Alavijeh

J

John A. Sayer

C

Claire L. Shovlin

J

Jenny C. Taylor

O

Omri Teltsh

I

Ian Tomlinson

A

Arianna Tucci

C

Clare Turnbull

A

Albertien M. van Eerde

J

James S. Ware

L

Laura M. Watts

A

Andrew R. Webster

S

Sarah K. Westbury

S

Sean L. Zheng

M

Mark Caulfield

D

Damian Smedley