疾病
全基因组关联研究
遗传关联
生物
遗传学
生物信息学
基因组
基因
孟德尔遗传
计算生物学
基因组学
生物信息学
医学
单核苷酸多态性
基因型
病理
作者
Valentina Cipriani,Letizia Vestito,Emma Magavern,Julius O.B. Jacobsen,Gavin Arno,Elijah R. Behr,Katherine A. Benson,Marta Bértoli,Detlef Böckenhauer,Michael R. Bowl,Kate Burley,Li F. Chan,Patrick F. Chinnery,Peter J. Conlon,Marcos Abreu Costa,Alice E. Davidson,Sally J. Dawson,Elhussein A. Elhassan,Sarah E. Flanagan,Marta Futema
出处
期刊:Nature
[Nature Portfolio]
日期:2025-02-26
被引量:13
标识
DOI:10.1038/s41586-025-08623-w
摘要
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.
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