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 language | English |
|---|---|
| Article number | e13761 |
| Number of pages | 17 |
| Journal | Nature |
| Early online date | 26 Feb 2025 |
| DOIs | |
| Publication status | E-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)
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SDG 3 Good Health and Well-being
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