A gene pathogenicity tool "GenePy" identifies missed biallelic diagnoses in the 100,000 Genomes Project.

Autor:	Seaby EG; Human Development and Health, Faculty of Medicine, University Hospital Southampton, Southampton, Hampshire, United Kingdom; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA; Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA; Paediatric Infectious Diseases, Imperial College London, London, United Kingdom. Electronic address: E.Seaby@soton.ac.uk., Leggatt G; Human Development and Health, Faculty of Medicine, University Hospital Southampton, Southampton, Hampshire, United Kingdom., Cheng G; Human Development and Health, Faculty of Medicine, University Hospital Southampton, Southampton, Hampshire, United Kingdom., Thomas NS; Human Development and Health, Faculty of Medicine, University Hospital Southampton, Southampton, Hampshire, United Kingdom; Wessex Regional Genomics Laboratory, Salisbury NHS Foundation Trust, Salisbury, United Kingdom., Ashton JJ; Human Development and Health, Faculty of Medicine, University Hospital Southampton, Southampton, Hampshire, United Kingdom., Stafford I; University of Surrey, Guildford, Surrey, United Kingdom., Baralle D; Human Development and Health, Faculty of Medicine, University Hospital Southampton, Southampton, Hampshire, United Kingdom., Rehm HL; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA; Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA., O'Donnell-Luria A; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA; Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA., Ennis S; Human Development and Health, Faculty of Medicine, University Hospital Southampton, Southampton, Hampshire, United Kingdom.
Jazyk:	angličtina
Zdroj:	Genetics in medicine : official journal of the American College of Medical Genetics [Genet Med] 2024 Apr; Vol. 26 (4), pp. 101073. Date of Electronic Publication: 2024 Jan 18.
DOI:	10.1016/j.gim.2024.101073
Abstrakt:	Purpose: The 100,000 Genomes Project diagnosed a quarter of affected participants, but 26% of diagnoses were not on the applied gene panel(s); with many being de novo variants. Assessing biallelic variants without a gene panel is more challenging. Methods: We sought to identify missed biallelic diagnoses using GenePy, which incorporates allele frequency, zygosity, and a user-defined deleterious metric, generating an aggregate GenePy score per gene, per participant. We calculated GenePy scores for 2862 recessive disease genes in 78,216 100,000 Genomes Project participants. For each gene, we ranked participant GenePy scores and scrutinized affected participants without a diagnosis, whose scores ranked among the top 5 for each gene. In cases which participant phenotypes overlapped with the disease gene of interest, we extracted rare variants and applied phase, ClinVar, and ACMG classification. Results: 3184 affected individuals without a molecular diagnosis had a top-5-ranked GenePy score and 682 of 3184 (21%) had phenotypes overlapping with a top-ranking gene. In 122 of 669 (18%) phenotype-matched cases (excluding 13 withdrawn participants), we identified a putative missed diagnosis (2.2% of all undiagnosed participants). A further 334 of 669 (50%) cases have a possible missed diagnosis but require functional validation. Conclusion: Applying GenePy at scale has identified 456 potential diagnoses, demonstrating the value of novel diagnostic strategies. Competing Interests: Conflict of Interest The authors declare no conflicts of interest. (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)
Databáze:	MEDLINE
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