Genet Med. 2024 Jan 17:101073. doi: 10.1016/j.gim.2024.101073. Online ahead of print.


PURPOSE: The 100,000 Genomes Project (100KGP) 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 100KGP participants. For each gene, we ranked participant GenePy scores, and scrutinised affected participants without a diagnosis whose scores ranked amongst the top-5 for each gene. Where 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 682/3184 (21%) had phenotypes overlapping with a top-ranking gene. In 122/669 (18%) of the phenotype-matched cases (excluding 13 withdrawn participants), we identified a putative missed diagnosis (2.2% of all undiagnosed participants). A further 334/669 (50%) of 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.

PMID:38245859 | DOI:10.1016/j.gim.2024.101073