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- Title
Molecular diagnoses in the congenital malformations caused by ciliopathies cohort of the 100 000 genomes project.
- Authors
Best, Sunayna; Lord, Jenny; Roche, Matthew; Watson, Christopher; Poulter, James; Szymanska, Katarzyna; Ellingford, Jamie; Carmichael, Jenny; Brittain, Helen; Toomes, Carmel; Inglehearn, Chris; Johnson, Colin; Wheway, Gabrielle
- Abstract
Purpose: To improve molecular diagnostic rates for participants recruited to the UK 100 000 Genomes Project suspected to have congenital malformations caused by ciliopathies. Methods: Bespoke variant filtering and analysis strategy. Results: Eighty‐three pre‐screened probands were recruited in the following disease categories: Bardet‐Biedl syndrome (n = 45), Joubert syndrome (n = 14) and Rare Multisystem Ciliopathy Disorders (n = 24). We determined a research molecular diagnosis for n = 43/83 (51.8%) of probands, n = 33 (39.8%) classified as confident or probable diagnoses. The diagnosis rate is 19.3% higher than the n = 27/83 (32.5%) previously reported by Genomics England. Interestingly, 19/43 (44.2%) of diagnoses are not ciliopathies. 4 patients have causative variants in eye disease genes not directly linked to cilia (PRPF8, RHO, PROM1, OPA1) and 15 in genes causative of non‐ciliopathy multisystemic conditions. This may reflect difficulties in clinical recognition of ciliopathies and highlights the importance of looking beyond the initial panel. n = 11/83 probands (13.3%) had at least one causative variant outside of the Tiers 1 and 2 variant annotation categories (defined by the Genomics England Rare Disease Tiering Process), which would otherwise be excluded in standard diagnostic strategies. These include 4 SVs and 3 predicted by SpliceAI to cause non‐canonical splicing defects. We found two homozygous truncating variants in the candidate ciliopathy genes LRRC45 and CFAP45 in a single proband. Identification of further individuals with ciliopathy phenotypes with pathogenic variants in these genes would strengthen confidence in their status as ciliopathy disease genes. Conclusions: This study shows the value of research collaborations to improve interpretation of genomic data. Improved integration of SV and splice variant analysis tools, such as SpliceAI, will be essential to maximise the diagnostic potential of WGS data beyond coding variants in exons of virtual panels of genes.
- Subjects
UNITED Kingdom; HUMAN abnormalities; GENOMES; JOUBERT syndrome; LAURENCE-Moon-Biedl syndrome; GENETIC variation; GENETIC code; AGROBACTERIUM tumefaciens
- Publication
Acta Ophthalmologica (1755375X), 2022, Vol 100, pN.PAG
- ISSN
1755-375X
- Publication type
Abstract
- DOI
10.1111/j.1755-3768.2022.130