Best, S, Lord, J, Roche, M et al. (13 more authors) (2022) Molecular diagnoses in the congenital malformations caused by ciliopathies cohort of the 100,000 Genomes Project. Journal of Medical Genetics, 59 (8). pp. 737-747. ISSN 0022-2593
Abstract
Background
Primary ciliopathies represent a group of inherited disorders due to defects in the primary cilium, the ‘cell’s antenna’. The 100,000 Genomes Project was launched in 2012 by Genomics England (GEL), recruiting National Health Service (NHS) patients with eligible rare diseases and cancer. Sequence data were linked to Human Phenotype Ontology (HPO) terms entered by recruiting clinicians.
Methods
Eighty-three prescreened probands were recruited to the 100,000 Genomes Project suspected to have congenital malformations caused by ciliopathies in the following disease categories: Bardet-Biedl syndrome (n=45), Joubert syndrome (n=14) and ‘Rare Multisystem Ciliopathy Disorders’ (n=24). We implemented a bespoke variant filtering and analysis strategy to improve molecular diagnostic rates for these participants.
Results
We determined a research molecular diagnosis for n=43/83 (51.8%) probands. This is 19.3% higher than previously reported by GEL (n=27/83 (32.5%)). A high proportion of diagnoses are due to variants in non-ciliopathy disease genes (n=19/43, 44.2%) which may reflect difficulties in clinical recognition of ciliopathies. n=11/83 probands (13.3%) had at least one causative variant outside the tiers 1 and 2 variant prioritisation categories (GEL’s automated triaging procedure), which would not be reviewed in standard 100,000 Genomes Project diagnostic strategies. These include four structural variants and three predicted to cause non-canonical splicing defects. Two unrelated participants have biallelic likely pathogenic variants in LRRC45, a putative novel ciliopathy disease gene.
Conclusion
These data illustrate the power of linking large-scale genome sequence to phenotype information. They demonstrate the value of research collaborations in order to maximise interpretation of genomic data.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY. Published by BMJ. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/. |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Medicine and Health (Leeds) > Institute of Molecular Medicine (LIMM) (Leeds) > Section of Opthalmology and Neurosciences (Leeds) |
Funding Information: | Funder Grant number MRC (Medical Research Council) MR/K011154/1 Wellcome Trust Not Known Wellcome Trust R120782 MRC (Medical Research Council) MR/T017503/1 |
Depositing User: | Symplectic Publications |
Date Deposited: | 24 Sep 2021 09:19 |
Last Modified: | 16 Aug 2022 21:56 |
Status: | Published |
Publisher: | BMJ Publishing Group |
Identification Number: | 10.1136/jmedgenet-2021-108065 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:178481 |