Kaplanis, J., Samocha, K.E., Wiel, L. et al. (30 more authors) (2020) Evidence for 28 genetic disorders discovered by combining healthcare and research data. Nature, 586 (7831). pp. 757-762. ISSN 0028-0836
Abstract
De novo mutations in protein-coding genes are a well-established cause of developmental disorders. However, genes known to be associated with developmental disorders account for only a minority of the observed excess of such de novo mutations. Here, to identify previously undescribed genes associated with developmental disorders, we integrate healthcare and research exome-sequence data from 31,058 parent–offspring trios of individuals with developmental disorders, and develop a simulation-based statistical test to identify gene-specific enrichment of de novo mutations. We identified 285 genes that were significantly associated with developmental disorders, including 28 that had not previously been robustly associated with developmental disorders. Although we detected more genes associated with developmental disorders, much of the excess of de novo mutations in protein-coding genes remains unaccounted for. Modelling suggests that more than 1,000 genes associated with developmental disorders have not yet been described, many of which are likely to be less penetrant than the currently known genes. Research access to clinical diagnostic datasets will be critical for completing the map of genes associated with developmental disorders.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2020 The Authors. This is an author-created version of a paper subsequently published in Nature. Available under the terms of the Creative Commons Attribution Licence (http://creativecommons.org/licenses/by/4.0/). |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Medicine, Dentistry and Health (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 29 Oct 2020 11:34 |
Last Modified: | 06 Nov 2020 09:06 |
Status: | Published |
Publisher: | Springer Nature |
Refereed: | Yes |
Identification Number: | 10.1038/s41586-020-2832-5 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:167366 |