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A gene-to-patient approach uplifts novel disease gene discovery and identifies 18 putative novel disease genes

A gene-to-patient approach uplifts novel disease gene discovery and identifies 18 putative novel disease genes
A gene-to-patient approach uplifts novel disease gene discovery and identifies 18 putative novel disease genes
Purpose

Exome and genome sequencing have drastically accelerated novel disease gene discoveries. However, discovery is still hindered by myriad variants of uncertain significance found in genes of undetermined biological function. This necessitates intensive functional experiments on genes of equal predicted causality, leading to a major bottleneck.

Methods

We apply the loss-of-function observed/expected upper-bound fraction metric of intolerance to gene inactivation to curate a list of predicted haploinsufficient disease genes. Using data from the 100,000 Genomes Project, we adopt a gene-to-patient approach that matches de novo loss-of-function variants in constrained genes to patients with rare disease. Through large-scale aggregation of data, we reduce excess analytical noise currently hindering novel discoveries.

Results

Results from 13,949 trios revealed 643 rare, de novo predicted loss-of-function events filtered from 1044 loss-of-function observed/expected upper-bound fraction–constrained genes. A total of 168 variants occurred within 126 genes without a known disease-gene relationship. Of these, 27 genes had >1 kindred affected, and for 18 of these genes, multiple kindreds had overlapping phenotypes. Two years after initial analysis, 11 of 18 (61%) of these genes have been independently published as novel disease gene discoveries.

Conclusion

Using large cohorts and adopting gene-based approaches can rapidly and objectively accelerate dominantly inherited novel gene discovery by targeting the most appropriate genes for functional validation.

Diagnostic uplift, Disease genes, Genome sequencing, Mendelian disease, Novel gene discovery
1098-3600
1697-1707
Seaby, Eleanor
ec948f42-007c-4bd8-9dff-bb86278bf03f
Smedley, Damian
e10e5b38-5efb-4b50-ae2b-8e7bb9fd2916
Tavares, Ana Lisa Taylor
730fb640-a84a-451f-815e-a3d7155e4938
Brittain, Helen
19411fbb-588d-49c3-93e8-f2926c8541e3
van Jaarsveld, Richard H
ca609c6b-828b-4cfc-bac5-8a77cc3085f6
Baralle, Diana
faac16e5-7928-4801-9811-8b3a9ea4bb91
Rehm, Heidi L
0e4087b7-519d-4b95-84ac-412d1c0173d1
O'Donnell-Luria, Anne
2e2786d6-b7c8-40f8-b727-6bbd630385d6
Ennis, Sarah
7b57f188-9d91-4beb-b217-09856146f1e9
Seaby, Eleanor
ec948f42-007c-4bd8-9dff-bb86278bf03f
Smedley, Damian
e10e5b38-5efb-4b50-ae2b-8e7bb9fd2916
Tavares, Ana Lisa Taylor
730fb640-a84a-451f-815e-a3d7155e4938
Brittain, Helen
19411fbb-588d-49c3-93e8-f2926c8541e3
van Jaarsveld, Richard H
ca609c6b-828b-4cfc-bac5-8a77cc3085f6
Baralle, Diana
faac16e5-7928-4801-9811-8b3a9ea4bb91
Rehm, Heidi L
0e4087b7-519d-4b95-84ac-412d1c0173d1
O'Donnell-Luria, Anne
2e2786d6-b7c8-40f8-b727-6bbd630385d6
Ennis, Sarah
7b57f188-9d91-4beb-b217-09856146f1e9

Seaby, Eleanor, Smedley, Damian, Tavares, Ana Lisa Taylor, Brittain, Helen, van Jaarsveld, Richard H, Baralle, Diana, Rehm, Heidi L, O'Donnell-Luria, Anne and Ennis, Sarah (2022) A gene-to-patient approach uplifts novel disease gene discovery and identifies 18 putative novel disease genes. Genetics in Medicine, 24 (8), 1697-1707. (doi:10.1016/j.gim.2022.04.019).

Record type: Article

Abstract

Purpose

Exome and genome sequencing have drastically accelerated novel disease gene discoveries. However, discovery is still hindered by myriad variants of uncertain significance found in genes of undetermined biological function. This necessitates intensive functional experiments on genes of equal predicted causality, leading to a major bottleneck.

Methods

We apply the loss-of-function observed/expected upper-bound fraction metric of intolerance to gene inactivation to curate a list of predicted haploinsufficient disease genes. Using data from the 100,000 Genomes Project, we adopt a gene-to-patient approach that matches de novo loss-of-function variants in constrained genes to patients with rare disease. Through large-scale aggregation of data, we reduce excess analytical noise currently hindering novel discoveries.

Results

Results from 13,949 trios revealed 643 rare, de novo predicted loss-of-function events filtered from 1044 loss-of-function observed/expected upper-bound fraction–constrained genes. A total of 168 variants occurred within 126 genes without a known disease-gene relationship. Of these, 27 genes had >1 kindred affected, and for 18 of these genes, multiple kindreds had overlapping phenotypes. Two years after initial analysis, 11 of 18 (61%) of these genes have been independently published as novel disease gene discoveries.

Conclusion

Using large cohorts and adopting gene-based approaches can rapidly and objectively accelerate dominantly inherited novel gene discovery by targeting the most appropriate genes for functional validation.

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More information

Accepted/In Press date: 14 April 2022
e-pub ahead of print date: 9 May 2022
Published date: 1 August 2022
Additional Information: Funding Information: This research was made possible through access to the data and findings generated by the 100,000 Genomes Project. The 100,000 Genomes Project is managed by Genomics England Limited (a wholly owned company of the Department of Health and Social Care). The 100,000 Genomes Project is funded by the National Institute for Health Research and NHS England. The Wellcome Trust, Cancer Research UK, and Medical Research Council have also funded research infrastructure. The 100,000 Genomes Project uses data provided by patients and collected by the National Health Service as part of their care and support. We would further like to extend our thanks to all the patients and their families for participation in the 100,000 Genomes Project. We are grateful to the Genome Aggregation Database teams for their helpful discussions in the development and application of constraint metrics in novel gene discovery.E.G.S. was supported by the Kerkut Charitable Trust and University of Southampton's Presidential Scholarship Award. H.L.R. was supported by the National Human Genome Research Institute (NHGRI) (U24 HG011450 and U41 HG006834). A.O.-L. was supported by the National Institute of Mental Health (U01 MH119689) and the Manton Center for Orphan Disease Research Scholar Award. E.G.S., H.L.R., and A.O.-L. were supported by NHGRI, the National Eye Institute, and the National Heart, Lung and Blood Institute (UM1 HG008900). D.B. was generously supported by a National Institute of Health Research Research Professorship (RP-2016-07-011). Publisher Copyright: © 2022 The Authors
Keywords: Diagnostic uplift, Disease genes, Genome sequencing, Mendelian disease, Novel gene discovery

Identifiers

Local EPrints ID: 457051
URI: http://eprints.soton.ac.uk/id/eprint/457051
ISSN: 1098-3600
PURE UUID: 27d93798-1bc0-4986-bae5-33aaa55ecf24
ORCID for Eleanor Seaby: ORCID iD orcid.org/0000-0002-6814-8648
ORCID for Diana Baralle: ORCID iD orcid.org/0000-0003-3217-4833
ORCID for Sarah Ennis: ORCID iD orcid.org/0000-0003-2648-0869

Catalogue record

Date deposited: 20 May 2022 16:48
Last modified: 17 Mar 2024 04:05

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Contributors

Author: Eleanor Seaby ORCID iD
Author: Damian Smedley
Author: Ana Lisa Taylor Tavares
Author: Helen Brittain
Author: Richard H van Jaarsveld
Author: Diana Baralle ORCID iD
Author: Heidi L Rehm
Author: Anne O'Donnell-Luria
Author: Sarah Ennis ORCID iD

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