Targeting de novo loss of function variants in constrained disease genes improves diagnostic rates in the 100,000 Genomes Project
Targeting de novo loss of function variants in constrained disease genes improves diagnostic rates in the 100,000 Genomes Project
Background: Genome sequencing was first offered clinically in the UK through the 100,000 Genomes Project (100KGP). Analysis was restricted to predefined gene panels associated with the patient’s phenotype. However, panels rely on clearly characterised phenotypes and risk missing diagnoses outside of the panel(s) applied. We propose a complementary method to rapidly identify pathogenic variants, including those missed by 100KGP methods. Methods: The Loss-of-function Observed/Expected Upper-bound Fraction (LOEUF) score quantifies gene constraint, with low scores correlated with haploinsufficiency. We applied DeNovoLOEUF, a filtering strategy to sequencing data from 13,949 rare disease trios in the 100KGP, by filtering for rare, de novo, loss-of-function variants in disease genes with a LOEUF score < 0.2. We compared our findings with the corresponding patient’s diagnostic reports. Results: 324/332 (98%) of the variants identified using DeNovoLOEUF were diagnostic or partially diagnostic (whereby the variant was responsible for some of the phenotype). We identified 39 diagnoses that were “missed” by 100KGP standard analyses, which are now being returned to patients. Conclusion: We have demonstrated a highly specific and rapid method with a 98% positive predictive value that has good concordance with standard analysis, low false-positive rate, and can identify additional diagnoses. Globally, as more patients are being offered genome sequencing, we anticipate that DeNovoLOEUF will rapidly identify new diagnoses and facilitate iterative analyses when new disease genes are discovered.
351-362
Seaby, Eleanor
ec948f42-007c-4bd8-9dff-bb86278bf03f
THOMAS, N Simon
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Webb, Amy
eb493497-92af-4a28-86d5-05b323678235
Brittain, Helen
19411fbb-588d-49c3-93e8-f2926c8541e3
Tavares, Ana Lisa Taylor
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Baralle, Diana
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Rehm, Heidi L.
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O'Donnell-Luria, Anne
cb827331-5ea7-4877-9074-a0efbf1907e1
Ennis, Sarah
7b57f188-9d91-4beb-b217-09856146f1e9
Genomics England Research Consortium
7 December 2022
Seaby, Eleanor
ec948f42-007c-4bd8-9dff-bb86278bf03f
THOMAS, N Simon
bfe39cd3-60b9-4733-8921-db53f7851e4c
Webb, Amy
eb493497-92af-4a28-86d5-05b323678235
Brittain, Helen
19411fbb-588d-49c3-93e8-f2926c8541e3
Tavares, Ana Lisa Taylor
730fb640-a84a-451f-815e-a3d7155e4938
Baralle, Diana
faac16e5-7928-4801-9811-8b3a9ea4bb91
Rehm, Heidi L.
0e4087b7-519d-4b95-84ac-412d1c0173d1
O'Donnell-Luria, Anne
cb827331-5ea7-4877-9074-a0efbf1907e1
Ennis, Sarah
7b57f188-9d91-4beb-b217-09856146f1e9
Baralle, Diana, Rehm, Heidi L., O'Donnell-Luria, Anne and Ennis, Sarah
,
Genomics England Research Consortium
(2022)
Targeting de novo loss of function variants in constrained disease genes improves diagnostic rates in the 100,000 Genomes Project.
Human Genetics, 142 (3), .
(doi:10.1007/s00439-022-02509-x).
Abstract
Background: Genome sequencing was first offered clinically in the UK through the 100,000 Genomes Project (100KGP). Analysis was restricted to predefined gene panels associated with the patient’s phenotype. However, panels rely on clearly characterised phenotypes and risk missing diagnoses outside of the panel(s) applied. We propose a complementary method to rapidly identify pathogenic variants, including those missed by 100KGP methods. Methods: The Loss-of-function Observed/Expected Upper-bound Fraction (LOEUF) score quantifies gene constraint, with low scores correlated with haploinsufficiency. We applied DeNovoLOEUF, a filtering strategy to sequencing data from 13,949 rare disease trios in the 100KGP, by filtering for rare, de novo, loss-of-function variants in disease genes with a LOEUF score < 0.2. We compared our findings with the corresponding patient’s diagnostic reports. Results: 324/332 (98%) of the variants identified using DeNovoLOEUF were diagnostic or partially diagnostic (whereby the variant was responsible for some of the phenotype). We identified 39 diagnoses that were “missed” by 100KGP standard analyses, which are now being returned to patients. Conclusion: We have demonstrated a highly specific and rapid method with a 98% positive predictive value that has good concordance with standard analysis, low false-positive rate, and can identify additional diagnoses. Globally, as more patients are being offered genome sequencing, we anticipate that DeNovoLOEUF will rapidly identify new diagnoses and facilitate iterative analyses when new disease genes are discovered.
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More information
Accepted/In Press date: 28 November 2022
e-pub ahead of print date: 7 December 2022
Published date: 7 December 2022
Additional Information:
Funding Information:
EGS was supported by the Kerkut Charitable Trust, Foulkes Foundation, and University of Southampton’s Presidential Scholarship Award; HR by the NHGRI U24 HG011450 and U41 HG006834; and AO’D-L by the National Institute of Mental Health U01 MH119689 and Manton Center for Orphan Disease Research Scholar Award. EGS, HLR, and AO’D-L were supported by the National Human Genome Research Institute (NHGRI), the National Eye Institute, and the National Heart, Lung and Blood Institute under Grant UM1 HG008900. DB was generously supported by a National Institute of Health Research (NIHR) Research Professorship under Grant RP-2016-07-011.
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 the 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 Broad Center for Mendelian Genomics and Genome Aggregation Database teams for their helpful discussions in the development and application of constraint metrics in novel gene discovery.
Publisher Copyright:
© 2022, The Author(s).
Identifiers
Local EPrints ID: 473050
URI: http://eprints.soton.ac.uk/id/eprint/473050
ISSN: 0340-6717
PURE UUID: 4941a9ce-d4d4-4d75-a472-b64d2abbaf58
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Date deposited: 09 Jan 2023 18:27
Last modified: 17 Mar 2024 04:05
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Contributors
Author:
Eleanor Seaby
Author:
N Simon THOMAS
Author:
Amy Webb
Author:
Helen Brittain
Author:
Ana Lisa Taylor Tavares
Author:
Heidi L. Rehm
Author:
Anne O'Donnell-Luria
Corporate Author: Genomics England Research Consortium
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