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Structural and non-coding variants increase the diagnostic yield of clinical whole genome sequencing for rare diseases.

Pagnamenta, AT; Camps, C; Giacopuzzi, E; Taylor, JM; Hashim, M; Calpena, E; Kaisaki, PJ; Hashimoto, A; Yu, J; Sanders, E; et al. Pagnamenta, AT; Camps, C; Giacopuzzi, E; Taylor, JM; Hashim, M; Calpena, E; Kaisaki, PJ; Hashimoto, A; Yu, J; Sanders, E; Schwessinger, R; Hughes, JR; Lunter, G; Dreau, H; Ferla, M; Lange, L; Kesim, Y; Ragoussis, V; Vavoulis, DV; Allroggen, H; Ansorge, O; Babbs, C; Banka, S; Baños-Piñero, B; Beeson, D; Ben-Ami, T; Bennett, DL; Bento, C; Blair, E; Brasch-Andersen, C; Bull, KR; Cario, H; Cilliers, D; Conti, V; Davies, EG; Dhalla, F; Dacal, BD; Dong, Y; Dunford, JE; Guerrini, R; Harris, AL; Hartley, J; Hollander, G; Javaid, K; Kane, M; Kelly, D; Kelly, D; Knight, SJL; Kreins, AY; Kvikstad, EM; Langman, CB; Lester, T; Lines, KE; Lord, SR; Lu, X; Mansour, S; Manzur, A; Maroofian, R; Marsden, B; Mason, J; McGowan, SJ; Mei, D; Mlcochova, H; Murakami, Y; Németh, AH; Okoli, S; Ormondroyd, E; Ousager, LB; Palace, J; Patel, SY; Pentony, MM; Pugh, C; Rad, A; Ramesh, A; Riva, SG; Roberts, I; Roy, N; Salminen, O; Schilling, KD; Scott, C; Sen, A; Smith, C; Stevenson, M; Thakker, RV; Twigg, SRF; Uhlig, HH; van Wijk, R; Vona, B; Wall, S; Wang, J; Watkins, H; Zak, J; Schuh, AH; Kini, U; Wilkie, AOM; Popitsch, N; Taylor, JC (2023) Structural and non-coding variants increase the diagnostic yield of clinical whole genome sequencing for rare diseases. Genome Med, 15 (1). p. 94. ISSN 1756-994X https://doi.org/10.1186/s13073-023-01240-0
SGUL Authors: Mansour, Sahar

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Abstract

BACKGROUND: Whole genome sequencing is increasingly being used for the diagnosis of patients with rare diseases. However, the diagnostic yields of many studies, particularly those conducted in a healthcare setting, are often disappointingly low, at 25-30%. This is in part because although entire genomes are sequenced, analysis is often confined to in silico gene panels or coding regions of the genome. METHODS: We undertook WGS on a cohort of 122 unrelated rare disease patients and their relatives (300 genomes) who had been pre-screened by gene panels or arrays. Patients were recruited from a broad spectrum of clinical specialties. We applied a bioinformatics pipeline that would allow comprehensive analysis of all variant types. We combined established bioinformatics tools for phenotypic and genomic analysis with our novel algorithms (SVRare, ALTSPLICE and GREEN-DB) to detect and annotate structural, splice site and non-coding variants. RESULTS: Our diagnostic yield was 43/122 cases (35%), although 47/122 cases (39%) were considered solved when considering novel candidate genes with supporting functional data into account. Structural, splice site and deep intronic variants contributed to 20/47 (43%) of our solved cases. Five genes that are novel, or were novel at the time of discovery, were identified, whilst a further three genes are putative novel disease genes with evidence of causality. We identified variants of uncertain significance in a further fourteen candidate genes. The phenotypic spectrum associated with RMND1 was expanded to include polymicrogyria. Two patients with secondary findings in FBN1 and KCNQ1 were confirmed to have previously unidentified Marfan and long QT syndromes, respectively, and were referred for further clinical interventions. Clinical diagnoses were changed in six patients and treatment adjustments made for eight individuals, which for five patients was considered life-saving. CONCLUSIONS: Genome sequencing is increasingly being considered as a first-line genetic test in routine clinical settings and can make a substantial contribution to rapidly identifying a causal aetiology for many patients, shortening their diagnostic odyssey. We have demonstrated that structural, splice site and intronic variants make a significant contribution to diagnostic yield and that comprehensive analysis of the entire genome is essential to maximise the value of clinical genome sequencing.

Item Type: Article
Additional Information: © Crown 2023. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
Keywords: Bioinformatics pipeline development, Clinical impact, Diagnostic yield, Genome sequencing, Non-coding, Pipeline optimisation, Rare diseases, Splice site variant, Structural variant, Humans, Genetic Variation, Rare Diseases, Whole Genome Sequencing, Genetic Testing, Mutation, Cell Cycle Proteins, Humans, Rare Diseases, Cell Cycle Proteins, Mutation, Genetic Variation, Genetic Testing, Whole Genome Sequencing, Genome sequencing, Rare diseases, Structural variant, Splice site variant, Non-coding, Diagnostic yield, Clinical impact, Bioinformatics pipeline development, Pipeline optimisation, 0604 Genetics, 1103 Clinical Sciences
SGUL Research Institute / Research Centre: Academic Structure > Molecular and Clinical Sciences Research Institute (MCS)
Journal or Publication Title: Genome Med
ISSN: 1756-994X
Language: eng
Dates:
DateEvent
9 November 2023Published
27 September 2023Accepted
Publisher License: Creative Commons: Attribution 4.0
Projects:
Project IDFunderFunder ID
222096/Z/20/ZWellcome Trusthttp://dx.doi.org/10.13039/100004440
102731Wellcome Trusthttp://dx.doi.org/10.13039/100004440
MR/WO1761X/1Medical Research CouncilUNSPECIFIED
MC_UU_00029/ 01-09Medical Research Councilhttp://dx.doi.org/10.13039/501100000265
MC_UU_00008Medical Research Councilhttp://dx.doi.org/10.13039/501100000265
MR/T014067/1Medical Research Councilhttp://dx.doi.org/10.13039/501100000265
MR/R007748/1Medical Research Councilhttp://dx.doi.org/10.13039/501100000265
R6-388 / WT 100127Wellcome Trusthttp://dx.doi.org/10.13039/100004440
UNSPECIFIEDDepartment of HealthUNSPECIFIED
203141/Z/16/ZWellcome Trusthttp://dx.doi.org/10.13039/100004440
223,149/Z/21/ZWellcome Trusthttp://dx.doi.org/10.13039/100004440
MC_UU_00016/14Medical Research Councilhttp://dx.doi.org/10.13039/501100000265
106,130/Z/14/ZWellcome Trusthttp://dx.doi.org/10.13039/100004440
MR/S007180/1Medical Research CouncilUNSPECIFIED
GN2855Action Medical Researchhttp://dx.doi.org/10.13039/501100000317
2545–1-0University of TübingenUNSPECIFIED
469,177,153Deutsche Forschungsgemeinschafthttp://dx.doi.org/10.13039/501100001659
G0902418WIMM Strategic AllianceUNSPECIFIED
MC UU 12025WIMM Strategic AllianceUNSPECIFIED
V4520Great Ormond Street Hospital Charityhttp://dx.doi.org/10.13039/501100001279
MR/T031670/1Medical Research Councilhttp://dx.doi.org/10.13039/501100000265
MR/S007180/1Medical Research Councilhttp://dx.doi.org/10.13039/501100000265
PubMed ID: 37946251
Web of Science ID: WOS:001099214900001
Go to PubMed abstract
URI: https://openaccess.sgul.ac.uk/id/eprint/116180
Publisher's version: https://doi.org/10.1186/s13073-023-01240-0

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