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.
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.
| Original language | English |
|---|---|
| Article number | 94 |
| Number of pages | 25 |
| Journal | Genome medicine |
| Volume | 15 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 9 Nov 2023 |
Bibliographical note
Funding:This research was funded and supported by the Wellcome Trust and Department of Health as part of the Health Innovation Challenge Fund scheme [R6-388 / WT 100127] awarded to JCT. This work was also supported in part by the National Institute for Health Research (NIHR) Oxford Biomedical Research Centre (BRC) and the Wellcome Trust Core Award [203141/Z/16/Z]. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR, the Department of Health or Wellcome Trust.
Computation used the Oxford Biomedical Research Computing (BMRC) facility, a joint development between the Wellcome Centre for Human Genetics and the Big Data Institute supported by Health Data Research UK and the NIHR Oxford Biomedical Research Centre. Financial support was provided by the Wellcome Trust Core Award Grant Number 203141/Z/16/Z. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health.
The following funding contributions are also acknowledged;
CB is supported by MRC funding MC_UU_00029/ 01–09, MC_UU_00008 and MR/T014067/1. DLB is a Wellcome Investigator, 223,149/Z/21/Z. EGD is funded by NIHR and Great Ormond Street Biomedical Research Centre. KRB is funded by MRC Kidney Research UK fellowship MR/R007748/1. FD is funded by NIHR Academic Clinical Lectureship & Academy of Medical Sciences Starter Grant for Clinical Lecturers. CC, EB, EC, JED, MF, MH, PK, YK, UK, SJLK, EMK, EO, ATP, MS, JCT, SRFT, DVV, HW and JY are supported by the Oxford NIHR Biomedical Research Centre. RG was supported by grants from the Tuscany Region Call for Health 2018 (grant DECODE-EE) and Fondazione Cassa di Risparmio di Firenze (Human Brain Optical Mapping Project). JRH is funded by MRC Core funding MC_UU_00016/14 and Wellcome Trust strategic award 106,130/Z/14/Z. AYK is funded by Wellcome Trust 222,096/Z/20/Z. SL is funded by Oxford Experimental Cancer Medicine Centre, NIHR Oxford Biomedical Research Centre. SGR is funded by MRC Core funding MC_UU_00016/14. IR and NR are funded by NIHR Rare Diseases Translational Research Collaboration. ES is funded by Wellcome Trust. CaS is funded by GN2855 Action Medical Research Grant. SRFT is funded by the VTCT Foundation. SW is funded by Oxford Craniofacial Unit, OUH NHS Foundation Trust. HHU is supported by the Health Research (NIHR) Oxford Biomedical Research Centre and The Leona M. and Harry B. Helmsley Charitable Trust. BV is funded by Intramural Funding (fortüne) at the University of Tübingen (2545–1-0), the Ministry of Science, Research and Art Baden-Württemberg and the German Research Foundation DFG VO 2138/7–1 grant 469,177,153. AOMW is funded by NIHR Oxford Biomedical Research Centre Programme, the WIMM Strategic Alliance (G0902418 and MC UU 12025), Wellcome (102,731), the VTCT Foundation, Great Ormond Street Charity (V4520) and the MRC through Project Grant MR/T031670/1. YD, JW are funded by MRC, grant reference MR/S007180/1. JZ is a recipient of the Cancer Research Institute/Irvington postdoctoral fellowship.
Keywords
- Splice site variant
- Pipeline optimisation
- Genome sequencing
- Structural variant
- Diagnostic yield
- Rare diseases
- Bioinformatics pipeline development
- Non-coding
- Clinical impact