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Samsom KG, Bosch LJW, Schipper LJ, Schout D, Roepman P, Boelens MC, Lalezari F, Klompenhouwer EG, de Langen AJ, Buffart TE, van Linder BMH, van Deventer K, van den Burg K, Unmehopa U, Rosenberg EH, Koster R, Hogervorst FBL, van den Berg JG, Riethorst I, Schoenmaker L, van Beek D, de Bruijn E, van der Hoeven JJM, van Snellenberg H, van der Kolk LE, Cuppen E, Voest EE, Meijer GA, Monkhorst K. Optimized whole-genome sequencing workflow for tumor diagnostics in routine pathology practice. Nat Protoc 2024; 19:700-726. [PMID: 38092944 DOI: 10.1038/s41596-023-00933-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Accepted: 10/19/2023] [Indexed: 03/10/2024]
Abstract
Two decades after the genomics revolution, oncology is rapidly transforming into a genome-driven discipline, yet routine cancer diagnostics is still mainly microscopy based, except for tumor type-specific predictive molecular tests. Pathology laboratories struggle to quickly validate and adopt biomarkers identified by genomics studies of new targeted therapies. Consequently, clinical implementation of newly approved biomarkers suffers substantial delays, leading to unequal patient access to these therapies. Whole-genome sequencing (WGS) can successfully address these challenges by providing a stable molecular diagnostic platform that allows detection of a multitude of genomic alterations in a single cost-efficient assay and facilitating rapid implementation, as well as by the development of new genomic biomarkers. Recently, the Whole-genome sequencing Implementation in standard Diagnostics for Every cancer patient (WIDE) study demonstrated that WGS is a feasible and clinically valid technique in routine clinical practice with a turnaround time of 11 workdays. As a result, WGS was successfully implemented at the Netherlands Cancer Institute as part of routine diagnostics in January 2021. The success of implementing WGS has relied on adhering to a comprehensive protocol including recording patient information, sample collection, shipment and storage logistics, sequencing data interpretation and reporting, integration into clinical decision-making and data usage. This protocol describes the use of fresh-frozen samples that are necessary for WGS but can be challenging to implement in pathology laboratories accustomed to using formalin-fixed paraffin-embedded samples. In addition, the protocol outlines key considerations to guide uptake of WGS in routine clinical care in hospitals worldwide.
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Affiliation(s)
- Kris G Samsom
- Department of Pathology, Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Linda J W Bosch
- Department of Pathology, Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Luuk J Schipper
- Department of Molecular Oncology, Netherlands Cancer Institute, Amsterdam, the Netherlands
- Oncode Institute, Office Jaarbeurs Innovation Mile (JIM), Utrecht, the Netherlands
| | - Daoin Schout
- Department of Pathology, Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Paul Roepman
- Hartwig Medical Foundation, Science Park, Amsterdam, the Netherlands
| | - Mirjam C Boelens
- Department of Pathology, Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Ferry Lalezari
- Department of Radiology, Netherlands Cancer Institute, Amsterdam, the Netherlands
| | | | - Adrianus J de Langen
- Department of Thoracic Oncology, Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Tineke E Buffart
- Department of Medical Oncology, Amsterdam UMC, Amsterdam, the Netherlands
| | - Berit M H van Linder
- Department of Pathology, Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Kelly van Deventer
- Department of Pathology, Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Kay van den Burg
- Department of Pathology, Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Unga Unmehopa
- Department of Pathology, Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Efraim H Rosenberg
- Department of Pathology, Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Roelof Koster
- Department of Pathology, Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Frans B L Hogervorst
- Department of Pathology, Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - José G van den Berg
- Department of Pathology, Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Immy Riethorst
- Hartwig Medical Foundation, Science Park, Amsterdam, the Netherlands
| | - Lieke Schoenmaker
- Hartwig Medical Foundation, Science Park, Amsterdam, the Netherlands
| | - Daphne van Beek
- Hartwig Medical Foundation, Science Park, Amsterdam, the Netherlands
| | - Ewart de Bruijn
- Hartwig Medical Foundation, Science Park, Amsterdam, the Netherlands
| | | | | | | | - Edwin Cuppen
- Oncode Institute, Office Jaarbeurs Innovation Mile (JIM), Utrecht, the Netherlands
- Hartwig Medical Foundation, Science Park, Amsterdam, the Netherlands
- Center for Molecular Medicine, University Medical Centre Utrecht, Utrecht, the Netherlands
| | - Emile E Voest
- Department of Molecular Oncology, Netherlands Cancer Institute, Amsterdam, the Netherlands
- Oncode Institute, Office Jaarbeurs Innovation Mile (JIM), Utrecht, the Netherlands
- Department of Medical Oncology, Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Gerrit A Meijer
- Department of Pathology, Netherlands Cancer Institute, Amsterdam, the Netherlands.
| | - Kim Monkhorst
- Department of Pathology, Netherlands Cancer Institute, Amsterdam, the Netherlands
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Wigby KM, Brockman D, Costain G, Hale C, Taylor SL, Belmont J, Bick D, Dimmock D, Fernbach S, Greally J, Jobanputra V, Kulkarni S, Spiteri E, Taft RJ. Evidence review and considerations for use of first line genome sequencing to diagnose rare genetic disorders. NPJ Genom Med 2024; 9:15. [PMID: 38409289 PMCID: PMC10897481 DOI: 10.1038/s41525-024-00396-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2023] [Accepted: 01/26/2024] [Indexed: 02/28/2024] Open
Abstract
Early use of genome sequencing (GS) in the diagnostic odyssey can reduce suffering and improve care, but questions remain about which patient populations are most amenable to GS as a first-line diagnostic test. To address this, the Medical Genome Initiative conducted a literature review to identify appropriate clinical indications for GS. Studies published from January 2011 to August 2022 that reported on the diagnostic yield (DY) or clinical utility of GS were included. An exploratory meta-analysis using a random effects model evaluated DY based on cohort size and diagnosed cases per cohort. Seventy-one studies met inclusion criteria, comprising over 13,000 patients who received GS in one of the following settings: hospitalized pediatric patients, pediatric outpatients, adult outpatients, or mixed. GS was the first-line test in 38% (27/71). The unweighted mean DY of first-line GS was 45% (12-73%), 33% (6-86%) in cohorts with prior genetic testing, and 33% (9-60%) in exome-negative cohorts. Clinical utility was reported in 81% of first-line GS studies in hospitalized pediatric patients. Changes in management varied by cohort and underlying molecular diagnosis (24-100%). To develop evidence-informed points to consider, the quality of all 71 studies was assessed using modified American College of Radiology (ACR) criteria, with five core points to consider developed, including recommendations for use of GS in the N/PICU, in lieu of sequential testing and when disorders with substantial allelic heterogeneity are suspected. Future large and controlled studies in the pediatric and adult populations may support further refinement of these recommendations.
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Affiliation(s)
- Kristen M Wigby
- University of California, Davis, CA, USA.
- Rady Children's Institute for Genomic Medicine, San Diego, CA, USA.
| | | | | | | | | | - John Belmont
- Genetics & Genomics Services Inc, Houston, TX, USA
| | | | - David Dimmock
- Rady Children's Institute for Genomic Medicine, San Diego, CA, USA
| | | | - John Greally
- Albert Einstein College of Medicine, Bronx, NY, USA
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3
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Bagger FO, Borgwardt L, Jespersen AS, Hansen AR, Bertelsen B, Kodama M, Nielsen FC. Whole genome sequencing in clinical practice. BMC Med Genomics 2024; 17:39. [PMID: 38287327 PMCID: PMC10823711 DOI: 10.1186/s12920-024-01795-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Accepted: 01/01/2024] [Indexed: 01/31/2024] Open
Abstract
Whole genome sequencing (WGS) is becoming the preferred method for molecular genetic diagnosis of rare and unknown diseases and for identification of actionable cancer drivers. Compared to other molecular genetic methods, WGS captures most genomic variation and eliminates the need for sequential genetic testing. Whereas, the laboratory requirements are similar to conventional molecular genetics, the amount of data is large and WGS requires a comprehensive computational and storage infrastructure in order to facilitate data processing within a clinically relevant timeframe. The output of a single WGS analyses is roughly 5 MIO variants and data interpretation involves specialized staff collaborating with the clinical specialists in order to provide standard of care reports. Although the field is continuously refining the standards for variant classification, there are still unresolved issues associated with the clinical application. The review provides an overview of WGS in clinical practice - describing the technology and current applications as well as challenges connected with data processing, interpretation and clinical reporting.
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Affiliation(s)
- Frederik Otzen Bagger
- Center for Genomic Medicine, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Line Borgwardt
- Center for Genomic Medicine, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Andreas Sand Jespersen
- Center for Genomic Medicine, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Anna Reimer Hansen
- Center for Genomic Medicine, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Birgitte Bertelsen
- Center for Genomic Medicine, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Miyako Kodama
- Center for Genomic Medicine, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Finn Cilius Nielsen
- Center for Genomic Medicine, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark.
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4
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Nurchis MC, Radio FC, Salmasi L, Heidar Alizadeh A, Raspolini GM, Altamura G, Tartaglia M, Dallapiccola B, Damiani G. Bayesian cost-effectiveness analysis of Whole genome sequencing versus Whole exome sequencing in a pediatric population with suspected genetic disorders. Eur J Health Econ 2023:10.1007/s10198-023-01644-0. [PMID: 37975990 DOI: 10.1007/s10198-023-01644-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/25/2023] [Accepted: 10/25/2023] [Indexed: 11/19/2023]
Abstract
Genetic diseases are medical conditions caused by sequence or structural changes in an individual's genome. Whole exome sequencing (WES) and whole genome sequencing (WGS) are increasingly used for diagnosing suspected genetic conditions in children to reduce the diagnostic delay and accelerating the implementation of appropriate treatments. While more information is becoming available on clinical efficacy and economic sustainability of WES, the broad implementation of WGS is still hindered by higher complexity and economic issues. The aim of this study is to estimate the cost-effectiveness of WGS versus WES and standard testing for pediatric patients with suspected genetic disorders. A Bayesian decision tree model was set up. Model parameters were retrieved both from hospital administrative datasets and scientific literature. The analysis considered a lifetime time frame and adopted the perspective of the Italian National Health Service (NHS). Bayesian inference was performed using the Markov Chain Monte Carlo simulation method. Uncertainty was explored through a probabilistic sensitivity analysis (PSA) and a value of information analysis (VOI). The present analysis showed that implementing first-line WGS would be a cost-effective strategy, against the majority of the other tested alternatives at a threshold of €30,000-50,000, for diagnosing outpatient pediatric patients with suspected genetic disorders. According to the sensitivity analyses, the findings were robust to most assumption and parameter uncertainty. Lessons learnt from this modeling study reinforces the adoption of first-line WGS, as a cost-effective strategy, depending on actual difficulties for the NHS to properly allocate limited resources.
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Affiliation(s)
- Mario Cesare Nurchis
- School of Economics, Università Cattolica del Sacro Cuore, Largo Francesco Vito 1, 00168, Rome, Italy.
- Department of Woman and Child Health and Public Health, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168, Rome, Italy.
| | | | - Luca Salmasi
- Department of Economics and Finance, Università Cattolica del Sacro Cuore, 00168, Rome, Italy
| | - Aurora Heidar Alizadeh
- Department of Health Sciences and Public Health, Section of Hygiene, Università Cattolica del Sacro Cuore, 00168, Rome, Italy
| | - Gian Marco Raspolini
- Department of Health Sciences and Public Health, Section of Hygiene, Università Cattolica del Sacro Cuore, 00168, Rome, Italy
| | - Gerardo Altamura
- Department of Health Sciences and Public Health, Section of Hygiene, Università Cattolica del Sacro Cuore, 00168, Rome, Italy
| | - Marco Tartaglia
- Molecular Genetics and Functional Genomics, Ospedale Pediatrico Bambino Gesù IRCCS, 00146, Rome, Italy
| | - Bruno Dallapiccola
- Molecular Genetics and Functional Genomics, Ospedale Pediatrico Bambino Gesù IRCCS, 00146, Rome, Italy
| | - Gianfranco Damiani
- Department of Woman and Child Health and Public Health, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168, Rome, Italy
- Department of Health Sciences and Public Health, Section of Hygiene, Università Cattolica del Sacro Cuore, 00168, Rome, Italy
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5
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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. Structural and non-coding variants increase the diagnostic yield of clinical whole genome sequencing for rare diseases. Genome Med 2023; 15:94. [PMID: 37946251 PMCID: PMC10636885 DOI: 10.1186/s13073-023-01240-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Accepted: 09/27/2023] [Indexed: 11/12/2023] Open
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.
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Affiliation(s)
- Alistair T Pagnamenta
- Wellcome Centre for Human Genetics, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7BN, UK
- NIHR Oxford Biomedical Research Centre, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 9DU, UK
| | - Carme Camps
- Wellcome Centre for Human Genetics, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7BN, UK
- NIHR Oxford Biomedical Research Centre, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 9DU, UK
| | - Edoardo Giacopuzzi
- Wellcome Centre for Human Genetics, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7BN, UK
- NIHR Oxford Biomedical Research Centre, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 9DU, UK
- Human Technopole, Viale Rita Levi Montalcini 1, 20157, Milan, Italy
| | - John M Taylor
- NIHR Oxford Biomedical Research Centre, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 9DU, UK
- Oxford Genetics Laboratories, Oxford University Hospitals NHS Foundation Trust, Churchill Hospital, Old Road, Oxford, OX3 7LE, UK
| | - Mona Hashim
- Wellcome Centre for Human Genetics, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7BN, UK
- NIHR Oxford Biomedical Research Centre, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 9DU, UK
| | - Eduardo Calpena
- NIHR Oxford Biomedical Research Centre, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 9DU, UK
- MRC Weatherall Institute of Molecular Medicine, University of Oxford, John Radcliffe Hospital, Oxford, OX3 9DS, UK
| | - Pamela J Kaisaki
- Wellcome Centre for Human Genetics, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7BN, UK
- NIHR Oxford Biomedical Research Centre, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 9DU, UK
| | - Akiko Hashimoto
- MRC Weatherall Institute of Molecular Medicine, University of Oxford, John Radcliffe Hospital, Oxford, OX3 9DS, UK
| | - Jing Yu
- Wellcome Centre for Human Genetics, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7BN, UK
- NIHR Oxford Biomedical Research Centre, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 9DU, UK
| | - Edward Sanders
- MRC Weatherall Institute of Molecular Medicine, University of Oxford, John Radcliffe Hospital, Oxford, OX3 9DS, UK
| | - Ron Schwessinger
- MRC Weatherall Institute of Molecular Medicine, University of Oxford, John Radcliffe Hospital, Oxford, OX3 9DS, UK
| | - Jim R Hughes
- MRC Weatherall Institute of Molecular Medicine, University of Oxford, John Radcliffe Hospital, Oxford, OX3 9DS, UK
| | - Gerton Lunter
- MRC Weatherall Institute of Molecular Medicine, University of Oxford, John Radcliffe Hospital, Oxford, OX3 9DS, UK
- University Medical Center Groningen, Groningen University, PO Box 72, 9700 AB, Groningen, The Netherlands
| | - Helene Dreau
- NIHR Oxford Biomedical Research Centre, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 9DU, UK
- Department of Oncology, Oxford Molecular Diagnostics Centre, University of Oxford, Level 4, John Radcliffe Hospital, Headley Way, Oxford, OX3 9DU, UK
| | - Matteo Ferla
- Wellcome Centre for Human Genetics, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7BN, UK
- NIHR Oxford Biomedical Research Centre, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 9DU, UK
| | - Lukas Lange
- Wellcome Centre for Human Genetics, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7BN, UK
- NIHR Oxford Biomedical Research Centre, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 9DU, UK
| | - Yesim Kesim
- Wellcome Centre for Human Genetics, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7BN, UK
- NIHR Oxford Biomedical Research Centre, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 9DU, UK
| | - Vassilis Ragoussis
- Wellcome Centre for Human Genetics, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7BN, UK
- NIHR Oxford Biomedical Research Centre, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 9DU, UK
| | - Dimitrios V Vavoulis
- Wellcome Centre for Human Genetics, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7BN, UK
- NIHR Oxford Biomedical Research Centre, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 9DU, UK
- Department of Oncology, Oxford Molecular Diagnostics Centre, University of Oxford, Level 4, John Radcliffe Hospital, Headley Way, Oxford, OX3 9DU, UK
| | - Holger Allroggen
- Neurosciences Department, UHCW NHS Trust, Clifford Bridge Road, Coventry, CV2 2DX, UK
| | - Olaf Ansorge
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, UK
| | - Christian Babbs
- MRC Weatherall Institute of Molecular Medicine, University of Oxford, John Radcliffe Hospital, Oxford, OX3 9DS, UK
| | - Siddharth Banka
- Division of Evolution, Infection and Genomics, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
- Manchester Centre for Genomic Medicine, Saint Mary's Hospital, Oxford Road, Manchester, M13 9WL, UK
| | - Benito Baños-Piñero
- Oxford Genetics Laboratories, Oxford University Hospitals NHS Foundation Trust, Churchill Hospital, Old Road, Oxford, OX3 7LE, UK
| | - David Beeson
- MRC Weatherall Institute of Molecular Medicine, University of Oxford, John Radcliffe Hospital, Oxford, OX3 9DS, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, UK
| | - Tal Ben-Ami
- Pediatric Hematology-Oncology Unit, Kaplan Medical Center, Rehovot, Israel
| | - David L Bennett
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, UK
| | - Celeste Bento
- Hematology Department, Hospitais da Universidade de Coimbra, Coimbra, Portugal
| | - Edward Blair
- NIHR Oxford Biomedical Research Centre, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 9DU, UK
- Oxford Centre for Genomic Medicine, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 7LE, UK
| | - Charlotte Brasch-Andersen
- Department of Clinical Genetics, Odense University Hospital and Department of Clinical Research, University of Southern Denmark, Odense, Denmark
| | - Katherine R Bull
- Wellcome Centre for Human Genetics, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7BN, UK
- Nuffield Department of Medicine, University of Oxford, Oxford, OX3 7BN, UK
| | - Holger Cario
- Department of Pediatrics and Adolescent Medicine, University Medical Center, Eythstrasse 24, 89075, Ulm, Germany
| | - Deirdre Cilliers
- Oxford Centre for Genomic Medicine, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 7LE, UK
| | - Valerio Conti
- Neuroscience Department, Meyer Children's Hospital IRCCS, Viale Pieraccini 24, 50139, Florence, Italy
| | - E Graham Davies
- Department of Immunology, Great Ormond Street Hospital for Children NHS Trust and UCL Great Ormond Street Institute of Child Health, Zayed Centre for Research, 2Nd Floor, 20C Guilford Street, London, WC1N 1DZ, UK
| | - Fatima Dhalla
- Department of Paediatrics, Institute of Developmental and Regenerative Medicine, IMS-Tetsuya Nakamura Building, Old Road Campus, Roosevelt Drive, Oxford, OX3 7TY, UK
| | - Beatriz Diez Dacal
- Oxford Genetics Laboratories, Oxford University Hospitals NHS Foundation Trust, Churchill Hospital, Old Road, Oxford, OX3 7LE, UK
| | - Yin Dong
- MRC Weatherall Institute of Molecular Medicine, University of Oxford, John Radcliffe Hospital, Oxford, OX3 9DS, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, UK
| | - James E Dunford
- Oxford NIHR Musculoskeletal BRC and Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, Nuffield Orthopaedic Centre, Old Road, Oxford, OX3 7HE, UK
| | - Renzo Guerrini
- Neuroscience Department, Meyer Children's Hospital IRCCS, Viale Pieraccini 24, 50139, Florence, Italy
| | - Adrian L Harris
- Department of Oncology, University of Oxford, Old Road Campus Research Building, Oxford, OX3 7DQ, UK
| | - Jane Hartley
- Liver Unit, Birmingham Women's & Children's Hospital and University of Birmingham, Steelhouse Lane, Birmingham, B4 6NH, UK
| | - Georg Hollander
- Department of Paediatrics, University of Oxford, Level 2, Children's Hospital, John Radcliffe Hospital, Oxford, OX3 9DU, UK
| | - Kassim Javaid
- Oxford NIHR Musculoskeletal BRC and Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, Nuffield Orthopaedic Centre, Old Road, Oxford, OX3 7HE, UK
| | - Maureen Kane
- Department of Pharmaceutical Sciences, School of Pharmacy, University of Maryland, Pharmacy Hall North, Room 731, 20 N. Pine Street, Baltimore, MD, 21201, USA
| | - Deirdre Kelly
- Liver Unit, Birmingham Women's & Children's Hospital and University of Birmingham, Steelhouse Lane, Birmingham, B4 6NH, UK
| | - Dominic Kelly
- Children's Hospital, OUH NHS Foundation Trust, NIHR Oxford BRC, Headley Way, Oxford, OX3 9DU, UK
| | - Samantha J L Knight
- Wellcome Centre for Human Genetics, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7BN, UK
- NIHR Oxford Biomedical Research Centre, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 9DU, UK
| | - Alexandra Y Kreins
- Department of Immunology, Great Ormond Street Hospital for Children NHS Trust and UCL Great Ormond Street Institute of Child Health, Zayed Centre for Research, 2Nd Floor, 20C Guilford Street, London, WC1N 1DZ, UK
| | - Erika M Kvikstad
- Wellcome Centre for Human Genetics, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7BN, UK
- NIHR Oxford Biomedical Research Centre, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 9DU, UK
| | - Craig B Langman
- Feinberg School of Medicine, Northwestern University, 211 E Chicago Avenue, Chicago, IL, MS37, USA
| | - Tracy Lester
- Oxford Genetics Laboratories, Oxford University Hospitals NHS Foundation Trust, Churchill Hospital, Old Road, Oxford, OX3 7LE, UK
| | - Kate E Lines
- NIHR Oxford Biomedical Research Centre, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 9DU, UK
- University of Oxford, Academic Endocrine Unit, OCDEM, Churchill Hospital, Oxford, OX3 7LJ, UK
| | - Simon R Lord
- Early Phase Clinical Trials Unit, Department of Oncology, University of Oxford, Cancer and Haematology Centre, Level 2 Administration Area, Churchill Hospital, Oxford, OX3 7LJ, UK
| | - Xin Lu
- Nuffield Department of Clinical Medicine, Ludwig Institute for Cancer Research, University of Oxford, Old Road Campus Research Building, Oxford, OX3 7DQ, UK
| | - Sahar Mansour
- St George's University Hospitals NHS Foundation Trust, Blackshore Road, Tooting, London, SW17 0QT, UK
| | - Adnan Manzur
- MRC Centre for Neuromuscular Diseases, National Hospital for Neurology and Neurosurgery, Queen Square, London, WC1N 3BG, UK
| | - Reza Maroofian
- Department of Neuromuscular Diseases, UCL Queen Square Institute of Neurology and The National Hospital for Neurology and Neurosurgery, London, WC1N 3BG, UK
| | - Brian Marsden
- Nuffield Department of Medicine, Kennedy Institute, University of Oxford, Oxford, OX3 7BN, UK
| | - Joanne Mason
- Yourgene Health Headquarters, Skelton House, Lloyd Street North, Manchester Science Park, Manchester, M15 6SH, UK
| | - Simon J McGowan
- MRC Weatherall Institute of Molecular Medicine, University of Oxford, John Radcliffe Hospital, Oxford, OX3 9DS, UK
| | - Davide Mei
- Neuroscience Department, Meyer Children's Hospital IRCCS, Viale Pieraccini 24, 50139, Florence, Italy
| | - Hana Mlcochova
- MRC Weatherall Institute of Molecular Medicine, University of Oxford, John Radcliffe Hospital, Oxford, OX3 9DS, UK
| | - Yoshiko Murakami
- Research Institute for Microbial Diseases, Osaka University, 3-1 Yamadaoka, Suita, Osaka, 565-0871, Japan
| | - Andrea H Németh
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, UK
- Oxford Centre for Genomic Medicine, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 7LE, UK
| | - Steven Okoli
- Imperial College NHS Trust, Department of Haematology, Hammersmith Hospital, Du Cane Road, London, W12 0HS, UK
| | - Elizabeth Ormondroyd
- NIHR Oxford Biomedical Research Centre, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 9DU, UK
- University of Oxford, Level 6 West Wing, Oxford, OX3 9DU, JR, UK
| | - Lilian Bomme Ousager
- Department of Clinical Genetics, Odense University Hospital and Department of Clinical Research, University of Southern Denmark, Odense, Denmark
| | - Jacqueline Palace
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, UK
| | - Smita Y Patel
- Clinical Immunology, John Radcliffe Hospital, Level 4A, Oxford, OX3 9DU, UK
| | - Melissa M Pentony
- Wellcome Centre for Human Genetics, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7BN, UK
- NIHR Oxford Biomedical Research Centre, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 9DU, UK
| | - Chris Pugh
- Nuffield Department of Medicine, University of Oxford, Oxford, OX3 7BN, UK
| | - Aboulfazl Rad
- Department of Otolaryngology-Head & Neck Surgery, Tübingen Hearing Research Centre, Eberhard Karls University, Elfriede-Aulhorn-Str. 5, 72076, Tübingen, Germany
| | - Archana Ramesh
- Wellcome Centre for Human Genetics, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7BN, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, UK
| | - Simone G Riva
- MRC Weatherall Institute of Molecular Medicine, University of Oxford, John Radcliffe Hospital, Oxford, OX3 9DS, UK
| | - Irene Roberts
- MRC Weatherall Institute of Molecular Medicine, University of Oxford, John Radcliffe Hospital, Oxford, OX3 9DS, UK
- Department of Paediatrics, University of Oxford, Level 2, Children's Hospital, John Radcliffe Hospital, Oxford, OX3 9DU, UK
| | - Noémi Roy
- Department of Haematology, Oxford University Hospitals NHS Foundation Trust, Level 4, Haematology, John Radcliffe Hospital, Oxford, OX3 9DU, UK
| | - Outi Salminen
- NIHR Oxford Biomedical Research Centre, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 9DU, UK
- Department of Oncology, Oxford Molecular Diagnostics Centre, University of Oxford, Level 4, John Radcliffe Hospital, Headley Way, Oxford, OX3 9DU, UK
| | - Kyleen D Schilling
- Ann & Robert H. Lurie Children's Hospital of Chicago, 225 E Chicago Avenue, Chicago, IL, 60611, USA
| | - Caroline Scott
- MRC Weatherall Institute of Molecular Medicine, University of Oxford, John Radcliffe Hospital, Oxford, OX3 9DS, UK
| | - Arjune Sen
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, UK
| | - Conrad Smith
- Oxford Genetics Laboratories, Oxford University Hospitals NHS Foundation Trust, Churchill Hospital, Old Road, Oxford, OX3 7LE, UK
| | - Mark Stevenson
- University of Oxford, Academic Endocrine Unit, OCDEM, Churchill Hospital, Oxford, OX3 7LJ, UK
| | - Rajesh V Thakker
- University of Oxford, Academic Endocrine Unit, OCDEM, Churchill Hospital, Oxford, OX3 7LJ, UK
| | - Stephen R F Twigg
- MRC Weatherall Institute of Molecular Medicine, University of Oxford, John Radcliffe Hospital, Oxford, OX3 9DS, UK
| | - Holm H Uhlig
- NIHR Oxford Biomedical Research Centre, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 9DU, UK
- Department of Paediatrics, University of Oxford, Level 2, Children's Hospital, John Radcliffe Hospital, Oxford, OX3 9DU, UK
- Translational Gastroenterology Unit, John Radcliffe Hospital, Oxford, OX3 9DU, UK
| | - Richard van Wijk
- UMC Utrecht, Heidelberglaan 100, 3584 CX, Utrecht, The Netherlands
| | - Barbara Vona
- Department of Otolaryngology-Head & Neck Surgery, Tübingen Hearing Research Centre, Eberhard Karls University, Elfriede-Aulhorn-Str. 5, 72076, Tübingen, Germany
- Institute of Human Genetics, University Medical Center Göttingen, Heinrich-Düker-Weg 12, 37073, Göttingen, Germany
- Institute for Auditory Neuroscience and InnerEarLab, University Medical Center Göttingen, Robert-Koch-Str. 40, 37075, Göttingen, Germany
| | - Steven Wall
- Oxford Craniofacial Unit, John Radcliffe Hospital, Level LG1, West Wing, Oxford, OX3 9DU, UK
| | - Jing Wang
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, UK
| | - Hugh Watkins
- NIHR Oxford Biomedical Research Centre, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 9DU, UK
- University of Oxford, Level 6 West Wing, Oxford, OX3 9DU, JR, UK
| | - Jaroslav Zak
- Nuffield Department of Clinical Medicine, Ludwig Institute for Cancer Research, University of Oxford, Old Road Campus Research Building, Oxford, OX3 7DQ, UK
- Department of Immunology and Microbiology, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, CA, 92037, USA
| | - Anna H Schuh
- Department of Oncology, Oxford Molecular Diagnostics Centre, University of Oxford, Level 4, John Radcliffe Hospital, Headley Way, Oxford, OX3 9DU, UK
| | - Usha Kini
- NIHR Oxford Biomedical Research Centre, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 9DU, UK
- Oxford Centre for Genomic Medicine, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 7LE, UK
| | - Andrew O M Wilkie
- NIHR Oxford Biomedical Research Centre, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 9DU, UK
- MRC Weatherall Institute of Molecular Medicine, University of Oxford, John Radcliffe Hospital, Oxford, OX3 9DS, UK
| | - Niko Popitsch
- Wellcome Centre for Human Genetics, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7BN, UK
- NIHR Oxford Biomedical Research Centre, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 9DU, UK
- Department of Biochemistry and Cell Biology, Max Perutz Labs, University of Vienna, Vienna BioCenter(VBC), Dr.-Bohr-Gasse 9, 1030, Vienna, Austria
| | - Jenny C Taylor
- Wellcome Centre for Human Genetics, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7BN, UK.
- NIHR Oxford Biomedical Research Centre, John Radcliffe Hospital, Oxford University Hospitals NHS Foundation Trust, Oxford, OX3 9DU, UK.
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6
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Jo HS, Yang M, Ahn SY, Sung SI, Park WS, Jang JH, Chang YS. Optimal Protocols and Management of Clinical and Genomic Data Collection to Assist in the Early Diagnosis and Treatment of Multiple Congenital Anomalies. Children (Basel) 2023; 10:1673. [PMID: 37892336 PMCID: PMC10605914 DOI: 10.3390/children10101673] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/20/2023] [Revised: 10/01/2023] [Accepted: 10/07/2023] [Indexed: 10/29/2023]
Abstract
Standardized protocols have been designed and developed specifically for clinical information collection and obtaining trio genomic information from infants affected with congenital anomalies (CA) and their parents, as well as securing human biological resources. The protocols include clinical and genomic information collection on multiple CA that were difficult to diagnose using pre-existing screening methods. We obtained human-derived resources and genomic information from 138 cases, including 45 families of infants with CA and their parent trios. For the clinical information collection protocol, criteria for target patient selection and a consent system for collecting and utilizing research resources are crucial. Whole genome sequencing data were generated for all participants, and standardized protocols were developed for resource collection and manufacturing. We recorded the phenotype information according to the Human Phenotype Ontology term, and epidemiological information was collected through an environmental factor questionnaire. Updating and recording of clinical symptoms and genetic information that have been newly added or changed over time are significant. The protocols enabled long-term tracking by including the growth and development status that reflect the important characteristics of newborns. Using these clinical and genetic information collection protocols for CA, an essential platform for early genetic diagnosis and diagnostic research can be established, and new genetic diagnostic guidelines can be presented in the near future.
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Affiliation(s)
- Heui Seung Jo
- Department of Pediatrics, Kangwon National University Hospital, Kangwon National University School of Medicine, Kangwon 24289, Republic of Korea
| | - Misun Yang
- Department of Pediatrics, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Republic of Korea
- Cell and Gene Therapy Institute, Samsung Medical Center, Seoul 06351, Republic of Korea
| | - So Yoon Ahn
- Department of Pediatrics, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Republic of Korea
- Cell and Gene Therapy Institute, Samsung Medical Center, Seoul 06351, Republic of Korea
| | - Se In Sung
- Department of Pediatrics, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Republic of Korea
- Cell and Gene Therapy Institute, Samsung Medical Center, Seoul 06351, Republic of Korea
| | - Won Soon Park
- Department of Pediatrics, CHA Gangnam Medical Center, CHA University, Seoul 06135, Republic of Korea
| | - Ja-Hyun Jang
- Department of Laboratory Medicine and Genetics, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Republic of Korea
| | - Yun Sil Chang
- Department of Pediatrics, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Republic of Korea
- Cell and Gene Therapy Institute, Samsung Medical Center, Seoul 06351, Republic of Korea
- Department of Health Sciences and Technology, Samsung Advanced Institute for Health Sciences and Technology, Sungkyunkwan University, Seoul 06351, Republic of Korea
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7
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Lowther C, Valkanas E, Giordano JL, Wang HZ, Currall BB, O'Keefe K, Pierce-Hoffman E, Kurtas NE, Whelan CW, Hao SP, Weisburd B, Jalili V, Fu J, Wong I, Collins RL, Zhao X, Austin-Tse CA, Evangelista E, Lemire G, Aggarwal VS, Lucente D, Gauthier LD, Tolonen C, Sahakian N, Stevens C, An JY, Dong S, Norton ME, MacKenzie TC, Devlin B, Gilmore K, Powell BC, Brandt A, Vetrini F, DiVito M, Sanders SJ, MacArthur DG, Hodge JC, O'Donnell-Luria A, Rehm HL, Vora NL, Levy B, Brand H, Wapner RJ, Talkowski ME. Systematic evaluation of genome sequencing for the diagnostic assessment of autism spectrum disorder and fetal structural anomalies. Am J Hum Genet 2023; 110:1454-1469. [PMID: 37595579 PMCID: PMC10502737 DOI: 10.1016/j.ajhg.2023.07.010] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Revised: 07/25/2023] [Accepted: 07/25/2023] [Indexed: 08/20/2023] Open
Abstract
Short-read genome sequencing (GS) holds the promise of becoming the primary diagnostic approach for the assessment of autism spectrum disorder (ASD) and fetal structural anomalies (FSAs). However, few studies have comprehensively evaluated its performance against current standard-of-care diagnostic tests: karyotype, chromosomal microarray (CMA), and exome sequencing (ES). To assess the clinical utility of GS, we compared its diagnostic yield against these three tests in 1,612 quartet families including an individual with ASD and in 295 prenatal families. Our GS analytic framework identified a diagnostic variant in 7.8% of ASD probands, almost 2-fold more than CMA (4.3%) and 3-fold more than ES (2.7%). However, when we systematically captured copy-number variants (CNVs) from the exome data, the diagnostic yield of ES (7.4%) was brought much closer to, but did not surpass, GS. Similarly, we estimated that GS could achieve an overall diagnostic yield of 46.1% in unselected FSAs, representing a 17.2% increased yield over karyotype, 14.1% over CMA, and 4.1% over ES with CNV calling or 36.1% increase without CNV discovery. Overall, GS provided an added diagnostic yield of 0.4% and 0.8% beyond the combination of all three standard-of-care tests in ASD and FSAs, respectively. This corresponded to nine GS unique diagnostic variants, including sequence variants in exons not captured by ES, structural variants (SVs) inaccessible to existing standard-of-care tests, and SVs where the resolution of GS changed variant classification. Overall, this large-scale evaluation demonstrated that GS significantly outperforms each individual standard-of-care test while also outperforming the combination of all three tests, thus warranting consideration as the first-tier diagnostic approach for the assessment of ASD and FSAs.
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Affiliation(s)
- Chelsea Lowther
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA; Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA; Department of Neurology, Harvard Medical School, Boston, MA, USA
| | - Elise Valkanas
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA; Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA; Program in Biological and Biomedical Sciences, Division of Medical Sciences, Harvard Medical School, Boston, MA, USA
| | - Jessica L Giordano
- Department of Obstetrics & Gynecology, Columbia University Medical Center, New York, NY, USA
| | - Harold Z Wang
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA; Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Benjamin B Currall
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA; Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA; Department of Neurology, Harvard Medical School, Boston, MA, USA
| | - Kathryn O'Keefe
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA; Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Emma Pierce-Hoffman
- Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Nehir E Kurtas
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA; Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA; Department of Neurology, Harvard Medical School, Boston, MA, USA
| | - Christopher W Whelan
- Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Stephanie P Hao
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA; Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Ben Weisburd
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA; Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Vahid Jalili
- Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Jack Fu
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA; Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA; Department of Neurology, Harvard Medical School, Boston, MA, USA
| | - Isaac Wong
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA; Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Ryan L Collins
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA; Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA; Program in Bioinformatics and Integrative Genomics, Division of Medical Sciences, Harvard Medical School, Boston, MA, USA
| | - Xuefang Zhao
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA; Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA; Department of Neurology, Harvard Medical School, Boston, MA, USA
| | - Christina A Austin-Tse
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA; Department of Pathology, Harvard Medical School, Boston, MA, USA
| | - Emily Evangelista
- Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Gabrielle Lemire
- Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Vimla S Aggarwal
- Department of Pathology and Cell Biology, Columbia University Medical Center, New York, NY, USA
| | - Diane Lucente
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Laura D Gauthier
- Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA; Data Science Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Charlotte Tolonen
- Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA; Data Science Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Nareh Sahakian
- Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA; Data Science Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Christine Stevens
- Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Joon-Yong An
- School of Biosystem and Biomedical Science, Korea University, Seoul, South Korea
| | - Shan Dong
- Department of Psychiatry, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Mary E Norton
- Center for Maternal-Fetal Precision Medicine, University of California, San Francisco, San Francisco, CA, USA; Department of Obstetrics, Gynecology, and Reproductive Sciences, University of California, San Francisco, San Francisco, California, USA
| | - Tippi C MacKenzie
- Center for Maternal-Fetal Precision Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Bernie Devlin
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Kelly Gilmore
- Department of Obstetrics and Gynecology, Division of Maternal-Fetal Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Bradford C Powell
- Department of Genetics, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Alicia Brandt
- Department of Genetics, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Francesco Vetrini
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Michelle DiVito
- Department of Obstetrics & Gynecology, Columbia University Medical Center, New York, NY, USA
| | - Stephan J Sanders
- Department of Psychiatry, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Daniel G MacArthur
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA; Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA; Centre for Population Genomics, Garvan Institute of Medical Research, and University of New South Wales Sydney, Sydney, NSW, Australia; Centre for Population Genomics, Murdoch Children's Research Institute, Melbourne, VIC, Australia
| | - Jennelle C Hodge
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Anne O'Donnell-Luria
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA; Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA; Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA, USA
| | - Heidi L Rehm
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA; Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Neeta L Vora
- Department of Obstetrics and Gynecology, Division of Maternal-Fetal Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Brynn Levy
- Department of Pathology and Cell Biology, Columbia University Medical Center, New York, NY, USA
| | - Harrison Brand
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA; Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA; Department of Neurology, Harvard Medical School, Boston, MA, USA
| | - Ronald J Wapner
- Department of Obstetrics & Gynecology, Columbia University Medical Center, New York, NY, USA
| | - Michael E Talkowski
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA; Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA; Department of Neurology, Harvard Medical School, Boston, MA, USA; Program in Biological and Biomedical Sciences, Division of Medical Sciences, Harvard Medical School, Boston, MA, USA; Program in Bioinformatics and Integrative Genomics, Division of Medical Sciences, Harvard Medical School, Boston, MA, USA.
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8
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Halley MC, Olson NW. Blurred Boundaries: Toward an Expanded Ethics of Research and Clinical Care. Am J Bioeth 2023; 23:5-9. [PMID: 38410998 DOI: 10.1080/15265161.2023.2224148] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/28/2024]
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9
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Nurchis MC, Altamura G, Riccardi MT, Radio FC, Chillemi G, Bertini ES, Garlasco J, Tartaglia M, Dallapiccola B, Damiani G. Whole genome sequencing diagnostic yield for paediatric patients with suspected genetic disorders: systematic review, meta-analysis, and GRADE assessment. Arch Public Health 2023; 81:93. [PMID: 37231492 DOI: 10.1186/s13690-023-01112-4] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2022] [Accepted: 05/18/2023] [Indexed: 05/27/2023] Open
Abstract
BACKGROUND About 80% of the roughly 7,000 known rare diseases are single gene disorders, about 85% of which are ultra-rare, affecting less than one in one million individuals. NGS technologies, in particular whole genome sequencing (WGS) in paediatric patients suffering from severe disorders of likely genetic origin improve the diagnostic yield allowing targeted, effective care and management. The aim of this study is to perform a systematic review and meta-analysis to assess the effectiveness of WGS, with respect to whole exome sequencing (WES) and/or usual care, for the diagnosis of suspected genetic disorders among the paediatric population. METHODS A systematic review of the literature was conducted querying relevant electronic databases, including MEDLINE, EMBASE, ISI Web of Science, and Scopus from January 2010 to June 2022. A random-effect meta-analysis was run to inspect the diagnostic yield of different techniques. A network meta-analysis was also performed to directly assess the comparison between WGS and WES. RESULTS Of the 4,927 initially retrieved articles, thirty-nine met the inclusion criteria. Overall results highlighted a significantly higher pooled diagnostic yield for WGS, 38.6% (95% CI: [32.6 - 45.0]), in respect to WES, 37.8% (95% CI: [32.9 - 42.9]) and usual care, 7.8% (95% CI: [4.4 - 13.2]). The meta-regression output suggested a higher diagnostic yield of the WGS compared to WES after controlling for the type of disease (monogenic vs non-monogenic), with a tendency to better diagnostic performances for Mendelian diseases. The network meta-analysis showed a higher diagnostic yield for WGS compared to WES (OR = 1.54, 95%CI: [1.11 - 2.12]). CONCLUSIONS Although whole genome sequencing for the paediatric population with suspected genetic disorders provided an accurate and early genetic diagnosis in a high proportion of cases, further research is needed for evaluating costs, effectiveness, and cost-effectiveness of WGS and achieving an informed decision-making process. TRIAL REGISTRATION This systematic review has not been registered.
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Grants
- RF-2018-12,366,391, 2018 Ministero della Salute
- RF-2018-12,366,391, 2018 Ministero della Salute
- RF-2018-12,366,391, 2018 Ministero della Salute
- RF-2018-12,366,391, 2018 Ministero della Salute
- RF-2018-12,366,391, 2018 Ministero della Salute
- RF-2018-12,366,391, 2018 Ministero della Salute
- RF-2018-12,366,391, 2018 Ministero della Salute
- RF-2018-12,366,391, 2018 Ministero della Salute
- RF-2018-12,366,391, 2018 Ministero della Salute
- RF-2018-12,366,391, 2018 Ministero della Salute
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Affiliation(s)
- Mario Cesare Nurchis
- Department of Woman and Child Health and Public Health, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168, Rome, Italy
- School of Economics, Università Cattolica del Sacro Cuore, 00168, Rome, Italy
| | - Gerardo Altamura
- Department of Health Sciences and Public Health, Section of Hygiene, Università Cattolica del Sacro Cuore, Largo Francesco Vito 1, 00168, Rome, Italy.
| | - Maria Teresa Riccardi
- Department of Health Sciences and Public Health, Section of Hygiene, Università Cattolica del Sacro Cuore, Largo Francesco Vito 1, 00168, Rome, Italy
| | - Francesca Clementina Radio
- Genetics and Rare Diseases Research Division, Ospedale Pediatrico Bambino Gesù IRCCS, 00146, Rome, Italy
| | - Giovanni Chillemi
- Department for Innovation in Biological Agro-Food and Forest Systems (DIBAF), University of Tuscia, 01100, Viterbo, Italy
- Institute of Biomembranes, Bioenergetics and Molecular Biotechnologies, Centro Nazionale Delle Ricerche, 70126, Bari, Italy
| | - Enrico Silvio Bertini
- Genetics and Rare Diseases Research Division, Ospedale Pediatrico Bambino Gesù IRCCS, 00146, Rome, Italy
| | - Jacopo Garlasco
- Department of Public Health Sciences and Paediatrics, University of Turin, 10126, Turin, Italy
| | - Marco Tartaglia
- Genetics and Rare Diseases Research Division, Ospedale Pediatrico Bambino Gesù IRCCS, 00146, Rome, Italy
| | - Bruno Dallapiccola
- Genetics and Rare Diseases Research Division, Ospedale Pediatrico Bambino Gesù IRCCS, 00146, Rome, Italy
| | - Gianfranco Damiani
- Department of Woman and Child Health and Public Health, Fondazione Policlinico Universitario A. Gemelli IRCCS, 00168, Rome, Italy
- Department of Health Sciences and Public Health, Section of Hygiene, Università Cattolica del Sacro Cuore, Largo Francesco Vito 1, 00168, Rome, Italy
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10
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Dahmer M, Jennings A, Parker M, Sanchez-Pinto LN, Thompson A, Traube C, Zimmerman JJ. Pediatric Critical Care in the Twenty-first Century and Beyond. Crit Care Clin 2023; 39:407-425. [PMID: 36898782 DOI: 10.1016/j.ccc.2022.09.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Pediatric critical care addresses prevention, diagnosis, and treatment of organ dysfunction in the setting of increasingly complex patients, therapies, and environments. Soon burgeoning data science will enable all aspects of intensive care: driving facilitated diagnostics, empowering a learning health-care environment, promoting continuous advancement of care, and informing the continuum of critical care outside the intensive care unit preceding and following critical illness/injury. Although novel technology will progressively objectify personalized critical care, humanism, practiced at the bedside, defines the essence of pediatric critical care now and in the future.
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Affiliation(s)
- Mary Dahmer
- Division of Critical Care, Department of Pediatrics, University of Michigan, 1500 East Medical Center Drive, F6790/5243, Ann Arbor, MI, USA
| | - Aimee Jennings
- Division of Critical Care Medicine, Advanced Practice, FA.2.112, Seattle Children's Hospital, 4800 Sandpoint Way Northeast, Seattle, WA 98105, USA
| | - Margaret Parker
- Department of Pediatrics, Stony Brook University, 7762 Bloomfield Road, Easton, MD 21601, USA
| | - Lazaro N Sanchez-Pinto
- Department of Pediatrics, Ann and Robert H Lurie Children's Hospital of Chicago, Northwestern University Feinberg School of Medicine, 225 East Chicago Avenue, Box 73, Chicago, IL 60611-2605, USA
| | - Ann Thompson
- Department of Critical Care Medicine, University of Pittsburgh, 3550 Terrace Street, Pittsburgh, PA 15261, USA
| | - Chani Traube
- Department of Pediatrics, Weill Cornell Medicine, 525 East 68th Street, Box 225, New York, NY 10065, USA
| | - Jerry J Zimmerman
- Department of Pediatrics, FA.2.300B Seattle Children's Hospital, 4800 Sandpoint Way Northeast, Seattle, WA 98105, USA; Pediatric Critical Care Medicine, Seattle Children's Hospital, Harborview Medical Center, University of Washington, School of Medicine, FA.2.300B, Seattle Children's Hospital, 4800 Sand Point Way Northeast, Seattle, WA 98105, USA.
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11
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Colin E, Duffourd Y, Chevarin M, Tisserant E, Verdez S, Paccaud J, Bruel AL, Tran Mau-Them F, Denommé-Pichon AS, Thevenon J, Safraou H, Besnard T, Goldenberg A, Cogné B, Isidor B, Delanne J, Sorlin A, Moutton S, Fradin M, Dubourg C, Gorce M, Bonneau D, El Chehadeh S, Debray FG, Doco-Fenzy M, Uguen K, Chatron N, Aral B, Marle N, Kuentz P, Boland A, Olaso R, Deleuze JF, Sanlaville D, Callier P, Philippe C, Thauvin-Robinet C, Faivre L, Vitobello A. Stepwise use of genomics and transcriptomics technologies increases diagnostic yield in Mendelian disorders. Front Cell Dev Biol 2023; 11:1021920. [PMID: 36926521 PMCID: PMC10011630 DOI: 10.3389/fcell.2023.1021920] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Accepted: 01/30/2023] [Indexed: 03/08/2023] Open
Abstract
Purpose: Multi-omics offer worthwhile and increasingly accessible technologies to diagnostic laboratories seeking potential second-tier strategies to help patients with unresolved rare diseases, especially patients clinically diagnosed with a rare OMIM (Online Mendelian Inheritance in Man) disease. However, no consensus exists regarding the optimal diagnostic care pathway to adopt after negative results with standard approaches. Methods: In 15 unsolved individuals clinically diagnosed with recognizable OMIM diseases but with negative or inconclusive first-line genetic results, we explored the utility of a multi-step approach using several novel omics technologies to establish a molecular diagnosis. Inclusion criteria included a clinical autosomal recessive disease diagnosis and single heterozygous pathogenic variant in the gene of interest identified by first-line analysis (60%-9/15) or a clinical diagnosis of an X-linked recessive or autosomal dominant disease with no causative variant identified (40%-6/15). We performed a multi-step analysis involving short-read genome sequencing (srGS) and complementary approaches such as mRNA sequencing (mRNA-seq), long-read genome sequencing (lrG), or optical genome mapping (oGM) selected according to the outcome of the GS analysis. Results: SrGS alone or in combination with additional genomic and/or transcriptomic technologies allowed us to resolve 87% of individuals by identifying single nucleotide variants/indels missed by first-line targeted tests, identifying variants affecting transcription, or structural variants sometimes requiring lrGS or oGM for their characterization. Conclusion: Hypothesis-driven implementation of combined omics technologies is particularly effective in identifying molecular etiologies. In this study, we detail our experience of the implementation of genomics and transcriptomics technologies in a pilot cohort of previously investigated patients with a typical clinical diagnosis without molecular etiology.
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Affiliation(s)
- Estelle Colin
- UFR Des Sciences de Santé, INSERM-Université de Bourgogne UMR1231 GAD "Génétique des Anomalies du Développement", FHUTRANSLAD, Dijon, France.,Service de Génétique Médicale, CHU d'Angers, Angers, France
| | - Yannis Duffourd
- UFR Des Sciences de Santé, INSERM-Université de Bourgogne UMR1231 GAD "Génétique des Anomalies du Développement", FHUTRANSLAD, Dijon, France
| | - Martin Chevarin
- UFR Des Sciences de Santé, INSERM-Université de Bourgogne UMR1231 GAD "Génétique des Anomalies du Développement", FHUTRANSLAD, Dijon, France.,Unité Fonctionnelle Innovation en Diagnostic Génomique des Maladies Rares, FHU-TRANSLAD, CHU Dijon Bourgogne, Dijon, France
| | - Emilie Tisserant
- UFR Des Sciences de Santé, INSERM-Université de Bourgogne UMR1231 GAD "Génétique des Anomalies du Développement", FHUTRANSLAD, Dijon, France
| | - Simon Verdez
- UFR Des Sciences de Santé, INSERM-Université de Bourgogne UMR1231 GAD "Génétique des Anomalies du Développement", FHUTRANSLAD, Dijon, France
| | - Julien Paccaud
- UFR Des Sciences de Santé, INSERM-Université de Bourgogne UMR1231 GAD "Génétique des Anomalies du Développement", FHUTRANSLAD, Dijon, France
| | - Ange-Line Bruel
- UFR Des Sciences de Santé, INSERM-Université de Bourgogne UMR1231 GAD "Génétique des Anomalies du Développement", FHUTRANSLAD, Dijon, France.,Unité Fonctionnelle Innovation en Diagnostic Génomique des Maladies Rares, FHU-TRANSLAD, CHU Dijon Bourgogne, Dijon, France
| | - Frédéric Tran Mau-Them
- UFR Des Sciences de Santé, INSERM-Université de Bourgogne UMR1231 GAD "Génétique des Anomalies du Développement", FHUTRANSLAD, Dijon, France.,Unité Fonctionnelle Innovation en Diagnostic Génomique des Maladies Rares, FHU-TRANSLAD, CHU Dijon Bourgogne, Dijon, France
| | - Anne-Sophie Denommé-Pichon
- UFR Des Sciences de Santé, INSERM-Université de Bourgogne UMR1231 GAD "Génétique des Anomalies du Développement", FHUTRANSLAD, Dijon, France.,Unité Fonctionnelle Innovation en Diagnostic Génomique des Maladies Rares, FHU-TRANSLAD, CHU Dijon Bourgogne, Dijon, France
| | - Julien Thevenon
- UFR Des Sciences de Santé, INSERM-Université de Bourgogne UMR1231 GAD "Génétique des Anomalies du Développement", FHUTRANSLAD, Dijon, France
| | - Hana Safraou
- UFR Des Sciences de Santé, INSERM-Université de Bourgogne UMR1231 GAD "Génétique des Anomalies du Développement", FHUTRANSLAD, Dijon, France.,Unité Fonctionnelle Innovation en Diagnostic Génomique des Maladies Rares, FHU-TRANSLAD, CHU Dijon Bourgogne, Dijon, France
| | - Thomas Besnard
- Service de Génétique Médicale, Nantes Université, CHU Nantes, Nantes, France.,CNRS, INSERM, L'institut du thorax, Nantes Université, CHU Nantes, Nantes, France
| | - Alice Goldenberg
- Department of Genetics and Reference Center for Developmental Disorders, Normandy Center for Genomic and Personalized Medicine, Rouen University Hospital, Rouen, France.,Normandie Univ, UNIROUEN, Inserm U1245, Rouen, France
| | - Benjamin Cogné
- Service de Génétique Médicale, Nantes Université, CHU Nantes, Nantes, France.,CNRS, INSERM, L'institut du thorax, Nantes Université, CHU Nantes, Nantes, France
| | - Bertrand Isidor
- Service de Génétique Médicale, CHU de Nantes, Nantes, France
| | - Julian Delanne
- UFR Des Sciences de Santé, INSERM-Université de Bourgogne UMR1231 GAD "Génétique des Anomalies du Développement", FHUTRANSLAD, Dijon, France.,Centre de Génétique et Centre de référence "Anomalies du Développement et Syndromes Malformatifs", Hôpital d'Enfants, Centre Hospitalier Universitaire de Dijon, Dijon, France
| | - Arthur Sorlin
- UFR Des Sciences de Santé, INSERM-Université de Bourgogne UMR1231 GAD "Génétique des Anomalies du Développement", FHUTRANSLAD, Dijon, France.,Centre de Génétique et Centre de référence "Anomalies du Développement et Syndromes Malformatifs", Hôpital d'Enfants, Centre Hospitalier Universitaire de Dijon, Dijon, France
| | - Sébastien Moutton
- UFR Des Sciences de Santé, INSERM-Université de Bourgogne UMR1231 GAD "Génétique des Anomalies du Développement", FHUTRANSLAD, Dijon, France.,Centre de Génétique et Centre de référence "Anomalies du Développement et Syndromes Malformatifs", Hôpital d'Enfants, Centre Hospitalier Universitaire de Dijon, Dijon, France
| | - Mélanie Fradin
- CHU Rennes, Service de Génétique Clinique, Centre de Référence Maladies Rares, CLAD-Ouest, Rennes, France
| | - Christèle Dubourg
- Service de Génétique Moléculaire et Génomique, CHU Rennes, Rennes, France.,Univ Rennes, CNRS, Institut de Genetique et Developpement de Rennes, UMR 6290, Rennes, France
| | - Magali Gorce
- Service de Génétique Médicale, CHU d'Angers, Angers, France
| | | | - Salima El Chehadeh
- Service de Génétique Médicale, Hôpital de Hautepierre, CHU Strasbourg, Strasbourg, France
| | | | - Martine Doco-Fenzy
- Medical School IFR53, EA3801, Université de Reims Champagne-Ardenne, Reims, France.,Service de Génétique, CHU Reims, Reims, France
| | - Kevin Uguen
- Department of Genetics and Reference Center for Developmental Disorders, Lyon University Hospital, Groupement Hospitalier Est, Hospices Civils de Lyon, Lyon, France.,CHU Brest, Inserm, Univ Brest, EFS, UMR 1078, GGB, Brest, France
| | - Nicolas Chatron
- Department of Genetics and Reference Center for Developmental Disorders, Lyon University Hospital, Groupement Hospitalier Est, Hospices Civils de Lyon, Lyon, France
| | - Bernard Aral
- Laboratoire de Génétique Chromosomique et Moléculaire, Pôle Biologie, CHU de Dijon, Dijon, France
| | - Nathalie Marle
- Laboratoire de Génétique Chromosomique et Moléculaire, Pôle Biologie, CHU de Dijon, Dijon, France
| | - Paul Kuentz
- UFR Des Sciences de Santé, INSERM-Université de Bourgogne UMR1231 GAD "Génétique des Anomalies du Développement", FHUTRANSLAD, Dijon, France.,Oncobiologie Génétique Bioinformatique, PCBio, Centre Hospitalier Universitaire de Besançon, Besançon, France
| | - Anne Boland
- Université Paris-Saclay, CEA, Centre National de Recherche en Génomique Humaine (CNRGH), Evry, France
| | - Robert Olaso
- Université Paris-Saclay, CEA, Centre National de Recherche en Génomique Humaine (CNRGH), Evry, France.,LabEx GENMED (Medical Genomics), Dijon, France
| | - Jean-François Deleuze
- Université Paris-Saclay, CEA, Centre National de Recherche en Génomique Humaine (CNRGH), Evry, France.,LabEx GENMED (Medical Genomics), Dijon, France
| | - Damien Sanlaville
- Department of Genetics and Reference Center for Developmental Disorders, Lyon University Hospital, Groupement Hospitalier Est, Hospices Civils de Lyon, Lyon, France
| | - Patrick Callier
- UFR Des Sciences de Santé, INSERM-Université de Bourgogne UMR1231 GAD "Génétique des Anomalies du Développement", FHUTRANSLAD, Dijon, France.,Laboratoire de Génétique Chromosomique et Moléculaire, Pôle Biologie, CHU de Dijon, Dijon, France
| | - Christophe Philippe
- UFR Des Sciences de Santé, INSERM-Université de Bourgogne UMR1231 GAD "Génétique des Anomalies du Développement", FHUTRANSLAD, Dijon, France.,Unité Fonctionnelle Innovation en Diagnostic Génomique des Maladies Rares, FHU-TRANSLAD, CHU Dijon Bourgogne, Dijon, France
| | - Christel Thauvin-Robinet
- UFR Des Sciences de Santé, INSERM-Université de Bourgogne UMR1231 GAD "Génétique des Anomalies du Développement", FHUTRANSLAD, Dijon, France.,Unité Fonctionnelle Innovation en Diagnostic Génomique des Maladies Rares, FHU-TRANSLAD, CHU Dijon Bourgogne, Dijon, France.,Centre de Référence Maladies Rares "Déficiences Intellectuelles de Causes Rares", Centre de Génétique, FHU-TRANSLAD, CHU Dijon Bourgogne, Dijon, France
| | - Laurence Faivre
- UFR Des Sciences de Santé, INSERM-Université de Bourgogne UMR1231 GAD "Génétique des Anomalies du Développement", FHUTRANSLAD, Dijon, France.,Centre de Génétique et Centre de référence "Anomalies du Développement et Syndromes Malformatifs", Hôpital d'Enfants, Centre Hospitalier Universitaire de Dijon, Dijon, France
| | - Antonio Vitobello
- UFR Des Sciences de Santé, INSERM-Université de Bourgogne UMR1231 GAD "Génétique des Anomalies du Développement", FHUTRANSLAD, Dijon, France.,Unité Fonctionnelle Innovation en Diagnostic Génomique des Maladies Rares, FHU-TRANSLAD, CHU Dijon Bourgogne, Dijon, France
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12
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Ewans LJ, Minoche AE, Schofield D, Shrestha R, Puttick C, Zhu Y, Drew A, Gayevskiy V, Elakis G, Walsh C, Adès LC, Colley A, Ellaway C, Evans CA, Freckmann ML, Goodwin L, Hackett A, Kamien B, Kirk EP, Lipke M, Mowat D, Palmer E, Rajagopalan S, Ronan A, Sachdev R, Stevenson W, Turner A, Wilson M, Worgan L, Morel-Kopp MC, Field M, Buckley MF, Cowley MJ, Dinger ME, Roscioli T. Whole exome and genome sequencing in mendelian disorders: a diagnostic and health economic analysis. Eur J Hum Genet 2022; 30:1121-31. [PMID: 35970915 DOI: 10.1038/s41431-022-01162-2] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2021] [Revised: 06/01/2022] [Accepted: 07/20/2022] [Indexed: 12/15/2022] Open
Abstract
Whole genome sequencing (WGS) improves Mendelian disorder diagnosis over whole exome sequencing (WES); however, additional diagnostic yields and costs remain undefined. We investigated differences between diagnostic and cost outcomes of WGS and WES in a cohort with suspected Mendelian disorders. WGS was performed in 38 WES-negative families derived from a 64 family Mendelian cohort that previously underwent WES. For new WGS diagnoses, contemporary WES reanalysis determined whether variants were diagnosable by original WES or unique to WGS. Diagnostic rates were estimated for WES and WGS to simulate outcomes if both had been applied to the 64 families. Diagnostic costs were calculated for various genomic testing scenarios. WGS diagnosed 34% (13/38) of WES-negative families. However, contemporary WES reanalysis on average 2 years later would have diagnosed 18% (7/38 families) resulting in a WGS-specific diagnostic yield of 19% (6/31 remaining families). In WES-negative families, the incremental cost per additional diagnosis using WGS following WES reanalysis was AU$36,710 (£19,407;US$23,727) and WGS alone was AU$41,916 (£22,159;US$27,093) compared to WES-reanalysis. When we simulated the use of WGS alone as an initial genomic test, the incremental cost for each additional diagnosis was AU$29,708 (£15,705;US$19,201) whereas contemporary WES followed by WGS was AU$36,710 (£19,407;US$23,727) compared to contemporary WES. Our findings confirm that WGS is the optimal genomic test choice for maximal diagnosis in Mendelian disorders. However, accepting a small reduction in diagnostic yield, WES with subsequent reanalysis confers the lowest costs. Whether WES or WGS is utilised will depend on clinical scenario and local resourcing and availability.
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13
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Nurchis MC, Riccardi MT, Damiani G. Health technology assessment of whole genome sequencing in the diagnosis of genetic disorders: a scoping review of the literature. Int J Technol Assess Health Care 2022; 38:e71. [PMID: 36016516 DOI: 10.1017/S0266462322000496] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
OBJECTIVE The aim of this scoping review is to map the available evidence about the use of health technology assessment (HTA) in the assessment of whole genome sequencing (WGS). METHODS A scoping review methodology was adopted. The population, concept, and context framework was used to build up the research question and to establish the eligibility criteria. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews was adopted to implement a comprehensive search strategy. Evidence was retrieved from scientific databases and HTA organizations Web sites. Reports were classified as full HTA, mini-HTA, rapid reviews or other. RESULTS The search strategy identified seven reports. Five HTA organizations from five countries elaborated the reports: one full HTA, four rapid reviews, and two classified as others. The reports were mainly focused on the evaluation of the clinical utility and cost-effectiveness of genome-wide sequencing as well as informing policy questions by providing analyses of organizational and ethical considerations. CONCLUSIONS Few HTA organizations are drafting reports for WGS. It is essential to stimulate a critical reflection during the elaboration of HTA reports for WGS to steer choices of decision makers in the establishment of priorities for research and policy and reimbursement rates.
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14
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May V, Koch L, Fischer-Zirnsak B, Horn D, Gehle P, Kornak U, Beule D, Holtgrewe M. ClearCNV: CNV calling from NGS panel data in the presence of ambiguity and noise. Bioinformatics 2022; 38:3871-3876. [PMID: 35751599 DOI: 10.1093/bioinformatics/btac418] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2021] [Revised: 04/27/2022] [Accepted: 06/23/2022] [Indexed: 12/24/2022] Open
Abstract
MOTIVATION While the identification of small variants in panel sequencing data can be considered a solved problem, the identification of larger, multi-exon copy number variants (CNVs) still poses a considerable challenge. Thus, CNV calling has not been established in all laboratories performing panel sequencing. At the same time, such laboratories have accumulated large datasets and thus have the need to identify CNVs on their data to close the diagnostic gap. RESULTS In this article, we present our method clearCNV that addresses this need in two ways. First, it helps laboratories to properly assign datasets to enrichment kits. Based on homogeneous subsets of data, clearCNV identifies CNVs affecting the targeted regions. Using real-world datasets and validation, we show that our method is highly competitive with previous methods and preferable in terms of specificity. AVAILABILITY AND IMPLEMENTATION The software is available for free under a permissible license at https://github.com/bihealth/clear-cnv. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Vinzenz May
- Core Unit Bioinformatics (CUBI), Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin 10117, Germany
| | - Leonard Koch
- Institute of Medical Genetics and Human Genetics, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin 13353, Germany
| | - Björn Fischer-Zirnsak
- Institute of Medical Genetics and Human Genetics, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin 13353, Germany.,FG Development and Disease, Max-Planck-Institut für Molekulare Genetik, Berlin 14195, Germany
| | - Denise Horn
- Institute of Medical Genetics and Human Genetics, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin 13353, Germany
| | - Petra Gehle
- Department of Internal Medicine-Cardiology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin 13353, Germany.,DZHK (German Center for Cardiovascular Research), Berlin, Germany
| | - Uwe Kornak
- FG Development and Disease, Max-Planck-Institut für Molekulare Genetik, Berlin 14195, Germany.,Institute of Human Genetics, University Medical Center Göttingen, Göttingen 37073, Germany
| | - Dieter Beule
- Core Unit Bioinformatics (CUBI), Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin 10117, Germany
| | - Manuel Holtgrewe
- Core Unit Bioinformatics (CUBI), Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin 10117, Germany
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15
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Brown D, Alcala H, Oelschlaeger P, Andresen BT. Polymorphisms in common antihypertensive targets: Pharmacogenomic implications for the treatment of cardiovascular disease. Adv Pharmacol 2022; 94:141-82. [PMID: 35659371 DOI: 10.1016/bs.apha.2022.04.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
The idea of personalized medicine came to fruition with sequencing the human genome; however, aside from a few cases, the genetic revolution has yet to materialize. Cardiovascular diseases are the leading cause of death globally, and hypertension is a common prelude to nearly all cardiovascular diseases. Thus, hypertension is an ideal candidate disease to apply tenants of personalized medicine to lessen cardiovascular disease. Herein is a survey that visually depicts the polymorphisms in the top eight antihypertensive targets. Although there are numerous genome-wide association studies regarding cardiovascular disease, few studies look at the effects of receptor polymorphisms on drug treatment. With 17,000+ polymorphisms in the combined target proteins examined, it is expected that some of the clinical variability in the treatment of hypertension is due to polymorphisms in the drug targets. Recent advances in techniques and technology, such as high throughput examination of single mutations, structure prediction, computational power for modeling, and CRISPR models of point mutations, allow for a relatively rapid and comprehensive examination of the effects of known and future polymorphisms on drug affinity and effects. As hypertension is easy to measure and has a plethora of clinically viable ligands, hypertension makes an excellent disease to study pharmacogenomics in the lab and the clinic. If the promises of personalized medicine are to materialize, a concerted effort to examine the effects polymorphisms have on drugs is required. A clinician with the knowledge of a patient's genotype can then prescribe drugs that are optimal for treating that specific patient.
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16
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Duan J, Ye Y, Cao D, Zou D, Lu X, Chen L, Wen J, Zou H, Gao J, Li B, Hu Z, Liao J. Clinical and genetic spectrum of 355 Chinese children with epilepsy: a trio-sequencing-based study. Brain 2022; 145:e43-e46. [PMID: 35231114 PMCID: PMC9166538 DOI: 10.1093/brain/awac053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Accepted: 01/23/2022] [Indexed: 02/05/2023] Open
Affiliation(s)
- Jing Duan
- Department of Neurology, Shenzhen Children’s Hospital, Shenzhen, China
| | - Yuanzhen Ye
- Department of Neurology, Shenzhen Children’s Hospital, Shenzhen, China
| | - Dezhi Cao
- Department of Neurology, Shenzhen Children’s Hospital, Shenzhen, China
| | - Dongfang Zou
- Department of Neurology, Shenzhen Children’s Hospital, Shenzhen, China
| | - Xinguo Lu
- Department of Neurology, Shenzhen Children’s Hospital, Shenzhen, China
| | - Li Chen
- Department of Neurology, Shenzhen Children’s Hospital, Shenzhen, China
| | - Jialun Wen
- Department of Neurology, Shenzhen Children’s Hospital, Shenzhen, China
| | - Huafang Zou
- Department of Neurology, Shenzhen Children’s Hospital, Shenzhen, China
| | - Jian Gao
- Aegicare (Shenzhen) Technology Co., Ltd., Shenzhen 518060, China
| | - Bingying Li
- Aegicare (Shenzhen) Technology Co., Ltd., Shenzhen 518060, China
| | - Zhanqi Hu
- Department of Neurology, Shenzhen Children’s Hospital, Shenzhen, China
- Correspondence may also be addressed to: Dr Zhanqi Hu Department of Neurology, Shenzhen Children’s Hospital 7019 Yitian Road, Futian District, Shenzhen Guangdong Province 518038, China E-mail:
| | - Jianxiang Liao
- Department of Neurology, Shenzhen Children’s Hospital, Shenzhen, China
- Correspondence to: Professor Jianxiang Liao Department of Neurology, Shenzhen Children’s Hospital 7019 Yitian Road, Futian District, Shenzhen Guangdong Province 518038, China E-mail:
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17
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Berger K, Arafat D, Chandrakasan S, Snapper SB, Gibson G. Targeted RNAseq Improves Clinical Diagnosis of Very Early-Onset Pediatric Immune Dysregulation. J Pers Med 2022; 12:919. [PMID: 35743704 PMCID: PMC9224647 DOI: 10.3390/jpm12060919] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2022] [Revised: 05/26/2022] [Accepted: 05/27/2022] [Indexed: 02/05/2023] Open
Abstract
Despite increased use of whole exome sequencing (WES) for the clinical analysis of rare disease, overall diagnostic yield for most disorders hovers around 30%. Previous studies of mRNA have succeeded in increasing diagnoses for clearly defined disorders of monogenic inheritance. We asked if targeted RNA sequencing could provide similar benefits for primary immunodeficiencies (PIDs) and very early-onset inflammatory bowel disease (VEOIBD), both of which are difficult to diagnose due to high heterogeneity and variable severity. We performed targeted RNA sequencing of a panel of 260 immune-related genes for a cohort of 13 patients (seven suspected PID cases and six VEOIBD) and analyzed variants, splicing, and exon usage. Exonic variants were identified in seven cases, some of which had been previously prioritized by exome sequencing. For four cases, allele specific expression or lack thereof provided additional insights into possible disease mechanisms. In addition, we identified five instances of aberrant splicing associated with four variants. Three of these variants had been previously classified as benign in ClinVar based on population frequency. Digenic or oligogenic inheritance is suggested for at least two patients. In addition to validating the use of targeted RNA sequencing, our results show that rare disease research will benefit from incorporating contributing genetic factors into the diagnostic approach.
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18
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Austin-Tse CA, Jobanputra V, Perry DL, Bick D, Taft RJ, Venner E, Gibbs RA, Young T, Barnett S, Belmont JW, Boczek N, Chowdhury S, Ellsworth KA, Guha S, Kulkarni S, Marcou C, Meng L, Murdock DR, Rehman AU, Spiteri E, Thomas-Wilson A, Kearney HM, Rehm HL. Best practices for the interpretation and reporting of clinical whole genome sequencing. NPJ Genom Med 2022; 7:27. [PMID: 35395838 PMCID: PMC8993917 DOI: 10.1038/s41525-022-00295-z] [Citation(s) in RCA: 39] [Impact Index Per Article: 19.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2021] [Accepted: 02/17/2022] [Indexed: 01/19/2023] Open
Abstract
Whole genome sequencing (WGS) shows promise as a first-tier diagnostic test for patients with rare genetic disorders. However, standards addressing the definition and deployment practice of a best-in-class test are lacking. To address these gaps, the Medical Genome Initiative, a consortium of leading health care and research organizations in the US and Canada, was formed to expand access to high quality clinical WGS by convening experts and publishing best practices. Here, we present best practice recommendations for the interpretation and reporting of clinical diagnostic WGS, including discussion of challenges and emerging approaches that will be critical to harness the full potential of this comprehensive test.
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Affiliation(s)
- Christina A Austin-Tse
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA. .,Laboratory for Molecular Medicine, Mass General Brigham Personalized Medicine, Cambridge, MA, USA. .,Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| | - Vaidehi Jobanputra
- Molecular Diagnostics Laboratory, New York Genome Center, New York, NY, USA.,Department of Pathology and Cell Biology, Columbia University Irving Medical Center, New York, NY, USA
| | | | - David Bick
- HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA
| | | | - Eric Venner
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Richard A Gibbs
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Ted Young
- Genome Diagnostics, Department of Paediatric Laboratory Medicine, The Hospital for Sick Children, Toronto, ON, Canada
| | - Sarah Barnett
- Division of Laboratory Genetics and Genomics, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | | | - Nicole Boczek
- Division of Laboratory Genetics and Genomics, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA.,Center for Individualized Medicine, College of Medicine, Mayo Clinic, Rochester, MN, USA
| | - Shimul Chowdhury
- Rady Children's Institute for Genomic Medicine, San Diego, CA, USA
| | | | - Saurav Guha
- Molecular Diagnostics Laboratory, New York Genome Center, New York, NY, USA
| | - Shashikant Kulkarni
- Baylor Genetics and Baylor College of Medicine, Houston, TX, USA.,Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Cherisse Marcou
- Division of Laboratory Genetics and Genomics, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - Linyan Meng
- Baylor Genetics and Baylor College of Medicine, Houston, TX, USA.,Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - David R Murdock
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA.,Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Atteeq U Rehman
- Molecular Diagnostics Laboratory, New York Genome Center, New York, NY, USA
| | - Elizabeth Spiteri
- Department of Pathology, Stanford Medicine, Stanford University, Stanford, CA, USA
| | | | - Hutton M Kearney
- Division of Laboratory Genetics and Genomics, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - Heidi L Rehm
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.,Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
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19
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González-Del Pozo M, Fernández-Suárez E, Bravo-Gil N, Méndez-Vidal C, Martín-Sánchez M, Rodríguez-de la Rúa E, Ramos-Jiménez M, Morillo-Sánchez MJ, Borrego S, Antiñolo G. A comprehensive WGS-based pipeline for the identification of new candidate genes in inherited retinal dystrophies. NPJ Genom Med 2022; 7:17. [PMID: 35246562 DOI: 10.1038/s41525-022-00286-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2021] [Accepted: 02/04/2022] [Indexed: 12/11/2022] Open
Abstract
To enhance the use of Whole Genome Sequencing (WGS) in clinical practice, it is still necessary to standardize data analysis pipelines. Herein, we aimed to define a WGS-based algorithm for the accurate interpretation of variants in inherited retinal dystrophies (IRD). This study comprised 429 phenotyped individuals divided into three cohorts. A comparison of 14 pathogenicity predictors, and the re-definition of its cutoffs, were performed using panel-sequencing curated data from 209 genetically diagnosed individuals with IRD (training cohort). The optimal tool combinations, previously validated in 50 additional IRD individuals, were also tested in patients with hereditary cancer (n = 109), and with neurological diseases (n = 47) to evaluate the translational value of this approach (validation cohort). Then, our workflow was applied for the WGS-data analysis of 14 individuals from genetically undiagnosed IRD families (discovery cohort). The statistical analysis showed that the optimal filtering combination included CADDv1.6, MAPP, Grantham, and SIFT tools. Our pipeline allowed the identification of one homozygous variant in the candidate gene CFAP20 (c.337 C > T; p.Arg113Trp), a conserved ciliary gene, which was abundantly expressed in human retina and was located in the photoreceptors layer. Although further studies are needed, we propose CFAP20 as a candidate gene for autosomal recessive retinitis pigmentosa. Moreover, we offer a translational strategy for accurate WGS-data prioritization, which is essential for the advancement of personalized medicine.
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20
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Nurchis MC, Riccardi MT, Radio FC, Chillemi G, Bertini ES, Tartaglia M, Cicchetti A, Dallapiccola B, Damiani G. Incremental net benefit of Whole Genome Sequencing for newborns and children with suspected genetic disorders: systematic review and meta-analysis of cost-effectiveness evidence. Health Policy 2022; 126:337-345. [DOI: 10.1016/j.healthpol.2022.03.001] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Revised: 02/16/2022] [Accepted: 03/01/2022] [Indexed: 11/16/2022]
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21
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Rapti M, Zouaghi Y, Meylan J, Ranza E, Antonarakis SE, Santoni FA. CoverageMaster: comprehensive CNV detection and visualization from NGS short reads for genetic medicine applications. Brief Bioinform 2022; 23:6537346. [PMID: 35224620 PMCID: PMC8921749 DOI: 10.1093/bib/bbac049] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2021] [Revised: 01/28/2022] [Accepted: 01/31/2022] [Indexed: 12/27/2022] Open
Abstract
CoverageMaster (CoM) is a copy number variation (CNV) calling algorithm based on depth-of-coverage maps designed to detect CNVs of any size in exome [whole exome sequencing (WES)] and genome [whole genome sequencing (WGS)] data. The core of the algorithm is the compression of sequencing coverage data in a multiscale Wavelet space and the analysis through an iterative Hidden Markov Model. CoM processes WES and WGS data at nucleotide scale resolution and accurately detects and visualizes full size range CNVs, including single or partial exon deletions and duplications. The results obtained with this approach support the possibility for coverage-based CNV callers to replace probe-based methods such as array comparative genomic hybridization and multiplex ligation-dependent probe amplification in the near future.
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Affiliation(s)
- Melivoia Rapti
- Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland.,Univesity of Lausanne, Lausanne, Switzerland
| | - Yassine Zouaghi
- Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland.,Univesity of Lausanne, Lausanne, Switzerland
| | - Jenny Meylan
- Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland
| | - Emmanuelle Ranza
- Medigenome, Swiss Institute of Genomic Medicine, Geneva, Switzerland
| | - Stylianos E Antonarakis
- Medigenome, Swiss Institute of Genomic Medicine, Geneva, Switzerland.,University of Geneva Medical Faculty, Geneva, Switzerland
| | - Federico A Santoni
- Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland.,Medigenome, Swiss Institute of Genomic Medicine, Geneva, Switzerland.,Univesity of Lausanne, Lausanne, Switzerland
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22
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Wu S, Yuan Z, Sun Z, Zhu T, Wei X, Zou X, Sui R. A novel tandem duplication of PRDM13 in a Chinese family with North Carolina macular dystrophy. Graefes Arch Clin Exp Ophthalmol 2022; 260:645-653. [PMID: 34427740 DOI: 10.1007/s00417-021-05376-w] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2021] [Revised: 07/29/2021] [Accepted: 08/10/2021] [Indexed: 10/20/2022] Open
Abstract
PURPOSES North Carolina macular dystrophy (NCMD) is a rare autosomal dominant inherited disorder characterized by macular impairment with a variety of phenotypic manifestations. The aims of this study were to assess the clinical features of a Chinese family with NCMD and to identify the underlying genetic cause of the disease. METHODS Three patients from a Chinese family were included in this study. Detailed ophthalmological examinations were performed, including best corrected visual acuity (BCVA), slit lamp, dilated indirect ophthalmoscopy, fundus photography, optical coherence tomography (OCT), fundus autofluorescence, full-field electroretinography (ERG), and electrooculography (EOG). Genomic DNA was extracted from peripheral blood samples. Whole-genome sequencing and long-read genome sequencing were applied to detect the pathogenic variants. Sanger sequencing was performed to confirm the breakpoints. RESULTS All three patients had macular involvement ranging from patchy yellowish-white lesions to big-area thinning, which are typical for NCMD. The BCVA ranged from 20/50 to 20/20. OCT revealed varying degrees of macular structure disorganization. The ERG responses were normal, and the Arden ration of the EOG was reduced. A novel 134.6 kb (g.99932464-100067110dup) tandem duplication on chromosome 6 (NC_000006.11) encompassing the entire CCNC and PRDM13 genes and a DNase 1 hypersensitivity site in the MCDR1 locus was identified. CONCLUSION A novel large tandem duplication in MCDR1 locus was confirmed in a Chinese family with NCMD with a variety of macular phenotypes.
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Affiliation(s)
- Shijing Wu
- Department of Ophthalmology, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China
| | - Zhisheng Yuan
- Department of Ophthalmology, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China
| | - Zixi Sun
- Department of Ophthalmology, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China
| | - Tian Zhu
- Department of Ophthalmology, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China
| | - Xing Wei
- Department of Ophthalmology, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China
| | - Xuan Zou
- Department of Ophthalmology, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China
| | - Ruifang Sui
- Department of Ophthalmology, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100730, China.
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23
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Barmada A, Ramaswamy A, Lucas CL. Maximizing insights from monogenic immune disorders. Curr Opin Immunol 2021; 73:50-57. [PMID: 34695727 DOI: 10.1016/j.coi.2021.09.008] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2021] [Revised: 09/24/2021] [Accepted: 09/28/2021] [Indexed: 11/29/2022]
Abstract
Monogenic immune disorders provide unprecedented insights into the consequences of disrupting single genes in humans, thereby informing our understanding of fundamental immune function and disease. Genomics has accelerated monogenic disease discovery while also revealing the complexity of human disease, where several factors beyond the genome can govern pathogenesis. At this juncture, the optimal path forward will focus on maximizing basic and translational immunology insights from these disorders. This pursuit will be most direct and impactful if human disease gene discovery is paired with mechanistic studies employing integrative omics and mouse modeling to leverage their unique strengths.
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Affiliation(s)
- Anis Barmada
- Yale University School of Medicine, Department of Immunobiology, New Haven, CT, USA
| | - Anjali Ramaswamy
- Yale University School of Medicine, Department of Immunobiology, New Haven, CT, USA
| | - Carrie L Lucas
- Yale University School of Medicine, Department of Immunobiology, New Haven, CT, USA.
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24
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25
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Nisar H, Wajid B, Shahid S, Anwar F, Wajid I, Khatoon A, Sattar MU, Sadaf S. Whole-genome sequencing as a first-tier diagnostic framework for rare genetic diseases. Exp Biol Med (Maywood) 2021; 246:2610-2617. [PMID: 34521224 DOI: 10.1177/15353702211040046] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
Rare diseases affect nearly 300 million people globally with most patients aged five or less. Traditional diagnostic approaches have provided much of the diagnosis; however, there are limitations. For instance, simply inadequate and untimely diagnosis adversely affects both the patient and their families. This review advocates the use of whole genome sequencing in clinical settings for diagnosis of rare genetic diseases by showcasing five case studies. These examples specifically describe the utilization of whole genome sequencing, which helped in providing relief to patients via correct diagnosis followed by use of precision medicine.
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Affiliation(s)
- Haseeb Nisar
- Office of Research, Innovation and Commercialization, University of Management and Technology, Lahore 54000, Pakistan.,School of Biochemistry & Biotechnology, University of the Punjab, Lahore 54000, Pakistan
| | - Bilal Wajid
- Department of Electrical Engineering, University of Engineering and Technology, Lahore 54000, Pakistan.,Ibn Sina Research & Development Division, Sabz-Qalam, Lahore 54000, Pakistan.,Department of Computer Sciences, University of Management and Technology, Lahore 54000, Pakistan
| | - Samiah Shahid
- Institute of Molecular Biology and Biotechnology, The University of Lahore, Lahore 54000, Pakistan
| | - Faria Anwar
- Out Patient Department, Mayo Hospital, Lahore 54000, Pakistan
| | - Imran Wajid
- Ibn Sina Research & Development Division, Sabz-Qalam, Lahore 54000, Pakistan
| | - Asia Khatoon
- School of Biochemistry & Biotechnology, University of the Punjab, Lahore 54000, Pakistan
| | - Mian Usman Sattar
- Institute of Social Sciences, Istanbul Commerce University, Istanbul, Turkey
| | - Saima Sadaf
- School of Biochemistry & Biotechnology, University of the Punjab, Lahore 54000, Pakistan
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26
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Umlai UKI, Bangarusamy DK, Estivill X, Jithesh PV. Genome sequencing data analysis for rare disease gene discovery. Brief Bioinform 2021; 23:6366880. [PMID: 34498682 DOI: 10.1093/bib/bbab363] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Revised: 07/24/2021] [Accepted: 08/17/2021] [Indexed: 12/14/2022] Open
Abstract
Rare diseases occur in a smaller proportion of the general population, which is variedly defined as less than 200 000 individuals (US) or in less than 1 in 2000 individuals (Europe). Although rare, they collectively make up to approximately 7000 different disorders, with majority having a genetic origin, and affect roughly 300 million people globally. Most of the patients and their families undergo a long and frustrating diagnostic odyssey. However, advances in the field of genomics have started to facilitate the process of diagnosis, though it is hindered by the difficulty in genome data analysis and interpretation. A major impediment in diagnosis is in the understanding of the diverse approaches, tools and datasets available for variant prioritization, the most important step in the analysis of millions of variants to select a few potential variants. Here we present a review of the latest methodological developments and spectrum of tools available for rare disease genetic variant discovery and recommend appropriate data interpretation methods for variant prioritization. We have categorized the resources based on various steps of the variant interpretation workflow, starting from data processing, variant calling, annotation, filtration and finally prioritization, with a special emphasis on the last two steps. The methods discussed here pertain to elucidating the genetic basis of disease in individual patient cases via trio- or family-based analysis of the genome data. We advocate the use of a combination of tools and datasets and to follow multiple iterative approaches to elucidate the potential causative variant.
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Affiliation(s)
- Umm-Kulthum Ismail Umlai
- Division of Genomics & Translational Biomedicine, College of Health & Life Sciences, Hamad Bin Khalifa University, B-147, Penrose House, PO Box 34110, Education City, Doha, Qatar
| | - Dhinoth Kumar Bangarusamy
- Division of Genomics & Translational Biomedicine, College of Health & Life Sciences, Hamad Bin Khalifa University, B-147, Penrose House, PO Box 34110, Education City, Doha, Qatar
| | - Xavier Estivill
- Quantitative Genomics Laboratories (qGenomics), Barcelona, Catalonia, Spain
| | - Puthen Veettil Jithesh
- Division of Genomics & Translational Biomedicine, College of Health & Life Sciences, Hamad Bin Khalifa University, B-147, Penrose House, PO Box 34110, Education City, Doha, Qatar
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27
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Abstract
Next-generation sequencing (NGS) has increased our understanding of the molecular basis of many primary mitochondrial diseases (PMDs). Despite this progress, many patients with suspected PMD remain without a genetic diagnosis, which restricts their access to in-depth genetic counselling, reproductive options and clinical trials, in addition to hampering efforts to understand the underlying disease mechanisms. Although they represent a considerable improvement over their predecessors, current methods for sequencing the mitochondrial and nuclear genomes have important limitations, and molecular diagnostic techniques are often manual and time consuming. However, recent advances in genomics and transcriptomics offer realistic solutions to these challenges. In this Review, we discuss the current genetic testing approach for PMDs and the opportunities that exist for increased use of whole-genome NGS of nuclear and mitochondrial DNA (mtDNA) in the clinical environment. We consider the possible role for long-read approaches in sequencing of mtDNA and in the identification of novel nuclear genomic causes of PMDs. We examine the expanding applications of RNA sequencing, including the detection of cryptic variants that affect splicing and gene expression and the interpretation of rare and novel mitochondrial transfer RNA variants.
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Affiliation(s)
- William L Macken
- Department of Neuromuscular Diseases, UCL Queen Square Institute of Neurology and The National Hospital for Neurology and Neurosurgery, London, UK
| | - Jana Vandrovcova
- Department of Neuromuscular Diseases, UCL Queen Square Institute of Neurology and The National Hospital for Neurology and Neurosurgery, London, UK
| | - Michael G Hanna
- Department of Neuromuscular Diseases, UCL Queen Square Institute of Neurology and The National Hospital for Neurology and Neurosurgery, London, UK
| | - Robert D S Pitceathly
- Department of Neuromuscular Diseases, UCL Queen Square Institute of Neurology and The National Hospital for Neurology and Neurosurgery, London, UK.
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28
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Abstract
The development of massively parallel sequencing-based genomic sequencing tests has increased genetic test availability and access. The field and practice of genetic counseling have adapted in response to this paradigm-shifting technology and the subsequent transition to practicing genomic medicine. While the key elements defining genetic counseling remain relevant, genetic counseling service delivery models and practice settings have evolved. Genetic counselors are addressing the challenges of direct-to-consumer and consumer-driven genetic testing, and genetic counseling training programs are responding to the ongoing increased demand for genetic counseling services across a broadening range of contexts. The need to diversify both the patient and participant groups with access to genetic information, as well as the field of genetic counseling, is at the forefront of research and training program initiatives. Genetic counselors are key stakeholders in the genomics era, and their contributions are essential to effectively and equitably deliver precision medicine.
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Affiliation(s)
- Laura M Amendola
- Department of Medicine, Division of Medical Genetics, University of Washington Medical Center, Seattle, Washington 98195, USA; ,
| | - Katie Golden-Grant
- Department of Medicine, Division of Medical Genetics, University of Washington Medical Center, Seattle, Washington 98195, USA; ,
| | - Sarah Scollon
- Department of Pediatrics, Baylor College of Medicine, Houston, Texas 77030, USA;
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29
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Abstract
Next-generation sequencing (NGS) technologies have changed the process of genetic diagnosis from a gene-by-gene approach to syndrome-based diagnostic gene panel sequencing (DPS), diagnostic exome sequencing (DES), and diagnostic genome sequencing (DGS). A priori information on the causative genes that might underlie a genetic condition is a prerequisite for genetic diagnosis before conducting clinical NGS tests. Theoretically, DPS, DES, and DGS do not require any information on specific candidate genes. Therefore, clinical NGS tests sometimes detect disease-related pathogenic variants in genes underlying different conditions from the initial diagnosis. These clinical NGS tests are expensive, but they can be a cost-effective approach for the rapid diagnosis of rare disorders with genetic heterogeneity, such as the glycogen storage disease, familial intrahepatic cholestasis, lysosomal storage disease, and primary immunodeficiency. In addition, DES or DGS may find novel genes that that were previously not linked to human diseases.
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30
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Haghshenas S, Bhai P, Aref-Eshghi E, Sadikovic B. Diagnostic Utility of Genome-Wide DNA Methylation Analysis in Mendelian Neurodevelopmental Disorders. Int J Mol Sci 2020; 21:ijms21239303. [PMID: 33291301 PMCID: PMC7730976 DOI: 10.3390/ijms21239303] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2020] [Revised: 12/03/2020] [Accepted: 12/04/2020] [Indexed: 12/14/2022] Open
Abstract
Mendelian neurodevelopmental disorders customarily present with complex and overlapping symptoms, complicating the clinical diagnosis. Individuals with a growing number of the so-called rare disorders exhibit unique, disorder-specific DNA methylation patterns, consequent to the underlying gene defects. Besides providing insights to the pathophysiology and molecular biology of these disorders, we can use these epigenetic patterns as functional biomarkers for the screening and diagnosis of these conditions. This review summarizes our current understanding of DNA methylation episignatures in rare disorders and describes the underlying technology and analytical approaches. We discuss the computational parameters, including statistical and machine learning methods, used for the screening and classification of genetic variants of uncertain clinical significance. Describing the rationale and principles applied to the specific computational models that are used to develop and adapt the DNA methylation episignatures for the diagnosis of rare disorders, we highlight the opportunities and challenges in this emerging branch of diagnostic medicine.
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Affiliation(s)
- Sadegheh Haghshenas
- Department of Pathology and Laboratory Medicine, Western University, London, ON N6A 3K7, Canada;
- Molecular Genetics Laboratory, Molecular Diagnostics Division, London Health Sciences Centre, London, ON N6A 5W9, Canada;
| | - Pratibha Bhai
- Molecular Genetics Laboratory, Molecular Diagnostics Division, London Health Sciences Centre, London, ON N6A 5W9, Canada;
| | - Erfan Aref-Eshghi
- Division of Genomic Diagnostics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA;
| | - Bekim Sadikovic
- Department of Pathology and Laboratory Medicine, Western University, London, ON N6A 3K7, Canada;
- Molecular Genetics Laboratory, Molecular Diagnostics Division, London Health Sciences Centre, London, ON N6A 5W9, Canada;
- Schulich School of Medicine and Dentistry, Western University, London, ON N6A 5C1, Canada
- Correspondence:
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31
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Marshall CR, Chowdhury S, Taft RJ, Lebo MS, Buchan JG, Harrison SM, Rowsey R, Klee EW, Liu P, Worthey EA, Jobanputra V, Dimmock D, Kearney HM, Bick D, Kulkarni S, Taylor SL, Belmont JW, Stavropoulos DJ, Lennon NJ. Best practices for the analytical validation of clinical whole-genome sequencing intended for the diagnosis of germline disease. NPJ Genom Med 2020; 5:47. [PMID: 33110627 PMCID: PMC7585436 DOI: 10.1038/s41525-020-00154-9] [Citation(s) in RCA: 55] [Impact Index Per Article: 13.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2020] [Accepted: 09/25/2020] [Indexed: 12/16/2022] Open
Abstract
Whole-genome sequencing (WGS) has shown promise in becoming a first-tier diagnostic test for patients with rare genetic disorders; however, standards addressing the definition and deployment practice of a best-in-class test are lacking. To address these gaps, the Medical Genome Initiative, a consortium of leading healthcare and research organizations in the US and Canada, was formed to expand access to high-quality clinical WGS by publishing best practices. Here, we present consensus recommendations on clinical WGS analytical validation for the diagnosis of individuals with suspected germline disease with a focus on test development, upfront considerations for test design, test validation practices, and metrics to monitor test performance. This work also provides insight into the current state of WGS testing at each member institution, including the utilization of reference and other standards across sites. Importantly, members of this initiative strongly believe that clinical WGS is an appropriate first-tier test for patients with rare genetic disorders, and at minimum is ready to replace chromosomal microarray analysis and whole-exome sequencing. The recommendations presented here should reduce the burden on laboratories introducing WGS into clinical practice, and support safe and effective WGS testing for diagnosis of germline disease.
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Affiliation(s)
- Christian R Marshall
- Department of Paediatric Laboratory Medicine, Genome Diagnostics, The Hospital for Sick Children, Toronto, ON Canada
| | - Shimul Chowdhury
- Rady Children's Institute for Genomic Medicine, San Diego, CA USA
| | | | - Mathew S Lebo
- Laboratory for Molecular Medicine, Partners HealthCare Personalized Medicine, Cambridge, MA USA.,Broad Institute of MIT and Harvard, Cambridge, MA USA
| | - Jillian G Buchan
- Stanford Medicine Clinical Genomics Program, Stanford Health Care, Stanford, CA USA.,Present Address: Department of Laboratory Medicine, University of Washington, Seattle, WA USA
| | - Steven M Harrison
- Laboratory for Molecular Medicine, Partners HealthCare Personalized Medicine, Cambridge, MA USA.,Broad Institute of MIT and Harvard, Cambridge, MA USA
| | - Ross Rowsey
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN USA
| | - Eric W Klee
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN USA.,Department of Health Sciences Research, Mayo Clinic, Rochester, MN USA
| | - Pengfei Liu
- Baylor Genetics and Baylor College of Medicine, Houston, TX USA
| | - Elizabeth A Worthey
- HudsonAlpha Institute for Biotechnology, Huntsville, AL USA.,Present Address: Center for Genomic Data Sciences, University of Alabama at Birmingham, Birmingham, AL USA
| | - Vaidehi Jobanputra
- Molecular Diagnostics, New York Genome Center, New York, NY USA.,Department of Pathology and Cell Biology, Columbia University Irving Medical Center (CUIMC), New York, NY USA
| | - David Dimmock
- Rady Children's Institute for Genomic Medicine, San Diego, CA USA
| | - Hutton M Kearney
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN USA
| | - David Bick
- HudsonAlpha Institute for Biotechnology, Huntsville, AL USA
| | - Shashikant Kulkarni
- Baylor Genetics and Baylor College of Medicine, Houston, TX USA.,Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX USA
| | | | | | - Dimitri J Stavropoulos
- Department of Paediatric Laboratory Medicine, Genome Diagnostics, The Hospital for Sick Children, Toronto, ON Canada
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32
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Huang D, Yi X, Zhou Y, Yao H, Xu H, Wang J, Zhang S, Nong W, Wang P, Shi L, Xuan C, Li M, Wang J, Li W, Kwan HS, Sham PC, Wang K, Li MJ. Ultrafast and scalable variant annotation and prioritization with big functional genomics data. Genome Res 2020; 30:1789-1801. [PMID: 33060171 PMCID: PMC7706736 DOI: 10.1101/gr.267997.120] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2020] [Accepted: 09/22/2020] [Indexed: 02/06/2023]
Abstract
The advances of large-scale genomics studies have enabled compilation of cell type–specific, genome-wide DNA functional elements at high resolution. With the growing volume of functional annotation data and sequencing variants, existing variant annotation algorithms lack the efficiency and scalability to process big genomic data, particularly when annotating whole-genome sequencing variants against a huge database with billions of genomic features. Here, we develop VarNote to rapidly annotate genome-scale variants in large and complex functional annotation resources. Equipped with a novel index system and a parallel random-sweep searching algorithm, VarNote shows substantial performance improvements (two to three orders of magnitude) over existing algorithms at different scales. It supports both region-based and allele-specific annotations and introduces advanced functions for the flexible extraction of annotations. By integrating massive base-wise and context-dependent annotations in the VarNote framework, we introduce three efficient and accurate pipelines to prioritize the causal regulatory variants for common diseases, Mendelian disorders, and cancers.
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Affiliation(s)
- Dandan Huang
- The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300070, China.,Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China.,Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Xianfu Yi
- School of Biomedical Engineering, Tianjin Medical University, Tianjin 300070, China
| | - Yao Zhou
- Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Hongcheng Yao
- School of Biomedical Sciences, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR 999077, China
| | - Hang Xu
- The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300070, China.,School of Biomedical Sciences, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR 999077, China
| | - Jianhua Wang
- Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Shijie Zhang
- Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Wenyan Nong
- School of Life Sciences, The Chinese University of Hong Kong, Hong Kong SAR 999077, China
| | - Panwen Wang
- Department of Health Sciences Research and Center for Individualized Medicine, Mayo Clinic, Scottsdale, Arizona 85259, USA
| | - Lei Shi
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Chenghao Xuan
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Miaoxin Li
- Center for Genome Research, Center for Precision Medicine, Zhongshan School of Medicine, First Affiliated Hospital, Sun Yat-Sen University, Guangzhou 510080, China
| | - Junwen Wang
- Department of Health Sciences Research and Center for Individualized Medicine, Mayo Clinic, Scottsdale, Arizona 85259, USA
| | - Weidong Li
- Department of Genetics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Hoi Shan Kwan
- School of Life Sciences, The Chinese University of Hong Kong, Hong Kong SAR 999077, China
| | - Pak Chung Sham
- Centre of Genomics Sciences, Departments of Psychiatry, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR 999077, China
| | - Kai Wang
- Raymond G. Perelman Center for Cellular and Molecular Therapeutics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania 19104, USA
| | - Mulin Jun Li
- The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300070, China.,Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China.,Department of Epidemiology and Biostatistics, Tianjin Key Laboratory of Molecular Cancer Epidemiology, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300070, China
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33
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Costain G, Walker S, Marano M, Veenma D, Snell M, Curtis M, Luca S, Buera J, Arje D, Reuter MS, Thiruvahindrapuram B, Trost B, Sung WWL, Yuen RKC, Chitayat D, Mendoza-Londono R, Stavropoulos DJ, Scherer SW, Marshall CR, Cohn RD, Cohen E, Orkin J, Meyn MS, Hayeems RZ. Genome Sequencing as a Diagnostic Test in Children With Unexplained Medical Complexity. JAMA Netw Open 2020; 3:e2018109. [PMID: 32960281 PMCID: PMC7509619 DOI: 10.1001/jamanetworkopen.2020.18109] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/29/2020] [Accepted: 07/12/2020] [Indexed: 12/16/2022] Open
Abstract
Importance Children with medical complexity (CMC) represent a growing population in the pediatric health care system, with high resource use and associated health care costs. A genetic diagnosis can inform prognosis, anticipatory care, management, and reproductive planning. Conventional genetic testing strategies for CMC are often costly, time consuming, and ultimately unsuccessful. Objective To evaluate the analytical and clinical validity of genome sequencing as a comprehensive diagnostic genetic test for CMC. Design, Setting, and Participants In this cohort study of the prospective use of genome sequencing and comparison with standard-of-care genetic testing, CMC were recruited from May 1, 2017, to November 30, 2018, from a structured complex care program based at a tertiary care pediatric hospital in Toronto, Canada. Recruited CMC had at least 1 chronic condition, technology dependence (child is dependent at least part of each day on mechanical ventilators, and/or child requires prolonged intravenous administration of nutritional substances or drugs, and/or child is expected to have prolonged dependence on other device-based support), multiple subspecialist involvement, and substantial health care use. Review of the care plans for 545 CMC identified 143 suspected of having an undiagnosed genetic condition. Fifty-four families met inclusion criteria and were interested in participating, and 49 completed the study. Probands, similarly affected siblings, and biological parents were eligible for genome sequencing. Exposures Genome sequencing was performed using blood-derived DNA from probands and family members using established methods and a bioinformatics pipeline for clinical genome annotation. Main Outcomes and Measures The primary study outcome was the diagnostic yield of genome sequencing (proportion of CMC for whom the test result yielded a new diagnosis). Results Genome sequencing was performed for 138 individuals from 49 families of CMC (29 male and 20 female probands; mean [SD] age, 7.0 [4.5] years). Genome sequencing detected all genomic variation previously identified by conventional genetic testing. A total of 15 probands (30.6%; 95% CI 19.5%-44.6%) received a new primary molecular genetic diagnosis after genome sequencing. Three individuals had novel diseases and an additional 9 had either ultrarare genetic conditions or rare genetic conditions with atypical features. At least 11 families received diagnostic information that had clinical management implications beyond genetic and reproductive counseling. Conclusions and Relevance This study suggests that genome sequencing has high analytical and clinical validity and can result in new diagnoses in CMC even in the setting of extensive prior investigations. This clinical population may be enriched for ultrarare and novel genetic disorders. Genome sequencing is a potentially first-tier genetic test for CMC.
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Affiliation(s)
- Gregory Costain
- Division of Clinical and Metabolic Genetics, The Hospital for Sick Children, Toronto, Ontario, Canada
- Centre for Genetic Medicine, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Susan Walker
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, Ontario, Canada
- Genetics and Genome Biology, Research Institute, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Maria Marano
- Division of Paediatric Medicine, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Danielle Veenma
- Division of Clinical and Metabolic Genetics, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Meaghan Snell
- Centre for Genetic Medicine, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Meredith Curtis
- Centre for Genetic Medicine, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Stephanie Luca
- Child Health Evaluative Sciences, Research Institute, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Jason Buera
- Division of Paediatric Medicine, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Danielle Arje
- Division of Paediatric Medicine, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Miriam S. Reuter
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, Ontario, Canada
- Genetics and Genome Biology, Research Institute, The Hospital for Sick Children, Toronto, Ontario, Canada
| | | | - Brett Trost
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Wilson W. L. Sung
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Ryan K. C. Yuen
- Genetics and Genome Biology, Research Institute, The Hospital for Sick Children, Toronto, Ontario, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
| | - David Chitayat
- Division of Clinical and Metabolic Genetics, The Hospital for Sick Children, Toronto, Ontario, Canada
- The Prenatal Diagnosis and Medical Genetics Program, Mount Sinai Hospital, Toronto, Ontario, Canada
- Department of Paediatrics, University of Toronto, Toronto, Ontario, Canada
| | - Roberto Mendoza-Londono
- Division of Clinical and Metabolic Genetics, The Hospital for Sick Children, Toronto, Ontario, Canada
- Centre for Genetic Medicine, The Hospital for Sick Children, Toronto, Ontario, Canada
- Department of Paediatrics, University of Toronto, Toronto, Ontario, Canada
| | - D. James Stavropoulos
- Centre for Genetic Medicine, The Hospital for Sick Children, Toronto, Ontario, Canada
- Genome Diagnostics, Department of Paediatric Laboratory Medicine, The Hospital for Sick Children, Toronto, Ontario, Canada
- Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada
- Department of Paediatrics, University of Toronto, Toronto, Ontario, Canada
| | - Stephen W. Scherer
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, Ontario, Canada
- Division of Paediatric Medicine, The Hospital for Sick Children, Toronto, Ontario, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
| | - Christian R. Marshall
- Centre for Genetic Medicine, The Hospital for Sick Children, Toronto, Ontario, Canada
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, Ontario, Canada
- Genome Diagnostics, Department of Paediatric Laboratory Medicine, The Hospital for Sick Children, Toronto, Ontario, Canada
- Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada
- Department of Paediatrics, University of Toronto, Toronto, Ontario, Canada
| | - Ronald D. Cohn
- Division of Clinical and Metabolic Genetics, The Hospital for Sick Children, Toronto, Ontario, Canada
- Division of Paediatric Medicine, The Hospital for Sick Children, Toronto, Ontario, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
- Department of Paediatrics, University of Toronto, Toronto, Ontario, Canada
| | - Eyal Cohen
- Division of Paediatric Medicine, The Hospital for Sick Children, Toronto, Ontario, Canada
- Child Health Evaluative Sciences, Research Institute, The Hospital for Sick Children, Toronto, Ontario, Canada
- Department of Paediatrics, University of Toronto, Toronto, Ontario, Canada
- Institute of Health Policy Management and Evaluation, University of Toronto, Toronto, Ontario, Canada
| | - Julia Orkin
- Division of Paediatric Medicine, The Hospital for Sick Children, Toronto, Ontario, Canada
- Child Health Evaluative Sciences, Research Institute, The Hospital for Sick Children, Toronto, Ontario, Canada
- Department of Paediatrics, University of Toronto, Toronto, Ontario, Canada
| | - M. Stephen Meyn
- Division of Clinical and Metabolic Genetics, The Hospital for Sick Children, Toronto, Ontario, Canada
- Centre for Genetic Medicine, The Hospital for Sick Children, Toronto, Ontario, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
- Department of Paediatrics, University of Toronto, Toronto, Ontario, Canada
- Center for Human Genomics and Precision Medicine, University of Wisconsin, Madison
| | - Robin Z. Hayeems
- Centre for Genetic Medicine, The Hospital for Sick Children, Toronto, Ontario, Canada
- Child Health Evaluative Sciences, Research Institute, The Hospital for Sick Children, Toronto, Ontario, Canada
- Institute of Health Policy Management and Evaluation, University of Toronto, Toronto, Ontario, Canada
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