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Maassen W, Legger G, Kul Cinar O, van Daele P, Gattorno M, Bader-Meunier B, Wouters C, Briggs T, Johansson L, van der Velde J, Swertz M, Omoyinmi E, Hoppenreijs E, Belot A, Eleftheriou D, Caorsi R, Aeschlimann F, Boursier G, Brogan P, Haimel M, van Gijn M. Curation and expansion of the Human Phenotype Ontology for systemic autoinflammatory diseases improves phenotype-driven disease-matching. Front Immunol 2023; 14:1215869. [PMID: 37781402 PMCID: PMC10536149 DOI: 10.3389/fimmu.2023.1215869] [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] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Accepted: 08/09/2023] [Indexed: 10/03/2023] Open
Abstract
Introduction Accurate and standardized phenotypic descriptions are essential in diagnosing rare diseases and discovering new diseases, and the Human Phenotype Ontology (HPO) system was developed to provide a rich collection of hierarchical phenotypic descriptions. However, although the HPO terms for inborn errors of immunity have been improved and curated, it has not been investigated whether this curation improves the diagnosis of systemic autoinflammatory disease (SAID) patients. Here, we aimed to study if improved HPO annotation for SAIDs enhanced SAID identification and to demonstrate the potential of phenotype-driven genome diagnostics using curated HPO terms for SAIDs. Methods We collected HPO terms from 98 genetically confirmed SAID patients across eight different European SAID expertise centers and used the LIRICAL (Likelihood Ratio Interpretation of Clinical Abnormalities) computational algorithm to estimate the effect of HPO curation on the prioritization of the correct SAID for each patient. Results Our results show that the percentage of correct diagnoses increased from 66% to 86% and that the number of diagnoses with the highest ranking increased from 38 to 45. In a further pilot study, curation also improved HPO-based whole-exome sequencing (WES) analysis, diagnosing 10/12 patients before and 12/12 after curation. In addition, the average number of candidate diseases that needed to be interpreted decreased from 35 to 2. Discussion This study demonstrates that curation of HPO terms can increase identification of the correct diagnosis, emphasizing the high potential of HPO-based genome diagnostics for SAIDs.
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Affiliation(s)
- Willem Maassen
- Genomics Coordination Centre, Department of Genetics, University Medical Centre Groningen, University of Groningen, Groningen, Netherlands
| | - Geertje Legger
- Department of Rheumatology and Clinical Immunology, University Medical Centre Groningen, University of Groningen, Groningen, Netherlands
| | - Ovgu Kul Cinar
- Department of Paediatric Rheumatology, Great Ormond Street Hospital for Children National Health Service Trust, London, United Kingdom
| | - Paul van Daele
- Department of Internal Medicine, Erasmus Medical Centre, Rotterdam, Netherlands
- Department of Immunology, Erasmus Medical Centre, Rotterdam, Netherlands
| | - Marco Gattorno
- UOC Reumatologia e Malattie Autoinfiammatorie, IRCCS Istituto Giannini Gaslini, Genoa, Italy
| | - Brigitte Bader-Meunier
- Department of Paediatric Immunology-Hematology and Rheumatology, Necker University Hospital - APHP, Paris, France
- Laboratory of Immunogenetics of Paediatric Autoimmune Diseases, UMR 1163, Imagine Institute, INSERM, Paris, France
| | - Carine Wouters
- Department of Pediatric Rheumatology, University Hospital Leuven, Leuven, Belgium
| | - Tracy Briggs
- Division of Evolution and Genomic Sciences, School of Biological Sciences, University of Manchester, Manchester, United Kingdom
- Manchester Centre for Genomic Medicine, St Mary’s Hospital, Manchester University Hospitals National Health Service Foundation Trust, Manchester, United Kingdom
| | - Lennart Johansson
- Genomics Coordination Centre, Department of Genetics, University Medical Centre Groningen, University of Groningen, Groningen, Netherlands
| | - Joeri van der Velde
- Genomics Coordination Centre, Department of Genetics, University Medical Centre Groningen, University of Groningen, Groningen, Netherlands
| | - Morris Swertz
- Genomics Coordination Centre, Department of Genetics, University Medical Centre Groningen, University of Groningen, Groningen, Netherlands
| | - Ebun Omoyinmi
- Department of Paediatric Rheumatology, Great Ormond Street Hospital for Children National Health Service Trust, London, United Kingdom
| | - Esther Hoppenreijs
- Department of Pediatric Rheumatology, Pediatrics, Radboud University Medical Center, Nijmegen, Netherlands
| | - Alexandre Belot
- National Referee Centre for Rheumatic and AutoImmune and Systemic Diseases in Children (RAISE), Pediatric Nephrology, Rheumatology, Dermatology Unit, INSERM, Hospital of Mother and Child, Hospices Civils of Lyon, Lyon, France
- International Center of Infectiology Research (CIRI), University of Lyon, INSERM, Claude Bernard University, Lyon, France
| | - Despina Eleftheriou
- Department of Paediatric Rheumatology, Great Ormond Street Hospital for Children National Health Service Trust, London, United Kingdom
| | - Roberta Caorsi
- UOC Reumatologia e Malattie Autoinfiammatorie, IRCCS Istituto Giannini Gaslini, Genoa, Italy
| | - Florence Aeschlimann
- Department of Paediatric Immunology-Hematology and Rheumatology, Necker University Hospital - APHP, Paris, France
- Division of Pediatric Rheumatology, University Children’s Hospital Basel, Basel, Switzerland
| | - Guilaine Boursier
- Laboratory of Rare and Autoinflammatory Genetic Diseases and Reference Centre for Autoinflammatory Diseases and Amyloidosis (CEREMAIA), Department of Medical Genetics, Rare Diseases and Personalized Medicine, CHU Montpellier, University of Montpellier, Montpellier, France
| | - Paul Brogan
- Inflammation and Rheumatology Section, University College London Great Ormond Street Institute of Child Health, London, United Kingdom
| | | | - Marielle van Gijn
- Department of Genetics, University Medical Centre Groningen, University of Groningen, Groningen, Netherlands
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Fujiwara T, Shin JM, Yamaguchi A. Advances in the development of PubCaseFinder, including the new application programming interface and matching algorithm. Hum Mutat 2022; 43:734-742. [PMID: 35143083 PMCID: PMC9305291 DOI: 10.1002/humu.24341] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [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: 09/30/2021] [Revised: 01/17/2022] [Accepted: 02/07/2022] [Indexed: 11/11/2022]
Abstract
Over 10,000 rare genetic diseases have been identified, and millions of newborns are affected by severe rare genetic diseases each year. A variety of Human Phenotype Ontology (HPO)-based clinical decision support systems (CDSS) and patient repositories have been developed to support clinicians in diagnosing patients with suspected rare genetic diseases. In September 2017, we released PubCaseFinder (https://pubcasefinder.dbcls.jp), a web-based CDSS that provides ranked lists of genetic and rare diseases using HPO-based phenotypic similarities, where top-listed diseases represent the most likely differential diagnosis. We also developed a Matchmaker Exchange (MME) application programming interface (API) to query PubCaseFinder, which has been adopted by several patient repositories. In this paper, we describe notable updates regarding PubCaseFinder, the GeneYenta matching algorithm implemented in PubCaseFinder, and the PubCaseFinder API. The updated GeneYenta matching algorithm improves the performance of the CDSS automated differential diagnosis function. Moreover, the updated PubCaseFinder and new API empower patient repositories participating in MME and medical professionals to actively use HPO-based resources. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Toyofumi Fujiwara
- Database Center for Life Science, Joint Support-Center for Data Science Research, Research Organization of Information and Systems, Kashiwa-shi, Chiba-ken, 277-0871, Japan
| | - Jae-Moon Shin
- Database Center for Life Science, Joint Support-Center for Data Science Research, Research Organization of Information and Systems, Kashiwa-shi, Chiba-ken, 277-0871, Japan
| | - Atsuko Yamaguchi
- Graduate School of Integrative Science and Engineering, Tokyo City University, Setagaya-ku, Tokyo, 158-8557, Japan
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Imafidon ME, Sikkema-Raddatz B, Abbott KM, Meems-Veldhuis MT, Swertz MA, van der Velde KJ, Beunders G, Bos DK, Knoers NVAM, Kerstjens-Frederikse WS, van Diemen CC. Strategies in Rapid Genetic Diagnostics of Critically Ill Children: Experiences From a Dutch University Hospital. Front Pediatr 2021; 9:600556. [PMID: 34136434 PMCID: PMC8200558 DOI: 10.3389/fped.2021.600556] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/30/2020] [Accepted: 04/29/2021] [Indexed: 12/03/2022] Open
Abstract
Background: Genetic disorders are a substantial cause of infant morbidity and mortality and are frequently suspected in neonatal intensive care units. Non-specific clinical presentation or limitations to physical examination can result in a plethora of genetic testing techniques, without clear strategies on test ordering. Here, we review our 2-years experiences of rapid genetic testing of NICU patients in order to provide such recommendations. Methods: We retrospectively included all patients admitted to the NICU who received clinical genetic consultation and genetic testing in our University hospital. We documented reasons for referral for genetic consultation, presenting phenotypes, differential diagnoses, genetic testing requested and their outcomes, as well as the consequences of each (rapid) genetic diagnostic approach. We calculated diagnostic yield and turnaround times (TATs). Results: Of 171 included infants that received genetic consultation 140 underwent genetic testing. As a result of testing as first tier, 13/14 patients received a genetic diagnosis from QF-PCR; 14/115 from SNP-array; 12/89 from NGS testing, of whom 4/46 were diagnosed with a small gene panel and 8/43 with a large OMIM-morbid based gene panel. Subsequent secondary or tertiary analysis and/or additional testing resulted in five more diagnoses. TATs ranged from 1 day (QF-PCR) to a median of 14 for NGS and SNP-array testing, with increasing TAT in particular when many consecutive tests were performed. Incidental findings were detected in 5/140 tested patients (3.6%). Conclusion: We recommend implementing a broad NGS gene panel in combination with CNV calling as the first tier of genetic testing for NICU patients given the often unspecific phenotypes of ill infants and the high yield of this large panel.
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Affiliation(s)
- Miriam E. Imafidon
- Department of Genetics, University of Groningen, University Medical Centre Groningen, Groningen, Netherlands
| | - Birgit Sikkema-Raddatz
- Department of Genetics, University of Groningen, University Medical Centre Groningen, Groningen, Netherlands
| | - Kristin M. Abbott
- Department of Genetics, University of Groningen, University Medical Centre Groningen, Groningen, Netherlands
| | - Martine T. Meems-Veldhuis
- Department of Genetics, University of Groningen, University Medical Centre Groningen, Groningen, Netherlands
| | - Morris A. Swertz
- Department of Genetics, University of Groningen, University Medical Centre Groningen, Groningen, Netherlands
- Genomics Coordination Center, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
| | - K. Joeri van der Velde
- Department of Genetics, University of Groningen, University Medical Centre Groningen, Groningen, Netherlands
- Genomics Coordination Center, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
| | - Gea Beunders
- Department of Genetics, University of Groningen, University Medical Centre Groningen, Groningen, Netherlands
| | - Dennis K. Bos
- Department of Genetics, University of Groningen, University Medical Centre Groningen, Groningen, Netherlands
| | - Nine V. A. M. Knoers
- Department of Genetics, University of Groningen, University Medical Centre Groningen, Groningen, Netherlands
| | | | - Cleo C. van Diemen
- Department of Genetics, University of Groningen, University Medical Centre Groningen, Groningen, Netherlands
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