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  • New workflow for classification of genetic variants’ pathogenicity applied to hereditary recurrent fevers by the International Study Group for Systemic Autoinflammatory Diseases (INSAID)

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Diagnostics
Original article
New workflow for classification of genetic variants’ pathogenicity applied to hereditary recurrent fevers by the International Study Group for Systemic Autoinflammatory Diseases (INSAID)
  1. Marielle E Van Gijn1,
  2. Isabella Ceccherini2,
  3. Yael Shinar3,
  4. Ellen C Carbo1,
  5. Mariska Slofstra4,
  6. Juan I Arostegui5,
  7. Guillaume Sarrabay6,
  8. Dorota Rowczenio7,
  9. Ebun Omoyımnı8,
  10. Banu Balci-Peynircioglu9,
  11. Hal M Hoffman10,
  12. Florian Milhavet6,
  13. Morris A Swertz4,
  14. Isabelle Touitou6
  1. 1 Department of Genetics, University Medical Center Utrecht, Utrecht, The Netherlands
  2. 2 UOC Medical Genetics, Giannina Gaslini Institute, Genova, Italy
  3. 3 Laboratory of FMF, Amyloidosis and Rare Autoinflammatory Diseases, Sheba Medical Center, Tel Hashomer, Israel
  4. 4 Genomics Coordination Center, Department of Genetics, University Medical Center Groningen, Groningen, The Netherlands
  5. 5 Department of Immunology, Hospital Clinic-IDIBAPS, Barcelona, Spain
  6. 6 Laboratory of Rare and Autoinflammatory Diseases, CHU Montpellier, Montpellier University, INSERM U1183, Montpellier, France
  7. 7 National Amyloidosis Centre, Division of Medicine, UCL, Royal Free Hospital, London, UK
  8. 8 Great Ormond Street Institute of Child Health (ICH), University College London, London, UK
  9. 9 Department of Medical Biology, Hacettepe University Faculty of Medicine, Ankara, Turkey
  10. 10 Department of Pediatrics, University of California, San Diego, California, USA
  1. Correspondence to Dr Marielle E Van Gijn, Department of Genetics, University Medical Center Utrecht, Utrecht 3584 CX, The Netherlands; m.e.vangijn{at}umcutrecht.nl

Abstract

Background Hereditary recurrent fevers (HRFs) are rare inflammatory diseases sharing similar clinical symptoms and effectively treated with anti-inflammatory biological drugs. Accurate diagnosis of HRF relies heavily on genetic testing.

Objectives This study aimed to obtain an experts’ consensus on the clinical significance of gene variants in four well-known HRF genes: MEFV, TNFRSF1A, NLRP3 and MVK.

Methods We configured a MOLGENIS web platform to share and analyse pathogenicity classifications of the variants and to manage a consensus-based classification process. Four experts in HRF genetics submitted independent classifications of 858 variants. Classifications were driven to consensus by recruiting four more expert opinions and by targeting discordant classifications in five iterative rounds.

Results Consensus classification was reached for 804/858 variants (94%). None of the unsolved variants (6%) remained with opposite classifications (eg, pathogenic vs benign). New mutational hotspots were found in all genes. We noted a lower pathogenic variant load and a higher fraction of variants with unknown or unsolved clinical significance in the MEFV gene.

Conclusion Applying a consensus-driven process on the pathogenicity assessment of experts yielded rapid classification of almost all variants of four HRF genes. The high-throughput database will profoundly assist clinicians and geneticists in the diagnosis of HRFs. The configured MOLGENIS platform and consensus evolution protocol are usable for assembly of other variant pathogenicity databases. The MOLGENIS software is available for reuse at http://github.com/molgenis/molgenis; the specific HRF configuration is available at http://molgenis.org/said/. The HRF pathogenicity classifications will be published on the INFEVERS database at https://fmf.igh.cnrs.fr/ISSAID/infevers/.

  • genetic diagnosis
  • pathogenicity classification
  • hereditary recurrent fever
  • molgenis
  • infevers

https://doi.org/10.1136/jmedgenet-2017-105216

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    Footnotes

    • MEVG, IC and YS contributed equally.

    • Contributors Design of the study: MEVG, IT, MAS and IC; design of databases: ECC, MS, MAS and FM. Data analysis: IT, MEVG, MS and ECC. Classifying variants: MEVG, IC, YS, JIA, GS, DR, EO, BP, HMH and IT. Writing the manuscript: IT, MEVG, IC and YS; revising the manuscript: JIA, DR, EO, MAS and HMH; all authors approved the manuscript.

    • Funding This study is part of the INSAID project funded by an E-Rare-3 program, grant number 9003037603. BBMRI-NL is a research infrastructure financed by the Netherlands Organization for Scientific Research (NWO), grant number 184.033.111. CORBEL is an ESFRI cluster project in the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 654248. RD-Connect has received funding from the European Union Seventh Framework Programme (FP7/2007–2013) under grant agreement no. 305,444 (RD-Connect).

    • Competing interests None declared.

    • Patient consent Detail has been removed from this case description/these case descriptions to ensure anonymity. The editors and reviewers have seen the detailed information available and are satisfied that the information backs up the case the authors are making.

    • Provenance and peer review Not commissioned; externally peer reviewed.

    • Data sharing statement The datasets generated and/or analysed during the current study are available in the MOLGENIS repository at http://molgenis.org/said/ and the INFEVERS repository at https://fmf.igh.cnrs.fr/ISSAID/infevers/. MOLGENIS software is available for reuse at http://github.com/molgenis/molgenis