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  • Data sharing to improve concordance in variant interpretation across laboratories: results from the Canadian Open Genetics Repository

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Diagnostics
Original research
Data sharing to improve concordance in variant interpretation across laboratories: results from the Canadian Open Genetics Repository
  1. Chloe Mighton1,2,3,4,
  2. Amanda C Smith5,
  3. Justin Mayers2,
  4. Robert Tomaszewski6,
  5. Sherryl Taylor6,7,
  6. Stacey Hume6,7,
  7. Ron Agatep8,9,
  8. Elizabeth Spriggs8,9,
  9. Harriet E Feilotter10,11,
  10. Laura Semenuk10,
  11. Henry Wong10,
  12. Lorena Lazo de la Vega12,13,
  13. Christian R Marshall14,15,
  14. Michelle M Axford14,15,
  15. Talia Silver14,
  16. George S Charames2,4,15,
  17. Vanessa Di Gioacchino2,
  18. Nicholas Watkins2,16,
  19. William D Foulkes17,18,
  20. Marcos Clavier18,
  21. Nancy Hamel19,
  22. George Chong18,20,
  23. Ryan E Lamont21,22,
  24. Jillian Parboosingh21,22,
  25. Aly Karsan23,
  26. Ian Bosdet23,24,
  27. Sean S Young23,24,
  28. Tracy Tucker23,24,
  29. Mohammad Reza Akbari25,26,
  30. Marsha D Speevak27,
  31. Andrea K Vaags27,
  32. Matthew S Lebo12,13,
  33. Jordan Lerner-Ellis2,4,15
  34. Canadian Open Genetics Repository Working Group
    1. 1 Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada
    2. 2 Pathology and Laboratory Medicine, Mount Sinai Hospital, Sinai Health, Toronto, Ontario, Canada
    3. 3 Li Ka Shing Knowledge Institute, St. Michael's Hospital, Unity Health Toronto, Toronto, Ontario, Canada
    4. 4 Lunenfeld Tanenbaum Research Institute, Sinai Health, Toronto, Ontario, Canada
    5. 5 CHEO Research Institute, Ottawa, Ontario, Canada
    6. 6 Alberta Precision Laboratories, Edmonton, Alberta, Canada
    7. 7 Medical Genetics, University of Alberta, Edmonton, Alberta, Canada
    8. 8 Shared Health, Winnipeg, Manitoba, Canada
    9. 9 Biochemistry & Medical Genetics, University of Manitoba, Winnipeg, Manitoba, Canada
    10. 10 Kingston Health Sciences Centre, Kingston, Ontario, Canada
    11. 11 Department of Pathology and Molecular Medicine, Queen's University, Kingston, Ontario, Canada
    12. 12 Laboratory for Molecular Medicine, Mass General Brigham Personalized Medicine, Cambridge, Massachusetts, USA
    13. 13 Department of Pathology, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA
    14. 14 Genome Diagnostics, The Hospital for Sick Children, Toronto, Ontario, Canada
    15. 15 Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada
    16. 16 Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
    17. 17 Departments of Oncology and Human Genetics, McGill University, Montreal, Quebec, Canada
    18. 18 Lady David Institute for Medical Research, Jewish General Hospital, Montreal, Quebec, Canada
    19. 19 Research Institute of the McGill University Health Centre, Montreal, Quebec, Canada
    20. 20 Department of Human Genetics, McGill University, Montreal, Quebec, Canada
    21. 21 Department of Medical Genetics, University of Calgary, Calgary, Alberta, Canada
    22. 22 Alberta Precision Laboratories, Calgary, Alberta, Canada
    23. 23 Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, British Columbia, Canada
    24. 24 BC Cancer Agency, Vancouver, British Columbia, Canada
    25. 25 Women's College Research Institute, Women's College Hospital, Toronto, Ontario, Canada
    26. 26 Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada
    27. 27 Trillium Health Partners, Mississauga, Ontario, Canada
    1. Correspondence to Dr Jordan Lerner-Ellis, Pathology and Laboratory Medicine, Mount Sinai Hospital, Sinai Health, Toronto, ON M5G 1X5, Canada; jordan.lerner-ellis{at}sinaihealth.ca

    Abstract

    Background This study aimed to identify and resolve discordant variant interpretations across clinical molecular genetic laboratories through the Canadian Open Genetics Repository (COGR), an online collaborative effort for variant sharing and interpretation.

    Methods Laboratories uploaded variant data to the Franklin Genoox platform. Reports were issued to each laboratory, summarising variants where conflicting classifications with another laboratory were noted. Laboratories could then reassess variants to resolve discordances. Discordance was calculated using a five-tier model (pathogenic (P), likely pathogenic (LP), variant of uncertain significance (VUS), likely benign (LB), benign (B)), a three-tier model (LP/P are positive, VUS are inconclusive, LB/B are negative) and a two-tier model (LP/P are clinically actionable, VUS/LB/B are not). We compared the COGR classifications to automated classifications generated by Franklin.

    Results Twelve laboratories submitted classifications for 44 510 unique variants. 2419 variants (5.4%) were classified by two or more laboratories. From baseline to after reassessment, the number of discordant variants decreased from 833 (34.4% of variants reported by two or more laboratories) to 723 (29.9%) based on the five-tier model, 403 (16.7%) to 279 (11.5%) based on the three-tier model and 77 (3.2%) to 37 (1.5%) based on the two-tier model. Compared with the COGR classification, the automated Franklin classifications had 94.5% sensitivity and 96.6% specificity for identifying actionable (P or LP) variants.

    Conclusions The COGR provides a standardised mechanism for laboratories to identify discordant variant interpretations and reduce discordance in genetic test result delivery. Such quality assurance programmes are important as genetic testing is implemented more widely in clinical care.

    • genetics
    • human genetics
    • genetic testing

    Data availability statement

    All data relevant to the study are included in the article or uploaded as supplementary information.

    https://doi.org/10.1136/jmedgenet-2021-107738

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      Data availability statement

      All data relevant to the study are included in the article or uploaded as supplementary information.

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      Footnotes

      • Collaborators Canadian Open Genetics Repository Working Group: Ron Agatep, Peter Ainsworth, Mohammad R Akbari, Melyssa Aronson, Raveen Basran, Andre Blavier, Andrea Blumenthal, Yvonne Bombard, Ian Bosdet, Kym Boycott, Michael Brudno, Kathleen Buckley, Jodi Campbell, Philippe M Campeau, Melanie Care, Nancy Carson, Martin C Chang, Ronald Carter, George Charames, David Chitayat, George Chong, Edmond Chouinard, Kathy Chun, Kenneth J Craddock, Vanessa Di Gioacchino, Rod Docking, Andrea Eisen, Hanna Faghfoury, Sandra Farrell, Harriet Feilotter, Bridget Fernandez, Marc Fiume, Cynthia Forster-Gibson, Jan Friedman, William Foulkes, Peter Goodhand, Robert Hegele, Spring Holter, Sheri Horsburgh, Lauren Hughes, Stacey Hume, Olga Jarinova, Anne Junker, Aly Karsan, Sam Khalouei, Raymond H Kim, Joan Knoll, Elena Kolomietz, Bartha Knoppers, Ryan Lamont, Matthew Lebo, Jordan Lerner-Ellis, Georges Maire, Christian Marshall, Elizabeth McCready, Grant Mitchell, Chantal Morel, Tanya Nelson, Abdul Noor, Brian O’Connor, Darren O’Rielly, Francis Ouellette, Jillian Parboosingh, Trevor Pugh, Hilary Racher, Heidi Rehm, Christie Riddell, Jean-Baptiste Riviere, David S Rosenblatt, Guy Rouleau, Andrea Ruchon, Peter Sabatini, Bekim Sadikovic, Kara Semotiuk, Stephen W Scherer, Cheryl Shuman, Josh Silver, Katherine Siminovitch, Lesley Solomon-Izsak, Jean-Francois Soucy, Marsha Speevak, James Stavropoulos, Lincoln Stein, Sherryl Taylor, Deborah Terespolsky, Robert Tomaszewski, Tracy Tucker, Richard F Wintle, Nora Wong, Marina Wang, Nicholas Watkins, John S Waye, Shana White, Michael O Woods, Philip Wyatt, Sean Young, Kathleen-Rose Zakoor.

      • Contributors Conceptualisation: JL-E, MSL. Formal analysis: CM. Funding acquisition: JL-E, MSL. Investigation: CM, ACS, JM, RT, ST, SH, RA, ES, HF, LS, HW, LLdlV, CRM, MMA, TS, GSC, VDG, NW, WDF, MC, NH, GC, REL, JP, AK, IB, SSY, TT, MRA, MS, AKV, MSL, JL-E. Methodology: JL-E. Project Administration: JL-E, CM. Resources: ACS, JM, RT, ST, SH, RA, ES, HF, LS, HW, LLdlV, CRM, MMA, TS, GSC, VDG, NW, WDF, MC, NH, GC, RL, JP, AK, IB, SSY, TT, MA, MDS, AKV, MSL, JL-E. Supervision: JL-E. Writing—original draft: CM, JL-E. Writing—review and editing: JL-E, CM, LLdlV, WDF, VDG, TT, TS, HEF, AKV, ES, CRM, MMA.

      • Funding This work was funded by the government of Canada through Genome Canada, the Ontario Genomics Institute (OGI-070) and Can-SHARE. The Can-SHARE project was supported by Genome Quebec; Genome Canada; the government of Canada; the Ministère de l’Économie, Innovation et Exportation du Québec and the Canadian Institutes of Health Research (fund 141210). This work was supported by the Canadian provincial genetic testing programs and their Ministries of Health as well as the laboratory directors and staff.

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      • Competing interests None declared.

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

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