RT Journal Article SR Electronic T1 Data sharing to improve concordance in variant interpretation across laboratories: results from the Canadian Open Genetics Repository JF Journal of Medical Genetics JO J Med Genet FD BMJ Publishing Group Ltd SP 571 OP 578 DO 10.1136/jmedgenet-2021-107738 VO 59 IS 6 A1 Chloe Mighton A1 Amanda C Smith A1 Justin Mayers A1 Robert Tomaszewski A1 Sherryl Taylor A1 Stacey Hume A1 Ron Agatep A1 Elizabeth Spriggs A1 Harriet E Feilotter A1 Laura Semenuk A1 Henry Wong A1 Lorena Lazo de la Vega A1 Christian R Marshall A1 Michelle M Axford A1 Talia Silver A1 George S Charames A1 Vanessa Di Gioacchino A1 Nicholas Watkins A1 William D Foulkes A1 Marcos Clavier A1 Nancy Hamel A1 George Chong A1 Ryan E Lamont A1 Jillian Parboosingh A1 Aly Karsan A1 Ian Bosdet A1 Sean S Young A1 Tracy Tucker A1 Mohammad Reza Akbari A1 Marsha D Speevak A1 Andrea K Vaags A1 Matthew S Lebo A1 Jordan Lerner-Ellis A1 , YR 2022 UL http://jmg.bmj.com/content/59/6/571.abstract AB 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.All data relevant to the study are included in the article or uploaded as supplementary information.