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. 2022 Jun;59(6):571-578.
doi: 10.1136/jmedgenet-2021-107738. Epub 2021 Apr 19.

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

Chloe Mighton  1   2   3   4 , Amanda C Smith  5 , Justin Mayers  2 , Robert Tomaszewski  6 , Sherryl Taylor  6   7 , Stacey Hume  6   7 , Ron Agatep  8   9 , Elizabeth Spriggs  8   9 , Harriet E Feilotter  10   11 , Laura Semenuk  10 , Henry Wong  10 , Lorena Lazo de la Vega  12   13 , Christian R Marshall  14   15 , Michelle M Axford  14   15 , Talia Silver  14 , George S Charames  2   4   15 , Vanessa Di Gioacchino  2 , Nicholas Watkins  2   16 , William D Foulkes  17   18 , Marcos Clavier  18 , Nancy Hamel  19 , George Chong  18   20 , Ryan E Lamont  21   22 , Jillian Parboosingh  21   22 , Aly Karsan  23 , Ian Bosdet  23   24 , Sean S Young  23   24 , Tracy Tucker  23   24 , Mohammad Reza Akbari  25   26 , Marsha D Speevak  27 , Andrea K Vaags  27 , Matthew S Lebo  12   13 , Jordan Lerner-Ellis  28   4   15 ; Canadian Open Genetics Repository Working Group
Collaborators, Affiliations

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

Chloe Mighton et al. J Med Genet. 2022 Jun.

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.

Keywords: genetic testing; genetics; human genetics.

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Conflict of interest statement

Competing interests: None declared.

Figures

Figure 1
Figure 1
Geographic location of all COGR Working Group laboratories. Sites that shared data in this initiative (1, 3, 5, 6, 7, 11, 12, 15, 18, 20, 22, 23) are indicated in yellow, and others are indicated in blue. *Accredited laboratories. COGR, Canadian Open Genetics Repository.
Figure 2
Figure 2
Rate of discordance among variants with multiple submissions (n=2419) at baseline and after reassessment, based on three different discrepancy models.
Figure 3
Figure 3
Number and direction of variant reclassifications. After data sharing and reassessment, laboratories changed the classification of 196 submissions. Most reclassifications were from VUS to likely benign (88). The x-axis indicates the variant’s final classification, the colour of the bars indicates the variant’s initial classification and the y-axis indicates the number of variants. VUS, variant of uncertain significance.
Figure 4
Figure 4
Percent of concordant and discordant variants in each gene at baseline and after reassessment, based on the five-tier model. Only genes with >20 variants with multiple submissions are included in this figure. Data for all genes can be found in online supplemental table 2.
See this image and copyright information in PMC

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