Presenter Bart Broeckx
Authors Iris Casselman (1), Carlotta Ferrari (2), Marie Abitbol (3), Danika Bannasch (4), Jerold Bell (5), Caroline Dufaure de Citres (6), Carrie J. Finno (7), Jessica J. Hayward (8), Jens Häggström (9), Jason T. Huff (10), Tosso Leeb (11), Ingrid Ljungvall (9), Maria Longeri (2), Leslie A. Lyons (12), Marcela Martinez (13), Cathryn Mellersh (14), Frank W. Nicholas (15), Åsa Ohlsson (16), Pascale Smets (17), Maria G. Strillacci (2), Imke Tammen (15), Frank G. van Steenbeek (18), Bart J.G. Broeckx (1, 19)
Affiliations 1 Laboratory of Animal Genetics, Department of Veterinary and Biosciences, Faculty of Veterinary Medicine, Ghent University, Merelbeke-Melle, Belgium. 2 Department of Veterinary Medicine and Animal Science, University of Milan, Lodi, Italy. 3 Univ Lyon, VetAgro Sup, Marcy-l’Etoile, France and Institut NeuroMyoGène INMG-PGNM, CNRS UMR5261, INSERM U1315, Faculté de Médecine, Rockefeller, Université Claude Bernard, Lyon, France. 4 Department of Population Health and Reproduction, School of Veterinary Medicine, University of California Davis, Davis, CA, USA. 5 Department of Clinical Sciences, Cummings School of Veterinary Medicine, Tufts University. N. Grafton, MA, USA. 6 Antagene - Animal Genomics Laboratory, La Tour de Salvagny, France. 7 Department of Population Health and Reproduction, University of California Davis School of Veterinary Medicine, Davis, USA. 8 Department of Biomedical Sciences and Cornell Veterinary Biobank, College of Veterinary Medicine, Cornell University, Ithaca, USA. 9 Department of Clinical Sciences, Faculty of Veterinary Medicine and Animal Science, Swedish University of Agricultural Sciences, Uppsala, Sweden. 10 Wisdom Panel, Mars Petcare Science & Diagnostics, Fountain Valley, USA. 11 Institute of Genetics, Vetsuisse Faculty, University of Bern, Bern, Switzerland. 12 Department of Veterinary Medicine and Surgery, College of Veterinary Medicine, University of Missouri, Columbia, USA. 13 Applied Genetics Laboratory, Sociedad Rural Argentina, Buenos Aires, Argentina. 14 Canine Genetics Centre, Department of Veterinary Medicine, University of Cambridge, Cambridge, United Kingdom. 15 Sydney School of Veterinary Science, Faculty of Science, The University of Sydney, Camden, Australia. 16 Department of Animal Biosciences, Faculty of Veterinary Medicine and Animal Science, Swedish University of Agricultural Sciences, Uppsala, Sweden. 17 Small Animal Department, Faculty of Veterinary Medicine, Ghent University, Merelbeke-Melle, Belgium. 18 Department of Clinical Sciences, Faculty of Veterinary Medicine, Utrecht University, Utrecht, The Netherlands. 19 Centre for Clinical Genetics of Companion Animals, Faculty of Veterinary Medicine, Ghent University, Merelbeke-Melle, Belgium.
Presentation Type Talk
Abstract
Until recently, due to the lack of standardized guidelines tailored for veterinary use, the evaluation of genetic variant pathogenicity for single-gene diseases was based on a subjective personal interpretation of the presented evidence, which has led to ambiguous interpretations. Assessing the pathogenicity is however vital, both on a population and individual scale. At the population level, breeding decisions based on invalid DNA tests can lead to the incorrect inclusion or exclusion of animals and compromise the long-term health of a population, and at the level of the individual animal, lead to incorrect treatment and even life-ending decisions. With the publication of the animal variant classification guidelines (AVCG), a more objective approach became available. Variants are evaluated based on twenty-three criteria and labeled as pathogenic, likely pathogenic, variant of uncertain significance, likely benign or benign. In two subsequent studies, we have evaluated the accuracy of these new guidelines, as well as the reproducibility of decisions on the scope and the final label.
To assess the accuracy of the guidelines, methods were developed to produce a “true” disease-causing variant dataset (n = 53), as well as a “benign” variant dataset (n = 47). This led to the first dataset where classifications by panelists were compared with the “truth”. For reproducibility, a second set of 150 published likely causal variants for single-gene diseases from three species (dog, cat, horse) was independently and blindly assessed by three different reviewers, each applying the same AVCG. To evaluate agreement, the classifications of each individual reviewer were compared pairwise, leading to a total of 450 pairwise comparisons.
In the first study, 92% of the pathogenic variants were accurately classified with AVCG. In the second study, there was an overall agreement of 93% for decisions on the scope, i.e. whether they fit the inclusion criteria to allow evaluation with AVCG. More importantly, the exact reproducibility was 65% for the pathogenicity classification and this increased further to 83% clinically important agreement. While a direct comparison of the reproducibility with human literature is not possible for the scope, the reproducibility on pathogenicity classification is in line with reports using the human American College of Medical Genetics and Genomics and Association for Molecular Pathology guidelines for human variants. Factors that might improve reproducibility include automated label calculation to avoid tabulation errors, and additional clarification of criteria.
Overall, with the AVCG, there is now a tool tailored for variant classification in domestic animals that has been demonstrated to be highly accurate and reproducible within current expectations. To ensure easy access and quick updating of labels whenever necessary, the labels will also be included in the Online Mendelian Inheritance in Animals variant table.