Hana Zouk1, Wanfeng Yu2, Andrea Oza2, Megan Hawley2, Prathik K Vijay Kumar2, Christopher Koch2, Lisa M Mahanta2, John B Harley3, Gail P Jarvik4, Elizabeth W Karlson5, Kathleen A Leppig6, Melanie F Myers7, Cynthia A Prows8, Marc S Williams9, Scott T Weiss5, Matthew S Lebo10, Heidi L Rehm11. 1. Laboratory for Molecular Medicine, Mass General Brigham Personalized Medicine, Cambridge, MA; Department of Pathology, Massachusetts General Hospital, Harvard Medical School, Boston, MA. 2. Laboratory for Molecular Medicine, Mass General Brigham Personalized Medicine, Cambridge, MA. 3. Division of Human Genetics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH; University of Cincinnati College of Medicine, Cincinnati, OH; US Department of Veteran Affairs Medical Center, Cincinnati, OH. 4. Departments of Medicine (Medical Genetics) and Genome Sciences, University of Washington School of Medicine, Seattle, WA. 5. Brigham and Women's Hospital, Harvard Medical School, Boston, MA. 6. Genetic Services, Kaiser Permanente of Washington, Seattle, WA. 7. Division of Human Genetics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH; University of Cincinnati College of Medicine, Cincinnati, OH. 8. Division of Human Genetics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH. 9. Genomic Medicine Institute, Geisinger, Danville, PA. 10. Laboratory for Molecular Medicine, Mass General Brigham Personalized Medicine, Cambridge, MA; Brigham and Women's Hospital, Harvard Medical School, Boston, MA; Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA. 11. Laboratory for Molecular Medicine, Mass General Brigham Personalized Medicine, Cambridge, MA; Department of Pathology, Massachusetts General Hospital, Harvard Medical School, Boston, MA; Brigham and Women's Hospital, Harvard Medical School, Boston, MA; Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA; Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA. Electronic address: hrehm@mgh.harvard.edu.
Abstract
PURPOSE: The clinical genomics knowledgebase is dynamic with variant classifications changing as newly identified cases, additional population data, and other evidence become available. This is a challenge for the clinical laboratory because of limited resource availability for variant reassessment. METHODS: Throughout the Electronic Medical Records and Genomics phase III program, clinical sites associated with the Mass General Brigham/Broad sequencing center received automated, real-time notifications when reported variants were reclassified. In this study, we summarized the nature of these reclassifications and described the proactive reassessment framework we used for the Electronic Medical Records and Genomics program data set to identify variants most likely to undergo reclassification. RESULTS: Reanalysis of 1855 variants led to the reclassification of 2% (n = 45) of variants, affecting 0.6% (n = 67) of participants. Of these reclassifications, 78% (n = 35) were high-impact changes affecting reportability, with 8 variants downgraded from likely pathogenic/pathogenic to variants of uncertain significance (VUS) and 27 variants upgraded from VUS to likely pathogenic/pathogenic. Most upgraded variants (67%) were initially classified as VUS-Favor Pathogenic, highlighting the benefit of VUS subcategorization. The most common reason for reclassification was new published case data and/or functional evidence. CONCLUSION: Our results highlight the importance of periodic sequence variant reevaluation and the need for automated approaches to advance routine implementation of variant reevaluations in clinical practice.
PURPOSE: The clinical genomics knowledgebase is dynamic with variant classifications changing as newly identified cases, additional population data, and other evidence become available. This is a challenge for the clinical laboratory because of limited resource availability for variant reassessment. METHODS: Throughout the Electronic Medical Records and Genomics phase III program, clinical sites associated with the Mass General Brigham/Broad sequencing center received automated, real-time notifications when reported variants were reclassified. In this study, we summarized the nature of these reclassifications and described the proactive reassessment framework we used for the Electronic Medical Records and Genomics program data set to identify variants most likely to undergo reclassification. RESULTS: Reanalysis of 1855 variants led to the reclassification of 2% (n = 45) of variants, affecting 0.6% (n = 67) of participants. Of these reclassifications, 78% (n = 35) were high-impact changes affecting reportability, with 8 variants downgraded from likely pathogenic/pathogenic to variants of uncertain significance (VUS) and 27 variants upgraded from VUS to likely pathogenic/pathogenic. Most upgraded variants (67%) were initially classified as VUS-Favor Pathogenic, highlighting the benefit of VUS subcategorization. The most common reason for reclassification was new published case data and/or functional evidence. CONCLUSION: Our results highlight the importance of periodic sequence variant reevaluation and the need for automated approaches to advance routine implementation of variant reevaluations in clinical practice.