Reanalysis of eMERGE phase III sequence variants in 10,500 participants and infrastructure to support the automated return of knowledge updates
- PMID: 34906510
- PMCID: PMC10128874
- DOI: 10.1016/j.gim.2021.10.010
Reanalysis of eMERGE phase III sequence variants in 10,500 participants and infrastructure to support the automated return of knowledge updates
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.
Keywords: Automated variant reclassification alerts; Variant reassessment framework; Variant reclassification; eMERGE.
Copyright © 2021 American College of Medical Genetics and Genomics. Published by Elsevier Inc. All rights reserved.
Conflict of interest statement
Conflict of Interest H.Z., W.Y., A.O., M.H., P.K.V.K., C.K., L.M.M., E.W.K., S.T.W., M.S.L., and H.L.R. were either employed at Mass General Brigham at the time this work was performed or are current employees of Mass General Brigham, which receives royalties on the sale of GeneInsight Software. All other authors declare no conflicts of interest.
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References
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