The Clinical Variant Analysis Tool: Analyzing the evidence supporting reported genomic variation in clinical practice.
Genetics in medicine : official journal of the American College of Medical Genetics
JGM, Exome, Genetic Testing, Genetic Variation, Genomics, Humans, Whole Exome Sequencing
Genet Med 2022 Jul; 24(7):1512-1522
PURPOSE: Genomic test results, regardless of laboratory variant classification, require clinical practitioners to judge the applicability of a variant for medical decisions. Teaching and standardizing clinical interpretation of genomic variation calls for a methodology or tool.
METHODS: To generate such a tool, we distilled the Clinical Genome Resource framework of causality and the American College of Medical Genetics/Association of Molecular Pathology and Quest Diagnostic Laboratory scoring of variant deleteriousness into the Clinical Variant Analysis Tool (CVAT). Applying this to 289 clinical exome reports, we compared the performance of junior practitioners with that of experienced medical geneticists and assessed the utility of reported variants.
RESULTS: CVAT enabled performance comparable to that of experienced medical geneticists. In total, 124 of 289 (42.9%) exome reports and 146 of 382 (38.2%) reported variants supported a diagnosis. Overall, 10.5% (1 pathogenic [P] or likely pathogenic [LP] variant and 39 variants of uncertain significance [VUS]) of variants were reported in genes without established disease association; 20.2% (23 P/LP and 54 VUS) were in genes without sufficient phenotypic concordance; 7.3% (15 P/LP and 13 VUS) conflicted with the known molecular disease mechanism; and 24% (91 VUS) had insufficient evidence for deleteriousness.
CONCLUSION: Implementation of CVAT standardized clinical interpretation of genomic variation and emphasized the need for collaborative and transparent reporting of genomic variation.
Chin, Hui-Lin; Gazzaz, Nour; Huynh, Stephanie; Handra, Iulia; Warnock, Lynn; Moller-Hansen, Ashley; Boerkoel, Pierre; Jacobsen, Julius O B; du Souich, Christèle; Zhang, Nan; Shefchek, Kent; Prentice, Leah M; Washington, Nicole; Haendel, Melissa; Armstrong, Linlea; Clarke, Lorne; Li, Wenhui Laura; Smedley, Damian; Robinson, Peter N; and Boerkoel, Cornelius F, "The Clinical Variant Analysis Tool: Analyzing the evidence supporting reported genomic variation in clinical practice." (2022). Faculty Research 2022. 158.