Literature DB >> 35442193

The Clinical Variant Analysis Tool: Analyzing the evidence supporting reported genomic variation in clinical practice.

Hui-Lin Chin1, Nour Gazzaz2, Stephanie Huynh3, Iulia Handra3, Lynn Warnock4, Ashley Moller-Hansen4, Pierre Boerkoel5, Julius O B Jacobsen6, Christèle du Souich7, Nan Zhang8, Kent Shefchek9, Leah M Prentice10, Nicole Washington11, Melissa Haendel9, Linlea Armstrong3, Lorne Clarke3, Wenhui Laura Li8, Damian Smedley6, Peter N Robinson12, Cornelius F Boerkoel13.   

Abstract

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.
Copyright © 2022 American College of Medical Genetics and Genomics. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Exome sequencing; Genomic medicine; Precision medicine; Variant classification; Variant interpretation

Mesh:

Year:  2022        PMID: 35442193      PMCID: PMC9363005          DOI: 10.1016/j.gim.2022.03.013

Source DB:  PubMed          Journal:  Genet Med        ISSN: 1098-3600            Impact factor:   8.864


  29 in total

1.  Evaluating the Clinical Validity of Gene-Disease Associations: An Evidence-Based Framework Developed by the Clinical Genome Resource.

Authors:  Natasha T Strande; Erin Rooney Riggs; Adam H Buchanan; Ozge Ceyhan-Birsoy; Marina DiStefano; Selina S Dwight; Jenny Goldstein; Rajarshi Ghosh; Bryce A Seifert; Tam P Sneddon; Matt W Wright; Laura V Milko; J Michael Cherry; Monica A Giovanni; Michael F Murray; Julianne M O'Daniel; Erin M Ramos; Avni B Santani; Alan F Scott; Sharon E Plon; Heidi L Rehm; Christa L Martin; Jonathan S Berg
Journal:  Am J Hum Genet       Date:  2017-05-25       Impact factor: 11.025

2.  A method and server for predicting damaging missense mutations.

Authors:  Ivan A Adzhubei; Steffen Schmidt; Leonid Peshkin; Vasily E Ramensky; Anna Gerasimova; Peer Bork; Alexey S Kondrashov; Shamil R Sunyaev
Journal:  Nat Methods       Date:  2010-04       Impact factor: 28.547

Review 3.  Sequencing studies in human genetics: design and interpretation.

Authors:  David B Goldstein; Andrew Allen; Jonathan Keebler; Elliott H Margulies; Steven Petrou; Slavé Petrovski; Shamil Sunyaev
Journal:  Nat Rev Genet       Date:  2013-06-11       Impact factor: 53.242

4.  Enhanced utility of family-centered diagnostic exome sequencing with inheritance model-based analysis: results from 500 unselected families with undiagnosed genetic conditions.

Authors:  Kelly D Farwell; Layla Shahmirzadi; Dima El-Khechen; Zöe Powis; Elizabeth C Chao; Brigette Tippin Davis; Ruth M Baxter; Wenqi Zeng; Cameron Mroske; Melissa C Parra; Stephanie K Gandomi; Ira Lu; Xiang Li; Hong Lu; Hsiao-Mei Lu; David Salvador; David Ruble; Monica Lao; Soren Fischbach; Jennifer Wen; Shela Lee; Aaron Elliott; Charles L M Dunlop; Sha Tang
Journal:  Genet Med       Date:  2014-11-13       Impact factor: 8.822

5.  A general framework for estimating the relative pathogenicity of human genetic variants.

Authors:  Martin Kircher; Daniela M Witten; Preti Jain; Brian J O'Roak; Gregory M Cooper; Jay Shendure
Journal:  Nat Genet       Date:  2014-02-02       Impact factor: 38.330

6.  Modeling the ACMG/AMP variant classification guidelines as a Bayesian classification framework.

Authors:  Sean V Tavtigian; Marc S Greenblatt; Steven M Harrison; Robert L Nussbaum; Snehit A Prabhu; Kenneth M Boucher; Leslie G Biesecker
Journal:  Genet Med       Date:  2018-01-04       Impact factor: 8.822

7.  Gene.iobio: an interactive web tool for versatile, clinically-driven variant interrogation and prioritization.

Authors:  Tonya Di Sera; Matt Velinder; Alistair Ward; Yi Qiao; Stephanie Georges; Chase Miller; Anders Pitman; Will Richards; Aditya Ekawade; David Viskochil; John C Carey; Laura Pace; Jim Bale; Stacey L Clardy; Ashley Andrews; Lorenzo Botto; Gabor Marth
Journal:  Sci Rep       Date:  2021-10-13       Impact factor: 4.379

8.  Clinical application of whole-exome sequencing across clinical indications.

Authors:  Kyle Retterer; Jane Juusola; Megan T Cho; Patrik Vitazka; Francisca Millan; Federica Gibellini; Annette Vertino-Bell; Nizar Smaoui; Julie Neidich; Kristin G Monaghan; Dianalee McKnight; Renkui Bai; Sharon Suchy; Bethany Friedman; Jackie Tahiliani; Daniel Pineda-Alvarez; Gabriele Richard; Tracy Brandt; Eden Haverfield; Wendy K Chung; Sherri Bale
Journal:  Genet Med       Date:  2015-12-03       Impact factor: 8.822

Review 9.  A Curriculum for Genomic Education of Molecular Genetic Pathology Fellows: A Report of the Association for Molecular Pathology Training and Education Committee.

Authors:  Jason N Rosenbaum; Anna B Berry; Alanna J Church; Kristy Crooks; Jeffrey R Gagan; Dolores López-Terrada; John D Pfeifer; Hanna Rennert; Iris Schrijver; Anthony N Snow; David Wu; Mark D Ewalt
Journal:  J Mol Diagn       Date:  2021-07-07       Impact factor: 5.568

10.  Recommendations for application of the functional evidence PS3/BS3 criterion using the ACMG/AMP sequence variant interpretation framework.

Authors:  Sarah E Brnich; Ahmad N Abou Tayoun; Fergus J Couch; Garry R Cutting; Marc S Greenblatt; Christopher D Heinen; Dona M Kanavy; Xi Luo; Shannon M McNulty; Lea M Starita; Sean V Tavtigian; Matt W Wright; Steven M Harrison; Leslie G Biesecker; Jonathan S Berg
Journal:  Genome Med       Date:  2019-12-31       Impact factor: 11.117

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