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      Dutch genome diagnostic laboratories accelerated and improved variant interpretation and increased accuracy by sharing data

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          Abstract

          Each year diagnostic laboratories in the Netherlands profile thousands of individuals for heritable disease using next‐generation sequencing (NGS). This requires pathogenicity classification of millions of DNA variants on the standard 5‐tier scale. To reduce time spent on data interpretation and increase data quality and reliability, the nine Dutch labs decided to publicly share their classifications. Variant classifications of nearly 100,000 unique variants were catalogued and compared in a centralized MOLGENIS database. Variants classified by more than one center were labeled as “consensus” when classifications agreed, and shared internationally with LOVD and ClinVar. When classifications opposed (LB/B vs. LP/P), they were labeled “conflicting”, while other nonconsensus observations were labeled “no consensus”. We assessed our classifications using the InterVar software to compare to ACMG 2015 guidelines, showing 99.7% overall consistency with only 0.3% discrepancies. Differences in classifications between Dutch labs or between Dutch labs and ACMG were mainly present in genes with low penetrance or for late onset disorders and highlight limitations of the current 5‐tier classification system. The data sharing boosted the quality of DNA diagnostics in Dutch labs, an initiative we hope will be followed internationally. Recently, a positive match with a case from outside our consortium resulted in a more definite disease diagnosis.

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          InterVar: Clinical Interpretation of Genetic Variants by the 2015 ACMG-AMP Guidelines.

          In 2015, the American College of Medical Genetics and Genomics (ACMG) and the Association for Molecular Pathology (AMP) published updated standards and guidelines for the clinical interpretation of sequence variants with respect to human diseases on the basis of 28 criteria. However, variability between individual interpreters can be extensive because of reasons such as the different understandings of these guidelines and the lack of standard algorithms for implementing them, yet computational tools for semi-automated variant interpretation are not available. To address these problems, we propose a suite of methods for implementing these criteria and have developed a tool called InterVar to help human reviewers interpret the clinical significance of variants. InterVar can take a pre-annotated or VCF file as input and generate automated interpretation on 18 criteria. Furthermore, we have developed a companion web server, wInterVar, to enable user-friendly variant interpretation with an automated interpretation step and a manual adjustment step. These tools are especially useful for addressing severe congenital or very early-onset developmental disorders with high penetrance. Using results from a few published sequencing studies, we demonstrate the utility of InterVar in significantly reducing the time to interpret the clinical significance of sequence variants.
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            Sequence variant classification and reporting: recommendations for improving the interpretation of cancer susceptibility genetic test results.

            Genetic testing of cancer susceptibility genes is now widely applied in clinical practice to predict risk of developing cancer. In general, sequence-based testing of germline DNA is used to determine whether an individual carries a change that is clearly likely to disrupt normal gene function. Genetic testing may detect changes that are clearly pathogenic, clearly neutral, or variants of unclear clinical significance. Such variants present a considerable challenge to the diagnostic laboratory and the receiving clinician in terms of interpretation and clear presentation of the implications of the result to the patient. There does not appear to be a consistent approach to interpreting and reporting the clinical significance of variants either among genes or among laboratories. The potential for confusion among clinicians and patients is considerable and misinterpretation may lead to inappropriate clinical consequences. In this article we review the current state of sequence-based genetic testing, describe other standardized reporting systems used in oncology, and propose a standardized classification system for application to sequence-based results for cancer predisposition genes. We suggest a system of five classes of variants based on the degree of likelihood of pathogenicity. Each class is associated with specific recommendations for clinical management of at-risk relatives that will depend on the syndrome. We propose that panels of experts on each cancer predisposition syndrome facilitate the classification scheme and designate appropriate surveillance and cancer management guidelines. The international adoption of a standardized reporting system should improve the clinical utility of sequence-based genetic tests to predict cancer risk. (c) 2008 Wiley-Liss, Inc.
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              A common MYBPC3 (cardiac myosin binding protein C) variant associated with cardiomyopathies in South Asia.

              Heart failure is a leading cause of mortality in South Asians. However, its genetic etiology remains largely unknown. Cardiomyopathies due to sarcomeric mutations are a major monogenic cause for heart failure (MIM600958). Here, we describe a deletion of 25 bp in the gene encoding cardiac myosin binding protein C (MYBPC3) that is associated with heritable cardiomyopathies and an increased risk of heart failure in Indian populations (initial study OR = 5.3 (95% CI = 2.3-13), P = 2 x 10(-6); replication study OR = 8.59 (3.19-25.05), P = 3 x 10(-8); combined OR = 6.99 (3.68-13.57), P = 4 x 10(-11)) and that disrupts cardiomyocyte structure in vitro. Its prevalence was found to be high (approximately 4%) in populations of Indian subcontinental ancestry. The finding of a common risk factor implicated in South Asian subjects with cardiomyopathy will help in identifying and counseling individuals predisposed to cardiac diseases in this region.
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                Author and article information

                Contributors
                M.E.van.Gijn@umcg.nl
                Journal
                Hum Mutat
                Hum. Mutat
                10.1002/(ISSN)1098-1004
                HUMU
                Human Mutation
                John Wiley and Sons Inc. (Hoboken )
                1059-7794
                1098-1004
                03 September 2019
                December 2019
                : 40
                : 12 ( doiID: 10.1002/humu.v40.12 )
                : 2230-2238
                Affiliations
                [ 1 ] Department of Human Genetics Leiden University Medical Center Leiden The Netherlands
                [ 2 ] Genomics Coordination Center & Department of Genetics University Medical Center, Groningen, University of Groningen Groningen The Netherlands
                [ 3 ] Department of Clinical Genetics Leiden University Medical Center Leiden The Netherlands
                [ 4 ] Department of Pathology Netherlands Cancer Institute Amsterdam The Netherlands
                [ 5 ] Department of Human Genetics, Donders Institute for Brain, Cognition and Behaviour Radboud University Medical Center Nijmegen The Netherlands
                [ 6 ] Department of Clinical Genetics Maastricht University Medical Center Maastricht The Netherlands
                [ 7 ] Department of Clinical Genetics, Academic Medical Center Amsterdam UMC Amsterdam The Netherlands
                [ 8 ] Department of Clinical Genetics, Vrije Universiteit Amsterdam Amsterdam UMC Amsterdam The Netherlands
                [ 9 ] Department of Genetics, University of Groningen University Medical Center Groningen Groningen The Netherlands
                [ 10 ] Department of Research IT Netherlands Cancer Institute Amsterdam The Netherlands
                [ 11 ] Medicine Department of Genetics, Division Laboratories, Pharmacy and Biomedical Genetics University Medical Center Utrecht Utrecht The Netherlands
                [ 12 ] DGG‐Genomics Software Solutions Agilent Technologies Leuven Belgium
                [ 13 ] Department of Human Genetics Radboud University Medical Center Nijmegen The Netherlands
                [ 14 ] Department of Clinical Genetics Erasmus Medical Center Rotterdam The Netherlands
                Author notes
                [*] [* ] Correspondence Marielle van Gijn, Department of Genetics, University Medical Center Groningen, Antonius Deusinglaan 1, HPC CB51, Postbus 30.001, 9700 RB Groningen, the Netherlands.

                Email: M.E.van.Gijn@ 123456umcg.nl

                [†]

                Fokkema and van der Velde are joint first authors. Laros, Swertz and van Gijn are joint senior authors.

                Author information
                http://orcid.org/0000-0002-1368-1939
                Article
                HUMU23896
                10.1002/humu.23896
                6900155
                31433103
                f685ca8f-defa-40d3-8f35-7adf8183f75a
                © 2019 The Authors. Human Mutation Published by Wiley Periodicals, Inc.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

                History
                : 20 February 2019
                : 05 August 2019
                : 14 August 2019
                Page count
                Figures: 3, Tables: 3, Pages: 9, Words: 5920
                Funding
                Funded by: Nederlandse Organisatie voor Wetenschappelijk Onderzoek , open-funder-registry 10.13039/501100003246;
                Award ID: 184.033.111
                Award ID: 917.164.455
                Funded by: ZonMw , open-funder-registry 10.13039/501100001826;
                Award ID: 846002003
                Categories
                Databases
                Databases
                Custom metadata
                2.0
                December 2019
                Converter:WILEY_ML3GV2_TO_JATSPMC version:5.7.2 mode:remove_FC converted:05.12.2019

                Human biology
                data sharing,database,diagnostics,ngs,whole‐exome sequencing
                Human biology
                data sharing, database, diagnostics, ngs, whole‐exome sequencing

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