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An Evidence-Based Assessment of Genes in Dilated Cardiomyopathy

Jordan, E; Peterson, L; Ai, T; Asatryan, B; Bronicki, L; Brown, E; Celeghin, R; ... Hershberger, RE; + view all (2021) An Evidence-Based Assessment of Genes in Dilated Cardiomyopathy. Circulation 10.1161/CIRCULATIONAHA.120.053033. (In press). Green open access

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Abstract

BACKGROUND: The cardiomyopathies, classically categorized as hypertrophic (HCM), dilated (DCM), and arrhythmogenic right ventricular (ARVC), each have a signature genetic theme. HCM and ARVC are largely understood as genetic diseases of sarcomere or desmosome proteins, respectively. In contrast, >250 genes spanning more than 10 gene ontologies have been implicated in DCM, representing a complex and diverse genetic architecture. To clarify this, a systematic curation of evidence to establish the relationship of genes with DCM was conducted. METHODS: An international Panel with clinical and scientific expertise in DCM genetics evaluated evidence supporting monogenic relationships of genes with idiopathic DCM. The Panel utilized the ClinGen semi-quantitative gene-disease clinical validity classification framework with modifications for DCM genetics to classify genes into categories based on the strength of currently available evidence. Representation of DCM genes on clinically available genetic testing panels was evaluated. RESULTS: Fifty-one genes with human genetic evidence were curated. Twelve genes (23%) from eight gene ontologies were classified as having definitive (BAG3, DES, FLNC, LMNA, MYH7, PLN, RBM20, SCN5A, TNNC1, TNNT2, TTN) or strong (DSP) evidence. Seven genes (14%) (ACTC1, ACTN2, JPH2, NEXN, TNNI3, TPM1, VCL) including two additional ontologies were classified as moderate evidence; these genes are likely to emerge as strong or definitive with additional evidence. Of these 19 genes, six were similarly classified for HCM and three for ARVC. Of the remaining 32 genes (63%), 25 (49%) had limited evidence, 4 (8%) were disputed, 2 (4%) had no disease relationship, and 1 (2%) was supported by animal model data only. Of 16 evaluated clinical genetic testing panels, most definitive genes were included, but panels also included numerous genes with minimal human evidence. CONCLUSIONS: In the curation of 51 genes, 19 had high evidence (12 definitive/strong; seven moderate). Notably, these 19 genes only explain a minority of cases, leaving the remainder of DCM genetic architecture incompletely addressed. Clinical genetic testing panels include most high evidence genes, however genes lacking robust evidence are also commonly included. We recommend that high evidence DCM genes be used for clinical practice and to exercise caution when interpreting variants in variable evidence DCM genes.

Type: Article
Title: An Evidence-Based Assessment of Genes in Dilated Cardiomyopathy
Location: United States
Open access status: An open access version is available from UCL Discovery
DOI: 10.1161/CIRCULATIONAHA.120.053033
Publisher version: https://doi.org/10.1161/CIRCULATIONAHA.120.053033
Language: English
Additional information: © 2021 The Authors. Circulation is published on behalf of the American Heart Association, Inc., by Wolters Kluwer Health, Inc. This is an open access article under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/).
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Cardiovascular Science
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Cardiovascular Science > Clinical Science
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Health Informatics
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Health Informatics > Infectious Disease Informatics
URI: https://discovery.ucl.ac.uk/id/eprint/10127451
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