A gene-centric strategy for identifying disease-causing rare variants in dilated cardiomyopathy

Horvat, C; Johnson, R; Lam, L; Munro, J; Mazzarotto, F; Roberts, AM; Herman, DS; Parfenov, M; Haghighi, A; McDonough, B; DePalma, SR; Keogh, AM; Macdonald, PS; Hayward, CS; Roberts, A; Barton, PJR; Felkin, LE; Giannoulatou, E; Cook, SA; Seidman, JG; Seidman, CE; Fatkin, D

A gene-centric strategy for identifying disease-causing rare variants in dilated cardiomyopathy

Horvat, C Johnson, R Lam, L Munro, J Mazzarotto, F Roberts, AM Herman, DS Parfenov, M Haghighi, A McDonough, B DePalma, SR Keogh, AM Macdonald, PS

Hayward, CS Roberts, A Barton, PJR Felkin, LE Giannoulatou, E Cook, SA Seidman, JG Seidman, CE Fatkin, D

Permalink

Publication Type:: Journal Article
Citation:: Genetics in Medicine, 2019, 21 (1), pp. 133 - 143
Issue Date:: 2019-01-01

Closed Access

	Filename	Description	Size
	A gene-centric strategy for identifying disease-causing rare variants in dilated cardiomyopathy.pdf	Published Version	574.04 kB	Adobe PDF	View/Open

Copyright Clearance Process

Recently Added
In Progress
Closed Access

This item is closed access and not available.

Full metadata record

Field	Value	Language
dc.contributor.author	Horvat, C	en_US
dc.contributor.author	Johnson, R	en_US
dc.contributor.author	Lam, L	en_US
dc.contributor.author	Munro, J	en_US
dc.contributor.author	Mazzarotto, F	en_US
dc.contributor.author	Roberts, AM	en_US
dc.contributor.author	Herman, DS	en_US
dc.contributor.author	Parfenov, M	en_US
dc.contributor.author	Haghighi, A	en_US
dc.contributor.author	McDonough, B	en_US
dc.contributor.author	DePalma, SR	en_US
dc.contributor.author	Keogh, AM	en_US
dc.contributor.author	Macdonald, PS https://orcid.org/0000-0001-5378-2825	en_US
dc.contributor.author	Hayward, CS	en_US
dc.contributor.author	Roberts, A	en_US
dc.contributor.author	Barton, PJR	en_US
dc.contributor.author	Felkin, LE	en_US
dc.contributor.author	Giannoulatou, E	en_US
dc.contributor.author	Cook, SA	en_US
dc.contributor.author	Seidman, JG	en_US
dc.contributor.author	Seidman, CE	en_US
dc.contributor.author	Fatkin, D	en_US
dc.date.available	2018-03-27	en_US
dc.date.issued	2019-01-01	en_US
dc.identifier.citation	Genetics in Medicine, 2019, 21 (1), pp. 133 - 143	en_US
dc.identifier.issn	1098-3600	en_US
dc.identifier.uri	http://hdl.handle.net/10453/134768
dc.description.abstract	© 2018, American College of Medical Genetics and Genomics. Purpose: We evaluated strategies for identifying disease-causing variants in genetic testing for dilated cardiomyopathy (DCM). Methods: Cardiomyopathy gene panel testing was performed in 532 DCM patients and 527 healthy control subjects. Rare variants in 41 genes were stratified using variant-level and gene-level characteristics. Results: A majority of DCM cases and controls carried rare protein-altering cardiomyopathy gene variants. Variant-level characteristics alone had limited discriminative value. Differentiation between groups was substantially improved by addition of gene-level information that incorporated ranking of genes based on literature evidence for disease association. The odds of DCM were increased to nearly 9-fold for truncating variants or high-impact missense variants in the subset of 14 genes that had the strongest biological links to DCM (P <0.0001). For some of these genes, DCM-associated variants appeared to be clustered in key protein functional domains. Multiple rare variants were present in many family probands, however, there was generally only one “driver” pathogenic variant that cosegregated with disease. Conclusion: Rare variants in cardiomyopathy genes can be effectively stratified by combining variant-level and gene-level information. Prioritization of genes based on their a priori likelihood of disease causation is a key factor in identifying clinically actionable variants in cardiac genetic testing.	en_US
dc.relation.ispartof	Genetics in Medicine	en_US
dc.relation.isbasedon	10.1038/s41436-018-0036-2	en_US
dc.subject.classification	Genetics & Heredity	en_US
dc.subject.mesh	Humans	en_US
dc.subject.mesh	Cardiomyopathy, Dilated	en_US
dc.subject.mesh	Genetic Predisposition to Disease	en_US
dc.subject.mesh	Rare Diseases	en_US
dc.subject.mesh	Pedigree	en_US
dc.subject.mesh	Mutation, Missense	en_US
dc.subject.mesh	Middle Aged	en_US
dc.subject.mesh	Female	en_US
dc.subject.mesh	Male	en_US
dc.subject.mesh	Genetic Testing	en_US
dc.subject.mesh	High-Throughput Nucleotide Sequencing	en_US
dc.title	A gene-centric strategy for identifying disease-causing rare variants in dilated cardiomyopathy	en_US
dc.type	Journal Article
utslib.citation.volume	1	en_US
utslib.citation.volume	21	en_US
utslib.for	0604 Genetics	en_US
utslib.for	1103 Clinical Sciences	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Health
utslib.copyright.status	closed_access
pubs.issue	1	en_US
pubs.publication-status	Published	en_US
pubs.volume	21	en_US

Abstract:

© 2018, American College of Medical Genetics and Genomics. Purpose: We evaluated strategies for identifying disease-causing variants in genetic testing for dilated cardiomyopathy (DCM). Methods: Cardiomyopathy gene panel testing was performed in 532 DCM patients and 527 healthy control subjects. Rare variants in 41 genes were stratified using variant-level and gene-level characteristics. Results: A majority of DCM cases and controls carried rare protein-altering cardiomyopathy gene variants. Variant-level characteristics alone had limited discriminative value. Differentiation between groups was substantially improved by addition of gene-level information that incorporated ranking of genes based on literature evidence for disease association. The odds of DCM were increased to nearly 9-fold for truncating variants or high-impact missense variants in the subset of 14 genes that had the strongest biological links to DCM (P <0.0001). For some of these genes, DCM-associated variants appeared to be clustered in key protein functional domains. Multiple rare variants were present in many family probands, however, there was generally only one “driver” pathogenic variant that cosegregated with disease. Conclusion: Rare variants in cardiomyopathy genes can be effectively stratified by combining variant-level and gene-level information. Prioritization of genes based on their a priori likelihood of disease causation is a key factor in identifying clinically actionable variants in cardiac genetic testing.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/134768