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|Title:||A gene-centric strategy for identifying disease-causing rare variants in dilated cardiomyopathy||Authors:||Horvat C.
|Issue Date:||2018||Publisher:||Springer Nature||Citation:||Horvat C., Johnson R., Lam L., Munro J., Mazzarotto F., Roberts A.M., Herman D.S., Parfenov M., Haghighi A., McDonough B., DePalma S.R., Keogh A.M., Macdonald P.S., Hayward C.S., Roberts A., Barton P.J.R., Felkin L.E., Giannoulatou E., Cook S.A., Seidman J.G., Seidman C.E., Fatkin D. (2018). A gene-centric strategy for identifying disease-causing rare variants in dilated cardiomyopathy. Genetics in Medicine : 1-11. ScholarBank@NUS Repository. https://doi.org/10.1038/s41436-018-0036-2||Abstract:||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. 2018 American College of Medical Genetics and Genomics.||Source Title:||Genetics in Medicine||URI:||http://scholarbank.nus.edu.sg/handle/10635/150243||ISSN:||10983600||DOI:||10.1038/s41436-018-0036-2|
|Appears in Collections:||Staff Publications|
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