Targeted Analysis of Whole Genome Sequence Data to Diagnose Genetic Cardiomyopathy
Abstract
Background—Cardiomyopathy is highly heritable but genetically diverse. At present, genetic testing for cardiomyopathy uses targeted sequencing to simultaneously assess the coding regions of more than 50 genes. New genes are routinely added to panels to improve the diagnostic yield. With the anticipated $1000 genome, it is expected that genetic testing will shift towards comprehensive genome sequencing accompanied by targeted gene analysis. Therefore, we assessed the reliability of whole genome sequencing and targeted analysis to identify cardiomyopathy variants in 11 subjects with cardiomyopathy. Methods and Results—Whole genome sequencing with an average of 37× coverage was combined with targeted analysis focused on 204 genes linked to cardiomyopathy. Genetic variants were scored using multiple prediction algorithms combined with frequency data from public databases. This pipeline yielded 1-14 potentially pathogenic variants per individual. Variants were further analyzed using clinical criteria and/or segregation analysis. Three of three previously identified primary mutations were detected by this analysis. In six subjects for whom the primary mutation was previously unknown, we identified mutations that segregated with disease, had clinical correlates, and/or had additional pathological correlation to provide evidence for causality. For two subjects with previously known primary mutations, we identified additional variants that may act as modifiers ofmore »
- Authors:
-
- Univ. of Chicago, IL (United States); Argonne National Lab. (ANL), Argonne, IL (United States)
- Publication Date:
- Research Org.:
- Argonne National Laboratory (ANL), Argonne, IL (United States)
- Sponsoring Org.:
- USDOE; National Institutes of Health (NIH)
- OSTI Identifier:
- 1280878
- Grant/Contract Number:
- F32 HL097587; T32 HL007237
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Circulation. Cardiovascular genetics
- Additional Journal Information:
- Journal Volume: 7; Journal Issue: 6; Journal ID: ISSN 1942-325X
- Publisher:
- American Heart Association
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 59 BASIC BIOLOGICAL SCIENCES; cardiomyopathy; genetics; human; genomics; whole genome sequencing
Citation Formats
Golbus, Jessica R., Puckelwartz, Megan J., Dellefave-Castillo, Lisa, Fahrenbach, John P., Nelakuditi, Viswateja, Pesce, Lorenzo L., Pytel, Peter, and McNally, Elizabeth M. Targeted Analysis of Whole Genome Sequence Data to Diagnose Genetic Cardiomyopathy. United States: N. p., 2014.
Web. doi:10.1161/circgenetics.113.000578.
Golbus, Jessica R., Puckelwartz, Megan J., Dellefave-Castillo, Lisa, Fahrenbach, John P., Nelakuditi, Viswateja, Pesce, Lorenzo L., Pytel, Peter, & McNally, Elizabeth M. Targeted Analysis of Whole Genome Sequence Data to Diagnose Genetic Cardiomyopathy. United States. https://doi.org/10.1161/circgenetics.113.000578
Golbus, Jessica R., Puckelwartz, Megan J., Dellefave-Castillo, Lisa, Fahrenbach, John P., Nelakuditi, Viswateja, Pesce, Lorenzo L., Pytel, Peter, and McNally, Elizabeth M. Mon .
"Targeted Analysis of Whole Genome Sequence Data to Diagnose Genetic Cardiomyopathy". United States. https://doi.org/10.1161/circgenetics.113.000578. https://www.osti.gov/servlets/purl/1280878.
@article{osti_1280878,
title = {Targeted Analysis of Whole Genome Sequence Data to Diagnose Genetic Cardiomyopathy},
author = {Golbus, Jessica R. and Puckelwartz, Megan J. and Dellefave-Castillo, Lisa and Fahrenbach, John P. and Nelakuditi, Viswateja and Pesce, Lorenzo L. and Pytel, Peter and McNally, Elizabeth M.},
abstractNote = {Background—Cardiomyopathy is highly heritable but genetically diverse. At present, genetic testing for cardiomyopathy uses targeted sequencing to simultaneously assess the coding regions of more than 50 genes. New genes are routinely added to panels to improve the diagnostic yield. With the anticipated $1000 genome, it is expected that genetic testing will shift towards comprehensive genome sequencing accompanied by targeted gene analysis. Therefore, we assessed the reliability of whole genome sequencing and targeted analysis to identify cardiomyopathy variants in 11 subjects with cardiomyopathy. Methods and Results—Whole genome sequencing with an average of 37× coverage was combined with targeted analysis focused on 204 genes linked to cardiomyopathy. Genetic variants were scored using multiple prediction algorithms combined with frequency data from public databases. This pipeline yielded 1-14 potentially pathogenic variants per individual. Variants were further analyzed using clinical criteria and/or segregation analysis. Three of three previously identified primary mutations were detected by this analysis. In six subjects for whom the primary mutation was previously unknown, we identified mutations that segregated with disease, had clinical correlates, and/or had additional pathological correlation to provide evidence for causality. For two subjects with previously known primary mutations, we identified additional variants that may act as modifiers of disease severity. In total, we identified the likely pathological mutation in 9 of 11 (82%) subjects. We conclude that these pilot data demonstrate that ~30-40× coverage whole genome sequencing combined with targeted analysis is feasible and sensitive to identify rare variants in cardiomyopathy-associated genes.},
doi = {10.1161/circgenetics.113.000578},
journal = {Circulation. Cardiovascular genetics},
number = 6,
volume = 7,
place = {United States},
year = {Mon Sep 01 00:00:00 EDT 2014},
month = {Mon Sep 01 00:00:00 EDT 2014}
}
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