Targeted Analysis of Whole Genome Sequence Data to Diagnose Genetic Cardiomyopathy

• Published in: Circulation. Cardiovascular genetics Vol. 7; no. 6; pp. 751 - 759
• Main Authors: Golbus, Jessica R., Puckelwartz, Megan J., Dellefave-Castillo, Lisa, Fahrenbach, John P., Nelakuditi, Viswateja, Pesce, Lorenzo L., Pytel, Peter, McNally, Elizabeth M.
• Format: Journal Article
• Language: English
• Published: United States American Heart Association, Inc 01.12.2014; American Heart Association
• Subjects: Adaptor Proteins, Signal Transducing - genetics; Adolescent; Adult; Algorithms; BASIC BIOLOGICAL SCIENCES; Cardiomyopathies - diagnosis; Cardiomyopathies - economics; Cardiomyopathies - genetics; cardiomyopathy; Child; Databases, Genetic; genetics; Genome, Human; genomics; High-Throughput Nucleotide Sequencing; human; Humans; LIM Domain Proteins - genetics; Middle Aged; Myosin Heavy Chains - genetics; NAV1.5 Voltage-Gated Sodium Channel - genetics; Pedigree; Polymorphism, Single Nucleotide; Sequence Analysis, DNA; whole genome sequencing; Young Adult; genomics; genetics; cardiomyopathies; humans
• ISSN: 1942-325X; 1942-3268; 1942-3268
• DOI: 10.1161/CIRCGENETICS.113.000578

BACKGROUND—Cardiomyopathy is highly heritable but genetically diverse. At present, genetic testing for cardiomyopathy uses targeted sequencing to simultaneously assess the coding regions of >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 toward 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 to 14 potentially pathogenic variants per individual. Variants were further analyzed using clinical criteria and segregation analysis, where available. Three of 3 previously identified primary mutations were detected by this analysis. In 6 subjects for whom the primary mutation was previously unknown, we identified mutations that segregated with disease, had clinical correlates, and had additional pathological correlation to provide evidence for causality. For 2 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. CONCLUSIONS—These pilot data demonstrate that ≈30 to 40× coverage whole genome sequencing combined with targeted analysis is feasible and sensitive to identify rare variants in cardiomyopathy-associated genes.