Evaluating pathogenicity of rare variants from dilated cardiomyopathy in the exome era

Inherited cardiomyopathies: molecular genetics and clinical genetic testing in the postgenomic era

Inherited cardiomyopathies include hypertrophic cardiomyopathy, dilated cardiomyopathy, arrhythmogenic right ventricular cardiomyopathy, left ventricular noncompaction, and restrictive cardiomyopathy. These diseases have a substantial genetic component and predispose to sudden cardiac death, which provides a high incentive to identify and sequence disease genes in affected individuals to identify pathogenic variants. Clinical genetic testing, which is now widely available, can be a powerful tool for identifying presymptomatic individuals. However, locus and allelic heterogeneity are the rule, as are clinical variability and reduced penetrance of disease in carriers of pathogenic variants. These factors, combined with genetic and phenotypic overlap between different cardiomyopathies, have made clinical genetic testing a lengthy and costly process. Next-generation sequencing technologies have removed many limitations such that comprehensive testing is now feasible, shortening diagnostic odysseys for clinically complex cases. Remaining challenges include the incomplete understanding of the spectrum of benign and pathogenic variants in the cardiomyopathy genes, which is a source of inconclusive results. This review provides an overview of inherited cardiomyopathies with a focus on their genetic etiology and diagnostic testing in the postgenomic era.

Cardiac structural and sarcomere genes associated with cardiomyopathy exhibit marked intolerance of genetic variation

BACKGROUND

The clinical significance of variants in genes associated with inherited cardiomyopathies can be difficult to determine because of uncertainty regarding population genetic variation and a surprising amount of tolerance of the genome even to loss-of-function variants. We hypothesized that genes associated with cardiomyopathy might be particularly resistant to the accumulation of genetic variation.

METHODS AND RESULTS

We analyzed the rates of single nucleotide genetic variation in all known genes from the exomes of >5000 individuals from the National Heart, Lung, and Blood Institute's Exome Sequencing Project, as well as the rates of structural variation from the Database of Genomic Variants. Most variants were rare, with over half unique to 1 individual. Cardiomyopathy-associated genes exhibited a rate of nonsense variants, about 96.1% lower than other Mendelian disease genes. We tested the ability of in silico algorithms to distinguish between a set of variants in MYBPC3, MYH7, and TNNT2 with strong evidence for pathogenicity and variants from the Exome Sequencing Project data. Algorithms based on conservation at the nucleotide level (genomic evolutionary rate profiling, PhastCons) did not perform as well as amino acid-level prediction algorithms (Polyphen-2, SIFT). Variants with strong evidence for disease causality were found in the Exome Sequencing Project data at prevalence higher than expected.

CONCLUSIONS

Genes associated with cardiomyopathy carry very low rates of population variation. The existence in population data of variants with strong evidence for pathogenicity suggests that even for Mendelian disease genetics, a probabilistic weighting of multiple variants may be preferred over the single gene causality model.

Identifying disease mutations in genomic medicine settings: current challenges and how to accelerate progress

The pace of exome and genome sequencing is accelerating, with the identification of many new disease-causing mutations in research settings, and it is likely that whole exome or genome sequencing could have a major impact in the clinical arena in the relatively near future. However, the human genomics community is currently facing several challenges, including phenotyping, sample collection, sequencing strategies, bioinformatics analysis, biological validation of variant function, clinical interpretation and validity of variant data, and delivery of genomic information to various constituents. Here we review these challenges and summarize the bottlenecks for the clinical application of exome and genome sequencing, and we discuss ways for moving the field forward. In particular, we urge the need for clinical-grade sample collection, high-quality sequencing data acquisition, digitalized phenotyping, rigorous generation of variant calls, and comprehensive functional annotation of variants. Additionally, we suggest that a 'networking of science' model that encourages much more collaboration and online sharing of medical history, genomic data and biological knowledge, including among research participants and consumers/patients, will help establish causation and penetrance for disease causal variants and genes. As we enter this new era of genomic medicine, we envision that consumer-driven and consumer-oriented efforts will take center stage, thus allowing insights from the human genome project to translate directly back into individualized medicine.