Characterization of the genetic architecture of dilated cardiomyopathy using families and cohorts

Cardiomyopathies are the leading cause of heart transplantation in the developed world, and dilated cardiomyopathy accounts for an important proportion of all heart failure cases in large clinical trials. In spite of a strong genetic basis for dilated cardiomyopathy being demonstrated widely in the past two decades, 60% of familial cases remain unexplained. Dilated cardiomyopathy is characterized by marked genetic heterogeneity, with more than 60 individual genes reported to cause the disease, yet only one (TTN) explaining more than 10% of cases. Here, high-throughput sequencing data, advanced imaging techniques and bioinformatics analyses were used to dissect the genetic architecture of dilated cardiomyopathy, by measuring the contribution of single genes and multi-genic variation on disease risk and severity, and performing gene and variant discovery in affected families. Burden testing (using bespoke software developed in the R programming language for this study) and regression modelling were used to examine the genetic determinants of disease by comparing a cohort of disease cases (n=332) to ethnically matched, phenotypically characterised healthy controls (n=319). This produced a measure of the contribution of each gene to dilated cardiomyopathy, taking into account the background variation rate in the general population. Analyses of multi-genic interactions were also performed, and having detected the signature of additive effects of variation in multiple genes on both disease likelihood and severity, further analyses were performed to identify specific gene-gene interactions in causing dilated cardiomyopathy. Subsequently, variant prioritisation strategies were developed to identify, from whole-exome sequencing data, possible genetic causes of an unexplained and very severe form of early-onset dilated cardiomyopathy segregating in a family. This led to the identification of new candidate genes, which might contribute towards a genetic diagnosis in the analysed family and to new insights into the pathogenesis of dilated cardiomyopathy. Preparatory work in developing variant prioritisation pipelines from whole-exome sequencing data had been performed earlier, on families affected with various inherited arrhythmia syndromes.