Cardiomyopathy Genomes Project Main

Cardiomyopathy is highly heritable, and cardiomyopathies are classified based on heart morphology with two major forms being dilated and hypertrophic cardiomyopathy (DCM and HCM, respectively). In adult familial cardiomyopathy, the most common form of inheritance is autosomal dominant with variable expressivity and penetrance. Genetic testing now samples >80 genes and identifies a primary mutation in approximately half the cases. With the same single mutation, there is considerable phenotypic variability. This is well seen in families, where all members share the same primary mutation but with differing age of onset and expression. The “missing heritability” for cardiomyopathy may be due to multiple factors, undiscovered primary or “driver” gene mutations and/or an oligogenic genetic mechanism involving the interplay between driver variants and the genomic context in which they are expressed. The genomic context for cardiomyopathy includes genetic modifiers, which are not restricted to coding regions of the genome and likely includes noncoding genetic variation. Genetic modifiers are defined as genetic variants that alter the phenotypic expression of a primary mutation, and identifying these pathways is useful for clinical prognosis and to identify potential pathways around which therapy can be developed. Historically, cardiomyopathy genetic investigations have been restricted to a small fraction of the genome with limited information on the larger genomic signature of heart failure. Whole genome sequencing (WGS) provides a more comprehensive picture of genomic context, including both rare and common variation, that shapes the manifestation of driver variant(s) extending beyond the coding region. In the prior funding interval, we generated and analyzed WGS data coupled with clinical cardiac phenotype information from >300 individuals with cardiomyopathy. As a complement, we also now have WGS data from >1000 individuals from Northwestern’s NUgene Biobank, and these data are linked to clinical data. Analysis of the cardiomyopathy genomes reveals variants in genes regulating cardiac energetics and mitochondrial function as modifiers of HCM and DCM, as we will study this through mechanistic approaches in model organisms and human cell models. We now propose to decipher complex cardiomyopathy genetics by integrating WGS information, epigenetic signatures, and gene expression data. Defining genetic modifiers for cardiomyopathy is expected to provide novel pathways contributing to heart failure.