Background: Cardiomyopathy (CM) is a devastating disease that affects millions in the USA. Like many autosomal dominant diseases CM has highly variable penetrance and expressivity. One genetic mechanism that could account for this is epistasis, wherein multiple variants in the same or different genes act together to modify phenotypes. Interestingly, epistatic variants need not be pathogenic on their own, but may only act to modify existing pathogenic variants in the genome. A corollary to this is that epistatic variants need not be rare or as deleterious to gene function as pathogenic variants. In the past 5 years there have been numerous, independent reports of digenic inheritance in clinical CM cohorts. There have also been a small handful of reports of epistasis in mouse models of CM. However, there are few, if any, published reports testing clinically identified epistatic inheritance in a model system to establish causality, a critical unmet need. Hypothesis: Multiple pathogenic mutations lead to more severe phenotype in CM and seemingly benign variants cause more severe disease in combination with known pathogenic variants.
Specific Aims :
Aim1 : Identify candidate epistatic interactors for CM.
Aim 2 : Functionally test combinations of known, seemingly benign and pathogenic variants. Study design:
Aim1 : We will use an existing algorithm which prioritizes variants for pathogenicity in CM and modify it to permit discovery of epistatic variants in large publicly available cohorts of CM patients and normal populations. We will also sequence and analyze 40 additional patients with CM followed at Rady Children's Hospital.
Aim 2 : Combinations of pathogenic mutations in TTN, MYH7, LDB3 and MYBPC3, known CM genes, will be functionally tested in human induced pluripotent stem cell derived cardiomyocytes. Mutation- induced biochemical structural and functional phenotypes will be examined, representing a range of cardiac phenotypes. Likewise, we will test a specific, seemingly benign mutation in MYBPC3 (p.R326Q) ? a variant enriched in an existing CM cohort and correlated with increased clinical severity ? in the genetic background of known pathogenic mutations in LDB3 and MYBPC3. We will also test the 6 best candidates from Aim 1 in pathogenic backgrounds. The best candidates from the in vitro model will be assessed in a mouse model. Assessment will be performed in the basal state and after cardiac stress via ventricular pressure overload. Clinical Significance: Currently, genetic diagnoses of CM often fail to predict severity or incidence of heart failure, significantly increasing likelihood of death in CM patients. This is driven in part by poor understanding of genetic interactions in CM. This work will alter how some uncommon variants are interpreted in a clinical setting, improving ability to predict phenotype. Further, this work will provide critically needed data to help generate computational models to predict polygenic inheritance and build infrastructure to conduct high- throughput assays to test polygenic inheritance in CM.
Over 1/500 people will be subject to cardiomyopathy with 200,000 new diagnoses a year. Many of those afflicted can die suddenly if undiagnosed. Determining how our genes play a role in cardiomyopathy is important to making diagnoses. This work seeks to better understand how multiple genes work together to increase the severity and risk of getting cardiomyopathy which will help medical professionals give better treatments and advice to patients.
