Genotype-Phenotype Associations in Pediatric Cardiomyopathy (PCM GENES)

Overview

Cardiomyopathy in children is a serious disease which can result in death, disability, heart transplantation or serious heart rhythm disorders. Doctors know little about the causes of cardiomyopathy but would like to learn more. In fact, up to 50-75% of cases in children have no known cause. For this reason, the purpose of this study is to identify genes that cause cardiomyopathy or that influence how people with cardiomyopathy do over time. These findings could improve disease prevention, surveillance, early management, and prognosis.

Pediatric cardiomyopathy is a heterogeneous genetic disease with high morbidity and mortality in which children often present with fulminant disease leading to death or transplant. The long-term goal of this project is to identify the genetic basis of cardiomyopathy and to correlate these findings with clinical phenotypes for risk stratification. These findings could improve disease prevention, surveillance, early management, and prognosis. The specific aims of this study are: 1. To identify the disease-causing and disease-associated genetic variants underlying pediatric cardiomyopathy in a carefully phenotyped cohort. 2. To identify genotype-phenotype correlations that allow for risk stratification and improve management and therapy. Exome sequencing will be used as part of a tiered genetic analysis in a large cohort of up to 700 pediatric cardiomyopathy subjects with systolic (dilated cardiomyopathy) or diastolic (hypertrophic or restrictive cardiomyopathy) dysfunction. The biological parent(s) of enrolled participants will also be approached about participating and providing a blood sample for genetic testing. In addition to the parent(s), the participants siblings and other relatives may also be approached regarding enrollment, based on the pedigree and family history. This study will significantly increase our understanding of pediatric cardiomyopathy by defining the prevalence of mutations in genes known to cause cardiomyopathy as well as identifying novel disease-causing genes in the pediatric population. Genetic association tests will identify variants that modify disease. Novel bioinformatics and systems biology applications for interpretation of exome level genetic information will contribute fundamental knowledge and technical innovation to the translation of genomic data to clinical utility. These aims will provide critical genetic architecture data, identify variants with large effects, and enable genotype-phenotype correlations necessary for advancing management and therapy. The Study will have two components: 1) clinical data collection by chart review and family interview, and 2) biospecimen collection and genetic testing.