Arrhythmogenic right ventricular cardiomyopathy (ARVC) is an inherited heart disease that is associated with sudden cardiac death. Clinical symptoms are frequently absent before a sudden death event, so innovative approaches for early detection are needed. Most ARVC cases (60%) are caused by genetic variants in desmosome proteins, so ?genome-first? diagnosis is a promising new paradigm. Yet, current knowledge gaps limit this approach: A) the prevalence and phenotypic effect of ARVC-associated variants in the general population are unknown; and B) sensitive methods are needed for effectively distinguishing sub-clinical disease from non-penetrance for genotype-positive, ?phenotype-negative? (G+/P-) individuals. Geisinger's ?MyCode? Initiative is projected to have 150,000 participants with whole-exome sequencing by the end of 2018 and participant consent for clinical return of actionable findings.
In Aim 1, we will leverage these resources to determine the prevalence of pathogenic and likely pathogenic ARVC genetic variants and the associated phenotypic burden. Findings from MyCode will be compared against other reference populations for a generalizable assessment. Race-specific differences will also be quantified. We will then recruit all MyCode participants confirmed to have pathogenic/likely pathogenic ARVC variants (G+) for prospective clinical and research phenotyping assessments to define: 1) the number of patients satisfying the ARVC Task Force diagnostic criteria and 2) the spectrum of phenotypic manifestations related to ARVC variants. Another important unknown in ARVC is the factor(s) mediating genetic penetrance. Structural deterioration of cardiac desmosome connections through a vigorously active lifestyle is the currently prevailing hypothesis.
In Aim 2, we will confirm this link between exercise and ARVC penetrance in a genome-first population. For individuals enrolled in Aim 1, we will collect a detailed history of past and present exercise/athletic participation to test the hypotheses that a) an ARVC phenotype in G+ subjects is dependent on a history of athletic activity; and b) development of incident symptoms during follow-up is associated with a vigorously active lifestyle. Finally, the genome-first paradigm requires new diagnostic methods to help distinguish non-penetrance from ?concealed? disease.
In Aim 3, we will use advanced MRI techniques to look for evidence of subtle changes in cardiac structure and function in ARVC G+ patients which could be suggestive of disease. These techniques include 3D myocardial strain measurement and high-resolution imaging of myocardial fat and fibrosis. These advanced techniques have enhanced sensitivity compared with existing clinical methods, and are better suited to evaluate the RV. We will acquire these MRI data in ARVC G+ patients and matched controls to test the hypotheses that 3D bi-ventricular myocardial strains and myocardial fat/fibrosis are abnormal in ARVC G+ patients. Completion of these aims will provide critical and immediate advances in our understanding of ARVC, and provide a foundation for longitudinal studies to evaluate the clinical utility of this precision medicine approach.

Public Health Relevance

Arrhythmogenic right ventricular cardiomyopathy (ARVC) is a degenerative heart disease responsible for 20% of sudden cardiac death in individuals under age 35. Screening genomic data for ARVC risk factors is a novel approach to disease diagnosis, which may help prevent sudden cardiac death. This proposal seeks to define critical evidence and effective strategies for this precision medicine approach, such as evaluating the prevalence and penetrance of genetic risk factors for ARVC in a large clinical cohort, and exploring the use of advanced medical imaging techniques to detect early signs of disease.

Agency
National Institute of Health (NIH)
Institute
National Heart, Lung, and Blood Institute (NHLBI)
Type
Research Project (R01)
Project #
5R01HL141901-03
Application #
10071196
Study Section
Cancer, Heart, and Sleep Epidemiology A Study Section (CHSA)
Program Officer
Shi, Yang
Project Start
2019-01-19
Project End
2023-12-31
Budget Start
2021-01-01
Budget End
2021-12-31
Support Year
3
Fiscal Year
2021
Total Cost
Indirect Cost
Name
Geisinger Clinic
Department
Type
DUNS #
079161360
City
Danville
State
PA
Country
United States
Zip Code
17822