Discovery and Characterization of Rare Variant Effects in Dilated Cardiomyopathy via Large-Scale Biobank Analysis

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SUMMARY Dilated cardiomyopathy (DCM) affects up to 1:250 individuals and is responsible for ~40% of cardiac transplants. Guidelines recommend genetic testing in DCM probands to help establish diagnosis, guide medical care, inform risk stratification, and identify at-risk relatives. However, causal variants are identified in fewer than half of patients, ~30-40% of tests return variants of uncertain significance (VUS), and a modest number of genes have adequate genotype-phenotype data to inform medical management. In this proposal we address 4 gaps in DCM research: 1) Most data are from individuals of European ancestry referred for genetic testing, creating bias in estimates of the contribution, penetrance, and phenotype in the broader clinical and community population. 2) Most established DCM genes have insufficient genotype-phenotype data to inform gene-specific clinical management. 3) The evidence for most candidate genes is equivocal due to lack of study in cohorts sufficiently large to evaluate pathogenicity. 4) Some disease loci likely remain undiscovered because GWAS and linkage approaches used in prior studies are not well-powered for diseases, such as DCM, with variable age of onset, both high genetic and allelic heterogeneity, and incomplete penetrance. We will address these fundamental knowledge gaps using innovative genetic methods and a novel, large-scale DCM research platform that includes harmonized phenotypic, genotyping, sequencing, and identity-by-descent (IBD) data from 5 large biobanks comprising ~1M participants and >10,000 DCM cases. Specifically, we propose to use rare variant and IBD- based methods to: Aim 1) Define the contribution and phenotypic manifestations of established disease genes in multiple diverse, non-referral DCM populations; Aim 2) Assess the pathogenicity of candidate DCM genes with equivocal evidence and establish a novel platform to evaluate VUS in established genes; and Aim 3: Discover novel DCM genes via IBD mapping and rare variant association within and across biobanks at scale. To balance the innovation of these aims, we present compelling preliminary data demonstrating the feasibility of our approaches which identified a cluster of distantly related individuals harboring a common pathogenic variant in RBM20. We anticipate these analyses will substantially expand our understanding of the genetic factors underlying DCM risk and their clinical manifestations. Once established, our platform will support future clinical and genetic research and advance the long-term goal of implementing targeted interventions at the clinic and population level to reduce the burden of DCM for all patients.