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

摘要 扩张型心肌病(DCM)影响高达1：250的患者，约占心脏移植手术的40%。 指南建议对DCM先证者进行基因检测，以帮助建立诊断、指导医疗保健、告知 风险分层，并确定有风险的亲属。然而，在不到一半的人中发现了因果变异 患者，大约30%-40%的测试返回了不确定意义的变异(VUS)，并且有少量基因 充足的基因型-表型数据，为医疗管理提供信息。在本提案中，我们解决了DCM中的4个差距 研究：1)大多数数据来自欧洲血统的个人，用于基因测试，造成了偏见 在更广泛的临床和社区人群中对贡献、外显率和表型的估计。2) 大多数已建立的扩张型心肌病基因没有足够的基因表型数据来提供基因特异性临床信息。 管理层。3)大多数候选基因的证据是模棱两可的，因为缺乏对队列的充分研究。 大以评估致病性。4)一些疾病位点可能仍未被发现，因为GWAs和连锁 以前的研究中使用的方法对疾病，如扩张型心肌炎，发病年龄不同， 遗传异质性和等位基因异质性高，外显性不完全。我们将解决这些基本问题 使用创新遗传方法的知识差距和一个新颖的大规模DCM研究平台，其中包括 来自5个大型生物库的统一表型、基因分型、测序和血统鉴定(IBD)数据 包括约100万名参与者和10,000个DCM案例。具体地说，我们建议使用稀有变异和IBD- 基于方法：目的1)确定已建立的疾病基因的贡献和表型表现 在多个不同的非转诊DCM人群中；目的2)评估候选DCM基因的致病性 模棱两可的证据，并建立一个新的平台来评估已建立的基因中的VUS；以及目标3：发现 通过IBD定位新的DCM基因，以及生物库内和生物库之间的罕见变异关联。保持平衡 这些目标的创新，我们提供了令人信服的初步数据，证明了我们的 确定一群远亲个体携带一种常见的致病变异体的方法 RBM20。我们预计这些分析将大大扩展我们对遗传因素的理解。 潜在的DCM风险及其临床表现。一旦建立，我们的平台将支持未来的临床 和基因研究，推进在临床和临床实施有针对性的干预的长期目标 人群水平，以减轻所有患者的扩张性心肌病负担。

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.