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

通过大规模生物库分析发现和表征扩张型心肌病的罕见变异效应

• 批准号: 10682290
• 负责人: Jennifer Below
• 金额: $ 76.92万
• 依托单位: VANDERBILT UNIVERSITY MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-05-15 至 2027-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10682290
• 关键词: Address; Affect; Age; Age of Onset; Alleles; Arrhythmia; Candidate Disease Gene; Cardiac; Cardiology; Caring; Clinic; Clinical; Clinical Management; Clinical Research; Communities; DNA; Data; Data Set; Diagnosis; Dilated Cardiomyopathy; Disease; Distant; England; Equilibrium; European ancestry; Future; Genes; Genetic; Genetic Research; Genetic Variation; Genomic Segment; Genomics; Genotype; Goals; Guidelines; Heart Transplantation; Heritability; Heterogeneity; Human Genetics; Individual; Informatics; Intervention; Knowledge; Link; Literature; Maps; Medical; Medical Genetics; Methods; Participant; Pathogenicity; Patient Care; Patients; Penetrance; Phenotype; Population; Recommendation; Relative Risks; Reporting; Research; Resources; Risk; Sample Size; Site; Testing; Uncertainty; Variant; Work; barrier to care; biobank; candidate identification; causal variant; clinical effect; clinically significant; cohort; data harmonization; defined contribution; exome sequencing; genetic testing; genome wide association study; identity by descent; improved; innovation; novel; personalized care; personalized screening; phenome; phenotypic data; proband; rare variant; risk stratification; risk variant; screening; trait; variant detection; variant of unknown significance

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.

总结 扩张型心肌病（DCM）影响高达1：250的个体，约占心脏移植的40%。 指南建议在DCM先证者中进行基因检测，以帮助建立诊断，指导医疗护理， 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， 大约30-40%的测试返回不确定意义的变异（VUS），并且少量基因具有 充分的基因型-表型数据，以告知医疗管理。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体，用于基因检测， 在更广泛的临床和社区人群中的贡献、转化率和表型的估计。（二） 大多数已建立的DCM基因没有足够的基因型-表型数据来告知基因特异性临床诊断。 管理3)由于缺乏足够的队列研究，大多数候选基因的证据是模棱两可的 以评估致病性。4)一些疾病位点可能仍然未被发现，因为GWAS和连锁 在先前研究中使用的方法对于疾病，例如DCM，具有不同的发病年龄， 高遗传和等位基因异质性和不完全多态性。我们将解决这些基本问题。 利用创新的遗传方法和一个新的、大规模的DCM研究平台， 来自5个大型生物库的统一表型、基因分型、测序和血统鉴别（IBD）数据 包括约1 M参与者和> 10，000个DCM病例。具体来说，我们建议使用罕见变异和IBD- 目的1）定义已建立的疾病基因的贡献和表型表现 在多种多样的非转诊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，以评估VUS在已建立的基因;和目标3：发现 新的DCM基因通过IBD映射和罕见的变异关联内和跨生物库的规模。平衡 这些目标的创新，我们提出了令人信服的初步数据证明我们的可行性， 这些方法确定了一组具有共同致病性变异的远亲个体， 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 和遗传研究，并推进在诊所实施有针对性的干预措施的长期目标， 人群水平，以减轻所有患者的DCM负担。