Systematically mapping variant effects for cardiovascular genes

系统地绘制心血管基因的变异效应

• 批准号: 10501975
• 负责人: Euan A Ashley
• 金额: $ 208.6万
• 依托单位: VANDERBILT UNIVERSITY MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-08-25 至 2026-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10501975
• 关键词: Amino Acids; Arrhythmia; Atherosclerosis; Atlases; Automobile Driving; Bar Codes; Benign; Biological; Biological Assay; Biology; Calcium; Calmodulin; Cardiac Myocytes; Cardiomyopathies; Cardiopulmonary Resuscitation; Cardiovascular Diseases; Cardiovascular system; Cause of Death; Cell Size; Cells; Cellular Assay; Child; Clinical; Clinical Management; Clustered Regularly Interspaced Short Palindromic Repeats; Collaborations; Communities; DNA; Data; Decision Support Systems; Development; Diagnosis; Disease; Dyslipidemias; Electrocardiogram; Electrophysiology (science); Environmental Risk Factor; Family; Family member; Functional disorder; Gene Frequency; Gene Targeting; Genes; Genetic; Genomic Segment; Genomic medicine; Heart Arrest; Heart Diseases; Heart failure; Human; Immunofluorescence Immunologic; In Situ; Individual; Ion Channel; Letters; Life; Lipoproteins; Low-Density Lipoproteins; Maps; Measures; Medical center; Medicine; Membrane Proteins; Minor; Molecular; Mutagenesis; Nucleotides; Pathogenesis; Pathogenicity; Patients; Performance; Phenotype; Proteins; Publications; Reagent; Research Personnel; Resources; Scientist; Site; Standardization; Surface; System; Tertiary Protein Structure; Testing; Time; Toxin; Uncertainty; Update; Variant; Vascular Diseases; Vision; Zebrafish; aged; base; cardiovascular effects; cell growth; clinical care; clinical diagnosis; cohort; disability; drug development; experience; genetic testing; genetic variant; genome sequencing; genome wide association study; heart rhythm; high throughput screening; improved; in vitro Assay; induced pluripotent stem cell; insight; lipid disorder; machine learning model; novel; patch clamp; protein function; protein structure; public database; rare variant; response; trait; uptake

Cardiovascular diseases are leading global causes of death and disability, presenting as interrelated phenotypes of atherosclerotic vascular disease, heart failure, and arrhythmias. They arise from interactions between environmental factors and common and rare genetic variants, including relatively common Mendelian lipid disorders, cardiomyopathies, and arrhythmias that collectively occur in at least 1/100 individuals. The availability of genetic sequencing is altering clinical management, but a major barrier to the widespread application of this practice is that the function of the vast majority of variants in key cardiovascular disease genes is unknown. Variant effect maps that define function for nearly all missense variants in a target sequence offer a way forward. This project brings together scientists at the forefront of variant effect mapping in diverse cellular systems, illuminating underlying cardiovascular biology, establishing relationships between variant function and human phenotypes, and working with others in multi-institutional collaborations. Our CardioVar team will generate a comprehensive atlas of variant effect maps for key cardiovascular disease genes. In Aim 1, we will develop, optimize, and validate a range of high-throughput cellular assays. We will use a range of generalizable (e.g. surface abundance) and bespoke (e.g. electrophysiological, lipoprotein uptake) assays to directly measure variant function in disease-relevant context. Assays will be assessed by their ability to discriminate pathogenic from benign variants. In Aim 2, we will use in situ targeted mutagenesis or insertion of variant constructs at a safe harbor site to generate pools of cells capturing all single-nucleotide changes in target genes. We will then deploy existing validated assays and those emerging from Aim 1 to generate and validate variant effect maps at scale. Functional scores and uncertainty estimates will be derived and evaluated, both by performance on pathogenic and benign variants and on correlation with discrete and quantitative phenotypes in clinical cohorts. In Aim 3, we will derive biological and clinical insights from variant effect maps. Discordant cases, where variant scores diverge from clinical annotation, will be further investigated in zebrafish, iPSC-cardiomyocytes, and automated patch clamping systems. Through a combination of hypothesis-driven analysis and machine learning models, we will reveal relationships among variant effects, protein structure, protein function, and human phenotypes. To optimize use of the atlas, we will provide a portal serving as a variant-centric decision support system for evaluating functional evidence of pathogenicity. We will release variant effect map data pre- publication via MaveDB (that we co-developed) and share all renewable variant assay reagents. The CardioVar atlas of missense variant effects, covering key cardiovascular disease genes, will be an essential and interpretable community resource for clinical and mechanistic studies of cardiovascular disease.

心血管疾病是全球主要的死亡和残疾原因，表现为相互关联 动脉粥样硬化性血管疾病、心力衰竭和心律失常的表型。它们产生于相互作用 在环境因素和常见和罕见的遗传变异之间，包括相对常见的孟德尔 共同发生在至少1/100个体中的血脂紊乱、心肌病和心律失常。这个 基因测序的可用性正在改变临床管理，但这是普及的主要障碍 这一实践的应用是，绝大多数变异的功能在心血管关键部位 疾病基因尚不清楚。变量效果图，定义目标中几乎所有错义变量的功能 序列提供了一条前进的道路。该项目汇集了处于变化效果映射前沿的科学家 不同的细胞系统，阐明潜在的心血管生物学，建立 不同的功能和人类表型，以及在多机构合作中与他人合作。我们的 心脏变量团队将为主要心血管疾病生成一份全面的不同效应图图谱 疾病基因。 在目标1中，我们将开发、优化和验证一系列高通量细胞分析。我们将使用 可概括的范围(如表面丰度)和定制范围(如电生理、脂蛋白摄取) 在与疾病相关的情况下直接测量变异功能的分析。化验将根据它们的能力进行评估 来区分致病的和良性的变异。 在目标2中，我们将使用原位定向突变或在安全港位置插入变异结构来 生成捕获目标基因中所有单核苷酸变化的细胞库。然后，我们将部署现有的 验证的分析和从目标1产生的那些，以生成和验证规模上的不同效果图。功能性 分数和不确定度估计将根据致病和良性方面的表现来得出和评估。 变异以及与临床队列中离散和定量表型的相关性。 在目标3中，我们将从不同的效应图中获得生物学和临床方面的见解。不和谐的案例，其中 不同的分数与临床注释不同，将在斑马鱼、IPSC-心肌细胞、 和自动膜片钳系统。通过假设驱动的分析和机器的组合 学习模型，我们将揭示各种效应、蛋白质结构、蛋白质功能和人类之间的关系 表型。为了优化地图集的使用，我们将提供一个门户网站，作为以变体为中心的决策支持 用于评价致病性功能证据的系统。我们将提前发布变体效果图数据 通过MaveDB(我们共同开发)发布，并共享所有可更新的变异分析试剂。 涵盖关键心血管疾病基因的心脏变量错义变异效应图谱将是一个 心血管疾病的临床和机制研究的基本和可解释的社区资源。