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.

心血管疾病是全球死亡和残疾的主要原因，以相互关联为 动脉粥样硬化血管疾病，心力衰竭和心律不齐的表型。它们来自互动 在环境因素与常见和稀有遗传变异之间，包括相对常见的孟德尔人 脂质疾病，心肌病和心律不齐，至少在1/100个个体中发生。这 遗传测序的可用性正在改变临床管理，但是广泛的主要障碍 这种做法的应用是，钥匙心血管中绝大多数变体的功能 疾病基因尚不清楚。定义目标中所有错义变体功能的变体效应图 序列提供了前进的方向。该项目将科学家汇集到了变体效应映射的最前沿 各种细胞系统，阐明了潜在的心血管生物学，建立了关系 变体功能和人类表型，并与其他人合作进行多机构合作。我们的 Cardiovar团队将为钥匙心血管生成一个全面的变体效应图图地图集 疾病基因。 在AIM 1中，我们将开发，优化和验证一系列高通量细胞分析。我们将使用一个 可推广（例如表面丰度）和定制范围（例如电生理，脂蛋白摄取） 在与疾病有关的情况下直接测量变异功能的测定。测定将根据其能力进行评估 将致病性与良性变体区分开。 在AIM 2中，我们将使用原位靶向诱变或在安全港地点插入变体构造 生成捕获目标基因中所有单核苷酸变化的细胞池。然后，我们将部署现有 经过验证的测定和从AIM 1出现的测定法以生成和验证变异效应图表。功能 分数和不确定性估计将得出和评估，无论是通过致病性和良性表现 变体以及与临床队列中离散和定量表型的相关性。 在AIM 3中，我们将从变异效应图中得出生物学和临床见解。不一致的情况，哪里 斑马鱼，IPSC-核腺癌细胞，将进一步研究与临床注释不同的变异评分。 和自动补丁夹具系统。通过假设驱动的分析和机器的结合 学习模型，我们将揭示变异效应，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，作为以各种为中心的决策支持 评估致病性功能证据的系统。我们将发布变体效果图数据预先 通过MavedB（我们共同开发）出版，并共享所有可再生变体测定试剂。 错义变体效应的心脏瓦尔图集，涵盖关键心血管疾病基因，将是一个 对于心血管疾病的临床和机理研究，必需的和可解释的社区资源。