High-throughput cellular genetics to connect noncoding variants to coronary artery disease genes

高通量细胞遗传学将非编码变异与冠状动脉疾病基因连接起来

• 批准号: 10659996
• 负责人: JESSE M ENGREITZ
• 金额: $ 68.66万
• 依托单位: BROAD INSTITUTE, INC.
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-04-01 至 2027-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10659996
• 关键词: Acceleration; Address; Affect; Atherosclerosis; Biological; Biological Assay; Blood Pressure; Blood Vessels; Cardiovascular system; Cause of Death; Cell physiology; Cells; Cellular Assay; Cellular Morphology; Cessation of life; Cholesterol; Chromosome Mapping; Complex; Computing Methodologies; Coronary Arteriosclerosis; Data; Data Set; Development; Disease; Distal; Endothelial Cells; Endothelin-1; Enhancers; Genes; Genetic; Genetic Diseases; Genetic Transcription; Genetic study; Goals; Guide RNA; Heritability; Human; Hyperlipidemia; Hypertension; Inflammatory; Link; Maps; Measures; Methodology; Methods; Molecular; Morphology; Paint; Pathway interactions; Phenotype; Physiological; Process; Rest; Risk; Signal Pathway; Stimulus; Technology; Testing; Time; United States; Untranslated RNA; Variant; Vascular Endothelial Cell; Vasoconstrictor Agents; Work; biological adaptation to stress; blood pressure control; causal variant; cell type; computational pipelines; cytokine; data integration; disorder risk; effective therapy; epigenomics; experimental study; genetic variant; genome wide association study; genomic locus; human disease; in situ sequencing; insight; invention; novel; oxidized low density lipoprotein; prevent; programs; shear stress; transcriptome; transcriptomics

ABSTRACT Despite effective therapies to control blood pressure and cholesterol, coronary artery disease (CAD) remains the leading cause of death in the United States and the world. Recent genome-wide association studies (GWAS) have identified >200 genetic loci significantly associated with CAD. The majority of these loci are not associated with hypertension or hyperlipidemia, but contain genes expressed in vascular cells, suggesting the presence of undiscovered CAD disease mechanisms operating through cells of the blood vessel wall. Identifying the biologic mechanisms of these loci is difficult because most of the common variants associated with CAD are non-coding, likely functioning through enhancers that can regulate multiple genes at great distances, and be highly cell-type specific. This has slowed discovery, so that only a few such loci have been ‘solved’, preventing the realization of the full potential of genetic studies for the development of much needed new classes of therapies for CAD. What is needed are much higher-throughput, unbiased methods to systematically dissect these loci, to identify molecular and cellular mechanisms of disease. To accomplish this goal, we have developed and validated two novel high-throughput approaches with the ability to quantify the molecular and morphological effects of thousands of genes in CAD loci: optimized Perturb-seq (to link genes to transcriptional phenotypes) and pooled perturbation Cell Painting (to link genes to morphological effects). We propose to use these technologies, together with new and novel computational approaches, to: 1) analyze the transcriptomic effects of perturbing CAD-locus genes in vascular endothelial cells (ECs) subjected to four stimuli associated with atherosclerosis, 2) quantify the morphological effects of perturbing all CAD-locus genes in ECs, 3) integrate these data with epigenomic and genetic data to nominate causal genes and build hypotheses connecting variants to genes, and genes to disease-associated cellular phenotypes, and then test the top 5 of each of these hypotheses using variant-editing and EC-functional assays. This includes several prioritized causal variant hypotheses that regulate EC shear stress response upstream of KLF2 expression. The completion of these studies will accelerate understanding of the links between CAD genetics and disease, and provide insights into EC functions in CAD that may inform the development of new classes of therapies. More broadly, this study will establish new scalable experimental and computational methods to link noncoding disease variants to genes and cellular phenotypes, which could dramatically accelerate variant-to-function studies for cardiovascular and other common diseases.

抽象的 尽管有效控制血压和胆固醇的疗法，但冠状动脉疾病（CAD）仍然存在 美国和世界的死亡主要原因。最近全基因组关联研究（GWAS） 已经鉴定出> 200个遗传基因座与CAD显着相关。这些基因座中的大多数无关 高血压或高脂血症，但包含在血管细胞中表达的基因，表明存在 通过血管壁细胞运行的未发现的CAD疾病机制。识别生物学 这些基因座的机制很困难，因为与CAD相关的大多数常见变体都是非编码的， 可能通过增强子功能来调节多个基因，并且是高度细胞类型的 具体的。这已经放慢了发现，因此只有少数这样的本地被“解决”，从而阻止了实现 遗传研究的全部潜力是开发急需的CAD疗法的新疗法。 需要的是系统地剖析这些局部的高通量，公正的方法，以识别 疾病的分子和细胞机制。为了实现这一目标，我们已经开发并验证了两个 新型的高通量方法具有量化分子和形态效应的能力 CAD基因座中的数千个基因：优化的wisturb-seq（将基因与转录表型联系起来）并合并 扰动细胞绘画（将基因与形态效应联系起来）。 我们建议将这些技术与新的和新颖的计算方法一起使用：1）分析 在血管内皮细胞（EC）中扰动CAD-固定基因的转录组作用。 与动脉粥样硬化相关的刺激，2）量化所有CAD-locus基因的形态学效应 在ECS中，3）将这些数据与表观基因组和遗传数据集成在一起，以提名毒素基因并构建假设 将变体连接到基因，以及基因与疾病相关的细胞表型，然后测试前5个 这些假设中的每一个都使用变体编辑和EC功能测定法。这包括几个优先级催化 变体假设调节KLF2表达上游的EC剪切应力反应。 这些研究的完成将加速对CAD遗传学与疾病之间的联系， 并提供有关CAD中EC功能的见解，这些功能可能会为新的疗法的发展提供信息。 更广泛地，这项研究将建立新的可扩展实验和计算方法来链接非编码 基因和细胞表型的疾病变异，可以显着加速变异到功能 心血管和其他常见疾病的研究。