Identification of Novel Variants And Genes Causing Thoracic Aortic Disease

导致胸主动脉疾病的新变异和基因的鉴定

• 批准号: 10733412
• 负责人: Bulat A. Ziganshin
• 金额: $ 5.02万
• 依托单位: COLUMBIA UNIVERSITY HEALTH SCIENCES
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10733412
• 关键词: Affect; Aneurysm; Aorta; Aortic Aneurysm; Aortic Diseases; Aortic Segment; Applied Skills; Atherosclerosis; Candidate Disease Gene; Cause of Death; Cells; Cessation of life; Classification; Clinical; Clinical Data; DNA; DNA Sequence Alteration; DNA sequencing; Data; Descending aorta; Development; Disease; Dissection; Embryo; Etiology; Family; Family member; Frequencies; Gene Expression; Gene Expression Profile; Genes; Genetic; Genetic Diseases; Genetic Predisposition to Disease; Genomic medicine; Genomics; Human Genetics; Individual; MYLK gene; Medical; Mus; Mutation; Natural History; Operative Surgical Procedures; Pathogenicity; Patients; Population Control; Prognosis; Public Health; Reporting; Risk; Role; Rupture; Sampling; Statistical Data Interpretation; Statistical Methods; Surgical Management; Susceptibility Gene; Testing; Thoracic Aortic Aneurysm; Thoracic aorta; Training; United States; Variant; ascending aorta; bioinformatics pipeline; candidate identification; case control; cell type; clinical phenotype; clinical sequencing; cohort; diagnostic accuracy; differential expression; exome sequencing; gene discovery; genetic analysis; genetic predictors; genetic testing; genetic variant; genomic data; human old age (65+); improved; in silico; innovation; molecular subtypes; novel; personalized care; precision medicine; prevent; programs; repaired; risk variant; segregation; single-cell RNA sequencing; transcriptome sequencing; transcriptomics; variant of unknown significance

PROJECT SUMMARY/ABSTRACT IDENTIFICATION OF NOVEL VARIANTS AND GENES CAUSING THORACIC AORTIC DISEASE Aortic diseases are among the top 20 causes of death in the US. Thoracic aortic aneurysms are rarely symptomatic and often not detected until they dissect or rupture. One fifth of all cases of thoracic aortic aneurysm and dissection (TAAD) are familial, and 20-30% of these are associated with a known, germline genetic variant. The other 70-80% may be due to genes not yet identified. Identifying disease-causing variants and novel risk genes is important for preventing aortic-related complications or deaths by identifying at risk family members. In preliminary studies, we conducted exome sequencing in 303 TAAD patients and identified pathogenic variants in genes known to cause TAAD in 3% of patients and variants of uncertain significance (VUS) in 26%. We hypothesize that: (1) Many of our identified VUS are disease-causing pathogenic variants and many other new pathogenic variants in known TAAD risk genes are likely to be discovered, and (2) There are additional novel genes causing TAAD in our cohort. The aims of the study are to: (1) Identify potential pathogenic variants in known or candidate TAAD risk genes by integrating genomic and clinical data; (2) Characterize cell-type specific gene expression patterns in the normal developing mouse ascending aorta; (3) Identify novel TAAD risk genes through case-control association of rare damaging variants and integrative analysis of genetic and transcriptomic data and characterize clinical phenotypes of patients carrying mutations in novel risk genes. For this project, DNA samples for a total of 1507 patients with TAAD have been collected and are currently undergoing exome sequencing. We will use novel in silico predictors of pathogenicity and family segregation studies to assess variants in known TAAD risk genes. To identify novel TAAD risk genes, we will use statistical methods to integrate case-control association of rare damaging variants with gene expression data. In particular, we will quantify gene expression through bulk and single cell RNA-seq of developing ascending aorta in E15.5 mice, and then identify cell types associated with TAAD by analysis of known and candidate genes with cell-type specific expression. In parallel, we will compare cases with a large set of population controls with comparable exome sequencing data in case-control association analysis. Finally, we will use expression level in relevant cell types to further improve the power and sensitivity of risk gene identification, with the hypothesis that true risk genes are highly expressed in one or multiple cell types relevant to the disease. For novel candidate risk genes, we will characterize the clinical phenotypes of patients who carry damaging variants in these genes. This study will provide training in human genetics, computational genomics, and precision medicine to gain expertise in analyzing large-scale genomic data derived from DNA- and RNA-sequencing and will apply these skills to identify novel disease- causing genes for thoracic aortic aneurysms.

项目概要/摘要 导致胸主动脉疾病的新变异和基因的鉴定 主动脉疾病是美国 20 大死因之一。胸主动脉瘤很少见 有症状，通常直到它们被解剖或破裂才被发现。占所有胸主动脉瘤病例的五分之一 和解剖 (TAAD) 是家族性的，其中 20-30% 与已知的种系遗传变异有关。 另外70-80%可能是由于尚未确定的基因造成的。识别致病变异和新风险 基因对于通过识别高危家庭成员来预防主动脉相关并发症或死亡非常重要。在 初步研究，我们对 303 名 TAAD 患者进行了外显子组测序并鉴定了致病变异 3% 的患者存在已知导致 TAAD 的基因，26% 的患者存在显着性不确定 (VUS) 的变异。我们 假设：（1）我们发现的许多 VUS 是致病性致病变异和许多其他新的致病变异 已知 TAAD 风险基因的致病性变异很可能被发现，并且 (2) 还有其他新的变异 在我们的队列中导致 TAAD 的基因。该研究的目的是：（1）识别潜在的致病变异 通过整合基因组和临床数据已知或候选 TAAD 风险基因； (2) 表征细胞类型特异性 正常发育的小鼠升主动脉中的基因表达模式； (3) 识别新的TAAD风险基因 通过罕见破坏性变异的病例对照关联以及遗传和转录组学的综合分析 数据并表征携带新风险基因突变的患者的临床表型。对于这个项目， 总共1507名TAAD患者的DNA样本已经收集完毕，目前正在接受外显子组检测 测序。我们将使用致病性和家族隔离研究的新型计算机预测因子来评估 已知 TAAD 风险基因的变异。为了识别新的 TAAD 风险基因，我们将使用统计方法来整合 罕见破坏性变异与基因表达数据的病例对照关联。特别是，我们将量化基因 通过 E15.5 小鼠发育中的升主动脉的批量和单细胞 RNA-seq 进行表达，然后鉴定 通过分析具有细胞类型特异性表达的已知基因和候选基因，确定与 TAAD 相关的细胞类型。在 同时，我们将使用具有可比外显子组测序数据的大量群体对照来比较病例 在病例对照关联分析中。最后，我们将利用相关细胞类型中的表达水平来进一步提高 风险基因识别的力量和敏感性，假设真正的风险基因高度表达 与疾病相关的一种或多种细胞类型。对于新的候选风险基因，我们将表征 携带这些基因破坏性变异的患者的临床表型。这项研究将提供培训 人类遗传学、计算基因组学和精准医学，以获得大规模分析的专业知识 来自 DNA 和 RNA 测序的基因组数据将应用这些技能来识别新的疾病 导致胸主动脉瘤的基因。