Collaborative Research to Explore Genetic Variation and Phenotypic Spectrum of Elastin and Related Genes

探索弹性蛋白及相关基因的遗传变异和表型谱的合作研究

基本信息

批准号：
10368060
负责人：
Beth A Kozel
金额：
$ 66.99万
依托单位：
GEISINGER CLINIC
依托单位国家：
美国
项目类别：
财政年份：
2020
资助国家：
美国
起止时间：
2020-03-20 至 2025-02-28
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10368060
关键词：
Address Affect Aneurysm Aortic Valve Stenosis Area Awareness Basic Science Biological Blood Vessels C-terminal Caliber Case Study Cell Line Characteristics Chronic Obstructive Pulmonary Disease Clinical Clinical Data Clinical Research Code Collaborations Communities Community Health Connective Tissue Connective Tissue Diseases Cutis Laxa Data Defect Diagnosis Disease Disease model Doctor of Philosophy Elastic Fiber Elastic Tissue Elastin Electronic Health Record Enrollment Ensure Extramural Activities FBLN5 gene Family Family history of Fibroblasts Frequencies Functional disorder General Population Genes Genetic Genetic Variation Genetic study Genomic medicine Genomics Genotype Goals Health Health system Human Hypertension Iceberg In Vitro Individual Institute of Medicine (U.S.)Institution Intracranial Aneurysm Investigation Laboratories Lead Leadership Learning Link Literature Lung Lung diseases Mediating Medical Medical Records Methods Mining Mutation Online Mendelian Inheritance In Man Participant Pathogenicity Patients Penetrance Phenotype Physicians Population Protein-Lysine 6-Oxidase Proteins Publishing Pulmonary Emphysema Rare Diseases Recording of previous events Records Research Research Personnel Research Project Grants Sampling Skin Stretching Tissues Translational Research Translations United States National Institutes of Health Variant Work arterial tortuosity base burden of illness clinical application clinical center clinical phenotype clinically relevant cohort electronic structure exome exome sequencing experience fibulin-4 genetic pedigree genetic testing genetic variant genomic data human disease improved in vitro Model individual patient induced pluripotent stem cell innovation insight interest multidisciplinary novel novel strategies phenotypic data population based premature profiles in patients protein structure function rare variant success text searching treatment strategy

项目摘要

Summary In the past, new diseases were delineated when clinicians brought together a cohort of individuals with similar phenotypic characteristics. They then performed genetic testing and looked for shared genetic changes among the affected cohort. While this method proved successful in some cases, discovery was limited to disorders with relatively few genes and highly distinctive presentation. Since the advent of exome sequencing, physicians have become increasingly aware of the wide spectrum of variability of clinical features associated with previously known genes, with the actual manifestations attributable to a genetic variation being far greater than what was previously anticipated--the proverbial, “iceberg effect.” Overcoming these challenges requires a new approach. Instead of starting with the defined phenotype, we propose starting at the gene and working our way forward to identify the full spectrum of phenotypes that can arise from these genetic variations. Such work requires high numbers of well-phenotyped and genotyped samples, as well as the expertise to appropriately evaluate patients of interest. This application brings together two institutions with the experience and capability to do just that. The Geisinger Health System maintains extensive medical records and genotype and sequence data on more than 141,000 participants enrolled in the MyCode Community Health Initiative and has the expertise to mine those records and genomic sequences for meaningful and medically relevant associations. The NIH has expertise in the deep phenotyping and discovery in rare disease. For proof of principle that this gene-first strategy works, we are beginning our analysis into elastic fiber mediated connective tissue disease, an area with which our NIH collaborators have significant expertise. Previous literature linked changes in elastic fiber genes to defects in aortic diameter and tortuosity, lung changes such as emphysema and skin changes including laxity with more recent work suggesting connections to more common phenotypes such as hypertension, intracranial aneurysm, and chronic obstructive pulmonary disease. Our goal is to define all phenotypes, rare and common, associated with elastic fiber disease and to investigate the mechanism by which variation in these genes produces phenotypes in order to develop novel treatment strategies. In order to achieve this goal, we have developed two specific aims combining the strengths of Geisinger and the National Institutes of Health investigators. Aim 1. A) Screen an unselected population for variants in elastin and other elastic fiber genes and B) correlate with phenotypic features mined from the electronic health record. Aim 2: Identify previously unidentified phenotypes in patients with known and novel damaging variants in elastic fiber genes through deep phenotyping and disease modeling in vitro functional analysis. Collaboration between the two institution's diverse and multidisciplinary teams will increase understanding about the impact of elastic fiber disease and provide insight leading to treatment of human disease.

概括过去，当忠诚者将一群具有相似症状的人聚集在一起时，就会描述出新的疾病。然后，他们进行了基因测试并寻找共同的基因变化。虽然这种方法在某些情况下被证明是成功的，但发现仅限于疾病。自从外显子组测序出现以来，具有相对较少的基因和高度独特的表现。医生越来越意识到相关临床特征的广泛变异性与先前已知的基因相比，由于遗传变异而导致的实际表现要大得多超出之前的预期——众所周知的“冰山效应”。我们建议从基因开始并研究我们的新方法，而不是从定义的表型开始。确定这些遗传变异可能产生的全部表型的前进方向。需要大量表型和基因型良好的样本，以及适当的专业知识该应用程序汇集了两个具有经验和能力的机构。盖辛格卫生系统保存着大量的医疗记录以及基因型和序列。超过 141,000 名参加 MyCode 社区健康计划的参与者的数据，并具有挖掘这些记录和基因组序列的专业知识，以获得有意义的和医学相关的关联。 NIH 在罕见疾病的深度表型分析和发现方面拥有专业知识，以证明这一点。基因优先策略有效，我们开始分析弹性纤维介导的结缔组织疾病，我们的 NIH 合作者在这一领域拥有丰富的专业知识，之前的文献将这一领域的变化联系起来。弹性纤维基因导致主动脉直径和迂曲度缺陷、肺变化（例如肺气肿和皮肤）包括松懈在内的变化，最近的工作表明与更常见的表型有联系，例如我们的目标是定义所有高血压、颅内动脉瘤和慢性阻塞性肺病。罕见和常见的表型与弹性纤维疾病相关，并通过以下方法研究其机制这些基因的变异会产生表型，以便开发新的治疗策略。为了实现这一目标，我们结合 Geisinger 和 National 的优势制定了两个具体目标健康研究所研究人员的目标 1. A) 筛查未选择的人群中弹性蛋白和其他物质的变异。弹性纤维基因和 B) 与从电子健康记录中挖掘的表型特征相关。目标 2：识别具有已知和新型弹性纤维破坏性变异的患者中先前未识别的表型通过深度表型分析和疾病模型体外功能分析来分析基因。两个机构的多元化和多学科团队将加深对弹性纤维影响的了解疾病并为治疗人类疾病提供见解。