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

总结 在过去，当临床医生将一组具有相似症状的个体聚集在一起时， 表型特征然后，他们进行了基因测试，并寻找共享的基因变化， 受影响的群体。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 基因相对较少，呈现高度独特。自从外显子组测序出现以来， 医生已经越来越意识到与这些疾病相关的临床特征的广泛的可变性 与以前已知的基因，与实际表现归因于遗传变异要大得多 比之前预期的要多--众所周知的“冰山效应”。克服这些挑战需要 新方法我们建议从基因开始，而不是从定义的表型开始， 这是一个前进的方向，以确定可能由这些遗传变异引起的全谱表型。这种工作 需要大量良好的表型和基因型样本，以及适当的专业知识， 评估感兴趣的患者。这一应用程序汇集了两个机构的经验和能力， 去做这件事。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名参与者的数据参加了MyCode社区健康计划， 专家们挖掘这些记录和基因组序列，以获得有意义的和医学相关的关联。 NIH在罕见疾病的深层表型和发现方面具有专业知识。为了证明这一原则， 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。以前的文献将变化与 弹性纤维基因与主动脉直径和迂曲度的缺陷、肺气肿和皮肤等肺部变化有关 变化包括松弛，最近的研究表明与更常见的表型有关， 高血压、颅内动脉瘤和慢性阻塞性肺病。我们的目标是定义所有 表型，罕见的和常见的，与弹性纤维疾病，并探讨机制， 这些基因中的变异产生表型，以便开发新的治疗策略。为了 为了实现这一目标，我们制定了两个具体的目标，结合Geisinger和National的优势， 卫生研究院的调查员。目标1。A）针对弹性蛋白和其他蛋白质中的变体筛选一个人的群体。 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。目标二： 在弹性纤维中存在已知和新型损伤性变异的患者中鉴定先前未鉴定的表型 基因通过深度表型和疾病建模体外功能分析。协作 两个机构的多元化和多学科的团队将增加对弹性纤维的影响的理解 疾病，并提供导致治疗人类疾病的见解。

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.