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

摘要 在过去，当临床医生将一群患有类似疾病的人聚集在一起时，就会描绘出新的疾病。 表型特征。然后，他们进行了基因测试，并寻找彼此之间共有的基因变化 受影响的人群。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。 具有相对较少的基因和非常独特的外观。自从外显子组测序出现以来， 医生们越来越意识到与之相关的临床特征的广泛变异性 与之前已知的基因有关，但实际表现可归因于基因变异的程度要大得多 比之前预期的要好--俗称的“冰山效应”。克服这些挑战需要 新方法。而不是从定义的表型开始，我们建议从基因开始，并研究我们的 未来的方向是确定这些遗传变异可能产生的全部表型谱。这样的工作 需要大量良好的表型和基因分型的样本，以及适当的专业知识 评估感兴趣的患者。这个应用程序将两个具有经验和能力的机构聚集在一起 正是为了做到这一点。盖辛格健康系统维护着大量的医疗记录以及基因和序列 登记在MyCode社区健康计划中的超过141,000名参与者的数据，并具有 挖掘这些记录和基因组序列以寻找有意义的和医学上相关的联系的专业知识。 美国国立卫生研究院在罕见疾病的深层表型和发现方面拥有专业知识。为了证明这一原则 基因优先策略奏效了，我们开始分析弹性纤维介导的结缔组织疾病， 这是我们的NIH合作者拥有丰富专业知识的领域。以前的文献将变化与 弹力纤维基因对主动脉内径和弯曲、肺部病变、肺气肿和皮肤的影响 变化包括松懈，最近的工作表明与更常见的表型有关，如 高血压、颅内动脉瘤和慢性阻塞性肺疾病。我们的目标是定义所有 表型，罕见的和常见的，与弹性纤维疾病相关，并通过 这些基因的变异会产生表型，以开发新的治疗策略。为了 为了实现这一目标，我们制定了两个具体目标，结合盖辛格和国家 卫生研究院的调查人员。目标1.a)在未经选择的人群中筛选弹性蛋白和其他 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： 在具有已知和新的弹性纤维损伤变异的患者中识别以前未确定的表型 基因通过深入的表型和疾病模型的体外功能分析。之间的协作 两个机构的不同和多学科团队将增加对弹性纤维影响的了解 并为人类疾病的治疗提供洞察力。

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.