Exome Sequencing in Familial Cardiovascular Malformations

关于大多数心血管畸形（CVM）的特定病因学，存在知识空白。 这个缺口代表了一个重要的问题，因为除非它得到解决，否则潜在的分子机制将 在很大程度上是不可穿透的。 我们的长期目标是更好地了解潜在的遗传原因， 导致CVM的分子机制。这项R21应用的总体目标是发现基因 变异导致一个亚组的脑血管畸形，左心室流出道（LVOT）畸形， 包括主动脉瓣狭窄、主动脉缩窄和左心发育不良综合征。 存在较大 这些畸形的遗传成分，但很少有易感基因已被确定。 中央 一种假说是，致病基因可以通过高度选择性的全基因组方法来识别， 家族表现出孟德尔遗传模式的LVOT畸形。建议的理由 研究表明，确定LVOT畸形的遗传原因有可能提供更好的风险， 为一组畸形提供咨询，这些畸形导致很大比例的婴儿出生死亡 缺陷 在最近支持这一前提的文献和拥有独特家庭群体的指导下， 中心假设将通过追求一个单一的特定目标来测试，使用基因组分割捕获 所有已知人类基因的外显子的技术，然后对捕获的基因进行大规模平行测序， 目标的这将适用于受影响的个人从四个家系表现出常染色体显性遗传 遗传模式根据现有的变异数据库，将不太可能导致疾病的变异过滤掉 以及可通过计算机获得的个人基因组序列数据。 将使用生物信息学（预测突变 效果、基因表达数据等） 来识别致病变异体 变体将由桑格确认 测序和通过表达测定研究它们的功能作用。 一个更大的群体将被 筛选已鉴定基因的突变。这种做法是创新的。 它将采用新技术， 快速识别多重家庭中的致病基因，绕过以前的全基因组方法， 连锁分析，精细定位和候选基因选择，创造了基因研究方法的范式转变 映射. 此外，还开发了独特的方法来过滤大量的预期数据， 确定可能的因果变量。 该研究具有重要意义，因为它有望垂直 通过识别LVOT畸形的第一个致病基因来推进该领域。这一过程的自然发展 这项工作将导致R01的应用，以研究所确定的变异的分子机制。在 当前胎儿诊断和干预的时代，以及对许多CVM是遗传的理解， 这些知识可以潜在地用于提供更好的家庭风险咨询，新的预防措施， 子宫内早期诊断和靶向治疗。

There is a gap in knowledge regarding the specific etiologies for most cardiovascular malformations (CVMs). This gap represents a significant problem, because until it is solved, the underlying molecular mechanisms will be largely impenetrable. Our long term goal is to better understand the underlying genetic causes and molecular mechanisms leading to CVMs. The overall objective of this R21 application is to discover the genetic variation leading to a subgroup of CVMs, the left ventricular outflow tract (LVOT) malformations that includes aortic valve stenosis, coarctation of the aorta, and hypoplastic left heart syndrome. There is a large genetic component to these malformations, but few susceptibility genes have been identified. The central hypothesis is disease causing genes can be identified by highly selective genome-wide approaches, using families exhibiting Mendelian inheritance patterns for LVOT malformations. The rationale for the proposed research is that identifying the genetic causes of LVOT malformations has the potential to provide better risk counseling for a group of malformations that contribute to a large proportion of infant mortality due to birth defects. Guided by recent literature supporting this premise and possession of a unique cohort of families, the central hypothesis will be tested by pursuing a single specific aim to use genome partitioning capture technology for the exons of all known human genes followed by massively parallel sequencing of the captured targets. This will be applied to affected individuals from four pedigrees exhibiting an autosomal dominant inheritance pattern. Unlikely disease causing variants will be filtered out, based on existing variant databases and publically available personal genome sequence data. Bioinformatics will be used (predicted mutation effect, gene expression data, etc.) to identify the causal variant. Variants will be confirmed by Sanger sequencing and their functional effects investigated by expression assays. A larger cohort will then be screened for mutations in the identified genes. This approach is innovative. It will employ new technology to rapidly identify the causative gene in multiplex families, by-passing previous methods of genome wide linkage analysis, fine mapping, and candidate gene selection, creating a paradigm shift in the approach to gene mapping. In addition, unique methods have been developed to filter the large amount of expected data and identify the likely causal variant. The proposed research is significant because it is expected to vertically advance the field by identifying the first causal genes for LVOT malformations. The natural progression of this work will lead to an R01 application to investigate the molecular mechanisms of the variants identified. In the current era of fetal diagnosis and intervention, as well as the understanding that many CVMs are inherited, this knowledge can potentially be used to provide better family risk counseling, novel preventive measures, early in utero diagnosis, and targeted therapies.