Exome Sequencing in Familial Cardiovascular Malformations

对于大多数心血管畸形(CVM)的具体病因，人们的认识还存在差距。 这一差距代表着一个重大问题，因为在它得到解决之前，潜在的分子机制将 很大程度上是无法穿透的。我们的长期目标是更好地了解潜在的遗传原因和 导致CMS的分子机制。此R21应用程序的总体目标是发现基因 导致CVM亚群的变异，左室流出道(LVOT)畸形 包括主动脉瓣狭窄、主动脉缩窄和左心发育不全综合征。有一个很大的 这些畸形的遗传成分很少，但几乎没有发现易感基因。中环 假设致病基因可以通过高度选择性的全基因组方法识别，使用 左心室流出道畸形表现为孟德尔遗传模式的家系。建议的理由是 研究表明，确定左心室流出道畸形的遗传原因有可能提供更好的风险 为一组导致婴儿出生死亡的很大比例的畸形提供咨询 缺陷。根据最近支持这一前提的文献和拥有独特的家庭队列， 中心假说将通过追求单一的特定目标来检验，即使用基因组分割捕获 对所有已知人类基因的外显子进行大规模并行测序的技术 目标。这将适用于来自四个表现常染色体显性遗传的家系的受影响个体。 继承模式。基于现有的变异数据库，不太可能导致疾病的变异将被过滤掉 和公开可用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)以确定因果变量。变种将由桑格确认 通过表达分析研究其测序及其功能效应。届时将有一个更大的队列 对识别出的基因进行突变筛选。这种方法是创新的。它将采用新技术来 绕过以前的全基因组方法，快速鉴定多个家族中的致病基因 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预期数据和 找出可能的因果变量。这项拟议的研究具有重要意义，因为预计它将垂直 通过识别第一个导致左心室流出道畸形的致病基因来推进这一领域。这一过程的自然发展 这项工作将导致R01的应用，以研究已确定的变种的分子机制。在 当今的胎儿诊断和干预时代，以及对许多CVM是遗传的认识， 这种知识可能被用来提供更好的家庭风险咨询、新的预防措施、 早期宫内诊断和靶向治疗。

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.