Cardiomyopathy Genomes Project

 描述(由申请人提供)：心力衰竭是住院和死亡的主要原因。自1995年以来，心力衰竭的发病率没有显著下降，反映出其治疗缺乏新的医学发展。因此，开发治疗心力衰竭的新方法是一个巨大的、尚未得到满足的需求。充血性心力衰竭的主要原因之一是心肌病，这是一种具有很高遗传成分的疾病。家族性心肌病的遗传学研究已经确定了70多种不同的基因，当突变时，会导致心肌病和心力衰竭。对心力衰竭和心肌病背后的遗传缺陷的更好的理解为指导临床决策提供了预后信息，并提供了更好的关于心力衰竭的生物学基础的信息。心肌病的基因诊断也可能有助于确定心肌病的亚型，以更好地指导治疗。重要的是，基因诊断为早期发现和早期干预提供了机会。目前的基因诊断策略依赖于基因板，多个基因同时测序，几乎所有这些基因都编码已知的心脏功能蛋白，包括粗丝蛋白和细丝蛋白，以及那些对细胞骨架和核完整性至关重要的蛋白。我们建议对心肌病患者进行全面的基因组测序，以确定心肌病患者存在的致病变异范围。最初的分析将集中在影响基因编码区的罕见变异上，特别是那些被预测会扰乱蛋白质生产的变异。为此，还将对非编码区进行调查，重点是缺失或重复(也称为结构变体)，这些缺失或重复会扰乱已知与心肌病有关的基因的调控区，以及那些影响microRNA和长非编码RNA的基因。来自个体心肌病基因组的数据将通过家庭分离研究进行验证。这个心肌病基因变异的数据库将产生一个公众可用的资源，它将帮助解释临床基因测试，识别已知基因的新突变以及新的 对心肌病很重要的基因。

 DESCRIPTION (provided by applicant): Heart failure is a leading cause of hospitalization and death. Since 1995, there has been no significant decline in heart failure, reflecting the absence of new medical developments for its treatment. Therefore, developing new approaches to heart failure is a large, unmet need. One of the leading causes of congestive heart failure is cardiomyopathy, a disorder with a high heritable component. Genetic studies of familial cardiomyopathy have identified more than 70 different genes that, when mutated, cause cardiomyopathy and heart failure. An improved understanding of the genetic defects that underlie heart failure and cardiomyopathy provides prognostic information to guide clinical decision-making and to provide better information about the biological underpinnings of heart failure. Genetic diagnosis in cardiomyopathy may also help define subclasses of cardiomyopathy to better guide therapy. Importantly, genetic diagnosis affords the opportunity for early detection and early intervention. The current strategy for genetic diagnosis relies on gene panels, where multiple genes are sequenced simultaneously, and nearly all these genes encode proteins are known cardiac function including thick and thin filament proteins and those important for cytoskeletal and nuclear integrity. We propose to conduct comprehensive genome sequencing in cardiomyopathy patients to define the range of pathogenic variation present in subjects with cardiomyopathy. Initial analysis will focus on rare variants that affect the coding regions of genes, especially those that are predicted to disrupt protein production. To this end, noncoding regions will also be surveyed with emphasis on deletions or duplication (also known as structural variants) that disrupt regulatory regions for the genes known to be linked to cardiomyopathy as well as those that affect microRNAs and long noncoding RNAs. Data from individual cardiomyopathy genomes will be verified by family segregation studies. This database of genetic variation in cardiomyopathy will generate a publically available resource that will aid in interpretation of clinical genetic testing, identify new mutations in known genes as well as new genes important for cardiomyopathy.