Genomic Studies in Charcot-Marie-Tooth Disease

项目摘要 各种形式的腓骨肌萎缩症（CMT）包括一组遗传异质性的 周围神经病变目前，已经鉴定了超过90种不同的CMT基因;然而，对于轴突CMT 2， 这些基因只能解释30-40%的遗传效应。尤其是外显子组测序的应用 在过去的五年里，已经以前所未有的速度确定了大约一半的基因。我们一直 在过去的七年里，有22多个新的基因鉴定发表在这一发展的最前沿。这 只有通过广泛的国家和国际合作、数据共享和 开发先进的分析工具和方法。我们还了解到，尽管外显子组测序， 50%的轴突型CMT患者仍未确诊，这表明有更多的基因;然而，我们的初步研究表明， 数据也支持非编码变异作为孟德尔等位基因贡献者的存在。在这份协议中，我们 继续我们在CMT家族招募、外显子组测序和传统基因测序方面的高影响力工作 识别.此外，我们将把基因研究扩展到全基因组测序，重点是 在全外显子组研究中已经探索了不成功的家族。我们还计划进行第一次大型罕见的 罕见疾病CMT 2中的变异负荷分析-这仅可能通过特殊的临床试验来实现。 我们在过去十年中建立的资源。最后，有了许多可用的CMT基因，我们将执行 对CMT-ome进行统计网络分析，以确定基因模块和途径， 点的多药理学和提供洞察周围神经变性的病理生理学。所有数据 将实时提供给全球现有的CMT调查员网络，并存入dbGAP 每年。 !

PROJECT SUMMARY The various forms of Charcot-Marie-Tooth disease (CMT) comprise a genetically heterogeneous set of peripheral neuropathies. Currently >90 different CMT genes have been identified; yet, for the axonal CMT2 subtype these genes explain only 30-40% of the genetic effect. Especially the application of exome sequencing has led to an unprecedented pace in identifying about half of those genes in the past five years. We have been at the forefront of this development with 22+ published new gene identifications in the past seven years. This success was only possible through broad national and international collaborations, data sharing, and the development of advanced analysis tools and methods. We also learned that despite exome sequencing, over 50% of axonal CMT patients remain undiagnosed pointing towards even more genes; however, our preliminary data also support the existence of non- coding variation as Mendelian allele contributor. In this grant we will continue our highly impactful work in CMT family recruitment, exome sequencing and traditional gene identification. In addition, we will expand the genetic studies to whole genome sequencing with a focus on families already explored unsuccessfully in whole exome studies. We further plan to perform the first large rare variant burden analysis in the rare disorder CMT2 – this is only possibly through the exceptional clinical resources we have built over the past decade. Finally, with many CMT genes available, we will perform statistical network analyses on a CMT-ome to identify gene modules and pathways that will be the starting point of polypharmacology and provide insight into pathophysiology of peripheral nerve degeneration. All data will be available in real-time to an existing network of CMT investigators worldwide, and deposited in dbGAP annually. !