Genomic Studies in Charcot-Marie-Tooth Disease

项目总结 各种形式的Charcot-Marie-Tooth病(CMT)由一组遗传异质性的 周围神经病。目前已经确定了90种不同的CMT基因；然而，对于轴突CMT2 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，在识别这些基因中的大约一半方面取得了前所未有的速度。我们一直在 在这一发展的前沿，在过去的七年中公布了22个以上的新基因鉴定。这 只有通过广泛的国内和国际合作、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%的轴索性CMT患者仍然没有得到诊断，指向更多的基因；然而，我们的初步研究 数据还支持非编码变异作为孟德尔等位基因贡献者的存在。在这笔赠款中，我们将 继续我们在CMT家族招募、外显子组测序和传统基因方面的高效工作 身份证明。此外，我们将把基因研究扩展到全基因组测序，重点是 家族已经在整个外显性研究中进行了探索，但都没有成功。我们还计划表演第一个大型稀有 罕见疾病CMT2的变异负荷分析--这只可能是通过特殊的临床 我们在过去十年中积累的资源。最后，有了许多CMT基因，我们将执行 在CMT-OME上进行统计网络分析以确定基因模块和通路将是开始 多药理学观点，并提供对周围神经退行性变的病理生理学的洞察。所有数据 将实时提供给世界各地现有的CMT调查人员网络，并存放在DBGaP中 每年一次。 好了！

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. !