Genomic Studies in Charcot-Marie-Tooth Disease
腓骨肌萎缩症的基因组研究
基本信息
- 批准号:9027884
- 负责人:
- 金额:$ 57.76万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2012
- 资助国家:美国
- 起止时间:2012-05-01 至 2020-01-31
- 项目状态:已结题
- 来源:
- 关键词:AffectAfferent NeuronsAmericanAnimal ModelAustraliaAxonal NeuropathyBiological ModelsBrazilCLIA certifiedCell Culture TechniquesCharcot-Marie-Tooth DiseaseChromosome MappingClinicClinicalClinical ResearchClinical TrialsCodeCollectionComplexCopy Number PolymorphismCountryDNADataDatabasesDegenerative DisorderDevelopmentDiabetic NeuropathiesDiseaseEuropeExonsFamilyFoundationsFunctional disorderFundingFutureGenesGeneticGenetic ScreeningGenetic VariationGenetic screening methodGenomic approachGenomicsGenotypeGrantHaplotypesHeadHereditary Motor and Sensory-Neuropathy Type IIHigh-Throughput Nucleotide SequencingHispanicsHospitalsHousingHumanInborn Genetic DiseasesIndividualInheritedInstitutesInternationalKnowledgeLaboratoriesLeadLondonMammalian CellMedicalMedical GeneticsMedicareMethodsModelingMolecularMolecular ModelsMotor Neuron DiseaseMotor NeuronsNational Institute of Neurological Disorders and StrokeNeurologistNeurologyNeuromuscular DiseasesNeuropathyPMP22 genePathway interactionsPatientsPeripheral NervesPeripheral Nervous System DiseasesPharmaceutical PreparationsProteinsProxyPublishingRare DiseasesRecording of previous eventsRegistriesReportingResourcesRunningSamplingSiteSocietiesTechnologyTestingTherapeuticTherapeutic InterventionTimeTrustVariantYeastsZebrafishabstractingaxonal degenerationbasebiological systemsclinical research sitecostcost efficientdesigndisease registryexomeexome sequencingfollow-upgenetic linkage analysisgenetic pedigreegenetic variantgenome sequencinggenomic variationhereditary neuropathyimprovedin vitro Modelindexinginnovationinsightmembermolecular modelingnext generation sequencingnovelrepositorysample collectionscreeningsuccesswhole genomeyeast genetics
项目摘要
DESCRIPTION (provided by applicant): Approximately 20 million Americans develop peripheral neuropathy with annual costs to Medicare alone in excess of $3.5 billion. These diseases are poorly understood and therapeutic options are limited to non- existent. The hereditary forms of peripheral neuropathies present a unique window of opportunity to identify and dissect the key genes and pathways. In fact, these hereditary neuropathies, known as Charcot-Marie- Tooth disease (CMT), represent the most common inherited disorders in Neurology with 1/2500 individuals affected. Despite impressive success in gene identification in CMT, only ~30% of the genetic causes have been identified for the arguably most important, axonal subtype. Classic methods for gene identification, which depend on large pedigrees, become increasingly ineffective to resolve this problem. New high- throughput sequencing technology is now available that permits for the efficient analysis of whole genomes or highly informative proxies thereof, such as the exome, the entire collection of coding exons. Under the lead of Dr. Zuchner, Director of the Center for Human Molecular Genomics at the state-of-the-art Hussman Institute for Human Genomics, we have recently published the first exome sequencing study of a multigenerational pedigree and the first exome study on CMT and have now published several new genes identified with this method. We fully expect that this technology will add tremendously to resolving causative genes in relatively small CMT families not suitable for classic linkage analysis. The second PI of this proposal, Dr. Michael Shy, is Director of the largest CMT Clinic in the country as well as the PI of the NINDS/ORD funded Rare Disease Clinical Research Center (RDCRC) for genetic neuropathies and the MDA/CMTA funded North American Database and the North American CMT Network. Consequently, we have access to CMT patients throughout the world and propose in this grant a bold approach involving the application of high- throughput genomic technologies that will lead to the discovery of a considerable number of genes in a few years time. In addition we are pursuing genetic results with an innovative functional design in multiple biological systems, yeast, zebrafish, mammalian cell culture, that lend themselves to higher throughput studies. We have assembled an interdisciplinary team of clinicians, molecular and statistical geneticists, bioinformaticians, and molecular biologists to successfully apply these highly complex technologies. All data will be made available to publicly accessible databases laying the foundation for a future genomic repository for peripheral neuropathies. It is only by identifying the genetic causes of CMT that we will be able to study the function of encoded proteins and develop rational approaches to therapeutic intervention. Importantly, related axonal neuropathies, such as diabetic neuropathy, drug-induced neuropathies and degenerative diseases of motor and sensory neurons will greatly benefit from the results of such studies.
描述(由申请人提供):大约 2000 万美国人患有周围神经病,仅医疗保险每年的费用就超过 35 亿美元。人们对这些疾病知之甚少,治疗选择也仅限于不存在。周围神经病的遗传形式为识别和剖析关键基因和通路提供了独特的机会之窗。事实上,这些遗传性神经病,称为腓骨肌萎缩症 (CMT),是神经病学中最常见的遗传性疾病,有 1/2500 人受到影响。尽管 CMT 基因鉴定取得了令人印象深刻的成功,但对于可以说是最重要的轴突亚型,只有约 30% 的遗传原因被确定。依赖于大谱系的经典基因鉴定方法对于解决这个问题变得越来越无效。现在可以使用新的高通量测序技术,可以有效分析整个基因组或其信息丰富的代理,例如外显子组,即编码外显子的整个集合。在最先进的胡斯曼人类基因组学研究所人类分子基因组学中心主任 Zuchner 博士的领导下,我们最近发表了第一个多代谱系的外显子组测序研究和第一个关于CMT 现已发表了用这种方法鉴定的几个新基因。我们完全期望这项技术将极大地解决不适合经典连锁分析的相对较小的 CMT 家族中的致病基因。该提案的第二位 PI 博士 Michael Shy 是该国最大的 CMT 诊所的主任,也是 NINDS/ORD 资助的遗传性神经病罕见病临床研究中心 (RDCRC) 和 MDA/CMTA 资助的 PI北美数据库和北美 CMT 网络。因此,我们可以接触到世界各地的 CMT 患者,并在这笔赠款中提出了一种大胆的方法,涉及应用高通量基因组技术,这将导致在几年内发现大量基因。此外,我们还在酵母、斑马鱼、哺乳动物细胞培养等多种生物系统中通过创新的功能设计追求遗传结果,这有助于更高通量的研究。我们组建了一支由临床医生、分子和统计遗传学家、生物信息学家和分子生物学家组成的跨学科团队,成功应用这些高度复杂的技术。所有数据都将提供给可公开访问的数据库,为未来周围神经病基因组存储库奠定基础。只有通过确定 CMT 的遗传原因,我们才能够研究编码蛋白的功能并开发合理的治疗干预方法。重要的是,相关的轴突神经病变,如糖尿病神经病变、药物引起的神经病变以及运动和感觉神经元的退行性疾病将极大地受益于此类研究的结果。
项目成果
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MICHAEL E. SHY其他文献
MICHAEL E. SHY的其他文献
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{{ truncateString('MICHAEL E. SHY', 18)}}的其他基金
Natural History Studies on the Inherited Neuropathies
遗传性神经病的自然史研究
- 批准号:
8918094 - 财政年份:2014
- 资助金额:
$ 57.76万 - 项目类别:
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10456930 - 财政年份:2009
- 资助金额:
$ 57.76万 - 项目类别:
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