Genetics of Parkinsonism

帕金森病的遗传学

基本信息

项目摘要

DESCRIPTION (provided by applicant): The University of Miami Udall center continues its focus on identifying genes important to causing Parkinson Disease (PD). As common variant polymorphisms (CV) have failed to explain a large amount of the genetic contribution to PD risk. Project one uses DNA capture technology and Next generation sequencing (NGS) to look for rare variants (RV) and mutations (M) in 500 patients and 500 controls. 809 genes from multiple data sources will be sequenced. Seventy of these genes are mitochondrial genes that will be used in Project 2. Subsequent genes containing potential RV will be sequenced in a second independent dataset of 500 patients and 500 controls, and aggregate analysis performed to see which RV are significantly associated with PD. It also uses a whole exome capture approach (180K exons) with NGS to identify M in six extended pedigree families with PD. Project 2 focuses on complex I of the mitochondria, using a new method called Mito-Seq to isolate mtDNA in brains of PD and controls for deletions, somatic mutations and heteroplasmy. We hypothesize that RV or de novo changes in nuclear encoded complex I genes are a risk factor for idiopathic PD directly, or through causing abnormal interaction between complex I's many components. The same brain tissue samples will be examined for protein modifications, and integrity of respiratory chain super-complexes using innovative proteomic and biochemical assays. Combining all data will allow for comparative studies of the pathology in PD brains. Project 3 examines the genetics of essential tremor (ET). To identify novel genes associated with ET, and study their potential influence on developing PD, we will 1) Identify novel ET loci by a genome wide linkage screen of the twelve largest ET kindreds; 2) Genetically and physically map ET candidate gene regions using recombination breakpoint and haplotype analysis to refine the Minimal Candidate Regions (MCR); 3) Identify positional candidate genes within each MCR and screen for causative disease mutations using NGS 4) Test confirmed ET genes in our full ET data set. The Center has four cores: Core A =administrative. Core B =clinical and neuropathology. Core C =statistical analysis and bioinformatics. Core D = education and training. PROJECT 1 Principal Investigator: Jeffery M. Vance Title: Discovery of Rare Variants and Mutations in Parkinson Disease Description (provided by applicant): Genetic studies have been a major tool fueling the tremendous growth in PD research over the last 10 years. Project 1 builds on our very successful work, 50 publications, 60 abstracts over the last funding period, examining the effect of common variants (CV) (polymorphisms) in PD. Table 1 shows the three primary types of genetic variations that contribute to disease risk. Genome wide association studies (GWAS) have focused on exploring the contribution of CV to disease susceptibility. While the traditional definition of CV is a minor allele frequency (MAF) > 1% in the population, in practice, GWAS and association studies have only looked at CV with a MAF>5%. So we have defined CV for this proposal as those variants with MAF> 5%. The individual contribution to disease risk (odds ratios) per CV is small. Therefore, it is the accumulation of CV associated with PD that affects the overall risk for PD in an individual. One of the first descriptions of rare variants (RV) came from (1) who suggested that "subtle or unconventional mutations in cancer predisposition genes" may contribute to the increased risk of cancer observed in family members of cancer patients. Cohen et al (2) suggested that "variants are likely to be rare individually; they may be sufficiently common in aggregate (in a gene) to contribute to variation in common traits in the population". RV can be considered genetic variations that often present with mildly deleterious effects on protein function. Their effect on gene and protein function is thought to lie between that of CV and those severely deleterious mutations (M). Recent estimates (3) suggest that 53% of de novo missense mutations fall within this RV category. This would be high enough to ensure their continued presence in the population, and would support their presence as a significant explanation for the genetic contributions of common disease. Indeed, Bodmer and Bonilla (4) in a recent review of RV suggest that 1/3 of the population attributable risk for complex disease may come from RV. Indeed, several examples of RV are already known in PD (5,6). Mutations are the rarest of DNA changes, and functionally cause PD by themselves. These are the changes that we refer to as Mendelian (autosomal recessive, autosomal dominant, or X-linked). Mutations are well known in PD as well (7). Identifying CV for association has been very successful. Six GWAS studies have now been reported for PD. However, only SNCA and MAPT have had highly significant association with PD across all of the studies. (8-13). Therefore, there is increasing realization that CV alone are not responsible for the genetic contribution to risk for PD and many other complex disorders. (14-17). This strongly suggests that the other categories of DNA variation in Table 1 must have a substantial contribution to PD. As RV can only be seen by sequencing (Table 1) it is only with the availability of an established target enrichment technology that captures specific DNA sequences for "next-generation" sequencers (NGS), that we can search for RV/M on a large scale. Large versions of this same approach have lead to whole exome sequencing, i.e. providing sequence on 180,000 exons in each individual (18-20). We will use both of these approaches in this project. The resulting sequence data and RV/M from this project will be used by both Projects 1 and 2. For cost and efficiency, we have included the 70 mitochondrial genes of project 2 in the initial sequencing of project 1. However, follow-up on these genes will occur in project 2. In addition, genes identified by project 3 will be incorporated in subsequent DNA captures of project 1. The project will be administrated by Core A. and all individuals for sequencing will be obtained from Core B. The considerable statistical and bioinformatic analyses will be done in conjunction with Core C. Laboratory opportunities for Neurology residents and clinical experience for Project 1 laboratory personnel will be given through Cores B and D.
描述(由申请人提供):迈阿密大学尤德尔中心继续致力于鉴定对引起帕金森病 (PD) 很重要的基因。由于常见的变异多态性 (CV) 未能解释遗传对帕金森病风险的大部分影响。项目一使用 DNA 捕获技术和下一代测序 (NGS) 在 500 名患者和 500 名对照者中寻找罕见变异 (RV) 和突变 (M)。来自多个数据源的 809 个基因将被测序。其中 70 个基因是线粒体基因,将在项目 2 中使用。包含潜在 RV 的后续基因将在包含 500 名患者和 500 名对照的第二个独立数据集中进行测序,并进行聚合分析以了解哪些 RV 与 PD 显着相关。它还使用全外显子组捕获方法(180K 外显子)和 NGS 来识别 6 个患有 PD 的大谱系家族中的 M。项目 2 重点关注线粒体复合体 I,使用一种名为 Mito-Seq 的新方法分离 PD 大脑中的 mtDNA,并控制缺失、体细胞突变和异质性。我们假设 RV 或核编码复合物 I 基因的从头变化直接或通过引起复合物 I 的许多组件之间的异常相互作用是特发性 PD 的危险因素。将使用创新的蛋白质组学和生化检测方法检查相同的脑组织样本的蛋白质修饰和呼吸链超级复合物的完整性。结合所有数据将有助于对帕金森病大脑的病理学进行比较研究。项目 3 检查特发性震颤 (ET) 的遗传学。为了识别与 ET 相关的新基因,并研究它们对发生 PD 的潜在影响,我们将 1) 通过十二个最大 ET 家族的全基因组连锁筛选来识别新的 ET 位点; 2) 使用重组断点和单倍型分析对 ET 候选基因区域进行遗传和物理图谱,以细化最小候选区域 (MCR); 3) 识别每个 MCR 中的位置候选基因,并使用 NGS 筛选致病突变 4) 在我们的完整 ET 数据集中测试确认的 ET 基因。该中心有四个核心: 核心 A = 行政。核心 B =临床和神经病理学。核心C=统计分析和生物信息学。核心 D = 教育和培训。 项目1 首席研究员:Jeffery M. Vance 标题:帕金森病罕见变异和突变的发现 描述(由申请人提供):过去 10 年来,遗传学研究一直是推动 PD 研究巨大增长的主要工具。 项目 1 以我们非常成功的工作为基础,在上一个资助期间发表了 50 篇出版物、60 篇摘要,研究了 PD 中常见变异 (CV)(多态性)的影响。表 1 显示了导致疾病风险的三种主要遗传变异类型。全基因组关联研究 (GWAS) 的重点是探索 CV 对疾病易感性的影响。虽然 CV 的传统定义是人群中次要等位基因频率 (MAF) > 1%,但实际上,GWAS 和关联研究仅关注 MAF > 5% 的 CV。因此,我们将此提案的 CV 定义为 MAF > 5% 的变体。每个 CV 对疾病风险(比值比)的个体贡献很小。因此,与 PD 相关的 CV 积累会影响个体患 PD 的总体风险。 对罕见变异 (RV) 的最早描述之一来自 (1),他提出“癌症易感基因中的微妙或非常规突变”可能导致癌症患者家庭成员中观察到的癌症风险增加。 Cohen 等人 (2) 认为“个体变异可能很罕见;它们在总体上(在基因中)可能足够常见,从而导致群体中常见性状的变异”。 RV 可以被认为是遗传变异,通常会对蛋白质功能产生轻微的有害影响。它们对基因和蛋白质功能的影响被认为介于 CV 和那些严重有害的突变 (M) 之间。最近的估计 (3) 表明 53% 的从头错义突变属于这一 RV 类别。这将足以确保它们在人群中持续存在,并支持它们的存在作为常见疾病遗传贡献的重要解释。事实上,Bodmer 和 Bonilla (4) 在最近的 RV 综述中表明,1/3 的人口复杂疾病风险可能来自 RV。事实上,PD 中已知有几个 RV 的例子 (5,6)。突变是最罕见的 DNA 变化,从功能上来说,突变本身会导致帕金森病。这些变化我们称为孟德尔遗传(常染色体隐性遗传、常染色体显性遗传或 X 连锁)。帕金森病中的突变也是众所周知的 (7)。 为协会确定简历非常成功。目前已有六项针对 PD 的 GWAS 研究报告。然而,在所有研究中,只有 SNCA 和 MAPT 与 PD 具有高度显着的相关性。 (8-13)。因此,人们越来越多地认识到,遗传因素对帕金森病和许多其他复杂疾病的风险的影响并不是仅由心血管因素造成的。 (14-17)。这强烈表明表 1 中其他类别的 DNA 变异必定对 PD 有重大贡献。由于 RV 只能通过测序看到(表 1),因此只有使用既定的目标富集技术来捕获“下一代”测序仪 (NGS) 的特定 DNA 序列,我们才能在规模大。这种相同方法的大型版本导致了全外显子组测序,即提供每个个体 (18-20) 180,000 个外显子的序列。我们将在这个项目中使用这两种方法。 该项目所得的序列数据和 RV/M 将被项目 1 和 2 使用。出于成本和效率考虑,我们已将项目 2 的 70 个线粒体基因纳入项目 1 的初始测序中。但是,后续工作这些基因将出现在项目 2 中。此外,项目 3 鉴定的基因将纳入项目 1 的后续 DNA 捕获中。该项目将由 Core A 管理,所有用于测序的个体将从 Core B 获得。统计和生物信息分析将与核心 C 一起进行。神经科住院医师的实验室机会和项目 1 实验室人员的临床经验将通过核心 B 和 D 提供。

项目成果

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JEFFERY Marvin VANCE其他文献

JEFFERY Marvin VANCE的其他文献

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{{ truncateString('JEFFERY Marvin VANCE', 18)}}的其他基金

Summer Research Experience in Biological and Computational Sciences
生物和计算科学暑期研究经历
  • 批准号:
    9212963
  • 财政年份:
    2014
  • 资助金额:
    $ 4.74万
  • 项目类别:
Summer Research Experience in Biological and Computational Sciences
生物和计算科学暑期研究经历
  • 批准号:
    8830703
  • 财政年份:
    2014
  • 资助金额:
    $ 4.74万
  • 项目类别:
Summer Research Experience in Biological and Computational Sciences
生物和计算科学暑期研究经历
  • 批准号:
    10319999
  • 财政年份:
    2014
  • 资助金额:
    $ 4.74万
  • 项目类别:
Summer Research Experience in Biological and Computational Sciences
生物和计算科学暑期研究经历
  • 批准号:
    9920446
  • 财政年份:
    2014
  • 资助金额:
    $ 4.74万
  • 项目类别:
Summer Research Experience in Biological and Computational Sciences
生物和计算科学暑期研究经历
  • 批准号:
    10084322
  • 财政年份:
    2014
  • 资助金额:
    $ 4.74万
  • 项目类别:
Identification of Rare Variants in PD through Whole Exome Sequencing
通过全外显子组测序鉴定 PD 罕见变异
  • 批准号:
    8540540
  • 财政年份:
    2012
  • 资助金额:
    $ 4.74万
  • 项目类别:
Identification of Rare Variants in PD through Whole Exome Sequencing
通过全外显子组测序鉴定 PD 罕见变异
  • 批准号:
    8264601
  • 财政年份:
    2011
  • 资助金额:
    $ 4.74万
  • 项目类别:
Genetics of Parkonsonism
帕金森症的遗传学
  • 批准号:
    8263842
  • 财政年份:
    2010
  • 资助金额:
    $ 4.74万
  • 项目类别:
Genetics of Parkinsonism
帕金森病的遗传学
  • 批准号:
    8005830
  • 财政年份:
    2010
  • 资助金额:
    $ 4.74万
  • 项目类别:
Genetics of Parkonsonism
帕金森症的遗传学
  • 批准号:
    8540539
  • 财政年份:
    2010
  • 资助金额:
    $ 4.74万
  • 项目类别:

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