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Common and Rare Genetic Factors in an Ethnically Homogeneous Schizophrenia Cohort

Common and Rare Genetic Factors in an Ethnically Homogeneous Schizophrenia Cohort
种族同质精神分裂症队列中常见和罕见的遗传因素
批准号:
7855944
负责人:
TODD LENCZ
金额:
$200.18万
依托单位国家:
美国
项目类别:
财政年份:
2009
资助国家:
美国
项目状态:
已结题
起止时间:
2009-09-30 至 2011-08-31

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项目成果

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中文摘要
翻译
描述(由申请人提供):精神分裂症(SZ)具有高遗传率(~80%)和高兄弟姐妹复发率(;s ~ 10)的特点,但易感基因的鉴定极具挑战性。这份申请的标题是“种族同质精神分裂症队列中的常见和罕见遗传因素”,是对NIMH精神疾病基因组图谱重大机会领域的回应。在该提案中,我们的目标是在一个大型(n=4000)德系犹太人精神分裂症患者和匹配良好的德系犹太人对照中进行全基因组关联研究(GWAS),随后进行广泛的下一代重测序(Illumina/Solexa技术)。所有的DNA已经被收集,并立即准备进行基因分型。阿什肯纳兹犹太人来自有限数量的创始人,可能丰富了一组常见和/或罕见的易感等位基因,因此可能比以前的研究发现的优势比更高。来自私人捐助者的匹配资金将允许高质量的GWAS以大大降低NIH的成本进行。GWAS将使用新的Illumina HumanOmni1-Quad BeadChip,它可能允许识别新的风险变异(包括拷贝数变异和来自1000基因组计划的罕见变异),这些变异在前几代DNA微阵列中是无法获得的。除了强大的标准GWAS分析之外,GWAS数据将使用一种新颖的单倍型共享方法进行分析。这种方法的目的是识别在病例染色体中选择性共享的扩展单倍型,并且可能包含作为显性或隐性风险等位基因的罕见变异。然后使用Illumina(以前的Solexa) GA2平台通过靶向重测序来询问共享单倍型。将常见变异+罕见变异的混合范式应用于SZ的研究,这一概念范式已被证明在多种生物医学疾病和数量性状的其他几种复杂疾病中取得了成功。综上所述,我们相信,在一个大的、有良好特征的、种族同质的人群中,这种双重方法将提供关于这种毁灭性和致残疾病遗传结构中常见和罕见变异作用的信息数据,并为未来对这一独特人群的研究提供宝贵的国家资源。提议的样本将对精神病学GWAS联盟的持续努力做出重大贡献,PI是该联盟的成员,该联盟将作为结果复制和验证的来源。
英文摘要
DESCRIPTION (provided by applicant): Schizophrenia (SZ) is characterized by high heritability (~80%) and elevated sibling recurrence (;s ~ 10), yet the identification of susceptibility genes has proven extremely challenging. This application entitled "Common and Rare Genetic Factors in an Ethnically Homogeneous Schizophrenia Cohort" is in response to the NIMH Grand Opportunity area Genomic Profiling of Mental Disorders. In this proposal, we aim to perform a genomewide association study (GWAS), followed by extensive next-generation resequencing (Illumina/Solexa technology), in a large (n=4000) cohort of Ashkenazi Jewish patients with schizophrenia and well-matched Ashkenazi controls. All DNA has already been collected and is immediately ready for genotyping. The Ashkenazi Jewish population, derived from a limited number of founders, may be enriched for a subset of common and/or rare susceptibility alleles, which may therefore have higher odds ratios than those detected by previous studies. Matching funds from private donors will permit high-quality GWAS to be performed at substantially reduced cost to NIH. GWAS will use the new Illumina HumanOmni1-Quad BeadChip, which may permit identification of novel risk variants (including copy number variants and rare variants derived from the 1000 Genomes Project) that have been inaccessible in prior generations of DNA microarrays. In addition to well-powered standard GWAS analysis, GWAS data will be analyzed using a novel haplotype sharing approach. This approach aims to identify extended haplotypes that are shared selectively in case chromosomes, and which may harbor rare variants acting as dominant or recessive risk alleles. Shared haplotypes will then be interrogated by targeted resequencing using the Illumina (formerly Solexa) GA2 platform. The application of a hybrid common+rare variant paradigm to the study of SZ applies a conceptual paradigm that has proven successful in several other complex disorders across multiple biomedical diseases and quantitative traits. Taken together, we believe that this dual approach in a large, well characterized, and ethnically homogenous population will provide informative data on the role of common and rare variants in the genetic architecture of this devastating and disabling disorder, as well as provide an invaluable national resource for future studies of this unique population. The proposed sample will contribute substantially to the ongoing efforts of the Psychiatric GWAS Consortium, of which the PI is a member, and which will serve as a source for replication and validation of results. PUBLIC HEALTH RELEVANCE: Schizophrenia (SZ) constitutes the fifth leading cause of disability in the US. Although strongly heritable, specific genetic risk factors remain unclear. We aim to use state-of-the-art genotyping and resequencing technology in a large, ethnically homogeneous cohort of SZ cases and controls. Findings will create new opportunities for diagnosis and prediction of schizophrenia, and for understanding its biology.
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