2/2-A Large-Scale Schizophrenia Association Study in Sweden
2/2-A Large-Scale Schizophrenia Association Study in Sweden
批准号:
8531354
负责人:
PAMELA SKLAR
金额:
$44.09万
依托单位国家:
美国
项目类别:
财政年份:
2012
资助国家:
美国
项目状态:
已结题
起止时间:
2012-08-15 至 2015-07-31
关键词:
AgeArchitectureBioinformaticsBiological AssayBirthCandidate Disease GeneClinicalCodeCognitiveCollaborationsComplexCraniocerebral TraumaDataDatabasesDetectionDiseaseElementsEnvironmentEnvironmental Risk FactorEpidemiologyEvaluationFrequenciesFundingGenerationsGenesGeneticGenetic PolymorphismGenetic RiskGenetic VariationGenomeGenomicsGenotypeGoalsGrantHumanInstitutesInsulin-Dependent Diabetes MellitusInternationalInvestmentsKnowledgeLeadLearningLiteratureMeta-AnalysisModelingNational Institute of Mental HealthNatureOutcomePaperPathway interactionsQuality ControlRiskRisk FactorsRoleRuralSNP genotypingSamplingSampling StudiesSchizophreniaSiteSocietiesSwedenUnited States National Institutes of HealthVariantWorkbasecase controlcostdesigndisorder riskexomeexome sequencinggenome wide association studygenome-wideimprovednovelsample collectionseason of birthsuccesstrait
中文摘要
描述(由申请人提供):这是R01 MH077139竞争性续期的第二次也是最后一次提交,R01 MH077139是瑞典的一项大规模精神分裂症相关研究。这个项目非常成功,所有目标都已实现,甚至超过了目标。我们成功地确定了我们得到资助的病例和对照的数量(总共12996例)。我们对大约一半的样本进行了GWAS,而不是对候选基因进行基因分型。这些数据是两篇国际精神分裂症联盟自然论文的关键组成部分,也是精神病学GWAS联盟精神分裂症大分析的相当一部分。最后,我们的瑞典样本被用于NIH拨款的两个“重大机会”(外显子组测序和全基因组甲基组学)。我们在这里提出新的目标,利用这个独特的样本来增加我们对SCZ的了解,并保持这个高效团队的完整。这里研究的样本将使SCZ的可用样本增加61%,这将大大增强检测具有风险或保护作用的网络和位点的能力。在目标1中,我们将完成12996名受试者(5851例SCZ病例,7145例对照)的全样本基因组特征。这包括对所有受试者进行GWAS基因分型和新型Illumina“外显子组芯片”,以及对1000例病例和1000例对照进行外显子组测序。所有的化验都由慈善机构资助。我们要求资金支持我们的团队进行严格的质量控制、估算和数据仓库。在目标2中,我们将进行旨在阐明赋予SCZ风险或保护的遗传效应的分析。(2a)通路和网络分析:通过严格评估经典和新型经验通路中基因的较小p值是否丰富了基因组结果,确定SCZ的其他高置信度通路。¿(2b)对SCZ的外显子组多态性进行第一次高功率的基因组规模分析。这种新型外显子组芯片是由Illumina和Broad的同事开发的,可以捕获MAF为0.1%的错义和无义编码变异,以及MAF为0.01-0.1%的很大一部分。这可以识别低频错义或无义多态性,有助于SCZ。(2c)分析瑞典数据中直接基因分型和输入的常见变异,并与PGC SCZ结果进行meta分析。根据需要进行验证型基因分型。预期结果:10-20个新基因座的全基因组显著证据。(2d)识别导致SCZ的结构变异。对CNPs、索引、新插入和其他结构多态性进行首次系统评估。评估CNV与SCZ的关系,并结合外部结果进行meta分析。根据需要进行验证型基因分型。预期结果:增加对主要CNV位点的理解,以及新结构变异的作用。在目标3中,估计高置信度的遗传效应是否被确定的SCZ流行病学危险因素所改变。对于这种复杂的性状,环境风险通常可能与因果遗传变异相互作用。对于Aim 2的结果,如果流行病学风险因素建模,遗传效应是增强还是减弱?风险因素来自高质量的数据库,通常进行前瞻性评估(出生季节、城市/农村出生、父亲和祖父母年龄、病前认知水平和头部创伤)。预期结果:了解特定的遗传和环境风险因素如何在SCZ中相互作用,这可能导致新的机制假设。我们的目标是迅速更多地了解精神分裂症的遗传学,以及基因和环境如何相互作用以改变疾病风险。我们建议使用该领域最大和最全面的研究样本收集来做到这一点,其中包括遗传和环境风险因素。
英文摘要
DESCRIPTION (provided by applicant): This is the second and final submission of the competitive renewal of R01 MH077139, A Large-Scale Schizophrenia Association Study in Sweden. This project has been very successful with all aims accomplished and, indeed, exceeded. We successfully ascertained the numbers of cases and controls for which we were funded (N~12,996 in total). Instead of candidate gene genotyping, we conducted GWAS on around half the sample. These data were key components in two International Schizophrenia Consortium Nature papers and are a sizable fraction of the Psychiatric GWAS Consortium schizophrenia mega-analysis. Finally, our Swedish sample is being used for two "grand opportunity" NIH grants (exome sequencing and genome-wide methylomics). We propose here new aims that use this unique sample to increase our knowledge of SCZ and to keep this highly productive team intact. The samples studied here will increase available samples for SCZ by 61% which will provide substantially enhanced power for detection of networks and loci that confer risk or protection. In Aim 1, we will complete the genomic characterization of the full sample of 12,996 subjects (5,851 SCZ cases, 7,145 controls). This includes GWAS genotyping and a novel Illumina "exome chip" on all subjects plus exome sequencing on 1,000 cases and 1,000 controls. All assays are funded by philanthropy. We request funds for our team to conduct rigorous quality control, imputation, and data warehousing. In Aim 2, we will conduct analyses designed to elucidate genetic effects that confer risk or protection for SCZ. ¿ (2a) Pathway and network analyses: identify additional high-confidence pathways for SCZ by rigorous assessment of whether genomic results are enriched for smaller p-values in genes in classical and novel empirical pathways. ¿ (2b) Conduct the first highly powered genome-scale analysis of exome polymorphism in SCZ. The novel exome chip was developed by Illumina and our colleagues at the Broad, and captures missense and nonsense coding variation with MAF e0.1%, and a substantial fraction with MAF 0.01-0.1%. This could identify low-frequency missense or nonsense polymorphisms that contribute to SCZ. (2c) Analyze directly genotyped and imputed common variants in the Swedish data, and meta-analyze with the PGC SCZ results. Conduct verification genotyping as required. Anticipated outcome: genome-wide significant evidence for 10-20 novel loci. (2d) Identify structural variation contributing to SCZ. Conduct the first systematic evaluations of CNPs, indels, novel insertions, and other structural polymorphisms. Evaluate CNV associations with SCZ, and meta-analyze with external results. Conduct verification genotyping as required. Anticipated outcome: increase understanding of the major CNV loci, and the role of novel structural variants. In Aim 3, estimate if high-confidence genetic effects are modified by established epidemiological risk factors for SCZ. For this complex trait, environmental risks may generally interact with causal genetic variation. For Aim 2 results, are genetic effects strengthened or lessened if epidemiological risk factors are modeled? Risk factors are from high-quality databases and were often assessed prospectively (season of birth, urban/rural birth, paternal and grandparental age, pre-morbid cognitive attainment, and head trauma). Anticipated outcome: understanding of how specific genetic and environmental risk factors interact in SCZ that could lead to new mechanistic hypotheses. Our goal is rapidly to learn more about the genetics of schizophrenia and how genes and environment might act and interact to alter disease risk. We propose to do this using the largest and most comprehensively studied sample collection in the field and which includes both genetic and environmental risk factors.
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