Alzheimer's disease risk analyzed using population imaging genomics
使用群体成像基因组学分析阿尔茨海默病风险
基本信息
- 批准号:8900153
- 负责人:
- 金额:$ 48.73万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2011
- 资助国家:美国
- 起止时间:2011-09-01 至 2017-05-31
- 项目状态:已结题
- 来源:
- 关键词:AddressAdultAffectAgeAllelesAlzheimer&aposs DiseaseAlzheimer&aposs disease riskAnatomyAnisotropyAtrophicBrainCandidate Disease GeneCase-Control StudiesCerebrovascular CirculationClinical TrialsCorpus callosum spleniumDementiaDiagnosisDiffusion Magnetic Resonance ImagingDiseaseElderlyEnvironmental Risk FactorEvaluationFiberFunctional Magnetic Resonance ImagingGenesGeneticGenetic ModelsGenetic RiskGenomicsGlucoseGoalsImageImpaired cognitionIndividualInvestigationLifeLipidsMagnetic Resonance ImagingMathematicsMeasurementMeasuresMedialMeta-AnalysisModelingMyelinNeurotransmittersPathologyPathway interactionsPatientsPharmaceutical PreparationsPopulationPrevention strategyProcessProxyQueenslandRegulationResearchResearch PersonnelRestRiskRisk FactorsSamplingSiblingsSignal TransductionSingle Nucleotide PolymorphismSymptomsTimeTwin Multiple Birthapolipoprotein E-4basecingulate cortexcingulate gyruscognitive testingcohortdisease diagnosisempoweredendophenotypefrontal lobegenetic analysisgenetic risk assessmentgenetic risk factorgenome wide association studygenome-wideglucose metabolismgray matterimaging biomarkerimprovedinnovationlifestyle factorsmyelinationneuroimagingneuron lossnovelperformance testsrisk varianttime usewhite matteryoung adult
项目摘要
DESCRIPTION (provided by applicant): The recent discovery of new Alzheimer's disease (AD) risk genes has re-ignited efforts to understand how genes interact to impact brain vulnerability to AD. Deeper genetic analysis of AD risk using sophisticated imaging biomarkers will enable us to (1) predict risk for AD in younger adults to initiate prevention strategies in those at risk and (2) boost power in drug trials by selecting those at greatest risk of decline. Our goal is to assess genetic control over two measures that show deficits in AD patients: (1) functional "connectivity" (synchronicity) between the posterior cingulate cortex (PCC) and medial frontal cortex (MFC) at rest and (2) white matter integrity in the associated cingulum tract and splenium of the corpus callosum. Our project advances the study of AD genetic risk by investigating how multiple risk genes interact to disrupt brain connectivity. In this first-ever genomic analysis of structural and functional connectivity, we use both genome-wide association scanning (GWAS) and a candidate gene analyses of two large healthy cohorts: (1) 1150 young adult Queensland twins (QTwin; age: 20-29), and (2) 273 older healthy and cognitively impaired adults in the Alzheimer's Disease Neuroimaging Initiative cohort (ADNI; age: 55-90). Carriers of a common AD risk gene (CLU) have deficits in white matter integrity even as young adults and AD pathology may later exploit this vulnerability. We now expand our investigation of DTI genetics to assess structural connectivity. We also study how risk genes may impair functional synchronicity between PCC and MFC using resting state fMRI (rs-fMRI). We will: 3/4 Use a candidate gene approach to reveal how (1) known risk genes impair connectivity and fiber integrity in the splenium and cingulum in the young and elderly (QTwin and ADNI) and how (2) PCC-MFC synchronicity is influenced in both cohorts by top identified AD risk SNPs and SNPs that affect white matter integrity in the splenium and cingulum. 3/4 Use GWAS to identify new risk genes, whose carriers have impaired brain connectivity. We previously used GWAS to identify genes related to deficits in gray and white matter. We extend these findings to determine SNPs associated with (1) reduced FA and structural connectivity in the splenium and cingulum and (2) reduced synchronicity of PCC-MFC fMRI signal in the QTwin and ADNI samples. Promising hits will be proposed for verification and meta-analysis in Enigma (http://enigma.loni.ucla.edu) (N=10,000). 3/4 Use new multi-locus genetic models (ridge regression, PC regression, vGeneWAS) to evaluate how multiple common risk SNPs and multiple genes interact to impair brain connectivity. The product of these efforts will be (1) new assessments of genetic risk for brain dysconnectivity in healthy adults, (2) a means to boost clinical trial power, based on imaging and multi-SNP modeling of liability.
描述(由申请人提供):最近发现新阿尔茨海默氏病(AD)风险基因已重新点燃了基因如何相互作用以影响大脑对AD的脆弱性的努力。 使用复杂成像生物标志物对AD风险进行更深入的遗传分析将使我们能够(1)预测年轻人中AD的风险,可以通过选择具有最大衰落风险的人来启动风险患者的预防策略,以及(2)在药物试验中提高药物试验。 我们的目标是评估对两种表现出AD患者缺陷的遗传控制:(1)在静止和(2)相关的c和(2)白色质量完整性的相关的c和(2)白质完整性相关的c和splenium corpus corpus coldosum corpus corposum collosum coldosum coldosum coldosum coldosum consosum cortection(PCC)和内侧额叶皮层(MFC)之间的功能“连通性”(同步性)。 我们的项目通过研究多个风险基因如何相互作用以破坏大脑连接性来推进对AD遗传风险的研究。 In this first-ever genomic analysis of structural and functional connectivity, we use both genome-wide association scanning (GWAS) and a candidate gene analyses of two large healthy cohorts: (1) 1150 young adult Queensland twins (QTwin; age: 20-29), and (2) 273 older healthy and cognitively impaired adults in the Alzheimer's Disease Neuroimaging Initiative cohort (ADNI;年龄:55-90)。 普通AD风险基因(CLU)的载体在白质完整性方面存在缺陷,即使年轻人和AD病理可能会在后来利用这种脆弱性。 现在,我们扩大对DTI遗传学的研究以评估结构连通性。 我们还研究了风险基因如何使用静止状态fMRI(RS-FMRI)在PCC和MFC之间损害功能同步。 我们将:3/4使用候选基因方法来揭示(1)已知的风险基因如何损害年轻人和老年人(Qtwin and Adni)的脾和纤维的连通性和纤维完整性,以及(2)PCC-MFC同步性在两种群体中如何受到最佳识别AD风险SNP和SNP的影响,从而影响了白物和sphum splum splum splum splum splum splum splum and splum。 3/4使用GWAS识别携带者的新风险基因的大脑连通性受损。 我们以前使用GWAS识别与灰质和白质缺陷有关的基因。 我们扩展了这些发现,以确定与(1)脾和扣带中的FA降低和结构连通性相关的SNP,以及(2)QTWIN和ADNI样品中PCC-MFC FMRI信号的同步性降低。 将提出有希望的命中率,以进行谜(http://enigma.loni.ucla.edu)的验证和荟萃分析(n = 10,000)。 3/4使用新的多元基因遗传模型(脊回归,PC回归,VGENEWAS)来评估多个常见的风险SNP和多个基因如何相互作用以损害大脑的连接。 这些努力的产物将是(1)对健康成年人中脑功能障碍性遗传风险的新评估,(2)基于成像和多SNP责任建模的临床试验能力的一种手段。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
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PAUL M THOMPSON其他文献
PAUL M THOMPSON的其他文献
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{{ truncateString('PAUL M THOMPSON', 18)}}的其他基金
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