Alzheimer's disease risk analyzed using population imaging genomics

描述（由申请人提供）：最近发现的新的阿尔茨海默病（AD）风险基因重新点燃了了解基因如何相互作用影响大脑对AD的易感性的努力。利用复杂的成像生物标志物对阿尔茨海默病风险进行更深入的遗传分析，将使我们能够(1)预测年轻人患阿尔茨海默病的风险，从而在风险人群中启动预防策略；(2)通过选择风险下降最大的人群，提高药物试验的有效性。我们的目标是评估遗传控制对阿尔茨海默病患者两项缺陷的影响：(1)静止状态下后扣带皮层（PCC）和内侧额叶皮层（MFC）之间的功能“连通性”（同步性）；(2)相关扣带束和胼胝体脾的白质完整性。我们的项目通过研究多种风险基因如何相互作用以破坏大脑连接来推进AD遗传风险的研究。在这首个结构和功能连通性的基因组分析中，我们使用了全基因组关联扫描（GWAS）和两个大型健康队列的候选基因分析：(1)1150名年轻昆士兰双胞胎（QTwin，年龄：20-29），(2)273名老年健康和认知受损的老年阿尔茨海默病神经影像学倡议队列（ADNI，年龄：55-90）。一种常见的阿尔茨海默病风险基因（CLU）的携带者即使在年轻人中也存在白质完整性缺陷，阿尔茨海默病病理可能在以后利用这种脆弱性。我们现在扩大了对DTI遗传学的研究，以评估结构连通性。我们还利用静息状态fMRI （rs-fMRI）研究了风险基因如何损害PCC和MFC之间的功能同步性。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脾带和束带的连通性和纤维完整性（QTwin和ADNI），以及(2)两个队列中PCC-MFC同步性如何受到已确定的AD风险snp和影响脾带和束带白质完整性的snp的影响。3/4使用GWAS识别新的风险基因，其携带者大脑连接受损。我们之前使用GWAS来识别与灰质和白质缺陷相关的基因。我们扩展了这些发现，以确定snp与(1)脾脏和扣带FA和结构连通性降低以及(2)QTwin和ADNI样本中PCC-MFC fMRI信号同步性降低相关。在Enigma (http://enigma.loni.ucla.edu) （N=10,000）中提出有希望的命中值进行验证和元分析。3/4使用新的多位点遗传模型（岭回归、PC回归、vGeneWAS）评估多个常见风险snp和多个基因如何相互作用损害大脑连通性。这些努力的结果将是：(1)对健康成人大脑连接障碍的遗传风险进行新的评估；(2)基于成像和多snp责任模型，提高临床试验的能力。

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.