Alzheimer's disease risk analyzed using population imaging genomics

描述(申请人提供)：最近发现了新的阿尔茨海默病(AD)风险基因，重新点燃了了解基因相互作用如何影响大脑对AD易感性的努力。使用复杂的成像生物标记物对AD风险进行更深入的遗传分析将使我们能够(1)预测年轻人的AD风险，以便在有风险的人中启动预防策略，(2)通过选择那些下降风险最大的人来提高药物试验的能力。我们的目标是评估对显示AD患者存在缺陷的两项指标的遗传控制：(1)静息状态下扣带回后部皮质(PCC)和额叶内侧皮质(MFC)之间的功能性“连通性”(同步性)；(2)相关扣带束和穹隆压部白质的完整性。我们的项目通过研究多个风险基因如何相互作用来破坏大脑连接来推进AD遗传风险的研究。在这项首次对结构和功能连接性进行的基因组分析中，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对昆士兰双胞胎(QTwin；年龄：20-29)；(2)阿尔茨海默病神经成像倡议队列(ADNI；年龄：55-90)中273名健康和认知受损的老年成年人。常见AD风险基因(CLU)的携带者在白质完整性方面存在缺陷，即使年轻人和AD病理后来可能会利用这一漏洞。我们现在扩大对DTI遗传学的研究，以评估结构的连通性。我们还使用静息状态功能磁共振成像(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(QTwin和ADNI)压部和扣带的连通性和纤维完整性，以及(2)在这两个队列中，最常见的AD风险SNPs和影响压部和扣带中白质完整性的SNPs如何影响PCC-MFC的同步性。四分之三的人使用GWAS来识别新的风险基因，这些基因的携带者已经损害了大脑的连接。我们之前使用GWARs来识别与灰质和白质缺陷相关的基因。我们将这些发现扩展到确定与(1)压部和扣带区FA和结构连接性降低以及(2)QTwin和ADNI样本中PCC-MFC功能磁共振信号同步性降低相关的SNPs。将提出有希望的HITS用于Enigma(http://enigma.loni.ucla.edu)(N=10,000))的验证和荟萃分析。3/4使用新的多基因座遗传模型(岭回归、PC回归、vGenewas)来评估多个共同风险SNPs和多个基因如何相互作用来损害大脑连接。这些努力的成果将是(1)对健康成年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易感性建模的提高临床试验能力的手段。

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.