High resolution mapping of the genetic risk for disease in the aging brain

摘要 作为正常的健康衰老过程的一部分，大脑结构在一生中都会经历变化，但有些 遗传因素被认为嵌入在我们的DNA中，改变并可能加速体内的衰老过程 大脑。虽然许多神经成像研究的目标是绘制痴呆症的遗传学图谱，但 群体和方法与可归因于任何单一遗传变异的小效应大小相混淆 导致调查结果不一致，调查真相的资源有限。几十种神经成像技术 为了更好地了解这种联系，世界各地都进行了基因研究。然而， 这些研究经常采用的独立性质可能会限制科学进步。与其收集 新的数据来回答同样的问题，我们协调了现有研究和池中的脑图工作 不仅研究健康大脑和痴呆症大脑之间的差异，而且还检查正常大脑的信息 健康的衰老趋势，并确定偏离的第一个迹象，并绘制出 导致痴呆症风险的基因。在我们的努力中，我们的目标是精确定位机械轨迹和大脑回路 通过它，被广泛研究的载脂蛋白E4基因单倍型在一生中影响大脑。尽管被确认为 20多年前阿尔茨海默病的遗传风险，对世界各地人群大脑的影响 是非常不一致的。用新的脑图技术覆盖数万个个体 在整个生命周期中，我们将执行最强大的大脑映射计划，并构建必要的工具来 邀请来自世界各地的其他研究人员为这一发现增添信心。我们还将确定-通过 史无前例的力量--AD的总风险如何通过新的研究促进大脑加速退变 用于大规模流行病学遗传研究的快速纵向线性混合建模技术 重复数据。我们的提案汇集了多学科合作者与WORLD 在神经退行性变、脑成像、大数据、人工智能、流行病学、 基因组学和表观基因组学，统计遗传学，以及分子和生物精神病学。我们的技术 专业知识将提供以最好的分辨率可视化遗传结果的资源，并提供工具 研究人员使用我们的协调分析来构建他们自己的男性人口老龄化假说 和世界各地的女性，甚至在老龄化方面针对特定性别的假设。随着新的大脑成像和 基因数据正在变得迅速可用，我们提供工具来将数据协调到此工作流程中，以便 再过几年。在此方案的数据共享和重用的推动下，我们为研究人员提供了一个门户 今天和明天访问这项提案中包含的所有研究的结果，并添加到 效果的集体储存库。我们希望我们对数据的仔细协调，以及新的数学， 工具和有针对性的假设的选择将指导未来的合作研究，以便继续重复使用。

ABSTRACT Brain structure undergoes changes throughout life as part of the normal healthy aging process, yet some genetic factors embedded in our DNA are believed to alter and potentially accelerate the aging process within the brain. While numerous neuroimaging studies have aimed to map the genetics of dementia, differences in populations and approaches confounded with the small effect sizes attributable to any single genetic variant leads to inconsistencies in findings and limited resources to investigate the truth. Dozens of neuroimaging genetic studies have been collected around the world to help better understand the link. However, the independent nature by which the studies often operate may be limiting scientific advance. Instead of collecting new data to answer the same questions, we harmonize brain mapping efforts across existing studies and pool information to not only study differences between the healthy and demented brain, but also examine normal healthy aging trends, and determine the first signs of deviation, and map out the neurobiological effect of genes that confer risk for dementia. In our effort, we aim to pinpoint mechanistic trajectories and brain circuits by which the widely studied ApoE4 genetic haplotype affects brain throughout life. Despite being identified as a genetic risk for Alzheimer's disease over 20 years ago, the effects on the brain in populations around the world are remarkably inconsistent. With novel brain mapping techniques across tens of thousands of individuals across the lifespan, we will perform the most well powered brain mapping initiative and build necessary tools to invite other researchers from around the world to add confidence to the findings. We will also determine – with unprecedented power -- how the aggregate risk for AD promotes accelerated brain degeneration with novel expedited longitudinal linear mixed modeling techniques for large scale epidemiological genetic studies with repeat data. Our proposal brings together contributions from multidisciplinary collaborators with world renowned expertise in neurodegeneration, brain mapping, big data, artificial intelligence, epidemiology, genomics and epigenomes, statistical genetics, and molecular and biological psychiatry. Our technical expertise will provide resources for visualizing genetic results at the finest resolution and provide tools for researchers to use our harmonized analyses to structure their own aging hypotheses in populations of men and women around the world, and even target sex-specific hypotheses in aging. As new brain imaging and genetic data is becoming rapidly available, we provide the tools to harmonize the data into this workflow for years to come. Driven by the data sharing and reuse of this proposal, we provide a portal for researchers of today and tomorrow to access findings from all the studies incorporated in this proposal and add to the collective repository of effects. We hope our careful harmonization of data, along with novel mathematics, tools, and selection of targeted hypotheses will guide future collaborative studies for continuous reuse.