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

摘要 作为正常健康衰老过程的一部分，大脑结构在整个生命过程中都会发生变化， 嵌入我们DNA中的遗传因素被认为会改变并可能加速我们体内的衰老过程。 大脑虽然许多神经影像学研究的目的是绘制痴呆症的遗传学图谱，但 与任何单一遗传变异引起的小效应量混淆的人群和方法 导致调查结果不一致，调查真相的资源有限。几十个神经成像 已收集了世界各地的遗传研究，以帮助更好地了解这种联系。但 研究的独立性可能限制了科学的进步。而不是收集 新的数据来回答同样的问题，我们在现有的研究中协调大脑图谱的工作， 这些信息不仅可以研究健康和痴呆大脑之间的差异，还可以检查正常的大脑。 健康的老龄化趋势，并确定偏差的第一个迹象，并绘制出神经生物学的影响， 导致痴呆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 被广泛研究的ApoE 4基因单倍型通过其影响大脑的整个生命。尽管被认定为 早在20多年前，阿尔茨海默氏症的遗传风险就已经开始了， 非常不一致通过对数万人进行大脑测绘的新技术 在整个生命周期中，我们将执行最有力的大脑映射计划，并建立必要的工具， 邀请来自世界各地的其他研究人员为研究结果增添信心。我们还将确定-与 前所未有的力量-AD的总风险如何促进新的加速大脑退化 大规模流行病学遗传学研究的快速纵向线性混合建模技术 重复数据。我们的建议汇集了来自世界多学科合作者的贡献 在神经退行性疾病、脑图谱、大数据、人工智能、流行病学、 基因组学和表观基因组、统计遗传学以及分子和生物精神病学。我们的技术 专业知识将为以最佳分辨率可视化遗传结果提供资源，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设， 和世界各地的女性，甚至针对衰老中的性别特异性假设。作为新的大脑成像和 基因数据正在迅速变得可用，我们提供了工具来协调数据到这个工作流程中， 几年之后在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网站， 今天和明天，访问本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，沿着新的数学， 工具，并选择有针对性的假设将指导未来的合作研究，以不断重复使用。

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.