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

衰老大脑疾病遗传风险的高分辨率绘图

• 批准号: 9750590
• 负责人: Neda Jahanshad
• 金额: $ 61.99万
• 依托单位: UNIVERSITY OF SOUTHERN CALIFORNIA
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-08-01 至 2023-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9750590
• 关键词: Affect; Age; Aging; Algorithmic Software; Alzheimer' s Disease; Alzheimer' s disease risk; American; Area; Artificial Intelligence; Automobile Driving; Big Data; Biological; Biological Psychiatry; Brain; Brain Diseases; Brain Mapping; Brain imaging; Cardiovascular Diseases; Cardiovascular system; Chromosome Mapping; Chronic; Clinical; Collection; Communities; DNA; Data; Data Analyses; Data Set; Dementia; Diagnosis; Disease; Environmental Risk Factor; Epidemiology; Female; Foundations; Fright; Future; Genes; Genetic; Genetic Risk; Genetic study; Genomics; Genotype; Haplotypes; Healthcare; Heart Diseases; Human; Imaging Techniques; Impaired cognition; Individual; International; Lead; Life; Link; Literature; Longevity; Longitudinal Studies; Malignant Neoplasms; Maps; Mathematics; Medicine; Meta-Analysis; Methods; Modeling; Molecular; Monitor; Nature; Nerve Degeneration; Neurobiology; Neurosciences; Participant; Population; Process; Reporting; Reproducibility; Research; Research Personnel; Resolution; Resources; Sample Size; Scientific Advances and Accomplishments; Sex Differences; Structure; Surveys; Technical Expertise; Techniques; Testing; Time; Uncertainty; Variant; Visualization software; Woman; Work; X Chromosome; aging brain; aging population; apolipoprotein E-4; biobank; brain health; cognitive testing; data sharing; demented; dementia risk; disorder risk; epidemiology study; epigenome; flexibility; gene environment interaction; genetic association; genetic epidemiology; genetic profiling; genetic variant; genome-wide; global health; healthy aging; image processing; imaging genetics; insight; male; men; multidisciplinary; neuroimaging; novel; novel therapeutics; repository; risk variant; screening; sex; tool; trait; trend

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.

抽象的 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，但有些 人们相信，嵌入我们 DNA 中的遗传因素会改变并可能加速体内的衰老过程。 虽然许多神经影像学研究旨在绘制痴呆症的遗传学图谱，但大脑中的差异。 人群和方法与任何单一遗传变异造成的小效应大小相混淆 导致结果不一致，并且调查真相的资源有限。 世界各地的基因研究已被收集起来，以帮助更好地理解这种联系。 这些研究通常的独立性可能会限制科学进步，而不是收集。 新数据来回答相同的问题，我们协调现有研究和池中的大脑图谱工作 信息不仅可以研究健康大脑和痴呆大脑之间的差异，还可以检查正常大脑 健康的衰老趋势，确定偏差的第一个迹象，并绘制出神经生物学效应 我们的目标是查明导致痴呆症风险的基因轨迹和大脑回路。 广泛研究的 ApoE4 遗传单倍型尽管被确定为一种基因单倍型，但仍会影响大脑的整个生命周期。 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 新颖的大脑图谱技术在数以万计的个体中并不常见。 在整个生命周期中，我们将执行最有力的大脑绘图计划并构建必要的工具 我们还将邀请来自世界各地的其他研究人员为研究结果增添信心。 前所未有的力量——AD 的总体风险如何通过新颖的方法加速大脑退化 用于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 我们的提案汇集了来自世界各地的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。 专业知识将为以最高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统一分析来构建他们自己的男性衰老假设 以及世界各地的女性，甚至针对衰老中的性别特异性假设作为新的大脑成像和研究。 遗传数据正在迅速变得可用，我们提供工具将数据协调到此工作流程中 在该提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。 今天和明天获取本提案中纳入的所有研究的结果，并将其添加到 我们希望我们仔细协调数据以及新颖的数学， 工具和有针对性的假设的选择将指导未来的持续重用合作研究。