Imaging Genomics of the Aging Brain

项目概要/摘要 我们的目标是表征遗传和环境对正常衰老相关变化的影响 神经解剖学、神经生理学和神经认知指数。使用大量随机选择的数据收集 来自大脑结构和功能遗传学 (GOBS) 研究的谱系，我们之前记录过 基因型×年龄（G×A）相互作用影响神经认知能力下降和皮质厚度减少 内侧颞叶皮质和顶叶皮质。虽然这些发现表明遗传因素与大脑衰老有关，但它们是 基于横截面数据，缺乏对个体内衰老的直接评估。更强大的方法 检测健康老龄化的遗传和环境影响需要纵向数据。因此，我们 提出一项基于谱系的混合纵向研究，以重新对最古老的 700 名 GOBS 个体进行表型分析 ~10 最初评估后的几年。 10 年的间隔是测量与年龄相关的认知能力的理想选择， 由于练习效果和其他阶段性变化被最小化，神经解剖学和神经生理学下降。 GOBS 队列中的个体具有密集的遗传和表型特征，包括整体特征 基因组测序（WGS）、综合神经认知评估、大脑结构和功能 成像和基于血液的环境指数。我们的具体目标是 (1) 记录 10 年的神经认知 700 名非痴呆 GOBS 参与者（当前年龄 69.05 ± 8.4 [57-102]）的神经影像学下降； (2) 采用我们的 G×A 方法建立纵向大脑衰老表型； (3) 识别序列变异 先前与影响大脑衰老的正常或病理性衰老相关的候选基因/途径 表型并在档案样本中复制这些发现； (4) 应用一种新颖的统计方法 最大限度地利用系统环境信号来识别环境对大脑衰老表型的影响。 描绘与年龄相关的神经认知和神经影像的遗传和环境结构 变化将提供重要的生物学见解，进而可以提供增加 成功老龄化的美国人数量。 David Glahn 博士（耶鲁大学）和 John Blangero 博士（德克萨斯大学里奥格兰德河谷医学院） 学校、德克萨斯大学健康学院的 Rene Olvera 博士是本申请的联合首席研究员 圣安东尼奥科学中心将领导一项分包合同。鉴于丰富的表型、环境和 该队列中已有基因型数据，拟议的研究代表了一种现成的、成本低廉的 阐明大脑衰老机制的有效且强大的资源。

PROJECT SUMMARY/ABSTRACT Our goal is to characterize the genetic and environmental influences on normal aging-related changes in neuroanatomic, neurophysiologic and neurocognitive indices. Using data collected in large, randomly selected pedigrees from the Genetics of Brain Structure and Function (GOBS) study, we previously documented genotype × age (G×A) interactions influencing neurocognitive decline and reduced cortical thickness within medial temporal and parietal cortices. While these findings implicate genetic factors in brain aging, they are based on cross-sectional data and lack direct evaluation of intra-individual aging. More powerful methods for the detection of genetic and environmental influences of healthy aging require longitudinal data. Thus, we propose a pedigree-based, mixed longitudinal study to re-phenotype the oldest 700 GOBS individuals ~10 years after their initial assessment. A 10-year interval is ideal for measuring age-related cognitive, neuroanatomic and neurophysiological declines as practice effects and other phasic alterations are minimized. Individuals in the GOBS cohort have intensive genetic and phenotypic characterization, including whole genome sequencing (WGS), comprehensive neurocognitive assessment, structural and functional brain imaging and blood-based environmental indices. Our specific aims are to (1) document 10-year neurocognitive and neuroimaging declines in 700 non-demented GOBS participants (current age 69.05+8.4 [57-102]); (2) employ our G×A approach to establish longitudinal brain aging phenotypes; (3) identify sequence variation in candidate genes/pathways previously associated with normal or pathological aging that influencing brain aging phenotypes and replicate these findings in archival samples; and (4) apply a novel statistical approach to maximize systematic environmental signals to identify environmental influences on brain aging phenotypes. Delineating the genetic and environmental architecture of age-related neurocognitive and neuroimaging changes will offer important biological insights which in turn could provide strategies for increasing the numbers of Americans who successfully age. Dr. David Glahn, Yale University, and Dr. John Blangero, University of Texas Rio Grande Valley Medical School, are co-principal investigators on this application and Dr. Rene Olvera, University of Texas Health Science Center San Antonio, will lead a subcontract. Given the wealth of phenotypic, environmental and genotypic data already available in this cohort, the proposed study represents a readily available, cost- effective, and powerful resource for elucidating mechanisms of brain aging.