Imaging Genomics of the Aging Brain

衰老大脑的成像基因组学

• 批准号: 10200628
• 负责人: John Blangero
• 金额: $ 81.31万
• 依托单位: BOSTON CHILDREN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-30 至 2023-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10200628
• 关键词: Age; Aging; Alzheimer' s Disease; American; Architecture; Biological; Biological Markers; Biology of Aging; Blood; Brain; Brain imaging; Candidate Disease Gene; Child; Chronology; Clinical; Cognitive; Coupled; Data; Data Set; Diabetes Mellitus; Diffusion; Dimensions; Education; Elderly; Environment; Environmental Risk Factor; Evaluation; Gas Chromatography; Generations; Genes; Genetic; Genetic Variation; Genomics; Genotype; Goals; Health Sciences; Image; Individual; Lead; Longevity; Longitudinal Studies; MRI Scans; Mass Spectrum Analysis; Measurement; Measures; Medial; Neuroanatomy; Neurocognition; Neurocognitive; Neurocognitive Deficit; Neurologic Examination; Obesity; Parietal Lobe; Parkinson Disease; Participant; Pathway interactions; Phase; Phenotype; Plasma; Principal Investigator; Quality of life; Recording of previous events; Resources; Rest; Sampling; Scotland; Signal Transduction; Smoking; Socioeconomic Status; Spatial Distribution; Structure; Technology; Temporal Lobe; Testing; Texas; Thick; Time; Universities; Variant; age related; aging brain; base; biobank; brain health; cohort; cost effective; design; detection method; functional MRI scan; genetic approach; genetic architecture; genetic association; genetic pedigree; genome sequencing; genome wide association study; health care service utilization; healthy aging; high dimensionality; human old age (65+); improved; indexing; insight; interest; lipidomics; medical schools; metabolomics; neuroimaging; neurophysiology; non-demented; normal aging; novel; novel strategies; pathological aging; sample archive; socioeconomics; trait; whole genome

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.

项目摘要/摘要 我们的目标是表征对正常衰老相关变化的遗传和环境影响 神经解剖学，神经生理学和神经认知指数。使用大型，随机选择的数据 来自大脑结构和功能（GOB）研究的遗传学的血统，我们先前记录了 基因型×年龄（G×A）相互作用会影响神经认知的下降，并减少皮质厚度 媒体临时和顶叶皮层。尽管这些发现暗示了大脑衰老中的遗传因素，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 检测健康衰老的遗传和环境影响需要纵向数据。那，我们 提案基于血统的混合纵向研究，重新表现为最古老的700 GOBS个人〜10 初次评估后的几年。 10年间隔非常适合测量与年龄相关的认知， 随着实践效应和其他阶段变化的最小化，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表征，包括整个 基因组测序（WGS），全面的神经认知评估，结构和功能性大脑 想象和基于血液的环境指数。我们的具体目的是（1）文档10年的神经认知 700名非痴呆的GOB参与者（当前69.05+8.4 [57-102]）的神经影像学下降了； （2） 员工我们的G×一种方法来建立纵向脑老化表型； （3）确定序列变化 候选基因/途径先前与正常或病理衰老相关的，影响大脑衰老 表型并在档案样本中复制这些发现； （4）将新颖的统计方法应用于 最大化系统的环境信号，以识别对脑老化表型的环境影响。 描述与年龄有关的神经认知和神经影像学的遗传和环境结构 变化将提供重要的生物学见解，反过来可以为增加 成功年龄的美国人人数。 耶鲁大学的大卫·格拉恩（David Glahn）博士和德克萨斯大学里奥格兰德谷大学医学的约翰·布兰格罗博士 学校是有关此申请的联合首长调查员，德克萨斯大学健康大学的Rene Olvera博士 科学中心圣安东尼奥将领导分包合同。考虑到大量的表型，环境和 该队列中已经可用的基因型数据，拟议的研究代表了一项随时可用的，成本 - 有效且强大的资源，用于阐明大脑衰老的机制。