Brain structure, chemistry and function investigations in aging using MRI/MRS

使用 MRI/MRS 研究衰老过程中的脑结构、化学和功能

• 批准号: 8931645
• 负责人: Dimitrios Kapogiannis
• 金额: $ 18.77万
• 依托单位: NATIONAL INSTITUTE ON AGING
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/8931645
• 关键词: Affective; Age; Aging; Agonist; Alzheimer' s Disease; Amyloid deposition; Anterior; Area; Atrophic; Biological Markers; Brain; CNR1 gene; Caloric Restriction; Cephalic; Chemistry; Clinical Research; Cognition; Cognitive; Collaborations; Data; Data Set; Databases; Disease; Disease Progression; Enrollment; Etiology; Financial compensation; Food; Functional Magnetic Resonance Imaging; Future; Generations; Genetic Crossing Over; Glucose; Glutamates; Glutamine; Glycine; Goals; Hippocampus (Brain); Hypothalamic structure; Image; Individual; Insula of Reil; Insulin; Insulin Resistance; Investigation; Journals; Knowledge; Magnetic Resonance Imaging; Magnetic Resonance Spectroscopy; Manuscripts; Measurement; Measures; Medial; Mentors; Metabolic; Metabolic Control; Metabolism; Methodology; Metric; Mind; Nerve Degeneration; Neurology; Neurotransmitters; Obesity; Participant; Pathogenesis; Pathway interactions; Patients; Pattern; Performance; Peripheral; Placebo Control; Play; Positron-Emission Tomography; Postdoctoral Fellow; Prefrontal Cortex; Process; Psychiatry; Publishing; Randomized; Religious Belief; Reporting; Research; Rest; Role; Staging; Structure; Techniques; Temporal Lobe; Ventral Tegmental Area; age group; aging brain; brain metabolism; brain volume; data reduction; disease diagnosis; exenatide; frontal lobe; gamma-Aminobutyric Acid; glucose metabolism; independent component analysis; insulin secretion; interest; memory encoding; memory retrieval; mild cognitive impairment; neurochemistry; neuroimaging; neurotransmission; novel; response; sex; systematic review; theories; trait; uptake; visual stimulus

Volumetric measures obtained with analysis of high-definition 3D structural MRI images capture neuroanatomical variability which may be associated with long-standing traits or may help explain why certain brain areas or individuals are vulnerable to neurodegenerative processes. This last year, I applied a data reduction technique called group-level independent component analysis (ICA) to structural MRI images to uncover patterns of structural covariance (Independent Components). We applied ICA to MRI data collected in the ADNI study and examined how they can discriminate between participants with normal cognition, mild cognitive impairment (MCI) and Alzheimer's disease (AD). We showed that ICs can be useful as classifiers and predictors of future AD diagnosis or conversion to AD from MCI (the manuscript is currently in press in "Psychiatry Research: Neuroimaging"). In addition, given the association between insulin resistance and Alzheimer's disease, we examined how volumetric and FDG-PET uptake measures for several key regions of interest for AD relate to peripheral insulin resistance. We found that insulin resistance promotes two abnormal and pathogenic compensations: it increases glucose metabolism in the hippocampus and medial temporal lobe at the stage of mild cognitive impairment and increases glucose metabolism in default mode network nodes at the stage of AD. Prior fMRI studies suggest that these compensatory increases in metabolism are associated with disease progression; therefore, insulin resistance seems to promote a maladaptive compensation. The manuscript is currently under review in the journal "Neurology". Together with a post-doctoral fellow I mentor, Dr. Auriel Willette, we conducted a systematic review of neuroimaging studies looking at associations of obesity and brain volume across the age-span. We found that increased obesity is associated with atrophy mainly in the frontal lobes. Our review was published by the journal "Aging Research Reviews". I conducted an fMRI study using a novel methodology for effective connectivity analysis to fMRI data based on the principles of Granger causality. This methodology allows us to uncover causal pathways between nodes of a brain network. I implemented this analysis in a dataset from a fMRI study on religious beliefs conducted in 2009. The findings support the theory that areas implicated in Theory of Mind are key to generation of religious beliefs. The study was published in the journal "Brain Connectivity". Finally, in collaboration with Drs. Chia and Egan, we completed the "RISE study", a multi-faceted randomized placebo-controlled cross-over clinical study of the effects of a CB1 receptor agonist and antagonist on peripheral metabolism, brain function and brain metabolic control. The study included a robust neuroimaging component including fMRI and MRS. We performed two activation-paradigm fMRI studies, one to discover brain correlates of cephalic insulin secretion and the effects of CB1 receptors, the second to assess the effects of CB1 receptors on food appetitiveness. The goal of the first study was to demonstrate a rise in insulin levels in response to food visual stimuli (cephalic insulin response) as a result of activation of certain brain areas (insula, anterior cingulate, hypothalamus, ventral tegmental area, etc). Moreover, given the presence of CB1 receptors in the candidate areas, we aimed to demonstrate a difference in their level of activation with CB1 agonists and antagonists. The goal of the second study was to demonstrate dissociable effects of CB1 receptor stimulation on food value (food choices) and salience (intensity of such choices). In addition, we performed a resting fMRI study to assess CB1 modulation of functional connectivity of the various brain networks. Finally, we performed MRS to assess CB1 modulation of brain metabolism (glucose, lactate) and neurotransmission (glutamate, GABA, glycine). We are currently in the process of analyzing and interpreting the data from these studies.

通过分析高清3D结构MRI图像获得的体积测量捕获神经解剖学变异性，这可能与长期的特征有关，或者可能有助于解释为什么某些大脑区域或个人很容易受到神经退行性过程的影响。去年，我将一种称为组级独立组件分析（ICA）的数据还原技术应用于结构MRI图像，以发现结构协方差的模式（独立组件）。我们将ICA应用于ADNI研究中收集的MRI数据，并研究了它们如何区分患有正常认知，轻度认知障碍（MCI）和阿尔茨海默氏病（AD）的参与者。我们表明，IC可以用作分类器和未来AD诊断或转换为MCI的AD的预测指标（手稿目前在“精神病学研究：神经影像学”中出版）。 此外，鉴于胰岛素抵抗与阿尔茨海默氏病之间的关联，我们研究了AD的几个关键关键区域的体积和FDG-PET摄取量与外围胰岛素抵抗如何相关。我们发现胰岛素抵抗会促进两种异常和致病性补偿：它在轻度认知障碍阶段增加了海马和内侧颞叶的葡萄糖代谢，并在AD阶段增加了默认的葡萄糖代谢在默认模式网络节点。先前的功能磁共振成像研究表明，这些代谢增加与疾病进展有关。因此，胰岛素抵抗似乎促进了适应不良的补偿。该手稿目前正在“神经病学”杂志上进行综述。 我们与一位博士后同胞I指导者Auriel Willette博士一起进行了系统的综述，对整个Age-Span的肥胖和大脑体积的关联进行了神经影像学研究。我们发现，肥胖症的增加与额叶叶片主要有关。我们的评论由《老化研究评论》杂志发表。 我使用一种新方法进行了功能磁共振成像研究，以基于Granger因果关系的原理来有效地与fMRI数据进行连通性分析。这种方法使我们能够发现大脑网络节点之间的因果途径。我在2009年对宗教信仰的一项功能磁共振成像研究的数据集中实施了这一分析。该发现支持以下理论：与思想理论有关的领域是产生宗教信仰的关键的理论。该研究发表在《大脑连通性》杂志上。 最后，与Drs合作。 Chia和Egan，我们完成了“ RISE研究”，这是一项多面的随机安慰剂对照的跨界临床研究，对CB1受体激动剂和拮抗剂对外周代谢，脑功能和脑代谢控制的影响。该研究包括包括fMRI和MRS在内的强大神经影像成分。我们进行了两项激活 - 范式pRADIGM FMRI研究，其中一项发现头孢氨胰岛素分泌的脑相关性和CB1受体的作用，第二种是评估CB1受体对食物食欲的影响的第二种。第一项研究的目的是证明胰岛素水平响应于食物视觉刺激（头孢酸胰岛素反应），这是由于某些大脑区域的激活（岛状，前扣带回，下丘脑，腹侧段盖面积等）的结果。此外，鉴于候选区域中CB1受体的存在，我们旨在证明它们与CB1激动剂和拮抗剂的激活水平有所不同。第二项研究的目的是证明CB1受体刺激对食物价值（食物选择）和显着性（这种选择的强度）的可分离作用。此外，我们进行了静止的功能磁共振成像研究，以评估各种大脑网络功能连通性的CB1调制。最后，我们进行了MRS评估脑代谢（葡萄糖，乳酸）和神经传递（谷氨酸，GABA，甘氨酸）的CB1调节。目前，我们正在分析和解释这些研究的数据。