Neuroimaging and Vascular Correlates of Mild Cognitive Impairment Subtypes

轻度认知障碍亚型的神经影像学和血管相关性

• 批准号: 9220724
• 负责人: Katherine Bangen
• 金额: --
• 依托单位: VA SAN DIEGO HEALTHCARE SYSTEM
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-10-01 至 2019-09-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9220724
• 关键词: Aging; Alzheimer' s Disease; Amyloid; Anisotropy; Anterior; Attenuated; Biological Markers; Blood Vessels; Brain; Cause of Death; Cerebrospinal Fluid; Cerebrovascular Disorders; Clinical; Clinical Trials; Cognitive; Complex; Data; Data Analyses; Data Collection; Dementia; Detection; Diagnosis; Diagnostic; Diffuse; Diffusion; Diffusion Magnetic Resonance Imaging; Disease; Effectiveness of Interventions; Elderly; Equilibrium; Evaluation; Exclusion; Explosion; Exposure to; Framingham Heart Study; Future; Goals; Heterogeneity; Hippocampus (Brain); Image; Impaired cognition; Impairment; Individual; Inferior; Intervention; Laboratories; Liquid substance; Longitudinal Studies; Magnetic Resonance Imaging; Measurement; Measures; Medial; Modeling; Monitor; Myelin; Nature; Nerve Degeneration; Neuropsychology; Pathology; Perfusion; Physiologic pulse; Probability; Protocols documentation; Radial; Recovery; Research; Research Design; Resolution; Risk; Risk Assessment; Risk Factors; Risk Marker; Selection Criteria; Selection for Treatments; Severities; Structure; Subgroup; Symptoms; Techniques; Temporal Lobe; Testing; Time; Training; Veterans; White Matter Hyperintensity; Wood material; aging population; amnestic mild cognitive impairment; apolipoprotein E-4; career; cerebrovascular; clinical predictors; cognitive ability; disability; experience; fasting glucose; frontal lobe; gray matter; high risk; imaging biomarker; improved; indexing; interest; limbic lobe; longitudinal dataset; mild cognitive impairment; multimodality; neuroimaging; neuroimaging marker; neuropathology; novel; outcome forecast; potential biomarker; programs; public health relevance; skills; tau Proteins; treatment strategy; vascular factor; white matter; white matter change; white matter damage

DESCRIPTION (provided by applicant): Since the aging population is growing at an unprecedented pace, the number of Veterans diagnosed with dementia is estimated to increase dramatically. Identification of individuals before the onset of significant clinical symptoms is essential for facilitating intervention when therapies may be most effective. One approach to identifying potential biomarkers of prodromal dementia involves assessing brain structure in individuals at increased risk for developing Alzheimer's disease (AD), such as those with mild cognitive impairment (MCI). With a recent explosion in MCI research, it has become clear that it is a heterogeneous disorder and distinct clinical subtypes (e.g., amnestic, nonamnestic) have been proposed. Heterogeneity in the clinical presentation of MCI may relate in part to the heterogeneity of underlying neuropathological mechanism(s). Although debated, evidence suggests that individuals with amnestic MCI demonstrate greater medial temporal lobe damage typical of early AD (e.g., Singh et al., 2006). In contrast, those with nonamnestic MCI show greater frontal lobe involvement (Nobili et al., 2008) and greater cerebrovascular disease (as evidenced by white matter abnormalities) on MRI (Delano-Wood et al., 2009). Mixed MCI characterized by impairment in multiple domains of cognitive ability may represent individuals with mixed pathology with both neurodegenerative and cerebrovascular features (Libon et al., 2010). Taken together, previous studies highlight a complex relationship between MCI, white matter, AD pathology, and cerebrovascular functioning. The proposed study will combine imaging markers of white matter abnormalities and vascular risk markers with AD-related biomarkers (e.g., cerebrospinal fluid [CSF] measures of amyloid and tau, hippocampal volume) as well as take into account MCI clinical subtypes in order to more completely characterize the contributions of AD and cerebrovascular risk to the dementia prodrome. In doing so, we can compare the prevailing model of biomarkers of MCI and AD, which emphasizes neurodegeneration (e.g., Jack et al., 2013) with a model relating the combined effects of vascular and AD pathologies to the probability of developing dementia (Chui et al., 2012). The current study aims to (1) better characterize the structural brain changes and vascular risk profiles underlying distinct MCI subtypes, (2) critically examine novel neuroimaging measures that might distinguish MCI subtypes and contribute to the nature and severity of cognitive impairment, and (3) determine which neuroimaging markers of white and gray matter alterations and additional risk factors for dementia (i.e., vascular risk factors, APOE �4 status) are most useful in predicting cognitive decline and progression to dementia. In the proposed study, 92 older adults (23 cognitively normal, 23 amnestic MCI, 23 nonamnestic MCI, and 23 mixed/multiple domain MCI) will undergo comprehensive neuropsychological assessment; laboratory testing to assess vascular risk factors (e.g., fasting glucose); CSF measurement of amyloid and tau; and neuroimaging exams including high resolution structural, perfusion, and white matter imaging. White matter imaging protocols include T2-weighted fluid attenuated inversion recovery (FLAIR) as well as two cutting edge techniques: diffusional kurtosis imaging (DKI) and a novel, myelin-selective technique (multi-component driven equilibrium single pulse observation of T1 and T2 [mcDESPOT]). It is hypothesized that greater vascular risk burden and white matter changes in frontal regions will be associated with nonamnestic MCI and mixed/multiple domain MCI. In contrast, white matter changes in medial temporal lobe regions will be associated with amnestic MCI and mixed/multiple domain MCI. A better understanding of the underlying neuropathology associated with distinct MCI clinical subtypes and the implementation of multimodal neuroimaging markers that better detect heterogeneous pathologies may have important implications for diagnosis, prognosis, treatment selection, and monitoring of disease-modifying effects of therapy as well as selection criteria for clinical trials.

描述（由申请人提供）： 由于人口老龄化正以前所未有的速度增长，估计被诊断患有痴呆症的退伍军人人数将急剧增加。在出现显著临床症状之前识别个体对于在治疗可能最有效时促进干预至关重要。识别前驱痴呆的潜在生物标志物的一种方法涉及评估患有阿尔茨海默病（AD）的风险增加的个体的脑结构，例如患有轻度认知障碍（MCI）的个体。随着MCI研究的最近爆发，已经清楚的是，它是一种异质性疾病和不同的临床亚型（例如，遗忘的，非遗忘的）。MCI临床表现的异质性可能部分与潜在神经病理机制的异质性有关。尽管存在争议，但有证据表明，患有遗忘型MCI的个体表现出更大的早期AD典型的内侧颞叶损伤（例如，Singh等人，2006年）。相比之下，那些患有非遗忘型MCI的人显示出更大的额叶受累（Nobili等人，2008）和更大的脑血管疾病（如由白色物质异常所证明）（Delano-Wood等，2009年）。以多个认知能力领域受损为特征的混合型MCI可能代表具有神经退行性和脑血管特征的混合病理的个体（Libon等人，2010年）。综上所述，以前的研究强调了MCI、白色物质、AD病理和脑血管功能之间的复杂关系。拟议的研究将联合收割机将白色异常的成像标志物和血管风险标志物与AD相关的生物标志物（例如，脑脊液[CSF]测量淀粉样蛋白和tau蛋白，海马体积），并考虑MCI临床亚型，以更全面地表征AD和脑血管风险对痴呆前驱症状的贡献。在这样做时，我们可以比较MCI和AD的生物标志物的流行模型，其强调神经变性（例如，杰克等人，2013），该模型将血管和AD病理的组合效应与发展痴呆的可能性相关联（Chui et al.，2012年）。目前的研究旨在（1）更好地表征不同MCI亚型的脑结构变化和血管风险特征，（2）严格检查可能区分MCI亚型并有助于认知障碍的性质和严重程度的新神经影像学指标，以及（3）确定白色和灰质改变的神经影像学标志物以及痴呆的其他风险因素（即，血管危险因素，APOE-4状态）在预测认知能力下降和痴呆进展方面最有用。在拟议的研究中，92名老年人（23名认知正常，23名遗忘型MCI，23名非遗忘型MCI和23名混合/多领域MCI）将接受全面的神经心理学评估;实验室测试以评估血管风险因素（例如，空腹血糖）; CSF淀粉样蛋白和tau蛋白测量;神经影像学检查，包括高分辨率结构、灌注和白色物质成像。白色物质成像方案包括T2加权液体衰减反转恢复（FLAIR）以及两种前沿技术：弥散峰度成像（DKI）和一种新型髓鞘选择性技术（T1和T2的多组分驱动平衡单脉冲观察[mcDESPOT]）。据推测，更大的血管风险负担和额叶区域的白色物质变化将与非遗忘型MCI和混合/多域MCI相关。相反，内侧颞叶区域中的白色物质变化将与遗忘型MCI和混合/多域MCI相关。更好地了解与不同MCI临床亚型相关的潜在神经病理学，以及更好地检测异质性病理学的多模式神经影像学标记物的实施可能对诊断、预后、治疗选择和监测治疗的疾病修饰效应以及临床试验的选择标准具有重要意义。