Neuroimaging Predictors of Cognitive Decline, Impairment, and Resilience

工作总结：与年龄相关的认知和记忆变化的神经解剖学和神经生理学基础仍不清楚，因为关于非痴呆症患者的纵向脑变化的研究数量有限。我们正在对巴尔的摩老龄化纵向研究(BLSA)的参与者进行系列磁共振成像(MRI)，包括测量血管变化、正电子发射断层扫描(PET)和神经心理学评估，以调查记忆变化和认知障碍的神经生物学基础。这些评估使我们能够检查大脑结构和功能的变化，这可能是认知变化和损伤的早期预测因素，包括阿尔茨海默病(AD)。我们正在继续对老年参与者进行纵向测试，并对新参与者进行评估，包括对55岁以下的参与者进行核磁共振成像和同时进行的神经心理学评估。对于55岁及以上的人，我们目前还进行了一次脑血流的PET测量，然后使用11-C-匹兹堡化合物B(PIB)进行PET扫描，以测量体内淀粉样蛋白的分布。我们在过去一年的进展包括继续获取新的神经成像评估以及继续分析现有数据和方法开发。大约一半的神经成像研究参与者参加了BLSA尸检计划，尸检和成像结果的整合是一个活跃的调查领域，以更好地了解促进患有淀粉样变但没有表现出记忆障碍的个人的认知弹性的因素。此外，我们正在使用神经成像工具来研究认知和大脑变化的调节因素，包括大脑老化的性别差异、遗传风险因素以及性类固醇和其他激素的影响。了解这些大脑行为关联，及早发现预测认知能力下降和损害的大脑加速变化，对于识别可能从新干预措施中受益的个人至关重要。 在过去的一年里，我们发表了许多这项研究的论文。与其他中心的成像结果和尸检研究一致，我们发现大约30%认知正常的老年人大脑中有可检测到的淀粉样蛋白水平。我们的PIB研究表明，在认知正常的个体中，较高的PIB水平与精神状态和记忆随着时间的推移而下降的程度更大相关(Resnick等人，2010年)，但在正常个体中，PIB与局部组织丢失并不显著相关(Driscoll等人，2011年)。这些研究还显示，在最初的PIB评估中，PIB留存较高的个体的PIB留存纵向增加(Sojkova等人，2011年)，以及体内淀粉样蛋白成像模式与CERAD对AD病理诊断的病理分级之间的一致性和不一致性(Sojkova等人，2010年)。我们的成像-神经病理学分析突出了使用标准神经病理诊断对PIB进行尸检验证的困难，这是由于在标准CERAD评估下检查的区域和在PIB成像上显示最早淀粉样蛋白沉积的大脑区域的不同。我们正在使用PIB结合的空间模式(以及MRI组织丢失和损伤)来指导更详细的尸检分析。 此外，我们还研究了聚集素和其他血浆蛋白浓度以及与PIB水平和模式相关的遗传风险。在基线神经影像评估时，血浆中较高的聚集素浓度与10年后较高的内侧颞叶PIB滞留率相关(Thambitetty等人，2010年)。此外，我们将蛋白质组学与体内淀粉样蛋白成像相结合，以确定一组18个2DGE血浆蛋白斑点，这些斑点区分脑A高和低的个体(ThamBisetty等，2010)。质谱学鉴定了这些蛋白质，其中许多蛋白质在A&A清除过程中发挥了作用，包括来自载脂蛋白-E(ApoE)的强烈信号。血浆载脂蛋白E浓度与内侧颞叶的A负荷增加有关，在海马区和内嗅皮层表现最为明显。与非携带者相比，载脂蛋白E携带者在几个脑区的A水平也更高。这些结果提示，ApoE蛋白的外周浓度和APOE基因与AD易感脑区的早期神经病理改变有关，即使在非痴呆的老年人也是如此。 该项目的数据还继续被用于加强纵向神经成像数据分析的重要方法学开发，包括描述MRI上剥离头骨的新方法的论文(Carass等人，2011年)，用于检测基于集群的病理测量的成像数据的集群分析(Filipovych等人，2011年)，以及扩展生物参数映射，以在一般线性模型的神经成像应用的背景下包括稳健回归和稳健推断(薛等人，2011年)。

Summary of work: The neuroanatomic and neurophysiologic underpinnings of age-associated cognitive and memory change remain unclear, as there are a limited number of studies of longitudinal brain changes in individuals without dementia. We are performing serial magnetic resonance imaging (MRI), including measures of vascular changes, positron emission tomography (PET), and neuropsychological assessments in participants from the Baltimore Longitudinal Study of Aging (BLSA) to investigate the neurobiological basis of memory change and cognitive impairment. These evaluations allow us to examine changes in brain structure and function which may be early predictors of cognitive change and impairment, including Alzheimer's disease (AD). We are continuing longitudinal testing of older participants and evaluating new participants, including MRI and concurrent neuropsychological assessments of participants less than 55 years old. For individuals aged 55 and older, we also currently perform a single PET measurement of CBF, followed by a PET scan using 11-C-Pittsburgh Compound B (PiB) to measure in vivo amyloid distribution. Our progress over the last year includes continued acquisition of new neuroimaging assessments as well as continued analysis of existing data and methods development. Approximately half of the neuroimaging study participants are enrolled in the BLSA autopsy program, and the integration of autopsy and imaging findings is an active area of investigation to gain a better understanding of factors that promote cognitive resilience in individuals who have amyloid pathology but do not show memory impairment. In addition, we are using neuroimaging tools to investigate modulators of cognitive and brain changes, including sex differences in brain aging, genetic risk factors, and the effects of sex steroid and other hormones. An understanding of these brain-behavior associations and early detection of accelerated brain changes that predict cognitive decline and impairment will be critical in identifying individuals likely to benefit from new interventions. Over the last year, we have published a number of papers from this study. Consistent with imaging findings at other centers and autopsy studies, we find that about 30 percent of cognitively normal older adults have detectable levels of amyloid in the brain. Our PiB studies have demonstrated that higher PiB levels in cognitively normal individuals are associated with greater decline over time in mental status and memory (Resnick et al, 2010) but PiB was not significantly associated with regional tissue loss in normal individuals (Driscoll et al, 2011). These studies also have revealed longitudinal increases in PiB retention in individuals with higher PiB retention at initial PiB assessment (Sojkova et al, 2011) and the concordance and discordance between in vivo amyloid imaging patterns and pathological ratings of amyloid plaques according to the CERAD classification for pathological diagnosis of AD (Sojkova et al, 2010). Our imaging-neuropathology analyses have highlighted difficulties in using standard neuropathological diagnosis for autopsy validation of PiB due to differences in regions examined under the standard CERAD assessment and the brain regions showing the earliest amyloid deposition on PiB imaging. We are using the spatial patterns of PiB binding (and MRI tissue loss and lesions) to guide more detailed autopsy analyses. In addition, we have investigated clusterin and other plasma protein concentrations and genetic risk in relation to PiB levels and patterns. Higher clusterin concentration in plasma at baseline neuroimaging assessment was associated with higher medial temporal PiB retention more than 10 years later (Thambisetty et al, 2010). In addition, we combined proteomics with in in vivo amyloid imaging to identify a panel of 18 2DGE plasma protein spots that discriminated between individuals with high and low brain Aβ (Thambisetty et al, 2010). Mass spectrometry identified these proteins, many of which have established roles in Aβ clearance, including a strong signal from apolipoprotein-E (ApoE). Plasma ApoE concentration was associated with increased Aβ burden in the medial temporal lobe, most pronounced in the hippocampus and entorhinal cortex. APOE ε4 carriers also showed greater Aβ levels in several brain regions relative to ε4 non-carriers. These results suggest that both peripheral concentration of ApoE protein and APOE genotype are related to early neuropathological changes in brain regions vulnerable to AD pathology even in the non-demented elderly. The data from this project also continue to be used for important methodological developments to enhance analysis of longitudinal neuroimaging data, including papers describing new approaches for skull-stripping on MRI (Carass et al., 2011), cluster analysis of imaging data for detection of a cluster-based measure of pathology that reflects the deviation of a subject's MR image from a normal (i.e. cognitively stable) state (Filipovych et al, 2011), and an extension of Biological Parametric Mapping to include robust regression and robust inference in the neuroimaging context of application of the general linear model (Xue et al, 2011).