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Testing a longitudinal compensation model in premanifest Huntington’s disease

机译:测试预感亨廷顿氏病的纵向补偿模型

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摘要

The initial stages of neurodegeneration are commonly marked by normal levels of cognitive and motor performance despite the presence of structural brain pathology. Compensation is widely assumed to account for this preserved behaviour, but despite the apparent simplicity of such a concept, it has proven incredibly difficult to demonstrate such a phenomenon and distinguish it from disease-related pathology. Recently, we developed a model of compensation whereby brain activation, behaviour and pathology, components key to understanding compensation, have specific longitudinal trajectories over three phases of progression. Here, we empirically validate our explicit mathematical model by testing for the presence of compensation over time in neurodegeneration. Huntington’s disease is an ideal model for examining longitudinal compensation in neurodegeneration as it is both monogenic and fully penetrant, so disease progression and potential compensation can be monitored many years prior to diagnosis. We defined our conditions for compensation as non-linear longitudinal trajectories of brain activity and performance in the presence of linear neuronal degeneration and applied our model of compensation to a large longitudinal cohort of premanifest and early-stage Huntington’s disease patients from the multisite Track-On HD study. Focusing on cognitive and motor networks, we integrated progressive volume loss, task and resting state functional MRI and cognitive and motor behaviour across three sequential phases of neurodegenerative disease progression, adjusted for genetic disease load. Multivariate linear mixed models were fitted and trajectories for each variable tested. Our conceptualization of compensation was partially realized across certain motor and cognitive networks at differing levels. We found several significant network trends that were more complex than that hypothesized in our model. These trends suggest changes to our theoretical model where the network effects are delayed relative to performance effects. There was evidence of compensation primarily in the prefrontal component of the cognitive network, with increased effective connectivity between the left and right dorsolateral prefrontal cortex. Having developed an operational model for the explicit testing of longitudinal compensation in neurodegeneration, it appears that general patterns of our framework are consistent with the empirical data. With the proposed modifications, our operational model of compensation can be used to test for both cross-sectional and longitudinal compensation in neurodegenerative disease with similar patterns to Huntington’s disease.
机译:尽管存在结构性脑病理,但神经变性的初始阶段通常以正常的认知和运动能力水平为标志。人们普遍认为补偿是造成这种保留行为的原因,但是尽管这种概念明显简单,但事实证明,证明这种现象并将其与疾病相关的病理学区别非常困难。最近,我们开发了一种补偿模型,大脑激活,行为和病理学(理解补偿的关键要素)在进展的三个阶段具有特定的纵向轨迹。在这里,我们通过测试神经变性中随时间的补偿是否存在来凭经验验证我们的显式数学模型。亨廷顿舞蹈病是单基因且完全渗透的,是检查神经变性纵向补偿的理想模型,因此可以在诊断之前多年监测疾病的进展和潜在的补偿。我们将补偿条件定义为在线性神经元变性的情况下脑部活动和表现的非线性纵向轨迹,并将补偿模型应用于多站点Track-On的大量预后和早期Huntington病患者的纵向队列高清学习。着重于认知和运动网络,我们将神经退行性疾病进展的三个连续阶段(针对遗传疾病负荷进行了调整)整合了进行性体积损失,任务和休息状态功能MRI以及认知和运动行为。拟合多元线性混合模型,并测试每个变量的轨迹。我们的补偿概念在不同水平的某些运动和认知网络中部分实现。我们发现了几个重要的网络趋势,这些趋势比我们的模型中假设的更为复杂。这些趋势表明我们的理论模型发生了变化,其中网络效应相对于绩效效应有所延迟。有证据表明,补偿主要发生在认知网络的前额叶部分,左,右背外侧前额叶皮层之间的有效连接性增加。已经开发了用于神经变性的纵向补偿的明确测试的操作模型,看来我们框架的一般模式与经验数据是一致的。通过提出的修改方案,我们的补偿操作模型可用于测试神经退行性疾病中与亨廷顿氏病相似的横断面和纵向补偿。

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