Laboratory Alzheimer's Neuroimaging & Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, via Pilastroni 4, 25125, Brescia, Italy.
Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy.
Brain Imaging Behav. 2020 Dec;14(6):2594-2605. doi: 10.1007/s11682-019-00212-6.
Age at symptom onset (AAO) underlies different Alzheimer's disease (AD) clinical variants: late-onset AD (LOAD) is characterized by memory deficits, while early-onset AD (EOAD) presents predominantly with non-memory symptoms. The involvement of different neural networks may explain these distinct clinical phenotypes. In this study, we tested the hypothesis of an early and selective involvement of neural networks based on AAO in AD. Twenty memory clinic patients with prodromal AD (i.e., mild cognitive impairment with an AD-like cerebrospinal fluid profile) and 30 healthy controls underwent a cognitive evaluation and a resting state functional MRI exam. Independent component analysis was performed to assess functional connectivity (FC) in the following networks: default mode, frontoparietal, limbic, visual, and sensorimotor. Patients were stratified into late-onset (pLOAD) and early-onset (pEOAD) prodromal AD according to the AAO and controls were stratified into younger and older groups accordingly. Decreased FC within the default mode and the limbic networks was observed in pLOAD, while pEOAD showed lower FC in the frontoparietal and visual networks. The sensorimotor network did not show differences between groups. A significant association was found between memory and limbic network FC in pLOAD, and between executive functions and frontoparietal network FC in pEOAD, although the latter association did not survive multiple comparison correction. Our findings indicate that aberrant connectivity in memory networks is associated with pLOAD, while networks underlying executive and visuo-spatial functions are affected in pEOAD. These findings are in line with the hypothesis that the pathophysiological mechanisms underlying EOAD and LOAD are distinct.
发病年龄（AAO）是阿尔茨海默病（AD）不同临床变异型的基础：晚发性 AD（LOAD）以记忆缺陷为特征，而早发性 AD（EOAD）主要表现为非记忆症状。不同神经网络的参与可能解释了这些不同的临床表型。在这项研究中，我们测试了基于 AAO 在 AD 中涉及不同神经网络的假设。20 名有前驱 AD（即具有 AD 样脑脊液特征的轻度认知障碍）的记忆诊所患者和 30 名健康对照者接受了认知评估和静息状态功能磁共振成像检查。进行独立成分分析以评估以下网络的功能连接（FC）：默认模式、额顶叶、边缘、视觉和感觉运动。根据 AAO 将患者分为晚发性（pLOAD）和早发性（pEOAD）前驱 AD，相应地将对照组分为年轻组和老年组。在 pLOAD 中观察到默认模式和边缘网络内的 FC 降低，而在 pEOAD 中观察到额顶叶和视觉网络内的 FC 降低。感觉运动网络在组间没有差异。在 pLOAD 中发现记忆和边缘网络 FC 之间存在显著相关性，在 pEOAD 中发现执行功能和额顶叶网络 FC 之间存在显著相关性，尽管后者的相关性在多次比较校正后不成立。我们的发现表明，记忆网络中异常的连接与 pLOAD 相关，而执行和视觉空间功能的网络则受到影响。这些发现与 EOAD 和 LOAD 的病理生理机制不同的假设一致。
