Department of Psychiatry and Psychotherapy, Technische Universität München (TUM), München, Germany.
TUM-Neuroimaging Center (TUM-NIC), Klinikum Rechts der Isar, München, Germany.
Hum Brain Mapp. 2021 Sep;42(13):4134-4143. doi: 10.1002/hbm.24517. Epub 2019 Jan 30.
A prominent finding of postmortem and molecular imaging studies on Alzheimer's disease (AD) is the accumulation of neuropathological proteins in brain regions of the default mode network (DMN). Molecular models suggest that the progression of disease proteins depends on the directionality of signaling pathways. At network level, effective connectivity (EC) reflects directionality of signaling pathways. We hypothesized a specific pattern of EC in the DMN of patients with AD, related to cognitive impairment. Metabolic connectivity mapping is a novel measure of EC identifying regions of signaling input based on neuroenergetics. We simultaneously acquired resting-state functional MRI and FDG-PET data from patients with early AD (n = 35) and healthy subjects (n = 18) on an integrated PET/MR scanner. We identified two distinct subnetworks of EC in the DMN of healthy subjects: an anterior part with bidirectional EC between hippocampus and medial prefrontal cortex and a posterior part with predominant input into medial parietal cortex. Patients had reduced input into the medial parietal system and absent input from hippocampus into medial prefrontal cortex (p < 0.05, corrected). In a multiple linear regression with unimodal imaging and EC measures (F = 5.63, p = 0.002, r = 0.47), we found that EC (β = 0.45, p = 0.012) was stronger associated with cognitive deficits in patients than any of the PET and fMRI measures alone. Our approach indicates specific disruptions of EC in the DMN of patients with AD and might be suitable to test molecular theories about downstream and upstream spreading of neuropathology in AD.
阿尔茨海默病(AD)的尸检和分子影像学研究的一个突出发现是,神经病理学蛋白在默认模式网络(DMN)的大脑区域积累。分子模型表明,疾病蛋白的进展取决于信号通路的方向性。在网络层面上,有效连接(EC)反映了信号通路的方向性。我们假设 AD 患者 DMN 的 EC 存在特定模式,与认知障碍有关。代谢连接图是一种新的 EC 测量方法,它基于神经能量学来识别信号输入的区域。我们在集成的 PET/MR 扫描仪上同时从早期 AD 患者(n = 35)和健康受试者(n = 18)采集静息状态功能 MRI 和 FDG-PET 数据。我们在健康受试者的 DMN 中确定了两个不同的 EC 子网:一个具有海马体和内侧前额叶皮质之间双向 EC 的前部分,以及一个具有向内侧顶叶皮质主要输入的后部分。患者的内侧顶叶系统输入减少,海马体到内侧前额叶皮质的输入缺失(p < 0.05,校正)。在一个具有单模态成像和 EC 测量的多元线性回归中(F = 5.63,p = 0.002,r = 0.47),我们发现 EC(β = 0.45,p = 0.012)与患者的认知缺陷的相关性比任何单一的 PET 和 fMRI 测量都更强。我们的方法表明 AD 患者 DMN 中 EC 存在特定的破坏,可能适合测试关于 AD 中神经病理学下游和上游扩散的分子理论。