Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Department of CT & MRI, The First Affiliated Hospital, College of Medicine, Shihezi University, Shihezi, China.
J Neurosci Res. 2024 May;102(5):e25357. doi: 10.1002/jnr.25357.
Aging is widely acknowledged as the primary risk factor for brain degeneration, with Parkinson's disease (PD) tending to follow accelerated aging trajectories. We aim to investigate the impact of structural brain aging on the temporal dynamics of a large-scale functional network in PD. We enrolled 62 PD patients and 32 healthy controls (HCs). The level of brain aging was determined by calculating global and local brain age gap estimates (G-brainAGE and L-brainAGE) from structural images. The neural network activity of the whole brain was captured by identifying coactivation patterns (CAPs) from resting-state functional images. Intergroup differences were assessed using the general linear model. Subsequently, a spatial correlation analysis between the L-brainAGE difference map and CAPs was conducted to uncover the anatomical underpinnings of functional alterations. Compared to HCs (-3.73 years), G-brainAGE was significantly higher in PD patients (+1.93 years), who also exhibited widespread elevation in L-brainAGE. G-brainAGE was correlated with disease severity and duration. PD patients spent less time in CAPs involving activated default mode and the fronto-parietal network (DMN-FPN), as well as the sensorimotor and salience network (SMN-SN), and had a reduced transition frequency from other CAPs to the DMN-FPN and SMN-SN CAPs. Furthermore, the pattern of localized brain age acceleration showed spatial similarities with the SMN-SN CAP. Accelerated structural brain aging in PD adversely affects brain function, manifesting as dysregulated brain network dynamics. These findings provide insights into the neuropathological mechanisms underlying neurodegenerative diseases and imply the possibility of interventions for modifying PD progression by slowing the brain aging process.
衰老是公认的大脑退化的主要风险因素,帕金森病(PD)往往遵循加速衰老的轨迹。我们旨在研究结构大脑老化对 PD 中大规模功能网络的时间动态的影响。我们招募了 62 名 PD 患者和 32 名健康对照组(HCs)。通过从结构图像计算全局和局部大脑年龄差距估计值(G-brainAGE 和 L-brainAGE)来确定大脑老化的程度。通过识别静息状态功能图像中的共激活模式(CAPs)来捕获整个大脑的神经网络活动。使用一般线性模型评估组间差异。随后,对 L-brainAGE 差异图和 CAPs 之间的空间相关性进行分析,以揭示功能改变的解剖基础。与 HCs(-3.73 岁)相比,PD 患者的 G-brainAGE 明显更高(+1.93 岁),他们的 L-brainAGE 也广泛升高。G-brainAGE 与疾病严重程度和持续时间相关。PD 患者在涉及激活默认模式和额顶网络(DMN-FPN)以及感觉运动和突显网络(SMN-SN)的 CAP 中花费的时间更少,并且从其他 CAP 到 DMN-FPN 和 SMN-SN CAP 的转换频率降低。此外,局部大脑加速老化的模式与 SMN-SN CAP 具有空间相似性。PD 中加速的结构大脑老化对大脑功能产生不利影响,表现为大脑网络动态失调。这些发现为神经退行性疾病的神经病理学机制提供了深入的了解,并暗示通过减缓大脑老化过程来改变 PD 进展的干预措施的可能性。