Ni Weiwei, Liu Weiyin Vivian, Li Mingrui, Wei Shouchao, Xu Xuanzi, Huang Shutong, Zhu Lanhui, Wang Jieru, Wen Fengling, Zhou Hailing
Physical Examination Centre, Central People's Hospital of Zhanjiang, Zhanjiang, China.
MR Research, GE Healthcare, Beijing, China.
Front Neurosci. 2025 Jan 28;19:1472010. doi: 10.3389/fnins.2025.1472010. eCollection 2025.
Type 2 diabetes mellitus (T2DM) accelerates brain aging and disrupts brain functional network connectivity, though the specific mechanisms remain unclear. This study aimed to investigate T2DM-driven alterations in brain functional network connectivity and topology.
Eighty-five T2DM patients and 67 healthy controls (HCs) were included. All participants underwent clinical, neuropsychological, and laboratory tests, followed by MRI examinations, including resting-state functional magnetic resonance imaging (rs-fMRI) and three-dimensional high-resolution T1-weighted imaging (3D-T1WI) on a 3.0 T MRI scanner. Post-image preprocessing, brain functional networks were constructed using the Dosenbach atlas and analyzed with the DPABI-NET toolkit through graph theory.
In T2DM patients, functional connectivity within and between the default mode network (DMN), frontal parietal network (FPN), subcortical network (SCN), ventral attention network (VAN), somatosensory network (SMN), and visual network (VN) was significantly reduced compared to HCs. Conversely, two functional connections within the VN and between the DMN and SMN were significantly increased. Global network topology analysis showed an increased shortest path length and decreased clustering coefficient, global efficiency, and local efficiency in the T2DM group. MoCA scores were negatively correlated with the shortest path length and positively correlated with global and local efficiency in the T2DM group. Node network topology analysis indicated reduced clustering coefficient, degree centrality, eigenvector centrality, and nodal efficiency in multiple nodes in the T2DM group. MoCA scores positively correlated with clustering coefficient and nodal efficiency in the bilateral precentral gyrus in the T2DM group.
This study demonstrated significant abnormalities in connectivity and topology of large-scale brain functional networks in T2DM patients. These findings suggest that brain functional network connectivity and topology could serve as imaging biomarkers, providing insights into the underlying neuropathological processes associated with T2DM-related cognitive impairment.
2型糖尿病（T2DM）会加速大脑衰老并破坏脑功能网络连接，但其具体机制仍不清楚。本研究旨在调查T2DM驱动的脑功能网络连接和拓扑结构的改变。
纳入85例T2DM患者和67例健康对照（HCs）。所有参与者均接受临床、神经心理学和实验室检查，随后进行MRI检查，包括在3.0 T MRI扫描仪上进行静息态功能磁共振成像（rs-fMRI）和三维高分辨率T1加权成像（3D-T1WI）。图像预处理后，使用多森巴赫图谱构建脑功能网络，并通过图论用DPABI-NET工具包进行分析。
与HCs相比，T2DM患者默认模式网络（DMN）、额顶网络（FPN）、皮质下网络（SCN）、腹侧注意网络（VAN）、体感网络（SMN）和视觉网络（VN）内部及之间的功能连接显著降低。相反，VN内部以及DMN和SMN之间的两个功能连接显著增加。全局网络拓扑分析显示，T2DM组的最短路径长度增加，聚类系数、全局效率和局部效率降低。在T2DM组中，蒙特利尔认知评估量表（MoCA）评分与最短路径长度呈负相关，与全局和局部效率呈正相关。节点网络拓扑分析表明，T2DM组多个节点的聚类系数、度中心性、特征向量中心性和节点效率降低。在T2DM组中，MoCA评分与双侧中央前回的聚类系数和节点效率呈正相关。
本研究证明T2DM患者大规模脑功能网络的连接性和拓扑结构存在显著异常。这些发现表明，脑功能网络连接性和拓扑结构可作为影像学生物标志物，为与T2DM相关的认知障碍相关的潜在神经病理过程提供见解。
