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2型糖尿病患者视觉运动网络中大脑动力学失调及其与认知障碍的关系。

Dysregulated brain dynamics in the visualmotor network in type 2 diabetes patients and their relationship with cognitive impairment.

作者信息

Yu Ying, Hu Bo, Yu Xin-Wen, Cui Yan-Yan, Cao Xin-Yu, Ni Min-Hua, Li Si-Ning, Dai Pan, Sun Qian, Bai Xiao-Yan, Tong Yao, Jing Xiao-Rui, Yang Ai-Li, Liang Sheng-Ru, Du Li-Juan, Guo Shuo, Yan Lin-Feng, Gao Bin, Cui Guang-Bin

机构信息

Department of Radiology & Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu Hospital, Fourth Military Medical University (Air Force Medical University), 569 Xinsi Road, Xi'an, Shaanxi 710038, China.

Department of Endocrinology, Tangdu Hospital, Fourth Military Medical University (Air Force Medical University), 569 Xinsi Road, Xi'an, Shaanxi 710038, China.

出版信息

Brain Res Bull. 2025 May;224:111313. doi: 10.1016/j.brainresbull.2025.111313. Epub 2025 Mar 18.

Abstract

OBJECTIVE

Type 2 diabetes mellitus (T2DM) is a significant risk factor for mild cognitive impairment (MCI). Here, we identified a T2DM-specific effective connectivity (EC) network, the dynamic features of which could be used to distinguish T2DM patients with MCI from healthy controls (HC) and correlation with cognitive performance.

METHODS

Local and multicentered T2DM patients and matched HC who underwent functional magnetic resonance imaging were recruited. Their static and dynamic effective connectivity were compared. The relationships between connectome characteristics and cognitive performance were also evaluated.

RESULTS

The nodes of the T2DM-related static causality network included the anterior central gyrus, tail of the parahippocampal gyrus, posterior superior temporal sulcus, posterior central parietal lobe, posterior central gyrus and V5 region of the occipital lobe. The V5 region of the visual cortex was the core node. In the multicentered dataset, compared with the HC group, the T2DM with MCI group had significantly greater fractional window and mean dwell time. Fractional windows of the state, which was dominated by the interaction of the nodes from SomMot_Network, Limbic_Network, Default_Network, in the T2DM-specific network increased with poorer cognitive performance in T2DM with MCI patients.

CONCLUSION

Our findings provide insights into the neurobiological mechanisms of the cognitive impairment of T2DM patients from a dynamic network perspective, which may ultimately inform more targeted and effective strategies to prevent MCI.

摘要

目的

2型糖尿病(T2DM)是轻度认知障碍(MCI)的一个重要危险因素。在此,我们确定了一个T2DM特异性有效连接(EC)网络,其动态特征可用于区分患有MCI的T2DM患者与健康对照(HC),并与认知表现相关联。

方法

招募接受功能磁共振成像的本地和多中心T2DM患者及匹配的HC。比较他们的静态和动态有效连接。还评估了连接组特征与认知表现之间的关系。

结果

T2DM相关静态因果网络的节点包括中央前回、海马旁回尾部、颞上沟后部、中央后顶叶、中央后回和枕叶V5区。视觉皮层的V5区是核心节点。在多中心数据集中,与HC组相比,患有MCI的T2DM组具有显著更大的分数窗口和平均停留时间。在患有MCI的T2DM患者中,由SomMot_Network、Limbic_Network、Default_Network的节点相互作用主导的状态的分数窗口随着认知表现变差而增加。

结论

我们的研究结果从动态网络角度为T2DM患者认知障碍的神经生物学机制提供了见解,这可能最终为预防MCI提供更有针对性和有效的策略。

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