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2型糖尿病患者异常的动态功能网络连接性。

Aberrant dynamic functional network connectivity in type 2 diabetes mellitus individuals.

作者信息

Lyu Wenjiao, Wu Ye, Huang Haoming, Chen Yuna, Tan Xin, Liang Yi, Ma Xiaomeng, Feng Yue, Wu Jinjian, Kang Shangyu, Qiu Shijun, Yap Pew-Thian

机构信息

Department of Radiology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong China.

Department of Radiology and Biomedical Research Imaging Center (BRIC), University of North Carolina at Chapel Hill, Chapel Hill, NC USA.

出版信息

Cogn Neurodyn. 2023 Dec;17(6):1525-1539. doi: 10.1007/s11571-022-09899-8. Epub 2022 Nov 21.

DOI:10.1007/s11571-022-09899-8
PMID:37969945
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10640562/
Abstract

An increasing number of recent brain imaging studies are dedicated to understanding the neuro mechanism of cognitive impairment in type 2 diabetes mellitus (T2DM) individuals. In contrast to efforts to date that are limited to static functional connectivity, here we investigate abnormal connectivity in T2DM individuals by characterizing the time-varying properties of brain functional networks. Using group independent component analysis (GICA), sliding-window analysis, and k-means clustering, we extracted thirty-one intrinsic connectivity networks (ICNs) and estimated four recurring brain states. We observed significant group differences in fraction time (FT) and mean dwell time (MDT), and significant negative correlation between the Montreal Cognitive Assessment (MoCA) scores and FT/MDT. We found that in the T2DM group the inter- and intra-network connectivity decreases and increases respectively for the default mode network (DMN) and task-positive network (TPN). We also found alteration in the precuneus network (PCUN) and enhanced connectivity between the salience network (SN) and the TPN. Our study provides evidence of alterations of large-scale resting networks in T2DM individuals and shed light on the fundamental mechanisms of neurocognitive deficits in T2DM.

摘要

最近,越来越多的脑成像研究致力于了解2型糖尿病(T2DM)患者认知障碍的神经机制。与迄今为止仅限于静态功能连接的研究不同,我们通过表征脑功能网络的时变特性来研究T2DM患者的异常连接。使用组独立成分分析(GICA)、滑动窗口分析和k均值聚类,我们提取了31个内在连接网络(ICN)并估计了四种反复出现的脑状态。我们观察到分数时间(FT)和平均停留时间(MDT)存在显著的组间差异,并且蒙特利尔认知评估(MoCA)得分与FT/MDT之间存在显著负相关。我们发现,在T2DM组中,默认模式网络(DMN)和任务阳性网络(TPN)的网络间和网络内连接分别减少和增加。我们还发现楔前叶网络(PCUN)发生改变,突显网络(SN)与TPN之间的连接增强。我们的研究为T2DM患者大规模静息网络的改变提供了证据,并揭示了T2DM神经认知缺陷的基本机制。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a10/10640562/e61280f3ede1/11571_2022_9899_Fig7_HTML.jpg
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IDF Diabetes Atlas: Global, regional and country-level diabetes prevalence estimates for 2021 and projections for 2045.国际糖尿病联盟(IDF)糖尿病地图集:2021 年全球、区域和国家糖尿病患病率估算值以及 2045 年预测值。
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