Zhang Tianyi, Luo Xiao, Zeng Qingze, Li Kaicheng, Chen Yi, Sun Yan, Leng Lumin, Peng Guoping, Zhang Minming, Liu Zhirong
Department of Neurology, The 2nd Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China.
Department of Radiology, The 2nd Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China.
J Alzheimers Dis. 2025 Jun;105(3):893-903. doi: 10.1177/13872877251333152. Epub 2025 May 4.
BackgroundSmoking, a modifiable risk factor for Alzheimer's disease (AD), is associated with impaired functional connectivity in resting-state networks (RSNs). This study investigates how smoking affects brain effective connectivity (EC).ObjectiveInvestigate smoking-associated EC alterations.MethodsWe identified 129 cognitively unimpaired (CU: 85 non-smokers, 44 smokers) and 84 mild cognitive impairment (MCI: 55 non-smokers, 29 smokers) participants. Granger causality analysis was used to calculate the directed interactions of information flows based on the seed areas of the default mode network, executive control network, and salience network. Mixed-effect analyses were performed to explore the interactive effects of smoking × cognitive status. Linear mixed-effects models evaluated correlations between EC values and longitudinal cognitive decline.ResultsMixed-effect analyses revealed significant interactive EC differences among 4 groups: (1) Smoking MCI individuals showed reduced EC from the left putamen to the frontoinsular cortex (FIC) compared to the smoking CU and non-smoking MCI group; (2) Non-smoking MCI subjects had lower EC from the dorsolateral prefrontal cortex (DLPFC) to the right inferior occipital gyrus (IOG) than non-smoking CU; (3) Smoking CU subjects exhibited increased EC from the DLPFC to the left middle cingulate cortex compared to the with the non-smoking CU and smoking MCI individuals. Additionally, EC and EC significantly predicted MMSE and ADNI_EF scores over time, respectively.ConclusionsSmoking distinctly impacts EC within RSNs and overall brain function in both MCI and CU individuals, potentially reducing functional compensation in MCI. These results support smoking cessation as part of AD management strategies.
背景
吸烟是阿尔茨海默病(AD)的一个可改变的风险因素,与静息态网络(RSNs)中的功能连接受损有关。本研究调查吸烟如何影响大脑有效连接(EC)。
目的
研究与吸烟相关的EC改变。
方法
我们确定了129名认知未受损(CU:85名非吸烟者,44名吸烟者)和84名轻度认知障碍(MCI:55名非吸烟者,29名吸烟者)参与者。基于默认模式网络、执行控制网络和突显网络的种子区域,使用格兰杰因果分析来计算信息流的定向相互作用。进行混合效应分析以探索吸烟×认知状态的交互作用。线性混合效应模型评估EC值与纵向认知衰退之间的相关性。
结果
混合效应分析显示4组之间存在显著的交互性EC差异:(1)与吸烟CU组和非吸烟MCI组相比,吸烟MCI个体从左侧壳核到额岛叶皮质(FIC)的EC降低;(2)非吸烟MCI受试者从背外侧前额叶皮质(DLPFC)到右侧枕下回(IOG)的EC低于非吸烟CU受试者;(3)与非吸烟CU组和吸烟MCI个体相比,吸烟CU受试者从DLPFC到左侧中央扣带回皮质的EC增加。此外,EC和EC分别显著预测了随时间变化的MMSE和ADNI_EF评分。
结论
吸烟对MCI和CU个体的RSNs内的EC和整体脑功能有明显影响,可能会降低MCI中的功能代偿能力。这些结果支持将戒烟作为AD管理策略的一部分。