Jiang Ping, Sun Jiayu, Zhou Xiaobo, Lu Lu, Li Lei, Xu Jiajun, Huang Xiaoqi, Li Jing, Gong Qiyong
Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China.
Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu, China.
Drug Alcohol Depend Rep. 2022 May 14;3:100065. doi: 10.1016/j.dadr.2022.100065. eCollection 2022 Jun.
The global prevalence of methamphetamine use disorder (MUD) and the associated economic burden are increasing, but effective pharmacological treatment is lacking. Therefore, understanding the neurological mechanisms underlying MUD is essential to develop clinical strategies and improve patient care. Individuals with MUD can show static brain network abnormalities during the resting state, but their alterations in dynamic functional network connectivity (dFNC) are unclear.
In this study, we obtained resting-state functional magnetic resonance imaging from 42 males with MUD and 41 healthy controls. Sliding-window and spatial independent component analyses with a -means clustering algorithm were used to assess the recurring functional connectivity states. The temporal properties of the dFNC, including fraction and dwelling time of each state and the number of transitions between different states, were compared between the two groups. In addition, the relationships between the temporal properties of the dFNC and clinical characteristics of the MUDs, including their anxiety and depressive symptoms, were further explored.
While the two groups shared many similarities in their dFNC, the occurrence of a highly integrated functional network state and a state featuring balanced integration and segregation in the MUDs significantly correlated with the total drug usage (Spearman's rho = 0.47, = 0.002) and duration of abstinence (Spearman's rho = 0.38, = 0.013), respectively.
The observed results in our study demonstrate that methamphetamines can affect dFNC, which may reflect the drug's influence on cognitive abilities. Our study justifies further studies into the effects of MUD on dynamic neural mechanisms.
甲基苯丙胺使用障碍（MUD）的全球患病率及相关经济负担正在增加，但缺乏有效的药物治疗。因此，了解MUD背后的神经机制对于制定临床策略和改善患者护理至关重要。患有MUD的个体在静息状态下可表现出静态脑网络异常，但其动态功能网络连接性（dFNC）的改变尚不清楚。
在本研究中，我们获取了42名患有MUD的男性和41名健康对照者的静息态功能磁共振成像。使用滑动窗口和空间独立成分分析以及均值聚类算法来评估反复出现的功能连接状态。比较了两组之间dFNC的时间特性，包括每个状态的分数和停留时间以及不同状态之间的转换次数。此外，进一步探讨了dFNC的时间特性与MUD临床特征（包括焦虑和抑郁症状）之间的关系。
虽然两组在dFNC方面有许多相似之处，但MUD中高度整合的功能网络状态和具有平衡整合与分离特征的状态的出现分别与总药物使用量（Spearman等级相关系数ρ = 0.47，P = 0.002）和禁欲持续时间（Spearman等级相关系数ρ = 0.38，P = 0.013）显著相关。
我们研究中观察到的结果表明，甲基苯丙胺可影响dFNC，这可能反映了该药物对认知能力的影响。我们的研究为进一步研究MUD对动态神经机制的影响提供了依据。
