Sun Jieping, Huang Huiyu, Dang Jinghan, Zhang Mengzhe, Niu Xiaoyu, Tao Qiuying, Kang Yimeng, Ma Longyao, Mei Bohui, Wang Weijian, Han Shaoqiang, Cheng Jingliang, Zhang Yong
Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China; Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Henan Province, China.
Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China; Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Henan Province, China.
Prog Neuropsychopharmacol Biol Psychiatry. 2025 Jan 10;136:111187. doi: 10.1016/j.pnpbp.2024.111187. Epub 2024 Nov 2.
Nicotine addiction (NA) is recognized as a significant neurobehavioral disorder that affects both individuals and society. It is suggested that alterations in functional network connectivity (FNC) within specific brain networks underlie its neurobiological basis.
The default mode network (DMN), executive control network (ECN), and salience network (SN) are identified using data from the Human Connectome Project. The study includes 47 individuals with NA and 35 normal controls (NC), all of whom undergo resting-state fMRI alongside smoking-related clinical assessments. A sliding window analysis is employed to assess connectivity metrics, including static functional network connectivity (FNC), standard deviation (SD), and coefficient of variation (CV), to compare information integration between the groups. Participants with NA are classified based on longitudinal changes in Fagerström Test for Nicotine Dependence (FTND) scores over six years into three categories: addiction tendency (AT), withdrawal tendency (WT), and stable tendency (ST). Correlation analyses are conducted to explore relationships between FNC abnormalities and clinical assessments.
Individuals with NA exhibit reduced static FNC (p_FDR = 0.029) between the dorsal DMN and the right ECN, accompanied by increased SD (p_FDR = 0.029) and CV (p_FDR = 0.029). A significant increase in SD (p_FDR = 0.049) is also observed in the dorsal DMN and left ECN. Correlations indicate that the SD of the dorsal DMN and right ECN relates to the pharmacological dimension of the Russell Smoking Reasons Questionnaire (RRSQ) scale (r = 0.416, p_FDR = 0.044), while CV correlates with changes in the FTND over six years (r = -0.391, p_FDR = 0.044) and the pharmacological dimension of the RRSQ scale (r = 0.402, p_FDR = 0.044). Post-hoc subgroup analyses reveal that these FNC intensity changes are present among WT patients (p_FDR < 0.05).
Alterations in brain network function within the DMN and ECN are suggested to precede behavioral changes in NA. These findings are interpreted as potential neurobiological markers of nicotine addiction.
尼古丁成瘾（NA）被认为是一种影响个人和社会的重要神经行为障碍。有研究表明，特定脑网络内的功能网络连接性（FNC）改变是其神经生物学基础。
利用人类连接体项目的数据识别默认模式网络（DMN）、执行控制网络（ECN）和突显网络（SN）。该研究纳入了47名尼古丁成瘾者和35名正常对照者（NC），所有参与者均接受静息态功能磁共振成像（fMRI）以及与吸烟相关的临床评估。采用滑动窗口分析来评估连接性指标，包括静态功能网络连接性（FNC）、标准差（SD）和变异系数（CV），以比较两组之间的信息整合情况。根据尼古丁依赖的Fagerström测试（FTND）分数在六年内的纵向变化，将尼古丁成瘾者分为三类：成瘾倾向（AT）、戒断倾向（WT）和稳定倾向（ST）。进行相关性分析以探讨FNC异常与临床评估之间的关系。
尼古丁成瘾者在背侧DMN与右侧ECN之间的静态FNC降低（p_FDR = 0.029），同时SD（p_FDR = 0.029）和CV（p_FDR = 0.029）增加。在背侧DMN与左侧ECN之间也观察到SD显著增加（p_FDR = 0.049）。相关性分析表明，背侧DMN与右侧ECN的SD与罗素吸烟原因问卷（RRSQ）量表的药理学维度相关（r = 0.416，p_FDR = 0.044），而CV与FTND在六年内的变化相关（r = -0.391，p_FDR = 0.044）以及RRSQ量表的药理学维度相关（r = 0.402，p_FDR = 0.044）。事后亚组分析显示，这些FNC强度变化在WT患者中存在（p_FDR < 0.05）。
DMN和ECN内的脑网络功能改变被认为先于尼古丁成瘾的行为变化。这些发现被解释为尼古丁成瘾的潜在神经生物学标志物。
