Sun Yunkai, Xie An, Fang Yehong, Chen Haobo, Li Ling, Tang Jinsong, Liao Yanhui
Department of Psychiatry, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, PR China.
Department of Radiology, The People's Hospital of Hunan Province, Changsha, Hunan, PR China.
Transl Psychiatry. 2024 Jul 17;14(1):293. doi: 10.1038/s41398-024-03007-6.
Electronic cigarettes (e-cigs) use, especially among youngsters, has been on the rise in recent years. However, little is known about the long-term effects of the use of e-cigs on brain functional activity. We acquired the resting-state functional magnetic resonance imaging (rs-fMRI) data from 93 e-cigs users with nicotine dependence and 103 health controls (HC). The local synchronization was analyzed via the regional homogeneity (ReHo) method at voxel-wise level. The functional connectivity (FC) between the nucleus accumbens (NAcc), the ventral tegmental area (VTA), and the insula was calculated at ROI-wise level. The support vector machining classification model based on rs-fMRI measures was used to identify e-cigs users from HC. Compared with HC, nicotine-dependent e-cigs users showed increased ReHo in the right rolandic operculum and the right insula (p < 0.05, FDR corrected). At the ROI-wise level, abnormal FCs between the NAcc, the VTA, and the insula were found in e-cigs users compared to HC (p < 0.05, FDR corrected). Correlation analysis found a significant negative correlation between ReHo in the left NAcc and duration of e-cigs use (r = -0.273, p = 0.008, FDR corrected). The following support vector machine model based on significant results of rs-fMRI successfully differentiates chronic e-cigs users from HC with an accuracy of 73.47%, an AUC of 0.781, a sensitivity of 67.74%, and a specificity of 78.64%. Dysregulated spontaneous activity and FC of addiction-related regions were found in e-cigs users with nicotine dependence, which provides crucial insights into the prevention of its initial use and intervention for quitting e-cigs.
近年来，电子烟的使用呈上升趋势，尤其是在年轻人当中。然而，关于使用电子烟对大脑功能活动的长期影响，我们却知之甚少。我们获取了93名有尼古丁依赖的电子烟使用者和103名健康对照者（HC）的静息态功能磁共振成像（rs-fMRI）数据。通过基于体素水平的局部一致性（ReHo）方法分析局部同步性。在感兴趣区（ROI）水平计算伏隔核（NAcc）、腹侧被盖区（VTA）和脑岛之间的功能连接（FC）。基于rs-fMRI测量的支持向量机分类模型用于从HC中识别电子烟使用者。与HC相比，有尼古丁依赖的电子烟使用者右侧中央后回盖和右侧脑岛的ReHo增加（p < 0.05，经FDR校正）。在ROI水平上，与HC相比，电子烟使用者的NAcc、VTA和脑岛之间存在异常的FC（p < 0.05，经FDR校正）。相关性分析发现左侧NAcc的ReHo与电子烟使用时长之间存在显著负相关（r = -0.273，p = 0.008，经FDR校正）。基于rs-fMRI显著结果的支持向量机模型成功地将慢性电子烟使用者与HC区分开来，准确率为73.47%，曲线下面积（AUC）为0.781，灵敏度为67.74%，特异性为78.64%。在有尼古丁依赖的电子烟使用者中发现成瘾相关区域的自发活动和FC失调，这为预防其初次使用和戒烟干预提供了关键见解。
