双相障碍和精神分裂症患者脑白质网络聚类系数差异研究  

Differences in clustering coefficient of brain structure networks between bipolar disorder and schizophrenia patients

作　　者：花玲玲[1] 史家波[1] 阎锐[1] 汤浩[1] 姚志剑[1] 刘海燕[1] HUA Ling-ling;SHI Jia-bo;YAN Rui;TANG hao;YAO Zhi-jian;LIU Hai-yan(Department of Psychiatry,The Affiliated Brain Hospital of Nanjing Medical University,Nanjing 210029,China)

机构地区：[1]南京医科大学附属脑科医院精神科,210029

出　　处：《临床精神医学杂志》2024年第5期349-353,共5页Journal of Clinical Psychiatry

基　　金：国家自然科学基金(82151315,82271568,82101573,82301718);江苏精神疾病医学创新中心(CXZX202226);江苏省重点研发计划专项(BE2019675);苏州市社会发展科技创新重点项目(2022SS04);南京市科技发展计划重点项目(ZKX22043)。

摘　　要：目的:探讨双相障碍与精神分裂症患者脑白质结构网络聚类系数的差异性,并评价聚类属性指标在识别两种疾病中的预测能力。方法:对2012年12月至2014年12月南京脑科医院精神科入组的37例住院患者(患者组)进行≥9年的随访。复核诊断无变化的双相障碍患者18例、精神分裂患者19例及30名健康对照纳入统计分析,在SPSS 26.0中,对一般临床资料、脑结构网络聚类属性值进行3组间方差分析及受试者工作曲线(receiver operation characteristic,ROC)绘制。结果:与健康组相比,患者组在左侧额下回眶部、右侧颞上回的聚类系数升高;患者组间比较,精神分裂症患者在右侧颞中回的聚类系数高于双相障碍组,差异有统计学意义(P<0.05,多重比较校正)。以右侧颞中回网络聚类系数作为描绘ROC曲线,两组疾病的识别率达95%。结论:脑网络聚类系数可以作为一个潜在的影像学生物标志物识别双相障碍与精神分裂症。Objective:To explore the differences in clustering coefficient of brain structure networks between bipolar disorder and schizophrenia patients,and evaluate the predictive ability of clustering coefficient in identifying diseases.Method:A total of 37 participants were enrolled in the psychiatric department of Nanjing brain hospital from December 2012 to December 2014 during a follow-up period of≥9 years.Eighteen patients with bipolar disorder,nineteen patients with schizophrenia,who had no changes in the review examination diagnosis,and 30 healthy controls were included in the statistical analysis.In SPSS 26.0,the variances between three groups and receiver operation characteristic(ROC)were plotted for general clinical data and brain structural network clustering attribute values.Results:Compared with the healthy control group,the clustering coefficient of the patient group increased in the left inferior frontal gyrus and right superior temporal gyrus;compared between patient groups,the clustering coefficient of schizophrenia patients in the right temporal gyrus was higher than that in the bipolar depression group,and the difference was statistically significant(P<0.05,family wise error correction).Using the clustering coefficient of the right middle temporal gyrus network as the depiction of the ROC curve,the recognition rate of the two groups of diseases reached 95%.Conclusion:The clustering coefficient of brain networks can serve as a potential imaging biomarker to identify bipolar disorder and schizophrenia.

关 键 词：双相障碍 精神分裂症 弥散张量成像 聚类系数 

分 类 号：R749.4[医药卫生—神经病学与精神病学]