抑郁患者一级亲属的结构网络改变及其与抑郁发病的相关性研究  

Structural network changes in first-degree relatives of depressed patients and their correlation with the onset of depression

作　　者：李洋 谢宇航 王冉超 蔡黎黎 咸娴 李月峰[1] Li Yang;Xie Yuhang;Wang Ranchao;Cai Lili;Xian Xian;Li Yuefeng(Department of Radiology,Affiliated Hospital of Jiangsu University,Zhenjiang 212001,China)

机构地区：[1]江苏大学附属医院医学影像科,镇江212001

出　　处：《中华神经科杂志》2022年第12期1381-1388,共8页Chinese Journal of Neurology

基　　金：国家自然科学基金(81871343);江苏省重点研发计划项目(BE2021693)。

摘　　要：目的:探究抑郁患者一级亲属的大脑结构网络变化及其与抑郁发作之间的关系。方法:前瞻性收集江苏大学附属医院2017年5月至2018年6月收治的抑郁患者健康一级亲属200名纳入研究,同期在社区通过问卷形式收集无抑郁家族史的健康对照者(HC/FH-组)50名作为健康对照。所有研究对象入组后均接受系统磁共振成像扫描和相关量表评估,随后进行长达3年的纵向随访(每3个月1次)。采用精神障碍诊断与统计手册第4版结构化访谈内容评估受试者在随访期间是否发生抑郁。将随访期间发生抑郁的一级亲属纳入一级亲属发生抑郁组(DD/FH+),而未发生抑郁的一级亲属则纳入一级亲属未发生抑郁组(HC/FH+)。通过24项汉密尔顿抑郁评定量表(HDRS)和Holmes和Rahe社会再适应评定量表分别评估受试者的抑郁严重程度和是否经历重大压力生活事件。构建Logistic回归模型探究脑结构网络属性对于抑郁的预测效能。基于Pearson相关分析探究受试者的脑结构网络与HDRS评分之间的相关性。结果:HC/FH-组(50例)、HC/FH+组(115例)以及DD/FH+组(21例)的支线连接(17.62±1.34、17.03±1.39、15.82±1.12,F=13.63,P<0.001)、全局效率(0.24±0.03、0.23±0.03、0.22±0.03,F=4.73,P=0.010)、右侧脑岛节点效率(0.20±0.02、0.21±0.01、0.20±0.01,F=4.62,P=0.011)、左侧海马节点效率(0.27±0.01、0.27±0.01、0.24±0.02,F=18.56,P<0.001)、左侧杏仁核节点效率(0.24±0.02、0.24±0.02、0.23±0.01,F=3.40,P=0.036)差异存在统计学意义。Logistic回归模型显示支线连接(OR=0.55,95%CI 0.38~0.78,P=0.001)和左侧海马节点效率(OR=0.58,95%CI 0.40~0.81,P<0.001)可以预测最终抑郁的发生情况,并且具有良好的预测效能,受试者工作特征曲线下面积分别为0.75、0.78。相关分析结果显示DD/FH+组基线时支线连接(r=-0.58,P=0.006)和左侧海马节点效率(r=-0.60,P=0.004)与其第一次随访时的HDRS评分相关。结论:抑郁患者的健Objective To explore the structural brain network changes in healthy first-degree relatives of depressed patients and their relationship with depressive episodes.Methods Prospectively,200 healthy first-degree relatives of depressed patients admitted to Jiangsu University Hospital from May 2017 to June 2018 were collected.Meanwhile,50 matched healthy controls without family history of depression(HC/FH-)were collected by questionnaire in the nearby community as study subjects.All study subjects underwent systemic magnetic resonance imaging scans and assessment of relevant scales after enrollment,followed by longitudinal follow-up(every 3 months)for up to 3 years.The diagnostic and statistical manual of mental disorders,4th edition,structured interview was used to assess whether the subjects became depressed during the follow-up period.First-degree relatives who experienced depression during follow-up were included in the group of first-degree relatives who experienced depression(DD/FH+),whereas first-degree relatives who did not experience depression were included in the group of first-degree relatives who did not experience depression(HC/FH+).Subjects′depression severity and whether they experienced major stressful life events were assessed by the 24-item Hamilton Depression Rating Scale(HDRS)and the Holmes and Rahe Social Readjustment Rating Scale,respectively.Correlations between subjects′brain structural networks and HDRS scores were explored based on Pearson correlation analysis.Logistic regression models were constructed to investigate the predictive efficacy of brain structural network attributes on depression.Results Significant group differences existed in the HC/FH-group(50 cases),HC/FH+group(115 cases),and DD/FH+group(21 cases)in feeder connectivity(17.62±1.34,17.03±1.39,15.82±1.12,F=13.63,P<0.001),global efficiency(0.24±0.03,0.23±0.03,0.22±0.03,F=4.73,P=0.010),right insula node efficiency(0.20±0.02,0.21±0.01,0.20±0.01,F=4.62,P=0.011),left hippocampal node efficiency(0.27±0.01,0.27±0.01,0.

关 键 词：抑郁症 一级亲属 结构网络 预测 

分 类 号：R749.4[医药卫生—神经病学与精神病学]