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首发未用药的重性抑郁障碍患者异常的动态功能网络连接。

Abnormal dynamic functional network connectivity in first-episode, drug-naïve patients with major depressive disorder.

机构信息

Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin 300222, China.

Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China.

出版信息

J Affect Disord. 2022 Dec 15;319:336-343. doi: 10.1016/j.jad.2022.08.072. Epub 2022 Sep 6.

Abstract

Dynamic functional network connectivity (dFNC) could capture temporal features of spontaneous brain activity during MRI scanning, and it might be a powerful tool to examine functional brain network alters in major depressive disorder (MDD). Therefore, this study investigated the changes in temporal properties of dFNC of first-episode, drug-naïve patients with MDD. A total of 48 first-episode, drug-naïve MDD patients and 46 age- and gender-matched healthy controls were recruited in this study. Sliding windows were implied to construct dFNC. We assessed the relationships between altered dFNC temporal properties and depressive symptoms. Receiver operating characteristic (ROC) curve analyses were used to examine the diagnostic performance of these altered temporal properties. The results showed that patients with MDD have more occurrences and spent more time in a weak connection state, but with fewer occurrences and shorter dwell time in a strong connection state. Importantly, the fractional time and mean dwell time of state 2 was negatively correlated with Hamilton Depression Rating Scale (HDRS) scores. ROC curve analysis demonstrated that these temporal properties have great identified power including the fractional time and mean dwell time in state 2, and the AUC is 0.872, 0.837, respectively. The AUC of the combination of fractional time and mean dwell time in state 2 with age, gender is 0.881. Our results indicated the temporal properties of dFNC are altered in first-episode, drug-naïve patients with MDD, and these changes' properties could serve as a potential biomarker in MDD.

摘要

动态功能网络连接(dFNC)可以捕捉磁共振成像扫描期间自发脑活动的时间特征,它可能是检查重性抑郁障碍(MDD)患者功能性大脑网络改变的有力工具。因此,本研究探讨了首发、未用药的 MDD 患者 dFNC 的时间特征变化。本研究共纳入 48 例首发、未用药的 MDD 患者和 46 名年龄和性别匹配的健康对照者。通过滑动窗口构建 dFNC。我们评估了改变的 dFNC 时间特性与抑郁症状之间的关系。采用受试者工作特征(ROC)曲线分析评估这些改变的时间特性的诊断性能。结果显示,MDD 患者出现弱连接状态的次数更多,持续时间更长,而出现强连接状态的次数更少,持续时间更短。重要的是,状态 2 的分数时间和平均停留时间与汉密尔顿抑郁评定量表(HDRS)评分呈负相关。ROC 曲线分析表明,这些时间特性具有很好的识别能力,包括状态 2 的分数时间和平均停留时间,AUC 分别为 0.872、0.837。状态 2 的分数时间和平均停留时间与年龄、性别组合的 AUC 为 0.881。我们的结果表明,首发、未用药的 MDD 患者的 dFNC 时间特性发生改变,这些改变的特性可能成为 MDD 的潜在生物标志物。

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