一项巢式病例对照研究方案：识别青少年亚临床抑郁和气滞体质进展为重度抑郁症的神经影像生物标志物。

Protocol for a nested case-control study: identifying neuroimaging biomarkers for the progression of subclinical depression and qi-stagnation constitution to major depressive disorder in adolescents.

作者信息

Wang Jing, Zhang Chengfeng, Zhang Yueqi, Liu Yuanyuan, Zhang Jingli, Fang Xingwei, Xia Wangyang, Xie Yanzhao, Lan Zhongli, Wang Jinhui, Lu Min, Chen Jun

机构信息

Institute for Brain Research and Rehabilitation, South China Normal University, Guangzhou, China.

Department of Radiology, Guangdong Provincial Hospital of Chinese Medicine, Zhuhai, China.

出版信息

Front Psychiatry. 2025 Jan 21;15:1516846. doi: 10.3389/fpsyt.2024.1516846. eCollection 2024.

DOI:10.3389/fpsyt.2024.1516846

PMID:39906680

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11790624/

Abstract

BACKGROUND

Major depressive disorder (MDD) frequently results in suboptimal treatment outcomes and elevated recurrence rate, with patients frequently engaging in self-harm and suicidal behavior, thereby placing a heavy burden on families and society. Specifically, MDD in adolescents is linked to an elevated suicide risk. Thus, early identification and intervention is crucial for adolescents at high risk for developing MDD. Subclinical depression (SD), characterized by depressive symptoms that do not meet the full criteria for MDD, substantially increases the risk of developing MDD. According to Traditional Chinese Medicine body constitution theory, Qi-stagnation constitution (QSC) is also considered a significant risk factor for the progression to MDD. This study protocol aims to identify neuroimaging biomarkers for the progression from adolescents with SD and QSC to those with MDD, facilitating early intervention strategies.

METHODS AND ANALYSIS

This nested case-control study includes both longitudinal follow-up and cross-sectional comparison. Three hundred first-year senior high school students diagnosed with SD and QSC will be recruited. The 300 adolescents will undergo rs-fMRI scans at baseline and again after one year. We then divide the 300 adolescents with SD and QSC into two groups based on whether they progress to MDD after one year. Functional brain networks will be constructed based on 400 regions of interest (ROIs). Neuroimaging measures, including regional homogeneity and low-frequency fluctuation for each ROI, as well as graph-based global efficiency, nodal efficiency, and nodal centrality from the binary networks, will then be calculated. Finally, differences in these neuroimaging measures between the two groups at baseline will be analyzed to identify biomarkers that can predict the progression from adolescents with SD and QSC to those with MDD.

STUDY REGISTRATION

This study protocol does not involve clinical interventions and is classified as an observational study, so it was not subject to prior registration.

摘要

背景

重度抑郁症（MDD）常常导致治疗效果欠佳和复发率升高，患者频繁出现自我伤害和自杀行为，给家庭和社会带来沉重负担。具体而言，青少年MDD与自杀风险升高有关。因此，早期识别和干预对于有发展为MDD高风险的青少年至关重要。亚临床抑郁症（SD）以不符合MDD完整标准的抑郁症状为特征，会大幅增加发展为MDD的风险。根据中医体质理论，气郁体质（QSC）也被认为是进展为MDD的一个重要风险因素。本研究方案旨在识别从患有SD和QSC的青少年进展为MDD的神经影像学生物标志物，以促进早期干预策略。

方法与分析

这项嵌套病例对照研究包括纵向随访和横断面比较。将招募300名被诊断为患有SD和QSC的高一学生。这300名青少年将在基线时和一年后再次接受静息态功能磁共振成像（rs-fMRI）扫描。然后，我们根据这300名患有SD和QSC的青少年在一年后是否进展为MDD将他们分为两组。将基于400个感兴趣区域（ROI）构建脑功能网络。然后将计算神经影像学指标，包括每个ROI的局部一致性和低频波动，以及二元网络的基于图论的全局效率、节点效率和节点中心性。最后，将分析两组在基线时这些神经影像学指标的差异，以识别能够预测从患有SD和QSC的青少年进展为MDD的生物标志物。