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

TITLE=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

JOURNAL=Frontiers in Psychiatry

VOLUME=Volume 15 - 2024

YEAR=2025

URL=https://www.frontiersin.org/journals/psychiatry/articles/10.3389/fpsyt.2024.1516846

DOI=10.3389/fpsyt.2024.1516846

ISSN=1664-0640

ABSTRACT=BackgroundMajor 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 analysisThis 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 registrationThis study protocol does not involve clinical interventions and is classified as an observational study, so it was not subject to prior registration.