Zheng Yuhong, Wang Peng, Yao Chi, Wang Jinghua, Wang Jinhui, Xue Shao-Wei
Center for Cognition and Brain Disorders/Department of Neurology, The Affiliated Hospital, Hangzhou Normal University, Hangzhou, Zhejiang, China.
Institute for Brain Research and Rehabilitation, South China Normal University, Guangzhou, China.
Hum Brain Mapp. 2025 Jun 1;46(8):e70249. doi: 10.1002/hbm.70249.
Concerns have arisen regarding the heterogeneity of patients with major depressive disorder (MDD), particularly when the varying disease progression trajectories among individuals are overlooked. Recognizing these distinct trajectories is crucial for personalized assessments and accurate disease progression predictions in MDD, posing a significant challenge in clinical practice. We utilized a data-driven subtype and stage inference (SuStaIn) model to infer trajectories based on cross-sectional amplitude of low-frequency fluctuations (ALFF) derived from resting-state functional magnetic resonance imaging data of 833 patients with MDD and 834 healthy controls. Based on distinct trajectories, two subtypes of MDD were identified: Subtype 1 showed declining ALFF from paracentral lobule (PCL) to thalamus to medial orbitofrontal cortex (OFCmed), with higher core depression scores and gray matter atrophy, whereas Subtype 2 had an opposing trajectory, with initial OFCmed ALFF decrease gradually extending to PCL. Our findings contribute to a better understanding of MDD heterogeneity and facilitate precise disease progression predictions.
对于重度抑郁症（MDD）患者的异质性已经出现了担忧，尤其是当个体之间不同的疾病进展轨迹被忽视时。认识到这些不同的轨迹对于MDD的个性化评估和准确的疾病进展预测至关重要，这在临床实践中构成了重大挑战。我们利用数据驱动的亚型和阶段推断（SuStaIn）模型，基于从833例MDD患者和834例健康对照的静息态功能磁共振成像数据中得出的低频波动的横断面振幅（ALFF）来推断轨迹。基于不同的轨迹，确定了MDD的两种亚型：亚型1显示从中央旁小叶（PCL）到丘脑再到眶额内侧皮质（OFCmed）的ALFF下降，核心抑郁评分和灰质萎缩较高，而亚型2有相反的轨迹，最初OFCmed的ALFF下降逐渐扩展到PCL。我们的研究结果有助于更好地理解MDD的异质性，并促进精确的疾病进展预测。
