Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China.
Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, China.
J Affect Disord. 2022 Sep 15;313:235-242. doi: 10.1016/j.jad.2022.06.082. Epub 2022 Jul 3.
Although anhedonia is a key symptom of major depressive disorder (MDD), there is neither a concise nor effective method to distinguish and define anhedonia in MDD. The current study attempts to answer two questions based on validating the Dimensional Anhedonia Rating Scale (DARS) in Chinese MDD patients: 1) whether anhedonia subgroup can be identified? 2) whether patients with anhedonia display unique psychosocial and clinical features?
In the discovery sample, 533 MDD patients and 124 healthy controls were recruited into a multicenter study. For replication, a further 112 first-episode, drug-naïve MDD patients were recruited. Latent profile analysis (LPA) was used to identify the latent subgroups based on their hedonic function measured by the DARS. According to the categorization, ROC curves were applied to find the cut-off value. Lasso regression was performed to characterize psychological and clinical features linked to anhedonia.
The data-driven approach identified and validated the anhedonia subgroup, and proposed that the cut-off value for distinguishing anhedonia was 28.5 based on the total score of DARS. Lasso regression demonstrated that melancholia, lower levels of positive affect and education, more severe depressive symptoms, older age were associated with anhedonia in MDD patients.
This study used a data-driven approach to propose a new and convenient method for distinguishing the anhedonia of MDD patients with unique psychological and clinical features. Identifying the subtype may contribute to pinpointing more specific biomarkers in shedding light on the mechanisms of anhedonia in MDD.
TNDTAD study, NCT03294525; TOSD study, NCT03148522.
尽管快感缺失是重性抑郁障碍（MDD）的一个关键症状，但目前既没有一种简洁又有效的方法来区分和定义 MDD 中的快感缺失。本研究试图通过验证中文版多维快感缺失评定量表（DARS）来回答两个问题：1）能否识别快感缺失亚组？2）是否存在快感缺失的患者表现出独特的心理社会和临床特征？
在发现样本中，共招募了 533 名 MDD 患者和 124 名健康对照者参加多中心研究。为了复制研究，进一步招募了 112 名首发、未用药的 MDD 患者。采用潜在剖面分析（LPA）根据 DARS 测量的愉悦功能对患者进行亚组分析。根据分类，应用 ROC 曲线确定区分快感缺失的截断值。采用套索回归分析来描述与快感缺失相关的心理和临床特征。
数据驱动的方法识别和验证了快感缺失亚组，并提出基于 DARS 总分，区分快感缺失的截断值为 28.5。套索回归显示，在 MDD 患者中，忧郁症、积极情绪和教育程度较低、抑郁症状更严重、年龄较大与快感缺失相关。
本研究采用数据驱动的方法提出了一种新的简便方法，用于区分具有独特心理和临床特征的 MDD 患者的快感缺失。识别亚组可能有助于确定更具体的生物标志物，从而深入了解 MDD 中快感缺失的机制。
TNDTAD 研究，NCT03294525；TOSD 研究，NCT03148522。
