Define and characterize the anhedonia in major depressive disorder: An explorative study.

BACKGROUND

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?

METHODS

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.

RESULTS

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.

CONCLUSION

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.

TRIAL REGISTRATION

TNDTAD study, NCT03294525; TOSD study, NCT03148522.