TY - JOUR PY - 2022// TI - Age of onset for major depressive disorder and its association with symptomatology JO - Journal of affective disorders A1 - Cui, Lvchun A1 - Wang, Yun A1 - Cao, Lan A1 - Wu, Zhiguo A1 - Peng, Daihui A1 - Chen, Jun A1 - Yang, Haichen A1 - Rong, Han A1 - Liu, Tiebang A1 - Fang, Yiru SP - ePub EP - ePub VL - ePub IS - ePub N2 - BACKGROUND: The age of onset (AOO) is a key factor for heterogeneity in major depressive disorder (MDD). Looking at the effect of AOO on symptomatology may improve clinical outcomes. This study aims to examine whether and how AOO affects symptomatology using a machine learning approach and latent profile analysis (LPA).

METHODS: The study enrolled 915 participants diagnosed with MDD from eight hospitals across China. Depressive symptoms were assessed using the 17-item Hamilton Depression Rating Scale. The relationship between symptom profiles and AOO was explored using Random Forest. The effect of AOO on symptom clusters and subtypes was investigated using multiple linear regression and LPA. A continuous AOO indicator was used to conduct the analyses.

RESULTS: Based on the Random Forest, symptom profiles were closely associated with AOO. The regression model showed that the severity of neurovegetative symptoms was positively associated with AOO (β = 0.18, p < 0.001), and the severity of cognitive-behavioral symptoms was negatively associated with AOO (β = -0.12, p < 0.001). LPA demonstrated that the subgroups characterized by suicide and guilt had earlier onset of depression. The subgroup with the lowest global severity of depression had the latest onset. LIMITATIONS: AOO was recalled retrospectively. The relative scarcity of participants with childhood and adolescence onset depression.

CONCLUSIONS: AOO has an important impact on symptomatology. The findings may enhance clinical evaluations for MDD and assist clinicians in promoting earlier detection and individualized care in vulnerable individuals.

Language: en

LA - en SN - 0165-0327 UR - http://dx.doi.org/10.1016/j.jad.2022.09.096 ID - ref1 ER -