Admixture Analysis of Age of Onset in Late-Life Major Depressive Disorder

Objective Age-of-onset is suggested as a feature to distinguish between subtypes of depression, albeit consensus on cut-off ages for early- versus late-onset is lacking. In this study, we used a data driven technique to determine whether a single or multiple normal distribution model best fitted the age-of-onset data in our sample of depressed older persons. Based on the optimal distribution, we then determined empirical cut-off point(s). Next, age-of-onset was examined as a marker of potentially discerning characteristics. Methods Data were derived from 353 participants, 60–93 years old, with a major depressive disorder (MDD), who participated in the Netherlands Study of Depression in Older Persons (NESDO). Admixture analysis was conducted, using solely age-of-onset data, to find the best fitting distribution model for age-of-onset. Next, associations between age-of-onset subtypes and various characteristics were examined using multinomial logistic regression analysis. Results A three-population model was found to fit the data. This clinically plausible model consists of an early-; intermediate- and late-onset group divided by cut-off ages of 33 and 47 years. The early-onset group was associated with childhood trauma (OR 2.55 [95%CI 1.22–5.32]). The late-onset group was associated with more prevalent recent life-events (OR 2.23 [95%CI 1.18–4.21]). Conclusion In our sample, MDD was characterized by a trimodal age-of-onset distribution with cut-off ages of 33 and 47 years. However, age-of-onset was found to be associated with only few clinical and vulnerability characteristics. Possible overlap between de age-of-onset subtypes in later life may obscure differentiation between the characteristics.