Disentangling vulnerability, state and trait features of neurocognitive impairments in depression

Abstract

Depression is a debilitating disorder that often starts manifesting in early childhood and peaks in onset during adolescence. Neurocognitive impairments have emerged as clinically important characteristics of depression, but it remains controversial which domains specifically index pre-existing vulnerability, state-related or trait-related markers. Here, we disentangled these effects by analysing the Adolescent Brain Cognitive Development dataset (n = 4626). Using information of participants' current and past mental disorders, as well as family mental health history, we identified low-risk healthy (n = 2100), high-risk healthy (n = 2023), remitted depressed (n = 401) and currently depressed children (n = 102). Factor analysis of 11 cognitive variables was performed to elucidate latent structure and canonical correlation analyses conducted to probe regional brain volumes reliably associated with the cognitive factors. Bayesian model comparison of various a priori hypotheses differing in how low-risk healthy, high-risk healthy, remitted depressed and currently depressed children performed in various cognitive domains was performed. Factor analysis revealed three domains: language and reasoning, cognitive flexibility and memory recall. Deficits in language and reasoning ability, as well as in volumes of associated regions such as the middle temporal and superior frontal gyrus, represented state- and trait-related markers of depression but not pre-existing vulnerability. In contrast, there was no compelling evidence of impairments in other domains. These findings-although cross-sectional and specific to 9-10-year-old children-might have important clinical implications, suggesting that cognitive dysfunction may not be useful targets of preventive interventions. Depressed patients, even after remission, might also benefit from less commonly used treatments such as cognitive remediation therapy.

Keywords: affective disorders; child psychiatry; computational psychiatry; depression; imaging.