My Depression Wellness Toolkit Study

Relapse and recurrence following recovery from Major Depressive Disorder (MDD) are common and debilitating outcomes that carry enormous social costs \[1-3\]. Our CIHR funded program of research has studied the nature of psychological vulnerability in affective disorder. We have recently identified the activation of a depressive cognitive mode triggered by temporary dysphoric states as a reliable risk marker for depressive relapse \[4, see attached\]. In parallel, functional imaging studies have increased our understanding of the neural mechanisms underlying normative affective responses \[5\] and have begun to examine their dysregulation in affective disorder \[6-8\]. Our research has identified potential brain biomarkers that predict episode relapse in unipolar depression. However, it remains unknown how these potential biomarkers are related to dysphoria-triggered information processing modes that also predict relapse, and whether these neurocognitive vulnerabilities are amenable to intervention, resulting in more lasting prophylaxis. The present proposal employs a cognitive neuroscience approach to examine whether our previously identified neural markers of depression relapse and prophylaxis are associated with a dysphoric information processing mode. In particular, we will use functional magnetic resonance imaging (fMRI) and behavioural probes to undertake a finely tuned examination of mood linked biases in attention toward dysphoric stimulus events (i.e., sad faces) to link our previously identified neural markers with a specific information processing mode. Further, our preliminary data presented here demonstrate a correlation between these mood linked neural markers and relapse, but we cannot demonstrate that these markers are causally related to relapse or prophylaxis. To address this, we will examine whether these markers and associated dysphoric attentional biases are 1) modifiable via attentional training designed to overcome reflexive modes of thought and perception and 2) are predictive of relapse status across an 24-month prospective follow up of treated patients. This research will elucidate the neural and information processing correlates that may signal relapse risk in recovered depressed patients. This knowledge will increase our limited understanding of the mechanisms underlying enduring depressive relapse vulnerability as well as assess potentially efficient strategies for relapse prophylaxis.