Connectivity Affecting the Antidepressant REsponse (The CAARE Study)

Detailed Summary

It can be difficult to achieve remission in individuals with late-life depression (LLD) and they often require aggressive treatment. This challenge is in part due to age-related vascular changes that are common in LLD. Successful antidepressant treatment involve changes across affective, cognitive, and default mode networks. We hypothesize that in LLD, vascular disease adversely affects response to antidepressants by disrupting connectivity of these networks. The primary goal of this project is to characterize how focal vascular damage affects regional connectivity and response to antidepressants. Based on past work and pilot data, we a priori focus on the cingulum bundle and uncinate fasciculus. These key fiber bundles connect frontal, temporal, and cingulate regions involved in cognition and affective responses. Our central hypothesis is that ischemic damage to the cingulum bundle and uncinate fasciculus contributes to structural and functional connectivity deficits of those tracts. This results in a disconnection effect that alters the function of connected regions. In turn, this increases the risk of a poor response to antidepressants. Our approach is to enroll up to 130 adults over age 60 years with a diagnosis of Major Depressive Disorder. Subjects will complete clinical evaluation, cognitive testing, and MRI/functional MRI (fMRI) sessions, including an fMRI emotional oddball task that includes attentional and affective components. Participants will be stratified by cerebral lesion severity and randomized in a 2:1 ratio to a double-blinded 8-week trial of escitalopram or matching placebo. Those who do not remit will transition to an 8-week trial of open-label bupropion, an antidepressant with a different mechanism of action. This will allow us to determine if different and distinct circuit deficits affect response to antidepressants with different mechanisms of action while also accounting for the placebo response.

Study Details

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