Journal
EUROPEAN NEUROPSYCHOPHARMACOLOGY
Volume 26, Issue 12, Pages 2000-2010Publisher
ELSEVIER
DOI: 10.1016/j.euroneuro.2016.09.640
Keywords
Dynamic causal modeling; BOLD fMRI; Depression; SSRI; Emotion
Funding
- Medical Research Council [MR/K022202/1]
- MRC [G0701421, MR/K022202/1] Funding Source: UKRI
- Medical Research Council [G0701421, MR/K022202/1] Funding Source: researchfish
Ask authors/readers for more resources
The timely selection of the optimal treatment for depressed patients is critical to improve remission rates. The detection of pre-treatment variables able to predict differential treatment response may provide novel approaches for treatment selection. Selective serotonin reuptake inhibitors (SSRIs) modulate the fronto-limbic functional response and connectivity, an effect preceding the overt clinical antidepressant effects. Here we investigated whether the cortico-limbic connectivity associated with emotional bias measured before SSRI administration predicts the efficacy of antidepressant treatment in MDD patients. fMRI and Dynamic Causal Modeling (DCM) were combined to study if effective connectivity might differentiate healthy controls (HC) and patients affected by major depression who later responded (RMDD, n=21), or failed to respond (nRMDD, n=12), to 6 weeks of escitalopram administration. Sixteen DCMs exploring connectivity between anterior cingulate cortex (ACC), ventrolateral prefrontal cortex (VLPFC), Amygdala (Amy), and fusiform gyrus (FG) were constructed. Analyses revealed that nRMDD had reduced endogenous connectivity from Amy to VLPFC and to ACC, with an increased connectivity and modulation of the ACC to Amy connectivity when processing of fearful emotional stimuli compared to NC. RMDD and HC did not significantly differ among themselves. Pre-treatment effective connectivity in fronto-limbic circuitry could be an important factor affecting antidepressant response, and highlight the mechanisms which may be involved in recovery from depression. These results suggest that fronto-limbic connectivity might provide a neural biomarker to predict the clinical outcome to SSRIs administration in major depression. (C) 2016 Elsevier B.V. and ECNP. All rights reserved.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available