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  • Addiction, Drugs
  • Information from Lay-Language Summaries is Embargoed Until the Conclusion of the Scientific Presentation

    540—Mood Disorders: Human Biomarkers and Treatment Studies

    Tuesday, November 12, 2013, 8:00 am - 12:00 noon

    540.08: Neural predictors of antidepressant treatment response to Quetiapine XR and Citalopram in Major Depressive Disorder

    Location: Halls B-H

    *A. BURGESS1, R. WHITE1, F. CORTESE2, B. GOODYEAR2, A. PANICKER1, A. KARNES1, K. ROY1, V. DIWADKAR1, R. RAMMASUBBU2;
    1Psychiatry and Behavioral Neurosci., Wayne State Univ. Sch. of Med., Detroit, MI; 2Univ. of Calgary, Calgary, AB, Canada

    Abstract Body: Background: Clinical response to antidepressant treatment is varied and unpredictable in patients with major depressive disorder (MDD). Imaging studies have shown general neural predictors of clinical improvement to antidepressants (Pizzagalli 2011). However, identifying differential predictors of clinical response to antidepressants with different pharamacological profiles may help match patients with appropriate anti-depressants early in treatment. Here we investigated general and specific neural predictors of antidepressant treatment response to citalopram and quetiapine XR treatment in MDD.
    Methods: During fMRI (3T), 46 subjects with MDD participated in a picture-matching task (Hariri et al., 2003) during which subjects’ matched pairs of faces (or geometric objects) among triads of stimuli. The event-related design was analyzed in SPM8 using standard methods. Pre-trial fMRI responses were compared (based on end outcome; 8-week) between clinically improved and non-improved groups. 2nd level random effects analyses of fMRI data assessed activity-related differences for both positive and negative valence classes. Analyses were thresholded to a depression and treatment recovery neural circuit consisting of the amygdala, dorsal ACC, subgenual ACC, precuneus, orbito-frontal, and dorsolateral frontal cortex.
    Results: Responders to antidepressant treatment showed increased pre-treatment activation in frontolimbic regions including the dorsal nexus, dorsal prefrontal cortex, ACC, orbitofrontal cortex and amygdala (Figure 1).
    Conclusions: These findings confirm that pre-treatment anterior cingulate activity to negative emotions may represent generic predictor of clinical improvement to antidepressants. Future studies should examine whether functional interactions of ACC with other regions implicated in emotional regulation or depression differentially predict antidepressant response.

    Lay Language Summary: Major depressive disorder (MDD) is a highly prevalent, chronic disabling condition with substantial morbidity and mortality. Depression currently is the fourth leading cause of global burden of disease and disability worldwide, and is expected to be second by 2020(WHO-2008). Despite significant advances in pharmacological treatment, the global burden of depression is increasing worldwide. The major challenge in the treatment of depression is the clinicians’ inability to predict the variability in individual response to the treatment.Clinical response to antidepressant treatment is highly varied and unpredictable in patients with major depressive disorder (MDD). Approximately 60% of patients fail to remit to the first antidepressant prescribed and the subsequent selection of antidepressants remains a matter of trial and error. Using this trial and error approach, it may take a year or more to find the successful treatment for a patient. The protracted ineffective treatment results in prolonged suffering, substantial morbidity, loss of productivity and an increased burden on patient’s family. Brain-based biomarkers could assist in predicting clinical response to treatment intervention and in tailoring treatment for individual patients.
    Emerging functional magnetic resonance imaging (fMRI) studies suggest that neural activity in anterior cingulate cortex (ACC) or amygdala and hippocampal volumes may predict clinical improvement to a variety of antidepressant therapies. However, at present there are no class specific neural markers to predict clinical response to antidepressants with different pharmacological profiles. This would limit clinician’s ability to match patients with appropriate anti-depressants early in treatment. In this fMRI study, we investigated general and specific neural predictors of antidepressant treatment response to two different class of antidepressants; citalopram and quetiapine XR treatment in subjects with MDD.
    Forty-six subjects [mean: 37.8 yrs: 22-58 yrs; F: 26, M: 20] with MDD who completed the 8-week clinical trial were included in this study. Subjects were randomized into one of two different antidepressant treatment regimens of Citalopram or Quetiapine XR. Imaging was performed on subjects at three time points [Before the treatment; week1 and week 8 after the treatment]. During imaging subjects performed a picture matching task consisting of alternating matching faces with facial expressions [angry, fearful, sad, and happy] or a geometric control. Subjects had to select one of the two faces or geometrical designs presented at the top of the screen that matched the face or design presented at the bottom of the screen. During this task, data were collected to measure how the brain was functioning before the treatment. From these data, we analyzed how changes in the brain during the task could differentiate the subjects who responded from those who did not respond at the end of the treatment. We found increased activityin the mid-cingulate, amygdala, and certain prefrontal regions in response to negative stimuli differentiated responders from non-responders to both treatments. However, no brain activity could distinguish citalopram responders from quetiapine XR responders.
    The clinical implications of our findings are that the pre-treatment evaluation of neural activity in the mid-cingulate, amygdala and prefrontal regions in response to negatively valenced emotion may be useful to predict responsiveness to general antidepressant therapy. However, this may not
    be appropriate for differential treatment prediction between Citalopram and Quetiapine XR treatment. We are currently analyzing the data to investigate whether functional changes at the early phase of antidepressant treatment (week 1) or functional interactions of the cingulate and amygdala can differentially predict class specific antidepressant treatment response.