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1.  Using Standardized fMRI Protocols to Identify Patterns of Prefrontal Circuit Dysregulation that are Common and Specific to Cognitive and Emotional Tasks in Major Depressive Disorder: First Wave Results from the iSPOT-D Study 
Neuropsychopharmacology  2013;38(5):863-871.
Functional neuroimaging studies have implicated dysregulation of prefrontal circuits in major depressive disorder (MDD), and these circuits are a viable target for predicting treatment outcomes. However, because of the heterogeneity of tasks and samples used in studies to date, it is unclear whether the central dysfunction is one of prefrontal hyperreactivity or hyporeactivity. We used a standardized battery of tasks and protocols for functional magnetic resonance imaging, to identify the common vs the specific prefrontal circuits engaged by these tasks in the same 30 outpatients with MDD compared with 30 matched, healthy control participants, recruited as part of the International Study to Predict Optimized Treatment in Depression (iSPOT-D). Reflecting cognitive neuroscience theory and established evidence, the battery included cognitive tasks designed to assess functions of selective attention, sustained attention-working memory and response inhibition, and emotion tasks to assess explicit conscious and implicit nonconscious viewing of facial emotion. MDD participants were distinguished by a distinctive biosignature of: hypoactivation of the dorsolateral prefrontal cortex during working memory updating and during conscious negative emotion processing; hyperactivation of the dorsomedial prefrontal cortex during working memory and response inhibition cognitive tasks and hypoactivation of the dorsomedial prefrontal during conscious processing of positive emotion. These results show that the use of standardized tasks in the same participants provides a way to tease out prefrontal circuitry dysfunction related to cognitive and emotional functions, and not to methodological or sample variations. These findings provide the frame of reference for identifying prefrontal biomarker predictors of treatment outcomes in MDD.
PMCID: PMC3671994  PMID: 23303059
Biological Psychiatry; biomarker; clinical Pharmacology/clinical trials; depression; unipolar/bipolar; functional MRI; Imaging; clinical or Preclinical; iSPOT-D; prefrontal cortex; standardized cognitive and emotion task protocols; not open access; functional MRI; prefrontal cortex; major depressive disorder; biomarker; standardized cognitive and emotion task protocols; iSPOT-D
2.  Widespread reductions in gray matter volume in depression☆ 
NeuroImage : Clinical  2013;3:332-339.
Abnormalities in functional limbic–anterior cingulate–prefrontal circuits associated with emotional reactivity, evaluation and regulation have been implicated in the pathophysiology of major depressive disorder (MDD). However, existing knowledge about structural alterations in depression is equivocal and based on cohorts of limited sample size. This study used voxel-based morphometry (VBM) and surface-based cortical thickness to investigate the structure of these circuits in a large and well-characterized patient cohort with MDD.
Non-geriatric MDD outpatients (n = 102) and age- and gender-matched healthy control participants (n = 34) provided T1-weighted magnetic resonance imaging data during their baseline visit as part of the International Study to Predict Optimized Treatment for Depression. Whole-brain VBM volumetric and surface-based cortical thickness assessments were performed voxel-wise and compared (at p < 0.05 corrected for multiple comparisons) between the MDD and control groups.
MDD participants had reduced gray matter volume in the anterior cingulate cortex, regions of the prefrontal circuits, including dorsolateral and dorsomedial prefrontal cortices, and lateral and medial orbitofrontal cortices, but not in limbic regions. Additional reductions were observed cortically in the posterior temporal and parieto-occipital cortices and, subcortically in the basal ganglia and cerebellum. Focal cortical thinning in the medial orbitofrontal cortex was also observed for the MDD group. These alterations in volume and cortical thickness were not associated with severity of depressive symptoms.
The findings demonstrate that widespread gray matter structural abnormalities are present in a well-powered study of patients with depression. The patterns of gray matter loss correspond to the same brain functional network regions that were previously established to be abnormal in MDD, which may support an underlying structural abnormality for these circuits.
•Focal gray matter volume decrease in depression exceeded loss via aging 11–50 years.•Gray matter differences were found in regions with established roles in depression.•Structural change findings support the idea of depression as a network abnormality.•Hippocampal gray matter volume loss likely has no role in non-geriatric depression.•Amygdala gray matter volume loss likely plays no role in depression pathophysiology.
PMCID: PMC3814952  PMID: 24273717
AAL, Automated Anatomical Labeling; ACC, Anterior Cingulate Cortex; BAs, Brodmann Areas; CVNA, Change in Volume expected in that region through Normal Aging; DLPFC, Dorsolateral Prefrontal Cortex; DTI, Diffusion Tensor Imaging; FDR, False Discovery Rate; fMRI, functional Magnetic Resonance Imaging; GM, Gray Matter; HRSD17, 17-Item Hamilton Rating Scale for Depression; iSPOT-D, International Study to Predict Optimized Treatment in Depression; MDD, Major Depressive Disorder; MPFC, Medial Prefrontal Cortex; MRI, Magnetic Resonance Imaging; OFC, Orbitofrontal Cortex; PFC, Prefrontal Cortex; VBM, Voxel-Based Morphometry; Gray matter; Major depressive disorder; VBM; Volume; Cortical thickness; iSPOT-D
3.  Brain imaging predictors and the international study to predict optimized treatment for depression: study protocol for a randomized controlled trial 
Trials  2013;14:224.
Approximately 50% of patients with major depressive disorder (MDD) do not respond optimally to antidepressant treatments. Given this is a large proportion of the patient population, pretreatment tests that predict which patients will respond to which types of treatment could save time, money and patient burden. Brain imaging offers a means to identify treatment predictors that are grounded in the neurobiology of the treatment and the pathophysiology of MDD.
The international Study to Predict Optimized Treatment in Depression is a multi-center, parallel model, randomized clinical trial with an embedded imaging sub-study to identify such predictors. We focus on brain circuits implicated in major depressive disorder and its treatment. In the full trial, depressed participants are randomized to receive escitalopram, sertraline or venlafaxine-XR (open-label). They are assessed using standardized multiple clinical, cognitive-emotional behavioral, electroencephalographic and genetic measures at baseline and at eight weeks post-treatment. Overall, 2,016 depressed participants (18 to 65 years old) will enter the study, of whom a target of 10% will be recruited into the brain imaging sub-study (approximately 67 participants in each treatment arm) and 67 controls. The imaging sub-study is conducted at the University of Sydney and at Stanford University. Structural studies include high-resolution three-dimensional T1-weighted, diffusion tensor and T2/Proton Density scans. Functional studies include standardized functional magnetic resonance imaging (MRI) with three cognitive tasks (auditory oddball, a continuous performance task, and Go-NoGo) and two emotion tasks (unmasked conscious and masked non-conscious emotion processing tasks). After eight weeks of treatment, the functional MRI is repeated with the above tasks. We will establish the methods in the first 30 patients. Then we will identify predictors in the first half (n = 102), test the findings in the second half, and then extend the analyses to the total sample.
Trial registration
International Study to Predict Optimized Treatment - in Depression (iSPOT-D)., NCT00693849.
PMCID: PMC3729660  PMID: 23866851
Major depressive disorder; Antidepressant treatments; Imaging; Biomarker; iSPOT-D
4.  Sensitivity, specificity, and predictive power of the “Brief Risk-resilience Index for SCreening,” a brief pan-diagnostic web screen for emotional health 
Brain and Behavior  2012;2(5):576-589.
Few standardized tools are available for time-efficient screening of emotional health status across diagnostic categories, especially in primary care. We evaluated the 45-question Brief Risk-resilience Index for SCreening (BRISC) and the 15-question mini-BRISC in identifying poor emotional health and coping capacity across a range of diagnostic groups – compared with a detailed clinical assessment – in a large sample of adult outpatients. Participants 18–60 years of age (n = 1079) recruited from 12 medical research and clinical sites completed the computerized assessments. Three index scores were derived from the full BRISC and the mini-BRISC: one for risk (negativity–positivity bias) and two for coping (resilience and social capacity). Summed answers were converted to standardized z-scores. BRISC scores were compared with detailed health assessment and diagnostic interview (for current psychiatric, psychological, and neurological conditions) by clinicians at each site according to diagnostic criteria. Clinicians were blinded to BRISC scores. Clinical assessment stratified participants as having “clinical” (n = 435) or “healthy” (n = 644) diagnostic status. Receiver operating characteristic analyses showed that a z-score threshold of −1.57 on the full BRISC index of emotional health provided an optimal classification of “clinical” versus “healthy” status (sensitivity: 81.2%, specificity: 92.7%, positive predictive power: 80.2%, and negative predictive power: 93.1%). Comparable findings were revealed for the mini-BRISC. Negativity–positivity bias index scores contributed the most to prediction. The negativity–positivity index of emotional health was most sensitive to classifying major depressive disorder (100%), posttraumatic stress disorder (95.8%), and panic disorder (88.7%). The BRISC and mini-BRISC both offer a brief, clinically useful screen to identify individuals at risk of disorders characterized by poor emotion regulation, from those with good emotional health and coping.
PMCID: PMC3489810  PMID: 23139903
Depression and anxiety; emotional well-being; Internet; mental health screen; risk and resilience; sensitivity and specificity
5.  International Study to Predict Optimized Treatment for Depression (iSPOT-D), a randomized clinical trial: rationale and protocol 
Trials  2011;12:4.
Clinically useful treatment moderators of Major Depressive Disorder (MDD) have not yet been identified, though some baseline predictors of treatment outcome have been proposed. The aim of iSPOT-D is to identify pretreatment measures that predict or moderate MDD treatment response or remission to escitalopram, sertraline or venlafaxine; and develop a model that incorporates multiple predictors and moderators.
The International Study to Predict Optimized Treatment - in Depression (iSPOT-D) is a multi-centre, international, randomized, prospective, open-label trial. It is enrolling 2016 MDD outpatients (ages 18-65) from primary or specialty care practices (672 per treatment arm; 672 age-, sex- and education-matched healthy controls). Study-eligible patients are antidepressant medication (ADM) naïve or willing to undergo a one-week wash-out of any non-protocol ADM, and cannot have had an inadequate response to protocol ADM. Baseline assessments include symptoms; distress; daily function; cognitive performance; electroencephalogram and event-related potentials; heart rate and genetic measures. A subset of these baseline assessments are repeated after eight weeks of treatment. Outcomes include the 17-item Hamilton Rating Scale for Depression (primary) and self-reported depressive symptoms, social functioning, quality of life, emotional regulation, and side-effect burden (secondary). Participants may then enter a naturalistic telephone follow-up at weeks 12, 16, 24 and 52. The first half of the sample will be used to identify potential predictors and moderators, and the second half to replicate and confirm.
First enrolment was in December 2008, and is ongoing. iSPOT-D evaluates clinical and biological predictors of treatment response in the largest known sample of MDD collected worldwide.
Trial registration
International Study to Predict Optimised Treatment - in Depression (iSPOT-D) Identifier: NCT00693849
PMCID: PMC3036635  PMID: 21208417

Results 1-6 (6)