Search

Background Major depressive disorder (MDD) is often accompanied by changes in appetite and weight. Prior task-based functional magnetic resonance imaging (fMRI) findings suggest these MDD phenotypes are associated with altered reward and interoceptive processing. Methods Using resting-state fMRI data, we compared the fractional amplitude of low-frequency fluctuations (fALFF) and seed-based connectivity (SBC) among hyperphagic (n = 77), hypophagic (n = 66), and euphagic (n = 42) MDD groups and a healthy comparison group (n = 38). We examined fALFF and SBC in a mask restricted to reward [nucleus accumbens (NAcc), putamen, caudate, ventral pallidum, and orbitofrontal cortex (OFC)] and interoceptive (anterior insula and hypothalamus) regions and also performed exploratory whole-brain analyses. SBC analyses included as seeds the NAcc and also regions demonstrating group differences in fALFF (i.e. right lateral OFC and right anterior insula). All analyses used threshold-free cluster enhancement. Results Mask-restricted analyses revealed stronger fALFF in the right lateral OFC, and weaker fALFF in the right anterior insula, for hyperphagic MDD v. healthy comparison. We also found weaker SBC between the right lateral OFC and left anterior insula for hyperphagic MDD v. healthy comparison. Whole-brain analyses revealed weaker fALFF in the right anterior insula, and stronger SBC between the right lateral OFC and left precentral gyrus, for hyperphagic MDD v. healthy comparison. Findings were no longer significant after controlling for body mass index, which was higher for hyperphagic MDD. Conclusions Our results suggest hyperphagic MDD may be associated with altered activity in and connectivity between interoceptive and reward regions.

Previous proton magnetic resonance spectroscopy ((1)H-MRS) studies suggest a perturbation in glutamate and/or GABA in Major Depressive Disorder (MDD). However, no studies examine the ratio of glutamate and glutamine (Glx) to GABA (Glx/GABA) as it relates to depressive symptoms, which may be more sensitive than either single metabolite. Using a within-subject design, we hypothesized that reduction in depressive symptoms correlates with reduction in Glx/GABA in the anterior cingulate cortex (ACC). The present trial is a randomized clinical trial that utilized (1)H-MRS to examine Glx/GABA before and after 8 weeks of escitalopram or placebo. Participants completed the 17-item Hamilton Depression Rating Scale (HDRS(17)) and underwent magnetic resonance spectroscopy before and after treatment. Two GABA-edited MEGA-PRESS acquisitions were interleaved with a water unsuppressed reference scan. GABA and Glx were quantified from the average difference spectrum, with preprocessing using Gannet and spectral fitting using TARQUIN. Linear mixed models were utilized to evaluate relationships between change in HDRS(17) and change in Glx/GABA using a univariate linear regression model, multiple linear regression incorporating treatment type as a covariate, and Bayes Factor (BF) hypothesis testing to examine strength of evidence. No significant relationship was detected between percent change in Glx, GABA, or Glx/GABA and percent change in HDRS(17), regardless of treatment type. Further, MDD severity before/after treatment did not correlate with ACC Glx/GABA. In light of variable findings in the literature and lack of association in our investigation, future directions should include evaluating glutamate and glutamine individually to shed light on the underpinnings of MDD severity.

Evidence suggests that adults with a history of childhood maltreatment, the experience of emotional or physical neglect and/or abuse within the family during childhood, have blunted reward and stress processing, and higher risk of depression. The mu opioid receptor rich nucleus accumbens and amygdala are critical to reward and stress processing respectively. We hypothesized that nucleus accumbens and amygdala mu opioid receptor densities and activity (change in receptor binding due to endogenous opioid release or receptor conformation change) were negatively associated with childhood maltreatment in healthy young adults. Maltreatment was assessed with the Childhood Trauma Questionnaire (CTQ). Healthy participants, n = 75 (52% female) completed [

PURPOSE This study proposes a novel Maximum Likelihood Expectation Maximization (MLEM) based positron emission tomography (PET) image reconstruction approach, designed to provide improved signal recovery, specifically in small structures. This proposed technique, termed GPSF-MLEM, utilizes a gradually decreasing full-width-half-maximum (FWHM) point spread function (PSF), designed to yield increased spatial details in progressing iterations when measured and estimated projection data are in closer consensus. METHODS GPSF-MLEM was compared with the analytical filtered back projection (FBP) and the iterative reconstruction techniques of standard MLEM and PSF incorporated into MLEM (PSF-MLEM). Simulated phantoms as well as cylindrical and brain phantoms were used to evaluate performance, contrast recovery and for visual assessment of image quality. The performance of GPSF-MLEM and PSF-MLEM with various FWHM kernel sizes was also investigated. This work presents evidence that the choice of reconstruction technique and parameters for the best quantification of reconstructed PET images should be based on the purpose (task-based optimization). RESULTS Quantitatively, across all reconstructions tested, the image intensity estimated using GPSF-MLEM terminated at an intermediate FWHM was in closest agreement to the raw image intensity in the simulated phantom. Qualitative analysis of reconstructed images with physical phantoms suggested that irrespective of the FWHM at the terminal iteration, GPSF-MLEM provided robust image contrast and increased suppression of background hotspot artifacts compared to MLEM and PSF-MLEM. Further, across all FWHM combinations tested, GPSF-MLEM yielded fewer artifacts inherent to PSF-MLEM images reconstructed with an overestimated FWHM. CONCLUSIONS Emphasizing common task scenarios frequently encountered in medical imaging: A) GPSF-MLEM is recommended for tasks requiring a low background noise; B) PSF-MLEM is recommended for tasks that require good image segmentation; C) GPSF-MLEM with a larger terminal FWHM is recommended for obtaining high contrast recovery in small image structures.

BackgroundTreatment for major depressive disorder (MDD) is imprecise and often involves trial-and-error to determine the most effective approach. To facilitate optimal treatment selection and inform timely adjustment, the current study investigated whether neurocognitive variables could predict an antidepressant response in a treatment-specific manner.MethodsIn the two-stage Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care (EMBARC) trial, outpatients with non-psychotic recurrent MDD were first randomized to an 8-week course of sertraline selective serotonin reuptake inhibitor or placebo. Behavioral measures of reward responsiveness, cognitive control, verbal fluency, psychomotor, and cognitive processing speeds were collected at baseline and week 1. Treatment responders then continued on another 8-week course of the same medication, whereas non-responders to sertraline or placebo were crossed-over under double-blinded conditions to bupropion noradrenaline/dopamine reuptake inhibitor or sertraline, respectively. Hamilton Rating for Depression scores were also assessed at baseline, weeks 8, and 16.ResultsGreater improvements in psychomotor and cognitive processing speeds within the first week, as well as better pretreatment performance in these domains, were specifically associated with higher likelihood of response to placebo. Moreover, better reward responsiveness, poorer cognitive control and greater verbal fluency were associated with greater likelihood of response to bupropion in patients who previously failed to respond to sertraline.ConclusionThese exploratory results warrant further scrutiny, but demonstrate that quick and non-invasive behavioral tests may have substantial clinical value in predicting antidepressant treatment response.

Major depressive disorder is associated with aberrant resting-state functional connectivity across multiple brain networks supporting emotion processing, executive function, and reward processing. The purpose of this study was to determine whether patterns of resting-state connectivity between brain regions predict differential outcome to antidepressant medication (sertraline) compared with placebo.Participants in the Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care (EMBARC) study underwent structural and resting-state functional MRI at baseline. Participants were then randomly assigned to receive either sertraline or placebo treatment for 8 weeks (N=279). A region of interest-based approach was utilized to compute functional connectivity between brain regions. Linear mixed-model intent-to-treat analyses were used to identify brain regions that moderated (i.e., differentially predicted) outcomes between the sertraline and placebo arms.Prediction of response to sertraline involved several within- and between-network connectivity patterns. In general, higher connectivity within the default mode network predicted better outcomes specifically for sertraline, as did greater between-network connectivity of the default mode and executive control networks. In contrast, both placebo and sertraline outcomes were predicted (in opposite directions) by between-network hippocampal connectivity.This study identified specific functional network-based moderators of treatment outcome involving brain networks known to be affected by major depression. Specifically, functional connectivity patterns of brain regions between and within networks appear to play an important role in identifying a favorable response for a drug treatment for major depressive disorder.

Delivery of effective antidepressant treatment has been hampered by a lack of objective tools for predicting or monitoring treatment response. This study aimed to address this gap by testing novel dynamic resting-state functional network markers of antidepressant response.The Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care (EMBARC) study randomized adults with major depressive disorder to 8 weeks of either sertraline or placebo, and depression severity was evaluated longitudinally. Participants completed resting-state neuroimaging pretreatment and again after 1 week of treatment (n = 259 eligible for analyses). Coactivation pattern analyses identified recurrent whole-brain states of spatial coactivation, and computed time spent in each state for each participant was the main dynamic measure. Multilevel modeling estimated the associations between pretreatment network dynamics and sertraline response and between early (pretreatment to 1 week) changes in network dynamics and sertraline response.Dynamic network markers of early sertraline response included increased time in network states consistent with canonical default and salience networks, together with decreased time in network states characterized by coactivation of cingulate and ventral limbic or temporal regions. The effect of sertraline on depression recovery was mediated by these dynamic network changes. In contrast, early changes in dynamic functioning of corticolimbic and frontoinsular-default networks were related to patterns of symptom recovery common across treatment groups.Dynamic resting-state markers of early antidepressant response or general recovery may assist development of clinical tools for monitoring and predicting effective intervention.

BACKGROUND: The brain circuitry of depression and anxiety/fear is well-established, involving regions such as the limbic system and prefrontal cortex. We expand prior literature by examining the extent to which four discrete factors of anxiety (immediate state anxiety, physiological/panic, neuroticism/worry, and agitation/restlessness) among depressed outpatients are associated with differential responses during reactivity to and regulation of emotional conflict. METHODS: A total of 172 subjects diagnosed with major depressive disorder underwent functional magnetic resonance imaging while performing an Emotional Stroop Task. Two main contrasts were examined using whole brain voxel wise analyses: emotional reactivity and emotion regulation. We also evaluated the association of these contrasts with the four aforementioned anxiety factors. RESULTS: During emotional reactivity, participants with higher immediate state anxiety showed potentiated activation in the rolandic operculum and insula, while individuals with higher levels of physiological/panic demonstrated decreased activation in the posterior cingulate. No significant results emerged for any of the four factors on emotion regulation. When re-analyzing these statistically-significant brain regions through analyses of a subsample with (n = 92) and without (n = 80) a current anxiety disorder, no significant associations occurred among those without an anxiety disorder. Among those with an anxiety disorder, results were similar to the full sample, except the posterior cingulate was associated with the neuroticism/worry factor. CONCLUSIONS: Divergent patterns of task-related brain activation across four discrete anxiety factors could be used to inform treatment decisions and target specific aspects of anxiety that involve intrinsic processing to attenuate overactive responses to emotional stimuli.

Background Neuroinflammation has long been theorized to arise from exposures to fine particulate matter and to be modulated when individuals experience chronic stress, both of which are also though to cause cognitive decline in part as a result of neuroinflammation. Objectives Hypothesizing that neuroinflammation might be linked to experiences at the World Trade Center (WTC) events, this study explored associations between glial activation and neuropsychological measures including post-traumatic stress disorder (PTSD) symptom severity and WTC exposure duration. Methods Translocator protein 18-kDa (TSPO) is overexpressed by activated glial cells, predominantly microglia and astrocytes, making TSPO distribution a putative biomarker for neuroinflammation. Twenty WTC responders completed neuropsychological assessments and in vivo PET brain scan with [18F]-FEPPA. Generalized linear modeling was used to test associations between PTSD, and WTC exposure duratiioni as the predictor and both global and regional [18F]-FEPPA total distribution volumes as the outcomes. Result Responders were 56.0 ​± ​4.7 years-old, and 75% were police officers on 9/11/2001, and all had at least a high school education. Higher PTSD symptom severity was associated with global and regional elevations in [18F]-FEPPA binding predominantly in the hippocampus (d ​= ​0.72, P ​= ​0.001) and frontal cortex (d ​= ​0.64, P ​= ​0.004). Longer exposure duration to WTC sites was associated with higher [18F]-FEPPA binding in the parietal cortex. Conclusion Findings from this study of WTC responders at midlife suggest that glial activation is associated with PTSD symptoms, and WTC exposure duration. Future investigation is needed to understand the important role of neuroinflammation in highly exposed WTC responders., Highlights • We examined the theory that glial activation is associated with 9/11 exposures. • TSPO-Vt was examined using PET in 20 responders adjusting for TSPO genotype. • Responders with PTSD had increased TSPO distribution volume in the hippocampus. • Heavily exposed responders had increased TSPO distribution in the parietal cortex.

Rejection sensitivity (RS) is the heightened expectation or perception of social rejection and is a feature of many psychiatric disorders. As endogenous opioid pathways have been implicated in response to social rejection and reward, we hypothesize that RS will be negatively associated with mu opioid receptor (MOR) baseline binding and activity during rejection and acceptance stimuli. In exploratory analyses, we assessed the relationships between MOR activity and changes in mood and self-esteem before and after stimuli. Healthy participants, N = 75 (52% female), completed rejection and acceptance tasks during [

Background Our lab has previously found that structural integrity in tracts from the raphe nucleus (RN) to the amygdala, measured by fractional anisotropy (FA), predicts remission to selective serotonin reuptake inhibitors (SSRIs) in major depressive disorder (MDD). This could potentially serve as a biomarker for remission that can guide clinical decision-making. To enhance repeatability and reproducibility, we replicated our study in a larger, more representative multi-site sample. Methods 64 direction DTI was collected in 144 medication-free patients with MDD from the Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care (EMBARC) study. We performed probabilistic tractography between the RN and bilateral amygdala and hippocampus and calculated weighted FA in these tracts. Patients were treated with either sertraline or placebo, and their change in Hamilton Depression Rating Scale (HDRS) score reported. Pretreatment weighted FA was compared between remitters and nonremitters, and correlation between FA and percent change in HDRS score was assessed. Exploratory moderator and voxel analyses were also performed. Results Contrary to our hypotheses, FA was greater in nonremitters than in remitters in RN-left and right amygdala tracts (p = 0.02 and 0.01, respectively). Pretreatment FA between the raphe and left amygdala correlated with greater, not reduced, HDRS (r = 0.18, p = 0.04). This finding was found to be greater in the placebo group. Moderator and voxel analyses yielded no significant findings. Conclusions We found greater FA in nonremitters between the RN and amygdala than in remitters, and a correlation between FA and symptom worsening, particularly with placebo. These findings may help reveal more about the nature of MDD, as well as guide research methods involving placebo response.

Major depressive disorder (MDD) is a serious, heterogeneous disorder accompanied by brain-related changes, many of which are still to be discovered or refined. Arterial spin labeling (ASL) is a neuroimaging technique used to measure cerebral blood flow (CBF; perfusion) to understand brain function and detect differences among groups. CBF differences have been detected in MDD, and may reveal biosignatures of disease-state. The current work aimed to discover and replicate differences in CBF between MDD participants and healthy controls (HC) as part of the EMBARC study. Participants underwent neuroimaging at baseline, prior to starting study medication, to investigate biosignatures in MDD. Relative CBF (rCBF) was calculated and compared between 106 MDD and 36 HC EMBARC participants (whole-brain Discovery); and 58 MDD EMBARC participants and 58 HC from the DLBS study (region-of-interest Replication). Both analyses revealed reduced rCBF in the right parahippocampus, thalamus, fusiform and middle temporal gyri, as well as the left and right insula, for those with MDD relative to HC. Both samples also revealed increased rCBF in MDD relative to HC in both the left and right inferior parietal lobule, including the supramarginal and angular gyri. Cingulate and prefrontal regions did not fully replicate. Lastly, significant associations were detected between rCBF in replicated regions and clinical measures of MDD chronicity. These results (1) provide reliable evidence for ASL in detecting differences in perfusion for multiple brain regions thought to be important in MDD, and (2) highlight the potential role of using perfusion as a biosignature of MDD.

Medications to treat major depressive disorder (MDD) are not equally effective across patients. Given that neural response to rewards is altered in MDD and given that reward-related circuitry is modulated by dopamine and serotonin, we examined, for the first time, whether reward-related neural activity moderated response to sertraline, an antidepressant medication that targets these neurotransmitters. 222 unmedicated adults with MDD randomized to receive sertraline (n=110) or placebo (n=112) in the EMBARC (Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care) study completed demographic and clinical assessments, and pre-treatment functional magnetic resonance imaging while performing a reward task. We tested whether an index of reward system function in the ventral striatum (VS), a key reward circuitry region, moderated differential response to sertraline versus placebo, assessed with the Hamilton Rating Scale for Depression over 8 weeks. We observed a significant moderation effect of the reward index, reflecting the temporal dynamics of VS activity, on Week-8 depression levels (Fs≥9.67,ps≤0.002). Specifically, VS responses that were abnormal with respect to predictions from reinforcement learning theory were associated with lower Week-8 depression symptoms in the sertraline versus placebo arms. Thus, a more abnormal pattern of pre-treatment VS dynamic response to reward expectancy (expected outcome value) and prediction error (difference between expected and actual outcome), likely reflecting serotonergic and dopaminergic deficits, was associated with better response to sertraline than placebo. Pre-treatment measures of reward-related VS activity may serve as objective neural markers to advance efforts to personalize interventions by guiding individual-level choice of antidepressant treatment. Trial Registration: NCT01407094; http://clinicaltrials.gov/show/NCT01407094

Background Baseline rostral anterior cingulate cortex (rACC) activity is a well-replicated nonspecific predictor of depression improvement. The rACC is a key hub of the default mode network, which prior studies indicate is hyperactive in major depressive disorder. Because default mode network downregulation is reliant on input from the salience network and frontoparietal network, an important question is whether rACC connectivity with these systems contributes to depression improvement. Methods Our study evaluated this hypothesis in outpatients (N = 238; 151 female) enrolled in the Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care (EMBARC) 8-week randomized clinical trial of sertraline versus placebo for major depressive disorder. Depression severity was measured using the Hamilton Rating Scale for Depression, and electroencephalography was recorded at baseline and week 1. Exact low-resolution electromagnetic tomography was used to compute activity from the rACC, and key regions within the default mode network (posterior cingulate cortex), frontoparietal network (left dorsolateral prefrontal cortex), and salience network (right anterior insula [rAI]). Connectivity in the theta band (4.5–7 Hz) and beta band (12.5–21 Hz) was computed using lagged phase synchronization. Results Stronger baseline theta-band rACC–rAI (salience network hub) connectivity predicted greater depression improvement across 8 weeks of treatment for both treatment arms (B = −0.57, 95% confidence interval = −1.07, −0.08, p = .03). Early increases in theta-band rACC–rAI connectivity predicted greater likelihood of achieving remission at week 8 (odds ratio = 2.90, p = .03). Conclusions Among patients undergoing treatment, theta-band rACC–rAI connectivity is a prognostic, albeit treatment-nonspecific, indicator of depression improvement, and early connectivity changes may predict clinically meaningful outcomes.

BACKGROUND: Despite the fact that higher levels of anxiety and anhedonia in Major Depressive Disorder (MDD) are linked to poorer treatment outcomes, mechanisms contributing to these clinical presentations remain unclear. Neuroticism, impaired cognitive control, and blunted reward learning may be critical processes involved in MDD and may help to explain symptoms of anxiety and anhedonia. METHODS: Using baseline data from patients with early-onset MDD (N=296) in the Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care (EMBARC) trial, we conducted a path analysis to model relationships between neuroticism, cognitive control, and reward learning to levels of anxiety and anhedonia. RESULTS: Neuroticism was positively associated with both anhedonia (standardized coefficient = 0.26, p < .001) and anxiety (standardized coefficient = 0.40, p < .001). Cognitive control was negatively associated with anxiety (standardized coefficient = −0.18, p < .05). Reward learning was not significantly associated with either anxiety or anhedonia. LIMITATIONS: Extraneous variables not included in the model may have even more influence in explaining symptoms of anxiety and anhedonia. Restricted range in these variables may have attenuated some of the hypothesized relationships. Most important, because this was a cross-sectional analysis in a currently depressed sample, we cannot draw any causal conclusions without experimental and longitudinal data. CONCLUSIONS: These cross-sectional findings suggest that neuroticism may contribute to anxiety and anhedonia in patients with early onset and either chronic or recurrent MDD, while enhanced cognitive control may protect against anxiety.

Background/aims: While substantial prior research has evaluated the psychometric properties of the 12-item Concise Health Risk Tracking-Self Report (CHRT-SR12), a measure of suicide propensity and suicidal thoughts, no prior research has investigated its factor structure, sensitivity to change over time, and other psychometric properties in a placebo-controlled trial of antidepressant medication, nor determined whether symptoms change throughout treatment. Methods: Participants in the multi-site Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care (EMBARC) study ( n=278) provided data to evaluate the factor structure and sensitivity to change over time of the CHRT-SR12 through eight weeks of a clinical trial in which participants received either placebo or antidepressant medication (sertraline). Results/Outcomes: Factor analysis confirmed two factors: propensity (comprised of first-order factors including pessimism, helplessness, social support, and despair) and suicidal thoughts. Internal consistency (α’s ranged from 0.69–0.92) and external validity were both acceptable, with the total score and propensity factor scores significantly correlated with total scores and single-item suicidal-thoughts scores on the self-report Quick Inventory of Depressive Symptoms and the clinician-rated 17-item Hamilton Rating Scale for Depression. Through analyzing CHRT-SR12 changes over eight treatment weeks, the total score and both the factors decreased regardless of baseline suicidal thoughts. Change in clinician-rated suicidal thoughts was reflected by change in both the total score and propensity factor score. Conclusions/interpretation: These results confirm the reliability, validity, and applicability of the CHRT-SR12 to a placebo-controlled clinical trial of depressed outpatients receiving antidepressant medication.

Memory deficits are reported in major depressive disorder (MDD). Prefrontal cortical and mesiotemporal cortical (MTC)/subcortical regions are involved in the Buschke Selective Reminding Task (SRT), a verbal list-learning task. To determine whether depression-related changes in resting brain metabolism explain (in part) the deficits in SRT performance found in MDD, statistical correlation maps were calculated between SRT total recall score (TR) and relative regional cerebral metabolic rate for glucose (rCMRglu), measured by [18F]-flourodeoxyglucose (FDG) positron emission tomography (PET), in unmedicated, depressed MDD patients (N = 29). Subsequently, to explore hypothesized loss of top-down control in MDD, we compared the correlations between rCMRglu of SRT-relevant regions of the dorsolateral prefrontal cortex (dlPFC) and amygdala in a larger cohort of MDD (N = 60; 29 inclusive) versus healthy controls (HC) (N = 43). SRT performance of patients is on average 0.5 standard deviation below published normative mean. TR and rCMRglu positively correlate in bilateral dorsomedial PFC, dlPFC, dorsal anterior cingulate; negatively correlate in bilateral MTC/subcortical regions, and cerebellum. rCMRglu in dlPFC correlates negatively with that in amygdala in HC but not in MDD. Depression-related changes present in FDG-PET measured resting brain activity may be in part responsible for memory deficit found in MDD.

Overexpression of Cyclooxygenase-2 (COX-2) enzyme is associated with the pathogenesis of inflammation, cancers, stroke, arthritis, and neurological disorders. Because of the involvement of COX-2 in these diseases, quantification of COX-2 expression using Positron Emission Tomography (PET) may be a biological marker for early diagnosis, monitoring of disease progression, and an indicator of effective treatment. At present there is no target-specific or validated PET tracer available for in vivo quantification of COX-2. The objective of this study is to evaluate [11C]TMI, a selective COX-2 inhibitor (Ki ≤ 1 nM) in nonhuman primates using PET imaging. PET imaging in baboons showed that [11C]TMI penetrates the blood brain barrier (BBB) and accumulates in brain in a somewhat heterogeneous pattern. Metabolite analyses indicated that [11C]TMI undergoes no significant metabolism of parent tracer in the plasma for baseline scans, however a relative faster metabolism was found for blocking scan. All the tested quantification approaches provide comparable tracer total distribution volume (VT) estimates in the range of 3.2–7 (mL/cm3). We observed about 25% lower VT values in blocking studies with meloxicam, a nonselective COX-2 inhibitor, compared to baseline [11C]TMI binding. Our findings indicate that [11C]TMI may be a suitable PET tracer for the quantification of COX-2 in vivo. Further experiments are needed to confirm the potential of this tracer in COX-2 overexpressing models for brain diseases.

Highlights • A clinically relevant method of predicting MDD treatment efficacy is needed. • The present investigation applies dynamic FDG-PET using blood as a reference. • FDG-PET was assessed in the raphe nuclei, ventral prefrontal cortex and insula. • Regional pretreatment metabolism does not relate to symptom severity decrease. • Predictive FDG-PET signal may not be generalizable to heterogeneous MDD cohorts., There is critical need for a clinically useful tool to predict antidepressant treatment outcome in major depressive disorder (MDD) to reduce suffering and mortality. This analysis sought to build upon previously reported antidepressant treatment efficacy prediction from 2-[18F]-fluorodeoxyglucose - Positron Emission Tomography (FDG-PET) using metabolic rate of glucose uptake (MRGlu) from dynamic FDG-PET imaging with the goal of translation to clinical utility. This investigation is a randomized, double-blind placebo-controlled trial. All participants were diagnosed with MDD and received an FDG-PET scan before randomization and after treatment. Hamilton Depression Rating Scale (HDRS-17) was completed in participants diagnosed with MDD before and after 8 weeks of escitalopram, or placebo. MRGlu (mg/(min*100 ml)) was estimated within the raphe nuclei, right insula, and left ventral Prefrontal Cortex in 63 individuals. Linear regression was used to examine the association between pretreatment MRGlu and percent decrease in HDRS-17. Additionally, the association between percent decrease in HDRS-17 and percent change in MRGlu between pretreatment scan and post-treatment scan was examined. Covariates were treatment type (SSRI/placebo), handedness, sex, and age. Depression severity decrease (n = 63) was not significantly associated with pretreatment MRGlu in the raphe nuclei (β = -2.61e-03 [-0.26, 0.25], p = 0.98), right insula (β = 0.05 [-0.23, 0.32], p = 0.72), or ventral prefrontal cortex (β = 0.06 [-0.23, 0.34], p = 0.68) where β is the standardized estimated coefficient, with a 95% confidence interval, or in whole brain voxelwise analysis (family-wise error correction, alpha = 0.05). MRGlu percent change was not significantly associated with depression severity decrease (n = 58) before multiple comparison correction in the RN (β = 0.20 [-0.07, 0.47], p = 0.15), right insula (β = 0.24 [-0.03, 0.51], p = 0.08), or vPFC (β = 0.22 [-0.06, 0.50], p = 0.12). We propose that FDG-PET imaging does not indicate a clinically relevant biomarker of escitalopram or placebo treatment response in heterogeneous major depressive disorder cohorts. Future directions include focusing on potential biologically-based subtypes of major depressive disorder by implementing biomarker stratified designs.

Background Major depressive disorder is associated with abnormal connectivity across emotion and reward circuits as well as other established circuits that may negatively impact treatment response. The goal of this study was to perform an exploratory reanalysis of archival data from a clinical trial to identify moderators of treatment outcome of sertraline over placebo. Methods EMBARC (Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care) study participants completed magnetic resonance imaging before randomization to either sertraline or placebo for 8 weeks (n = 279). Seed-based functional connectivity was computed using 4 bilateral seeds (2 spheres defined bilaterally): amygdala, dorsolateral prefrontal cortex (DLPFC), subcallosal cingulate cortex, and ventral striatum. Functional connectivity maps were generated, principal component analysis was performed, linear mixed effects models were used to determine moderators of treatment outcome, and post hoc analyses were used to determine level of connectivity (low and high, −1 and +1 SD from the mean) that was most sensitive to improved depression severity (baseline to week 8) based on treatment. Results Greater mean reduction in the 17-item Hamilton Rating Scale for Depression score by 8 weeks occurred with sertraline relative to placebo when connectivity in the DLPFC was low (3-way interaction test, p = .05). Conditional on low connectivity in the DLPFC and subcallosal cingulate cortex and high connectivity in the ventral striatum and amygdala, there was on average a 4.8-point greater reduction in the 17-item Hamilton Rating Scale for Depression score with sertraline relative to placebo (p = .003). Conclusions The level of functional connectivity seeded in both the DLPFC and the subcallosal cingulate cortex networks may play an important role in identifying a favorable response to sertraline over placebo.

We aimed to identify brain structural changes in cortical and subcortical regions linked to recent suicidal behavior. We performed secondary analyses of structural MRI data of two independent studies, namely the Establishing Moderators/Biosignatures of Antidepressant Response - Clinical Care (EMBARC) study and a Little Rock study on acute suicidal behavior. Study 1 (EMBARC, N = 187), compared individuals with remote suicide attempts (Remote-SA), individuals with lifetime suicide ideation but no attempts (Lifetime-SI only), and depressed individuals without lifetime suicide ideation or attempts (non-suicidal depressed). Study 2 (Little Rock data, N = 34) included patients recently hospitalized for suicide ideation or attempt constituted by: patients who recently attempted suicide (Recent-SA), individuals with remote suicide attempts (Remote-SA), and Lifetime-SI only. Study 3 combined the EMBARC and Little Rock datasets including Recent-SA, Remote-SA, Lifetime-SI only and non-suicidal depressed individuals. In Study 1 and Study 2, no significant differences were observed between groups. In Study 3, significantly lower middle temporal gyrus thickness, insular surface area, and thalamic volume and higher volume in the nucleus accumbens were observed in Recent-SA. This pattern of structural abnormalities may underlie pain and emotion dysregulation, which have been linked to the transition from suicidal thoughts to action.

Many studies have shown volumetric differences in the hippocampus between COMT gene polymorphisms and other studies have shown differences between depressed patients and controls; yet, few studies have been completed to identify the volumetric differences when taking both factors into consideration. Using voxel-based morphology (VBM) we investigated, in major depressive disorder (MDD) patients and healthy controls, the relationship between COMT gene polymorphism and volumetric abnormalities. Data from 60 MDD patients and 25 healthy controls were included in this study. Volumetric measurements and genotyping of COMTval158met polymorphism were conducted to determine its impact on gray matter volume (GMV) in the hippocampus and amygdala using a Met dominant model (Val/Val vs Met/Val & Met/Met). In the analysis, a significant difference in the right hippocampus (p = 0.015), right amygdala (p = 0.003) and entire amygdala (p = 0.019) was found between the interaction of diagnosis and genotype after MRI scanner, age and sex correction. Healthy controls (HC) with the Met dominant genotype exhibited a larger right hippocampal, right amygdalar and entire amydgalar volume than MDD patients with the Met dominant genotype. Conversely, HC with the Val/Val genotype displayed a lower right hippocampal, right amygdalar and entire amygdalar volume than their MDD counterparts. This study shows that COMT polymorphism and depression may have a confounding effect on neuroimaging studies.

It is a growing concern that outcomes of neuroimaging studies often cannot be replicated. To counteract this, the magnetic resonance (MR) neuroimaging community has promoted acquisition standards and created data sharing platforms, based on a consensus on how to organize and share MR neuroimaging data. Here, we take a similar approach to positron emission tomography (PET) data. To facilitate comparison of findings across studies, we first recommend publication standards for tracer characteristics, image acquisition, image preprocessing, and outcome estimation for PET neuroimaging data. The co-authors of this paper, representing more than 25 PET centers worldwide, voted to classify information as mandatory, recommended, or optional. Second, we describe a framework to facilitate data archiving and data sharing within and across centers. Because of the high cost of PET neuroimaging studies, sample sizes tend to be small and relatively few sites worldwide have the required multidisciplinary expertise to properly conduct and analyze PET studies. Data sharing will make it easier to combine datasets from different centers to achieve larger sample sizes and stronger statistical power to test hypotheses. The combining of datasets from different centers may be enhanced by adoption of a common set of best practices in data acquisition and analysis. ispartof: JOURNAL OF CEREBRAL BLOOD FLOW AND METABOLISM vol:40 issue:8 pages:1576-1585 ispartof: location:United States status: published

Attenuation correction is a notable challenge associated with simultaneous PET/MRI, particularly in neuroimaging, where sharp boundaries between air and bone volumes exist. This challenge leads to concerns about the visual and, more specifically, quantitative accuracy of PET reconstructions for data obtained with PET/MRI. Recently developed techniques can synthesize attenuation maps using only MRI data and are likely adequate for clinical use; however, little work has been conducted to assess their suitability for the dynamic PET studies frequently used in research to derive physiologic information such as the binding potential of neuroreceptors in a region. At the same time, existing PET/MRI attenuation correction methods are predicated on synthesizing CT data, which is not ideal, as CT data are acquired with much lower-energy photons than PET data and thus do not optimally reflect the PET attenuation map. Methods: We trained a convolutional neural network to generate patient-specific transmission data from T1-weighted MRI. Using the trained network, we generated transmission data for a testing set comprising 11 subjects scanned with 11C-labeled N-[2-]4-(2-methoxyphenyl)-1-piperazinyl]ethyl]-N-(2-pyridinyl)cyclohexanecarboxamide) (11C-WAY-100635) and 10 subjects scanned with 11C-labeled 3-amino-4-(2-dimethylaminomethyl-phenylsulfanyl)benzonitrile (11C-DASB). We assessed both static and dynamic reconstructions. For dynamic PET data, we report differences in both the nondisplaceable and the free binding potential for 11C-WAY-100635 and distribution volume for 11C-DASB. Results: The mean bias for generated transmission data was -1.06% ± 0.81%. Global biases in static PET uptake were -0.49% ± 1.7%, and -1.52% ± 0.73% for 11C-WAY-100635 and 11C-DASB, respectively. Conclusion: Our neural network approach is capable of synthesizing patient-specific transmission data with sufficient accuracy for both static and dynamic PET studies.