Features of immunometabolic depression as predictors of antidepressant treatment outcomes: pooled analysis of four clinical trials.

BACKGROUND: Profiling patients on a proposed 'immunometabolic depression' (IMD) dimension, described as a cluster of atypical depressive symptoms related to energy regulation and immunometabolic dysregulations, may optimise personalised treatment. AIMS: To test the hypothesis that baseline IMD features predict poorer treatment outcomes with antidepressants. METHOD: Data on 2551 individuals with depression across the iSPOT-D (n = 967), CO-MED (n = 665), GENDEP (n = 773) and EMBARC (n = 146) clinical trials were used. Predictors included baseline severity of atypical energy-related symptoms (AES), body mass index (BMI) and C-reactive protein levels (CRP, three trials only) separately and aggregated into an IMD index. Mixed models on the primary outcome (change in depressive symptom severity) and logistic regressions on secondary outcomes (response and remission) were conducted for the individual trial data-sets and pooled using random-effects meta-analyses. RESULTS: Although AES severity and BMI did not predict changes in depressive symptom severity, higher baseline CRP predicted smaller reductions in depressive symptoms (n = 376, ßpooled = 0.06, P = 0.049, 95% CI 0.0001-0.12, I2 = 3.61%); this was also found for an IMD index combining these features (n = 372, ßpooled = 0.12, s.e. = 0.12, P = 0.031, 95% CI 0.01-0.22, I2= 23.91%), with a higher - but still small - effect size compared with CRP. Confining analyses to selective serotonin reuptake inhibitor users indicated larger effects of CRP (ßpooled = 0.16) and the IMD index (ßpooled = 0.20). Baseline IMD features, both separately and combined, did not predict response or remission. CONCLUSIONS: Depressive symptoms of people with more IMD features improved less when treated with antidepressants. However, clinical relevance is limited owing to small effect sizes in inconsistent associations. Whether these patients would benefit more from treatments targeting immunometabolic pathways remains to be investigated.

Reward Behavior Disengagement, a Neuroeconomic Model-Based Objective Measure of Reward Pathology in Depression: Findings from the EMBARC Trial.

The probabilistic reward task (PRT) has identified reward learning impairments in those with major depressive disorder (MDD), as well as anhedonia-specific reward learning impairments. However, attempts to validate the anhedonia-specific impairments have produced inconsistent findings. Thus, we seek to determine whether the Reward Behavior Disengagement (RBD), our proposed economic augmentation of PRT, differs between MDD participants and controls, and whether there is a level at which RBD is high enough for depressed participants to be considered objectively disengaged. Data were gathered as part of the Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care (EMBARC) study, a double-blind, placebo-controlled clinical trial of antidepressant response. Participants included 195 individuals with moderate to severe MDD (Quick Inventory of Depressive Symptomatology (QIDS-SR) score ≥ 15), not in treatment for depression, and with complete PRT data. Healthy controls (n = 40) had no history of psychiatric illness, a QIDS-SR score < 8, and complete PRT data. Participants with MDD were treated with sertraline or placebo for 8 weeks (stage I of the EMBARC trial). RBD was applied to PRT data using discriminant analysis, and classified MDD participants as reward task engaged (n = 137) or reward task disengaged (n = 58), relative to controls. Reward task engaged/disengaged groups were compared on sociodemographic features, reward-behavior, and sertraline/placebo response (Hamilton Depression Rating Scale scores). Reward task disengaged MDD participants responded only to sertraline, whereas those who were reward task engaged responded to sertraline and placebo (F(1293) = 4.33, p = 0.038). Reward task engaged/disengaged groups did not differ otherwise. RBD was predictive of reward impairment in depressed patients and may have clinical utility in identifying patients who will benefit from antidepressants.

Immune Dysregulation in Treatment-Resistant Depression: Precision Approaches to Treatment Selection and Development of Novel Treatments.

Owing to the link between immune dysfunction and treatment-resistant depression (TRD) and the overwhelming evidence that the immune dysregulation and major depressive disorder (MDD) are associated with each other, using immune profiles to identify the biological distinct subgroup may be the step forward to understanding MDD and TRD. This report aims to briefly review the role of inflammation in the pathophysiology of depression (and TRD in particular), the role of immune dysfunction to guide precision medicine, tools used to understand immune function, and novel statistical techniques.

Leveraging the microbiome to understand clinical heterogeneity in depression: findings from the T-RAD study.

Alterations in the gut microbiome have been linked to a variety of mental illnesses including anxiety and depression. This study utilized advanced bioinformatics tools that integrated both the compositional and community nature of gut microbiota to investigate how gut microbiota influence clinical symptoms in a sample of participants with depression. Gut microbiota of 179 participants with major depressive disorder (MDD) in the Texas Resilience Against Depression (T-RAD) study were analyzed by 16S rRNA gene sequencing of stool samples. Severity of anxiety, depression, and anhedonia symptoms were assessed with General Anxiety Disorder - 7 item scale, Patient Health 9-item Questionnaire, and Dimensional Anhedonia Rating Scale, respectively. Using weighted correlation network analysis, a data-driven approach, three co-occurrence networks of bacterial taxa were identified. One of these co-occurrence networks was significantly associated with clinical features including depression and anxiety. The hub taxa associated with this co-occurrence module -one Ruminococcaceae family taxon, one Clostridiales vadinBB60 group family taxon, and one Christencenellaceae family taxon- were connected to several additional butyrate-producing bacteria suggesting that deficits in butyrate production may contribute to clinical symptoms. Therefore, by considering the community nature of the gut microbiome in a real world clinical sample, this study identified a gut microbial co-occurrence network that was significantly associated with clinical anxiety in a cohort of depressed individuals.

Brain Ventricle and Choroid Plexus Morphology as Predictor of Treatment Response: Findings from the EMBARC Study.

Recent observations suggest a role of the choroid plexus (CP) and cerebral ventricle volume (CV), to identify treatment resistance of major depressive disorder (MDD). We tested the hypothesis that these markers are associated with clinical improvement in subjects from the EMBARC study, as implied by a recent pilot study. The EMBARC study characterized biological markers in a randomized placebo-controlled trial of sertraline vs. placebo in patients with MDD. Association of baseline volumes of CV, CP and of the corpus callosum (CC) with treatment response after 4 weeks treatment were evaluated. 171 subjects (61 male, 110 female) completed the 4 week assessments; gender, site and age were taken into account for this analyses. As previously reported, no treatment effect of sertraline was observed, but prognostic markers for clinical improvement were identified. Responders (n = 54) had significantly smaller volumes of the CP and lateral ventricles, whereas the volume of mid-anterior and mid-posterior CC was significantly larger compared to non-responders (n = 117). A positive correlation between CV volume and CP volume was observed, whereas a negative correlation between CV volume and both central-anterior and central-posterior parts of the CC emerged. In an exploratory way correlations between enlarged VV and CP volume on the one hand and signs of metabolic syndrome, in particular triglyceride plasma concentrations, were observed. A primary abnormality of CP function in MDD may be associated with increased ventricles, compression of white matter volume, which may affect treatment response speed or outcome. Metabolic markers may mediate this relationship.

Accelerated Brain Aging in Adults With Major Depressive Disorder Predicts Poorer Outcome With Sertraline: Findings From the EMBARC Study.

BACKGROUND: Major depressive disorder (MDD) may be associated with accelerated brain aging (higher brain age than chronological age). This report evaluated whether brain age is a clinically useful biomarker by checking its test-retest reliability using magnetic resonance imaging scans acquired 1 week apart and by evaluating the association of accelerated brain aging with symptom severity and antidepressant treatment outcomes. METHODS: Brain age was estimated in participants of the EMBARC (Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care) study using T1-weighted structural magnetic resonance imaging (MDD n = 290; female n = 192; healthy control participants n = 39; female n = 24). Intraclass correlation coefficient was used for baseline-to-week-1 test-retest reliability. Association of baseline Δ brain age (brain age minus chronological age) with Hamilton Depression Rating Scale-17 and Concise Health Risk Tracking Self-Report domains (impulsivity, suicide propensity [measures: pessimism, helplessness, perceived lack of social support, and despair], and suicidal thoughts) were assessed at baseline (linear regression) and during 8-week-long treatment with either sertraline or placebo (repeated-measures mixed models). RESULTS: Mean ± SD baseline chronological age, brain age, and Δ brain age were 37.1 ± 13.3, 40.6 ± 13.1, and 3.1 ± 6.1 years in MDD and 37.1 ± 14.7, 38.4 ± 12.9, and 0.6 ± 5.5 years in healthy control groups, respectively. Test-retest reliability was high (intraclass correlation coefficient = 0.98-1.00). Higher baseline Δ brain age in the MDD group was associated with higher baseline impulsivity and suicide propensity and predicted smaller baseline-to-week-8 reductions in Hamilton Depression Rating Scale-17, impulsivity, and suicide propensity with sertraline but not with placebo. CONCLUSIONS: Brain age is a reliable and potentially clinically useful biomarker that can prognosticate antidepressant treatment outcomes.

Data driven clusters derived from resting state functional connectivity: Findings from the EMBARC study.

BACKGROUND: To address the clinical heterogeneity of Major Depressive Disorder (MDD), this investigation determined whether resting state functional magnetic resonance imaging (fMRI) could be deployed to identify circuit based homogeneous subgroups, and whether subgroups identified show differential treatment outcomes. METHODS: Pretreatment resting state fMRIs obtained from 278 outpatients with nonpsychotic MDD from Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care for Depression Study were used to create data-driven subgroups using CLICK clustering. These subgroups were then compared using baseline clinical data, as well as baseline-to-week 8 changes in depression severity measured using the 17-item Hamilton Rating Scale for Depression (HAMD17) and response/remission rates by treatment group. RESULTS: Three subgroups were identified. Cluster-1 was characterized by overallhyperconnectivity coupled with profound hypoconnectivity between the supramarginal gyrus (executive control network; ECN) and the superior frontal cortex (dorsal attention network; DAN). Cluster-2 was characterized by overall hypoconnectivity coupled with hyperconnectivity between supramarginal gyrus (ECN) and superior frontal cortex (DAN). Cluster-3 showed hypoconnectivity, especially profound between the angular cortex (default mode network; DMN) and middle frontal cortex (ECN). While baseline clinical measures did not differentiate the three clusters, Cluster-3 had the remission rate (51.6%) compared to Cluster-1 and Cluster-2 (32.7% and 31.9%) when treated with sertraline. LIMITATIONS: Due to the exploratory nature of these analyses, there were no adjustments for multiple comparisons. CONCLUSIONS: Baseline functional connectivity can be used to subgroup patients with MDD that differ in acute phase treatment outcomes. Measures of connectivity may address the heterogeneity of MDD.

Characterizing inflammatory profiles of suicidal behavior in adolescents: Rationale and design.

BACKGROUND: The suicide rate in youth and young adults continues to climb - we do not understand why this increase is occurring, nor do we have adequate tools to predict or prevent it. Increased efforts to treat underlying depression and other disorders that are highly associated with suicide have had limited impact, despite considerable financial investments in developing and disseminating available methods. Thus, there is a tremendous need to identify potential markers of suicide behavior for youth during this high-risk period. METHODS: Funded by the American Foundation for Suicide Prevention (AFSP), this study aims to map immune dysfunction to suicidal behavior and establish a reliable immune signature of suicide risk that can 1) guide future research into fundamental pathophysiology and 2) identify targets for drug development. The study design is an observational study where blood samples and a comprehensive array of clinical measures are collected from three groups of adolescents (n = 75 each) (1) with suicidal behavior [recent (within 3 months) suicide attempt or suicidal ideation warranting urgent evaluation,] (2) at risk for mood disorders, and (3) who are healthy (no psychiatric history). Participants will complete self-report and clinical assessments, along with a blood draw, at baseline, 3 months, 6 months and 12 months, and online self-report assessments once a month. RESULTS: The recruitment for this study is ongoing. LIMITATIONS: Observational, variability in treatment regimens. CONCLUSIONS: This study will help elucidate immune mechanisms that may play a causal role in suicide and serve as targets for future therapeutic development.

Accelerated brain aging in individuals with diabetes: Association with poor glycemic control and increased all-cause mortality.

BACKGROUND: Diabetes has been linked to accelerated brain aging, i.e., neuroimaging-predicted age of brain is higher than chronological age. This report evaluated whether accelerated brain aging in diabetes is associated with higher levels of glycated hemoglobin (HbA1c) and increased mortality. METHODS: Brain age in Dallas Heart Study (n = 1949) was estimated using T1-weighted magnetic resonance imaging (MRI) scans and a previously-published Gaussian Processes Regression model. Accelerated brain aging (adjusted Δ brain age) was computed as follows: (brain age adjusted for chronological age)-minus-(chronological age). Mortality data until 12/31/2016 were obtained from the National Death Index. Associations of adjusted Δ brain age with diabetes in full sample and with HbA1c in individuals with diabetes were evaluated. Proportion of association between diabetes and all-cause mortality that was accounted for by adjusted Δ brain age were evaluated with mediation analyses. Covariates included Framingham 10-year risk score, race/ethnicity, income, body mass index, and history of myocardial infarction. RESULTS: Diabetes was associated with] higher adjusted Δ brain age [estimate= 1.79; 95% confidence interval (CI): 0.889, 2.68]. Among those with diabetes, higher HbA1c (log-base-2-transformed) was associated with higher adjusted Δ brain age (estimate=3.88; 95% CI: 1.47, 6.30). Over a median follow-up of 97.5 months, 24/246 (9.8%) with diabetes and 63/1703 (3.7%) without diabetes died. Adjusted Δ brain age accounted for 65.3 (95% CI: 39.3, 100.0)% of the association between diabetes and all-cause mortality. CONCLUSION: Accelerated brain aging may be related to poor glycemic control in diabetes and partly account for the association between diabetes and all-cause mortality.

Immune characterization of suicidal behavior in female adolescents.

Background: To address the need to identify potential markers of suicide behavior for adolescents (ages 12-18 years), mass cytometry was used to explore the cellular mechanisms that may underpin immune dysregulation in adolescents with recent suicidal behavior. Methods: Peripheral blood mononuclear cell (PBMC) samples from 10 female adolescents with a recent suicide attempt and 4 healthy female adolescents were used. A panel of 30 antibodies was analyzed using mass cytometry. We used two complementary approaches to 1) identify the cell types that significantly differed between the two groups, and 2) explore differences in the expression profile of markers on the surface of these cells. Mass cytometry data were investigated using (Center for Disease Control, 2021) Opt-SNE for dimension reduced (Curtin and Heron, 2019), FlowSOM for clustering, and (Bridge et al., 2006) EgdeR and SAM for statistical analyses. Results: Opt-SNE (a data driven clustering analysis) identified 15 clusters of distinct cell types. From these 15 clusters, cluster 5 (classical monocytes) had statistically lower abundance in suicidal adolescents as compared to healthy controls, whereas cluster 7 (gamma-delta T cells) had statistically higher abundance in suicidal adolescents compared to healthy control. Furthermore, across the 15 cell types, chemokine receptors, CXCR3 (cluster 5) and CXCR5 (clusters 4, 5, 7, and 9), had an elevated expression profile in those with a recent suicide attempt versus healthy controls. Conclusion: This report demonstrates the utility of high dimensional cell phenotyping in psychiatric disorders and provides preliminary evidence for distinct immune dysfunctions in adolescents with recent suicide attempts as compared to healthy controls.

Patterns of Pretreatment Reward Task Brain Activation Predict Individual Antidepressant Response: Key Results From the EMBARC Randomized Clinical Trial.

BACKGROUND: The lack of biomarkers to inform antidepressant selection is a key challenge in personalized depression treatment. This work identifies candidate biomarkers by building deep learning predictors of individual treatment outcomes using reward processing measures from functional magnetic resonance imaging, clinical assessments, and demographics. METHODS: Participants in the EMBARC (Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care) study (n = 222) underwent reward processing task-based functional magnetic resonance imaging at baseline and were randomized to 8 weeks of sertraline (n = 106) or placebo (n = 116). Subsequently, sertraline nonresponders (n = 37) switched to 8 weeks of bupropion. The change in Hamilton Depression Rating Scale was measured after treatment. Reward processing, clinical measurements, and demographics were used to train treatment-specific deep learning models. RESULTS: The predictive model for sertraline achieved R2 of 48% (95% CI, 33%-61%; p < 10-3) in predicting the change in Hamilton Depression Rating Scale and number-needed-to-treat (NNT) of 4.86 participants in predicting response. The placebo model achieved R2 of 28% (95% CI, 15%-42%; p < 10-3) and NNT of 2.95 in predicting response. The bupropion model achieved R2 of 34% (95% CI, 10%-59%, p < 10-3) and NNT of 1.68 in predicting response. Brain regions where reward processing activity was predictive included the prefrontal cortex and cerebellar crus 1 for sertraline and the cingulate cortex, caudate, orbitofrontal cortex, and crus 1 for bupropion. CONCLUSIONS: These findings demonstrate the utility of reward processing measurements and deep learning to predict antidepressant outcomes and to form multimodal treatment biomarkers.

Comparison of inflammatory markers as moderators of depression outcomes: A CO-MED study.

BACKGROUND: Prior work suggests some individual immunomarkers may be useful moderators of treatment response between antidepressant medications. The relative moderating effect of individual immunomarkers remains unclear. It is also unknown whether combinations of immunomarkers have a superior moderating effect compared to any individual immunomarker. METHODS: Baseline immunomarker levels were assayed using multiplex from a subset of participants in the CO-MED trial (n = 143). Individual and combinations of 19 immunomarkers were modeled as moderators between the three treatment arms (escitalopram monotherapy, escitalopram-bupropion and venlafaxine-mirtazapine) across a variety of depression outcomes. RESULTS: Only IL-13 demonstrated a consistent moderating effect across all depression outcome measures. High IL-13 (>20 pg/ml) was associated with higher remission rates to bupropion-escitalopram (67%) versus escitalopram (24%) whereas low IL-13 was associated higher remission rates to escitalopram (59%) versus bupropion-escitalopram (38%). A similar, but weaker moderating effect was observed with venlafaxine-mirtazapine versus escitalopram. The addition of multiple immunomarkers did not consistently improve predictive modeling. LIMITATIONS: This is a secondary analysis of a single clinical trial with a relatively small sample size per treatment arm. The testing of specific individual and combinations of biomarkers was data-driven. CONCLUSIONS: Among 19 immunomarkers, Il-13 was the best single moderator of treatment outcome. Combinations of immunomarkers were not meaningfully superior to Il-13.

Dysfunction of default mode network is associated with active suicidal ideation in youths and young adults with depression: Findings from the T-RAD study.

Deaths due to suicide are one of the leading causes of mortality among youths and young adults. Active suicidal ideation (SI) is considered one of the strongest risk factors for suicide. Here, we evaluated the neurocircuitry of SI in a sample of youths and young adults (aged 10-26 years) with current or past diagnosis of either major depression or bipolar disorder who were enrolled in Texas Resilience Against Depression Study (T-RAD), and had neuroimaging and SI (assessed with the 3-item Suicidal Thoughts factor of Concise Health Risk Tracking self-report scale) data available (n = 72, 53 females). Resting-state functional connectivity (FC) was computed amongst 121 cortical and subcortical regions of interest resulting in 7260 FC pairs. Mean (SD) age and SI levels of participants were 19.6 years (4.01) and 1.48 (2.36) respectively. In univariate analyses, 34 out of the 7260 FC pairs were correlated with SI (p < .005). Stronger connectivity of default mode network (DMN) with striatum was associated with higher SI. Conversely, higher SI was associated with weaker connectivity of limbic network with hippocampus, DMN, dorsal attention network, and executive control network. In multivariate analyses, these 34 FC pairs together had an average correlation of 0.54 after five-fold cross-validation. In conclusion, SI was associated with distinct patterns of resting-state functional connectivity among youths and young adults with regions in DMN and the ventral striatum as key nodes.

Impact of the COVID-19 pandemic on adults with current and prior depression: initial findings from the longitudinal Texas RAD study.

BACKGROUND: Emerging work has suggested worsening mental health in the general population during the COVID-19 pandemic, but there is minimal data on individuals with a prior history of depression. METHODS: Data regarding depression, anxiety and quality of life in adult participants with a history of a depressive disorder (n = 308) were collected before and during the COVID-19 pandemic. Mixed effects regression models were fit for these outcomes over the period May - August 2020, controlling for pre-pandemic depressive groups (none, mild, moderate-to-severe), demographic characteristics, and early COVID-19 related experiences (such as disruptions in routines, mental health treatment, and social supports). RESULTS: In pre-to-early pandemic comparisons, the 3 pre-pandemic depressive categories varied significantly in anxiety (Fdf=2,197 = 7.93, p < 0.0005) and psychological QOL (Fdf=2,196 = 8.57, p = 0.0003). The mildly depressed group (Fdf=1,201 = 6.01, p = 0.02) and moderate-to-severely depressed group (Fdf=1,201 = 38.51, p < 0.0001) had a significant reduction in anxiety. There were no changes among the groups in any outcome from May to August 2020. However, early impact on mental health care access and disruption in routines predicted worse outcomes during this time. LIMITATIONS: Follow-up data were self-reported. Furthermore, the duration was a relatively short span into the pandemic. CONCLUSIONS: Symptoms of depression, anxiety, and quality of life were generally stable from 2019 throughout August 2020 in adults with a history of depression. Disruption in mental health care access and routines in May 2020 predicted worse symptom outcomes through August 2020.

Irritability as an independent predictor of concurrent and future suicidal ideation in adults with stimulant use disorder: Findings from the STRIDE study.

BACKGROUND: This report evaluated whether irritability in adults with stimulant use disorder is associated with suicidal ideation (SI) at the same visit (i.e., concurrently) and whether early changes in irritability predict subsequent levels of SI. METHODS: Adults with stimulant use disorder (n=302) from nine residential addiction treatment programs were included. Participants were randomized to augmentation of usual care with dosed exercise or health education intervention. Irritability, SI, and depression were measured every week with 5-item irritability domain of Concise Associated Symptom Tracking scale, 3-item suicidal thoughts factor of Concise Health Risk Tracking scale, and 16-item Quick Inventory of Depressive Symptomatology Clinician-Rated version (excluding the suicide-related item) respectively during acute-(baseline-to-week-12) and continuation-(week-12-to-week-36) phase. Covariates included age, sex, race, ethnicity, treatment arm, type of substance(s) used, and comorbid psychiatric and medical disorders. RESULTS: Higher irritability was associated with higher SI concurrently both in the acute-phase: r=0.28 (p<0.0001) and in the continuation-phase: r=0.33 (p<0.0001). Irritability was associated with concurrent SI after controlling for depression [acute-phase: ß=0.17 (p<0.0001); continuation-phase: ß=0.18 (p<0.0001)]. Greater baseline-to-week-2 reductions in irritability predicted lower levels of SI from week-2-to-week-12 (ß=-0.11, p=0.003) and from week-12-to-week-36 (ß=-0.22, p<0.0001) after controlling for baseline levels of depression and SI and baseline-to-week-2 changes in depression and SI. LIMITATIONS: Secondary analyses, self-report measures of irritability and SI, limited generalizability. CONCLUSIONS: Irritability is associated with SI concurrently, and greater reductions in irritability earlier in treatment are associated with lower levels of subsequent SI. Therefore, targeting irritability may reduce suicidality in adults with stimulant use disorder.

Smoking status links habenular volume to glycated hemoglobin: Findings from the Human Connectome Project-Young Adult.

BACKGROUND: The habenula-pancreas axis regulates the stimulatory effects of nicotine on blood glucose levels and may participate in the emergence of type 2 diabetes in human tobacco smokers. This secondary analysis of young adults from the Human Connectome Project (HCP-YA) evaluated whether smoking status links the relationship between habenular volume and glycated hemoglobin (HbA1c), a marker of long-term glycemic control. METHODS: Habenula segmentation was performed using a fully-automated myelin content-based approach in HCP-YA participants and the results were inspected visually (n = 693; aged 22-37 years). A linear regression analysis was used with habenular volume as the dependent variable, the smoking-by-HbA1c interaction as the independent variable of interest, and age, gender, race, ethnicity, education, income, employment status, body mass index, and total gray matter volume as covariates. RESULTS: Habenula volume and HbA1c were similar in smokers and nonsmokers. There was a significant interaction effect (F(1, 673)= 5.03, p = 0.025) indicating that habenular volume was related to HbA1c in a manner that depended on smoking status. Among participants who were smokers (n = 120), higher HbA1c was associated with apparently larger habenular volume (ß = 6.74, standard error=2.36, p = 0.005). No such association between habenular volume and HbA1c was noted among participants who were nonsmokers (n = 573). DISCUSSION: Blood glucose levels over an extended time period, reflected by HbA1c, were correlated with habenular volume in smokers, consistent with a relationship between the habenula and blood glucose homeostasis in smokers. Future studies are needed to evaluate how habenular function relates to glycemic control in smokers and nonsmokers.

Cross-Sectional Associations Among Symptoms of Pain, Irritability, and Depression and How These Symptoms Relate to Social Functioning and Quality of Life: Findings From the EMBARC and STRIDE Studies and the VitalSign6 Project.

OBJECTIVE: The aim of this report was to evaluate the psychometric properties of the Pain Frequency, Intensity, and Burden Scale (P-FIBS), a brief measure of pain, as well as the association of pain with irritability and depression and how these symptoms relate to functional impairments. METHODS: Participants of 2 randomized controlled trials (Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care [EMBARC; n = 251 with DSM-IV diagnosis of major depressive disorder; study duration: August 2011-December 2015] and STimulant Reduction Intervention Using Dosed Exercise [STRIDE; n = 302 with DSM-IV diagnosis of stimulant abuse or dependence; study-duration: July 2010-February 2013]) and treatment-seeking patients in primary care clinics from an ongoing quality-improvement project (VitalSign6; n = 4,370; project duration: August 2014-July 2019) were included. Psychometric properties of the P-FIBS were evaluated with confirmatory factor and item response theory analyses in EMBARC and VitalSign6. The approach of Baron and Kenny was used to assess whether irritability accounted for the effect of pain on depression. RESULTS: Cronbach α (0.84-0.89) and model fits for single-factor structure of P-FIBS were acceptable. Pain was positively correlated with irritability (r = 0.22-0.29) and depression (r = 0.10-0.33). Irritability accounted for 40.7%-65.5% of the effect of pain on depression. Higher irritability and depression were associated with poorer social functioning, quality of life, and productivity in work- and non-work-related activities. Pain was associated with non-work-related activity impairments even after controlling for irritability and depression. CONCLUSIONS: The P-FIBS is a brief and reliable measure of pain. Irritability is associated with pain and accounts for a large proportion of the effect of pain on depression. Symptoms of pain, irritability, and depression are associated with functional impairments. TRIAL REGISTRATION: ClinicalTrials.gov identifiers: NCT01407094 (EMBARC), NCT01141608 (STRIDE).

Differential response to SSRI versus Placebo and distinct neural signatures among data-driven subgroups of patients with major depressive disorder.

OBJECTIVE: To identify data-driven subgroups in Major Depressive Disorder (MDD) in order to elucidate underlying neural correlates and determine if these subgroups have utility in predicting response to antidepressant versus placebo. METHODS: Using 27 clinical measures at baseline of Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care for Depression (EMBARC) study, participants with MDD (n=244) were sub grouped using principal component (PC) analysis. Baseline-to-week-8 changes in depression severity with sertraline versus placebo were compared in these subgroups. Resting-state functional connectivity of these subgroups were compared to those of healthy controls (n=38). RESULTS: Eight subgroups were identified from four PCs: (PC1) severity of depression-associated symptoms, (PC2) sub-threshold mania and anhedonia, (PC3) childhood trauma, medical comorbidities, and sexual dysfunction, and (PC4) personality traits of openness and agreeableness. Participants with high childhood trauma experienced greater improvement with sertraline (Cohen's d=0.87), whereas those with either higher levels of subthreshold hypomanic symptoms (Cohen's d=0.67) or with lower levels of agreeableness and openness experienced greater improvement with placebo (Cohen's d=0.71). Participants with high childhood trauma had greater connectivity between salience and dorsal attention networks, whereas those with higher levels of subthreshold hypomanic symptoms and lower levels of agreeableness and openness had greater connectivity within limbic network and that of visual network with hippocampus and dorsal attention network. CONCLUSION: Assessing history of childhood trauma, presence of subthreshold hypomanic symptoms and personality traits may help to identify subgroups of patients with MDD who respond differentially to sertraline or placebo and have distinct neural signatures.

Anger attacks are associated with persistently elevated irritability in MDD: findings from the EMBARC study.

BACKGROUND: This report tests the association of self-reported symptoms of irritability with overt behavior of anger attacks (uncharacteristic sudden bouts of anger that are disproportionate to situation and associated with autonomic activation). METHODS: Participants of the Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care study who completed Massachusetts General Hospital Anger Attacks questionnaire were included (n = 293). At each visit, the 17-item Hamilton Depression Rating Scale and the 16-item Concise Associated Symptom Tracking scale were used to measure depression, anxiety, and irritability. In those with anger attacks present v. those without anger attacks, separate t tests and mixed model analyses compared afore-mentioned symptoms at baseline and changes with treatment respectively. As anger attacks may occur without aggressive behaviors, analyses were repeated based only on the presence of aggressive behaviors. RESULTS: At baseline, those with anger attacks (n = 109) v. those without anger attacks (n = 184) had similar levels of depression but higher levels of irritability [effect size (d) = 0.80] and anxiety (d = 0.32). With acute-phase treatment, participants with anger attacks experienced a greater reduction in irritability (p < 0.001) but not in depression (p = 0.813) or anxiety (p = 0.771) as compared to those without anger attacks. Yet, irritability levels at week-8 were higher in those with anger attacks (d = 0.32) than those without anger attacks. Similar results were found in participants with aggressive behaviors. CONCLUSIONS: The presence of anger attacks in outpatients with major depressive disorder may identify a sub-group of patients with persistently elevated irritability.