Personalized prediction of antidepressant v. placebo response: evidence from the EMBARC study.

BACKGROUND: Major depressive disorder (MDD) is a highly heterogeneous condition in terms of symptom presentation and, likely, underlying pathophysiology. Accordingly, it is possible that only certain individuals with MDD are well-suited to antidepressants. A potentially fruitful approach to parsing this heterogeneity is to focus on promising endophenotypes of depression, such as neuroticism, anhedonia, and cognitive control deficits. METHODS: Within an 8-week multisite trial of sertraline v. placebo for depressed adults (n = 216), we examined whether the combination of machine learning with a Personalized Advantage Index (PAI) can generate individualized treatment recommendations on the basis of endophenotype profiles coupled with clinical and demographic characteristics. RESULTS: Five pre-treatment variables moderated treatment response. Higher depression severity and neuroticism, older age, less impairment in cognitive control, and being employed were each associated with better outcomes to sertraline than placebo. Across 1000 iterations of a 10-fold cross-validation, the PAI model predicted that 31% of the sample would exhibit a clinically meaningful advantage [post-treatment Hamilton Rating Scale for Depression (HRSD) difference ⩾3] with sertraline relative to placebo. Although there were no overall outcome differences between treatment groups (d = 0.15), those identified as optimally suited to sertraline at pre-treatment had better week 8 HRSD scores if randomized to sertraline (10.7) than placebo (14.7) (d = 0.58). CONCLUSIONS: A subset of MDD patients optimally suited to sertraline can be identified on the basis of pre-treatment characteristics. This model must be tested prospectively before it can be used to inform treatment selection. However, findings demonstrate the potential to improve individual outcomes through algorithm-guided treatment recommendations.

Harmonization of cortical thickness measurements across scanners and sites.

With the proliferation of multi-site neuroimaging studies, there is a greater need for handling non-biological variance introduced by differences in MRI scanners and acquisition protocols. Such unwanted sources of variation, which we refer to as "scanner effects", can hinder the detection of imaging features associated with clinical covariates of interest and cause spurious findings. In this paper, we investigate scanner effects in two large multi-site studies on cortical thickness measurements across a total of 11 scanners. We propose a set of tools for visualizing and identifying scanner effects that are generalizable to other modalities. We then propose to use ComBat, a technique adopted from the genomics literature and recently applied to diffusion tensor imaging data, to combine and harmonize cortical thickness values across scanners. We show that ComBat removes unwanted sources of scan variability while simultaneously increasing the power and reproducibility of subsequent statistical analyses. We also show that ComBat is useful for combining imaging data with the goal of studying life-span trajectories in the brain.

Pretreatment Reward Sensitivity and Frontostriatal Resting-State Functional Connectivity Are Associated With Response to Bupropion After Sertraline Nonresponse.

BACKGROUND: Standard guidelines recommend selective serotonin reuptake inhibitors as first-line antidepressants for adults with major depressive disorder, but success is limited and patients who fail to benefit are often switched to non-selective serotonin reuptake inhibitor agents. This study investigated whether brain- and behavior-based markers of reward processing might be associated with response to bupropion after sertraline nonresponse. METHODS: In a two-stage, double-blinded clinical trial, 296 participants were randomized to receive 8 weeks of sertraline or placebo in stage 1. Individuals who responded continued on another 8-week course of the same intervention in stage 2, while sertraline and placebo nonresponders crossed over to bupropion and sertraline, respectively. Data from 241 participants were analyzed. The stage 2 sample comprised 87 patients with major depressive disorder who switched medication and 38 healthy control subjects. A total of 116 participants with major depressive disorder treated with sertraline in stage 1 served as an independent replication sample. The probabilistic reward task and resting-state functional magnetic resonance imaging were administered at baseline. RESULTS: Greater pretreatment reward sensitivity and higher resting-state functional connectivity between bilateral nucleus accumbens and rostral anterior cingulate cortex were associated with positive response to bupropion but not sertraline. Null findings for sertraline were replicated in the stage 1 sample. CONCLUSIONS: Pretreatment reward sensitivity and frontostriatal connectivity may identify patients likely to benefit from bupropion following selective serotonin reuptake inhibitor failures. Results call for a prospective replication based on these biomarkers to advance clinical care.

An electroencephalographic signature predicts antidepressant response in major depression.

Antidepressants are widely prescribed, but their efficacy relative to placebo is modest, in part because the clinical diagnosis of major depression encompasses biologically heterogeneous conditions. Here, we sought to identify a neurobiological signature of response to antidepressant treatment as compared to placebo. We designed a latent-space machine-learning algorithm tailored for resting-state electroencephalography (EEG) and applied it to data from the largest imaging-coupled, placebo-controlled antidepressant study (n = 309). Symptom improvement was robustly predicted in a manner both specific for the antidepressant sertraline (versus placebo) and generalizable across different study sites and EEG equipment. This sertraline-predictive EEG signature generalized to two depression samples, wherein it reflected general antidepressant medication responsivity and related differentially to a repetitive transcranial magnetic stimulation treatment outcome. Furthermore, we found that the sertraline resting-state EEG signature indexed prefrontal neural responsivity, as measured by concurrent transcranial magnetic stimulation and EEG. Our findings advance the neurobiological understanding of antidepressant treatment through an EEG-tailored computational model and provide a clinical avenue for personalized treatment of depression.

Brain regulation of emotional conflict predicts antidepressant treatment response for depression.

The efficacy of antidepressant treatment for depression is controversial due to the only modest superiority demonstrated over placebo. However, neurobiological heterogeneity within depression may limit overall antidepressant efficacy. We sought to identify a neurobiological phenotype responsive to antidepressant treatment by testing pretreatment brain activation during response to, and regulation of, emotional conflict as a moderator of the clinical benefit of the antidepressant sertraline versus placebo. Using neuroimaging data from a large randomized controlled trial, we found widespread moderation of clinical benefits by brain activity during regulation of emotional conflict, in which greater downregulation of conflict-responsive regions predicted better sertraline outcomes. Treatment-predictive machine learning using brain metrics outperformed a model trained on clinical and demographic variables. Our findings demonstrate that antidepressant response is predicted by brain activity underlying a key self-regulatory emotional capacity. Leveraging brain-based measures in psychiatry will forge a path toward better treatment personalization, refined mechanistic insights and improved outcomes.

Anxiety and anhedonia in depression: Associations with neuroticism and cognitive control.

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.

Pretreatment Rostral Anterior Cingulate Cortex Connectivity With Salience Network Predicts Depression Recovery: Findings From the EMBARC Randomized Clinical Trial.

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.

The Concise Health Risk Tracking-Self Report: Psychometrics within a placebo-controlled antidepressant trial among depressed outpatients.

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.

Keppi: A Tangible User Interface for Self-Reporting Pain.

Motivated by the need to support those self-managing chronic pain, we report on the development and evaluation of a novel pressure-based tangible user interface (TUI) for the self-report of scalar values representing pain intensity. Our TUI consists of a conductive foam-based, force-sensitive resistor (FSR) covered in a soft rubber with embedded signal conditioning, an ARM Cortex-M0 microprocessor, and Bluetooth Low Energy (BLE). In-lab usability and feasibility studies with 28 participants found that individuals were able to use the device to make reliable reports with four degrees of freedom as well map squeeze pressure to pain level and visual feedback. Building on insights from these studies, we further redesigned the FSR into a wearable device with multiple form factors, including a necklace, bracelet, and keychain. A usability study with an additional 7 participants from our target population, elderly individuals with chronic pain, found high receptivity to the wearable design, which offered a number of participant-valued characteristics (e.g., discreetness) along with other design implications that serve to inform the continued refinement of tangible devices that support pain self-assessment.

Test-retest reliability of cerebral blood flow in healthy individuals using arterial spin labeling: Findings from the EMBARC study.

INTRODUCTION: Previous investigations of test-retest reliability of cerebral blood flow (CBF) at rest measured with pseudo-continuous Arterial Spin Labeling (pCASL) demonstrated good reliability, but are limited by the use of similar scanner platforms. In the present study we examined test-retest reliability of CBF in regions implicated in emotion and the default mode network. MATERIAL AND METHODS: We measured absolute and relative CBF at rest in thirty-one healthy subjects in two scan sessions, one week apart, at four different sites and three different scan platforms. We derived CBF from pCASL images with an automated algorithm and calculated intra-class correlation coefficients (ICCs) across sessions for regions of interest. In addition, we investigated site effects. RESULTS: For both absolute and relative CBF measures, ICCs were good to excellent (i.e. >0.6) in most brain regions, with highest values observed for the subgenual anterior cingulate cortex and ventral striatum. A leave-one-site-out cross validation analysis did not show a significant effect for site on whole brain CBF and there was no proportional bias across sites. However, a significant site effect was present in the repeated measures ANOVA. CONCLUSIONS: The high test-retest reliability of CBF measured with pCASL in a range of brain regions implicated in emotion and salience processing, emotion regulation, and the default mode network, which have been previously linked to depression symptomatology supports its use in studies that aim to identify neuroimaging biomarkers of treatment response.

Pretreatment Rostral Anterior Cingulate Cortex Theta Activity in Relation to Symptom Improvement in Depression: A Randomized Clinical Trial.

Importance: Major depressive disorder (MDD) remains challenging to treat. Although several clinical and demographic variables have been found to predict poor antidepressant response, these markers have not been robustly replicated to warrant implementation in clinical care. Increased pretreatment rostral anterior cingulate cortex (rACC) theta activity has been linked to better antidepressant outcomes. However, no prior study has evaluated whether this marker has incremental predictive validity over clinical and demographic measures. Objective: To determine whether increased pretreatment rACC theta activity would predict symptom improvement regardless of randomization arm. Design, Setting, and Participants: A multicenter randomized clinical trial enrolled outpatients without psychosis and with chronic or recurrent MDD between July 29, 2011, and December 15, 2015 (Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care [EMBARC]). Patients were consecutively recruited from 4 university hospitals: 634 patients were screened, 296 were randomized to receive sertraline hydrochloride or placebo, 266 had electroencephalographic (EEG) recordings, and 248 had usable EEG data. Resting EEG data were recorded at baseline and 1 week after trial onset, and rACC theta activity was extracted using source localization. Intent-to-treat analysis was conducted. Data analysis was performed from October 7, 2016, to January 19, 2018. Interventions: An 8-week course of sertraline or placebo. Main Outcomes and Measures: The 17-item Hamilton Rating Scale for Depression score (assessed at baseline and weeks 1, 2, 3, 4, 6, and 8). Results: The 248 participants (160 [64.5%] women, 88 [35.5%] men) with usable EEG data had a mean (SD) age of 36.75 (13.15) years. Higher rACC theta activity at both baseline (b = -1.05; 95% CI, -1.77 to -0.34; P = .004) and week 1 (b = -0.83; 95% CI, -1.60 to -0.06; P < .04) predicted greater depressive symptom improvement, even when controlling for clinical and demographic variables previously linked with treatment outcome. These effects were not moderated by treatment arm. The rACC theta marker, in combination with clinical and demographic variables, accounted for an estimated 39.6% of the variance in symptom change (with 8.5% of the variance uniquely attributable to the rACC theta marker). Conclusions and Relevance: Increased pretreatment rACC theta activity represents a nonspecific prognostic marker of treatment outcome. This is the first study to date to demonstrate that rACC theta activity has incremental predictive validity. Trial Registration: clinicaltrials.gov Identifier: NCT01407094.

Characterizing anxiety subtypes and the relationship to behavioral phenotyping in major depression: Results from the EMBARC study.

The current study aimed to characterize the multifaceted nature of anxiety in patients with major depression by evaluating distinct anxiety factors. We then related these derived anxiety factors to performance on a Flanker Task of cognitive control, in order to further validate these factors. Data were collected from 195 patients with nonpsychotic chronic or recurrent major depression or dysthymic disorder. At baseline, participants completed self-report measures of anxiety, depression, and other related symptoms (mania, suicidality) and clinicians administered a structured diagnostic interview and the Hamilton Rating Scale for Depression, including anxiety/somatization items. Four discrete factors (State Anxiety, Panic, Neuroticism/Worry, and Restlessness/Agitation) emerged, with high degrees of internal consistency. Discriminant and convergent validity analyses also yielded findings in the expected direction. Furthermore, the neuroticism/worry factor was associated with Flanker Task interference, such that individuals higher on neuroticism/worry responded more incorrectly (yet faster) to incongruent vs. congruent trials whereas individuals higher on the fear/panic factor responded more slowly, with no accuracy effect, to the Flanker Task stimuli. These results parse anxiety into four distinct factors that encompass physiological, psychological, and cognitive components of anxiety. While state anxiety, panic and neuroticism/worry are related to existing measures of anxiety, the Restlessness/Agitation factor appears to be a unique measure of general anxious arousal. Furthermore, two factors were independently validated through the Flanker Task. These results suggest that these anxiety domains have distinct behavioral profiles and could have differential responses to distinct treatments.

Supporting the Self-Management of Chronic Pain Conditions with Tailored Momentary Self-Assessments.

To better support the self-management of chronic pain, this paper investigates how those living with the condition prefer to self-assess their pain levels using smartphones. Our work consists of three stages: design ideation and review, an in-lab user study with 10 participants resulting in nine candidate interfaces, and a 3 week field trial of two further honed measures with 12 participants. This research firstly yields a better understanding of participants' strong and sometimes contrasting preferences regarding their self-assessment of pain intensity. We additionally contribute two novel interfaces that support accurate, quick, and repeated use along with other participant-valued interactions (e.g., familiar, relatable, and highly usable). In particular, we focus on designing tailored measures that both enhance respondent motivation as well as minimize the difficulty of meaningful self-assessment by supporting the cog-nitive effort in translating a subjective experience into a single numerical value.

A comparison of structural connectivity in anxious depression versus non-anxious depression.

BACKGROUND: Major depressive disorder (MDD) and anxiety disorders are highly co-morbid. Research has shown conflicting evidence for white matter alteration and amygdala volume reduction in mood and anxiety disorders. To date, no studies have examined differences in structural connectivity between anxious depressed and non-anxious depressed individuals. This study compared fractional anisotropy (FA) and density of selected white matter tracts and amygdala volume between anxious depressed and non-anxious depressed individuals. METHODS: 64- direction DTI and T1 scans were collected from 110 unmedicated subjects with MDD, 39 of whom had a co-morbid anxiety disorder diagnosis. Region of interest (ROI) and tractography methods were performed to calculate amygdala volume and FA in the uncinate fasciculus, respectively. Diffusion connectometry was performed to identify whole brain group differences in white matter health. Correlations were computed between biological and clinical measures. RESULTS: Tractography and ROI analyses showed no significant differences between bilateral FA values or bilateral amygdala volumes when comparing the anxious depressed and non-anxious depressed groups. The diffusion connectometry analysis showed no significant differences in anisotropy between the groups. Furthermore, there were no significant relationships between MRI-based and clinical measures. CONCLUSION: The lack of group differences could indicate that structural connectivity and amygdalae volumes of those with anxious-depression are not significantly altered by a co-morbid anxiety disorder. Improving understanding of anxiety co-morbid with MDD would facilitate development of treatments that more accurately target the underlying networks.

Establishing moderators and biosignatures of antidepressant response in clinical care (EMBARC): Rationale and design.

UNLABELLED: Remission rates for Major Depressive Disorder (MDD) are low and unpredictable for any given antidepressant. No biological or clinical marker has demonstrated sufficient ability to match individuals to efficacious treatment. Biosignatures developed from the systematic exploration of multiple biological markers, which optimize treatment selection for individuals (moderators) and provide early indication of ultimate treatment response (mediators) are needed. The rationale and design of a multi-site, placebo-controlled randomized clinical trial of sertraline examining moderators and mediators of treatment response is described. The target sample is 300 participants with early onset (≤30 years) recurrent MDD. Non-responders to an 8-week trial are switched double blind to either bupropion (for sertraline non-responders) or sertraline (for placebo non-responders) for an additional 8 weeks. Clinical moderators include anxious depression, early trauma, gender, melancholic and atypical depression, anger attacks, Axis II disorder, hypersomnia/fatigue, and chronicity of depression. Biological moderator and mediators include cerebral cortical thickness, task-based fMRI (reward and emotion conflict), resting connectivity, diffusion tensor imaging (DTI), arterial spin labeling (ASL), electroencephalograpy (EEG), cortical evoked potentials, and behavioral/cognitive tasks evaluated at baseline and week 1, except DTI, assessed only at baseline. The study is designed to standardize assessment of biomarkers across multiple sites as well as institute replicable quality control methods, and to use advanced data analytic methods to integrate these markers. A Differential Depression Treatment Response Index (DTRI) will be developed. The data, including biological samples (DNA, RNA, and plasma collected before and during treatment), will become available in a public scientific repository. CLINICAL TRIAL REGISTRATION: Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care for Depression (EMBARC). Identifier: NCT01407094. URL: http://clinicaltrials.gov/show/NCT01407094.

Pneumomediastinum in a trumpeter diagnosed by the presence of Hamman's crunch.

A trumpet player presented with sudden onset chest sounds corresponding with systole. He was otherwise asymptomatic, and the complaint resolved spontaneously. He was diagnosed with pneumomediastinum clinically on the basis of the presence of Hamman's crunch, and was discharged home without complication.

Pilot study of Aurora, a social, mobile-phone-based emotion sharing and recording system.

BACKGROUND: Emotion is a ubiquitous aspect of humanity that governs behavior in a number of ways and is linked inextricably with health. Pausing to evaluate one's emotional state in the face of decisions and reflecting on past patterns of emotion have been shown to improve behaviors. Further, social expression of emotion has been shown to directly improve health outcomes. While the virtual reality research community does not ignore emotion on the whole, there does exist a need to explore what roles emotional awareness and emotion sharing can play in this domain. METHODS: A mobile-phone-based social emotion recording and sharing system, Aurora, was developed to provide individuals with a means to pause and evaluate their emotional state, reflect on past emotions, share emotions with others, and participate in socially supportive activities with peers. A study was conducted with 65 subjects to evaluate Aurora as a tool to encourage emotional reflection and awareness as well as social sharing of emotion. RESULTS: Users of Aurora reported an increased comfort in socially expressing emotion and were encouraged to share emotions, even with strangers. Subjects also reported liking reflecting on their emotional state and found it valuable. Subjects' behavior also suggested that the system encouraged individuals to reach out to one another in acts of social support. CONCLUSIONS: The Aurora system offers a tool for encouraging emotional awareness, emotion sharing, and socially supportive behavior. Such a tool could be impactful in numerous health settings where emotion is considered to be an important indicator of or influence on outcome, such as for weight loss, alcohol cessation, or cancer sufferers.