Early changes in neural circuit function engaged by negative emotion and modified by behavioural intervention are associated with depression and problem-solving outcomes: A report from the ENGAGE randomized controlled trial

BACKGROUND

Depression exerts a staggering toll that is worsened with co-occurring chronic conditions such as obesity. It is imperative to develop more effective interventions for depression and to identify objective and biological plausible neural mechanisms to understand intervention outcomes. The current study uses functional neuroimaging to determine whether a behavioural intervention changes the negative affect circuit and whether these changes relate to subsequent improvements in both symptom and problem-solving outcomes in depressed patients with co-occurring obesity.

METHODS

This study ('ENGAGE') was a pre-planned element of the randomized controlled trial, 'RAINBOW' (ClinicalTrials.gov NCT02246413). 108 depressed patients with obesity were randomized to receive an integrated collaborative care intervention (I-CARE) or usual care. Participants underwent functional neuroimaging using an established facial emotion task at baseline and two months (coinciding with the first two months of intervention focused on problem-solving therapy ('PST')). Amygdala, insula and anterior cingulate cortex activation was extracted using pre-planned definitions and standardized methods. The primary health and behavioural outcomes were depression symptom severity and problem-solving ability respectively, assessed at baseline, the main 6-month outcome point and at 12-month follow up. Mediation analyses used an intent-to-treat approach.

FINDINGS

PST, relative to usual care, reduced amygdala activation engaged by threat stimuli at two months. This reduction mediated subsequent improvements in depression severity in an intervention-dependent manner. PST did not change insula activation at two months but did temper the strength of the relationship between insula activation and improvements in problem-solving ability.

INTERPRETATION

The negative affect circuit may be an important neural target and potential mediator of PST in patients with comorbid obesity.

FUNDING

US National Institutes of Health/National Heart Lung and Blood Institute R01 HL119453 and UH2/UH3 HL132368.

StopWatch: Pilot study for an Apple Watch application for youth with ADHD

Introduction

To address the need for non-pharmacologic, scalable approaches for managing attention-deficit and hyperactivity disorder (ADHD) in young people, we report the results of a study of an application developed for a wearable device (Apple Watch) that was designed to track movement and provide visual and haptic feedback for ADHD.

Methods

Six-week, open label pilot study with structured rating scales ADHD and semi-structured qualitative interview. Apple Watch software application given to users that uses actigraphy and graphic interface as well as haptic feedback to provide feedback to users about level of movement during periods of intentional focus. Linear mixed models to estimate trajectories.

Results

Thirty-two participants entered the study. This application was associated with improvement in ADHD symptoms over the 6 weeks of the study. We observed an ADHD-Rating Scale change of β = −1.2 units/week (95% CI = −0.56 to −1.88, F = 13.4, P = .0004).

Conclusions

These positive clinical outcomes highlight the promise of such wearable applications for ADHD and the need to pursue their further development.

Understanding mechanisms of integrated behavioral therapy for co-occurring obesity and depression in primary care: a mediation analysis in the RAINBOW trial

The RAINBOW trial demonstrated that an integrated collaborative care intervention was effective for improving weight and depression. This study examined mediation of the treatment effect by a priori specified lifestyle behaviors and cognitive functioning. Participants were randomized to a 12-month integrated intervention (n = 204) or usual care (n = 205). Body mass index (BMI) and 20-item Depression Symptom Check List (SCL-20) were co-primary outcomes (Y). To examine mediation, we assessed (a) the effect of the integrated intervention (X) on lifestyle behaviors (diet and physical activity) and cognitive functioning (problem-solving; M, X→M path a) and (b) the association of these behaviors with BMI and SCL-20 (M→Y path b). Mediation existed if paths a and b were significant or if path a and the product of coefficients test (paths a and b) were significant. Compared with usual care, the intervention led to significant improvements in leisure time physical activity (201.3 MET minutes/week [SD, 1,457.6]) and total calorie intake (337.4 kcal/day [818.3]) at 6 months but not 12 months (path a). These improvements were not significantly associated with improvements in BMI or SCL-20 (path b). However, avoidant problem-solving style score and increased fruit and vegetable intake significantly correlated with improvements in BMI at 6 and 12 months, respectively. Also, increased fruit and vegetable intake, higher dietary quality, and better problem-solving abilities significantly correlated with improvements in SCL-20 at 6 and 12 months. These findings did not support the hypothesized mediation, but suggest lifestyle behaviors and cognitive functioning to target in future intervention optimization.

Sex Moderates Treatment Effects of Integrated Collaborative Care for Comorbid Obesity and Depression: The RAINBOW RCT

BACKGROUND

Sex influences health and related behaviors due to biological and psychosocial/socioeconomic factors. Assessing sex-specific responses to integrated treatment for comorbid obesity and depression could inform intervention targeting.

PURPOSE

To test (a) whether sex moderates the effects of integrated collaborative care on weight and depression outcomes through 24 months and (b) whether treatment response at 6 months predicts 12 and 24 month outcomes by sex.

METHODS

Secondary data analyses on weight and depression severity (SCL-20) measured over 24 months among 409 adults with obesity and depression in the Research Aimed at Improving Both Mood and Weight trial.

RESULTS

Men achieved significantly greater weight reductions in intervention versus usual care than women, whereas women achieved significantly greater percentage reductions in SCL-20 than men at both 12 and 24 months. In logistic models, at 80% specificity for correctly identifying participants not achieving clinically significant long-term outcomes, women who lost <3.0% weight and men who lost <4.1% weight at 6 months had ≥84% probability of not meeting 5% weight loss at 24 months. Similarly, at 80% specificity, women who reduced SCL-20 by <39.5% and men who reduced by <53.0% at 6 months had ≥82% probability of not meeting 50% decrease in SCL-20 at 24 months.

CONCLUSIONS

Sex modified the integrated treatment effects for obesity and depression. Sex-specific responses at 6 months predicted clinically significant weight loss and depression outcomes through 24 months. Based on early responses, interventions may need to be tailored to address sex-specific barriers and facilitators to achieving healthy weight and depression outcomes at later time points.

CLINICAL TRIAL REGISTRATION

NCT02246413 (https://clinicaltrials.gov/ct2/show/NCT02246413).

The factor structure of depressive symptoms in patients with obesity enrolled in the RAINBOW clinical trial

BACKGROUND

Examining variability in the presenting symptoms of depression may be particularly important in characterizing depression in patients with comorbid conditions such as obesity. Identifying the underlying constructs of depression in such patients may produce phenotypic information to aid diagnosis and treatment decisions.

OBJECTIVE

To examine the latent factors of symptoms using the depression Symptom Checklist (SCL-20) and the Patient Health Questionnaire (PHQ-9), separately, in patients with obesity and elevated depressive symptoms.

METHODS

Exploratory factor analysis (EFA) was performed on baseline data from 409 patients with obesity and elevated depressive symptoms recruited in primary care. Bootstrap analysis was performed to estimate the precision and potential replicability of identified latent factors.

RESULTS

Participants (70% women, mean age of 51.0 ± 12.1 years) had moderate depression. EFA of the SCL-20 suggested two reliable factors: dysphoric mood (71% of the variance) and anhedonia (15% of the variance). EFA of the PHQ-9 yielded one factor: dysphoric mood (87% of the variance). Bootstrapped results supported the replicability of these results. The top most endorsed symptoms were feeling low energy, overeating and disturbed sleep.

LIMITATIONS

The generalizability of these findings to severe depression may be limited.

CONCLUSIONS

Patients with elevated depressive symptoms and obesity present with heterogeneous symptoms. The SCL-20 seems more sensitive than the PHQ-9 for differentiating symptom profiles in this population. Some possible reasons include: 1) differences in number of scale items, and 2) differences in the aspects of depression they tap into; the SCL-20 measures the severity of symptoms, whereas the PHQ-9 measures the frequency of symptoms.

The impact of online brain training exercises on experiences of depression, anxiety and emotional wellbeing in a twin sample

This study assessed the effectiveness of cognitive and emotional brain training and transfer effects to wellbeing and depression and anxiety symptoms. 352 healthy adult twins were randomised to a training group where they were asked to play brain training games over a 30-day period, or a waitlist control group. This study focused on the impact of the brain training on explicit and implicit emotional cognition, and analysed effects using both Intention-To-Treat (ITT) and Per-Protocol (PP) approaches. Both analyses revealed significant training effects for improvement in the explicit identification of fear expressions (ITT: p < 0.001, d = 0.33; PP training 3 h+: p < 0.001, d = 0.55), and a reduction in implicit bias for anger expressions amongst males (ITT: p < 0.001, d = 0.94; PP training 3 h+: p = 0.04, d = 0.90). Female participants also showed improvements in implicit bias for happy expressions (ITT: p = 0.003, d = 0.34; PP training 3 h+: p = 0.03, d = 0.47). Improvements resulting from training in emotional cognition did not directly improve wellbeing, depression or anxiety symptoms. Regression modelling also suggested training improvements in emotional cognition yielded no indirect transfer effects for the mental health and wellbeing measures. The results suggest brain training in healthy populations has potential for improving emotional cognition, but the subsequent impact on improving wellbeing and mental health symptoms is still equivocal.

Reduced functional connectivity of default mode network subsystems in depression: Meta-analytic evidence and relationship with trait rumination

Resting-state functional connectivity changes in the default mode network (DMN) of patients with major depressive disorder (MDD) have been linked to rumination. The DMN is divided into three subsystems: a midline Core, a dorsal medial prefrontal cortex (DMPFC) subsystem, and a medial temporal lobe (MTL) subsystem. We examined resting-state functional connectivity within and between DMN subsystems in MDD and its association with rumination. First, we conducted a meta-analysis on a large multi-site dataset of 618 MDD and 683 controls to quantify the differences in DMN subsystem functional connectivity between MDD and controls. Second, we tested the association of DMN subsystem functional connectivity and rumination in a sample of 115 unmedicated participants with symptoms of anxiety/depression and 48 controls. In our meta-analysis, only functional connectivity in the DMN Core was significantly reduced in MDD compared to controls (g = -0.246, CI = [-0.417; -0.074], pFDR = 0.048). Functional connectivity in the DMPFC subsystem and between the Core and DMPFC subsystems was slightly reduced but not significantly (g = -0.162, CI = [-0.310; -0.013], pFDR = 0.096; g = -0.249, CI = [-0.464; -0.034], pFDR = 0.084). Results were heterogeneous across sites for connectivity in the Core and between Core and DMPFC (I2 = 0.348 and I2 = 0.576 respectively). Prediction intervals consistently encompassed 0. In the independent sample we collected, functional connectivity within the DMN Core, DMPFC and between Core and DMPFC was not reduced in MDD compared to controls (all pFDR > 0.05). Trait rumination did not predict connectivity within and between DMN subsystems (all pFDR > 0.05). We conclude that MDD as a diagnostic category shows slightly reduced functional connectivity within the DMN Core, independent of illness duration, treatment, symptoms and trait rumination. However, this effect is small, highly variable and heterogeneous across samples, so that we could only detect it at the meta-analytic level, with a sample size of several hundreds. Our results indicate that reduced Core DMN connectivity has significant limitations as a potential clinical or prognostic marker for the diagnosis of MDD and might be more relevant to consider as a characteristic distinguishing a subgroup of individuals within this diagnostic category.

Identifying response and predictive biomarkers for Transcranial magnetic stimulation outcomes: protocol and rationale for a mechanistic study of functional neuroimaging and behavioral biomarkers in veterans with Pharmacoresistant depression

BACKGROUND

Although repetitive transcranial magnetic stimulation ('TMS') is becoming a gold standard treatment for pharmacoresistant depression, we lack neural target biomarkers for identifying who is most likely to respond to TMS and why. To address this gap in knowledge we evaluate neural targets defined by activation and functional connectivity of the dorsolateral prefrontal cortex-anchored cognitive control circuit, regions of the default mode network and attention circuit, and interactions with the subgenual anterior cingulate. We evaluate whether these targets and interactions between them change in a dose-dependent manner, whether changes in these neural targets correspond to changes in cognitive behavioral performance, and whether baseline and early change in neural target and cognitive behavioral performance predict subsequent symptom severity, suicidality, and quality of life outcomes. This study is designed as a pragmatic, mechanistic trial partnering with the National Clinical TMS Program of the Veteran's Health Administration.

METHODS

Target enrollment consists of 100 veterans with pharmacoresistant Major Depressive Disorder (MDD). All veterans will receive a clinical course of TMS and will be assessed at 'baseline' pre-TMS commencement, 'first week' after initiation of TMS (targeting five sessions) and 'post-treatment' at the completion of TMS (targeting 30 sessions). Veterans will be assessed using functional magnetic resonance imaging (fMRI), a cognitive behavioral performance battery, and established questionnaires. Multivariate linear mixed models will be used to assess whether neural targets change with TMS as a function of dose (Aim 1), whether extent and change of neural target relates to and predicts extent of behavioral performance (Aim 3), and whether extent of neural target change predicts improvement in symptom severity, suicidality, and quality of life (Aim 3). For all three aims, we will also assess the contribution of baseline moderators such as biological sex and age.

DISCUSSION

To our knowledge, our study will be the first pragmatic, mechanistic observational trial to use fMRI imaging and cognitive-behavioral performance as biomarkers of TMS treatment response in pharmacoresistant MDD. The results of this trial will allow providers to select suitable candidates for TMS treatment and better predict treatment response by assessing circuit connectivity and cognitive-behavioral performance at baseline and during early treatment.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04663481 , December 5th, 2020, retrospectively registered. The first veteran was enrolled October 30th, 2020.

White matter anisotropy and response to cognitive behavior therapy for posttraumatic stress disorder

Trauma-focused cognitive behavior therapy (TF-CBT) is the gold standard treatment for posttraumatic stress disorder (PTSD), up to one-half of PTSD patients remain treatment non-responders. Although studies have used functional MRI to understand the neurobiology of treatment response, there is less understanding of the role of white matter brain structures in response to TF-CBT. Thirty-six treatment-seeking PTSD patients and 33 age-gender matched healthy controls completed diffusion-weighted imaging scans at baseline. Patients underwent nine sessions of TF-CBT treatment and PTSD symptom severity was assessed with the Clinician-Administered PTSD Scale before and after completing treatment. Patients were assessed to estimate the reduction in overall symptoms and also specifically fear and dysphoric symptoms of PTSD. Tract-based spatial statistical analyses were performed for the PTSD group to evaluate whole-brain correlations of fractional anisotropy (FA) with improvement in overall, fear, and dysphoric symptoms using non-parametric permutation inference testing (p_FWE < 0.05). Next, we evaluated if these significant measures also characterized PTSD from controls. Greater improvement in dysphoric symptoms was found correlated with lower FA in white matter regions associated with the limbic system, frontal cortex, thalamic association and projection fibers, corpus callosum, and tracts related to the brainstem. White matter anisotropy was not found associated with either overall or fear symptoms. FA in the significant clusters was similar between PTSD and controls. White-matter related to key functional regions may also play an important role in response to TF-CBT. Our results underscore the heterogeneity of PTSD and the need to evaluate distinct symptom phenotypes in treatment studies.

Neural correlates of emotional processing in panic disorder

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Abnormal non-conscious emotion processing in panic disorder.

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Impaired recruitment of implicit regulatory regions during affect processing.

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Lower pgACC activation in panic disorder for sad and happy faces.

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Deficits in key regulatory connections between inhibitory and emotion brain regions.

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Lower pgACC-amygdala connectivity for sad and fear faces.

Background

Deficits in emotional processing are conceptualized in prevailing models of anxiety to underpin key symptoms of panic disorder (PD). Neuroimaging studies show evidence of aberrant neural functioning in PD patients during emotional processing, however little is understood about how non-conscious emotional processing impacts neural processes.

Method

We examined activation and functional connectivity differences in brain regions involved in emotional processing between PD and healthy controls (HC) during subliminal and supraliminal presentations of facial emotions. Twenty-two PD and 33 HC participants were shown happy, sad, neutral, fear, anger and disgust facial expressions during functional magnetic resonance imaging using a 3T MRI scanner. We performed voxelwise ROI analyses at FWE-corrected p < 0.05 for main effects of group and group*emotion interactions.

Results

There was less pregenual anterior cingulate cortex (pgACC) activation to subliminal presentations of happy and sad faces in PD compared to HC participants (group*emotion). In addition, PD patients had less pgACC - right amygdala connectivity than HC participants during sad and fear subliminal processing (group*emotion). PD patients also exhibited lower right cerebellum activity across all supraliminal presentations of facial expressions compared to HC.

Conclusion

These findings suggest that there is aberrant neural processing in PD patients during both conscious and preconscious processing of both positive and negative stimuli, suggesting impaired recruitment of implicit regulatory networks during affective processing. It appears that PD patients may experience deficits in key regulatory connections between inhibitory and emotional neural networks at very early stages of processing of negative affective states.

Stress Markers for Mental States and Biotypes of Depression and Anxiety: A Scoping Review and Preliminary Illustrative Analysis

Depression and anxiety disrupt daily function and their effects can be long-lasting and devastating, yet there are no established physiological indicators that can be used to predict onset, diagnose, or target treatments. In this review, we conceptualize depression and anxiety as maladaptive responses to repetitive stress. We provide an overview of the role of chronic stress in depression and anxiety and a review of current knowledge on objective stress indicators of depression and anxiety. We focused on cortisol, heart rate variability and skin conductance that have been well studied in depression and anxiety and implicated in clinical emotional states. A targeted PubMed search was undertaken prioritizing meta-analyses that have linked depression and anxiety to cortisol, heart rate variability and skin conductance. Consistent findings include reduced heart rate variability across depression and anxiety, reduced tonic and phasic skin conductance in depression, and elevated cortisol at different times of day and across the day in depression. We then provide a brief overview of neural circuit disruptions that characterize particular types of depression and anxiety. We also include an illustrative analysis using predictive models to determine how stress markers contribute to specific subgroups of symptoms and how neural circuits add meaningfully to this prediction. For this, we implemented a tree-based multi-class classification model with physiological markers of heart rate variability as predictors and four symptom subtypes, including normative mood, as target variables. We achieved 40% accuracy on the validation set. We then added the neural circuit measures into our predictor set to identify the combination of neural circuit dysfunctions and physiological markers that accurately predict each symptom subtype. Achieving 54% accuracy suggested a strong relationship between those neural-physiological predictors and the mental states that characterize each subtype. Further work to elucidate the complex relationships between physiological markers, neural circuit dysfunction and resulting symptoms would advance our understanding of the pathophysiological pathways underlying depression and anxiety.

Deep phenotyping of attention impairments and the 'Inattention Biotype' in Major Depressive Disorder

BACKGROUND

Attention impairment is an under-investigated feature and diagnostic criterion of Major Depressive Disorder (MDD) that is associated with poorer outcomes. Despite increasing knowledge regarding mechanisms of attention in healthy adults, we lack a detailed characterization of attention impairments and their neural signatures in MDD.

METHODS

Here, we focus on selective attention and advance a deep multi-modal characterization of these impairments in MDD, using data acquired from n = 1008 patients and n = 336 age- and sex-matched healthy controls. Selective attention impairments were operationalized and anchored in a behavioral performance measure, assessed within a battery of cognitive tests. We sought to establish the accompanying neural signature using independent measures of functional magnetic resonance imaging (15% of the sample) and electroencephalographic recordings of oscillatory neural activity.

RESULTS

Greater impairment on the behavioral measure of selective attention was associated with intrinsic hypo-connectivity of the fronto-parietal attention network. Not only was this relationship specific to the fronto-parietal network unlike other large-scale networks; this hypo-connectivity was also specific to selective attention performance unlike other measures of cognition. Selective attention impairment was also associated with lower posterior alpha (8-13 Hz) power at rest and was related to more severe negative bias (frequent misidentifications of neutral faces as sad and lingering attention on sad faces), relevant to clinical features of negative attributions and brooding. Selective attention impairments were independent of overall depression severity and of worrying or sleep problems.

CONCLUSIONS

These results provide a foundation for the clinical translational development of objective markers and targeted therapeutics for attention impairment in MDD.

Differential neural predictors of treatment response for fear and dysphoric features of posttraumatic stress disorder

BACKGROUND

Although trauma-focused cognitive behavioral therapy (TF-CBT) is the frontline treatment for posttraumatic stress disorder (PTSD), at least one-third of patients are treatment nonresponders. This study aimed to identify neural markers of treatment response, specifically the prediction of remission of specific PTSD symptoms.

METHODS

This study assessed PTSD treatment-seeking patients (n = 40) before TF-CBT during functional magnetic brain resonance imaging (fMRI) when they processed fearful, sad, happy, and neutral faces. Patients underwent nine sessions of TF-CBT and were independently assessed on the Clinician-Administered PTSD Scale (CAPS) following treatment. Treatment responders and nonresponders were compared with healthy controls (n = 40). The severity of PTSD was assessed with the CAPS. fMRI responses were calculated for each emotion face compared to neutral contrast, which were correlated with reduction in PTSD severity from pretreatment to posttreatment. Treatment response was categorized by at least 50% reduction in the severity of PTSD.

RESULTS

The activation of left insula during the processing of both sad and fearful faces was associated with a greater reduction of fear but not with dysphoric symptoms after treatment. Connectivity of the left insula to the pregenual anterior cingulate cortex was associated with poorer response to treatment. Responders and controllers had similar levels of activation and connectivity and were different from nonresponders.

CONCLUSIONS

Positive response to TF-CBT is predicted during emotion processing by normal levels of recruitment of neural networks implicated in emotional information. These findings suggest that distinct neural networks are predictive of PTSD fear and dysphoric symptom reduction following TF-CBT.

Intrinsic functional connectivity of the default mode and cognitive control networks relate to change in behavioral performance over two years

Understanding how brain circuitry mediates cognitive control of behavior is crucial for understanding both mental health and disease. Cognitive control describes the group of behaviors that guide goal-directed action such as sustaining attention, processing information and inhibiting impulsive responses. We rely on these behaviors for daily social, occupational and emotional functioning. Two brain networks, the cognitive control network (CCN) and default mode network (DMN), are thought to cooperate in an inverse relationship to support these functions. However, we do not yet know how connectivity within and between these networks directly relates to healthy cognitive control behaviors, and whether these interactions change over time. Here, we employed a longitudinal design to investigate if change in intrinsic connectivity in these networks will correlate with change in a range of cognitive control functions. Over two years, 109 healthy individuals, aged eight to thirty-eight, were tested twice using fMRI to assess intrinsic functional connectivity of the CCN and DMN and a validated cognitive battery. We found that increased within-network connectivity through central and left DMN was associated with increased memory performance. Additionally, decreased connectivity between posterior parietal CCN and DMN nodes and decreased connectivity between left and right dorsolateral prefrontal nodes was associated with increased cognitive performance. These findings were age and gender controlled, suggesting that age-independent plastic change in intrinsic connectivity through these networks directly relate to changing behavior. This has implications for targeting intrinsic connectivity as a possible mechanism to improve cognitive function.

Diverse phenotypic measurements of wellbeing: Heritability, temporal stability and the variance explained by polygenic scores

Wellbeing, a key aspect of mental health, is moderately heritable with varying estimates reported from independent studies employing a variety of instruments. Recent genome-wide association studies (GWAS) have enabled the construction of polygenic scores (PGS) for wellbeing, providing the opportunity for direct comparisons of the variance explained by PGS for different instruments commonly employed in the field. Nine wellbeing measurements (multi-item and single-item), two personality domains (NEO-FFI neuroticism and extraversion), plus the depression domain of the DASS-42 were drawn from a larger self-report battery applied to the TWIN-E study-an Australian longitudinal twin cohort (N = 1660). Heritability was estimated using univariate twin modeling and 12-month test-retest reliability was estimated using intra-class correlation. PGS were constructed using wellbeing GWAS summary-statistics from Baselmans et al. (Nat Genet. 2019), and the variance explained estimated using linear models. Last, a GWAS was performed using COMPAS-W, a quantitative composite wellbeing measure, to explore its utility in genomic studies. Heritability estimates ranged from 23% to 47% across instruments, and multi-item measures showed higher heritability and test-retest reliability than single-item measures. The variance explained by PGS was ~0.5% to 1.5%, with considerable variation between measures, and within each measure over 12 months. Five loci with suggestive association (p < 1 × 10^-5 ) were identified from this initial COMPAS-W wellbeing GWAS. This work highlights the variability across measures currently employed in wellbeing research, with multi-item and composite measures favored over single-item measures. While wellbeing PGS are useful in a research setting, they explain little of the phenotypic variance, highlighting gaps for improved gene discovery.

Neurophysiological markers of attention distinguish bipolar disorder and unipolar depression

BACKGROUND

Attentional deficits are common in both symptomatic and symptom-remitted patients with bipolar disorder (BP) and major depressive disorder (MDD). However, whether the level of neurocognitive impairment in attentional processing is different between these two disorders, or not, is still unclear. Thus, we investigated the P300 event-related potential component as a biomarker of cognitive dysfunction to differentiate BP and MDD.

METHODS

Twenty-three age and gender matched BP, 20 MDD and 23 healthy controls (HC) were part of a discovery cohort to identify neurophysiological differences between groups and build a classification model of these disorders. The replication of this model was then tested in an independent second cohort of 17 BP, 19 MDD and 19 HC. All participants were symptom-remitted for at least two weeks. We compared neural responses to target stimuli during an auditory oddball task, computing peak amplitude and latency of the P300 component extracted from the midline centro-parietal electrode.

RESULTS

BP had significantly smaller P300 amplitudes compared to both MDD and HC, whereas there were no differences between MDD and HC. The differences between groups were replicated in the second cohort, however the accuracy level of the classification model was only 53.5%.

LIMITATIONS

Small sample sizes may have led to low accuracy levels of the classification model.

CONCLUSION

Specific neural mechanisms of attention and context updating seem not to recover with symptom remission in BP. These findings contribute to the detection of a potential electrophysiological marker for BP, which may allow its differentiation from unipolar major depressive disorder.

Test-retest reliability of the human functional connectome over consecutive days: identifying highly reliable portions and assessing the impact of methodological choices

Countless studies have advanced our understanding of the human brain and its organization by using functional magnetic resonance imaging (fMRI) to derive network representations of human brain function. However, we do not know to what extent these "functional connectomes" are reliable over time. In a large public sample of healthy participants (N = 833) scanned on two consecutive days, we assessed the test-retest reliability of fMRI functional connectivity and the consequences on reliability of three common sources of variation in analysis workflows: atlas choice, global signal regression, and thresholding. By adopting the intraclass correlation coefficient as a metric, we demonstrate that only a small portion of the functional connectome is characterized by good (6-8%) to excellent (0.08-0.14%) reliability. Connectivity between prefrontal, parietal, and temporal areas is especially reliable, but also average connectivity within known networks has good reliability. In general, while unreliable edges are weak, reliable edges are not necessarily strong. Methodologically, reliability of edges varies between atlases, global signal regression decreases reliability for networks and most edges (but increases it for some), and thresholding based on connection strength reduces reliability. Focusing on the reliable portion of the connectome could help quantify brain trait-like features and investigate individual differences using functional neuroimaging.

Intrinsic connectomes underlying response to trauma-focused psychotherapy in post-traumatic stress disorder

Although trauma-focused cognitive behavior therapy (TF-CBT) is the frontline treatment for post-traumatic stress disorder (PTSD), up to one-half of patients are treatment nonresponders. To understand treatment nonresponse, it is important to understand the neural mechanisms of TF-CBT. Here, we used whole-brain intrinsic functional connectivity analysis to identify neural connectomic signatures of treatment outcome. In total, 36 PTSD patients and 36 healthy individuals underwent functional MRI at pre-treatment baseline. Patients then underwent nine sessions of TF-CBT and completed clinical and follow-up MRIs. We used an established large-scale brain network atlas to parcellate the brain into 343 brain regions. Pairwise intrinsic task-free functional connectivity was calculated and used to identify pre-treatment connectomic features that were correlated with reduction of PTSD severity from pretreatment to post treatment. We formed a composite metric of intrinsic connections associated with therapeutic outcome, and then interrogated this composite metric to determine if it distinguished PTSD treatment responders and nonresponders from healthy control status and changed post treatment. Lower pre-treatment connectivity for the cingulo-opercular, salience, default mode, dorsal attention, and frontoparietal executive control brain networks was associated with treatment improvement. Treatment responders had lower while nonresponders had significantly greater connectivity than controls at pretreatment. With therapy, connectivity significantly increased for responders and decreased for nonresponders, while controls remain unchanged over this time period. We provide evidence that the intrinsic functional architecture of the brain, specifically connectivity within and between brain networks associated with external vigilance, self-awareness, and cognitive control, may characterize a positive response to TF-CBT for PTSD.

Perioperative intravenous contrast administration and the incidence of acute kidney injury after major gastrointestinal surgery: prospective, multicentre cohort study

BACKGROUND

This study aimed to determine the impact of preoperative exposure to intravenous contrast for CT and the risk of developing postoperative acute kidney injury (AKI) in patients undergoing major gastrointestinal surgery.

METHODS

This prospective, multicentre cohort study included adults undergoing gastrointestinal resection, stoma reversal or liver resection. Both elective and emergency procedures were included. Preoperative exposure to intravenous contrast was defined as exposure to contrast administered for the purposes of CT up to 7 days before surgery. The primary endpoint was the rate of AKI within 7 days. Propensity score-matched models were adjusted for patient, disease and operative variables. In a sensitivity analysis, a propensity score-matched model explored the association between preoperative exposure to contrast and AKI in the first 48 h after surgery.

RESULTS

A total of 5378 patients were included across 173 centres. Overall, 1249 patients (23·2 per cent) received intravenous contrast. The overall rate of AKI within 7 days of surgery was 13·4 per cent (718 of 5378). In the propensity score-matched model, preoperative exposure to contrast was not associated with AKI within 7 days (odds ratio (OR) 0·95, 95 per cent c.i. 0·73 to 1·21; P = 0·669). The sensitivity analysis showed no association between preoperative contrast administration and AKI within 48 h after operation (OR 1·09, 0·84 to 1·41; P = 0·498).

CONCLUSION

There was no association between preoperative intravenous contrast administered for CT up to 7 days before surgery and postoperative AKI. Risk of contrast-induced nephropathy should not be used as a reason to avoid contrast-enhanced CT.

The human connectome project for disordered emotional states: Protocol and rationale for a research domain criteria study of brain connectivity in young adult anxiety and depression

Through the Human Connectome Project (HCP) our understanding of the functional connectome of the healthy brain has been dramatically accelerated. Given the pressing public health need, we must increase our understanding of how connectome dysfunctions give rise to disordered mental states. Mental disorders arising from high levels of negative emotion or from the loss of positive emotional experience affect over 400 million people globally. Such states of disordered emotion cut across multiple diagnostic categories of mood and anxiety disorders and are compounded by accompanying disruptions in cognitive function. Not surprisingly, these forms of psychopathology are the leading cause of disability worldwide. The Research Domain Criteria (RDoC) initiative spearheaded by NIMH offers a framework for characterizing the relations among connectome dysfunctions, anchored in neural circuits and phenotypic profiles of behavior and self-reported symptoms. Here, we report on our Connectomes Related to Human Disease protocol for integrating an RDoC framework with HCP protocols to characterize connectome dysfunctions in disordered emotional states, and present quality control data from a representative sample of participants. We focus on three RDoC domains and constructs most relevant to depression and anxiety: 1) loss and acute threat within the Negative Valence System (NVS) domain; 2) reward valuation and responsiveness within the Positive Valence System (PVS) domain; and 3) working memory and cognitive control within the Cognitive System (CS) domain. For 29 healthy controls, we present preliminary imaging data: functional magnetic resonance imaging collected in the resting state and in tasks matching our constructs of interest ("Emotion", "Gambling" and "Continuous Performance" tasks), as well as diffusion-weighted imaging. All functional scans demonstrated good signal-to-noise ratio. Established neural networks were robustly identified in the resting state condition by independent component analysis. Processing of negative emotional faces significantly activated the bilateral dorsolateral prefrontal and occipital cortices, fusiform gyrus and amygdalae. Reward elicited a response in the bilateral dorsolateral prefrontal, parietal and occipital cortices, and in the striatum. Working memory was associated with activation in the dorsolateral prefrontal, parietal, motor, temporal and insular cortices, in the striatum and cerebellum. Diffusion tractography showed consistent profiles of fractional anisotropy along known white matter tracts. We also show that results are comparable to those in a matched sample from the HCP Healthy Young Adult data release. These preliminary data provide the foundation for acquisition of 250 subjects who are experiencing disordered emotional states. When complete, these data will be used to develop a neurobiological model that maps connectome dysfunctions to specific behaviors and symptoms.

Electroencephalography profiles as a biomarker of wellbeing: A twin study

Alterations to electroencephalography (EEG) power have been reported for psychiatric conditions such as depression and anxiety, but not for mental wellbeing in a healthy population. This study examined the resting EEG profiles associated with mental wellbeing, and how genetics and environment contribute to these associations using twin modelling. Mental wellbeing was assessed using the COMPAS-W Wellbeing Scale which measures both subjective and psychological wellbeing. In 422 healthy adult monozygotic and dizygotic twins aged 18-61 years, we examined the association between mental wellbeing and EEG power (alpha, beta, theta, delta) using linear mixed models. This was followed by univariate and multivariate twin modelling to assess the heritability of wellbeing and EEG power, and whether the association was driven by shared genetics or environment. A significant association between wellbeing and an interaction of alpha, beta, and delta (ABD) power was found (β = -0.33, p < 0.001) whereby a profile of high alpha and delta and low beta was associated with higher wellbeing, independent of depression and anxiety symptoms. This finding was supported by a five-fold cross-validation analysis. A significant genetic correlation (rG = -0.43) was found to account for 94% of the association between wellbeing and the EEG power interaction. Together, this study has identified a novel EEG profile with a common genetic component that may be a potential biomarker of mental wellbeing. Future studies need to clarify the causal direction of this association.