Cognitive predictors of stress-induced mood malleability in depression.

BACKGROUND & OBJECTIVES: Basic attentional control, negative biases in attention and interpretation, and rumination are all cognitive processes associated with depression; however, less is known about their predictive role in depressive mood reactivity and -recovery in response to stress, and their relation to severity of depression. DESIGN & METHODS: We experimentally induced stress based on an autobiographical imagery script in a sample of 92 participants with Major Depressive Disorder with or without comorbid anxiety disorders. We used simple regression analysis for investigating the roles of state- and trait rumination, attentional networks, and attentional and interpretation biases for predicting stress-induced depressive mood reactivity and -recovery, respectively, and whether they in parallel mediated the association between cognitive processes and depression severity. RESULTS: Stress-induced depressive mood reactivity was predicted by better orienting ability and more state rumination. Better recovery was predicted by better orienting efficiency and lower negative interpretation bias. Furthermore, the relation between state rumination and depression severity was partially mediated by depressive mood reactivity, however limited by the lack of temporal precedence in the analysis. CONCLUSIONS: We characterized the relation between cognitive processes and mood malleability in response to stress. Findings could refine theoretical models of depression if causality is established. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT04137367.

Corrigendum: Acceptance and commitment therapy preceded by attention bias modification on residual symptoms in depression: a 12-month follow-up.

[This corrects the article DOI: 10.3389/fpsyg.2019.01995.].

The long-term effects of ABM on symptom severity in patients with recurrent depression: A randomized sham-controlled trial.

BACKGROUND: The present study reports on long-term outcomes of ABM over one year in self-reported and clinician-rated depression symptoms, anxiety symptoms, and relapse rates. METHODS: We conducted a double-blind randomized sham-controlled trial in 301 participants with recurrent major depression disorder between January 2015 and October 2016 (#NCT02658682). Participants were allocated to ABM or sham condition twice daily for 14 consecutive days. Long-term effects of ABM were assessed by BDI-II, HDRS and BAI at one-, six-, and 12-months follow-up. Relapse rates at 12-months follow-up were also assessed. RESULTS: There was no long-term effect of ABM (as compared to sham) on clinician-rated depression symptoms, on anxiety symptoms, nor in relapse rates. By 12 months follow-up, there was a small effect on self-reported depression favoring ABM over sham. LIMITATIONS: The lack of an assessment-only condition hinders comparison to natural trajectories of depression symptoms. CONCLUSIONS: The overall long-term effect of ABM was limited, and currently there is no convincing evidence for implementing this as a viable treatment option in clinical populations. We speculate if the sham condition should be replaced by another control condition when investigating the clinical utility of ABM.

The effect of attention bias modification on depressive symptoms in a comorbid sample: a randomized controlled trial.

BACKGROUND: Studies investigating the long-term effect of attention bias modification (ABM) in clinical samples are lacking. This study investigates the 6-months follow-up effect of ABM on depressive symptoms in participant with major depressive disorder with and without comorbid disorders. METHODS: We conducted a double-blind randomized sham-controlled trial in 101 participants between 19 November 2019, and 17 August 2021. Follow-up ended 3 April 2022. Participants were allocated to ABM or sham condition twice daily for 14 consecutive days. Primary outcomes were the total score on the Beck Depression Inventory-II (BDI-II) at 6 months, mean Brief State Rumination Inventory (BSRI) score post-treatment and reduction in BSRI post-treatment. Secondary outcome was change in attentional bias (AB). The trial was preregistered in ClinicalTrials.gov (#NCT04137367). RESULTS: A total of 118 patients aged 18-65 years were assessed for eligibility, and 101 were randomized and subjected to intention-to-treat analyses. At 6 months, ABM had no effect on depression and anxiety compared to a sham condition. While rumination decreased during the intervention, there was no effect of condition on rumination and AB. Predictor analysis did not reveal differences between participants with ongoing major depressive episode or comorbid anxiety. CONCLUSION: Compared to sham training, there was no effect of ABM on depressive symptoms at 6-months follow-up. Since the intervention failed at modifying AB, it is unclear whether changes in AB are related to long-term outcomes.

Aberrant default mode connectivity in adolescents with early-onset psychosis: A resting state fMRI study.

Abnormal default mode network (DMN) connectivity has been found in schizophrenia and other psychotic disorders. However, there are limited studies on early onset psychosis (EOP), and their results show lack of agreement. Here, we investigated within-network DMN connectivity in EOP compared to healthy controls (HC), and its relationship to clinical characteristics. A sample of 68 adolescent patients with EOP (mean age 16.53 ± 1.12 [SD] years, females 66%) and 95 HC (mean age 16.24 ± 1.50 [SD], females 60%) from two Scandinavian cohorts underwent resting state functional magnetic resonance imaging (rsfMRI). A group independent component analysis (ICA) was performed to identify the DMN across all participants. Dual regression was used to estimate spatial maps reflecting each participant's DMN network, which were compared between EOP and HC using voxel-wise general linear models and permutation-based analyses. Subgroup analyses were performed within the patient group, to explore associations between diagnostic subcategories and current use of psychotropic medication in relation to connectivity strength. The analysis revealed significantly reduced DMN connectivity in EOP compared to HC in the posterior cingulate cortex, precuneus, fusiform cortex, putamen, pallidum, amygdala, and insula. The subgroup analysis in the EOP group showed strongest deviations for affective psychosis, followed by other psychotic disorders and schizophrenia. There was no association between DMN connectivity strength and the current use of psychotropic medication. In conclusion, the findings demonstrate weaker DMN connectivity in adolescent patients with EOP compared to healthy peers, and differential effects across diagnostic subcategories, which may inform our understanding of underlying disease mechanisms in EOP.

Over-the-counter analgesics use is associated with pain and psychological distress among adolescents: a mixed effects approach in cross-sectional survey data from Norway.

BACKGROUND: Over-the-counter analgesics (OTCA) such as Paracetamol and Ibuprofen are frequently used by adolescents, and the route of administration and access at home allows unsupervised use. Psychological distress and pain occur simultaneously and are more common among females than among males. There is a dynamic interplay between on-label pain indications and psychological distress, and frequent OTCA use or misuse can exacerbate symptoms. No studies have to date provided an overview of frequent OTCA use in a larger population-based study. The current study used survey data to explore associations between and the relative predictive value of on-label pain indication and measures of psychological distress, together with sex differences for weekly OTCA use. METHODS: This study included 349,528 adolescents aged 13-19. The data was collected annually between January 2014 and December 2018 as part of the Norwegian Young Data survey. Performance analysis was conducted to explore the relative roles and associations between on-label pain indication and psychological distress in weekly OTCA use. A mixed-effects logistic regression model was used to explore the unique contributions from four domains of on-label pain indication and psychological distress as measured by a combined measure of anxiety and depression (HSCL-10) and peer-bullying involvement as victims or bullies. RESULTS: Thirty percent of females and 13 % of males use OTCA weekly. Headache is the strongest on-label pain predictor of weekly OTCA use, followed by abdominal pain. Depression and anxiety are the strongest psychological predictor of weekly OTCA use, and higher symptom levels and being female increase the strength of this association. Anxiety and depression also predict weekly OTCA use after controlling for physiological pain. CONCLUSIONS: Sex, pain and anxiety and depression are inter-correlated and strong predictors of frequent OTCA use. Frequent OTCA use in the context of psychological distress may be a form of self-medication that can exacerbate symptoms and decrease psychosocial function. Longitudinal studies that explore causal trajectories between frequent on-label OTCA use and psychological distress are required. OTCA use among adolescents, and particularly among females, with anxiety and depression should be administered with caution and closely monitored.

Symptom severity moderates the outcome of attention bias modification for depression: An exploratory study.

A recent meta-analysis has questioned the relevance of attention bias modification (ABM) for depression outcomes. However, there might be patient characteristics not yet accounted for, that are relevant to the outcome. In the context of personalized treatment, the lack of moderator studies have limited the potential for matching ABM-treatment to individual patient characteristics. Subjects (N = 301) were randomly assigned 1:1 to receive either active or placebo Attention Bias Modification (ABM) twice daily for 14 days in a double-blind design (placebo n = 148; ABM n = 153). The outcome was change in symptoms based on the Hamilton Depression Rating Scale (HDRS). Moderator variables were self-reported depression (Beck Depression Inventory-II; BDI-II), anxiety (Beck Anxiety Inventory; BAI) and attentional bias (AB) assessed at baseline. This trial was registered with ClinicalTrials.gov, number NCT02658682. Only BAI (p for interaction = .01, Bootstrap 95% CI [0.046, 0.337]) moderated the effects of ABM on change in clinician rated depressive symptoms. Interactions were significant for BAI scores ≥8. The relative effect of the intervention increased with the highest symptom load. ABM was not effective in patients with the lowest symptom load. Future research should validate this finding and continue investigating moderators of the ABM-intervention to further enhance personalization of treatment to individual symptom characteristics.

Editorial: The Cognitive Neuropsychological Hypothesis in Pediatric Anxiety and the Advantage of Revealing Early Changes in Brain Mechanisms Associated With Therapeutic Effects.

There is a pressing need to improve treatment, and clinical trials should not only focus on efficacy, but also on identifying the underlying mechanisms through which treatments operate.1 Treatment with a serotonergic antidepressant is commonly used to treat pediatric anxiety disorders, including generalized anxiety disorder (GAD). Serotonergic antidepressants require considerable time to induce clinically observed responses, and tolerability and efficacy are difficult to predict. Risk and precautions have been widely discussed and are weighed against urgent needs for interventions early in life that may prevent recurrent mental health complaints. Drug-induced molecular, cellular, and chemical effects result in neurocognitive changes, which are believed to occur before behavioral changes. Assessments of early neurocognitive changes may therefore be a powerful tool to reveal key mechanisms through which antidepressants work. When the neurofunctional mechanisms believed to cause the symptoms are restored, the clinical manifestation of symptom improvement is expected. The degree of symptom improvement should also follow the degree of positive changes in neurocognitive function. Many patients do not respond early enough in the course of symptom evolution,2,3 and thus assessments of early neurocognitive mechanisms may guide treatment individualization during titration of doses and effects.

The genetic architecture of human brainstem structures and their involvement in common brain disorders.

Brainstem regions support vital bodily functions, yet their genetic architectures and involvement in common brain disorders remain understudied. Here, using imaging-genetics data from a discovery sample of 27,034 individuals, we identify 45 brainstem-associated genetic loci, including the first linked to midbrain, pons, and medulla oblongata volumes, and map them to 305 genes. In a replication sample of 7432 participants most of the loci show the same effect direction and are significant at a nominal threshold. We detect genetic overlap between brainstem volumes and eight psychiatric and neurological disorders. In additional clinical data from 5062 individuals with common brain disorders and 11,257 healthy controls, we observe differential volume alterations in schizophrenia, bipolar disorder, multiple sclerosis, mild cognitive impairment, dementia, and Parkinson's disease, supporting the relevance of brainstem regions and their genetic architectures in common brain disorders.

ENIGMA MDD: seven years of global neuroimaging studies of major depression through worldwide data sharing.

A key objective in the field of translational psychiatry over the past few decades has been to identify the brain correlates of major depressive disorder (MDD). Identifying measurable indicators of brain processes associated with MDD could facilitate the detection of individuals at risk, and the development of novel treatments, the monitoring of treatment effects, and predicting who might benefit most from treatments that target specific brain mechanisms. However, despite intensive neuroimaging research towards this effort, underpowered studies and a lack of reproducible findings have hindered progress. Here, we discuss the work of the ENIGMA Major Depressive Disorder (MDD) Consortium, which was established to address issues of poor replication, unreliable results, and overestimation of effect sizes in previous studies. The ENIGMA MDD Consortium currently includes data from 45 MDD study cohorts from 14 countries across six continents. The primary aim of ENIGMA MDD is to identify structural and functional brain alterations associated with MDD that can be reliably detected and replicated across cohorts worldwide. A secondary goal is to investigate how demographic, genetic, clinical, psychological, and environmental factors affect these associations. In this review, we summarize findings of the ENIGMA MDD disease working group to date and discuss future directions. We also highlight the challenges and benefits of large-scale data sharing for mental health research.

Multimodal fusion of structural and functional brain imaging in depression using linked independent component analysis.

Previous structural and functional neuroimaging studies have implicated distributed brain regions and networks in depression. However, there are no robust imaging biomarkers that are specific to depression, which may be due to clinical heterogeneity and neurobiological complexity. A dimensional approach and fusion of imaging modalities may yield a more coherent view of the neuronal correlates of depression. We used linked independent component analysis to fuse cortical macrostructure (thickness, area, gray matter density), white matter diffusion properties and resting-state functional magnetic resonance imaging default mode network amplitude in patients with a history of depression (n = 170) and controls (n = 71). We used univariate and machine learning approaches to assess the relationship between age, sex, case-control status, and symptom loads for depression and anxiety with the resulting brain components. Univariate analyses revealed strong associations between age and sex with mainly global but also regional specific brain components, with varying degrees of multimodal involvement. In contrast, there were no significant associations with case-control status, nor symptom loads for depression and anxiety with the brain components, nor any interaction effects with age and sex. Machine learning revealed low model performance for classifying patients from controls and predicting symptom loads for depression and anxiety, but high age prediction accuracy. Multimodal fusion of brain imaging data alone may not be sufficient for dissecting the clinical and neurobiological heterogeneity of depression. Precise clinical stratification and methods for brain phenotyping at the individual level based on large training samples may be needed to parse the neuroanatomy of depression.

Attentional bias modification is associated with fMRI response toward negative stimuli in individuals with residual depression: a randomized controlled trial

Background: Attentional bias modification (ABM) may lead to more adaptive emotion perception and emotion regulation. Understanding the neural basis of these effects may lead to greater precision for the development of future treatments. Task-related functional MRI (fMRI) after ABM training has not been investigated in depression so far. The main aim of this randomized controlled trial was to explore differences in brain activity after ABM training, in response to emotional stimuli. Methods: A total of 134 people with previous depression, who had been treated for depression and had various degrees of residual symptoms, were randomized to 14 days of active ABM or a closely matched placebo training, followed by an fMRI emotion regulation task. The training procedure was a classical dot­probe task with emotional face stimuli. In the active ABM condition, the probes replaced the more positively valenced face of a given pair. As participants implicitly learned to predict the probe location, this would be likely to induce a more positive attentional bias. The placebo condition was identical, except for the contingency of the probe, which appeared equally behind positive and negative stimuli. We compared depression symptoms and subjective ratings of perceived negativity during fMRI between the training groups. We explored brain activation in predefined regions of interest and across the whole brain. We explored activation in areas associated with changes in attentional bias and degree of depression. Results: Compared with the placebo group, the ABM group showed reduced activation in the amygdala and the anterior cingulate cortex when passively viewing negative images. We found no group differences in predefined regions of interest associated with emotion regulation strategies. Response in the temporal cortices was associated with the degree of change in attentional bias and the degree of depressive symptoms in ABM versus placebo. Limitations: These findings should be replicated in other samples of patients with depression, and in studies using fMRI designs that allow analyses of within-group variability from baseline to follow-up. Conclusion: Attentional bias modification training has an effect on brain function in the circuitry associated with emotional appraisal and the generation of affective states. Clinicaltrials.gov identifier: NCT02931487

Publisher Correction: Common brain disorders are associated with heritable patterns of apparent aging of the brain.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Brain Connectome Mapping of Complex Human Traits and Their Polygenic Architecture Using Machine Learning.

BACKGROUND: Mental disorders and individual characteristics such as intelligence and personality are complex traits sharing a largely unknown neuronal basis. Their genetic architectures are highly polygenic and overlapping, which is supported by heterogeneous phenotypic expression and substantial clinical overlap. Brain network analysis provides a noninvasive means of dissecting biological heterogeneity, yet its sensitivity, specificity, and validity in assessing individual characteristics relevant for brain function and mental health and their genetic underpinnings in clinical applications remain a challenge. METHODS: In a machine learning approach, we predicted individual scores for educational attainment, fluid intelligence and dimensional measures of depression, anxiety, and neuroticism using functional magnetic resonance imaging-based static and dynamic temporal synchronization between large-scale brain network nodes in 10,343 healthy individuals from the UK Biobank. In addition to using age and sex to serve as our reference point, we also predicted individual polygenic scores for related phenotypes and 13 different neuroticism traits and schizophrenia. RESULTS: Beyond high accuracy for age and sex, supporting the biological sensitivity of the connectome-based features, permutation tests revealed above chance-level prediction accuracy for trait-level educational attainment and fluid intelligence. Educational attainment and fluid intelligence were mainly negatively associated with static brain connectivity in frontal and default mode networks, whereas age showed positive correlations with a more widespread pattern. In contrast, prediction accuracy was at chance level for depression, anxiety, neuroticism, and polygenic scores across traits. CONCLUSIONS: These novel findings provide a benchmark for future studies linking the genetic architecture of individual and mental health traits with functional magnetic resonance imaging-based brain connectomics.

Common brain disorders are associated with heritable patterns of apparent aging of the brain.

Common risk factors for psychiatric and other brain disorders are likely to converge on biological pathways influencing the development and maintenance of brain structure and function across life. Using structural MRI data from 45,615 individuals aged 3-96 years, we demonstrate distinct patterns of apparent brain aging in several brain disorders and reveal genetic pleiotropy between apparent brain aging in healthy individuals and common brain disorders.

Acceptance and Commitment Therapy Preceded by Attention Bias Modification on Residual Symptoms in Depression: A 12-Month Follow-Up.

Depression is a highly recurrent disorder with limited treatment alternatives for reducing risk of subsequent episodes. Acceptance and commitment therapy (ACT) and attention bias modification (ABM) separately have shown some promise in reducing depressive symptoms. This study investigates (a) if group-based ACT had a greater impact in reducing residual symptoms of depression over a 12-month follow-up than a control condition, and (b) if preceding ACT with ABM produced added benefits. This multisite study consisted of two phases. In phase 1, participants with a history of depression, currently in remission (N = 244), were randomized to either receive 14 days of ABM or a control condition. In phase 2, a quasi- experimental design was adopted, and only phase-1 participants from the Sørlandet site (N = 124) next received an 8-week group-based ACT intervention. Self-reported and clinician-rated depression symptoms were assessed at baseline, immediately after phase 1 and at 1, 2, 6, and 12 months after the conclusion of phase 1. At 12-month follow-up, participants who received ACT exhibited fewer self-reported and clinician-rated depressive symptoms. There were no significant differences between ACT groups preceded by ABM or a control condition. There were no significant differences between ACT groups preceded by ABM or a control condition. Group-based ACT successfully decreased residual symptoms in depression over 12 months, suggesting some promise in preventing relapse.

Effects of Attentional Bias Modification on residual symptoms in depression: a randomized controlled trial.

BACKGROUND: Following treatment, many depressed patients have significant residual symptoms. However, large randomised controlled trials (RCT) in this population are lacking. When Attention bias modification training (ABM) leads to more positive emotional biases, associated changes in clinical symptoms have been reported. A broader and more transparent picture of the true advantage of ABM based on larger and more stringent clinical trials have been requested. The current study evaluates the early effect of two weeks ABM training on blinded clinician-rated and self-reported residual symptoms, and whether changes towards more positive attentional biases (AB) would be associated with symptom reduction. METHOD: A total of 321 patients with a history of depression were included in a preregistered randomized controlled double-blinded trial. Patients were randomised to an emotional ABM paradigm over fourteen days or a closely matched control condition. Symptoms based on the Hamilton Rating Scale for Depression (HRSD) and Beck Depression Inventory II (BDI-II) were obtained at baseline and after ABM training. RESULTS: ABM training led to significantly greater decrease in clinician-rated symptoms of depression as compared to the control condition. No differences between ABM and placebo were found for self-reported symptoms. ABM induced a change of AB towards relatively more positive stimuli for participants that also showed greater symptom reduction. CONCLUSION: The current study demonstrates that ABM produces early changes in blinded clinician-rated depressive symptoms and that changes in AB is linked to changes in symptoms. ABM may have practical potential in the treatment of residual depression. TRIAL REGISTRATION: ClinicalTrials.gov ID: NCT02658682 (retrospectively registered in January 2016).

Data-Driven Clustering Reveals a Link Between Symptoms and Functional Brain Connectivity in Depression.

BACKGROUND: Depression is a complex disorder with large interindividual variability in symptom profiles that often occur alongside symptoms of other psychiatric domains, such as anxiety. A dimensional and symptom-based approach may help refine the characterization of depressive and anxiety disorders and thus aid in establishing robust biomarkers. We use resting-state functional magnetic resonance imaging to assess the brain functional connectivity correlates of a symptom-based clustering of individuals. METHODS: We assessed symptoms using the Beck Depression and Beck Anxiety Inventories in individuals with or without a history of depression (N = 1084) and high-dimensional data clustering to form subgroups based on symptom profiles. We compared dynamic and static functional connectivity between subgroups in a subset of the total sample (n = 252). RESULTS: We identified five subgroups with distinct symptom profiles, which cut across diagnostic boundaries with different total severity, symptom patterns, and centrality. For instance, inability to relax, fear of the worst, and feelings of guilt were among the most severe symptoms in subgroups 1, 2, and 3, respectively. The distribution of individuals was 32%, 25%, 22%, 10%, and 11% in subgroups 1 to 5, respectively. These subgroups showed evidence of differential static brain-connectivity patterns, in particular comprising a frontotemporal network. In contrast, we found no significant associations with clinical sum scores, dynamic functional connectivity, or global connectivity. CONCLUSIONS: Adding to the pursuit of individual-based treatment, subtyping based on a dimensional conceptualization and unique constellations of anxiety and depression symptoms is supported by distinct patterns of static functional connectivity in the brain.

Acceptance and Commitment Therapy preceded by an experimental Attention Bias Modification procedure in recurrent depression: study protocol for a randomized controlled trial.

BACKGROUND: This project studies the effect of group-based Acceptance and Commitment Therapy (ACT) following Attention Bias Modification (ABM) on residual symptoms in recurrent depression. ACT is a cognitive-behavioral intervention combining acceptance and mindfulness processes with commitment and behavior-change processes. ACT enjoys modest empirical support in treating depression and has also shown promising results in secondary prevention of depression. The experimental cognitive bias modification (ABM) procedure has been shown to reduce surrogate markers of depression vulnerability in patients in remission from depression. The aim of the current project is to investigate if the effect of group-based ACT on reducing residual depressive symptoms can be enhanced by preceding it with ABM. Also, assessment of the relationship between conceptually relevant therapeutic processes and outcome will be investigated. METHODS/DESIGN: An invitation to participate in this project was extended to 120 individuals within a larger sample who had just completed a separate randomized, multisite, clinical trial (referred to hereafter as Phase 1) in which they received either ABM (n = 60) or a control condition without bias modification (n = 60). This larger Phase-1 sample consisted of 220 persons with a history of at least two episodes of major depression who were currently in remission or not fulfilling the criteria of major depression. After its inclusion, Phase-1 participants from the Sørlandet site (n = 120) were also recruited for this study in which they received an 8-week group-based ACT intervention. Measures will be taken immediately after Phase 1, 1 month, 2 months, 6 months, and 1 year after the conclusion of Phase 1. DISCUSSION: This study sequentially combines acceptable, nondrug interventions from neuropsychology and cognitive-behavioral psychology in treating residual symptoms in depression. The results will provide information about the effectiveness of treatment and on mechanisms and processes of change that may be valuable in understanding and further developing ABM and ACT, combined and alone. TRIAL REGISTRATION: ClinicalTrials.gov, Identifier: NCT02648165 . Registered on 6 January 2016.