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.

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

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).

Brain volumes and regional cortical thickness in young females with anorexia nervosa.

BACKGROUND: Anorexia nervosa (AN) is a severe mental illness, with an unknown etiology. Magnetic resonance imaging studies show reduced brain volumes and cortical thickness in patients compared to healthy controls. However, findings are inconsistent, especially concerning the anatomical location and extent of the differences. The purpose of this study was to estimate and compare brain volumes and regional cortical thickness in young females with AN and healthy controls. METHODS: Magnetic resonance imaging data was acquired from young females with anorexia nervosa (n = 23) and healthy controls (n = 28). Two different scanner sites were used. BMI varied from 13.5 to 20.7 within the patient group, and 11 patients had a BMI > 17.5. FreeSurfer was used to estimate brain volumes and regional cortical thickness. RESULTS: There were no differences between groups in total cerebral cortex volume, white matter volume, or lateral ventricle volume. There were also no volume differences in subcortical grey matter structures. However the results showed reduced cortical thickness bilaterally in the superior parietal gyrus, and in the right inferior parietal and superior frontal gyri. CONCLUSIONS: The functional significance of the findings is undetermined as the majority of the included patients was already partially weight-restored. We discuss whether these regions could be related to predisposing factors of the illness, or whether they are regions that are more vulnerable to starvation, malnutrition or associated processes in AN.

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.

In Vivo Amygdala Nuclei Volumes in Schizophrenia and Bipolar Disorders.

Abnormalities in amygdala volume are well-established in schizophrenia and commonly reported in bipolar disorders. However, the specificity of volumetric differences in individual amygdala nuclei is largely unknown. Patients with schizophrenia disorders (SCZ, N = 452, mean age 30.7 ± 9.2 [SD] years, females 44.4%), bipolar disorders (BP, N = 316, 33.7 ± 11.4, 58.5%), and healthy controls (N = 753, 34.1 ± 9.1, 40.9%) underwent T1-weighted magnetic resonance imaging. Total amygdala, nuclei, and intracranial volume (ICV) were estimated with Freesurfer (v6.0.0). Analysis of covariance and multiple linear regression models, adjusting for age, age2, ICV, and sex, were fitted to examine diagnostic group and subgroup differences in volume, respectively. Bilateral total amygdala and all nuclei volumes, except the medial and central nuclei, were significantly smaller in patients relative to controls. The largest effect sizes were found for the basal nucleus, accessory basal nucleus, and cortico-amygdaloid transition area (partial η2 > 0.02). The diagnostic subgroup analysis showed that reductions in amygdala nuclei volume were most widespread in schizophrenia, with the lateral, cortical, paralaminar, and central nuclei being solely reduced in this disorder. The right accessory basal nucleus was marginally smaller in SCZ relative to BP (t = 2.32, P = .05). Our study is the first to demonstrate distinct patterns of amygdala nuclei volume reductions in a well-powered sample of patients with schizophrenia and bipolar disorders. Volume differences in the basolateral complex (lateral, basal, and accessory basal nuclei), an integral part of the threat processing circuitry, were most prominent in schizophrenia.

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.

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.

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.

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.

Within-Network Connectivity in the Salience Network After Attention Bias Modification Training in Residual Depression: Report From a Preregistered Clinical Trial.

Alterations in resting state networks (RSNs) are associated with emotional- and attentional control difficulties in depressed individuals. Attentional bias modification (ABM) training may lead to more adaptive emotional processing in depression, but little is known about the neural underpinnings associated with ABM. In the current study a sample of 134 previously depressed individuals were randomized into 14 days of computerized ABM- or a closely matched placebo training regime followed by a resting state magnetic resonance imaging (MRI) scan. Using independent component analysis (ICA) we examined within-network connectivity in three major RSN's, the default mode network (DMN), the salience network (SN) and the central executive network (CEN) after 2 weeks of ABM training. We found a significant difference between the training groups within the SN, but no difference within the DMN or CEN. Moreover, a significant symptom improvement was observed in the ABM group after training. Clinical Trial Registration: www.ClinicalTrials.gov, identifier NCT02931487.

Right temporal cortical hypertrophy in resilience to trauma: an MRI study.

BACKGROUND: In studies employing physiological measures such as magnetic resonance imaging (MRI), it is often hard to distinguish what constitutes risk-resilience factors to posttraumatic stress disorder (PTSD) following trauma exposure and what the effects of trauma exposure and PTSD are. OBJECTIVE: We aimed to investigate whether there were observable morphological differences in cortical and sub-cortical regions of the brain, 7-8 years after a single potentially traumatic event. METHODS: Twenty-four participants, who all directly experienced the 2004 Indian Ocean Tsunami, and 25 controls, underwent structural MRI using a 3T scanner. We generated cortical thickness maps and parcellated sub-cortical volumes for analysis. RESULTS: We observed greater cortical thickness for the trauma-exposed participants relative to controls, in a right lateralized temporal lobe region including anterior fusiform gyrus, and superior, middle, and inferior temporal gyrus. CONCLUSIONS: We observed greater thickness in the right temporal lobe which might indicate that the region could be implicated in resilience to the long-term effects of a traumatic event. We hypothesize this is due to altered emotional semantic memory processing. However, several methodological and confounding issues warrant caution in interpretation of the results.

Patients with focal cerebellar lesions show reduced auditory cortex activation during silent reading.

Functional neuroimaging studies consistently report language-related cerebellar activations, but evidence from the clinical literature is less conclusive. Here, we attempt to bridge this gap by testing the effect of focal cerebellar lesions on cerebral activations in a reading task previously shown to involve distinct cerebellar regions. Patients (N=10) had lesions primarily affecting medial cerebellum, overlapping cerebellar regions activated during the presentation of random word sequences, but distinct from activations related to semantic prediction generation and prediction error processing. In line with this pattern of activation-lesion overlap, patients did not differ from matched healthy controls (N=10) in predictability-related activations. However, whereas controls showed increased activation in bilateral auditory cortex and parietal operculum when silently reading familiar words relative to viewing letter strings, this effect was absent in the patients. Our results highlight the need for careful lesion mapping and suggest possible roles for the cerebellum in visual-to-auditory mapping and/or inner speech.