Persistence of amygdala hyperactivity to subliminal negative emotion processing in the long-term course of depression.

Biased emotion processing has been suggested to underlie the etiology and maintenance of depression. Neuroimaging studies have shown mood-congruent alterations in amygdala activity in patients with acute depression, even during early, automatic stages of emotion processing. However, due to a lack of prospective studies over periods longer than 8 weeks, it is unclear whether these neurofunctional abnormalities represent a persistent correlate of depression even in remission. In this prospective case-control study, we aimed to examine brain functional correlates of automatic emotion processing in the long-term course of depression. In a naturalistic design, n = 57 patients with acute major depressive disorder (MDD) and n = 37 healthy controls (HC) were assessed with functional magnetic resonance imaging (fMRI) at baseline and after 2 years. Patients were divided into two subgroups according to their course of illness during the study period (n = 37 relapse, n = 20 no-relapse). During fMRI, participants underwent an affective priming task that assessed emotion processing of subliminally presented sad and happy compared to neutral face stimuli. A group × time × condition (3 × 2 × 2) ANOVA was performed for the amygdala as region-of-interest (ROI). At baseline, there was a significant group × condition interaction, resulting from amygdala hyperactivity to sad primes in patients with MDD compared to HC, whereas no difference between groups emerged for happy primes. In both patient subgroups, amygdala hyperactivity to sad primes persisted after 2 years, regardless of relapse or remission at follow-up. The results suggest that amygdala hyperactivity during automatic processing of negative stimuli persists during remission and represents a trait rather than a state marker of depression. Enduring neurofunctional abnormalities may reflect a consequence of or a vulnerability to depression.

Long-term effects of electroconvulsive therapy on brain structure in major depression.

BACKGROUND: Magnetic resonance imaging (MRI) studies on major depressive disorder (MDD) have predominantly found short-term electroconvulsive therapy (ECT)-related gray matter volume (GMV) increases, but research on the long-term stability of such changes is missing. Our aim was to investigate long-term GMV changes over a 2-year period after ECT administration and their associations with clinical outcome. METHODS: In this nonrandomized longitudinal study, patients with MDD undergoing ECT (n = 17) are assessed three times by structural MRI: Before ECT (t0), after ECT (t1) and 2 years later (t2). A healthy (n = 21) and MDD non-ECT (n = 33) control group are also measured three times within an equivalent time interval. A 3(group) × 3(time) ANOVA on whole-brain level and correlation analyses with clinical outcome variables is performed. RESULTS: Analyses yield a significant group × time interaction (pFWE < 0.001) resulting from significant volume increases from t0 to t1 and decreases from t1 to t2 in the ECT group, e.g., in limbic areas. There are no effects of time in both control groups. Volume increases from t0 to t1 correlate with immediate and delayed symptom increase, while volume decreases from t1 to t2 correlate with long-term depressive outcome (all p ⩽ 0.049). CONCLUSIONS: Volume increases induced by ECT appear to be a transient phenomenon as volume strongly decreased 2 years after ECT. Short-term volume increases are associated with less symptom improvement suggesting that the antidepressant effect of ECT is not due to volume changes. Larger volume decreases are associated with poorer long-term outcome highlighting the interplay between disease progression and structural changes.

Shared and distinct structural brain networks related to childhood maltreatment and social support: connectome-based predictive modeling.

Childhood maltreatment (CM) has been associated with changes in structural brain connectivity even in the absence of mental illness. Social support, an important protective factor in the presence of childhood maltreatment, has been positively linked to white matter integrity. However, the shared effects of current social support and CM and their association with structural connectivity remain to be investigated. They might shed new light on the neurobiological basis of the protective mechanism of social support. Using connectome-based predictive modeling (CPM), we analyzed structural connectomes of N = 904 healthy adults derived from diffusion-weighted imaging. CPM predicts phenotypes from structural connectivity through a cross-validation scheme. Distinct and shared networks of white matter tracts predicting childhood trauma questionnaire scores and the social support questionnaire were identified. Additional analyses were applied to assess the stability of the results. CM and social support were predicted significantly from structural connectome data (all rs ≥ 0.119, all ps ≤ 0.016). Edges predicting CM and social support were inversely correlated, i.e., positively correlated with CM and negatively with social support, and vice versa, with a focus on frontal and temporal regions including the insula and superior temporal lobe. CPM reveals the predictive value of the structural connectome for CM and current social support. Both constructs are inversely associated with connectivity strength in several brain tracts. While this underlines the interconnectedness of these experiences, it suggests social support acts as a protective factor following adverse childhood experiences, compensating for brain network alterations. Future longitudinal studies should focus on putative moderating mechanisms buffering these adverse experiences.

Towards a network control theory of electroconvulsive therapy response.

Electroconvulsive Therapy (ECT) is arguably the most effective intervention for treatment-resistant depression. While large interindividual variability exists, a theory capable of explaining individual response to ECT remains elusive. To address this, we posit a quantitative, mechanistic framework of ECT response based on Network Control Theory (NCT). Then, we empirically test our approach and employ it to predict ECT treatment response. To this end, we derive a formal association between Postictal Suppression Index (PSI)-an ECT seizure quality index-and whole-brain modal and average controllability, NCT metrics based on white-matter brain network architecture, respectively. Exploiting the known association of ECT response and PSI, we then hypothesized an association between our controllability metrics and ECT response mediated by PSI. We formally tested this conjecture in N = 50 depressive patients undergoing ECT. We show that whole-brain controllability metrics based on pre-ECT structural connectome data predict ECT response in accordance with our hypotheses. In addition, we show the expected mediation effects via PSI. Importantly, our theoretically motivated metrics are at least on par with extensive machine learning models based on pre-ECT connectome data. In summary, we derived and tested a control-theoretic framework capable of predicting ECT response based on individual brain network architecture. It makes testable, quantitative predictions regarding individual therapeutic response, which are corroborated by strong empirical evidence. Our work might constitute a starting point for a comprehensive, quantitative theory of personalized ECT interventions rooted in control theory.

Cognitive performance and brain structural connectome alterations in major depressive disorder.

BACKGROUND: Cognitive dysfunction and brain structural connectivity alterations have been observed in major depressive disorder (MDD). However, little is known about their interrelation. The present study follows a network approach to evaluate alterations in cognition-related brain structural networks. METHODS: Cognitive performance of n = 805 healthy and n = 679 acutely depressed or remitted individuals was assessed using 14 cognitive tests aggregated into cognitive factors. The structural connectome was reconstructed from structural and diffusion-weighted magnetic resonance imaging. Associations between global connectivity strength and cognitive factors were established using linear regressions. Network-based statistics were applied to identify subnetworks of connections underlying these global-level associations. In exploratory analyses, effects of depression were assessed by evaluating remission status-related group differences in subnetwork-specific connectivity. Partial correlations were employed to directly test the complete triad of cognitive factors, depressive symptom severity, and subnetwork-specific connectivity strength. RESULTS: All cognitive factors were associated with global connectivity strength. For each cognitive factor, network-based statistics identified a subnetwork of connections, revealing, for example, a subnetwork positively associated with processing speed. Within that subnetwork, acutely depressed patients showed significantly reduced connectivity strength compared to healthy controls. Moreover, connectivity strength in that subnetwork was associated to current depressive symptom severity independent of the previous disease course. CONCLUSIONS: Our study is the first to identify cognition-related structural brain networks in MDD patients, thereby revealing associations between cognitive deficits, depressive symptoms, and reduced structural connectivity. This supports the hypothesis that structural connectome alterations may mediate the association of cognitive deficits and depression severity.

Mega-analysis of association between obesity and cortical morphology in bipolar disorders: ENIGMA study in 2832 participants.

BACKGROUND: Obesity is highly prevalent and disabling, especially in individuals with severe mental illness including bipolar disorders (BD). The brain is a target organ for both obesity and BD. Yet, we do not understand how cortical brain alterations in BD and obesity interact. METHODS: We obtained body mass index (BMI) and MRI-derived regional cortical thickness, surface area from 1231 BD and 1601 control individuals from 13 countries within the ENIGMA-BD Working Group. We jointly modeled the statistical effects of BD and BMI on brain structure using mixed effects and tested for interaction and mediation. We also investigated the impact of medications on the BMI-related associations. RESULTS: BMI and BD additively impacted the structure of many of the same brain regions. Both BMI and BD were negatively associated with cortical thickness, but not surface area. In most regions the number of jointly used psychiatric medication classes remained associated with lower cortical thickness when controlling for BMI. In a single region, fusiform gyrus, about a third of the negative association between number of jointly used psychiatric medications and cortical thickness was mediated by association between the number of medications and higher BMI. CONCLUSIONS: We confirmed consistent associations between higher BMI and lower cortical thickness, but not surface area, across the cerebral mantle, in regions which were also associated with BD. Higher BMI in people with BD indicated more pronounced brain alterations. BMI is important for understanding the neuroanatomical changes in BD and the effects of psychiatric medications on the brain.

Treatment with the second-generation antipsychotic quetiapine is associated with increased subgenual ACC activation during reward processing in major depressive disorder.

BACKGROUND: The second-generation antipsychotic (SGA) quetiapine is an essential option for antidepressant augmentation therapy in major depressive disorder (MDD), yet neurobiological mechanisms behind its antidepressant properties remain unclear. As SGAs interfere with activity in reward-related brain areas, including the anterior cingulate cortex (ACC) - a key brain region in antidepressant interventions, this study examined whether quetiapine treatment affects ACC activity during reward processing in MDD patients. METHODS: Using the ACC as region of interest, an independent t-test comparing reward-related BOLD response of 51 quetiapine-taking and 51 antipsychotic-free MDD patients was conducted. Monetary reward outcome feedback was measured in a card-guessing paradigm using pseudorandom blocks. Participants were matched for age, sex, and depression severity and analyses were controlled for confounding variables, including total antidepressant medication load, illness chronicity and acute depression severity. Potential dosage effects were examined in a 3 × 1 ANOVA. Differences in ACC-related functional connectivity were assessed in psycho-physiological interaction (PPI) analyses. RESULTS: Left subgenual ACC activity was significantly higher in the quetiapine group compared to antipsychotic-free participants and dependent on high-dose quetiapine intake. Results remained significant after controlling for confounding variables. The PPI analysis did not yield significant group differences in ACC-related functional connectivity. LIMITATIONS: Causal interpretation is limited due to cross-sectional findings. CONCLUSION: Elevated subgenual ACC activity to rewarding stimuli may represent a neurobiological marker and potential key interface of quetiapine's antidepressant effects in MDD. These results underline ACC activity during reward processing as an investigative avenue for future research and therapeutic interventions to improve MDD treatment outcomes.

Shared and Specific Patterns of Structural Brain Connectivity Across Affective and Psychotic Disorders.

BACKGROUND: Altered brain structural connectivity has been implicated in the pathophysiology of psychiatric disorders including schizophrenia (SZ), bipolar disorder (BD), and major depressive disorder (MDD). However, it is unknown which part of these connectivity abnormalities are disorder specific and which are shared across the spectrum of psychotic and affective disorders. We investigated common and distinct brain connectivity alterations in a large sample (N = 1743) of patients with SZ, BD, or MDD and healthy control (HC) subjects. METHODS: This study examined diffusion-weighted imaging-based structural connectome topology in 720 patients with MDD, 112 patients with BD, 69 patients with SZ, and 842 HC subjects (mean age of all subjects: 35.7 years). Graph theory-based network analysis was used to investigate connectome organization. Machine learning algorithms were trained to classify groups based on their structural connectivity matrices. RESULTS: Groups differed significantly in the network metrics global efficiency, clustering, present edges, and global connectivity strength with a converging pattern of alterations between diagnoses (e.g., efficiency: HC > MDD > BD > SZ, false discovery rate-corrected p = .028). Subnetwork analysis revealed a common core of edges that were affected across all 3 disorders, but also revealed differences between disorders. Machine learning algorithms could not discriminate between disorders but could discriminate each diagnosis from HC. Furthermore, dysconnectivity patterns were found most pronounced in patients with an early disease onset irrespective of diagnosis. CONCLUSIONS: We found shared and specific signatures of structural white matter dysconnectivity in SZ, BD, and MDD, leading to commonly reduced network efficiency. These results showed a compromised brain communication across a spectrum of major psychiatric disorders.

Temporal stability and state-dependence of retrospective self-reports of childhood maltreatment in healthy and depressed adults.

Retrospective self-reports of childhood maltreatment (CM) are widely used. However, their validity has been questioned due to potential depressive bias. Yet, investigations of this matter are sparse. Thus, we investigated to what extent retrospective maltreatment reports vary in relation to longitudinal changes in depressive symptomatology. Two-year temporal stability of maltreatment reports was assessed via the Childhood Trauma Questionnaire (CTQ). Diagnosis of major depressive disorder (MDD) and depressive symptoms were assessed using the Structured Clinical Interview for DSM-IV and the Beck Depression Inventory (BDI). We included a total of n = 419 healthy controls (HC), n = 347 MDD patients, and a subsample with an initial depressive episode between both assessments (n = 27), from two independent cohorts (Marburg-Münster-affective-disorders-cohort-study and Münster-Neuroimaging-cohort). Analysis plan and hypotheses were preregistered prior to data analysis. Dimensional CTQ scores were highly stable in HC and MDD across both cohorts (ICC = .956; 95% CI [.949, .963] and ICC = .950; 95% CI [.933, .963]) and temporal stability did not differ between groups. Stability was lower for cutoff-based binary CTQ scores (K = .551; 95% CI [.479, .622] and K = .507; 95% CI [.371, .640]). Baseline dimensional CTQ scores were associated with concurrent and future BDI scores. However, longitudinal changes in BDI scores predicted variability in dimensional CTQ scores only to a small extent across cohorts (b = 0.101, p = .009, R² = .021 and b = 0.292, p = .320), with the effect being driven by emotional maltreatment subscales. Findings suggest that the CTQ provides temporally stable self-reports of CM in healthy and depressed populations and is only marginally biased by depressive symptomatology. A dimensional rather than binary conceptualization of maltreatment is advised for improving psychometric quality. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Emotion processing in depression with and without comorbid anxiety disorder.

BACKGROUND: Among mental disorders, major depressive disorder (MDD) is highly prevalent and associated with emotional dysfunctions linked to activity alterations in the brain, mainly in prefrontal regions, the insula, the anterior cingulate cortex and the amygdala. However, this evidence is heterogeneous, perhaps because magnetic resonance imaging (MRI) studies on MDD tend to neglect comorbid anxiety (COM-A). METHODS: To address this, here a sample of age- and sex-matched patients, nMDD = 90 and nCOM-A = 85, underwent functional MRI to assess neurofunctional group differences during a negative emotional face-matching task using a hypothesis-driven region of interest approach (dorsolateral prefrontal cortex, insula, anterior cingulate cortex, amygdala) and an explorative whole-brain approach. We also assessed these relationships with state-trait anxiety measures, a state depression measure, general functioning and medication load. RESULTS: During face processing, COM-A (compared to MDD) had significantly increased bilateral insula activity. No activity differences were found in the anterior cingulate cortex or the amygdala. Whole-brain analyses revealed increased inferior temporal activation and frontal activation (comprising the inferior and middle frontal gyrus) in COM-A that was positively linked to state anxiety as well as general functioning across groups. LIMITATIONS: Still, the lack of a healthy control and small effects mean this study should be replicated to further interpret the results. CONCLUSIONS: The findings highlight a discriminative activation pattern between MDD and COM-A regarding emotion processing and may present a correlate of potentially anxiety-related psychopathology. In future, further investigations in potential discriminative activity patterns could help to elucidate the origin, development and treatment of depression.

Brain functional correlates of emotional face processing in body dysmorphic disorder.

Previous neuroimaging studies in body dysmorphic disorder (BDD) have focused on discordances in visual processing systems. However, little is known about brain functional aberrations in individuals with BDD during emotional face processing. An fMRI paradigm with negative emotional faces was employed in 20 individuals with BDD and 43 mentally healthy controls (HC). We compared functional activity and whole-brain connectivity patterns of the amygdala and the fusiform gyrus (FFG) between both groups. Regression analyses were performed for associations of body dysmorphic symptoms with brain activity and connectivity. Individuals with BDD exhibited higher activity in the left amygdala compared to HC (pFWE = .04) as well as increased functional connectivity of the left amygdala with a network including frontostriatal and temporal regions (pFWE < .05). The FFG revealed increased functional connectivity in individuals with BDD, mapping to brain areas such as the cingulate cortex and temporo-limbic regions (pFWE < .05). In HC, higher levels of body dysmorphic symptoms were associated with higher functional amygdala and FFG activity (pFWE < .05). Individuals with BDD show aberrant functional activity and connectivity patterns within the amygdala and the FFG for negative emotional face processing. Body dysmorphic symptoms in HC are associated with a mild pattern of brain functional alterations, which could emphasize the relevance of a dimensional approach in addition to diagnosis. Treatments for BDD could benefit from targeting visual misperception and evaluation processes upon confrontation with emotional information.

Changes in brain function during negative emotion processing in the long-term course of depression.

BACKGROUND: Relapses in major depression are frequent and are associated with a high burden of disease. Although short-term studies suggest a normalisation of depression-associated brain functional alterations directly after treatment, long-term investigations are sparse. AIMS: To examine brain function during negative emotion processing in association with course of illness over a 2-year span. METHOD: In this prospective case-control study, 72 in-patients with current depression and 42 healthy controls were investigated during a negative emotional face processing paradigm, at baseline and after 2 years. According to their course of illness during the study interval, patients were divided into subgroups (n = 25 no-relapse, n = 47 relapse). The differential changes in brain activity were investigated by a group × time analysis of covariance for the amygdala, hippocampus, insula and at whole-brain level. RESULTS: A significant relapse × time interaction emerged within the amygdala (PTFCE-FWE = 0.011), insula (PTFCE-FWE = 0.001) and at the whole-brain level mainly in the temporal and prefrontal cortex (PTFCE-FWE = 0.027), resulting from activity increases within the no-relapse group, whereas in the relapse group, activity decreased during the study interval. At baseline, the no-relapse group showed amygdala, hippocampus and insula hypoactivity compared with healthy controls and the relapse group. CONCLUSIONS: This study reveals course of illness-associated activity changes in emotion processing areas. Patients in full remission show a normalisation of their baseline hypo-responsiveness to the activation level of healthy controls after 2 years. Brain function during emotion processing could further serve as a potential predictive marker for future relapse.

Visualizing Emotional Arousal within the Context of Body Size Evaluation: A Pilot Study of Steady-State Visual Evoked Potentials in Women with Anorexia Nervosa and Healthy Controls.

Maladaptive body size evaluation processes and body dissatisfaction are known as central risk factors for the development and maintenance of anorexia nervosa (AN). This study aimed to experimentally test potential key facets, such as (psycho)physiological, cognitive-verbal and behavioral mechanisms, within the context of these evaluation processes. Twenty-two females with AN (AN-G) and 22 healthy controls (HC-G) looked at pictures of their body gradually increasing in weight using a morphing technique. Implicit emotional arousal was assessed using steady-state visual evoked potentials (SSVEP) in electroencephalography. Additionally, in a forced-choice body size evaluation task, participants were asked to classify pictures of their own body as not big or big while reaction times were captured. A significantly earlier increase in SSVEPs emerged in AN-G compared to HC-G (p <.05), with AN-G evaluating their bodies in the morphing process as big at a significantly thinner body size (p <.05). The AN-G showed faster reaction times in the categorical evaluation of body stimuli (p <.05). Findings from this multimodal paradigm underline the importance of body size evaluation mechanisms and underlying emotional arousal for AN. A differentiated understanding of these processes is essential, since the effectiveness of therapeutic interventions for AN is limited and relapses are frequent.

Association Between Genetic Risk for Type 2 Diabetes and Structural Brain Connectivity in Major Depressive Disorder.

BACKGROUND: Major depressive disorder (MDD) and type 2 diabetes mellitus (T2D) are known to share clinical comorbidity and to have genetic overlap. Besides their shared genetics, both diseases seem to be associated with alterations in brain structural connectivity and impaired cognitive performance, but little is known about the mechanisms by which genetic risk of T2D might affect brain structure and function and if they do, how these effects could contribute to the disease course of MDD. METHODS: This study explores the association of polygenic risk for T2D with structural brain connectome topology and cognitive performance in 434 nondiabetic patients with MDD and 539 healthy control subjects. RESULTS: Polygenic risk score for T2D across MDD patients and healthy control subjects was found to be associated with reduced global fractional anisotropy, a marker of white matter microstructure, an effect found to be predominantly present in MDD-related fronto-temporo-parietal connections. A mediation analysis further suggests that this fractional anisotropy variation may mediate the association between polygenic risk score and cognitive performance. CONCLUSIONS: Our findings provide preliminary evidence of a polygenic risk for T2D to be linked to brain structural connectivity and cognition in patients with MDD and healthy control subjects, even in the absence of a direct T2D diagnosis. This suggests an effect of T2D genetic risk on white matter integrity, which may mediate an association of genetic risk for diabetes and cognitive impairments.

Diagnosis of bipolar disorders and body mass index predict clustering based on similarities in cortical thickness-ENIGMA study in 2436 individuals.

AIMS: Rates of obesity have reached epidemic proportions, especially among people with psychiatric disorders. While the effects of obesity on the brain are of major interest in medicine, they remain markedly under-researched in psychiatry. METHODS: We obtained body mass index (BMI) and magnetic resonance imaging-derived regional cortical thickness, surface area from 836 bipolar disorders (BD) and 1600 control individuals from 14 sites within the ENIGMA-BD Working Group. We identified regionally specific profiles of cortical thickness using K-means clustering and studied clinical characteristics associated with individual cortical profiles. RESULTS: We detected two clusters based on similarities among participants in cortical thickness. The lower thickness cluster (46.8% of the sample) showed thinner cortex, especially in the frontal and temporal lobes and was associated with diagnosis of BD, higher BMI, and older age. BD individuals in the low thickness cluster were more likely to have the diagnosis of bipolar disorder I and less likely to be treated with lithium. In contrast, clustering based on similarities in the cortical surface area was unrelated to BD or BMI and only tracked age and sex. CONCLUSIONS: We provide evidence that both BD and obesity are associated with similar alterations in cortical thickness, but not surface area. The fact that obesity increased the chance of having low cortical thickness could explain differences in cortical measures among people with BD. The thinner cortex in individuals with higher BMI, which was additive and similar to the BD-associated alterations, may suggest that treating obesity could lower the extent of cortical thinning in BD.

Neural processing of emotional facial stimuli in specific phobia: An fMRI study.

BACKGROUND: Patients with specific phobia (SP) show altered brain activation when confronted with phobia-specific stimuli. It is unclear whether this pathogenic activation pattern generalizes to other emotional stimuli. This study addresses this question by employing a well-powered sample while implementing an established paradigm using nonspecific aversive facial stimuli. METHODS: N = 111 patients with SP, spider subtype, and N = 111 healthy controls (HCs) performed a supraliminal emotional face-matching paradigm contrasting aversive faces versus shapes in a 3-T magnetic resonance imaging scanner. We performed region of interest (ROI) analyses for the amygdala, the insula, and the anterior cingulate cortex using univariate as well as machine-learning-based multivariate statistics based on this data. Additionally, we investigated functional connectivity by means of psychophysiological interaction (PPI). RESULTS: Although the presentation of emotional faces showed significant activation in all three ROIs across both groups, no group differences emerged in all ROIs. Across both groups and in the HC > SP contrast, PPI analyses showed significant task-related connectivity of brain areas typically linked to higher-order emotion processing with the amygdala. The machine learning approach based on whole-brain activity patterns could significantly differentiate the groups with 73% balanced accuracy. CONCLUSIONS: Patients suffering from SP are characterized by differences in the connectivity of the amygdala and areas typically linked to emotional processing in response to aversive facial stimuli (inferior parietal cortex, fusiform gyrus, middle cingulate, postcentral cortex, and insula). This might implicate a subtle difference in the processing of nonspecific emotional stimuli and warrants more research furthering our understanding of neurofunctional alteration in patients with SP.

Association between body mass index and subcortical brain volumes in bipolar disorders-ENIGMA study in 2735 individuals.

Individuals with bipolar disorders (BD) frequently suffer from obesity, which is often associated with neurostructural alterations. Yet, the effects of obesity on brain structure in BD are under-researched. We obtained MRI-derived brain subcortical volumes and body mass index (BMI) from 1134 BD and 1601 control individuals from 17 independent research sites within the ENIGMA-BD Working Group. We jointly modeled the effects of BD and BMI on subcortical volumes using mixed-effects modeling and tested for mediation of group differences by obesity using nonparametric bootstrapping. All models controlled for age, sex, hemisphere, total intracranial volume, and data collection site. Relative to controls, individuals with BD had significantly higher BMI, larger lateral ventricular volume, and smaller volumes of amygdala, hippocampus, pallidum, caudate, and thalamus. BMI was positively associated with ventricular and amygdala and negatively with pallidal volumes. When analyzed jointly, both BD and BMI remained associated with volumes of lateral ventricles  and amygdala. Adjusting for BMI decreased the BD vs control differences in ventricular volume. Specifically, 18.41% of the association between BD and ventricular volume was mediated by BMI (Z = 2.73, p = 0.006). BMI was associated with similar regional brain volumes as BD, including lateral ventricles, amygdala, and pallidum. Higher BMI may in part account for larger ventricles, one of the most replicated findings in BD. Comorbidity with obesity could explain why neurostructural alterations are more pronounced in some individuals with BD. Future prospective brain imaging studies should investigate whether obesity could be a modifiable risk factor for neuroprogression.

Overcoming limitations of self-report: an assessment of fear of weight gain in anorexia nervosa and healthy controls using implicit association tests.

BACKGROUND: Fear of weight gain is a characteristic feature of anorexia nervosa (AN), and reducing this fear is often a main target of treatment. However, research shows that 20% of individuals with AN do not report fear of weight gain. Studies are needed that evaluate the centrality of fear of weight gain for AN with a method less susceptible to deception than self-report. METHODS: We approximated implicit fear of weight gain by measuring implicit drive for thinness using implicit association tests (IATs). We asked 64 participants (35 AN, 29 healthy controls [HCs]) to categorize statements as pro-dieting vs. non-dieting and true vs. false in a questionnaire-based IAT, and pictures of underweight vs. normal-weight models and positive vs. negative words in a picture-based IAT using two response keys. We tested for associations between implicit drive for thinness and explicitly reported psychopathology within AN as well as group differences between AN and HC groups. RESULTS: Correlation analyses within the AN group showed that higher implicit drive for thinness was associated with more pronounced eating disorder-specific psychopathology. Furthermore, the AN group showed a stronger implicit drive for thinness than HCs in both IATs. CONCLUSION: The results highlight the relevance of considering fear of weight gain as a continuous construct. Our implicit assessment captures various degrees of fear of weight gain in AN, which might allow for more individually tailored interventions in the future.

Virtual Histology of Cortical Thickness and Shared Neurobiology in 6 Psychiatric Disorders.

IMPORTANCE: Large-scale neuroimaging studies have revealed group differences in cortical thickness across many psychiatric disorders. The underlying neurobiology behind these differences is not well understood. OBJECTIVE: To determine neurobiologic correlates of group differences in cortical thickness between cases and controls in 6 disorders: attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), major depressive disorder (MDD), obsessive-compulsive disorder (OCD), and schizophrenia. DESIGN, SETTING, AND PARTICIPANTS: Profiles of group differences in cortical thickness between cases and controls were generated using T1-weighted magnetic resonance images. Similarity between interregional profiles of cell-specific gene expression and those in the group differences in cortical thickness were investigated in each disorder. Next, principal component analysis was used to reveal a shared profile of group difference in thickness across the disorders. Analysis for gene coexpression, clustering, and enrichment for genes associated with these disorders were conducted. Data analysis was conducted between June and December 2019. The analysis included 145 cohorts across 6 psychiatric disorders drawn from the ENIGMA consortium. The numbers of cases and controls in each of the 6 disorders were as follows: ADHD: 1814 and 1602; ASD: 1748 and 1770; BD: 1547 and 3405; MDD: 2658 and 3572; OCD: 2266 and 2007; and schizophrenia: 2688 and 3244. MAIN OUTCOMES AND MEASURES: Interregional profiles of group difference in cortical thickness between cases and controls. RESULTS: A total of 12 721 cases and 15 600 controls, ranging from ages 2 to 89 years, were included in this study. Interregional profiles of group differences in cortical thickness for each of the 6 psychiatric disorders were associated with profiles of gene expression specific to pyramidal (CA1) cells, astrocytes (except for BD), and microglia (except for OCD); collectively, gene-expression profiles of the 3 cell types explain between 25% and 54% of variance in interregional profiles of group differences in cortical thickness. Principal component analysis revealed a shared profile of difference in cortical thickness across the 6 disorders (48% variance explained); interregional profile of this principal component 1 was associated with that of the pyramidal-cell gene expression (explaining 56% of interregional variation). Coexpression analyses of these genes revealed 2 clusters: (1) a prenatal cluster enriched with genes involved in neurodevelopmental (axon guidance) processes and (2) a postnatal cluster enriched with genes involved in synaptic activity and plasticity-related processes. These clusters were enriched with genes associated with all 6 psychiatric disorders. CONCLUSIONS AND RELEVANCE: In this study, shared neurobiologic processes were associated with differences in cortical thickness across multiple psychiatric disorders. These processes implicate a common role of prenatal development and postnatal functioning of the cerebral cortex in these disorders.

Faced with one's fear: Attentional bias in anorexia nervosa and healthy individuals upon confrontation with an obese body stimulus in an eye-tracking paradigm.

OBJECTIVES: Cognitive biases, particularly attentional biases, have been shown to be central to anorexia nervosa (AN). This study looked at attention deployment when consecutively viewing an obese and own body stimulus that both might represent feared stimuli in AN. METHODS: Individuals with AN (n = 26) and mentally healthy controls (MHCs; n = 16) viewed a picture of themselves and a standardized computer-generated obese body in random order for 4,000 ms each and then rated the attractiveness of the body parts of both stimuli. We compared dwell times on subjectively unattractive versus attractive body parts, and body parts that show weight status and gain most strongly (stomach, hips, thighs) versus least strongly. RESULTS: For both stimuli, participants focused longer on the subjectively unattractive body parts (p < .01 and .001), with an even stronger attentional bias in individuals with AN regarding the obese stimulus (p < .05). Both groups also gazed longer at body parts indicative of weight status or gain (both stimuli p < .001), with no group differences. CONCLUSIONS: The attentional bias to one's own subjectively unattractive body parts might represent a mechanism maintaining body image disturbance in women in general. This attentional bias is even stronger when women with AN are confronted with an obese stimulus, highlighting a potential mental preoccupation with being fat or weight gain and a behavior distinct for the disorder.