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A previously published genome-wide association study (GWAS) meta-analysis across eight neuropsychiatric disorders identified antagonistic single-nucleotide polymorphisms (SNPs) at eleven genomic loci where the same allele was protective against one neuropsychiatric disorder and increased the risk for another. Until now, these antagonistic SNPs have not been further investigated regarding their link to brain structural phenotypes. Here, we explored their associations with cortical surface area and cortical thickness (in 34 brain regions and one global measure each) as well as the volumes of eight subcortical structures using summary statistics of large-scale GWAS of brain structural phenotypes. We assessed if significantly associated brain structural phenotypes were previously reported to be associated with major neuropsychiatric disorders in large-scale case-control imaging studies by the ENIGMA consortium. We further characterized the effects of the antagonistic SNPs on gene expression in brain tissue and their association with additional cognitive and behavioral phenotypes, and performed an exploratory voxel-based whole-brain analysis in the FOR2107 study (n = 754 patients with major depressive disorder and n = 847 controls). We found that eight antagonistic SNPs were significantly associated with brain structural phenotypes in regions such as anterior parts of the cingulate cortex, the insula, and the superior temporal gyrus. Case-control differences in implicated brain structural phenotypes have previously been reported for bipolar disorder, major depressive disorder, and schizophrenia. In addition, antagonistic SNPs were associated with gene expression changes in brain tissue and linked to several cognitive-behavioral traits. In our exploratory whole-brain analysis, we observed significant associations of gray matter volume in the left superior temporal pole and left superior parietal region with the variants rs301805 and rs1933802, respectively. Our results suggest that multiple antagonistic SNPs for neuropsychiatric disorders are linked to brain structural phenotypes. However, to further elucidate these findings, future case-control genomic imaging studies are required., (© 2024. The Author(s).)

Childhood maltreatment (CM) is associated with increased limbic activity, while social support is linked to decreased limbic activity towards negative stimuli. Our study aimed to explore the interaction of perceived social support with CM, and their combined impact on limbic activity in negative emotion processing. A total of 130 healthy individuals (HC) underwent a negative emotional face processing paradigm. They were divided into two groups based on the Childhood Trauma Questionnaire: n = 65 HC without CM matched with n = 65 HC with CM. In a region-of-interest approach of the bilateral amygdala-hippocampus-complex (AHC), regression analyses investigating the association of CM and perceived social support with limbic activity and a social support x CM ANCOVA were conducted. CM was associated with increased AHC activity, while perceived social support tended to be associated with decreased AHC activity during negative emotion processing. The ANCOVA showed a significant interaction in bilateral AHC activity (p FWE  ≤ 0.024) driven by a negative association between perceived social support and bilateral AHC activity in HC without CM. No significant association was observed in HC with CM. Exploratory analyses using continuous CM scores support this finding. Our results suggest that CM moderates the link between perceived social support and limbic activity, with a protective effect of perceived social support only in HC without CM. The lack of this effect in HC with CM suggests that CM may alter the buffering effect of perceived social support on limbic functioning, highlighting the potential need for preventive interventions targeting social perception of HC with CM., (© 2024. The Author(s).)

Deficits in memory performance have been linked to a wide range of neurological and neuropsychiatric conditions. While many studies have assessed the memory impacts of individual conditions, this study considers a broader perspective by evaluating how memory recall is differentially associated with nine common neuropsychiatric conditions using data drawn from 55 international studies, aggregating 15,883 unique participants aged 15-90. The effects of dementia, mild cognitive impairment, Parkinson's disease, traumatic brain injury, stroke, depression, attention-deficit/hyperactivity disorder (ADHD), schizophrenia, and bipolar disorder on immediate, short-, and long-delay verbal learning and memory (VLM) scores were estimated relative to matched healthy individuals. Random forest models identified age, years of education, and site as important VLM covariates. A Bayesian harmonization approach was used to isolate and remove site effects. Regression estimated the adjusted association of each clinical group with VLM scores. Memory deficits were strongly associated with dementia and schizophrenia ( p < 0.001), while neither depression nor ADHD showed consistent associations with VLM scores ( p > 0.05). Differences associated with clinical conditions were larger for longer delayed recall duration items. By comparing VLM across clinical conditions, this study provides a foundation for enhanced diagnostic precision and offers new insights into disease management of comorbid disorders.

Multivariate techniques better fit the anatomy of complex neuropsychiatric disorders which are characterized not by alterations in a single region, but rather by variations across distributed brain networks. Here, we used principal component analysis (PCA) to identify patterns of covariance across brain regions and relate them to clinical and demographic variables in a large generalizable dataset of individuals with bipolar disorders and controls. We then compared performance of PCA and clustering on identical sample to identify which methodology was better in capturing links between brain and clinical measures. Using data from the ENIGMA-BD working group, we investigated T1-weighted structural MRI data from 2436 participants with BD and healthy controls, and applied PCA to cortical thickness and surface area measures. We then studied the association of principal components with clinical and demographic variables using mixed regression models. We compared the PCA model with our prior clustering analyses of the same data and also tested it in a replication sample of 327 participants with BD or schizophrenia and healthy controls. The first principal component, which indexed a greater cortical thickness across all 68 cortical regions, was negatively associated with BD, BMI, antipsychotic medications, and age and was positively associated with Li treatment. PCA demonstrated superior goodness of fit to clustering when predicting diagnosis and BMI. Moreover, applying the PCA model to the replication sample yielded significant differences in cortical thickness between healthy controls and individuals with BD or schizophrenia. Cortical thickness in the same widespread regional network as determined by PCA was negatively associated with different clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. PCA outperformed clustering and provided an easy-to-use and interpret method to study multivariate associations between brain structure and system-level variables. PRACTITIONER POINTS: In this study of 2770 Individuals, we confirmed that cortical thickness in widespread regional networks as determined by principal component analysis (PCA) was negatively associated with relevant clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. Significant associations of many different system-level variables with the same brain network suggest a lack of one-to-one mapping of individual clinical and demographic factors to specific patterns of brain changes. PCA outperformed clustering analysis in the same data set when predicting group or BMI, providing a superior method for studying multivariate associations between brain structure and system-level variables., (© 2024 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Although highly effective on average, exposure-based treatments do not work equally well for all patients with anxiety disorders. The identification of pre-treatment response-predicting patient characteristics may enable patient stratification. Preliminary research highlights the relevance of inhibitory fronto-limbic networks as such. We aimed to identify pre-treatment neural signatures differing between exposure treatment responders and non-responders in spider phobia and to validate results through rigorous replication. Data of a bi-centric intervention study comprised clinical phenotyping and pre-treatment resting-state functional connectivity (rsFC) data of n = 79 patients with spider phobia (discovery sample) and n = 69 patients (replication sample). RsFC data analyses were accomplished using the Matlab-based CONN-toolbox with harmonized analyses protocols at both sites. Treatment response was defined by a reduction of >30% symptom severity from pre- to post-treatment (Spider Phobia Questionnaire Score, primary outcome). Secondary outcome was defined by a reduction of >50% in a Behavioral Avoidance Test (BAT). Mean within-session fear reduction functioned as a process measure for exposure. Compared to non-responders and pre-treatment, results in the discovery sample seemed to indicate that responders exhibited stronger negative connectivity between frontal and limbic structures and were characterized by heightened connectivity between the amygdala and ventral visual pathway regions. Patients exhibiting high within-session fear reduction showed stronger excitatory connectivity within the prefrontal cortex than patients with low within-session fear reduction. Whereas these results could be replicated by another team using the same data (cross-team replication), cross-site replication of the discovery sample findings in the independent replication sample was unsuccessful. Results seem to support negative fronto-limbic connectivity as promising ingredient to enhance response rates in specific phobia but lack sufficient replication. Further research is needed to obtain a valid basis for clinical decision-making and the development of individually tailored treatment options. Notably, future studies should regularly include replication approaches in their protocols., (© 2024. The Author(s).)

Temporal neural synchrony disruption can be linked to a variety of symptoms of major depressive disorder (MDD), including mood rigidity and the inability to break the cycle of negative emotion or attention biases. This might imply that altered dynamic neural synchrony may play a role in the persistence and exacerbation of MDD symptoms. Our study aimed to investigate the changes in whole-brain dynamic patterns of the brain functional connectivity and activity related to depression using the hidden Markov model (HMM) on resting-state functional magnetic resonance imaging (rs-fMRI) data. We compared the patterns of brain functional dynamics in a large sample of 314 patients with MDD (65.9% female; age (mean ± standard deviation): 35.9 ± 13.4) and 498 healthy controls (59.4% female; age: 34.0 ± 12.8). The HMM model was used to explain variations in rs-fMRI functional connectivity and averaged functional activity across the whole-brain by using a set of six unique recurring states. This study compared the proportion of time spent in each state and the average duration of visits to each state to assess stability between different groups. Compared to healthy controls, patients with MDD showed significantly higher proportional time spent and temporal stability in a state characterized by weak functional connectivity within and between all brain networks and relatively strong averaged functional activity of regions located in the somatosensory motor (SMN), salience (SN), and dorsal attention (DAN) networks. Both proportional time spent and temporal stability of this brain state was significantly associated with depression severity. Healthy controls, in contrast to the MDD group, showed proportional time spent and temporal stability in a state with relatively strong functional connectivity within and between all brain networks but weak averaged functional activity across the whole brain. These findings suggest that disrupted brain functional synchrony across time is present in MDD and associated with current depression severity., (© 2023. The Author(s).)

Background: Anhedonia is a key symptom of major depressive disorder (MDD). Anhedonia is associated with aberrant reward processing, but whether it might interfere similarly with the neural processing of aversive stimuli, such as monetary loss, remains unknown. We aimed to investigate potential associations between anhedonia and neural response during reward and loss processing in patients with MDD., Methods: We investigated blood-oxygen-level-dependent response in the orbitofrontal cortex, cingulate cortex, insula and basal ganglia during monetary reward and loss processing in 182 patients with MDD, using a card-guessing paradigm. We measured anhedonia with the Social and Physical Anhedonia Scale (SASPAS), and we tested for the main and interaction effects of SASPAS scores and the experimental condition (reward or loss) in a full factorial model., Results: We detected a negative main effect of anhedonia, as well as a significant interaction effect of anhedonia and the experimental condition, on orbitofrontal and insular neural response. Post hoc analyses revealed that the interaction was driven by a significant association between higher anhedonia scores and hypoactivation during loss processing. We observed no significant association between anhedonia and neural response during reward processing., Limitations: This study had a cross-sectional design., Conclusion: Our findings confirmed that altered neural processing in the orbitofrontal cortex and insula is a neurobiological feature of anhedonic symptomatology in people with MDD. The pronounced association between anhedonia and blunted neural response during loss processing supports a broader concept for the neurobiological basis of anhedonia. Hence, MDD with anhedonic features might be characterized by reduced neural response to external stimuli, potentially because of amotivation., Competing Interests: Competing interests: J. Goltermann received a Society of Biological Psychiatry 2022 travel Award. No other competing interests declared., (© 2022 CMA Impact Inc. or its licensors.)

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 ( P TFCE-FWE = 0.011), insula ( P TFCE-FWE = 0.001) and at the whole-brain level mainly in the temporal and prefrontal cortex ( P TFCE-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.

Background: Childhood maltreatment has been associated with reduced hippocampal volume in healthy individuals, whereas social support, a protective factor, has been positively associated with hippocampal volumes. In this study, we investigated how social support is associated with hippocampal volume in healthy people with previous experience of childhood maltreatment., Methods: We separated a sample of 446 healthy participants into 2 groups using the Childhood Trauma Questionnaire: 265 people without maltreatment and 181 people with maltreatment. We measured perceived social support using a short version of the Social Support Questionnaire. We examined hippocampal volume using automated segmentation (Freesurfer). We conducted a social support × group analysis of covariance on hippocampal volumes controlling for age, sex, total intracranial volume, site and verbal intelligence., Results: Our analysis revealed significantly lower left hippocampal volume in people with maltreatment (left F1,432 = 5.686, p = 0.018; right F1,433 = 3.371, p = 0.07), but no main effect of social support emerged. However, we did find a significant social support × group interaction for left hippocampal volume (left F1,432 = 5.712, p = 0.017; right F1,433 = 3.480, p = 0.06). In people without maltreatment, we observed a trend toward a positive association between social support and hippocampal volume. In contrast, social support was negatively associated with hippocampal volume in people with maltreatment., Limitations: Because of the correlative nature of our study, we could not infer causal relationships between social support, maltreatment and hippocampal volume., Conclusion: Our results point to a complex dynamic between environmental risk, protective factors and brain structure - in line with previous evidence - suggesting a detrimental effect of maltreatment on hippocampal development., Competing Interests: None declared., (© 2021 CMA Joule Inc. or its licensors.)

Childhood maltreatment is associated with cognitive deficits that in turn have been predictive for therapeutic outcome in psychiatric patients. However, previous studies have either investigated maltreatment associations with single cognitive domains or failed to adequately control for confounders such as depression, socioeconomic environment, and genetic predisposition. We aimed to isolate the relationship between childhood maltreatment and dysfunction in diverse cognitive domains, while estimating the contribution of potential confounders to this relationship, and to investigate gene-environment interactions. We included 547 depressive disorder and 670 healthy control participants (mean age: 34.7 years, SD = 13.2). Cognitive functioning was assessed for the domains of working memory, executive functioning, processing speed, attention, memory, and verbal intelligence using neuropsychological tests. Childhood maltreatment and parental education were assessed using self-reports, and psychiatric diagnosis was based on DSM-IV criteria. Polygenic scores for depression and for educational attainment were calculated. Multivariate analysis of cognitive domains yielded significant associations with childhood maltreatment (η² p  = 0.083, P < 0.001), depression (η² p  = 0.097, P < 0.001), parental education (η² p  = 0.085, P < 0.001), and polygenic scores for depression (η² p  = 0.021, P = 0.005) and educational attainment (η² p  = 0.031, P < 0.001). Each of these associations remained significant when including all of the predictors in one model. Univariate tests revealed that maltreatment was associated with poorer performance in all cognitive domains. Thus, environmental, psychopathological, and genetic risk factors each independently affect cognition. The insights of the current study may aid in estimating the potential impact of different loci of interventions for cognitive dysfunction. Future research should investigate if customized interventions, informed by individual risk profiles and related cognitive preconditions, might enhance response to therapeutic treatments.

Background: Smartphone-based symptom monitoring has gained increased attention in psychiatric research as a cost-efficient tool for prospective and ecologically valid assessments based on participants' self-reports. However, a meaningful interpretation of smartphone-based assessments requires knowledge about their psychometric properties, especially their validity., Objective: The goal of this study is to systematically investigate the validity of smartphone-administered assessments of self-reported affective symptoms using the Remote Monitoring Application in Psychiatry (ReMAP)., Methods: The ReMAP app was distributed to 173 adult participants of ongoing, longitudinal psychiatric phenotyping studies, including healthy control participants, as well as patients with affective disorders and anxiety disorders; the mean age of the sample was 30.14 years (SD 11.92). The Beck Depression Inventory (BDI) and single-item mood and sleep information were assessed via the ReMAP app and validated with non-smartphone-based BDI scores and clinician-rated depression severity using the Hamilton Depression Rating Scale (HDRS)., Results: We found overall high comparability between smartphone-based and non-smartphone-based BDI scores (intraclass correlation coefficient=0.921; P<.001). Smartphone-based BDI scores further correlated with non-smartphone-based HDRS ratings of depression severity in a subsample (r=0.783; P<.001; n=51). Higher agreement between smartphone-based and non-smartphone-based assessments was found among affective disorder patients as compared to healthy controls and anxiety disorder patients. Highly comparable agreement between delivery formats was found across age and gender groups. Similarly, smartphone-based single-item self-ratings of mood correlated with BDI sum scores (r=-0.538; P<.001; n=168), while smartphone-based single-item sleep duration correlated with the sleep item of the BDI (r=-0.310; P<.001; n=166)., Conclusions: These findings demonstrate that smartphone-based monitoring of depressive symptoms via the ReMAP app provides valid assessments of depressive symptomatology and, therefore, represents a useful tool for prospective digital phenotyping in affective disorder patients in clinical and research applications., (©Janik Goltermann, Daniel Emden, Elisabeth Johanna Leehr, Katharina Dohm, Ronny Redlich, Udo Dannlowski, Tim Hahn, Nils Opel. Originally published in JMIR Mental Health (http://mental.jmir.org), 12.01.2021.)

It has been difficult to find robust brain structural correlates of the overall severity of major depressive disorder (MDD). We hypothesized that specific symptoms may better reveal correlates and investigated this for the severity of insomnia, both a key symptom and a modifiable major risk factor of MDD. Cortical thickness, surface area and subcortical volumes were assessed from T1-weighted brain magnetic resonance imaging (MRI) scans of 1053 MDD patients (age range 13-79 years) from 15 cohorts within the ENIGMA MDD Working Group. Insomnia severity was measured by summing the insomnia items of the Hamilton Depression Rating Scale (HDRS). Symptom specificity was evaluated with correlates of overall depression severity. Disease specificity was evaluated in two independent samples comprising 2108 healthy controls, and in 260 clinical controls with bipolar disorder. Results showed that MDD patients with more severe insomnia had a smaller cortical surface area, mostly driven by the right insula, left inferior frontal gyrus pars triangularis, left frontal pole, right superior parietal cortex, right medial orbitofrontal cortex, and right supramarginal gyrus. Associations were specific for insomnia severity, and were not found for overall depression severity. Associations were also specific to MDD; healthy controls and clinical controls showed differential insomnia severity association profiles. The findings indicate that MDD patients with more severe insomnia show smaller surfaces in several frontoparietal cortical areas. While explained variance remains small, symptom-specific associations could bring us closer to clues on underlying biological phenomena of MDD.

Background: Predictive models have revealed promising results for the individual prognosis of treatment response and relapse risk as well as for differential diagnosis in affective disorders. Yet, in order to translate personalized predictive modeling from research contexts to psychiatric clinical routine, standardized collection of information of sufficient detail and temporal resolution in day-to-day clinical care is needed. Digital collection of self-report measures by patients is a time- and cost-efficient approach to gain such data throughout treatment., Objective: The objective of this study was to investigate whether patients with severe affective disorders were willing and able to participate in such efforts, whether the feasibility of such systems might vary depending on individual patient characteristics, and if digitally acquired assessments were of sufficient diagnostic validity., Methods: We implemented a system for longitudinal digital collection of risk and symptom profiles based on repeated self-reports via tablet computers throughout inpatient treatment of affective disorders at the Department of Psychiatry at the University of Münster. Tablet-handling competency and the speed of data entry were assessed. Depression severity was additionally assessed by a clinical interviewer at baseline and before discharge., Results: Of 364 affective disorder patients who were approached, 242 (66.5%) participated in the study; 88.8% of participants (215/242) were diagnosed with major depressive disorder, and 27 (11.2%) had bipolar disorder. During the duration of inpatient treatment, 79% of expected assessments were completed, with an average of 4 completed assessments per participant; 4 participants (4/242, 1.6%) dropped out of the study prematurely. During data entry, 89.3% of participants (216/242) did not require additional support. Needing support with tablet handling and slower data entry pace were predicted by older age, whereas depression severity at baseline did not influence these measures. Patient self-reporting of depression severity showed high agreement with standardized external assessments by a clinical interviewer., Conclusions: Our results indicate that digital collection of self-report measures is a feasible, accessible, and valid method for longitudinal data collection in psychiatric routine, which will eventually facilitate the identification of individual risk and resilience factors for affective disorders and pave the way toward personalized psychiatric care., (©Maike Frederike Richter, Michael Storck, Rogério Blitz, Janik Goltermann, Juliana Seipp, Udo Dannlowski, Bernhard T Baune, Martin Dugas, Nils Opel. Originally published in JMIR Mental Health (http://mental.jmir.org), 01.12.2020.)

Reduced sleep duration and sleep deprivation have been associated with cognitive impairment as well as decreased white matter integrity as reported by experimental studies. However, it is largely unknown whether differences in sleep duration and sleep quality might affect microstructural white matter and cognition. Therefore, the present study aims to examine the cross-sectional relationship between sleep duration, sleep quality, and cognitive performance in a naturalistic study design, by focusing on the association with white matter integrity in a large sample of healthy, young adults. To address this, 1,065 participants, taken from the publicly available sample of the Human Connectome Project, underwent diffusion tensor imaging. Moreover, broad cognitive performance measures (NIH Cognition Toolbox) and sleep duration and quality (Pittsburgh Sleep Quality Index) were assessed. The results revealed a significant positive association between sleep duration and overall cognitive performance. Shorter sleep duration significantly correlated with fractional anisotropy (FA) reductions in the left superior longitudinal fasciculus (SLF). In turn, FA in this tract was related to measures of cognitive performance and was shown to significantly mediate the association of sleep duration and cognition. For cognition only, associations shift to a negative association of sleep duration and cognition for participants sleeping more than 8 hr a day. Investigations into subjective sleep quality showed no such associations. The present study showed that real-world differences in sleep duration, but not subjective sleep quality are related to cognitive performance measures and white matter integrity in the SLF in healthy, young adults., (© 2020 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Background: In treatment-resistant major depressive disorder (MDD), electroconvulsive therapy (ECT) is a treatment with high efficacy. While knowledge regarding changes in brain structure following ECT is growing, the effects of ECT on brain function during emotional processing are largely unknown., Objective: We investigated the effects of ECT on the activity of the anterior cingulate cortex (ACC) and amygdala during negative emotional stimuli processing and its association with clinical response., Methods: In this non-randomized longitudinal study, patients with MDD (n = 37) were assessed before and after treatment with ECT. Healthy controls (n = 37) were matched regarding age and gender. Functional magnetic resonance imaging (fMRI) was obtained twice, at baseline and after six weeks using a supraliminal face-matching paradigm. In order to evaluate effects of clinical response, additional post-hoc analyses were performed comparing responders to non-responders., Results: After ECT, patients with MDD showed a statistically significant increase in ACC activity during processing of negative emotional stimuli (p FWE  = .039). This effect was driven by responders (p FWE  = .023), while non-responders showed no increase. Responders also had lower pre-treatment ACC activity compared to non-responders (p FWE  = .025). No significant effects in the amygdala could be observed., Conclusions: ECT leads to brain functional changes in the ACC, a relevant region for emotional regulation during processing of negative stimuli. Furthermore, baseline ACC activity might serve as a biomarker for treatment response. Findings are in accordance with recent studies highlighting properties of pre-treatment ACC to be associated with general antidepressive treatment response., Competing Interests: Declaration of competing interest None., (Copyright © 2020 The Author(s). Published by Elsevier Inc. All rights reserved.)

Genetic predisposition and brain structural abnormalities have been shown to be involved in the biological underpinnings of anorexia nervosa (AN). Prefrontal brain regions are suggested to contribute through behavioral inhibition mechanisms to body weight. However, it is unknown if and to which extent biological correlates for AN might be present in individuals without clinical AN symptomatology. We therefore investigated the contribution of polygenic load for AN on body weight and prefrontal brain structure in a sample of n = 380 nonclinical individuals. A polygenic score (PGS) reflecting the individual genetic load for the trait of anorexia nervosa was calculated. Structural MRI data were acquired and preprocessed using the cortical parcellation stream of FreeSurfer. We observed a significant PGS × sex interaction effect on body mass index (BMI), which was driven by a negative correlation between PGS and BMI in female participants. Imaging analyses revealed significant interaction effects of sex  × PGS on surface area of the lateral orbitofrontal cortex (OFC), the pars orbitalis (PO), the rostral middle frontal gyrus (RMF) and the pars triangularis (PT) of the left frontal cortex. The interaction effects were driven by positive correlations between PGS and prefrontal surface areas in female participants and negative correlations in male participants. We furthermore found sex-specific associations between BMI and left RMF surface area as well as between BMI and left PO and left RMF thickness. Our findings demonstrate a sex-specific association between polygenic load for AN, BMI, and prefrontal brain structure in nonclinical individuals. Hence, this study identifies structural abnormalities associated with polygenic load for AN and BMI in brain regions deeply involved in behavioral inhibition and impulse regulation as candidate brain regions for future research.

Reduced fractional anisotropy (FA) associated with Major Depressive Disorder (MDD) overlaps anatomically with effects of childhood maltreatment experiences. The aim of this study was, therefore, to replicate the negative effect of childhood maltreatment on white matter fiber structure and to demonstrate, that alterations in MDD might be partially attributed to the higher occurrence of childhood maltreatment in MDD. Two independent cohorts (total N = 1 256) were investigated in a diffusion tensor imaging study: The Münster Neuroimaging Cohort (MNC, N = 186 MDD, N = 210 healthy controls, HC) as discovery sample and the Marburg-Münster Affective Disorders Cohort Study (MACS, N = 397 MDD, N = 462 HC) as replication sample. The effects of diagnosis (HC vs. MDD) and Childhood Trauma Questionnaire (CTQ) scores on FA were analyzed. A main effect of diagnosis with higher FA in MDD patients compared with HC was found in the MNC (p FWE  = 0.021), but not in the MACS (p FWE  = 0.52) before correcting for CTQ. A significant negative correlation of FA with CTQ emerged in both cohorts (MNC: p FWE  = 0.006, MACS: p FWE  = 0.012) in several tracts previously described in the literature. No CTQ × diagnosis interaction could be detected. Any main effect of diagnosis was abolished after correcting for CTQ (MNC: p FWE  = 0.562, MACS: p FWE  = 0.115). No differences in FA between MDD and HC could be found after correcting for childhood maltreatment, suggesting that previously reported group differences might be attributed partially to higher levels of maltreatment experiences in MDD rather than diagnosis itself. Furthermore, a well-established finding of reduced FA following childhood maltreatment experiences was replicated.

Background: Cross-sectional studies have repeatedly shown impaired white matter integrity in patients with major depressive disorder. Longitudinal analyses are missing from the current research and are crucial to elucidating the impact of disease trajectories on white matter impairment in major depressive disorder., Methods: Fifty-nine patients with major depressive disorder receiving inpatient treatment, as well as 49 healthy controls, took part in a prospective study. Participants were scanned twice (baseline and follow-up), approximately 2.25 years apart, using diffusion tensor imaging. We analyzed diffusion metrics using tract-based spatial statistics., Results: At baseline, patients had higher mean diffusivity in a large bilateral frontal cluster comprising the body and genu of the corpus callosum, the anterior and superior corona radiata, and the superior longitudinal fasciculus. A significant group × time interaction revealed a decrease of mean diffusivity in patients with major depressive disorder over time, abolishing group differences at follow-up. This effect was observed irrespective of disease course in the follow-up period., Limitations: Analyzing the course of illness is challenging because of recollection biases in patients with major depressive disorder., Conclusion: This study reports follow-up diffusion tensor imaging data in patients with major depressive disorder after an acute depressive episode. We demonstrated impaired prefrontal white matter microstructure (higher mean diffusivity) at baseline in patients with major depressive disorder, which normalized at follow-up after 2 years, irrespective of disease course. This might have been due to a general treatment effect and might have reflected recovery of white matter integrity., Competing Interests: H. Kugel has received consultation fees from MR:comp GmbH, Testing Services for MR Safety, outside the submitted work. V. Arolt is a member of the advisory boards of Allergan, Janssen-Cilag, Lundbeck, Otsuka, Servier and Trommsdorff and has received speaker fees from Janssen-Cilag, Lundbeck, Otsuka, Servier, outside the submitted work. No other competing interests declared., (© 2019 Joule Inc. or its licensors)

We aimed to extend our knowledge on the relationship between physical fitness (PF) and both white matter microstructure and cognition through in-depth investigation of various cognitive domains while accounting for potentially relevant nuisance covariates in a well-powered sample. To this end, associations between walking endurance, diffusion-tensor-imaging (DTI) based measures of fractional anisotropy (FA) within brain white matter and cognitive measures included in the NIH Toolbox Cognition Battery were investigated in a sample of n = 1206 healthy, young adults (mean age = 28.8; 45.5% male) as part of the human connectome project. Higher levels of endurance were associated with widespread higher FA (p FWE  < 0.05) as well as with enhanced global cognitive function (p < 0.001). Significant positive relationships between endurance and cognitive performance were similarly found for almost all cognitive domains. Higher FA was significantly associated with enhanced global cognitive function (p < 0.001) and FA was shown to significantly mediate the association between walking endurance and cognitive performance. Inclusion of potentially relevant nuisance covariates including gender, age, education, BMI, HBA1c, and arterial blood pressure did not change the overall pattern of results. These findings support the notion of a beneficial and potentially protective effect of PF on brain structure and cognition.

Theoretical background: The Apolipoprotein E (APOE) ε4 genotype is known to be one of the strongest single-gene predictors for Alzheimer disease, which is characterized by widespread brain structural degeneration progressing along with cognitive impairment. The ε4 allele status has been associated with brain structural alterations and lower cognitive ability in non-demented subjects. However, it remains unclear to what extent the visuospatial cognitive domain is affected, from what age onward changes are detectable and if alterations may interact with cognitive deficits in major depressive disorder (MDD). The current work investigated the effect of APOE ε4 homozygosity on visuospatial working memory (vWM) capacity, and on hippocampal morphometry. Furthermore, potential moderating roles of age and MDD were assessed. Methods: A sample of n = 31 homozygous ε4 carriers was contrasted with n = 31 non-ε4 carriers in a cross-sectional design. The sample consisted of non-demented, young to mid-age participants (mean age = 34.47; SD = 13.48; 51.6% female). Among them were n = 12 homozygous ε4 carriers and n = 12 non-ε4 carriers suffering from MDD (39%). VWM was assessed using the Corsi block-tapping task. Region of interest analyses of hippocampal gray matter density and volume were conducted using voxel-based morphometry (CAT12), and Freesurfer, respectively. Results: Homozygous ε4 carriers showed significantly lower Corsi span capacity than non-ε4 carriers did, and Corsi span capacity was associated with higher gray matter density of the hippocampus. APOE group differences in hippocampal volume could be detected but were no longer present when controlling for total intracranial volume. Hippocampal gray matter density did not differ between APOE groups. We did not find any interaction effects of age and MDD diagnosis on hippocampal morphometry. Conclusion: Our results point toward a negative association of homozygous ε4 allele status with vWM capacity already during mid-adulthood, which emerges independently of MDD diagnosis and age. APOE genotype seems to be associated with global brain structural rather than hippocampus specific alterations in young- to mid-age participants.