Publications by authors named "Udo Dannlowski"

231 Publications

Technical feasibility and adherence of the Remote Monitoring Application in Psychiatry (ReMAP) for the assessment of affective symptoms.

J Affect Disord 2021 Jul 16;294:652-660. Epub 2021 Jul 16.

Institute for Translational Psychiatry, University of Münster, Germany; Interdisciplinary Centre for Clinical Research (IZKF) Münster, University of Münster, Germany. Electronic address:

Background: Smartphone-based monitoring constitutes a cost-effective instrument to assess and predict affective symptom trajectories. Large-scale transdiagnostic studies utilizing this methodology are yet lacking in psychiatric research. Thus, we introduce the Remote Monitoring Application in Psychiatry (ReMAP) and evaluate its feasibility and adherence in a large transdiagnostic sample.

Methods: The ReMAP app was distributed among n = 997 healthy control participants and psychiatric patients, including affective, anxiety, and psychotic disorders. Passive sensor data (acceleration, geolocation, walking distance, steps), optional standardized self-reports on mood and sleep, and voice samples were assessed. Feasibility and adherence were evaluated based on frequency of transferred data, and participation duration. Preliminary results are presented while data collection is ongoing.

Results: Retention rates of 90.25% for the minimum study duration of two weeks and 33.09% for one year were achieved (median participation 135 days, IQR=111). Participants transferred an average of 51.83 passive events per day. An average of 34.59 self-report events were transferred per user, with a considerable range across participants (0-552 events). Clinical and non-clinical subgroups did not differ in participation duration or rate of data transfer. The mean rate of days with passive data was higher and less heterogeneous in iOS (91.85%, SD=21.25) as compared to Android users (63.04%, SD=35.09).

Limitations: Subjective user experience was not assessed limiting conclusions about app acceptance.

Conclusions: ReMAP is a technically feasible tool to assess affective symptoms with high temporal resolution in large-scale transdiagnostic samples with good adherence. Future studies should account for differences between operating systems.
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http://dx.doi.org/10.1016/j.jad.2021.07.030DOI Listing
July 2021

Behavioral and Magnetoencephalographic Correlates of Fear Generalization are Associated with Responses to Later Virtual Reality Exposure Therapy in Spider Phobia.

Biol Psychiatry Cogn Neurosci Neuroimaging 2021 Jul 26. Epub 2021 Jul 26.

Institute for Biomagnetism and Biosignalanalysis, University of Münster, Germany.

Background: As overgeneralization of fear is a pathogenic marker of anxiety disorders, we investigated whether pre-treatment levels of fear generalization in spider-phobic patients are related to their response to exposure-based treatment, in order to identify pre-treatment moderators of treatment success.

Methods: Ninety patients with spider phobia completed pre-treatment clinical and magnetoencephalography (MEG) assessments, one session of virtual reality exposure therapy, and a post-treatment clinical assessment. Based on the primary outcome (30% symptom reduction in self-reported symptoms) they were categorized as responders or non-responders. In a pre-treatment MEG fear generalization paradigm involving fear conditioning with two unconditioned stimuli (UCS), we obtained fear ratings, UCS-expectancy ratings, and event-related fields to conditioned stimuli (CS-, CS+) and 7 different generalization stimuli (GS) on a perceptual continuum from CS- to CS+.

Results: Prior to treatment, non-responders showed behavioral overgeneralization indicated by more linear generalization gradients in fear ratings. Analyses of MEG source estimations revealed that non-responders showed a decline of their (inhibitory) frontal activations to safety-signaling CS- and GS compared to CS+ over time, while responders maintained these activations at early (<300ms) and late processing stages.

Conclusions: Results provide initial evidence that pre-treatment differences of behavioral and neural markers of fear generalization may act as moderators of later responses to behavioral exposure. Stimulating further research on fear generalization as a potential predictive marker, our findings are an important first step in the attempt to identify patients who may not profit from ET, and to personalize and optimize treatment strategies for this vulnerable patient group.
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http://dx.doi.org/10.1016/j.bpsc.2021.07.006DOI Listing
July 2021

Brain structural connectivity, anhedonia, and phenotypes of major depressive disorder: A structural equation model approach.

Hum Brain Mapp 2021 Jul 24. Epub 2021 Jul 24.

Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany.

Aberrant brain structural connectivity in major depressive disorder (MDD) has been repeatedly reported, yet many previous studies lack integration of different features of MDD with structural connectivity in multivariate modeling approaches. In n = 595 MDD patients, we used structural equation modeling (SEM) to test the intercorrelations between anhedonia, anxiety, neuroticism, and cognitive control in one comprehensive model. We then separately analyzed diffusion tensor imaging (DTI) connectivity measures in association with those clinical variables, and finally integrated brain connectivity associations, clinical/cognitive variables into a multivariate SEM. We first confirmed our clinical/cognitive SEM. DTI analyses (FWE-corrected) showed a positive correlation of anhedonia with fractional anisotropy (FA) in the right anterior thalamic radiation (ATR) and forceps minor/corpus callosum, while neuroticism was negatively correlated with axial diffusivity (AD) in the left uncinate fasciculus (UF) and inferior fronto-occipital fasciculus (IFOF). An extended SEM confirmed the associations of ATR FA with anhedonia and UF/IFOF AD with neuroticism impacting on cognitive control. Our findings provide evidence for a differential impact of state and trait variables of MDD on brain connectivity and cognition. The multivariate approach shows feasibility of explaining heterogeneity within MDD and tracks this to specific brain circuits, thus adding to better understanding of heterogeneity on the biological level.
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http://dx.doi.org/10.1002/hbm.25600DOI Listing
July 2021

Clinical predictors of treatment response towards exposure therapy in virtuo in spider phobia: A machine learning and external cross-validation approach.

J Anxiety Disord 2021 Jul 10;83:102448. Epub 2021 Jul 10.

Department of Psychology, Humboldt-Universität zu Berlin, Berlin, Germany.

While being highly effective on average, exposure-based treatments are not equally effective in all patients. The a priori identification of patients with a poor prognosis may enable the application of more personalized psychotherapeutic interventions. We aimed at identifying sociodemographic and clinical pre-treatment predictors for treatment response in spider phobia (SP). N = 174 patients with SP underwent a highly standardized virtual reality exposure therapy (VRET) at two independent sites. Analyses on group-level were used to test the efficacy. We applied a state-of-the-art machine learning protocol (Random Forests) to evaluate the predictive utility of clinical and sociodemographic predictors for a priori identification of individual treatment response assessed directly after treatment and at 6-month follow-up. The reliability and generalizability of predictive models was tested via external cross-validation. Our study shows that one session of VRET is highly effective on a group-level and is among the first to reveal long-term stability of this treatment effect. Individual short-term symptom reductions could be predicted above chance, but accuracies dropped to non-significance in our between-site prediction and for predictions of long-term outcomes. With performance metrics hardly exceeding chance level and the lack of generalizability in the employed between-site replication approach, our study suggests limited clinical utility of clinical and sociodemographic predictors. Predictive models including multimodal predictors may be more promising.
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http://dx.doi.org/10.1016/j.janxdis.2021.102448DOI Listing
July 2021

Efficacy of temporally intensified exposure for anxiety disorders: A multicenter randomized clinical trial.

Depress Anxiety 2021 Jul 22. Epub 2021 Jul 22.

Institute of Clinical Psychology & Psychotherapy, Technische Universität Dresden, Dresden, Germany.

Background: The need to optimize exposure treatments for anxiety disorders may be addressed by temporally intensified exposure sessions. Effects on symptom reduction and public health benefits should be examined across different anxiety disorders with comorbid conditions.

Methods: This multicenter randomized controlled trial compared two variants of prediction error-based exposure therapy (PeEx) in various anxiety disorders (both 12 sessions + 2 booster sessions, 100 min/session): temporally intensified exposure (PeEx-I) with exposure sessions condensed to 2 weeks (n = 358) and standard nonintensified exposure (PeEx-S) with weekly exposure sessions (n = 368). Primary outcomes were anxiety symptoms (pre, post, and 6-months follow-up). Secondary outcomes were global severity (across sessions), quality of life, disability days, and comorbid depression.

Results: Both treatments resulted in substantial improvements at post (PeEx-I: d  = 1.50, PeEx-S: d  = 1.78) and follow-up (PeEx-I: d  = 2.34; PeEx-S: d  = 2.03). Both groups showed formally equivalent symptom reduction at post and follow-up. However, time until response during treatment was 32% shorter in PeEx-I (median = 68 days) than PeEx-S (108 days; TR  = 0.68). Interestingly, drop-out rates were lower during intensified exposure. PeEx-I was also superior in reducing disability days and improving quality of life at follow-up without increasing relapse.

Conclusions: Both treatment variants focusing on the transdiagnostic exposure-based violation of threat beliefs were effective in reducing symptom severity and disability in severe anxiety disorders. Temporally intensified exposure resulted in faster treatment response with substantial public health benefits and lower drop-out during the exposure phase, without higher relapse. Clinicians can expect better or at least comparable outcomes when delivering exposure in a temporally intensified manner.
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http://dx.doi.org/10.1002/da.23204DOI Listing
July 2021

PHOTONAI-A Python API for rapid machine learning model development.

PLoS One 2021 21;16(7):e0254062. Epub 2021 Jul 21.

Institute for Translational Psychiatry, University of Münster, Münster, Germany.

PHOTONAI is a high-level Python API designed to simplify and accelerate machine learning model development. It functions as a unifying framework allowing the user to easily access and combine algorithms from different toolboxes into custom algorithm sequences. It is especially designed to support the iterative model development process and automates the repetitive training, hyperparameter optimization and evaluation tasks. Importantly, the workflow ensures unbiased performance estimates while still allowing the user to fully customize the machine learning analysis. PHOTONAI extends existing solutions with a novel pipeline implementation supporting more complex data streams, feature combinations, and algorithm selection. Metrics and results can be conveniently visualized using the PHOTONAI Explorer and predictive models are shareable in a standardized format for further external validation or application. A growing add-on ecosystem allows researchers to offer data modality specific algorithms to the community and enhance machine learning in the areas of the life sciences. Its practical utility is demonstrated on an exemplary medical machine learning problem, achieving a state-of-the-art solution in few lines of code. Source code is publicly available on Github, while examples and documentation can be found at www.photon-ai.com.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0254062PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8294542PMC
July 2021

A genome-wide association study of the longitudinal course of executive functions.

Transl Psychiatry 2021 07 10;11(1):386. Epub 2021 Jul 10.

AMEOS Clinical Center Hildesheim, Hildesheim, 31135, Germany.

Executive functions are metacognitive capabilities that control and coordinate mental processes. In the transdiagnostic PsyCourse Study, comprising patients of the affective-to-psychotic spectrum and controls, we investigated the genetic basis of the time course of two core executive subfunctions: set-shifting (Trail Making Test, part B (TMT-B)) and updating (Verbal Digit Span backwards) in 1338 genotyped individuals. Time course was assessed with four measurement points, each 6 months apart. Compared to the initial assessment, executive performance improved across diagnostic groups. We performed a genome-wide association study to identify single nucleotide polymorphisms (SNPs) associated with performance change over time by testing for SNP-by-time interactions using linear mixed models. We identified nine genome-wide significant SNPs for TMT-B in strong linkage disequilibrium with each other on chromosome 5. These were associated with decreased performance on the continuous TMT-B score across time. Variant rs150547358 had the lowest P value = 7.2 × 10 with effect estimate beta = 1.16 (95% c.i.: 1.11, 1.22). Implementing data of the FOR2107 consortium (1795 individuals), we replicated these findings for the SNP rs150547358 (P value = 0.015), analyzing the difference of the two available measurement points two years apart. In the replication study, rs150547358 exhibited a similar effect estimate beta = 0.85 (95% c.i.: 0.74, 0.97). Our study demonstrates that longitudinally measured phenotypes have the potential to unmask novel associations, adding time as a dimension to the effects of genomics.
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http://dx.doi.org/10.1038/s41398-021-01510-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8272719PMC
July 2021

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

Depress Anxiety 2021 Aug 5;38(8):846-859. Epub 2021 Jul 5.

Institute for Translational Psychiatry, University of Münster, Münster, Germany.

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.
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http://dx.doi.org/10.1002/da.23191DOI Listing
August 2021

Elevated body weight modulates subcortical volume change and associated clinical response following electroconvulsive therapy.

J Psychiatry Neurosci 2021 07 5;46(4):E418-E426. Epub 2021 Jul 5.

From the Institute for Translational Psychiatry, University of Münster, Münster, Germany (Opel, Repple, Dannlowski, Redlich); Department of Psychiatry and Psychotherapy, University of Münster, Münster, Germany (Kavakbasi, Baune); the Departments of Neurology, Psychiatry, and Biobehavioral Sciences, University of California, Los Angeles, CA (Narr); the Department of Psychiatry, University of New Mexico School of Medicine, Albuquerque, NM (Abbott); the Institute of Behavioral Science, Feintein Institutes for Medical Research, Manhasset, NY (Argyelan); the Department of Psychiatry, The Zucker Hillside Hospital, Glen Oaks, NY (Argyelan); the Department of Psychiatry, University of California, Los Angeles (Espinoza); the Department of Geriatric Psychiatry, University Psychiatric Center KU Leuven, KU Leuven, Leuven, Belgium (Emsell, Vandenbulcke); the KU Leuven, Leuven Brain Institute, Department of Neurosciences, Neuropsychiatry & Geriatric Psychiatry, University Psychiatric Center KU Leuven, Belgium (Bouckaert); the Academic Center for ECT and Neurostimulation (AcCENT), University Psychiatric Center (UPC)-KU Leuven, Kortenberg, Belgium (Sienaert); the Center for Social and Affective Neuroscience, Department of Clinical and Experimental Medicine, Linköping University, Linköping, Sweden (Nordanskog); the Psychiatric Center Copenhagen (Rigshospitalet), Mental Health Services of the Capital Region of Denmark, Copenhagen, Denmark (Jorgensen); the Neurobiology Research Unit, Rigshospitalet and University of Copenhagen, Denmark (Paulson); the Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Denmark (Hanson); the Center for Magnetic Resonance, Department of Health Technology, Technical University of Denmark, Kgs, Lyngby, Denmark (Hanson); the GGZ in Geest Specialized Mental Health Care, Amsterdam, the Netherlands (Dols, Van Exel, Oudega); the Amsterdam UMC, Vrije Universiteit Amsterdam, Psychiatry, Amsterdam Neuroscience, Amsterdam, the Netherlands (Dols, van Exel, Oudega); the Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan (Takamiya, Kishimoto); the Department of Radiology, Haukeland University Hospital, Bergen, Norway (Ousdal); the Department of Biomedicine, University of Bergen, Bergen, Norway (Haavik); the Division of Psychiatry, Haukeland University Hospital, Bergen, Norway (Haavik, Hammar); the Department of Biological and Medical Psychology, University of Bergen, Norway (Hammar); the NORMENT, Department of Psychiatry, Haukeland University Hospital, Bergen, Norway (Oedegaard, Kessler); the Department of Clinical Medicine, University of Bergen, Bergen, Norway (Oedegaard, Kessler, Oltedal); the Department of Radiology, University of California, San Diego, La Jolla, California (Bartsch); the Mohn Medical Imaging and Visualization Centre, Department of Radiology, Haukeland University Hospital, Bergen, Norway (Bartsch, Oltedal); the Departments of Radiology, Neurosciences, and Psychiatry, University of California, San Diego (Dale); the Center for Multimodal Imaging and Genetics, University of California, San Diego, La Jolla, California (Dale); the Department of Psychiatry, University of Melbourne, Melbourne, Australia (Baune); the The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, VIC, Australia (Baune); and the Department of Psychology, University of Halle, Halle, Germany (Redlich).

Background: Obesity is a frequent somatic comorbidity of major depression, and it has been associated with worse clinical outcomes and brain structural abnormalities. Converging evidence suggests that electroconvulsive therapy (ECT) induces both clinical improvements and increased subcortical grey matter volume in patients with depression. However, it remains unknown whether increased body weight modulates the clinical response and structural neuroplasticity that occur with ECT.

Methods: To address this question, we conducted a longitudinal investigation of structural MRI data from the Global ECT-MRI Research Collaboration (GEMRIC) in 223 patients who were experiencing a major depressive episode (10 scanning sites). Structural MRI data were acquired before and after ECT, and we assessed change in subcortical grey matter volume using FreeSurfer and Quarc.

Results: Higher body mass index (BMI) was associated with a significantly lower increase in subcortical grey matter volume following ECT. We observed significant negative associations between BMI and change in subcortical grey matter volume, with pronounced effects in the thalamus and putamen, where obese participants showed increases in grey matter volume that were 43.3% and 49.6%, respectively, of the increases found in participants with normal weight. As well, BMI significantly moderated the association between subcortical grey matter volume change and clinical response to ECT. We observed no significant association between BMI and clinical response to ECT.

Limitations: Because only baseline BMI values were available, we were unable to study BMI changes during ECT and their potential association with clinical and grey matter volume change.

Conclusion: Future studies should take into account the relevance of body weight as a modulator of structural neuroplasticity during ECT treatment and aim to further explore the functional relevance of this novel finding.
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http://dx.doi.org/10.1503/jpn.200176DOI Listing
July 2021

Interaction of developmental factors and ordinary stressful life events on brain structure in adults.

Neuroimage Clin 2021 21;30:102683. Epub 2021 Apr 21.

Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany; Center for Mind, Brain and Behavior (CMBB), University of Marburg and Justus Liebig University Giessen, Hans-Meerwein-Str. 6, 35032 Marburg, Germany; Marburg University Hospital - UKGM, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany.

An interplay of early environmental and genetic risk factors with recent stressful life events (SLEs) in adulthood increases the risk for adverse mental health outcomes. The interaction of early risk and current SLEs on brain structure has hardly been investigated. Whole brain voxel-based morphometry analysis was performed in N = 786 (64.6% female, mean age = 33.39) healthy subjects to identify correlations of brain clusters with commonplace recent SLEs. Genetic and early environmental risk factors, operationalized as those for severe psychopathology (i.e., polygenic scores for neuroticism, childhood maltreatment, urban upbringing and paternal age) were assessed as modulators of the impact of SLEs on the brain. SLEs were negatively correlated with grey matter volume in the left medial orbitofrontal cortex (mOFC, FWE p = 0.003). This association was present for both, positive and negative, life events. Cognitive-emotional variables, i.e., neuroticism, perceived stress, trait anxiety, intelligence, and current depressive symptoms did not account for the SLE-mOFC association. Further, genetic and environmental risk factors were not correlated with grey matter volume in the left mOFC cluster and did not affect the association between SLEs and left mOFC grey matter volume. The orbitofrontal cortex has been implicated in stress-related psychopathology, particularly major depression in previous studies. We find that SLEs are associated with this area. Important early life risk factors do not interact with current SLEs on brain morphology in healthy subjects.
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http://dx.doi.org/10.1016/j.nicl.2021.102683DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8102615PMC
July 2021

Interaction of developmental factors and ordinary stressful life events on brain structure in adults.

Neuroimage Clin 2021 21;30:102683. Epub 2021 Apr 21.

Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany; Center for Mind, Brain and Behavior (CMBB), University of Marburg and Justus Liebig University Giessen, Hans-Meerwein-Str. 6, 35032 Marburg, Germany; Marburg University Hospital - UKGM, Rudolf-Bultmann-Str. 8, 35039 Marburg, Germany.

An interplay of early environmental and genetic risk factors with recent stressful life events (SLEs) in adulthood increases the risk for adverse mental health outcomes. The interaction of early risk and current SLEs on brain structure has hardly been investigated. Whole brain voxel-based morphometry analysis was performed in N = 786 (64.6% female, mean age = 33.39) healthy subjects to identify correlations of brain clusters with commonplace recent SLEs. Genetic and early environmental risk factors, operationalized as those for severe psychopathology (i.e., polygenic scores for neuroticism, childhood maltreatment, urban upbringing and paternal age) were assessed as modulators of the impact of SLEs on the brain. SLEs were negatively correlated with grey matter volume in the left medial orbitofrontal cortex (mOFC, FWE p = 0.003). This association was present for both, positive and negative, life events. Cognitive-emotional variables, i.e., neuroticism, perceived stress, trait anxiety, intelligence, and current depressive symptoms did not account for the SLE-mOFC association. Further, genetic and environmental risk factors were not correlated with grey matter volume in the left mOFC cluster and did not affect the association between SLEs and left mOFC grey matter volume. The orbitofrontal cortex has been implicated in stress-related psychopathology, particularly major depression in previous studies. We find that SLEs are associated with this area. Important early life risk factors do not interact with current SLEs on brain morphology in healthy subjects.
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http://dx.doi.org/10.1016/j.nicl.2021.102683DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8102615PMC
July 2021

Identification of transdiagnostic psychiatric disorder subtypes using unsupervised learning.

Neuropsychopharmacology 2021 Jun 14. Epub 2021 Jun 14.

Max Planck Institute of Psychiatry, Munich, Germany.

Psychiatric disorders show heterogeneous symptoms and trajectories, with current nosology not accurately reflecting their molecular etiology and the variability and symptomatic overlap within and between diagnostic classes. This heterogeneity impedes timely and targeted treatment. Our study aimed to identify psychiatric patient clusters that share clinical and genetic features and may profit from similar therapies. We used high-dimensional data clustering on deep clinical data to identify transdiagnostic groups in a discovery sample (N = 1250) of healthy controls and patients diagnosed with depression, bipolar disorder, schizophrenia, schizoaffective disorder, and other psychiatric disorders. We observed five diagnostically mixed clusters and ordered them based on severity. The least impaired cluster 0, containing most healthy controls, showed general well-being. Clusters 1-3 differed predominantly regarding levels of maltreatment, depression, daily functioning, and parental bonding. Cluster 4 contained most patients diagnosed with psychotic disorders and exhibited the highest severity in many dimensions, including medication load. Depressed patients were present in all clusters, indicating that we captured different disease stages or subtypes. We replicated all but the smallest cluster 1 in an independent sample (N = 622). Next, we analyzed genetic differences between clusters using polygenic scores (PGS) and the psychiatric family history. These genetic variables differed mainly between clusters 0 and 4 (prediction area under the receiver operating characteristic curve (AUC) = 81%; significant PGS: cross-disorder psychiatric risk, schizophrenia, and educational attainment). Our results confirm that psychiatric disorders consist of heterogeneous subtypes sharing molecular factors and symptoms. The identification of transdiagnostic clusters advances our understanding of the heterogeneity of psychiatric disorders and may support the development of personalized treatments.
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http://dx.doi.org/10.1038/s41386-021-01051-0DOI Listing
June 2021

The progression of disorder-specific brain pattern expression in schizophrenia over 9 years.

NPJ Schizophr 2021 Jun 14;7(1):32. Epub 2021 Jun 14.

Department of Psychiatry and Psychotherapy, Ludwig-Maximilian-University, Munich, Germany.

Age plays a crucial role in the performance of schizophrenia vs. controls (SZ-HC) neuroimaging-based machine learning (ML) models as the accuracy of identifying first-episode psychosis from controls is poor compared to chronic patients. Resolving whether this finding reflects longitudinal progression in a disorder-specific brain pattern or a systematic but non-disorder-specific deviation from a normal brain aging (BA) trajectory in schizophrenia would help the clinical translation of diagnostic ML models. We trained two ML models on structural MRI data: an SZ-HC model based on 70 schizophrenia patients and 74 controls and a BA model (based on 561 healthy individuals, age range = 66 years). We then investigated the two models' predictions in the naturalistic longitudinal Northern Finland Birth Cohort 1966 (NFBC1966) following 29 schizophrenia and 61 controls for nine years. The SZ-HC model's schizophrenia-specificity was further assessed by utilizing independent validation (62 schizophrenia, 95 controls) and depression samples (203 depression, 203 controls). We found better performance at the NFBC1966 follow-up (sensitivity = 75.9%, specificity = 83.6%) compared to the baseline (sensitivity = 58.6%, specificity = 86.9%). This finding resulted from progression in disorder-specific pattern expression in schizophrenia and was not explained by concomitant acceleration of brain aging. The disorder-specific pattern's progression reflected longitudinal changes in cognition, outcomes, and local brain changes, while BA captured treatment-related and global brain alterations. The SZ-HC model was also generalizable to independent schizophrenia validation samples but classified depression as control subjects. Our research underlines the importance of taking account of longitudinal progression in a disorder-specific pattern in schizophrenia when developing ML classifiers for different age groups.
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http://dx.doi.org/10.1038/s41537-021-00157-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8203625PMC
June 2021

The course of disease in major depressive disorder is associated with altered activity of the limbic system during negative emotion processing.

Biol Psychiatry Cogn Neurosci Neuroimaging 2021 Jun 5. Epub 2021 Jun 5.

Institute for Translational Psychiatry, University of Münster, Münster, Germany. Electronic address:

Background: Brain functional alterations during emotion processing in patients with major depressive disorder (MDD) compared to healthy controls (HC) are frequently reported. However, evidence for functional correlates of emotion processing with regard to MDD trajectories is scarce. The present study investigated the role of lifetime disease course for limbic brain activation during negative emotional face processing in patients with MDD.

Methods: In a large sample of MDD patients (n=333; 58.55% female) and HC (n=333; 60.06% female), brain activation was investigated during a negative emotional face processing task within a cross-sectional design. Group differences between HC and MDD were analysed. Previous disease course, characterized by two components, namely Hospitalization and Duration of Illness, was regressed on brain activation of the amygdala, (para-)hippocampus and insula in MDD patients.

Results: MDD patients showed increased activation in the amygdala, insula and hippocampus compared to HC (all p<.045). The Hospitalization component showed negative associations with brain activation in the bilateral insula (right: p=.026, left: p=.019) and (para-)hippocampus (right: p=.038, left: p=.031). No significant associations were found for the Duration of Illness component (all p>.057).

Conclusions: This study investigated negative emotion processing in a large sample of MDD patients and HC. Our results confirm limbic hyperactivation in patients with MDD during negative emotion processing, however this hyperactivation may resolve with a more severe lifetime disease course in the insula and (para-)hippocampus - brain regions involved in emotion processing and regulation. These findings need further replication in longitudinal studies.
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http://dx.doi.org/10.1016/j.bpsc.2021.05.008DOI Listing
June 2021

The Neuroanatomy of Transgender Identity: Mega-Analytic Findings From the ENIGMA Transgender Persons Working Group.

J Sex Med 2021 06 22;18(6):1122-1129. Epub 2021 May 22.

Institute for Translational Psychiatry, University of Muenster, Muenster, Germany.

Background: In contrast to cisgender persons, transgender persons identify with a different gender than the one assigned at birth. Although research on the underlying neurobiology of transgender persons has been accumulating over the years, neuroimaging studies in this relatively rare population are often based on very small samples resulting in discrepant findings.

Aim: To examine the neurobiology of transgender persons in a large sample.

Methods: Using a mega-analytic approach, structural MRI data of 803 non-hormonally treated transgender men (TM, n = 214, female assigned at birth with male gender identity), transgender women (TW, n = 172, male assigned at birth with female gender identity), cisgender men (CM, n = 221, male assigned at birth with male gender identity) and cisgender women (CW, n = 196, female assigned at birth with female gender identity) were analyzed.

Outcomes: Structural brain measures, including grey matter volume, cortical surface area, and cortical thickness.

Results: Transgender persons differed significantly from cisgender persons with respect to (sub)cortical brain volumes and surface area, but not cortical thickness. Contrasting the 4 groups (TM, TW, CM, and CW), we observed a variety of patterns that not only depended on the direction of gender identity (towards male or towards female) but also on the brain measure as well as the brain region examined.

Clinical Translation: The outcomes of this large-scale study may provide a normative framework that may become useful in clinical studies.

Strengths And Limitations: While this is the largest study of MRI data in transgender persons to date, the analyses conducted were governed (and restricted) by the type of data collected across all participating sites.

Conclusion: Rather than being merely shifted towards either end of the male-female spectrum, transgender persons seem to present with their own unique brain phenotype. Mueller SC, Guillamon A, Zubiaurre-Elorza L, et al. The Neuroanatomy of Transgender Identity: Mega-Analytic Findings From the ENIGMA Transgender Persons Working Group. J Sex Med 2021;18:1122-1129.
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http://dx.doi.org/10.1016/j.jsxm.2021.03.079DOI Listing
June 2021

Interpreting weights of multimodal machine learning models-problems and pitfalls.

Neuropsychopharmacology 2021 May 20. Epub 2021 May 20.

Institute for Translational Psychiatry, University of Münster, Münster, Germany.

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http://dx.doi.org/10.1038/s41386-021-01030-5DOI Listing
May 2021

Genome-wide association study of more than 40,000 bipolar disorder cases provides new insights into the underlying biology.

Nat Genet 2021 06 17;53(6):817-829. Epub 2021 May 17.

Department of Neuroscience, Istituto Di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy.

Bipolar disorder is a heritable mental illness with complex etiology. We performed a genome-wide association study of 41,917 bipolar disorder cases and 371,549 controls of European ancestry, which identified 64 associated genomic loci. Bipolar disorder risk alleles were enriched in genes in synaptic signaling pathways and brain-expressed genes, particularly those with high specificity of expression in neurons of the prefrontal cortex and hippocampus. Significant signal enrichment was found in genes encoding targets of antipsychotics, calcium channel blockers, antiepileptics and anesthetics. Integrating expression quantitative trait locus data implicated 15 genes robustly linked to bipolar disorder via gene expression, encoding druggable targets such as HTR6, MCHR1, DCLK3 and FURIN. Analyses of bipolar disorder subtypes indicated high but imperfect genetic correlation between bipolar disorder type I and II and identified additional associated loci. Together, these results advance our understanding of the biological etiology of bipolar disorder, identify novel therapeutic leads and prioritize genes for functional follow-up studies.
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http://dx.doi.org/10.1038/s41588-021-00857-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8192451PMC
June 2021

From multivariate methods to an AI ecosystem.

Mol Psychiatry 2021 May 12. Epub 2021 May 12.

Department of Psychiatry, University of Muenster, Münster, Germany.

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http://dx.doi.org/10.1038/s41380-021-01116-yDOI Listing
May 2021

Systematic misestimation of machine learning performance in neuroimaging studies of depression.

Neuropsychopharmacology 2021 07 6;46(8):1510-1517. Epub 2021 May 6.

Department of Psychiatry, University of Münster, Münster, Germany.

We currently observe a disconcerting phenomenon in machine learning studies in psychiatry: While we would expect larger samples to yield better results due to the availability of more data, larger machine learning studies consistently show much weaker performance than the numerous small-scale studies. Here, we systematically investigated this effect focusing on one of the most heavily studied questions in the field, namely the classification of patients suffering from Major Depressive Disorder (MDD) and healthy controls based on neuroimaging data. Drawing upon structural MRI data from a balanced sample of N = 1868 MDD patients and healthy controls from our recent international Predictive Analytics Competition (PAC), we first trained and tested a classification model on the full dataset which yielded an accuracy of 61%. Next, we mimicked the process by which researchers would draw samples of various sizes (N = 4 to N = 150) from the population and showed a strong risk of misestimation. Specifically, for small sample sizes (N = 20), we observe accuracies of up to 95%. For medium sample sizes (N = 100) accuracies up to 75% were found. Importantly, further investigation showed that sufficiently large test sets effectively protect against performance misestimation whereas larger datasets per se do not. While these results question the validity of a substantial part of the current literature, we outline the relatively low-cost remedy of larger test sets, which is readily available in most cases.
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http://dx.doi.org/10.1038/s41386-021-01020-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8209109PMC
July 2021

Dendritic Cells: Neglected Modulators of Peripheral Immune Responses and Neuroinflammation in Mood Disorders?

Cells 2021 Apr 19;10(4). Epub 2021 Apr 19.

Department of Mental Health, University of Münster, 48149 Münster, Germany.

Affective disorders (AD) including major depressive disorder (MDD) and bipolar disorder (BD) are common mood disorders associated with increased disability and poor health outcomes. Altered immune responses characterized by increased serum levels of pro-inflammatory cytokines and neuroinflammation are common findings in patients with AD and in corresponding animal models. Dendritic cells (DCs) represent a heterogeneous population of myeloid cells that orchestrate innate and adaptive immune responses and self-tolerance. Upon sensing exogenous and endogenous danger signals, mature DCs secrete proinflammatory factors, acquire migratory and antigen presenting capacities and thus contribute to neuroinflammation in trauma, autoimmunity, and neurodegenerative diseases. However, little is known about the involvement of DCs in the pathogenesis of AD. In this review, we summarize the current knowledge on DCs in peripheral immune responses and neuroinflammation in MDD and BD. In addition, we consider the impact of DCs on neuroinflammation and behavior in animal models of AD. Finally, we will discuss therapeutic perspectives targeting DCs and their effector molecules in mood disorders.
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http://dx.doi.org/10.3390/cells10040941DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8072712PMC
April 2021

Social support and hippocampal volume are negatively associated in adults with previous experience of childhood maltreatment.

J Psychiatry Neurosci 2021 Apr 27;46(3):E328-E336. Epub 2021 Apr 27.

From the Department of Psychiatry, University of Münster, Münster, Germany (Förster, Danzer, Redlich, Opel, Grotegerd, Leehr, Dohm, Enneking, Meinert, Goltermann, Lemke, Waltemate, Thiel, Behnert, Hahn, Repple, Dannlowski); the Clinical Psychology and Behavioral Neuroscience, Faculty of Psychology, TU Dresden, Dresden, Germany (Förster); the Department of Clinical Psychology, University of Halle, Halle, Germany (Redlich); the Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany (Brosch, Stein, Meller, Ringwald, Schmitt, Steinsträter, Jansen, Krug, Nenadic, Kircher); the Core-Unit Brain Imaging, Faculty of Medicine, University of Marburg, Marburg, Germany (Jansen); the Department of Psychiatry, University of Bonn, Bonn, Germany (Krug); and the University Clinic for Clinical Radiology, University of Münster, Münster, Germany (Kugel, Heindel).

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.
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http://dx.doi.org/10.1503/jpn.200162DOI Listing
April 2021

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

Mol Psychiatry 2021 Apr 16. Epub 2021 Apr 16.

Unit for Psychosomatics / CL Outpatient Clinic for Adults, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway.

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.
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http://dx.doi.org/10.1038/s41380-021-01098-xDOI Listing
April 2021

Psychopathological Syndromes Across Affective and Psychotic Disorders Correlate With Gray Matter Volumes.

Schizophr Bull 2021 Apr 16. Epub 2021 Apr 16.

Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany.

Introduction: More than a century of research on the neurobiological underpinnings of major psychiatric disorders (major depressive disorder [MDD], bipolar disorder [BD], schizophrenia [SZ], and schizoaffective disorder [SZA]) has been unable to identify diagnostic markers. An alternative approach is to study dimensional psychopathological syndromes that cut across categorical diagnoses. The aim of the current study was to identify gray matter volume (GMV) correlates of transdiagnostic symptom dimensions.

Methods: We tested the association of 5 psychopathological factors with GMV using multiple regression models in a sample of N = 1069 patients meeting Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) criteria for MDD (n = 818), BD (n = 132), and SZ/SZA (n = 119). T1-weighted brain images were acquired with 3-Tesla magnetic resonance imaging and preprocessed with CAT12. Interactions analyses (diagnosis × psychopathological factor) were performed to test whether local GMV associations were driven by DSM-IV diagnosis. We further tested syndrome specific regions of interest (ROIs).

Results: Whole brain analysis showed a significant negative association of the positive formal thought disorder factor with GMV in the right middle frontal gyrus, the paranoid-hallucinatory syndrome in the right fusiform, and the left middle frontal gyri. ROI analyses further showed additional negative associations, including the negative syndrome with bilateral frontal opercula, positive formal thought disorder with the left amygdala-hippocampus complex, and the paranoid-hallucinatory syndrome with the left angular gyrus. None of the GMV associations interacted with DSM-IV diagnosis.

Conclusions: We found associations between psychopathological syndromes and regional GMV independent of diagnosis. Our findings open a new avenue for neurobiological research across disorders, using syndrome-based approaches rather than categorical diagnoses.
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http://dx.doi.org/10.1093/schbul/sbab037DOI Listing
April 2021

DLPFC volume is a neural correlate of resilience in healthy high-risk individuals with both childhood maltreatment and familial risk for depression.

Psychol Med 2021 Apr 16:1-7. Epub 2021 Apr 16.

Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg and University Hospital Marburg, UKGM, Rudolf-Bultmann-Str. 8, 35039Marburg, Germany.

Background: Two prominent risk factors for major depressive disorder (MDD) are childhood maltreatment (CM) and familial risk for MDD. Despite having these risk factors, there are individuals who maintain mental health, i.e. are resilient, whereas others develop MDD. It is unclear which brain morphological alterations are associated with this kind of resilience. Interaction analyses of risk and diagnosis status are needed that can account for complex adaptation processes, to identify neural correlates of resilience.

Methods: We analyzed brain structural data (3T magnetic resonance imaging) by means of voxel-based morphometry (CAT12 toolbox), using a 2 × 2 design, comparing four groups (N = 804) that differed in diagnosis (healthy v. MDD) and risk profiles (low-risk, i.e. absence of CM and familial risk v. high-risk, i.e. presence of both CM and familial risk). Using regions of interest (ROIs) from the literature, we conducted an interaction analysis of risk and diagnosis status.

Results: Volume in the left middle frontal gyrus (MFG), part of the dorsolateral prefrontal cortex (DLPFC), was significantly higher in healthy high-risk individuals. There were no significant results for the bilateral superior frontal gyri, frontal poles, pars orbitalis of the inferior frontal gyri, and the right MFG.

Conclusions: The healthy high-risk group had significantly higher volumes in the left DLPFC compared to all other groups. The DLPFC is implicated in cognitive and emotional processes, and higher volume in this area might aid high-risk individuals in adaptive coping in order to maintain mental health. This increased volume might therefore constitute a neural correlate of resilience to MDD in high risk.
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http://dx.doi.org/10.1017/S0033291721001094DOI Listing
April 2021

Effects of polygenic risk for major mental disorders and cross-disorder on cortical complexity.

Psychol Med 2021 Apr 8:1-12. Epub 2021 Apr 8.

Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Rudolf-Bultmann-Str. 8, 35039Marburg, Germany.

Background: MRI-derived cortical folding measures are an indicator of largely genetically driven early developmental processes. However, the effects of genetic risk for major mental disorders on early brain development are not well understood.

Methods: We extracted cortical complexity values from structural MRI data of 580 healthy participants using the CAT12 toolbox. Polygenic risk scores (PRS) for schizophrenia, bipolar disorder, major depression, and cross-disorder (incorporating cumulative genetic risk for depression, schizophrenia, bipolar disorder, autism spectrum disorder, and attention-deficit hyperactivity disorder) were computed and used in separate general linear models with cortical complexity as the regressand. In brain regions that showed a significant association between polygenic risk for mental disorders and cortical complexity, volume of interest (VOI)/region of interest (ROI) analyses were conducted to investigate additional changes in their volume and cortical thickness.

Results: The PRS for depression was associated with cortical complexity in the right orbitofrontal cortex (right hemisphere: p = 0.006). A subsequent VOI/ROI analysis showed no association between polygenic risk for depression and either grey matter volume or cortical thickness. We found no associations between cortical complexity and polygenic risk for either schizophrenia, bipolar disorder or psychiatric cross-disorder when correcting for multiple testing.

Conclusions: Changes in cortical complexity associated with polygenic risk for depression might facilitate well-established volume changes in orbitofrontal cortices in depression. Despite the absence of psychopathology, changed cortical complexity that parallels polygenic risk for depression might also change reward systems, which are also structurally affected in patients with depressive syndrome.
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http://dx.doi.org/10.1017/S0033291721001082DOI Listing
April 2021

Genetic factors influencing a neurobiological substrate for psychiatric disorders.

Transl Psychiatry 2021 03 29;11(1):192. Epub 2021 Mar 29.

Institute of Neuroscience and Medicine (INM-1, INM-7), Research Centre Jülich, Jülich, Germany.

A retrospective meta-analysis of magnetic resonance imaging voxel-based morphometry studies proposed that reduced gray matter volumes in the dorsal anterior cingulate and the left and right anterior insular cortex-areas that constitute hub nodes of the salience network-represent a common substrate for major psychiatric disorders. Here, we investigated the hypothesis that the common substrate serves as an intermediate phenotype to detect genetic risk variants relevant for psychiatric disease. To this end, after a data reduction step, we conducted genome-wide association studies of a combined common substrate measure in four population-based cohorts (n = 2271), followed by meta-analysis and replication in a fifth cohort (n = 865). After correction for covariates, the heritability of the common substrate was estimated at 0.50 (standard error 0.18). The top single-nucleotide polymorphism (SNP) rs17076061 was associated with the common substrate at genome-wide significance and replicated, explaining 1.2% of the common substrate variance. This SNP mapped to a locus on chromosome 5q35.2 harboring genes involved in neuronal development and regeneration. In follow-up analyses, rs17076061 was not robustly associated with psychiatric disease, and no overlap was found between the broader genetic architecture of the common substrate and genetic risk for major depressive disorder, bipolar disorder, or schizophrenia. In conclusion, our study identified that common genetic variation indeed influences the common substrate, but that these variants do not directly translate to increased disease risk. Future studies should investigate gene-by-environment interactions and employ functional imaging to understand how salience network structure translates to psychiatric disorder risk.
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http://dx.doi.org/10.1038/s41398-021-01317-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8007575PMC
March 2021

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

Biol Psychiatry Cogn Neurosci Neuroimaging 2021 Mar 5. Epub 2021 Mar 5.

Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany.

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.
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http://dx.doi.org/10.1016/j.bpsc.2021.02.010DOI Listing
March 2021

Apolipoprotein E homozygous ε4 allele status: Effects on cortical structure and white matter integrity in a young to mid-age sample.

Eur Neuropsychopharmacol 2021 May 27;46:93-104. Epub 2021 Feb 27.

Department of Psychiatry, University of Münster, Münster, Germany. Electronic address:

Apolipoprotein E (APOE) genotype is the strongest single gene predictor of Alzheimer's disease (AD) and has been frequently associated with AD-related brain structural alterations before the onset of dementia. While previous research has primarily focused on hippocampal morphometry in relation to APOE, sporadic recent findings have questioned the specificity of the hippocampus and instead suggested more global effects on the brain. With the present study we aimed to investigate associations between homozygous APOE ε4 status and cortical gray matter structure as well as white matter microstructure. In our study, we contrasted n = 31 homozygous APOE ε4 carriers (age=34.47 years, including a subsample of n = 12 subjects with depression) with a demographically matched sample without an ε4 allele (resulting total sample: N = 62). Morphometry analyses included a) Freesurfer based cortical segmentations of thickness and surface area measures and b) tract based spatial statistics of DTI measures. We found pronounced and widespread reductions in cortical surface area of ε4 homozygotes in 57 out of 68 cortical brain regions. In contrast, no differences in cortical thickness were observed. Furthermore, APOE ε4 homozygous carriers showed significantly lower fractional anisotropy in the corpus callosum, the right internal and external capsule, the left corona radiata and the right fornix. The present findings support a global rather than regionally specific effect of homozygous APOE ε4 allele status on cortical surface area and white matter microstructure. Future studies should aim to delineate the clinical implications of these findings.
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http://dx.doi.org/10.1016/j.euroneuro.2021.02.006DOI Listing
May 2021
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