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1. Smartphone-Based Self-Reports of Depressive Symptoms Using the Remote Monitoring Application in Psychiatry (ReMAP): Interformat Validation Study

Author

Goltermann, Janik, Emden, Daniel, Leehr, Elisabeth Johanna, Dohm, Katharina, Redlich, Ronny, Dannlowski, Udo, Hahn, Tim, and Opel, Nils

Subjects
Psychology, BF1-990
Abstract

BackgroundSmartphone-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. ObjectiveThe 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). MethodsThe 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). ResultsWe found overall high comparability between smartphone-based and non–smartphone-based BDI scores (intraclass correlation coefficient=0.921; P

Published
2021
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2. The interplay between polygenic score for tumor necrosis factor-α, brain structural connectivity, and processing speed in major depression

Author

Flinkenflügel, Kira, Gruber, Marius, Meinert, Susanne, Thiel, Katharina, Winter, Alexandra, Goltermann, Janik, Usemann, Paula, Brosch, Katharina, Stein, Frederike, Thomas-Odenthal, Florian, Wroblewski, Adrian, Pfarr, Julia-Katharina, David, Friederike S., Beins, Eva C., Grotegerd, Dominik, Hahn, Tim, Leehr, Elisabeth J., Dohm, Katharina, Bauer, Jochen, Forstner, Andreas J., Nöthen, Markus M., Jamalabadi, Hamidreza, Straube, Benjamin, Alexander, Nina, Jansen, Andreas, Witt, Stephanie H., Rietschel, Marcella, Nenadić, Igor, van den Heuvel, Martijn P., Kircher, Tilo, Repple, Jonathan, and Dannlowski, Udo

Published
2024
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4. Neural foundation of the diathesis-stress model: longitudinal gray matter volume changes in response to stressful life events in major depressive disorder and healthy controls

Author

Thomas-Odenthal, Florian, Ringwald, Kai, Teutenberg, Lea, Stein, Frederike, Alexander, Nina, Bonnekoh, Linda M., Brosch, Katharina, Dohm, Katharina, Flinkenflügel, Kira, Grotegerd, Dominik, Hahn, Tim, Jansen, Andreas, Leehr, Elisabeth J., Meinert, Susanne, Pfarr, Julia-Katharina, Renz, Harald, Schürmeyer, Navid, Stief, Thomas, Straube, Benjamin, Thiel, Katharina, Usemann, Paula, Winter, Alexandra, Krug, Axel, Nenadić, Igor, Dannlowski, Udo, and Kircher, Tilo

Published
2024
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6. White and gray matter alterations in bipolar I and bipolar II disorder subtypes compared with healthy controls – exploring associations with disease course and polygenic risk

Author

Thiel, Katharina, Lemke, Hannah, Winter, Alexandra, Flinkenflügel, Kira, Waltemate, Lena, Bonnekoh, Linda, Grotegerd, Dominik, Dohm, Katharina, Hahn, Tim, Förster, Katharina, Kanske, Philipp, Repple, Jonathan, Opel, Nils, Redlich, Ronny, David, Friederike, Forstner, Andreas J., Stein, Frederike, Brosch, Katharina, Thomas-Odenthal, Florian, Usemann, Paula, Teutenberg, Lea, Straube, Benjamin, Alexander, Nina, Jamalabadi, Hamidreza, Jansen, Andreas, Witt, Stephanie H., Andlauer, Till F. M., Pfennig, Andrea, Bauer, Michael, Nenadić, Igor, Kircher, Tilo, Meinert, Susanne, and Dannlowski, Udo

Published
2024
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7. Volume of subcortical brain regions in social anxiety disorder: mega-analytic results from 37 samples in the ENIGMA-Anxiety Working Group.

Author

Groenewold, Nynke, Bas-Hoogendam, Janna, Amod, Alyssa, Laansma, Max, Van Velzen, Laura, Aghajani, Moji, Hilbert, Kevin, Oh, Hyuntaek, Salas, Ramiro, Jackowski, Andrea, Pan, Pedro, Salum, Giovanni, Blair, James, Blair, Karina, Hirsch, Joy, Pantazatos, Spiro, Schneier, Franklin, Talati, Ardesheer, Roelofs, Karin, Volman, Inge, Blanco-Hinojo, Laura, Cardoner, Narcís, Pujol, Jesus, Beesdo-Baum, Katja, Ching, Christopher, Thomopoulos, Sophia, Jansen, Andreas, Kircher, Tilo, Krug, Axel, Nenadić, Igor, Stein, Frederike, Dannlowski, Udo, Grotegerd, Dominik, Lemke, Hannah, Meinert, Susanne, Winter, Alexandra, Erb, Michael, Kreifelts, Benjamin, Gong, Qiyong, Lui, Su, Zhu, Fei, Mwangi, Benson, Soares, Jair, Wu, Mon-Ju, Bayram, Ali, Canli, Mesut, Tükel, Raşit, Westenberg, P, Heeren, Alexandre, Cremers, Henk, Hofmann, David, Straube, Thomas, Doruyter, Alexander, Lochner, Christine, Peterburs, Jutta, Van Tol, Marie-José, Gur, Raquel, Kaczkurkin, Antonia, Larsen, Bart, Satterthwaite, Theodore, Filippi, Courtney, Gold, Andrea, Harrewijn, Anita, Zugman, André, Bülow, Robin, Grabe, Hans, Völzke, Henry, Wittfeld, Katharina, Böhnlein, Joscha, Dohm, Katharina, Kugel, Harald, Schrammen, Elisabeth, Zwanzger, Peter, Leehr, Elisabeth, Sindermann, Lisa, Ball, Tali, Fonzo, Gregory, Paulus, Martin, Stein, Murray, Klumpp, Heide, Phan, K, Furmark, Tomas, Månsson, Kristoffer, Manzouri, Amirhossein, Avery, Suzanne, Blackford, Jennifer, Clauss, Jacqueline, Feola, Brandee, Harper, Jennifer, Sylvester, Chad, Lueken, Ulrike, Veltman, Dick, Winkler, Anderson, Jahanshad, Neda, Pine, Daniel, Thompson, Paul, Stein, Dan, Van der Wee, Nic, and Simmons, Alan

Subjects
Adult, Adolescent, Humans, Phobia, Social, Magnetic Resonance Imaging, Brain, Anxiety, Neuroimaging
Abstract

There is limited convergence in neuroimaging investigations into volumes of subcortical brain regions in social anxiety disorder (SAD). The inconsistent findings may arise from variations in methodological approaches across studies, including sample selection based on age and clinical characteristics. The ENIGMA-Anxiety Working Group initiated a global mega-analysis to determine whether differences in subcortical volumes can be detected in adults and adolescents with SAD relative to healthy controls. Volumetric data from 37 international samples with 1115 SAD patients and 2775 controls were obtained from ENIGMA-standardized protocols for image segmentation and quality assurance. Linear mixed-effects analyses were adjusted for comparisons across seven subcortical regions in each hemisphere using family-wise error (FWE)-correction. Mixed-effects d effect sizes were calculated. In the full sample, SAD patients showed smaller bilateral putamen volume than controls (left: d = -0.077, pFWE = 0.037; right: d = -0.104, pFWE = 0.001), and a significant interaction between SAD and age was found for the left putamen (r = -0.034, pFWE = 0.045). Smaller bilateral putamen volumes (left: d = -0.141, pFWE

Published
2023

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

Author

Winter, Alexandra, Gruber, Marius, Thiel, Katharina, Flinkenflügel, Kira, Meinert, Susanne, Goltermann, Janik, Winter, Nils R., Borgers, Tiana, Stein, Frederike, Jansen, Andreas, Brosch, Katharina, Wroblewski, Adrian, Thomas-Odenthal, Florian, Usemann, Paula, Straube, Benjamin, Alexander, Nina, Jamalabadi, Hamidreza, Nenadić, Igor, Bonnekoh, Linda M., Dohm, Katharina, Leehr, Elisabeth J., Opel, Nils, Grotegerd, Dominik, Hahn, Tim, van den Heuvel, Martijn P., Kircher, Tilo, Repple, Jonathan, and Dannlowski, Udo

Published
2023
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9. More Alike than Different: Quantifying Deviations of Brain Structure and Function in Major Depressive Disorder across Neuroimaging Modalities

Author

Winter, Nils R., Leenings, Ramona, Ernsting, Jan, Sarink, Kelvin, Fisch, Lukas, Emden, Daniel, Blanke, Julian, Goltermann, Janik, Opel, Nils, Barkhau, Carlotta, Meinert, Susanne, Dohm, Katharina, Repple, Jonathan, Mauritz, Marco, Gruber, Marius, Leehr, Elisabeth J., Grotegerd, Dominik, Redlich, Ronny, Jansen, Andreas, Nenadic, Igor, Nöthen, Markus, Forstner, Andreas, Rietschel, Marcella, Groß, Joachim, Bauer, Jochen, Heindel, Walter, Andlauer, Till, Eickhoff, Simon, Kircher, Tilo, Dannlowski, Udo, and Hahn, Tim

Subjects
Quantitative Biology - Neurons and Cognition, Quantitative Biology - Quantitative Methods
Abstract

Introduction: Identifying neurobiological differences between patients suffering from Major Depressive Disorder (MDD) and healthy individuals has been a mainstay of clinical neuroscience for decades. However, recent meta- and mega-analyses have raised concerns regarding the replicability and clinical relevance of brain alterations in depression. Methods: Here, we systematically investigate healthy controls and MDD patients across a comprehensive range of modalities including structural magnetic resonance imaging (MRI), diffusion tensor imaging, functional task-based and resting-state MRI under near-ideal conditions. To this end, we quantify the upper bounds of univariate effect sizes, predictive utility, and distributional dissimilarity in a fully harmonized cohort of N=1,809 participants. We compare the results to an MDD polygenic risk score (PRS) and environmental variables. Results: The upper bound of the effect sizes range from partial eta squared = .004 to .017, distributions overlap between 89% and 95%, with classification accuracies ranging between 54% and 55% across neuroimaging modalities. This pattern remains virtually unchanged when considering only acutely or chronically depressed patients. Differences are comparable to those found for PRS, but substantially smaller than for environmental variables. Discussion: We provide a large-scale, multimodal analysis of univariate biological differences between MDD patients and controls and show that even under near-ideal conditions and for maximum biological differences, deviations are extremely small and similarity dominates. We sketch an agenda for a new focus of future research in biological psychiatry facilitating quantitative, theory-driven research, an emphasis on computational psychiatry and multivariate machine learning approaches, as well as the utilization of ecologically valid phenotyping., Comment: 12 pages, 3 figures

Published
2021

10. Towards a Network Control Theory of Electroconvulsive Therapy Response

Author

Hahn, Tim, Jamalabadi, Hamidreza, Nozari, Erfan, Winter, Nils R., Ernsting, Jan, Gruber, Marius, Mauritz, Marco J., Grumbach, Pascal, Fisch, Lukas, Leenings, Ramona, Sarink, Kelvin, Blanke, Julian, Vennekate, Leon Kleine, Emden, Daniel, Opel, Nils, Grotegerd, Dominik, Enneking, Verena, Meinert, Susanne, Borgers, Tiana, Klug, Melissa, Leehr, Elisabeth J., Dohm, Katharina, Heindel, Walter, Gross, Joachim, Dannlowski, Udo, Redlich, Ronny, and Repple, Jonathan

Subjects
Electrical Engineering and Systems Science - Systems and Control, Quantitative Biology - Neurons and Cognition
Abstract

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

Published
2021

11. Virtual Ontogeny of Cortical Growth Preceding Mental Illness

Author

Patel, Yash, Shin, Jean, Abé, Christoph, Agartz, Ingrid, Alloza, Clara, Alnæs, Dag, Ambrogi, Sonia, Antonucci, Linda A, Arango, Celso, Arolt, Volker, Auzias, Guillaume, Ayesa-Arriola, Rosa, Banaj, Nerisa, Banaschewski, Tobias, Bandeira, Cibele, Başgöze, Zeynep, Cupertino, Renata Basso, Bau, Claiton HD, Bauer, Jochen, Baumeister, Sarah, Bernardoni, Fabio, Bertolino, Alessandro, Bonnin, Caterina Del Mar, Brandeis, Daniel, Brem, Silvia, Bruggemann, Jason, Bülow, Robin, Bustillo, Juan R, Calderoni, Sara, Calvo, Rosa, Canales-Rodríguez, Erick J, Cannon, Dara M, Carmona, Susanna, Carr, Vaughan J, Catts, Stanley V, Chenji, Sneha, Chew, Qian Hui, Coghill, David, Connolly, Colm G, Conzelmann, Annette, Craven, Alexander R, Crespo-Facorro, Benedicto, Cullen, Kathryn, Dahl, Andreas, Dannlowski, Udo, Davey, Christopher G, Deruelle, Christine, Díaz-Caneja, Covadonga M, Dohm, Katharina, Ehrlich, Stefan, Epstein, Jeffery, Erwin-Grabner, Tracy, Eyler, Lisa T, Fedor, Jennifer, Fitzgerald, Jacqueline, Foran, William, Ford, Judith M, Fortea, Lydia, Fuentes-Claramonte, Paola, Fullerton, Janice, Furlong, Lisa, Gallagher, Louise, Gao, Bingchen, Gao, Si, Goikolea, Jose M, Gotlib, Ian, Goya-Maldonado, Roberto, Grabe, Hans J, Green, Melissa, Grevet, Eugenio H, Groenewold, Nynke A, Grotegerd, Dominik, Gruber, Oliver, Haavik, Jan, Hahn, Tim, Harrison, Ben J, Heindel, Walter, Henskens, Frans, Heslenfeld, Dirk J, Hilland, Eva, Hoekstra, Pieter J, Hohmann, Sarah, Holz, Nathalie, Howells, Fleur M, Ipser, Jonathan C, Jahanshad, Neda, Jakobi, Babette, Jansen, Andreas, Janssen, Joost, Jonassen, Rune, Kaiser, Anna, Kaleda, Vasiliy, Karantonis, James, King, Joseph A, Kircher, Tilo, Kochunov, Peter, Koopowitz, Sheri-Michelle, Landén, Mikael, Landrø, Nils Inge, and Lawrie, Stephen

Subjects
Biological Psychology, Biomedical and Clinical Sciences, Psychology, Neurosciences, Genetics, Mental Health, Serious Mental Illness, Mental Illness, Women's Health, Brain Disorders, Preterm, Low Birth Weight and Health of the Newborn, Pregnancy, Pediatric, Perinatal Period - Conditions Originating in Perinatal Period, Behavioral and Social Science, Prevention, Schizophrenia, 2.1 Biological and endogenous factors, 2.3 Psychological, social and economic factors, Neurological, Reproductive health and childbirth, Mental health, Good Health and Well Being, Attention Deficit Disorder with Hyperactivity, Autism Spectrum Disorder, Bipolar Disorder, Cerebral Cortex, Child, Depressive Disorder, Major, Female, Humans, Infant, Newborn, Magnetic Resonance Imaging, Premature Birth, Cortical growth, Cortical surface area, Mental illness, Neurodevelopment, Neurogenesis, Psychiatric disorders, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry, Biological sciences, Biomedical and clinical sciences
Abstract

BackgroundMorphology of the human cerebral cortex differs across psychiatric disorders, with neurobiology and developmental origins mostly undetermined. Deviations in the tangential growth of the cerebral cortex during pre/perinatal periods may be reflected in individual variations in cortical surface area later in life.MethodsInterregional profiles of group differences in surface area between cases and controls were generated using T1-weighted magnetic resonance imaging from 27,359 individuals including those with attention-deficit/hyperactivity disorder, autism spectrum disorder, bipolar disorder, major depressive disorder, schizophrenia, and high general psychopathology (through the Child Behavior Checklist). Similarity of interregional profiles of group differences in surface area and prenatal cell-specific gene expression was assessed.ResultsAcross the 11 cortical regions, group differences in cortical area for attention-deficit/hyperactivity disorder, schizophrenia, and Child Behavior Checklist were dominant in multimodal association cortices. The same interregional profiles were also associated with interregional profiles of (prenatal) gene expression specific to proliferative cells, namely radial glia and intermediate progenitor cells (greater expression, larger difference), as well as differentiated cells, namely excitatory neurons and endothelial and mural cells (greater expression, smaller difference). Finally, these cell types were implicated in known pre/perinatal risk factors for psychosis. Genes coexpressed with radial glia were enriched with genes implicated in congenital abnormalities, birth weight, hypoxia, and starvation. Genes coexpressed with endothelial and mural genes were enriched with genes associated with maternal hypertension and preterm birth.ConclusionsOur findings support a neurodevelopmental model of vulnerability to mental illness whereby prenatal risk factors acting through cell-specific processes lead to deviations from typical brain development during pregnancy.

Published
2022

12. Association of hospitalization with structural brain alterations in patients with affective disorders over nine years

Author

Förster, Katharina, Grotegerd, Dominik, Dohm, Katharina, Lemke, Hannah, Enneking, Verena, Meinert, Susanne, Redlich, Ronny, Heindel, Walter, Bauer, Jochen, Kugel, Harald, Suslow, Thomas, Ohrmann, Patricia, Carballedo, Angela, O’Keane, Veronica, Fagan, Andrew, Doolin, Kelly, McCarthy, Hazel, Kanske, Philipp, Frodl, Thomas, and Dannlowski, Udo

Published
2023
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13. Genetic variants associated with longitudinal changes in brain structure across the lifespan

Author

Brouwer, Rachel M, Klein, Marieke, Grasby, Katrina L, Schnack, Hugo G, Jahanshad, Neda, Teeuw, Jalmar, Thomopoulos, Sophia I, Sprooten, Emma, Franz, Carol E, Gogtay, Nitin, Kremen, William S, Panizzon, Matthew S, Olde Loohuis, Loes M, Whelan, Christopher D, Aghajani, Moji, Alloza, Clara, Alnæs, Dag, Artiges, Eric, Ayesa-Arriola, Rosa, Barker, Gareth J, Bastin, Mark E, Blok, Elisabet, Bøen, Erlend, Breukelaar, Isabella A, Bright, Joanna K, Buimer, Elizabeth EL, Bülow, Robin, Cannon, Dara M, Ciufolini, Simone, Crossley, Nicolas A, Damatac, Christienne G, Dazzan, Paola, de Mol, Casper L, de Zwarte, Sonja MC, Desrivières, Sylvane, Díaz-Caneja, Covadonga M, Doan, Nhat Trung, Dohm, Katharina, Fröhner, Juliane H, Goltermann, Janik, Grigis, Antoine, Grotegerd, Dominik, Han, Laura KM, Harris, Mathew A, Hartman, Catharina A, Heany, Sarah J, Heindel, Walter, Heslenfeld, Dirk J, Hohmann, Sarah, Ittermann, Bernd, Jansen, Philip R, Janssen, Joost, Jia, Tianye, Jiang, Jiyang, Jockwitz, Christiane, Karali, Temmuz, Keeser, Daniel, Koevoets, Martijn GJC, Lenroot, Rhoshel K, Malchow, Berend, Mandl, René CW, Medel, Vicente, Meinert, Susanne, Morgan, Catherine A, Mühleisen, Thomas W, Nabulsi, Leila, Opel, Nils, de la Foz, Víctor Ortiz-García, Overs, Bronwyn J, Paillère Martinot, Marie-Laure, Redlich, Ronny, Marques, Tiago Reis, Repple, Jonathan, Roberts, Gloria, Roshchupkin, Gennady V, Setiaman, Nikita, Shumskaya, Elena, Stein, Frederike, Sudre, Gustavo, Takahashi, Shun, Thalamuthu, Anbupalam, Tordesillas-Gutiérrez, Diana, van der Lugt, Aad, van Haren, Neeltje EM, Wardlaw, Joanna M, Wen, Wei, Westeneng, Henk-Jan, Wittfeld, Katharina, Zhu, Alyssa H, Zugman, Andre, Armstrong, Nicola J, Bonfiglio, Gaia, Bralten, Janita, Dalvie, Shareefa, Davies, Gail, Di Forti, Marta, Ding, Linda, Donohoe, Gary, Forstner, Andreas J, and Gonzalez-Peñas, Javier

Subjects
Biological Psychology, Psychology, Genetics, Biomedical Imaging, Mental Health, Biotechnology, Human Genome, Prevention, Aging, Brain Disorders, Neurosciences, 2.1 Biological and endogenous factors, Aetiology, Mental health, Neurological, Brain, Genome-Wide Association Study, Humans, Longevity, Magnetic Resonance Imaging, IMAGEN Consortium, Cognitive Sciences, Neurology & Neurosurgery, Biological psychology
Abstract

Human brain structure changes throughout the lifespan. Altered brain growth or rates of decline are implicated in a vast range of psychiatric, developmental and neurodegenerative diseases. In this study, we identified common genetic variants that affect rates of brain growth or atrophy in what is, to our knowledge, the first genome-wide association meta-analysis of changes in brain morphology across the lifespan. Longitudinal magnetic resonance imaging data from 15,640 individuals were used to compute rates of change for 15 brain structures. The most robustly identified genes GPR139, DACH1 and APOE are associated with metabolic processes. We demonstrate global genetic overlap with depression, schizophrenia, cognitive functioning, insomnia, height, body mass index and smoking. Gene set findings implicate both early brain development and neurodegenerative processes in the rates of brain changes. Identifying variants involved in structural brain changes may help to determine biological pathways underlying optimal and dysfunctional brain development and aging.

Published
2022

14. A Network Control Theory Approach to Longitudinal Symptom Dynamics in Major Depressive Disorder

Author

Hahn, Tim, Jamalabadi, Hamidreza, Emden, Daniel, Goltermann, Janik, Ernsting, Jan, Winter, Nils R., Fisch, Lukas, Leenings, Ramona, Sarink, Kelvin, Holstein, Vincent, Gruber, Marius, Grotegerd, Dominik, Meinert, Susanne, Dohm, Katharina, Leehr, Elisabeth J., Richter, Maike, Sindermann, Lisa, Enneking, Verena, Lemke, Hannah, Witt, Stephanie, Rietschel, Marcella, Brosch, Katharina, Pfarr, Julia-Katharina, Meller, Tina, Ringwald, Kai Gustav, Schmitt, Simon, Stein, Frederike, Nenadic, Igor, Kircher, Tilo, Müller-Myhsok, Bertram, Andlauer, Till F. M., Repple, Jonathan, Dannlowski, Udo, and Opel, Nils

Subjects
Electrical Engineering and Systems Science - Systems and Control, Quantitative Biology - Neurons and Cognition
Abstract

Background: The evolution of symptoms over time is at the heart of understanding and treating mental disorders. However, a principled, quantitative framework explaining symptom dynamics remains elusive. Here, we propose a Network Control Theory of Psychopathology allowing us to formally derive a theoretical control energy which we hypothesize quantifies resistance to future symptom improvement in Major Depressive Disorder (MDD). We test this hypothesis and investigate the relation to genetic and environmental risk as well as resilience. Methods: We modelled longitudinal symptom-network dynamics derived from N=2,059 Beck Depression Inventory measurements acquired over a median of 134 days in a sample of N=109 patients suffering from MDD. We quantified the theoretical energy required for each patient and time-point to reach a symptom-free state given individual symptom-network topology (E 0 ) and 1) tested if E 0 predicts future symptom improvement and 2) whether this relationship is moderated by Polygenic Risk Scores (PRS) of mental disorders, childhood maltreatment experience, and self-reported resilience. Outcomes: We show that E 0 indeed predicts symptom reduction at the next measurement and reveal that this coupling between E 0 and future symptom change increases with higher genetic risk and childhood maltreatment while it decreases with resilience. Interpretation: Our study provides a mechanistic framework capable of predicting future symptom improvement based on individual symptom-network topology and clarifies the role of genetic and environmental risk as well as resilience. Our control-theoretic framework makes testable, quantitative predictions for individual therapeutic response and provides a starting-point for the theory-driven design of personalized interventions. Funding: German Research Foundation and Interdisciplinary Centre for Clinical Research, M\"unster, Comment: 21 pages, 2 figures

Published
2021

16. Negative Stressful Life Events and Social Support Are Associated With White Matter Integrity in Depressed Patients and Healthy Control Participants: A Diffusion Tensor Imaging Study

Author

Flinkenflügel, Kira, Meinert, Susanne, Thiel, Katharina, Winter, Alexandra, Goltermann, Janik, Strathausen, Lea, Brosch, Katharina, Stein, Frederike, Thomas-Odenthal, Florian, Evermann, Ulrika, Wroblewski, Adrian, Usemann, Paula, Pfarr, Julia-Katharina, Grotegerd, Dominik, Hahn, Tim, Leehr, Elisabeth J., Dohm, Katharina, Bauer, Jochen, Jamalabadi, Hamidreza, Straube, Benjamin, Alexander, Nina, Jansen, Andreas, Nenadić, Igor, Krug, Axel, Kircher, Tilo, and Dannlowski, Udo

Published
2023
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17. Biological sex classification with structural MRI data shows increased misclassification in transgender women

Author

Flint, Claas, Förster, Katharina, Koser, Sophie A., Konrad, Carsten, Zwitserlood, Pienie, Berger, Klaus, Hermesdorf, Marco, Kircher, Tilo, Nenadic, Igor, Krug, Axel, Baune, Bernhard T., Dohm, Katharina, Redlich, Ronny, Opel, Nils, Arolt, Volker, Hahn, Tim, Jiang, Xiaoyi, Dannlowski, Udo, and Grotegerd, Dominik

Subjects
Quantitative Biology - Neurons and Cognition, Computer Science - Computer Vision and Pattern Recognition
Abstract

Transgender individuals (TIs) show brain structural alterations that differ from their biological sex as well as their perceived gender. To substantiate evidence that the brain structure of TIs differs from male and female, we use a combined multivariate and univariate approach. Gray matter segments resulting from voxel-based morphometry preprocessing of $N = 1753$ cisgender (CG) healthy participants were used to train ($N=1402$) and validate (20 % hold-out; $N = 351$) a support-vector machine classifying the biological sex. As a second validation, we classified $N = 1104$ patients with depression. A third validation was performed using the matched CG sample of the transgender women (TWs) application-sample. Subsequently, the classifier was applied to $N = 26$ TWs. Finally, we compared brain volumes of CG-men, women and TW-pre/post treatment (cross-sex hormone treatment) in a univariate analysis controlling for sexual orientation, age and total brain volume. The application of our biological sex classifier to the transgender sample resulted in a significantly lower true positive rate (TPR) (TPR-male = 56.0 %). The TPR did not differ between CG-individuals with (TPR-male = 86.9 %) and without depression (TPR-male = 88.5 %). The univariate analysis of the transgender application-sample revealed that TW-pre/post treatment show brain structural differences from CG-women and CG-men in the putamen and insula, as well as the whole-brain analysis. Our results support the hypothesis that brain structure in TW differs from brain structure of their biological sex (male) as well as their perceived gender (female). This finding substantiates evidence that TIs show specific brain structural alterations leading to a different pattern of brain structure than CG-individuals., Comment: Content adapted to the publication at Neuropsychopharmacology

Published
2019
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18. The genetic architecture of the human cerebral cortex

Author

Grasby, Katrina L, Jahanshad, Neda, Painter, Jodie N, Colodro-Conde, Lucía, Bralten, Janita, Hibar, Derrek P, Lind, Penelope A, Pizzagalli, Fabrizio, Ching, Christopher RK, McMahon, Mary Agnes B, Shatokhina, Natalia, Zsembik, Leo CP, Thomopoulos, Sophia I, Zhu, Alyssa H, Strike, Lachlan T, Agartz, Ingrid, Alhusaini, Saud, Almeida, Marcio AA, Alnæs, Dag, Amlien, Inge K, Andersson, Micael, Ard, Tyler, Armstrong, Nicola J, Ashley-Koch, Allison, Atkins, Joshua R, Bernard, Manon, Brouwer, Rachel M, Buimer, Elizabeth EL, Bülow, Robin, Bürger, Christian, Cannon, Dara M, Chakravarty, Mallar, Chen, Qiang, Cheung, Joshua W, Couvy-Duchesne, Baptiste, Dale, Anders M, Dalvie, Shareefa, de Araujo, Tânia K, de Zubicaray, Greig I, de Zwarte, Sonja MC, Braber, Anouk den, Doan, Nhat Trung, Dohm, Katharina, Ehrlich, Stefan, Engelbrecht, Hannah-Ruth, Erk, Susanne, Fan, Chun Chieh, Fedko, Iryna O, Foley, Sonya F, Ford, Judith M, Fukunaga, Masaki, Garrett, Melanie E, Ge, Tian, Giddaluru, Sudheer, Goldman, Aaron L, Green, Melissa J, Groenewold, Nynke A, Grotegerd, Dominik, Gurholt, Tiril P, Gutman, Boris A, Hansell, Narelle K, Harris, Mathew A, Harrison, Marc B, Haswell, Courtney C, Hauser, Michael, Herms, Stefan, Heslenfeld, Dirk J, Ho, New Fei, Hoehn, David, Hoffmann, Per, Holleran, Laurena, Hoogman, Martine, Hottenga, Jouke-Jan, Ikeda, Masashi, Janowitz, Deborah, Jansen, Iris E, Jia, Tianye, Jockwitz, Christiane, Kanai, Ryota, Karama, Sherif, Kasperaviciute, Dalia, Kaufmann, Tobias, Kelly, Sinead, Kikuchi, Masataka, Klein, Marieke, Knapp, Michael, Knodt, Annchen R, Krämer, Bernd, Lam, Max, Lancaster, Thomas M, Lee, Phil H, Lett, Tristram A, Lewis, Lindsay B, Lopes-Cendes, Iscia, Luciano, Michelle, Macciardi, Fabio, Marquand, Andre F, Mathias, Samuel R, Melzer, Tracy R, and Milaneschi, Yuri

Subjects
Biological Sciences, Genetics, Neurosciences, Mental Health, Brain Disorders, Stem Cell Research, 2.1 Biological and endogenous factors, Aetiology, Neurological, Attention Deficit Disorder with Hyperactivity, Brain Mapping, Cerebral Cortex, Cognition, Genetic Loci, Genetic Variation, Genome-Wide Association Study, Humans, Magnetic Resonance Imaging, Organ Size, Parkinson Disease, Alzheimer’s Disease Neuroimaging Initiative, CHARGE Consortium, EPIGEN Consortium, IMAGEN Consortium, SYS Consortium, Parkinson’s Progression Markers Initiative, Enhancing NeuroImaging Genetics through Meta-Analysis Consortium (ENIGMA)—Genetics working group, General Science & Technology
Abstract

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder.

Published
2020

19. Structural brain alterations associated with suicidal thoughts and behaviors in young people: results from 21 international studies from the ENIGMA Suicidal Thoughts and Behaviours consortium

Author

van Velzen, Laura S., Dauvermann, Maria R., Colic, Lejla, Villa, Luca M., Savage, Hannah S., Toenders, Yara J., Zhu, Alyssa H., Bright, Joanna K., Campos, Adrián I., Salminen, Lauren E., Ambrogi, Sonia, Ayesa-Arriola, Rosa, Banaj, Nerisa, Başgöze, Zeynep, Bauer, Jochen, Blair, Karina, Blair, Robert James, Brosch, Katharina, Cheng, Yuqi, Colle, Romain, Connolly, Colm G., Corruble, Emmanuelle, Couvy-Duchesne, Baptiste, Crespo-Facorro, Benedicto, Cullen, Kathryn R., Dannlowski, Udo, Davey, Christopher G., Dohm, Katharina, Fullerton, Janice M., Gonul, Ali Saffet, Gotlib, Ian H., Grotegerd, Dominik, Hahn, Tim, Harrison, Ben J., He, Mengxin, Hickie, Ian B., Ho, Tiffany C., Iorfino, Frank, Jansen, Andreas, Jollant, Fabrice, Kircher, Tilo, Klimes-Dougan, Bonnie, Klug, Melissa, Leehr, Elisabeth J., Lippard, Elizabeth T. C., McLaughlin, Katie A., Meinert, Susanne, Miller, Adam Bryant, Mitchell, Philip B., Mwangi, Benson, Nenadić, Igor, Ojha, Amar, Overs, Bronwyn J., Pfarr, Julia-Katharina, Piras, Fabrizio, Ringwald, Kai G., Roberts, Gloria, Romer, Georg, Sanches, Marsal, Sheridan, Margaret A., Soares, Jair C., Spalletta, Gianfranco, Stein, Frederike, Teresi, Giana I., Tordesillas-Gutiérrez, Diana, Uyar-Demir, Aslihan, van der Wee, Nic J. A., van der Werff, Steven J., Vermeiren, Robert R. J. M., Winter, Alexandra, Wu, Mon-Ju, Yang, Tony T., Thompson, Paul M., Rentería, Miguel E., Jahanshad, Neda, Blumberg, Hilary P., van Harmelen, Anne-Laura, and Schmaal, Lianne

Published
2022
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20. Understanding the neurobiological basis of anhedonia in major depressive disorder--evidence for reduced neural activation during reward and loss processing

Author

Steinmann, Lavinia A., Dohm, Katharina, Goltermann, Janik, Richter, Maike, Enneking, Verena, Lippitz, Marcia, Repple, Jonathan, Mauritz, Marco, Dannlowski, Udo, and Opel, Nils

Subjects
Neural circuitry -- Health aspects -- Psychological aspects, Major depressive disorder -- Development and progression, Anhedonia -- Development and progression, Health, Psychology and mental health
Abstract

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., Introduction Anhedonia is one of the core symptoms of major depressive disorder (MDD) in addition to low mood, according to the International Statistical Classification of Diseases and Related Health Problems, [...]

Published
2022
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21. How movies move us – movie preferences are linked to differences in neuronal emotion processing of fear and anger: an fMRI study

Author

Zwiky, Esther, primary, König, Philine, additional, Herrmann, Rebekka Maria, additional, Küttner, Antonia, additional, Selle, Janine, additional, Ptasczynski, Lena Esther, additional, Schöniger, Konrad, additional, Rutenkröger, Mareike, additional, Enneking, Verena, additional, Borgers, Tiana, additional, Klug, Melissa, additional, Dohm, Katharina, additional, Leehr, Elisabeth J, additional, Bauer, Jochen, additional, Dannlowski, Udo, additional, and Redlich, Ronny, additional

Published
2024
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22. Brain structural correlates of recurrence following the first episode in patients with major depressive disorder

Author

Lemke, Hannah, Klute, Hannah, Skupski, Jennifer, Thiel, Katharina, Waltemate, Lena, Winter, Alexandra, Breuer, Fabian, Meinert, Susanne, Klug, Melissa, Enneking, Verena, Winter, Nils R., Grotegerd, Dominik, Leehr, Elisabeth J., Repple, Jonathan, Dohm, Katharina, Opel, Nils, Stein, Frederike, Meller, Tina, Brosch, Katharina, Ringwald, Kai G., Pfarr, Julia-Katharina, Thomas-Odenthal, Florian, Hahn, Tim, Krug, Axel, Jansen, Andreas, Heindel, Walter, Nenadić, Igor, Kircher, Tilo, and Dannlowski, Udo

Published
2022
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24. The Course of Disease in Major Depressive Disorder Is Associated With Altered Activity of the Limbic System During Negative Emotion Processing

Author

Lemke, Hannah, Probst, Stefanie, Warneke, Antonia, Waltemate, Lena, Winter, Alexandra, Thiel, Katharina, Meinert, Susanne, Enneking, Verena, Breuer, Fabian, Klug, Melissa, Goltermann, Janik, Hülsmann, Carina, Grotegerd, Dominik, Redlich, Ronny, Dohm, Katharina, Leehr, Elisabeth J., Repple, Jonathan, Opel, Nils, Brosch, Katharina, Meller, Tina, Pfarr, Julia-Katharina, Ringwald, Kai, Schmitt, Simon, Stein, Frederike, Krug, Axel, Jansen, Andreas, Nenadic, Igor, Kircher, Tilo, Hahn, Tim, and Dannlowski, Udo

Published
2022
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25. Association Between Genetic Risk for Type 2 Diabetes and Structural Brain Connectivity in Major Depressive Disorder

Author

Repple, Jonathan, König, Amelie, de Lange, Siemon C., Opel, Nils, Redlich, Ronny, Meinert, Susanne, Grotegerd, Dominik, Mauritz, Marco, Hahn, Tim, Borgers, Tiana, Leehr, Elisabeth J., Winter, Nils, Goltermann, Janik, Enneking, Verena, Fingas, Stella M., Lemke, Hannah, Waltemate, Lena, Dohm, Katharina, Richter, Maike, Mehler, David M.A., Holstein, Vincent, Gruber, Marius, Nenadic, Igor, Krug, Axel, Brosch, Katharina, Schmitt, Simon, Stein, Frederike, Meller, Tina, Jansen, Andreas, Steinsträter, Olaf, Amare, Azmeraw T., Kircher, Tilo, Baune, Bernhard T., van den Heuvel, Martijn P., and Dannlowski, Udo

Published
2022
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26. Association of brain white matter microstructure with cognitive performance in major depressive disorder and healthy controls: a diffusion-tensor imaging study

Author

Meinert, Susanne, Nowack, Nico, Grotegerd, Dominik, Repple, Jonathan, Winter, Nils R., Abheiden, Isabel, Enneking, Verena, Lemke, Hannah, Waltemate, Lena, Stein, Frederike, Brosch, Katharina, Schmitt, Simon, Meller, Tina, Pfarr, Julia-Katharina, Ringwald, Kai, Steinsträter, Olaf, Gruber, Marius, Nenadić, Igor, Krug, Axel, Leehr, Elisabeth J., Hahn, Tim, Thiel, Katharina, Dohm, Katharina, Winter, Alexandra, Opel, Nils, Schubotz, Ricarda I., Kircher, Tilo, and Dannlowski, Udo

Published
2022
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27. Apolipoprotein E homozygous ε4 allele status: Effects on cortical structure and white matter integrity in a young to mid-age sample

Author

Goltermann, Janik, Repple, Jonathan, Redlich, Ronny, Dohm, Katharina, Flint, Claas, Grotegerd, Dominik, Waltemate, Lena, Lemke, Hannah, Fingas, Stella Mercedes, Meinert, Susanne, Enneking, Verena, Hahn, Tim, Bauer, Jochen, Schmitt, Simon, Meller, Tina, Stein, Frederike, Brosch, Katharina, Steinsträter, Olaf, Jansen, Andreas, Krug, Axel, Nenadić, Igor, Baune, Bernhard T., Rietschel, Marcella, Witt, Stephanie, Forstner, Andreas J., Nöthen, Markus, Johnen, Andreas, Alferink, Judith, Kircher, Tilo, Dannlowski, Udo, and Opel, Nils

Published
2021
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28. Associations between white matter microstructure and cognitive decline in major depressive disorder versus controls in Germany: a prospective case-control cohort study

Author

Flinkenflügel, Kira, Meinert, Susanne, Hirtsiefer, Christopher, Grotegerd, Dominik, Gruber, Marius, Goltermann, Janik, Winter, Nils R, Stein, Frederike, Brosch, Katharina, Leehr, Elisabeth J, Böhnlein, Joscha, Dohm, Katharina, Bauer, Jochen, Redlich, Ronny, Hahn, Tim, Repple, Jonathan, Opel, Nils, Nitsch, Robert, Jamalabadi, Hamidreza, Straube, Benjamin, Alexander, Nina, Jansen, Andreas, Nenadić, Igor, van den Heuvel, Martijn P, Thiel, Katharina, Winter, Alexandra, Thomas-Odenthal, Florian, Usemann, Paula, Teutenberg, Lea, Pfarr, Julia-Katharina, Kircher, Tilo, and Dannlowski, Udo

Abstract

Cognitive deficits are a key source of disability in individuals with major depressive disorder (MDD) and worsen with disease progression. Despite their clinical relevance, the underlying mechanisms of cognitive deficits remain poorly elucidated, hampering effective treatment strategies. Emerging evidence suggests that alterations in white matter microstructure might contribute to cognitive dysfunction in MDD. We aimed to investigate the complex association between changes in white matter integrity, cognitive decline, and disease course in MDD in a comprehensive longitudinal dataset.

Published
2024
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29. Social support and hippocampal volume are negatively associated in adults with previous experience of childhood maltreatment

Author

Forster, Katharina, Danzer, Lorenz, Redlich, Ronny, Opel, Nils, Grotegerd, Dominik, Leehr, Elisabeth J., Dohm, Katharina, Enneking, Verena, Meinert, Susanne, Goltermann, Janik, Lemke, Hannah, Waltemate, Lena, Thiel, Katharina, Behnert, Katja, Brosch, Katharina, Stein, Frederike, Meller, Tina, Ringwald, Kai, Schmitt, Simon, Steinstrater, Olaf, Jansen, Andreas, Krug, Axel, Nenadic, Igor, Kircher, Tilo, Hahn, Tim, Kugel, Harald, Heindel, Walter, Repple, Jonathan, and Dannlowski, Udo

Subjects
Hippocampus (Brain) -- Physiological aspects, Child abuse -- Physiological aspects -- Psychological aspects, Social networks -- Psychological aspects -- Physiological aspects, Health, Psychology and mental health
Abstract

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 x 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 [F.sub.1,432] = 5.686, p = 0.018; right [F.sub.1,433] = 3.371, p = 0.07), but no main effect of social support emerged. However, we did find a significant social support x group interaction for left hippocampal volume (left [F.sub.1,432] = 5.712, p = 0.017; right [F.sub.1,433] = 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., Introduction Childhood maltreatment is an adverse social experience and is a risk factor for many mental disorders. (1) It is also associated with neuroendocrine dysregulation (e.g., hypercortisolism) and alterations in [...]

Published
2021
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30. Childhood maltreatment and cognitive functioning: the role of depression, parental education, and polygenic predisposition

Author

Goltermann, Janik, Redlich, Ronny, Grotegerd, Dominik, Dohm, Katharina, Leehr, Elisabeth J., Böhnlein, Joscha, Förster, Katharina, Meinert, Susanne, Enneking, Verena, Richter, Maike, Repple, Jonathan, DeVillers, Immanuel, Kloecker, Marine, Jansen, Andreas, Krug, Axel, Nenadić, Igor, Brosch, Katharina, Meller, Tina, Stein, Frederike, Schmitt, Simon, Rietschel, Marcella, Streit, Fabian, Witt, Stephanie H., Forstner, Andreas J., Nöthen, Markus M., Baune, Bernhard T., Andlauer, Till F. M., Kircher, Tilo, Opel, Nils, and Dannlowski, Udo

Published
2021
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31. Replication of a hippocampus specific effect of the tescalcin regulating variant rs7294919 on gray matter structure

Author

Goltermann, Janik, Opel, Nils, Redlich, Ronny, Repple, Jonathan, Kaehler, Claas, Grotegerd, Dominik, Dohm, Katharina, Leehr, Elisabeth J., Böhnlein, Joscha, Förster, Katharina, Meinert, Susanne, Enneking, Verena, Emden, Daniel, Leenings, Ramona, Winter, Nils R., Hahn, Tim, Mikhail, Sami, Jansen, Andreas, Krug, Axel, Nenadić, Igor, Rietschel, Marcella, Witt, Stephanie H., Heilmann-Heimbach, Stefanie, Hoffmann, Per, Forstner, Andreas J., Nöthen, Markus M., Baune, Bernhard T., Kircher, Tilo, and Dannlowski, Udo

Published
2020
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32. Cortical surface area alterations shaped by genetic load for neuroticism

Author

Opel, Nils, Amare, Azmeraw T., Redlich, Ronny, Repple, Jonathan, Kaehler, Claas, Grotegerd, Dominik, Dohm, Katharina, Zaremba, Dario, Leehr, Elisabeth J., Böhnlein, Joscha, Förster, Katharina, Bürger, Christian, Meinert, Susanne, Enneking, Verena, Emden, Daniel, Leenings, Ramona, Winter, Nils, Hahn, Tim, Heindel, Walter, Bauer, Jochen, Wilhelms, David, Schmitt, Simon, Jansen, Andreas, Krug, Axel, Nenadic, Igor, Rietschel, Marcella, Witt, Stephanie, Forstner, Andreas J., Nöthen, Markus M., Kircher, Tilo, Arolt, Volker, Baune, Bernhard T., and Dannlowski, Udo

Published
2020
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33. Brain structural correlates of alexithymia in patients with major depressive disorder

Author

Forster, Katharina, Enneking, Verena, Dohm, Katharina, Redlich, Ronny, Meinert, Susanne, Geisler, Adina Isabel, Leehr, Elisabeth Johanna, Kugel, Harald, Baune, Bernhard T., Arolt, Volker, Zwitserlood, Pienie, Grotegerd, Dominik, and Dannlowski, Udo

Subjects
Brain -- Analysis, Major depressive disorder -- Research -- Care and treatment -- Analysis, Medical research -- Analysis, Alexithymia -- Research -- Care and treatment -- Analysis, Brain research, Diagnostic imaging, Nature, Health, Psychology and mental health
Abstract

Background: Alexithymia is a risk factor for major depressive disorder (MDD) and has been associated with diminished treatment response. Neuroimaging studies have revealed structural aberrations of the anterior cingulate cortex and the fusiform gyrus in healthy controls with high levels of alexithymia. The present study tried to corroborate and extend these results to patients with MDD compared with healthy controls. Methods: We investigated the relationship between alexithymia, depression and grey matter volume in 63 patients with MDD (mean age [+ or -] standard deviation = 42.43 yr [+ or -] 11.91; 33 female) and 46 healthy controls (45.35 yr [+ or -] 8.37; 22 female). We assessed alexithymia using the Toronto Alexithymia Scale. We conducted an alexithymia x group analysis of covariance; we used a region-of-interest approach, including the fusiform gyrus and anterior cingulate cortex, and conducted whole brain analysis using voxel-based morphometry. Results: Our analysis revealed a significant alexithymia x group interaction in the fusiform gyrus (left, [p.sub.FWE] = 0.031; right, [p.sub.FWE] = 0.010). Higher alexithymia scores were associated with decreased grey matter volume in patients with MDD ([p.sub.FWE] = 0.009), but with increased grey matter volume of the fusiform gyrus in healthy controls ([p.sub.FWE] = 0.044). We found no significant main effects in the region-of-interest analysis. Limitations: Owing to the naturalistic nature of our study, patients with MDD and healthy controls differed significantly in their alexithymia scores. Conclusion: Our results showed the fusiform gyrus as a correlate of alexithymia. We also found differences related to alexithymia between patients with MDD and healthy controls in the fusiform gyrus. Our study encourages research related to the transition from risk to MDD in people with alexithymia., Introduction Major depressive disorder (MDD) is one of the most common and disabling psychiatric diseases worldwide. (1) At least one-third of patients with MDD do not respond to first-line treatment, [...]

Published
2020
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35. Evidence for a sex-specific contribution of polygenic load for anorexia nervosa to body weight and prefrontal brain structure in nonclinical individuals

Author

Leehr, Elisabeth J., Opel, Nils, Werner, Janina, Redlich, Ronny, Repple, Jonathan, Grotegerd, Dominik, Dohm, Katharina, Goltermann, Janik, Böhnlein, Joscha, Amare, Azmeraw T., Sindermann, Lisa, Förster, Katharina, Meinert, Susanne, Enneking, Verena, Richter, Maike, Hahn, Tim, Baune, Bernhard T., and Dannlowski, Udo

Published
2019
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37. The effects of processing speed on memory impairment in patients with major depressive disorder

Author

Zaremba, Dario, Schulze Kalthoff, Ida, Förster, Katharina, Redlich, Ronny, Grotegerd, Dominik, Leehr, Elisabeth J., Meinert, Susanne, Dohm, Katharina, Bürger, Christian, Enneking, Verena, Böhnlein, Joscha, Repple, Jonathan, Opel, Nils, Jörgens, Silke, Yüksel, Dilara, Schmitt, Simon, Stein, Frederike, Kircher, Tilo, Krug, Axel, Nenadić, Igor, Zwitserlood, Pienie, Baune, Bernhard T., Arolt, Volker, and Dannlowski, Udo

Published
2019
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38. Associations of schizophrenia risk genes ZNF804A and CACNA1C with schizotypy and modulation of attention in healthy subjects

Author

Meller, Tina, Schmitt, Simon, Stein, Frederike, Brosch, Katharina, Mosebach, Johannes, Yüksel, Dilara, Zaremba, Dario, Grotegerd, Dominik, Dohm, Katharina, Meinert, Susanne, Förster, Katharina, Redlich, Ronny, Opel, Nils, Repple, Jonathan, Hahn, Tim, Jansen, Andreas, Andlauer, Till F.M., Forstner, Andreas J., Heilmann-Heimbach, Stefanie, Streit, Fabian, Witt, Stephanie H., Rietschel, Marcella, Müller-Myhsok, Bertram, Nöthen, Markus M., Dannlowski, Udo, Krug, Axel, Kircher, Tilo, and Nenadić, Igor

Published
2019
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39. Mediation of the influence of childhood maltreatment on depression relapse by cortical structure: a 2-year longitudinal observational study

Author

Opel, Nils, Redlich, Ronny, Dohm, Katharina, Zaremba, Dario, Goltermann, Janik, Repple, Jonathan, Kaehler, Claas, Grotegerd, Dominik, Leehr, Elisabeth J, Böhnlein, Joscha, Förster, Katharina, Meinert, Susanne, Enneking, Verena, Sindermann, Lisa, Dzvonyar, Fanni, Emden, Daniel, Leenings, Ramona, Winter, Nils, Hahn, Tim, Kugel, Harald, Heindel, Walter, Buhlmann, Ulrike, Baune, Bernhard T, Arolt, Volker, and Dannlowski, Udo

Published
2019
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40. Childhood maltreatment moderates the influence of genetic load for obesity on reward related brain structure and function in major depression

Author

Opel, Nils, Redlich, Ronny, Repple, Jonathan, Kaehler, Claas, Grotegerd, Dominik, Dohm, Katharina, Zaremba, Dario, Goltermann, Janik, Steinmann, Lavinia-Alexandra M., Krughöfer, Rahel, Leehr, Elisabeth J., Böhnlein, Joscha, Förster, Katharina, Bürger, Christian, Meinert, Susanne, Enneking, Verena, Emden, Daniel, Leenings, Ramona, Winter, Nils, Heindel, Walter, Kugel, Harald, Thalamuthu, Anbupalam, Hahn, Tim, Arolt, Volker, Baune, Bernhard T., and Dannlowski, Udo

Published
2019
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41. A Systematic Evaluation of Machine Learning–Based Biomarkers for Major Depressive Disorder.

Author

Winter, Nils R., Blanke, Julian, Leenings, Ramona, Ernsting, Jan, Fisch, Lukas, Sarink, Kelvin, Barkhau, Carlotta, Emden, Daniel, Thiel, Katharina, Flinkenflügel, Kira, Winter, Alexandra, Goltermann, Janik, Meinert, Susanne, Dohm, Katharina, Repple, Jonathan, Gruber, Marius, Leehr, Elisabeth J., Opel, Nils, Grotegerd, Dominik, and Redlich, Ronny

Subjects
DIFFUSION tensor imaging, MENTAL depression, GENETIC risk score, FUNCTIONAL magnetic resonance imaging, MAGNETIC resonance imaging
Abstract

Key Points: Question: Can multivariate machine learning approaches identify the neural signature of major depressive disorder in individual patients? Findings: In this case-control neuroimaging study that included 1801 patients with depression and healthy controls, the best machine learning algorithm only achieved a diagnostic classification accuracy of 62% across major neuroimaging modalities. Meaning: Although multivariate neuroimaging markers increase predictive power compared with univariate analyses, no depression biomarker could be uncovered that is able to identify individual patients. This case-control study evaluates whether machine learning can identify a multivariate biomarker for major depressive disorder. Importance: Biological psychiatry aims to understand mental disorders in terms of altered neurobiological pathways. However, for one of the most prevalent and disabling mental disorders, major depressive disorder (MDD), no informative biomarkers have been identified. Objective: To evaluate whether machine learning (ML) can identify a multivariate biomarker for MDD. Design, Setting, and Participants: This study used data from the Marburg-Münster Affective Disorders Cohort Study, a case-control clinical neuroimaging study. Patients with acute or lifetime MDD and healthy controls aged 18 to 65 years were recruited from primary care and the general population in Münster and Marburg, Germany, from September 11, 2014, to September 26, 2018. The Münster Neuroimaging Cohort (MNC) was used as an independent partial replication sample. Data were analyzed from April 2022 to June 2023. Exposure: Patients with MDD and healthy controls. Main Outcome and Measure: Diagnostic classification accuracy was quantified on an individual level using an extensive ML-based multivariate approach across a comprehensive range of neuroimaging modalities, including structural and functional magnetic resonance imaging and diffusion tensor imaging as well as a polygenic risk score for depression. Results: Of 1801 included participants, 1162 (64.5%) were female, and the mean (SD) age was 36.1 (13.1) years. There were a total of 856 patients with MDD (47.5%) and 945 healthy controls (52.5%). The MNC replication sample included 1198 individuals (362 with MDD [30.1%] and 836 healthy controls [69.9%]). Training and testing a total of 4 million ML models, mean (SD) accuracies for diagnostic classification ranged between 48.1% (3.6%) and 62.0% (4.8%). Integrating neuroimaging modalities and stratifying individuals based on age, sex, treatment, or remission status does not enhance model performance. Findings were replicated within study sites and also observed in structural magnetic resonance imaging within MNC. Under simulated conditions of perfect reliability, performance did not significantly improve. Analyzing model errors suggests that symptom severity could be a potential focus for identifying MDD subgroups. Conclusion and Relevance: Despite the improved predictive capability of multivariate compared with univariate neuroimaging markers, no informative individual-level MDD biomarker—even under extensive ML optimization in a large sample of diagnosed patients—could be identified. [ABSTRACT FROM AUTHOR]

Published
2024
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42. Long-term effects of electroconvulsive therapy on brain structure in major depression.

Author

Borgers, Tiana, Enneking, Verena, Klug, Melissa, Garbe, Jasper, Meinert, Hannah, Wulle, Marius, König, Philine, Zwiky, Esther, Herrmann, Rebekka, Selle, Janine, Dohm, Katharina, Kraus, Anna, Grotegerd, Dominik, Repple, Jonathan, Opel, Nils, Leehr, Elisabeth J., Gruber, Marius, Goltermann, Janik, Meinert, Susanne, and Bauer, Jochen

Subjects
BRAIN anatomy, STATISTICAL correlation, ELECTROCONVULSIVE therapy, RESEARCH funding, TREATMENT effectiveness, DESCRIPTIVE statistics, MAGNETIC resonance imaging, LONGITUDINAL method, GRAY matter (Nerve tissue), ANTIDEPRESSANTS, ANALYSIS of variance, RESEARCH, DATA analysis software, MENTAL depression, TIME, DISEASE progression
Abstract

Background: Magnetic resonance imaging (MRI) studies on major depressive disorder (MDD) have predominantly found short-term electroconvulsive therapy (ECT)-related gray matter volume (GMV) increases, but research on the long-term stability of such changes is missing. Our aim was to investigate long-term GMV changes over a 2-year period after ECT administration and their associations with clinical outcome. Methods: In this nonrandomized longitudinal study, patients with MDD undergoing ECT (n = 17) are assessed three times by structural MRI: Before ECT (t 0), after ECT (t 1) and 2 years later (t 2). A healthy (n = 21) and MDD non-ECT (n = 33) control group are also measured three times within an equivalent time interval. A 3(group) × 3(time) ANOVA on whole-brain level and correlation analyses with clinical outcome variables is performed. Results: Analyses yield a significant group × time interaction (pFWE < 0.001) resulting from significant volume increases from t 0 to t 1 and decreases from t 1 to t 2 in the ECT group, e.g., in limbic areas. There are no effects of time in both control groups. Volume increases from t 0 to t 1 correlate with immediate and delayed symptom increase, while volume decreases from t 1 to t 2 correlate with long-term depressive outcome (all p ⩽ 0.049). Conclusions: Volume increases induced by ECT appear to be a transient phenomenon as volume strongly decreased 2 years after ECT. Short-term volume increases are associated with less symptom improvement suggesting that the antidepressant effect of ECT is not due to volume changes. Larger volume decreases are associated with poorer long-term outcome highlighting the interplay between disease progression and structural changes. [ABSTRACT FROM AUTHOR]

Published
2024
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43. Childhood trauma moderates schizotypy-related brain morphology: analyses of 1182 healthy individuals from the ENIGMA schizotypy working group

Author

Quidé, Yann, primary, Watkeys, Oliver J., additional, Tonini, Emiliana, additional, Grotegerd, Dominik, additional, Dannlowski, Udo, additional, Nenadić, Igor, additional, Kircher, Tilo, additional, Krug, Axel, additional, Hahn, Tim, additional, Meinert, Susanne, additional, Goltermann, Janik, additional, Gruber, Marius, additional, Stein, Frederike, additional, Brosch, Katharina, additional, Wroblewski, Adrian, additional, Thomas-Odenthal, Florian, additional, Usemann, Paula, additional, Straube, Benjamin, additional, Alexander, Nina, additional, Leehr, Elisabeth J., additional, Bauer, Jochen, additional, Winter, Nils R., additional, Fisch, Lukas, additional, Dohm, Katharina, additional, Rössler, Wulf, additional, Smigielski, Lukasz, additional, DeRosse, Pamela, additional, Moyett, Ashley, additional, Houenou, Josselin, additional, Leboyer, Marion, additional, Gilleen, James, additional, Thomopoulos, Sophia I., additional, Thompson, Paul M., additional, Aleman, André, additional, Modinos, Gemma, additional, and Green, Melissa J., additional

Published
2023
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44. Interrelated effects of age and parenthood on whole-brain controllability: protective effects of parenthood in mothers

Author

Jamalabadi, Hamidreza, primary, Hahn, Tim, additional, Winter, Nils R., additional, Nozari, Erfan, additional, Ernsting, Jan, additional, Meinert, Susanne, additional, Leehr, Elisabeth J., additional, Dohm, Katharina, additional, Bauer, Jochen, additional, Pfarr, Julia-Katharina, additional, Stein, Frederike, additional, Thomas-Odenthal, Florian, additional, Brosch, Katharina, additional, Mauritz, Marco, additional, Gruber, Marius, additional, Repple, Jonathan, additional, Kaufmann, Tobias, additional, Krug, Axel, additional, Nenadić, Igor, additional, Kircher, Tilo, additional, Dannlowski, Udo, additional, and Derntl, Birgit, additional

Published
2023
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45. The relationship between social cognition and executive function in Major Depressive Disorder in high-functioning adolescents and young adults

Author

Förster, Katharina, Jörgens, Silke, Air, Tracy M., Bürger, Christian, Enneking, Verena, Redlich, Ronny, Zaremba, Dario, Grotegerd, Dominik, Dohm, Katharina, Meinert, Susanne, Leehr, Elisabeth J., Böhnlein, Joscha, Repple, Jonathan, Opel, Nils, Kavakbasi, Erhan, Arolt, Volker, Zwitserlood, Pienie, Dannlowski, Udo, and Baune, Bernhard T.

Published
2018
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46. Elevated body-mass index is associated with reduced white matter integrity in two large independent cohorts

Author

Repple, Jonathan, Opel, Nils, Meinert, Susanne, Redlich, Ronny, Hahn, Tim, Winter, Nils R., Kaehler, Claas, Emden, Daniel, Leenings, Ramona, Grotegerd, Dominik, Zaremba, Dario, Bürger, Christian, Förster, Katharina, Dohm, Katharina, Enneking, Verena, Leehr, Elisabeth J., Böhnlein, Joscha, Karliczek, Greta, Heindel, Walter, Kugel, Harald, Bauer, Jochen, Arolt, Volker, and Dannlowski, Udo

Published
2018
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47. Time heals all wounds? A 2-year longitudinal diffusion tensor imaging study in major depressive disorder

Author

Repple, Jonathan, Zaremba, Dario, Meinert, Susanne, Grotegerd, Dominik, Redlich, Ronny, Forster, Katharina, Dohm, Katharina, Opel, Nils, Hahn, Tim, Enneking, Verena, Leehr, Elisabeth J., Bohnlein, Joscha, Dzvonyar, Fanni, Sindermann, Lisa, Winter, Nils, Goltermann, Janik, Kugel, Harald, Bauer, Jochen, Heindel, Walter, Arolt, Volker, and Dannlowski, Udo

Subjects
Major depressive disorder -- Care and treatment, Medical research, Depression (Mood disorder), Health, Psychology and mental health
Abstract

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 x 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., Introduction Major depressive disorder (MDD) is expected to become the second-highest contributor to global disease burden by the year 2020, (1) and yet our understanding of its pathophysiological basis remains [...]

Published
2019
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48. Reduced fractional anisotropy in depressed patients due to childhood maltreatment rather than diagnosis

Author

Meinert, Susanne, Repple, Jonathan, Nenadic, Igor, Krug, Axel, Jansen, Andreas, Grotegerd, Dominik, Förster, Katharina, Enneking, Verena, Dohm, Katharina, Schmitt, Simon, Stein, Frederike, Brosch, Katharina, Meller, Tina, Redlich, Ronny, Böhnlein, Joscha, Sindermann, Lisa, Goltermann, Janik, Leehr, Elisabeth J., Opel, Nils, Aldermann, Leni, Reuter, Andreas, Schubotz, Ricarda I., Hahn, Tim, Kircher, Tilo, and Dannlowski, Udo

Published
2019
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50. Brain structural correlates of insomnia severity in 1053 individuals with major depressive disorder: results from the ENIGMA MDD Working Group

Author

Leerssen, Jeanne, Blanken, Tessa F., Pozzi, Elena, Jahanshad, Neda, Aftanas, Lyubomir, Andreassen, Ole A., Baune, Bernhard T., Brack, Ivan, Carballedo, Angela, Ching, Christopher R. K., Dannlowski, Udo, Dohm, Katharina, Enneking, Verena, Filimonova, Elena, Fingas, Stella M., Frodl, Thomas, Godlewska, Beata R., Goltermann, Janik, Gotlib, Ian H., Grotegerd, Dominik, Gruber, Oliver, Harris, Mathew A., Hatton, Sean N., Hawkins, Emma, Hickie, Ian B., Jaworska, Natalia, Kircher, Tilo, Krug, Axel, Lagopoulos, Jim, Lemke, Hannah, Li, Meng, MacMaster, Frank P., McIntosh, Andrew M., McLellan, Quinn, Meinert, Susanne, Mwangi, Benson, Nenadić, Igor, Osipov, Evgeny, Portella, Maria J., Redlich, Ronny, Repple, Jonathan, Sacchet, Matthew D., Sämann, Philipp G., Simulionyte, Egle, Soares, Jair C., Walter, Martin, Watanabe, Norio, Whalley, Heather C., Yüksel, Dilara, Veltman, Dick J., Thompson, Paul M., Schmaal, Lianne, and Van Someren, Eus J. W.

Published
2020
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