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7. 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

8. 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

9. 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

10. 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

11. Genetic, Individual, and Familial Risk Correlates of Brain Network Controllability in Major Depressive Disorder

Author

Hahn, Tim, Winter, Nils R., Ernsting, Jan, Gruber, Marius, Mauritz, Marco J., Fisch, Lukas, Leenings, Ramona, Sarink, Kelvin, Blanke, Julian, Holstein, Vincent, Emden, Daniel, Beisemann, Marie, Opel, Nils, Grotegerd, Dominik, Meinert, Susanne, Heindel, Walter, Witt, Stephanie, Rietschel, Marcella, Nöthen, Markus M., Forstner, Andreas J., Kircher, Tilo, Nenadic, Igor, Jansen, Andreas, Müller-Myhsok, Bertram, Andlauer, Till F. M., Walter, Martin, Heuvel, Martijn P. van den, Jamalabadi, Hamidreza, Dannlowski, Udo, and Repple, Jonathan

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

Background: A therapeutic intervention in psychiatry can be viewed as an attempt to influence the brain's large-scale, dynamic network state transitions underlying cognition and behavior. Building on connectome-based graph analysis and control theory, Network Control Theory is emerging as a powerful tool to quantify network controllability - i.e., the influence of one brain region over others regarding dynamic network state transitions. If and how network controllability is related to mental health remains elusive. Methods: From Diffusion Tensor Imaging data, we inferred structural connectivity and inferred calculated network controllability parameters to investigate their association with genetic and familial risk in patients diagnosed with major depressive disorder (MDD, n=692) and healthy controls (n=820). Results: First, we establish that controllability measures differ between healthy controls and MDD patients while not varying with current symptom severity or remission status. Second, we show that controllability in MDD patients is associated with polygenic scores for MDD and psychiatric cross-disorder risk. Finally, we provide evidence that controllability varies with familial risk of MDD and bipolar disorder as well as with body mass index. Conclusions: We show that network controllability is related to genetic, individual, and familial risk in MDD patients. We discuss how these insights into individual variation of network controllability may inform mechanistic models of treatment response prediction and personalized intervention-design in mental health., Comment: 24 pages, 1 figure

Published
2021

12. Multiparametric chemical exchange saturation transfer MRI detects metabolic changes in breast cancer following immunotherapy

Author

Hoffmann, Emily, Schache, Daniel, Höltke, Carsten, Soltwisch, Jens, Niland, Stephan, Krähling, Tobias, Bergander, Klaus, Grewer, Martin, Geyer, Christiane, Groeneweg, Linda, Eble, Johannes A., Vogl, Thomas, Roth, Johannes, Heindel, Walter, Maus, Bastian, Helfen, Anne, Faber, Cornelius, Wildgruber, Moritz, Gerwing, Mirjam, and Hoerr, Verena

Published
2023
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14. 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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16. Genetic, individual, and familial risk correlates of brain network controllability in major depressive disorder

Author

Hahn, Tim, Winter, Nils R., Ernsting, Jan, Gruber, Marius, Mauritz, Marco J., Fisch, Lukas, Leenings, Ramona, Sarink, Kelvin, Blanke, Julian, Holstein, Vincent, Emden, Daniel, Beisemann, Marie, Opel, Nils, Grotegerd, Dominik, Meinert, Susanne, Heindel, Walter, Witt, Stephanie, Rietschel, Marcella, Nöthen, Markus M., Forstner, Andreas J., Kircher, Tilo, Nenadic, Igor, Jansen, Andreas, Müller-Myhsok, Bertram, Andlauer, Till F. M., Walter, Martin, van den Heuvel, Martijn P., Jamalabadi, Hamidreza, Dannlowski, Udo, and Repple, Jonathan

Published
2023
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20. Analysis of the Predictability of Postoperative Meningioma Resection Status Based on Clinical Features.

Author

Musigmann, Manfred, Akkurt, Burak Han, Krähling, Hermann, Brokinkel, Benjamin, Spille, Dorothee Cäcilia, Stummer, Walter, Heindel, Walter, and Mannil, Manoj

Subjects
PREDICTION models, TUMOR grading, RETROSPECTIVE studies, DESCRIPTIVE statistics, SURGICAL complications, LONGITUDINAL method, MENINGIOMA, MEDICAL records, ACQUISITION of data, DECISION trees, SENSITIVITY & specificity (Statistics), SYMPTOMS
Abstract

Simple Summary: This study explored the predictability of meningioma resection status (gross total vs. subtotal) based on clinical features. We analyzed 23 features to determine their effectiveness in forecasting resection outcomes, comparing predictions based on the Simpson grading system and postoperative tumor volume (POTV). Using data from 157 patients, our developed models demonstrated high accuracy with only two key features, achieving an average AUC of 0.885 and accuracy of 0.866. The final model, a simple decision tree, may be useful for guiding decisions for surgical planning and postoperative treatments. Background: Our aim was to investigate the predictability of postoperative meningioma resection status based on clinical features. Methods: We examined 23 clinical features to assess their effectiveness in distinguishing gross total resections (GTR) from subtotal resections (STR). We analyzed whether GTR/STR cases are better predictable if the classification is based on the Simpson grading or the postoperative operative tumor volume (POTV). Results: Using a study cohort comprising a total of 157 patients, multivariate models for the preoperative prediction of GTR/STR outcome in relation to Simpson grading and POTV were developed and subsequently compared. Including only two clinical features, our models showed a notable discriminatory power in predicting postoperative resection status. Our final model, a straightforward decision tree applicable in daily clinical practice, achieved a mean AUC of 0.885, a mean accuracy of 0.866, a mean sensitivity of 0.889, and a mean specificity of 0.772 based on independent test data. Conclusions: Such models can be a valuable tool both for surgical planning and for early planning of postoperative treatment, e.g., for additional radiotherapy/radiosurgery, potentially required in case of subtotal resections. [ABSTRACT FROM AUTHOR]

Published
2024
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22. Longitudinal Structural Brain Changes in Bipolar Disorder: A Multicenter Neuroimaging Study of 1232 Individuals by the ENIGMA Bipolar Disorder Working Group

Author

Abé, Christoph, Ching, Christopher R.K., Liberg, Benny, Lebedev, Alexander V., Agartz, Ingrid, Akudjedu, Theophilus N., Alda, Martin, Alnæs, Dag, Alonso-Lana, Silvia, Benedetti, Francesco, Berk, Michael, Bøen, Erlend, Bonnin, Caterina del Mar, Breuer, Fabian, Brosch, Katharina, Brouwer, Rachel M., Canales-Rodríguez, Erick J., Cannon, Dara M., Chye, Yann, Dahl, Andreas, Dandash, Orwa, Dannlowski, Udo, Dohm, Katharina, Elvsåshagen, Torbjørn, Fisch, Lukas, Fullerton, Janice M., Goikolea, Jose M., Grotegerd, Dominik, Haatveit, Beathe, Hahn, Tim, Hajek, Tomas, Heindel, Walter, Ingvar, Martin, Sim, Kang, Kircher, Tilo T.J., Lenroot, Rhoshel K., Malt, Ulrik F., McDonald, Colm, McWhinney, Sean R., Melle, Ingrid, Meller, Tina, Melloni, Elisa M.T., Mitchell, Philip B., Nabulsi, Leila, Nenadić, Igor, Opel, Nils, Overs, Bronwyn J., Panicalli, Francesco, Pfarr, Julia-Katharina, Poletti, Sara, Pomarol-Clotet, Edith, Radua, Joaquim, Repple, Jonathan, Ringwald, Kai G., Roberts, Gloria, Rodriguez-Cano, Elena, Salvador, Raymond, Sarink, Kelvin, Sarró, Salvador, Schmitt, Simon, Stein, Frederike, Suo, Chao, Thomopoulos, Sophia I., Tronchin, Giulia, Vieta, Eduard, Westlye, Lars T., White, Adam G., Yatham, Lakshmi N., Zak, Nathalia, Thompson, Paul M., Andreassen, Ole A., and Landén, Mikael

Published
2022
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24. 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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33. Dose escalation and expansion phase I studies with the tumour-targeting antibody-tumour necrosis factor fusion protein L19TNF plus doxorubicin in patients with advanced tumours, including sarcomas

Author

Schliemann, Christoph, Hemmerle, Teresa, Berdel, Andrew F., Angenendt, Linus, Kerkhoff, Andrea, Hering, Jan P., Heindel, Walter, Hartmann, Wolfgang, Wardelmann, Eva, Chawla, Sant P., de Braud, Filippo, Lenz, Georg, Neri, Dario, Kessler, Torsten, and Berdel, Wolfgang E.

Published
2021
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36. 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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44. 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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49. 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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50. 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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