Simon Schmitt1,2,3, Tina Meller1,2, Frederike Stein1,2, Katharina Brosch1,2,3, Kai Ringwald1,2, Julia-Katharina Pfarr1,2, Clemens Bordin1, Nina Peusch1, Olaf Steinsträter1, Dominik Grotegerd4, Katharina Dohm4, Susanne Meinert4, Katharina Förster4, Ronny Redlich4,5, Nils Opel4, Tim Hahn4, Andreas Jansen1,2,6, Andreas J Forstner7,8,9, Fabian Streit10, Stephanie H Witt10, Marcella Rietschel10, Bertram Müller-Myhsok11,12,13, Markus M Nöthen8, Udo Dannlowski4, Axel Krug1,2,14, Tilo Kircher1,2,3, Igor Nenadić1,2,3. 1. Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Rudolf-Bultmann-Str. 8, 35039Marburg, Germany. 2. Center for Mind, Brain and Behavior (CMBB), Philipps-Universität Marburg and Justus Liebig Universität Giessen, Hans-Meerwein-Str. 6, 35032Marburg, Germany. 3. Marburg University Hospital - UKGM, Rudolf-Bultmann-Str. 8, 35039Marburg, Germany. 4. Department of Psychiatry, Westfälische Wilhelms-Universität Münster, Albert-Schweitzer-Campus 1, Building A9, 48149Münster, Germany. 5. Department of Psychology, University of Halle, Halle, Germany. 6. Faculty of Medicine, Core-Facility BrainImaging, Philipps-Universität Marburg, Rudolf-Bultmann-Str. 8, 35039, Germany. 7. Centre for Human Genetics, Philipps-Universität Marburg, Baldingerstr., 35033Marburg, Germany. 8. Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Venusberg-Campus 1, 53127Bonn, Germany. 9. Institute of Neuroscience and Medicine (INM-1), Research Center Jülich, Wilhelm-Johnen-Straße, 52428Jülich, Germany. 10. Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, J5, 68159Mannheim, Germany. 11. Munich Cluster for Systems Neurology (SyNergy), Feodor-Lynen-Str. 17, 81377Munich, Germany. 12. Institute of Translational Medicine, University of Liverpool, Crown Street, LiverpoolL69 3BX, UK. 13. Max-Planck-Institute of Psychiatry, Kraepelinstr. 2-10, 80804Munich, Germany. 14. Department of Psychiatry and Psychotherapy, University of Bonn, Bonn, Germany.
Abstract
BACKGROUND: MRI-derived cortical folding measures are an indicator of largely genetically driven early developmental processes. However, the effects of genetic risk for major mental disorders on early brain development are not well understood. METHODS: We extracted cortical complexity values from structural MRI data of 580 healthy participants using the CAT12 toolbox. Polygenic risk scores (PRS) for schizophrenia, bipolar disorder, major depression, and cross-disorder (incorporating cumulative genetic risk for depression, schizophrenia, bipolar disorder, autism spectrum disorder, and attention-deficit hyperactivity disorder) were computed and used in separate general linear models with cortical complexity as the regressand. In brain regions that showed a significant association between polygenic risk for mental disorders and cortical complexity, volume of interest (VOI)/region of interest (ROI) analyses were conducted to investigate additional changes in their volume and cortical thickness. RESULTS: The PRS for depression was associated with cortical complexity in the right orbitofrontal cortex (right hemisphere: p = 0.006). A subsequent VOI/ROI analysis showed no association between polygenic risk for depression and either grey matter volume or cortical thickness. We found no associations between cortical complexity and polygenic risk for either schizophrenia, bipolar disorder or psychiatric cross-disorder when correcting for multiple testing. CONCLUSIONS: Changes in cortical complexity associated with polygenic risk for depression might facilitate well-established volume changes in orbitofrontal cortices in depression. Despite the absence of psychopathology, changed cortical complexity that parallels polygenic risk for depression might also change reward systems, which are also structurally affected in patients with depressive syndrome.
BACKGROUND: MRI-derived cortical folding measures are an indicator of largely genetically driven early developmental processes. However, the effects of genetic risk for major mental disorders on early brain development are not well understood. METHODS: We extracted cortical complexity values from structural MRI data of 580 healthy participants using the CAT12 toolbox. Polygenic risk scores (PRS) for schizophrenia, bipolar disorder, major depression, and cross-disorder (incorporating cumulative genetic risk for depression, schizophrenia, bipolar disorder, autism spectrum disorder, and attention-deficit hyperactivity disorder) were computed and used in separate general linear models with cortical complexity as the regressand. In brain regions that showed a significant association between polygenic risk for mental disorders and cortical complexity, volume of interest (VOI)/region of interest (ROI) analyses were conducted to investigate additional changes in their volume and cortical thickness. RESULTS: The PRS for depression was associated with cortical complexity in the right orbitofrontal cortex (right hemisphere: p = 0.006). A subsequent VOI/ROI analysis showed no association between polygenic risk for depression and either grey matter volume or cortical thickness. We found no associations between cortical complexity and polygenic risk for either schizophrenia, bipolar disorder or psychiatric cross-disorder when correcting for multiple testing. CONCLUSIONS: Changes in cortical complexity associated with polygenic risk for depression might facilitate well-established volume changes in orbitofrontal cortices in depression. Despite the absence of psychopathology, changed cortical complexity that parallels polygenic risk for depression might also change reward systems, which are also structurally affected in patients with depressive syndrome.
Entities:
Keywords:
Bipolar disorder; brain development; cortical complexity; magnetic resonance imaging (MRI); major depressive disorder; polygenic risk; schizophrenia; surface-based morphometry
Authors: Susan S Kuo; David R Roalf; Konasale M Prasad; Christie W Musket; Petra E Rupert; Joel Wood; Ruben C Gur; Laura Almasy; Raquel E Gur; Vishwajit L Nimgaonkar; Michael F Pogue-Geile Journal: J Psychopathol Clin Sci Date: 2022-06-23
Authors: Anca-Larisa Sandu; Gordon D Waiter; Roger T Staff; Nafeesa Nazlee; Tina Habota; Chris J McNeil; Dorota Chapko; Justin H Williams; Caroline H D Fall; Giriraj R Chandak; Shailesh Pene; Murali Krishna; Andrew M McIntosh; Heather C Whalley; Kalyanaraman Kumaran; Ghattu V Krishnaveni; Alison D Murray Journal: Sci Rep Date: 2022-06-30 Impact factor: 4.996