1
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Winter NR, Blanke J, Leenings R, Ernsting J, Fisch L, Sarink K, Barkhau C, Emden D, Thiel K, Flinkenflügel K, Winter A, Goltermann J, Meinert S, Dohm K, Repple J, Gruber M, Leehr EJ, Opel N, Grotegerd D, Redlich R, Nitsch R, Bauer J, Heindel W, Gross J, Risse B, Andlauer TFM, Forstner AJ, Nöthen MM, Rietschel M, Hofmann SG, Pfarr JK, Teutenberg L, Usemann P, Thomas-Odenthal F, Wroblewski A, Brosch K, Stein F, Jansen A, Jamalabadi H, Alexander N, Straube B, Nenadić I, Kircher T, Dannlowski U, Hahn T. A Systematic Evaluation of Machine Learning-Based Biomarkers for Major Depressive Disorder. JAMA Psychiatry 2024; 81:386-395. [PMID: 38198165 PMCID: PMC10782379 DOI: 10.1001/jamapsychiatry.2023.5083] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Accepted: 11/05/2023] [Indexed: 01/11/2024]
Abstract
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.
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Affiliation(s)
- Nils R. Winter
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- Otto Creutzfeldt Center for Cognitive and Behavioral Neuroscience, University of Münster, Münster, Germany
| | - Julian Blanke
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Ramona Leenings
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- Faculty of Mathematics and Computer Science, University of Münster, Münster, Germany
| | - Jan Ernsting
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- Faculty of Mathematics and Computer Science, University of Münster, Münster, Germany
- Institute for Geoinformatics, University of Münster, Münster, Germany
| | - Lukas Fisch
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Kelvin Sarink
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Carlotta Barkhau
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Daniel Emden
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Katharina Thiel
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Kira Flinkenflügel
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Alexandra Winter
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Janik Goltermann
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Susanne Meinert
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- Institute for Translational Neuroscience, University of Münster, Münster, Germany
| | - Katharina Dohm
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Jonathan Repple
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital Frankfurt, Goethe University, Frankfurt am Main, Germany
| | - Marius Gruber
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital Frankfurt, Goethe University, Frankfurt am Main, Germany
| | - Elisabeth J. Leehr
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Nils Opel
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- Department of Psychiatry and Psychotherapy, University Hospital Jena, Jena, Germany
- Center for Intervention and Research on Adaptive and Maladaptive Brain Circuits Underlying Mental Health, Jena, Germany
- German Center for Mental Health (DZPG), Jena, Germany
| | - Dominik Grotegerd
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Ronny Redlich
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- Center for Intervention and Research on Adaptive and Maladaptive Brain Circuits Underlying Mental Health, Jena, Germany
- Department of Psychology, University of Halle, Halle, Germany
- German Center for Mental Health (DZPG), Halle, Germany
| | - Robert Nitsch
- Otto Creutzfeldt Center for Cognitive and Behavioral Neuroscience, University of Münster, Münster, Germany
- Institute for Translational Neuroscience, University of Münster, Münster, Germany
| | - Jochen Bauer
- Clinic for Radiology, University of Münster, University Hospital Münster, Münster, Germany
| | - Walter Heindel
- Clinic for Radiology, University of Münster, University Hospital Münster, Münster, Germany
| | - Joachim Gross
- Otto Creutzfeldt Center for Cognitive and Behavioral Neuroscience, University of Münster, Münster, Germany
- Institute for Biomagnetism and Biosignalanalysis, University of Münster, Münster, Germany
| | - Benjamin Risse
- Otto Creutzfeldt Center for Cognitive and Behavioral Neuroscience, University of Münster, Münster, Germany
- Faculty of Mathematics and Computer Science, University of Münster, Münster, Germany
- Institute for Geoinformatics, University of Münster, Münster, Germany
| | - Till F. M. Andlauer
- Department of Neurology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Andreas J. Forstner
- Institute of Human Genetics, University of Bonn, School of Medicine and University Hospital Bonn, Bonn, Germany
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany
| | - Markus M. Nöthen
- Institute of Human Genetics, University of Bonn, School of Medicine and University Hospital Bonn, Bonn, Germany
| | - Marcella Rietschel
- Department of Genetic Epidemiology, Central Institute of Mental Health, Faculty of Medicine Mannheim, University of Heidelberg, Mannheim, Germany
| | - Stefan G. Hofmann
- Department of Clinical Psychology, Philipps-University Marburg, Marburg, Germany
| | - Julia-Katharina Pfarr
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), Marburg, Germany
| | - Lea Teutenberg
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), Marburg, Germany
| | - Paula Usemann
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), Marburg, Germany
| | - Florian Thomas-Odenthal
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), Marburg, Germany
| | - Adrian Wroblewski
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), Marburg, Germany
| | - Katharina Brosch
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), Marburg, Germany
| | - Frederike Stein
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), Marburg, Germany
| | - Andreas Jansen
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), Marburg, Germany
- Core Facility Brain Imaging, Faculty of Medicine, Philipps-University Marburg, Marburg, Germany
| | - Hamidreza Jamalabadi
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany
| | - Nina Alexander
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), Marburg, Germany
| | - Benjamin Straube
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), Marburg, Germany
| | - Igor Nenadić
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), Marburg, Germany
| | - Tilo Kircher
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), Marburg, Germany
| | - Udo Dannlowski
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- Otto Creutzfeldt Center for Cognitive and Behavioral Neuroscience, University of Münster, Münster, Germany
| | - Tim Hahn
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- Otto Creutzfeldt Center for Cognitive and Behavioral Neuroscience, University of Münster, Münster, Germany
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2
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Thiel K, Meinert S, Winter A, Lemke H, Waltemate L, Breuer F, Gruber M, Leenings R, Wüste L, Rüb K, Pfarr JK, Stein F, Brosch K, Meller T, Ringwald KG, Nenadić I, Krug A, Repple J, Opel N, Koch K, Leehr EJ, Bauer J, Grotegerd D, Hahn T, Kircher T, Dannlowski U. Reduced fractional anisotropy in bipolar disorder v. major depressive disorder independent of current symptoms. Psychol Med 2023; 53:4592-4602. [PMID: 35833369 PMCID: PMC10388324 DOI: 10.1017/s0033291722001490] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/21/2022] [Revised: 04/28/2022] [Accepted: 05/05/2022] [Indexed: 11/07/2022]
Abstract
BACKGROUND Patients with bipolar disorder (BD) show reduced fractional anisotropy (FA) compared to patients with major depressive disorder (MDD). Little is known about whether these differences are mood state-independent or influenced by acute symptom severity. Therefore, the aim of this study was (1) to replicate abnormalities in white matter microstructure in BD v. MDD and (2) to investigate whether these vary across depressed, euthymic, and manic mood. METHODS In this cross-sectional diffusion tensor imaging study, n = 136 patients with BD were compared to age- and sex-matched MDD patients and healthy controls (HC) (n = 136 each). Differences in FA were investigated using tract-based spatial statistics. Using interaction models, the influence of acute symptom severity and mood state on the differences between patient groups were tested. RESULTS Analyses revealed a main effect of diagnosis on FA across all three groups (ptfce-FWE = 0.003). BD patients showed reduced FA compared to both MDD (ptfce-FWE = 0.005) and HC (ptfce-FWE < 0.001) in large bilateral clusters. These consisted of several white matter tracts previously described in the literature, including commissural, association, and projection tracts. There were no significant interaction effects between diagnosis and symptom severity or mood state (all ptfce-FWE > 0.704). CONCLUSIONS Results indicated that the difference between BD and MDD was independent of depressive and manic symptom severity and mood state. Disruptions in white matter microstructure in BD might be a trait effect of the disorder. The potential of FA values to be used as a biomarker to differentiate BD from MDD should be further addressed in future studies using longitudinal designs.
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Affiliation(s)
- Katharina Thiel
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Susanne Meinert
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- Institute of Translational Neuroscience, University of Münster, Münster, Germany
| | - Alexandra Winter
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Hannah Lemke
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Lena Waltemate
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Fabian Breuer
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Marius Gruber
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Ramona Leenings
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Lucia Wüste
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Kathrin Rüb
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | | | - Frederike Stein
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
| | - Katharina Brosch
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
| | - Tina Meller
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
| | - Kai Gustav Ringwald
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
| | - Igor Nenadić
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
| | - Axel Krug
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
- Department of Psychiatry and Psychotherapy, University Hospital Bonn, Bonn, Germany
| | - Jonathan Repple
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Nils Opel
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Katharina Koch
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Elisabeth J. Leehr
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Jochen Bauer
- Department of Clinical Radiology, University of Muenster, Muenster, Germany
| | - Dominik Grotegerd
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Tim Hahn
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Tilo Kircher
- Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
| | - Udo Dannlowski
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
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3
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Hahn T, Winter NR, Ernsting J, Gruber M, Mauritz MJ, Fisch L, Leenings R, Sarink K, Blanke J, Holstein V, Emden D, Beisemann M, Opel N, Grotegerd D, Meinert S, Heindel W, Witt S, Rietschel M, Nöthen MM, Forstner AJ, Kircher T, Nenadic I, Jansen A, Müller-Myhsok B, Andlauer TFM, Walter M, van den Heuvel MP, Jamalabadi H, Dannlowski U, Repple J. Genetic, individual, and familial risk correlates of brain network controllability in major depressive disorder. Mol Psychiatry 2023; 28:1057-1063. [PMID: 36639510 PMCID: PMC10005934 DOI: 10.1038/s41380-022-01936-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Revised: 12/14/2022] [Accepted: 12/16/2022] [Indexed: 01/15/2023]
Abstract
Many therapeutic interventions in psychiatry can be viewed as attempts to influence the brain's large-scale, dynamic network state transitions. 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. Here, 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). 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. In summary, 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.
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Affiliation(s)
- Tim Hahn
- Institute for Translational Psychiatry, University of Münster, Münster, Germany.
| | - Nils R Winter
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Jan Ernsting
- Institute for Translational Psychiatry, University of Münster, Münster, Germany.,Faculty of Mathematics and Computer Science, University of Münster, Münster, Germany
| | - Marius Gruber
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Marco J Mauritz
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Lukas Fisch
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Ramona Leenings
- Institute for Translational Psychiatry, University of Münster, Münster, Germany.,Faculty of Mathematics and Computer Science, University of Münster, Münster, Germany
| | - Kelvin Sarink
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Julian Blanke
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Vincent Holstein
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Daniel Emden
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Marie Beisemann
- Department of Statistics, TU Dortmund University, Dortmund, Germany
| | - Nils Opel
- Institute for Translational Psychiatry, University of Münster, Münster, Germany.,Interdisciplinary Centre for Clinical Research IZKF, University of Münster, Münster, Germany
| | - Dominik Grotegerd
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Susanne Meinert
- Institute for Translational Psychiatry, University of Münster, Münster, Germany.,Institute for Translational Neuroscience, University of Münster, Münster, Germany
| | - Walter Heindel
- Institute of Clinical Radiology, University of Münster, Münster, Germany
| | - Stephanie Witt
- Department of Genetic Epidemiology, Central Institute of Mental Health, Faculty of Medicine Mannheim, University of Heidelberg, Mannheim, Germany
| | - Marcella Rietschel
- Department of Genetic Epidemiology, Central Institute of Mental Health, Faculty of Medicine Mannheim, University of Heidelberg, Mannheim, Germany
| | - Markus M Nöthen
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
| | - Andreas J Forstner
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
| | - Tilo Kircher
- Department of Psychiatry and Psychotherapy, Phillips University Marburg, Marburg, Germany
| | - Igor Nenadic
- Department of Psychiatry and Psychotherapy, Phillips University Marburg, Marburg, Germany
| | - Andreas Jansen
- Department of Psychiatry and Psychotherapy, Phillips University Marburg, Marburg, Germany.,Core-Facility Brainimaging, Faculty of Medicine, University of Marburg, Marburg, Germany
| | | | - Till F M Andlauer
- Department of Neurology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Martin Walter
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany
| | - Martijn P van den Heuvel
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands.,Department of Child Psychiatry, Amsterdam University Medical Center, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Hamidreza Jamalabadi
- Department of Psychiatry and Psychotherapy, Phillips University Marburg, Marburg, Germany
| | - Udo Dannlowski
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Jonathan Repple
- Institute for Translational Psychiatry, University of Münster, Münster, Germany.,Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital Frankfurt, Goethe University, Frankfurt, Germany
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4
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Hahn T, Jamalabadi H, Nozari E, Winter NR, Ernsting J, Gruber M, Mauritz MJ, Grumbach P, Fisch L, Leenings R, Sarink K, Blanke J, Vennekate LK, Emden D, Opel N, Grotegerd D, Enneking V, Meinert S, Borgers T, Klug M, Leehr EJ, Dohm K, Heindel W, Gross J, Dannlowski U, Redlich R, Repple J. Towards a network control theory of electroconvulsive therapy response. PNAS Nexus 2023; 2:pgad032. [PMID: 36874281 PMCID: PMC9982063 DOI: 10.1093/pnasnexus/pgad032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/08/2022] [Revised: 12/09/2022] [Accepted: 01/17/2023] [Indexed: 02/04/2023]
Abstract
Electroconvulsive Therapy (ECT) is arguably the most effective intervention for treatment-resistant depression. While large interindividual variability exists, a theory capable of explaining 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.
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Affiliation(s)
- Tim Hahn
- Institute for Translational Psychiatry, University of Münster, 48149 Münster, Germany
| | - Hamidreza Jamalabadi
- Department of Psychiatry and Psychotherapy, University of Tübingen, 72076 Tübingen, Germany
| | - Erfan Nozari
- Department of Mechanical Engineering, University of California, 92521 Riverside, USA
| | - Nils R Winter
- Institute for Translational Psychiatry, University of Münster, 48149 Münster, Germany
| | - Jan Ernsting
- Institute for Translational Psychiatry, University of Münster, 48149 Münster, Germany.,Faculty of Mathematics and Computer Science, University of Münster, 48149 Münster, Germany
| | - Marius Gruber
- Institute for Translational Psychiatry, University of Münster, 48149 Münster, Germany
| | - Marco J Mauritz
- Institute for Translational Psychiatry, University of Münster, 48149 Münster, Germany
| | - Pascal Grumbach
- Institute for Translational Psychiatry, University of Münster, 48149 Münster, Germany
| | - Lukas Fisch
- Institute for Translational Psychiatry, University of Münster, 48149 Münster, Germany
| | - Ramona Leenings
- Institute for Translational Psychiatry, University of Münster, 48149 Münster, Germany.,Faculty of Mathematics and Computer Science, University of Münster, 48149 Münster, Germany
| | - Kelvin Sarink
- Institute for Translational Psychiatry, University of Münster, 48149 Münster, Germany
| | - Julian Blanke
- Institute for Translational Psychiatry, University of Münster, 48149 Münster, Germany
| | - Leon Kleine Vennekate
- Institute for Translational Psychiatry, University of Münster, 48149 Münster, Germany
| | - Daniel Emden
- Institute for Translational Psychiatry, University of Münster, 48149 Münster, Germany
| | - Nils Opel
- Institute for Translational Psychiatry, University of Münster, 48149 Münster, Germany
| | - Dominik Grotegerd
- Institute for Translational Psychiatry, University of Münster, 48149 Münster, Germany
| | - Verena Enneking
- Institute for Translational Psychiatry, University of Münster, 48149 Münster, Germany
| | - Susanne Meinert
- Institute for Translational Psychiatry, University of Münster, 48149 Münster, Germany.,Institute for Translational Neuroscience, University of Münster, 48149 Münster, Germany
| | - Tiana Borgers
- Institute for Translational Psychiatry, University of Münster, 48149 Münster, Germany
| | - Melissa Klug
- Institute for Translational Psychiatry, University of Münster, 48149 Münster, Germany
| | - Elisabeth J Leehr
- Institute for Translational Psychiatry, University of Münster, 48149 Münster, Germany
| | - Katharina Dohm
- Institute for Translational Psychiatry, University of Münster, 48149 Münster, Germany
| | - Walter Heindel
- Institute of Clinical Radiology, University of Münster, 48149 Münster, Germany
| | - Joachim Gross
- Institute for Biomagnetism and Biosignalanalysis, University Hospital Münster, 48149 Münster, Germany
| | - Udo Dannlowski
- Institute for Translational Psychiatry, University of Münster, 48149 Münster, Germany
| | - Ronny Redlich
- Institute for Translational Psychiatry, University of Münster, 48149 Münster, Germany.,Department of Psychology, University of Halle, 06099 Halle (Saale), Germany
| | - Jonathan Repple
- Institute for Translational Psychiatry, University of Münster, 48149 Münster, Germany
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5
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Han LK, Dinga R, Leenings R, Hahn T, Cole JH, Aftanas LI, Amod AR, Besteher B, Colle R, Corruble E, Couvy-Duchesne B, Danilenko KV, Fuentes-Claramonte P, Gonul AS, Gotlib IH, Goya-Maldonado R, Groenewold NA, Hamilton P, Ichikawa N, Ipser JC, Itai E, Koopowitz SM, Li M, Okada G, Okamoto Y, Churikova OS, Osipov EA, Penninx BW, Pomarol-Clotet E, Rodríguez-Cano E, Sacchet MD, Shinzato H, Sim K, Stein DJ, Uyar-Demir A, Veltman DJ, Schmaal L. A large-scale ENIGMA multisite replication study of brain age in depression. Neuroimage: Reports 2022. [DOI: 10.1016/j.ynirp.2022.100149] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/05/2022]
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6
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Winter NR, Leenings R, Ernsting J, Sarink K, Fisch L, Emden D, Blanke J, Goltermann J, Opel N, Barkhau C, Meinert S, Dohm K, Repple J, Mauritz M, Gruber M, Leehr EJ, Grotegerd D, Redlich R, Jansen A, Nenadic I, Nöthen MM, Forstner A, Rietschel M, Groß J, Bauer J, Heindel W, Andlauer T, Eickhoff SB, Kircher T, Dannlowski U, Hahn T. Quantifying Deviations of Brain Structure and Function in Major Depressive Disorder Across Neuroimaging Modalities. JAMA Psychiatry 2022; 79:879-888. [PMID: 35895072 PMCID: PMC9330277 DOI: 10.1001/jamapsychiatry.2022.1780] [Citation(s) in RCA: 46] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
IMPORTANCE Identifying neurobiological differences between patients with major depressive disorder (MDD) and healthy individuals has been a mainstay of clinical neuroscience for decades. However, recent meta-analyses have raised concerns regarding the replicability and clinical relevance of brain alterations in depression. OBJECTIVE To quantify the upper bounds of univariate effect sizes, estimated predictive utility, and distributional dissimilarity of healthy individuals and those with depression across structural magnetic resonance imaging (MRI), diffusion-tensor imaging, and functional task-based as well as resting-state MRI, and to compare results with an MDD polygenic risk score (PRS) and environmental variables. DESIGN, SETTING, AND PARTICIPANTS This was a cross-sectional, case-control clinical neuroimaging study. Data were part of the Marburg-Münster Affective Disorders Cohort Study. Patients with depression and healthy controls were recruited from primary care and the general population in Münster and Marburg, Germany. Study recruitment was performed from September 11, 2014, to September 26, 2018. The sample comprised patients with acute and chronic MDD as well as healthy controls in the age range of 18 to 65 years. Data were analyzed from October 29, 2020, to April 7, 2022. MAIN OUTCOMES AND MEASURES Primary analyses included univariate partial effect size (η2), classification accuracy, and distributional overlapping coefficient for healthy individuals and those with depression across neuroimaging modalities, controlling for age, sex, and additional modality-specific confounding variables. Secondary analyses included patient subgroups for acute or chronic depressive status. RESULTS A total of 1809 individuals (861 patients [47.6%] and 948 controls [52.4%]) were included in the analysis (mean [SD] age, 35.6 [13.2] years; 1165 female patients [64.4%]). The upper bound of the effect sizes of the single univariate measures displaying the largest group difference ranged from partial η2 of 0.004 to 0.017, and distributions overlapped between 87% and 95%, with classification accuracies ranging between 54% and 56% across neuroimaging modalities. This pattern remained virtually unchanged when considering either only patients with acute or chronic depression. Differences were comparable with those found for PRS but substantially smaller than for environmental variables. CONCLUSIONS AND RELEVANCE Results of this case-control study suggest that even for maximum univariate biological differences, deviations between patients with MDD and healthy controls were remarkably small, single-participant prediction was not possible, and similarity between study groups dominated. Biological psychiatry should facilitate meaningful outcome measures or predictive approaches to increase the potential for a personalization of the clinical practice.
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Affiliation(s)
- Nils R. Winter
- University of Münster, Institute for Translational Psychiatry, Münster, Germany
| | - Ramona Leenings
- University of Münster, Institute for Translational Psychiatry, Münster, Germany,University of Münster, Department of Mathematics and Computer Science, Münster, Germany
| | - Jan Ernsting
- University of Münster, Institute for Translational Psychiatry, Münster, Germany,University of Münster, Department of Mathematics and Computer Science, Münster, Germany
| | - Kelvin Sarink
- University of Münster, Institute for Translational Psychiatry, Münster, Germany
| | - Lukas Fisch
- University of Münster, Institute for Translational Psychiatry, Münster, Germany
| | - Daniel Emden
- University of Münster, Institute for Translational Psychiatry, Münster, Germany
| | - Julian Blanke
- University of Münster, Institute for Translational Psychiatry, Münster, Germany
| | - Janik Goltermann
- University of Münster, Institute for Translational Psychiatry, Münster, Germany
| | - Nils Opel
- University of Münster, Institute for Translational Psychiatry, Münster, Germany
| | - Carlotta Barkhau
- University of Münster, Institute for Translational Psychiatry, Münster, Germany
| | - Susanne Meinert
- University of Münster, Institute for Translational Psychiatry, Münster, Germany,University of Münster, Institute for Translational Neuroscience, Münster, Germany
| | - Katharina Dohm
- University of Münster, Institute for Translational Psychiatry, Münster, Germany
| | - Jonathan Repple
- University of Münster, Institute for Translational Psychiatry, Münster, Germany
| | - Marco Mauritz
- University of Münster, Institute for Translational Psychiatry, Münster, Germany
| | - Marius Gruber
- University of Münster, Institute for Translational Psychiatry, Münster, Germany
| | - Elisabeth J. Leehr
- University of Münster, Institute for Translational Psychiatry, Münster, Germany
| | - Dominik Grotegerd
- University of Münster, Institute for Translational Psychiatry, Münster, Germany
| | - Ronny Redlich
- University of Münster, Institute for Translational Psychiatry, Münster, Germany,Institute of Psychology, University of Halle, Halle, Germany
| | - Andreas Jansen
- Department of Psychiatry and Psychotherapy, Philipps University Marburg, Marburg, Germany
| | - Igor Nenadic
- Department of Psychiatry and Psychotherapy, Philipps University Marburg, Marburg, Germany
| | - Markus M. Nöthen
- Institute of Human Genetics, University of Bonn, School of Medicine and University Hospital Bonn, Bonn, Germany
| | - Andreas Forstner
- Institute of Human Genetics, University of Bonn, School of Medicine and University Hospital Bonn, Bonn, Germany,Centre for Human Genetics, University of Marburg, Marburg, Germany,Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany
| | - Marcella Rietschel
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Joachim Groß
- Institute for Biomagnetism and Biosignalanalysis, University of Münster, Münster, Germany
| | - Jochen Bauer
- Department of Clinical Radiology, University of Münster, Münster, Germany
| | - Walter Heindel
- Department of Clinical Radiology, University of Münster, Münster, Germany
| | - Till Andlauer
- Department of Neurology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Simon B. Eickhoff
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany,Institute of Neuroscience and Medicine (INM-7), Research Centre Jülich, Jülich, Germany
| | - Tilo Kircher
- Department of Psychiatry and Psychotherapy, Philipps University Marburg, Marburg, Germany
| | - Udo Dannlowski
- University of Münster, Institute for Translational Psychiatry, Münster, Germany
| | - Tim Hahn
- University of Münster, Institute for Translational Psychiatry, Münster, Germany
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7
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Leenings R, Winter NR, Dannlowski U, Hahn T. Recommendations for machine learning benchmarks in neuroimaging. Neuroimage 2022; 257:119298. [PMID: 35561945 DOI: 10.1016/j.neuroimage.2022.119298] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Revised: 04/19/2022] [Accepted: 05/09/2022] [Indexed: 11/30/2022] Open
Abstract
The field of neuroimaging has embraced methods from machine learning in a variety of ways. Although an increasing number of initiatives have published open-access neuroimaging datasets, specifically designed benchmarks are rare in the field. In this article, we first describe how benchmarks in computer science and biomedical imaging have fostered methodological progress in machine learning. Second, we identify the special characteristics of neuroimaging data and outline what researchers have to ensure when establishing a neuroimaging benchmark, how datasets should be composed and how adequate evaluation criteria can be chosen. Based on lessons learned from machine learning benchmarks, we argue for an extended evaluation procedure that, next to applying suitable performance metrics, focuses on scientifically relevant aspects such as explainability, robustness, uncertainty, computational efficiency and code quality. Lastly, we envision a collaborative neuroimaging benchmarking platform that combines the discussed aspects in a collaborative and agile framework, allowing researchers across disciplines to work together on the key predictive problems of the field of neuroimaging and psychiatry.
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Affiliation(s)
- Ramona Leenings
- University of Münster, Institute for Translational Psychiatry, Albert-Schweitzer-Campus 1, Münster 48149, Germany; University of Münster, Faculty of Mathematics and Computer Science, Münster, Germany.
| | - Nils R Winter
- University of Münster, Institute for Translational Psychiatry, Albert-Schweitzer-Campus 1, Münster 48149, Germany
| | - Udo Dannlowski
- University of Münster, Institute for Translational Psychiatry, Albert-Schweitzer-Campus 1, Münster 48149, Germany
| | - Tim Hahn
- University of Münster, Institute for Translational Psychiatry, Albert-Schweitzer-Campus 1, Münster 48149, Germany
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8
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Hahn T, Ernsting J, Winter NR, Holstein V, Leenings R, Beisemann M, Fisch L, Sarink K, Emden D, Opel N, Redlich R, Repple J, Grotegerd D, Meinert S, Hirsch JG, Niendorf T, Endemann B, Bamberg F, Kröncke T, Bülow R, Völzke H, von Stackelberg O, Sowade RF, Umutlu L, Schmidt B, Caspers S, Kugel H, Kircher T, Risse B, Gaser C, Cole JH, Dannlowski U, Berger K. An uncertainty-aware, shareable, and transparent neural network architecture for brain-age modeling. Sci Adv 2022; 8:eabg9471. [PMID: 34985964 PMCID: PMC8730629 DOI: 10.1126/sciadv.abg9471] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/08/2021] [Accepted: 11/11/2021] [Indexed: 06/14/2023]
Abstract
The deviation between chronological age and age predicted from neuroimaging data has been identified as a sensitive risk marker of cross-disorder brain changes, growing into a cornerstone of biological age research. However, machine learning models underlying the field do not consider uncertainty, thereby confounding results with training data density and variability. Also, existing models are commonly based on homogeneous training sets, often not independently validated, and cannot be shared because of data protection issues. Here, we introduce an uncertainty-aware, shareable, and transparent Monte Carlo dropout composite quantile regression (MCCQR) Neural Network trained on N = 10,691 datasets from the German National Cohort. The MCCQR model provides robust, distribution-free uncertainty quantification in high-dimensional neuroimaging data, achieving lower error rates compared with existing models. In two examples, we demonstrate that it prevents spurious associations and increases power to detect deviant brain aging. We make the pretrained model and code publicly available.
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Affiliation(s)
- Tim Hahn
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Jan Ernsting
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- Faculty of Mathematics and Computer Science, University of Münster, Münster, Germany
| | - Nils R. Winter
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Vincent Holstein
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Ramona Leenings
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- Faculty of Mathematics and Computer Science, University of Münster, Münster, Germany
| | - Marie Beisemann
- Department of Statistics, TU Dortmund University, Dortmund, Germany
| | - Lukas Fisch
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Kelvin Sarink
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Daniel Emden
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Nils Opel
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- Interdisciplinary Centre for Clinical Research (IZKF) of the Medical Faculty Münster, University of Münster, Münster, Germany
| | - Ronny Redlich
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
- Department of Psychology, University of Halle, Halle, Germany
| | - Jonathan Repple
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Dominik Grotegerd
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Susanne Meinert
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | | | - Thoralf Niendorf
- Berlin Ultrahigh Field Facility (B.U.F.F.), NAKO imaging site Berlin, Max-Delbrueck Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
| | - Beate Endemann
- Berlin Ultrahigh Field Facility (B.U.F.F.), NAKO imaging site Berlin, Max-Delbrueck Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
| | - Fabian Bamberg
- Department of Radiology, Medical Center–University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Thomas Kröncke
- Department of Diagnostic and Interventional Radiology, University Hospital Augsburg, Augsburg, Germany
| | - Robin Bülow
- Institute of Diagnostic Radiology and Neuroradiology, University of Greifswald, Greifswald, Germany
| | - Henry Völzke
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Oyunbileg von Stackelberg
- Department of Diagnostic and Interventional Radiology, University Hospital Heidelberg, Heidelberg, Germany
- Translational Lung Research Center, Member of the German Lung Research Center, Heidelberg, Germany
| | - Ramona Felizitas Sowade
- Department of Diagnostic and Interventional Radiology, University Hospital Heidelberg, Heidelberg, Germany
- Translational Lung Research Center, Member of the German Lung Research Center, Heidelberg, Germany
| | - Lale Umutlu
- Institute for Medical Informatics, Biometry and Epidemiology, University of Duisburg-Essen, Duisburg, Germany
| | - Börge Schmidt
- Institute for Medical Informatics, Biometry and Epidemiology, University of Duisburg-Essen, Duisburg, Germany
| | - Svenja Caspers
- Institute for Anatomy I, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, 40225 Düsseldorf, Germany
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, 52425 Jülich, Germany
| | - Harald Kugel
- Institute of Clinical Radiology, University of Münster, Münster, Germany
| | - Tilo Kircher
- Department of Psychiatry and Psychotherapy, Phillips University Marburg, Marburg, Germany
| | - Benjamin Risse
- Faculty of Mathematics and Computer Science, University of Münster, Münster, Germany
| | - Christian Gaser
- Department of Psychiatry and Psychotherapy, and Department of Neurology, Jena University Hospital, Jena, Germany
| | - James H. Cole
- Department of Neuroimaging, Institute of Psychiatry, Psychology, and Neuroscience, King’s College London, London, UK
- Computational, Cognitive and Clinical Neuroimaging Laboratory, Department King’s College, London, UK
| | - Udo Dannlowski
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Klaus Berger
- Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany
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9
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Pelin H, Ising M, Stein F, Meinert S, Meller T, Brosch K, Winter NR, Krug A, Leenings R, Lemke H, Nenadić I, Heilmann-Heimbach S, Forstner AJ, Nöthen MM, Opel N, Repple J, Pfarr J, Ringwald K, Schmitt S, Thiel K, Waltemate L, Winter A, Streit F, Witt S, Rietschel M, Dannlowski U, Kircher T, Hahn T, Müller-Myhsok B, Andlauer TFM. Identification of transdiagnostic psychiatric disorder subtypes using unsupervised learning. Neuropsychopharmacology 2021; 46:1895-1905. [PMID: 34127797 PMCID: PMC8429672 DOI: 10.1038/s41386-021-01051-0] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/28/2021] [Revised: 05/24/2021] [Accepted: 05/28/2021] [Indexed: 02/07/2023]
Abstract
Psychiatric disorders show heterogeneous symptoms and trajectories, with current nosology not accurately reflecting their molecular etiology and the variability and symptomatic overlap within and between diagnostic classes. This heterogeneity impedes timely and targeted treatment. Our study aimed to identify psychiatric patient clusters that share clinical and genetic features and may profit from similar therapies. We used high-dimensional data clustering on deep clinical data to identify transdiagnostic groups in a discovery sample (N = 1250) of healthy controls and patients diagnosed with depression, bipolar disorder, schizophrenia, schizoaffective disorder, and other psychiatric disorders. We observed five diagnostically mixed clusters and ordered them based on severity. The least impaired cluster 0, containing most healthy controls, showed general well-being. Clusters 1-3 differed predominantly regarding levels of maltreatment, depression, daily functioning, and parental bonding. Cluster 4 contained most patients diagnosed with psychotic disorders and exhibited the highest severity in many dimensions, including medication load. Depressed patients were present in all clusters, indicating that we captured different disease stages or subtypes. We replicated all but the smallest cluster 1 in an independent sample (N = 622). Next, we analyzed genetic differences between clusters using polygenic scores (PGS) and the psychiatric family history. These genetic variables differed mainly between clusters 0 and 4 (prediction area under the receiver operating characteristic curve (AUC) = 81%; significant PGS: cross-disorder psychiatric risk, schizophrenia, and educational attainment). Our results confirm that psychiatric disorders consist of heterogeneous subtypes sharing molecular factors and symptoms. The identification of transdiagnostic clusters advances our understanding of the heterogeneity of psychiatric disorders and may support the development of personalized treatments.
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Affiliation(s)
- Helena Pelin
- Max Planck Institute of Psychiatry, Munich, Germany.
- International Max Planck Research School for Translational Psychiatry, Munich, Germany.
| | - Marcus Ising
- Max Planck Institute of Psychiatry, Munich, Germany
| | - Frederike Stein
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), Marburg, Germany
| | - Susanne Meinert
- Institute for Translational Psychiatry, Westfälische Wilhelms-Universität Münster, Münster, Germany
| | - Tina Meller
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), Marburg, Germany
| | - Katharina Brosch
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), Marburg, Germany
| | - Nils R Winter
- Institute for Translational Psychiatry, Westfälische Wilhelms-Universität Münster, Münster, Germany
| | - Axel Krug
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg, Germany
- Department of Psychiatry and Psychotherapy, University of Bonn, Bonn, Germany
| | - Ramona Leenings
- Institute for Translational Psychiatry, Westfälische Wilhelms-Universität Münster, Münster, Germany
| | - Hannah Lemke
- Institute for Translational Psychiatry, Westfälische Wilhelms-Universität Münster, Münster, Germany
| | - Igor Nenadić
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), Marburg, Germany
| | - Stefanie Heilmann-Heimbach
- Institute of Human Genetics, University of Bonn School of Medicine & University Hospital Bonn, Bonn, Germany
| | - Andreas J Forstner
- Institute of Human Genetics, University of Bonn School of Medicine & University Hospital Bonn, Bonn, Germany
- Institute of Neuroscience and Medicine (INM-1), Research Center Jülich, Jülich, Germany
- Centre for Human Genetics, University of Marburg, Marburg, Germany
| | - Markus M Nöthen
- Institute of Human Genetics, University of Bonn School of Medicine & University Hospital Bonn, Bonn, Germany
| | - Nils Opel
- Institute for Translational Psychiatry, Westfälische Wilhelms-Universität Münster, Münster, Germany
| | - Jonathan Repple
- Institute for Translational Psychiatry, Westfälische Wilhelms-Universität Münster, Münster, Germany
| | - Julia Pfarr
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg, Germany
| | - Kai Ringwald
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), Marburg, Germany
| | - Simon Schmitt
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), Marburg, Germany
| | - Katharina Thiel
- Institute for Translational Psychiatry, Westfälische Wilhelms-Universität Münster, Münster, Germany
| | - Lena Waltemate
- Institute for Translational Psychiatry, Westfälische Wilhelms-Universität Münster, Münster, Germany
| | - Alexandra Winter
- Institute for Translational Psychiatry, Westfälische Wilhelms-Universität Münster, Münster, Germany
| | - Fabian Streit
- Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Stephanie Witt
- Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Marcella Rietschel
- Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Udo Dannlowski
- Institute for Translational Psychiatry, Westfälische Wilhelms-Universität Münster, Münster, Germany
| | - Tilo Kircher
- Department of Psychiatry and Psychotherapy, Philipps-Universität Marburg, Marburg, Germany
- Center for Mind, Brain and Behavior (CMBB), Marburg, Germany
| | - Tim Hahn
- Institute for Translational Psychiatry, Westfälische Wilhelms-Universität Münster, Münster, Germany
| | - Bertram Müller-Myhsok
- Max Planck Institute of Psychiatry, Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
- Institute of Translational Medicine, University of Liverpool, Liverpool, UK
| | - Till F M Andlauer
- Max Planck Institute of Psychiatry, Munich, Germany.
- Department of Neurology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany.
- Global Computational Biology and Data Sciences, Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach an der Riß, Germany.
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10
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Han LKM, Dinga R, Hahn T, Ching CRK, Eyler LT, Aftanas L, Aghajani M, Aleman A, Baune BT, Berger K, Brak I, Filho GB, Carballedo A, Connolly CG, Couvy-Duchesne B, Cullen KR, Dannlowski U, Davey CG, Dima D, Duran FLS, Enneking V, Filimonova E, Frenzel S, Frodl T, Fu CHY, Godlewska BR, Gotlib IH, Grabe HJ, Groenewold NA, Grotegerd D, Gruber O, Hall GB, Harrison BJ, Hatton SN, Hermesdorf M, Hickie IB, Ho TC, Hosten N, Jansen A, Kähler C, Kircher T, Klimes-Dougan B, Krämer B, Krug A, Lagopoulos J, Leenings R, MacMaster FP, MacQueen G, McIntosh A, McLellan Q, McMahon KL, Medland SE, Mueller BA, Mwangi B, Osipov E, Portella MJ, Pozzi E, Reneman L, Repple J, Rosa PGP, Sacchet MD, Sämann PG, Schnell K, Schrantee A, Simulionyte E, Soares JC, Sommer J, Stein DJ, Steinsträter O, Strike LT, Thomopoulos SI, van Tol MJ, Veer IM, Vermeiren RRJM, Walter H, van der Wee NJA, van der Werff SJA, Whalley H, Winter NR, Wittfeld K, Wright MJ, Wu MJ, Völzke H, Yang TT, Zannias V, de Zubicaray GI, Zunta-Soares GB, Abé C, Alda M, Andreassen OA, Bøen E, Bonnin CM, Canales-Rodriguez EJ, Cannon D, Caseras X, Chaim-Avancini TM, Elvsåshagen T, Favre P, Foley SF, Fullerton JM, Goikolea JM, Haarman BCM, Hajek T, Henry C, Houenou J, Howells FM, Ingvar M, Kuplicki R, Lafer B, Landén M, Machado-Vieira R, Malt UF, McDonald C, Mitchell PB, Nabulsi L, Otaduy MCG, Overs BJ, Polosan M, Pomarol-Clotet E, Radua J, Rive MM, Roberts G, Ruhe HG, Salvador R, Sarró S, Satterthwaite TD, Savitz J, Schene AH, Schofield PR, Serpa MH, Sim K, Soeiro-de-Souza MG, Sutherland AN, Temmingh HS, Timmons GM, Uhlmann A, Vieta E, Wolf DH, Zanetti MV, Jahanshad N, Thompson PM, Veltman DJ, Penninx BWJH, Marquand AF, Cole JH, Schmaal L. Brain aging in major depressive disorder: results from the ENIGMA major depressive disorder working group. Mol Psychiatry 2021; 26:5124-5139. [PMID: 32424236 PMCID: PMC8589647 DOI: 10.1038/s41380-020-0754-0] [Citation(s) in RCA: 97] [Impact Index Per Article: 32.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/10/2019] [Revised: 04/01/2020] [Accepted: 04/23/2020] [Indexed: 01/15/2023]
Abstract
Major depressive disorder (MDD) is associated with an increased risk of brain atrophy, aging-related diseases, and mortality. We examined potential advanced brain aging in adult MDD patients, and whether this process is associated with clinical characteristics in a large multicenter international dataset. We performed a mega-analysis by pooling brain measures derived from T1-weighted MRI scans from 19 samples worldwide. Healthy brain aging was estimated by predicting chronological age (18-75 years) from 7 subcortical volumes, 34 cortical thickness and 34 surface area, lateral ventricles and total intracranial volume measures separately in 952 male and 1236 female controls from the ENIGMA MDD working group. The learned model coefficients were applied to 927 male controls and 986 depressed males, and 1199 female controls and 1689 depressed females to obtain independent unbiased brain-based age predictions. The difference between predicted "brain age" and chronological age was calculated to indicate brain-predicted age difference (brain-PAD). On average, MDD patients showed a higher brain-PAD of +1.08 (SE 0.22) years (Cohen's d = 0.14, 95% CI: 0.08-0.20) compared with controls. However, this difference did not seem to be driven by specific clinical characteristics (recurrent status, remission status, antidepressant medication use, age of onset, or symptom severity). This highly powered collaborative effort showed subtle patterns of age-related structural brain abnormalities in MDD. Substantial within-group variance and overlap between groups were observed. Longitudinal studies of MDD and somatic health outcomes are needed to further assess the clinical value of these brain-PAD estimates.
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Grants
- RF1 AG041915 NIA NIH HHS
- G0802594 Medical Research Council
- R01 MH083968 NIMH NIH HHS
- MR/L010305/1 Medical Research Council
- R01 MH116147 NIMH NIH HHS
- T32 AG058507 NIA NIH HHS
- R01 HD050735 NICHD NIH HHS
- R21 MH113871 NIMH NIH HHS
- T35 AG026757 NIA NIH HHS
- R56 AG058854 NIA NIH HHS
- K23 MH090421 NIMH NIH HHS
- Wellcome Trust
- R61 AT009864 NCCIH NIH HHS
- P41 EB015922 NIBIB NIH HHS
- P20 GM121312 NIGMS NIH HHS
- R37 MH101495 NIMH NIH HHS
- P41 RR008079 NCRR NIH HHS
- T32 MH073526 NIMH NIH HHS
- 104036/Z/14/Z Wellcome Trust
- UL1 TR001872 NCATS NIH HHS
- Department of Health
- U54 EB020403 NIBIB NIH HHS
- R01 MH117601 NIMH NIH HHS
- MR/R024790/2 Medical Research Council
- K01 MH117442 NIMH NIH HHS
- R01 MH085734 NIMH NIH HHS
- R21 AT009173 NCCIH NIH HHS
- RF1 AG051710 NIA NIH HHS
- R01 AG059874 NIA NIH HHS
- CC was supported by NIH grants U54 EB020403, RF1 AG041915, RF1AG051710, P41EB015922, R01MH116147, and R56AG058854
- Russian Science Foundation (RSF)
- The study was supported by a grant from the German Federal Ministry of Education and Research (BMBF; grant FKZ-01ER0816 and FKZ-01ER1506)
- Dr. Busatto was supported by the funding agencies FAPESP and CNPq, Brazil
- Department of Health | National Health and Medical Research Council (NHMRC)
- Deutsche Forschungsgemeinschaft (German Research Foundation)
- This study was funded by National Health and Medical Research Council of Australia (NHMRC) Project Grants 1064643 (Principal Investigator BJH) and 1024570 (Principal Investigator CGD).
- Science Foundation Ireland (SFI)
- This work was supported by NIH grant R37 MH101495
- The Study of Health in Pomerania (SHIP) is part of the Community Medicine Research net (CMR) (http://www.medizin.uni-greifswald.de/icm) of the University Medicine Greifswald, which is supported by the German Federal State of Mecklenburg- West Pomerania. MRI scans in SHIP and SHIP-TREND have been supported by a joint grant from Siemens Healthineers, Erlangen, Germany and the Federal State of Mecklenburg-West Pomerania. This study was further supported by the EU-JPND Funding for BRIDGET (FKZ:01ED1615).
- Gratama Foundation, the Netherlands (2012/35 to NG)
- This work was partially supported by the Deutsche Forschungsgemeinschaft (DFG) via grants to OG (GR1950/5-1 and GR1950/10-1).
- This study was supported by the following National Health and Medical Research Council funding sources: Programme Grant (no. 566529), Centres of Clinical Research Excellence Grant (no. 264611), Australia Fellowship (no. 511921) and Clinical Research Fellowship (no. 402864).
- This study was funded by the National Institute of Mental health grant K23MH090421 (D. Cullen) and Biotechnology Research Center grant P41RR008079 (Center for Magnetic Resonance Research), the National Alliance for Research on Schizophrenia and Depression, the University of Minnesota Graduate School, and the Minnesota Medical Foundation. This work was carried out in part using computing resources at the University of Minnesota Supercomputing Institute.
- This work was funded by the German Research Foundation (DFG, grant FOR2107 KR 3822/7-2 to AK; FOR2107 KI 588/14-2 to TK and FOR2107 JA 1890/7-2 to AJ)
- The research leading to these results was supported by IMAGEMEND, which received funding from the European Community's Seventh Framework Programme (FP7/2007-2013) under grant agreement no. 602450. This paper reflects only the author’s views and the European Union is not liable for any use that may be made of the information contained therein. This work was also supported by a Wellcome Trust Strategic Award 104036/Z/14/Z
- The QTIM dataset was supported by the Australian National Health and Medical Research Council (Project Grants No. 496682 and 1009064) and US National Institute of Child Health and Human Development(RO1HD050735)
- MJP was funded by Ministerio de Ciencia e Innovación of Spanish Government (ISCIII) through a "Miguel Servet II" (CP16/00020)
- Jair C. Soares supported by the Pat Rutherford Chair in Psychiatry, UTHealth. Jair Soares has received research support from Allergan, Pfizer, Johnson & Johnson, Alquermes and COMPASS. He is a member of the speakers’ bureaus for Sunovion and Sanofi and he is a consultant for Johnson & Johnson.
- The QTIM dataset was supported by the Australian National Health and Medical Research Council (Project Grants No. 496682 and 1009064) and US National Institute of Child Health and Human Development (RO1HD050735)
- SIT was supported in part by NIH grants U54 EB020403, RF1 AG041915, RF1AG051710, P41EB015922, R01MH116147, and R56AG058854
- The CODE cohort was collected from studies funded by Lundbeck and the German Research Foundation (WA 1539/4-1, SCHN 1205/3-1, SCHR443/11-1)
- Canadian Institutes of Health Research (142255)
- Fundet by Research Council of Norway (223273, 248778, 273291), NIH (ENIGMA grants)
- Funded by the South-Eastern Norway Regional Health Authority and a research grant from Mrs. Throne-Holst.
- This work was supported by the Health Research Board, Ireland and the Irish Research Council
- The Cardiff dataset was supported through a 2010 NARSAD Young Investigator Award (ref: 17319) to Dr. Xavier Caseras
- This work was supported by the FRM (Fondation pour la recherche Biomédicale) "Bio-informatique pour la biologie" 2014 grant
- Canadian Institutes of Health Research (103703, 106469), Nova Scotia Health Research Foundation, Dalhousie Clinical Research Scholarship to T. Hajek, Brain & Behavior Research Foundation (formerly NARSAD) 2007 Young Investigator and 2015 Independent Investigator Awards to T. Hajek
- This work was supported by the University Research Council of the University of Cape Town and the National Research Foundation of South Africa.
- Australian NHMRC Program Grant 1037196 and Project Grants 1063960 and 1066177.
- This work was supported by research grants from Grenoble University Hospital
- This work was supported by the Generalitat de Catalunya (2014 SGR 1573) and Instituto de Salud Carlos III (CPII16/00018) and (PI14/01151 and PI14/01148).
- The DIADE dataset was suported by a ZonMW OOG 2007 grant (100-002-034). HG Ruhe was supported by a ZonMW VENI grant (016.126.059)
- JS is supported by the National Institute of General Medical Sciences (P20GM121312) and the National Insitute of Mental Health (R21MH113871)
- Dr. Mauricio was supported by the funding agencies CAPES, Brazil
- This study was supported by R01MH083968, Desert-Pacific Mental Illness Research Education and Clinical Center, and the US National Science Foundation (Science Gateways Community Institutes; XSEDE).
- GT's work was supported by the National Institutes of Health, Grant T35 AG026757/AG/NIA and the University of California San Diego, Stein Institute for Research on Aging
- "EV thanks the support of the Spanish Ministry of Science, Innovation and Universities (PI15/00283) integrated into the Plan Nacional de I+D+I y cofinanciado por el ISCIII-Subdirección General de Evaluación y el Fondo Europeo de Desarrollo Regional (FEDER); CIBERSAM; and the Comissionat per a Universitats i Recerca del DIUE de la Generalitat de Catalunya to the Bipolar Disorders Group (2017 SGR 1365) and the project SLT006/17/00357, from PERIS 2016-2020 (Departament de Salut). CERCA Programme/Generalitat de Catalunya. "
- Dr. Zanetti was supported by FAPESP, Brazil (grant no. 2013/03905-4).
- NIH grants R01 MH117601, R01 AG059874, U54 EB020403, RF1 AG041915, RF1AG051710, P41EB015922, R01MH116147, and R56AG058854
- PT was supported in part by NIH grants U54 EB020403, RF1 AG041915, RF1AG051710, P41EB015922, R01MH116147, and R56AG058854
- Dr Cole is funded by a UKRI Innovation Fellowship
- This work was supported by NIH grants U54 EB020403 and R01 MH116147. LS is supported by a NHMRC Career Development Fellowship (1140764).
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Affiliation(s)
- Laura K M Han
- Department of Psychiatry, Amsterdam Public Health and Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit & GGZinGeest, Amsterdam, The Netherlands.
| | - Richard Dinga
- Department of Psychiatry, Amsterdam Public Health and Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit & GGZinGeest, Amsterdam, The Netherlands
- Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, The Netherlands
| | - Tim Hahn
- Department of Psychiatry, University of Münster, Münster, Germany
| | - Christopher R K Ching
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Lisa T Eyler
- Desert-Pacific Mental Illness Research Education and Clinical Center, VA San Diego Healthcare, San Diego, CA, USA
- Department of Psychiatry, University of California San Diego, Los Angeles, CA, USA
| | - Lyubomir Aftanas
- FSSBI "Scientific Research Institute of Physiology & Basic Medicine", Laboratory of Affective, Cognitive & Translational Neuroscience, Novosibirsk, Russia
- Department of Neuroscience, Novosibirsk State University, Novosibirsk, Russia
| | - Moji Aghajani
- Department of Psychiatry, Amsterdam Public Health and Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit & GGZinGeest, Amsterdam, The Netherlands
| | - André Aleman
- Department of Neuroscience, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
- Department of Clinical and Developmental Neuropsychology, University of Groningen, Groningen, The Netherlands
| | - Bernhard T Baune
- Department of Psychiatry, University of Münster, Münster, Germany
- Department of Psychiatry, Melbourne Medical School, The University of Melbourne, Melbourne, VIC, Australia
- The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Melbourne, VIC, Australia
| | - Klaus Berger
- Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany
| | - Ivan Brak
- FSSBI "Scientific Research Institute of Physiology & Basic Medicine", Laboratory of Affective, Cognitive & Translational Neuroscience, Novosibirsk, Russia
- Laboratory of Experimental & Translational Neuroscience, Novosibirsk State University, Novosibirsk, Russia
| | - Geraldo Busatto Filho
- Laboratory of Psychiatric Neuroimaging (LIM-21), Instituto de Psiquiatria, Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, SP, Brazil
| | - Angela Carballedo
- Department for Psychiatry, Trinity College Dublin, Dublin, Ireland
- North Dublin Mental Health Services, Dublin, Ireland
| | - Colm G Connolly
- Department of Biomedical Sciences, Florida State University, Tallahassee, FL, USA
| | | | - Kathryn R Cullen
- Department of Psychiatry and Behavioral Sciences, University of Minnesota Medical School, Minneapolis, Minnesota, USA
| | - Udo Dannlowski
- Department of Psychiatry, University of Münster, Münster, Germany
| | - Christopher G Davey
- Orygen, The National Centre of Excellence in Youth Mental Health, Parkville, VIC, Australia
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, VIC, Australia
| | - Danai Dima
- Department of Psychology, School of Arts and Social Sciences, City, University of London, London, UK
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College, London, UK
| | - Fabio L S Duran
- Laboratory of Psychiatric Neuroimaging (LIM-21), Instituto de Psiquiatria, Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, SP, Brazil
| | - Verena Enneking
- Department of Psychiatry, University of Münster, Münster, Germany
| | - Elena Filimonova
- FSSBI "Scientific Research Institute of Physiology & Basic Medicine", Laboratory of Affective, Cognitive & Translational Neuroscience, Novosibirsk, Russia
| | - Stefan Frenzel
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | - Thomas Frodl
- Department for Psychiatry, Trinity College Dublin, Dublin, Ireland
- Department of Psychiatry and Psychotherapy, Otto von Guericke University (OVGU), Magdeburg, Germany
- German Center for Neurodegenerative Diseases (DZNE), Göttingen, Germany
| | - Cynthia H Y Fu
- Centre for Affective Disorders, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- School of Psychology, University of East London, London, UK
| | | | - Ian H Gotlib
- Department of Psychology, Stanford University, Stanford, CA, USA
| | - Hans J Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
- German Center of Neurodegenerative Diseases (DZNE) Site Rostock/Greifswald, Greifswald, Germany
| | - Nynke A Groenewold
- Interdisciplinary Center Psychopathology and Emotion regulation (ICPE), University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
- Department of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | | | - Oliver Gruber
- Section for Experimental Psychopathology and Neuroimaging, Department of Psychiatry, University of Heidelberg, Heidelberg, Germany
| | - Geoffrey B Hall
- Department of Psychology, Neuroscience & Behaviour, McMaster University, Hamilton, ON, Canada
| | - Ben J Harrison
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne & Melbourne Health, Melbourne, VIC, Australia
| | - Sean N Hatton
- Youth Mental Health Team, Brain and Mind Centre, University of Sydney, Sydney, NSW, Australia
- Department of Neuroscience, University of California San Diego, San Diego, CA, USA
| | - Marco Hermesdorf
- Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany
| | - Ian B Hickie
- Youth Mental Health Team, Brain and Mind Centre, University of Sydney, Sydney, NSW, Australia
| | - Tiffany C Ho
- Department of Psychology, Stanford University, Stanford, CA, USA
- Department of Psychiatry & Behavioral Sciences, Standord University, Stanford, CA, USA
| | - Norbert Hosten
- Department of Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, Greifswald, Germany
| | - Andreas Jansen
- Department of Psychiatry, Philipps-University Marburg, Marburg, Germany
| | - Claas Kähler
- Department of Psychiatry, University of Münster, Münster, Germany
| | - Tilo Kircher
- Department of Psychiatry, Philipps-University Marburg, Marburg, Germany
| | | | - Bernd Krämer
- Section for Experimental Psychopathology and Neuroimaging, Department of Psychiatry, University of Heidelberg, Heidelberg, Germany
| | - Axel Krug
- Department of Psychiatry, Philipps-University Marburg, Marburg, Germany
- Department of Psychiatry and Psychotherapy, University of Bonn, Bonn, Germany
| | - Jim Lagopoulos
- Youth Mental Health Team, Brain and Mind Centre, University of Sydney, Sydney, NSW, Australia
- Sunshine Coast Mind and Neuroscience Institute, University of the Sunshine Coast QLD, Sippy Downs, QLD, Australia
| | - Ramona Leenings
- Department of Psychiatry, University of Münster, Münster, Germany
| | - Frank P MacMaster
- Departments of Psychiatry and Pediatrics, University of Calgary, Calgary, AB, Canada
- Addictions and Mental Health Strategic Clinical Network, Calgary, AB, Canada
| | - Glenda MacQueen
- Department of Psychiatry, University of Calgary, Calgary, AB, Canada
| | - Andrew McIntosh
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
| | - Quinn McLellan
- Departments of Psychiatry and Pediatrics, University of Calgary, Calgary, AB, Canada
- Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Alberta, Canada
| | - Katie L McMahon
- School of Clinical Sciences, Queensland University of Technology, Brisbane, QLD, Australia
- Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, QLD, Australia
| | - Sarah E Medland
- QIMR Berghofer Medical Research Instititute, Brisbane, QLD, Australia
| | - Bryon A Mueller
- Department of Psychiatry and Behavioral Sciences, University of Minnesota Medical School, Minneapolis, Minnesota, USA
| | - Benson Mwangi
- Department of Psychiatry and Behavioral Sciences, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Evgeny Osipov
- Laboratory of Experimental & Translational Neuroscience, Novosibirsk State University, Novosibirsk, Russia
| | - Maria J Portella
- Institut d'Investigació Biomèdica Sant Pau, Barcelona, Catalonia, Spain
- Centro de Investigación Biomédica en Red de Salud Mental, Cibersam, Spain
| | - Elena Pozzi
- Department of Psychiatry and Behavioral Sciences, University of Minnesota Medical School, Minneapolis, Minnesota, USA
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne & Melbourne Health, Melbourne, VIC, Australia
| | - Liesbeth Reneman
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, AMC, Amsterdam, The Netherlands
| | - Jonathan Repple
- Department of Psychiatry, University of Münster, Münster, Germany
| | - Pedro G P Rosa
- Laboratory of Psychiatric Neuroimaging (LIM-21), Instituto de Psiquiatria, Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, SP, Brazil
| | - Matthew D Sacchet
- Center for Depression, Anxiety, and Stress Research, McLean Hospital, Harvard Medical School, Belmont, MA, USA
| | | | - Knut Schnell
- Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, Göttingen, Germany
- Department of Psychiatry and Psychotherapy, Asklepios Fachklinikum Göttingen, Göttingen, Germany
| | - Anouk Schrantee
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, AMC, Amsterdam, The Netherlands
| | - Egle Simulionyte
- Department of Psychology, Neuroscience & Behaviour, McMaster University, Hamilton, ON, Canada
| | - Jair C Soares
- Department of Psychiatry and Behavioral Sciences, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Jens Sommer
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Dan J Stein
- Department of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa
- SA MRC Unit on Risk and Resilience, University of Cape Town, Cape Town, South Africa
| | - Olaf Steinsträter
- Department of Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, Greifswald, Germany
| | - Lachlan T Strike
- Queensland Brain Institute, University of Queensland, Brisbane, QLD, Australia
| | - Sophia I Thomopoulos
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Marie-José van Tol
- Cognitive Neuroscience Center, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Ilya M Veer
- Division of Mind and Brain Research, Department of Psychiatry and Psychotherapy CCM, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Robert R J M Vermeiren
- Department of Child Psychiatry, University Medical Center, Leiden, The Netherlands
- Leiden Institute for Brain and Cognition, Leiden University, Leiden, The Netherlands
| | - Henrik Walter
- Division of Mind and Brain Research, Department of Psychiatry and Psychotherapy CCM, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Nic J A van der Wee
- Leiden Institute for Brain and Cognition, Leiden University, Leiden, The Netherlands
- Department of Psychiatry, Leiden University Medical Center, Leiden, The Netherlands
| | - Steven J A van der Werff
- Leiden Institute for Brain and Cognition, Leiden University, Leiden, The Netherlands
- Department of Psychiatry, Leiden University Medical Center, Leiden, The Netherlands
| | - Heather Whalley
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
| | - Nils R Winter
- Department of Psychiatry, University of Münster, Münster, Germany
| | - Katharina Wittfeld
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
- German Center of Neurodegenerative Diseases (DZNE) Site Rostock/Greifswald, Greifswald, Germany
| | - Margaret J Wright
- Queensland Brain Institute, University of Queensland, Brisbane, QLD, Australia
- Centre for Advanced Imaging, University of Queensland, Brisbane, QLD, Australia
| | - Mon-Ju Wu
- Department of Psychiatry and Behavioral Sciences, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Henry Völzke
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Tony T Yang
- Department of Psychiatry, Division of Child and Adolescent Psychiatry, UCSF School of Medicine, UCSF, San Francisco, CA, USA
| | | | - Greig I de Zubicaray
- Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, QLD, Australia
- Faculty of Health, Queensland University of Technology, Brisbane, QLD, Australia
| | - Giovana B Zunta-Soares
- Department of Psychiatry and Behavioral Sciences, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Christoph Abé
- Department of Clinical Neuroscience, Osher Center, Karolinska Institutet, Stockholm, Sweden
| | - Martin Alda
- Department of Psychiatry, Dalhousie University, Halifax, NS, Canada
| | - Ole A Andreassen
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Erlend Bøen
- Clinic for Mental Health and Dependency, C-L psychiatry and Psychosomatic Unit, Oslo University Hospital, Oslo, Norway
| | - Caterina M Bonnin
- Hospital Clinic, University of Barcelona, IDIBAPS, CIBERSAM, Barcelona, Catalonia, Spain
| | | | - Dara Cannon
- Centre for Neuroimaging & Cognitive Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, College of Medicine Nursing and Health Sciences, National University of Ireland Galway, H91 TK33, Galway, Ireland
| | - Xavier Caseras
- MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, UK
| | - Tiffany M Chaim-Avancini
- Laboratory of Psychiatric Neuroimaging (LIM-21), Instituto de Psiquiatria, Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, SP, Brazil
| | - Torbjørn Elvsåshagen
- Norwegian Centre for Mental Disorders Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Neurology, Oslo University Hospital, Oslo, Norway
| | - Pauline Favre
- UNIACT, Psychiatry Team, Neurospin, Atomic Energy Commission, Gif-Sur-Yvette, France
- Translational Psychiatry Team, Pôle de psychiatrie, Faculté de Médecine, APHP, Hôpitaux Universitaires Mondor, INSERM, U955, Créteil, France
| | - Sonya F Foley
- Cardiff University Brain Research Imaging Centre, Cardiff University, Cardiff, UK
| | - Janice M Fullerton
- Neuroscience Research Australia, Randwick, Sydney, NSW, Australia
- School of Medical Sciences, University of New South Wales, Sydney, NSW, Australia
| | - Jose M Goikolea
- Hospital Clinic, University of Barcelona, IDIBAPS, CIBERSAM, Barcelona, Catalonia, Spain
| | - Bartholomeus C M Haarman
- Department of Psychiatry, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Tomas Hajek
- Department of Psychiatry, Dalhousie University, Halifax, NS, Canada
| | - Chantal Henry
- Université de Paris, Service Hospitalo-Universitaire, GHU Paris Psychiatrie & Neuroscience, F-75014, Paris, France
| | - Josselin Houenou
- UNIACT, Psychiatry Team, Neurospin, Atomic Energy Commission, Gif-Sur-Yvette, France
- Translational Psychiatry Team, Pôle de psychiatrie, Faculté de Médecine, APHP, Hôpitaux Universitaires Mondor, INSERM, U955, Créteil, France
| | - Fleur M Howells
- Department of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Martin Ingvar
- Department of Clinical Neuroscience, Osher Center, Karolinska Institutet, Stockholm, Sweden
| | | | - Beny Lafer
- Department of Psychiatry, School of Medicine, University of Sao Paulo (FMUSP), Sao Paulo, Brazil
| | - Mikael Landén
- Department of Clinical Neuroscience, Osher Center, Karolinska Institutet, Stockholm, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Rodrigo Machado-Vieira
- Department of Psychiatry, School of Medicine, University of Sao Paulo (FMUSP), Sao Paulo, Brazil
| | - Ulrik F Malt
- Department of Clinical Neuroscience, University of Oslo, Oslo, Norway
- Clinic for Psychiatry and Dependency, C-L psychiatry and Psychosomatic Unit, Oslo University Hospital, Oslo, Norway
| | - Colm McDonald
- Centre for Neuroimaging & Cognitive Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, College of Medicine Nursing and Health Sciences, National University of Ireland Galway, H91 TK33, Galway, Ireland
| | - Philip B Mitchell
- School of Psychiatry, University of New South Wales, Kingsford, Sydney, NSW, Australia
- Black Dog Institute, Prince of Wales Hospital, Randwick, Sydney, NSW, Australia
| | - Leila Nabulsi
- Centre for Neuroimaging & Cognitive Genomics (NICOG), Clinical Neuroimaging Laboratory, NCBES Galway Neuroscience Centre, College of Medicine Nursing and Health Sciences, National University of Ireland Galway, H91 TK33, Galway, Ireland
| | - Maria Concepcion Garcia Otaduy
- Instituto de Radiologia, Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, SP, Brazil
| | - Bronwyn J Overs
- Neuroscience Research Australia, Randwick, Sydney, NSW, Australia
| | - Mircea Polosan
- Department of Psychiatry and Neurology, CHU Grenoble Alpes, Université Grenoble Alpes, F-38000, Grenoble, France
- Inserm 1216, Grenoble Institut des Neurosciences, GIN, F-38000, Grenoble, France
| | - Edith Pomarol-Clotet
- FIDMAG Germanes Hospitalàries Research Foundation, CIBERSAM, Barcelona, Catalonia, Spain
| | - Joaquim Radua
- Hospital Clinic, University of Barcelona, IDIBAPS, CIBERSAM, Barcelona, Catalonia, Spain
| | - Maria M Rive
- Department of Psychiatry, Amsterdam University Medical Centers, AMC, Amsterdam, The Netherlands
| | - Gloria Roberts
- School of Psychiatry, University of New South Wales, Kingsford, Sydney, NSW, Australia
- Black Dog Institute, Prince of Wales Hospital, Randwick, Sydney, NSW, Australia
| | - Henricus G Ruhe
- Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, The Netherlands
- Department of Psychiatry, Amsterdam University Medical Centers, AMC, Amsterdam, The Netherlands
- Department of Psychiatry, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Raymond Salvador
- FIDMAG Germanes Hospitalàries Research Foundation, CIBERSAM, Barcelona, Catalonia, Spain
| | - Salvador Sarró
- FIDMAG Germanes Hospitalàries Research Foundation, CIBERSAM, Barcelona, Catalonia, Spain
| | - Theodore D Satterthwaite
- Department of Psychiatry, University of Pennsylvannia Perelman School of Medicine, Philadelphia, PA, USA
| | - Jonathan Savitz
- Laureate Institute for Brain Research, Tulsa, OK, USA
- Oxley College of Health Sciences, The University of Tulsa, Tulsa, OK, USA
| | - Aart H Schene
- Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, The Netherlands
- Department of Psychiatry, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Peter R Schofield
- Neuroscience Research Australia, Randwick, Sydney, NSW, Australia
- School of Medical Sciences, University of New South Wales, Sydney, NSW, Australia
| | - Mauricio H Serpa
- Laboratory of Psychiatric Neuroimaging (LIM-21), Instituto de Psiquiatria, Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, SP, Brazil
| | - Kang Sim
- West Region and Research Division, Institute of Mental Health, Singapore, Singapore
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | | | - Ashley N Sutherland
- Department of Psychiatry, University of California San Diego, Los Angeles, CA, USA
| | - Henk S Temmingh
- Section for Experimental Psychopathology and Neuroimaging, Department of Psychiatry, University of Heidelberg, Heidelberg, Germany
- Valkenberg Psychiatric Hospital, Cape Town, South Africa
| | - Garrett M Timmons
- Department of Psychiatry, University of California San Diego, Los Angeles, CA, USA
| | - Anne Uhlmann
- Department of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Eduard Vieta
- Hospital Clinic, University of Barcelona, IDIBAPS, CIBERSAM, Barcelona, Catalonia, Spain
| | - Daniel H Wolf
- Department of Psychiatry, University of Pennsylvannia Perelman School of Medicine, Philadelphia, PA, USA
| | - Marcus V Zanetti
- Laboratory of Psychiatric Neuroimaging (LIM-21), Instituto de Psiquiatria, Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, SP, Brazil
- Instituto de Ensino e Pesquisa, Hospital Sírio-Libanês, Sao Paulo, SP, Brazil
| | - Neda Jahanshad
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Paul M Thompson
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Dick J Veltman
- Department of Psychiatry, Amsterdam Public Health and Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit & GGZinGeest, Amsterdam, The Netherlands
| | - Brenda W J H Penninx
- Department of Psychiatry, Amsterdam Public Health and Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit & GGZinGeest, Amsterdam, The Netherlands
| | - Andre F Marquand
- Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, The Netherlands
- Department of Cognitive Neuroscience, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - James H Cole
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College, London, UK
- Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK
- Dementia Research Centre, Institute of Neurology, University College London, London, UK
| | - Lianne Schmaal
- Orygen, The National Centre of Excellence in Youth Mental Health, Parkville, VIC, Australia
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, VIC, Australia
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11
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Hahn T, Fisch L, Ernsting J, Winter NR, Leenings R, Sarink K, Emden D, Kircher T, Berger K, Dannlowski U. From 'loose fitting' to high-performance, uncertainty-aware brain-age modelling. Brain 2021; 144:e31. [PMID: 33826702 DOI: 10.1093/brain/awaa454] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Affiliation(s)
- Tim Hahn
- Department of Psychiatry, University of Münster, Münster, Germany
| | - Lukas Fisch
- Department of Psychiatry, University of Münster, Münster, Germany
| | - Jan Ernsting
- Department of Psychiatry, University of Münster, Münster, Germany
- Department of Mathematics and Computer Science, University of Münster, Münster, Germany
| | - Nils R Winter
- Department of Psychiatry, University of Münster, Münster, Germany
| | - Ramona Leenings
- Department of Psychiatry, University of Münster, Münster, Germany
| | - Kelvin Sarink
- Department of Psychiatry, University of Münster, Münster, Germany
| | - Daniel Emden
- Department of Psychiatry, University of Münster, Münster, Germany
| | - Tilo Kircher
- Department of Psychiatry and Psychotherapy, Phillips University Marburg, Marburg, Germany
| | - Klaus Berger
- Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany
| | - Udo Dannlowski
- Department of Psychiatry, University of Münster, Münster, Germany
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12
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Fisch L, Leenings R, Winter NR, Dannlowski U, Gaser C, Cole JH, Hahn T. Editorial: Predicting Chronological Age From Structural Neuroimaging: The Predictive Analytics Competition 2019. Front Psychiatry 2021; 12:710932. [PMID: 34421686 PMCID: PMC8374100 DOI: 10.3389/fpsyt.2021.710932] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/17/2021] [Accepted: 07/09/2021] [Indexed: 11/13/2022] Open
Affiliation(s)
- Lukas Fisch
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Ramona Leenings
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Nils R. Winter
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Udo Dannlowski
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
| | - Christian Gaser
- Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany
- Department of Neurology, Jena University Hospital, Jena, Germany
| | - James H. Cole
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
- Computational, Cognitive and Clinical Neuroimaging Laboratory, Department King's College, London, United Kingdom
| | - Tim Hahn
- Institute for Translational Psychiatry, University of Münster, Münster, Germany
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13
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Flint C, Cearns M, Opel N, Redlich R, Mehler DMA, Emden D, Winter NR, Leenings R, Eickhoff SB, Kircher T, Krug A, Nenadic I, Arolt V, Clark S, Baune BT, Jiang X, Dannlowski U, Hahn T. Systematic misestimation of machine learning performance in neuroimaging studies of depression. Neuropsychopharmacology 2021; 46:1510-1517. [PMID: 33958703 PMCID: PMC8209109 DOI: 10.1038/s41386-021-01020-7] [Citation(s) in RCA: 46] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/18/2021] [Revised: 04/01/2021] [Accepted: 04/09/2021] [Indexed: 02/06/2023]
Abstract
We currently observe a disconcerting phenomenon in machine learning studies in psychiatry: While we would expect larger samples to yield better results due to the availability of more data, larger machine learning studies consistently show much weaker performance than the numerous small-scale studies. Here, we systematically investigated this effect focusing on one of the most heavily studied questions in the field, namely the classification of patients suffering from Major Depressive Disorder (MDD) and healthy controls based on neuroimaging data. Drawing upon structural MRI data from a balanced sample of N = 1868 MDD patients and healthy controls from our recent international Predictive Analytics Competition (PAC), we first trained and tested a classification model on the full dataset which yielded an accuracy of 61%. Next, we mimicked the process by which researchers would draw samples of various sizes (N = 4 to N = 150) from the population and showed a strong risk of misestimation. Specifically, for small sample sizes (N = 20), we observe accuracies of up to 95%. For medium sample sizes (N = 100) accuracies up to 75% were found. Importantly, further investigation showed that sufficiently large test sets effectively protect against performance misestimation whereas larger datasets per se do not. While these results question the validity of a substantial part of the current literature, we outline the relatively low-cost remedy of larger test sets, which is readily available in most cases.
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Affiliation(s)
- Claas Flint
- grid.5949.10000 0001 2172 9288Department of Psychiatry, University of Münster, Münster, Germany ,grid.5949.10000 0001 2172 9288Faculty of Mathematics and Computer Science, University of Münster, Münster, Germany
| | - Micah Cearns
- grid.1010.00000 0004 1936 7304Discipline of Psychiatry, School of Medicine, University of Adelaide, Adelaide, SA Australia ,grid.1008.90000 0001 2179 088XDepartment of Psychiatry, Melbourne Medical School, The University of Melbourne, Parkville, VIC Australia
| | - Nils Opel
- grid.5949.10000 0001 2172 9288Department of Psychiatry, University of Münster, Münster, Germany
| | - Ronny Redlich
- grid.5949.10000 0001 2172 9288Department of Psychiatry, University of Münster, Münster, Germany
| | - David M. A. Mehler
- grid.5949.10000 0001 2172 9288Department of Psychiatry, University of Münster, Münster, Germany
| | - Daniel Emden
- grid.5949.10000 0001 2172 9288Department of Psychiatry, University of Münster, Münster, Germany
| | - Nils R. Winter
- grid.5949.10000 0001 2172 9288Department of Psychiatry, University of Münster, Münster, Germany
| | - Ramona Leenings
- grid.5949.10000 0001 2172 9288Department of Psychiatry, University of Münster, Münster, Germany
| | - Simon B. Eickhoff
- grid.8385.60000 0001 2297 375XInstitute of Neuroscience and Medicine (INM-7) Research Center Jülich, Jülich, Germany ,grid.411327.20000 0001 2176 9917Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Tilo Kircher
- grid.10253.350000 0004 1936 9756Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
| | - Axel Krug
- grid.10253.350000 0004 1936 9756Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
| | - Igor Nenadic
- grid.10253.350000 0004 1936 9756Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
| | - Volker Arolt
- grid.5949.10000 0001 2172 9288Department of Psychiatry, University of Münster, Münster, Germany
| | - Scott Clark
- grid.1010.00000 0004 1936 7304Discipline of Psychiatry, School of Medicine, University of Adelaide, Adelaide, SA Australia
| | - Bernhard T. Baune
- grid.5949.10000 0001 2172 9288Department of Psychiatry, University of Münster, Münster, Germany ,grid.1008.90000 0001 2179 088XDepartment of Psychiatry, Melbourne Medical School, The University of Melbourne, Parkville, VIC Australia ,grid.1008.90000 0001 2179 088XThe Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, VIC Australia
| | - Xiaoyi Jiang
- grid.5949.10000 0001 2172 9288Faculty of Mathematics and Computer Science, University of Münster, Münster, Germany
| | - Udo Dannlowski
- Department of Psychiatry, University of Münster, Münster, Germany.
| | - Tim Hahn
- grid.5949.10000 0001 2172 9288Department of Psychiatry, University of Münster, Münster, Germany
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14
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Winter NR, Cearns M, Clark SR, Leenings R, Dannlowski U, Baune BT, Hahn T. From multivariate methods to an AI ecosystem. Mol Psychiatry 2021; 26:6116-6120. [PMID: 33981009 PMCID: PMC8760040 DOI: 10.1038/s41380-021-01116-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/25/2020] [Revised: 03/29/2021] [Accepted: 04/12/2021] [Indexed: 02/02/2023]
Affiliation(s)
- Nils R. Winter
- grid.5949.10000 0001 2172 9288Department of Psychiatry, University of Muenster, Münster, Germany
| | - Micah Cearns
- grid.1010.00000 0004 1936 7304Discipline of Psychiatry, School of Medicine, University of Adelaide, Adelaide, SA Australia ,grid.1008.90000 0001 2179 088XDepartment of Psychiatry, Melbourne Medical School, The University of Melbourne, Parkville, VIC Australia
| | - Scott R. Clark
- grid.1010.00000 0004 1936 7304Discipline of Psychiatry, School of Medicine, University of Adelaide, Adelaide, SA Australia
| | - Ramona Leenings
- grid.5949.10000 0001 2172 9288Department of Psychiatry, University of Muenster, Münster, Germany
| | - Udo Dannlowski
- grid.5949.10000 0001 2172 9288Department of Psychiatry, University of Muenster, Münster, Germany
| | - Bernhard T. Baune
- grid.5949.10000 0001 2172 9288Department of Psychiatry, University of Muenster, Münster, Germany ,grid.1010.00000 0004 1936 7304Discipline of Psychiatry, School of Medicine, University of Adelaide, Adelaide, SA Australia ,grid.1008.90000 0001 2179 088XDepartment of Psychiatry, Melbourne Medical School, The University of Melbourne, Parkville, VIC Australia ,grid.1008.90000 0001 2179 088XThe Florey Institute of Mental Health, The University of Melbourne, Melbourne, VIC Australia
| | - Tim Hahn
- Department of Psychiatry, University of Muenster, Münster, Germany.
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15
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Opel N, Thalamuthu A, Milaneschi Y, Grotegerd D, Flint C, Leenings R, Goltermann J, Richter M, Hahn T, Woditsch G, Berger K, Hermesdorf M, McIntosh A, Whalley HC, Harris MA, MacMaster FP, Walter H, Veer IM, Frodl T, Carballedo A, Krug A, Nenadic I, Kircher T, Aleman A, Groenewold NA, Stein DJ, Soares JC, Zunta-Soares GB, Mwangi B, Wu MJ, Walter M, Li M, Harrison BJ, Davey CG, Cullen KR, Klimes-Dougan B, Mueller BA, Sämann PG, Penninx B, Nawijn L, Veltman DJ, Aftanas L, Brak IV, Filimonova EA, Osipov EA, Reneman L, Schrantee A, Grabe HJ, Van der Auwera S, Wittfeld K, Hosten N, Völzke H, Sim K, Gotlib IH, Sacchet MD, Lagopoulos J, Hatton SN, Hickie I, Pozzi E, Thompson PM, Jahanshad N, Schmaal L, Baune BT, Dannlowski U. Correction: Brain structural abnormalities in obesity: relation to age, genetic risk, and common psychiatric disorders. Mol Psychiatry 2021; 26:7854. [PMID: 34158622 PMCID: PMC8873007 DOI: 10.1038/s41380-021-01191-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Affiliation(s)
- Nils Opel
- Department of Psychiatry, University of Münster, Münster, Germany. .,Interdisciplinary Centre for Clinical Research (IZKF), University of Münster, Münster, Germany.
| | - Anbupalam Thalamuthu
- grid.1005.40000 0004 4902 0432Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales, Sydney, NSW Australia ,grid.250407.40000 0000 8900 8842Neuroscience Research Australia, Randwick, NSW Australia
| | - Yuri Milaneschi
- Department of Psychiatry, Amsterdam UMC/Vrije Universiteit, Amsterdam, Netherlands
| | - Dominik Grotegerd
- grid.5949.10000 0001 2172 9288Department of Psychiatry, University of Münster, Münster, Germany
| | - Claas Flint
- grid.5949.10000 0001 2172 9288Department of Psychiatry, University of Münster, Münster, Germany ,grid.5949.10000 0001 2172 9288Faculty of Mathematics and Computer Science, University of Münster, Münster, Germany
| | - Ramona Leenings
- grid.5949.10000 0001 2172 9288Department of Psychiatry, University of Münster, Münster, Germany
| | - Janik Goltermann
- grid.5949.10000 0001 2172 9288Department of Psychiatry, University of Münster, Münster, Germany
| | - Maike Richter
- grid.5949.10000 0001 2172 9288Department of Psychiatry, University of Münster, Münster, Germany
| | - Tim Hahn
- grid.5949.10000 0001 2172 9288Department of Psychiatry, University of Münster, Münster, Germany
| | - Georg Woditsch
- grid.5949.10000 0001 2172 9288IT Department, University of Muenster, Münster, Germany
| | - Klaus Berger
- grid.5949.10000 0001 2172 9288Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany
| | - Marco Hermesdorf
- grid.5949.10000 0001 2172 9288Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany
| | - Andrew McIntosh
- grid.4305.20000 0004 1936 7988Division of Psychiatry, University of Edinburgh, Edinburgh, UK
| | - Heather C. Whalley
- grid.4305.20000 0004 1936 7988Division of Psychiatry, University of Edinburgh, Edinburgh, UK
| | - Mathew A. Harris
- grid.4305.20000 0004 1936 7988Division of Psychiatry, University of Edinburgh, Edinburgh, UK
| | - Frank P. MacMaster
- grid.22072.350000 0004 1936 7697Psychiatry and Paediatrics, University of Calgary, Calgary, AB Canada ,Addictions and Mental Health Strategic Clinical Network Calgary, Calgary, AB Canada
| | - Henrik Walter
- grid.6363.00000 0001 2218 4662Division of Mind and Brain Research, Department of Psychiatry and Psychotherapy CCM, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Ilya M. Veer
- grid.6363.00000 0001 2218 4662Division of Mind and Brain Research, Department of Psychiatry and Psychotherapy CCM, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Thomas Frodl
- grid.8217.c0000 0004 1936 9705Department of Psychiatry, Trinity College Dublin, Dublin, Ireland ,grid.5807.a0000 0001 1018 4307Department of Psychiatry and Psychotherapy, Otto von Guericke University Magdeburg, Magdeburg, Germany
| | - Angela Carballedo
- grid.8217.c0000 0004 1936 9705Department of Psychiatry, Trinity College Dublin, Dublin, Ireland
| | - Axel Krug
- grid.10253.350000 0004 1936 9756Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
| | - Igor Nenadic
- grid.10253.350000 0004 1936 9756Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
| | - Tilo Kircher
- grid.10253.350000 0004 1936 9756Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
| | - Andre Aleman
- grid.4494.d0000 0000 9558 4598Department of Biomedical Sciences of Cells and Systems, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Nynke A. Groenewold
- grid.4494.d0000 0000 9558 4598Department of Biomedical Sciences of Cells and Systems, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Dan J. Stein
- grid.7836.a0000 0004 1937 1151SA MRC Unit on Risk & Resilience, Department of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Jair C. Soares
- grid.267308.80000 0000 9206 2401UT Center of Excellence on Mood Disorders, Department of Psychiatry and Behavioral Sciences, University of Texas Health Science Center at Houston, Houston, TX USA
| | - Giovana B. Zunta-Soares
- grid.267308.80000 0000 9206 2401UT Center of Excellence on Mood Disorders, Department of Psychiatry and Behavioral Sciences, University of Texas Health Science Center at Houston, Houston, TX USA
| | - Benson Mwangi
- grid.267308.80000 0000 9206 2401Department of Psychiatry, University of Texas Health Science Center at Houston, Houston, TX USA
| | - Mon-Ju Wu
- grid.267308.80000 0000 9206 2401Department of Psychiatry, University of Texas Health Science Center at Houston, Houston, TX USA
| | - Martin Walter
- grid.275559.90000 0000 8517 6224Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany
| | - Meng Li
- grid.275559.90000 0000 8517 6224Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany
| | - Ben J. Harrison
- grid.1008.90000 0001 2179 088XMelbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne & Melbourne Health, Parkville, VIC Australia
| | - Christopher G. Davey
- grid.488501.00000 0004 8032 6923Orygen, The National Centre of Excellence in Youth Mental Health, Parkville, VIC Australia ,grid.1008.90000 0001 2179 088XCentre for Youth Mental Health, The University of Melbourne, Parkville, VIC Australia
| | - Kathryn R. Cullen
- grid.17635.360000000419368657Department of Psychiatry and Behavioral Sciences, School of Medicine, University of Minnesota, Minneapolis, MN USA
| | - Bonnie Klimes-Dougan
- grid.17635.360000000419368657Department of Psychology, University of Minnesota, Minneapolis, MN USA
| | - Bryon A. Mueller
- grid.17635.360000000419368657Department of Psychiatry and Behavioral Sciences, School of Medicine, University of Minnesota, Minneapolis, MN USA
| | - Philipp G. Sämann
- grid.419548.50000 0000 9497 5095Max Planck Institute of Psychiatry, Munich, Germany
| | - Brenda Penninx
- Department of Psychiatry, Amsterdam UMC/Vrije Universiteit, Amsterdam, Netherlands
| | - Laura Nawijn
- Department of Psychiatry, Amsterdam UMC/Vrije Universiteit, Amsterdam, Netherlands
| | - Dick J. Veltman
- Department of Psychiatry, Amsterdam UMC/Vrije Universiteit, Amsterdam, Netherlands
| | - Lyubomir Aftanas
- grid.473784.bFSSBI “Scientific Research Institute of Physiology & Basic Medicine”, Laboratory of Affective, Cognitive & Translational Neuroscience, Novosibirsk, Russia
| | - Ivan V. Brak
- grid.473784.bFSSBI “Scientific Research Institute of Physiology & Basic Medicine”, Laboratory of Affective, Cognitive & Translational Neuroscience, Novosibirsk, Russia
| | - Elena A. Filimonova
- grid.473784.bFSSBI “Scientific Research Institute of Physiology & Basic Medicine”, Laboratory of Affective, Cognitive & Translational Neuroscience, Novosibirsk, Russia
| | - Evgeniy A. Osipov
- grid.4605.70000000121896553Novosibirsk State University, Laboratory of Experimental & Translational Neuroscience, Novosibirsk, Russia
| | - Liesbeth Reneman
- grid.7177.60000000084992262Department of Radiology and Nuclear Medicine, Academic Medical Center, University of Amsterdam, Amsterdam, Netherlands
| | - Anouk Schrantee
- grid.7177.60000000084992262Department of Radiology and Nuclear Medicine, Academic Medical Center, University of Amsterdam, Amsterdam, Netherlands
| | - Hans J. Grabe
- grid.5603.0Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany ,grid.424247.30000 0004 0438 0426German Center for Neurodegenerative Diseases (DZNE), Greifswald/Rostock, site Greifswald, Greifswald, Germany
| | - Sandra Van der Auwera
- grid.5603.0Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany ,grid.424247.30000 0004 0438 0426German Center for Neurodegenerative Diseases (DZNE), Greifswald/Rostock, site Greifswald, Greifswald, Germany
| | - Katharina Wittfeld
- grid.5603.0Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany ,grid.424247.30000 0004 0438 0426German Center for Neurodegenerative Diseases (DZNE), Greifswald/Rostock, site Greifswald, Greifswald, Germany
| | - Norbert Hosten
- grid.5603.0Institute of Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, Greifswald, Germany
| | - Henry Völzke
- grid.5603.0Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany ,grid.452396.f0000 0004 5937 5237German Center for Cardiovascular Research (DZHK), Partner Site Greifswald, Greifswald, Germany
| | - Kang Sim
- grid.414752.10000 0004 0469 9592West Region, Institute of Mental Health, Singapore, Singapore ,grid.4280.e0000 0001 2180 6431Yoo Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Ian H. Gotlib
- grid.168010.e0000000419368956Department of Psychology, Stanford University, Stanford, CA USA
| | - Matthew D. Sacchet
- grid.38142.3c000000041936754XCenter for Depression, Anxiety, and Stress Research, McLean Hospital, Harvard Medical School, Belmont, MA USA
| | - Jim Lagopoulos
- grid.1034.60000 0001 1555 3415Sunshine Coast Mind and Neuroscience Thompson Institute, University of the Sunshine Coast, Sippy Downs, QLD Australia
| | - Sean N. Hatton
- grid.1013.30000 0004 1936 834XBrain and Mind Centre, University of Sydney, Camperdown, NSW Australia
| | - Ian Hickie
- grid.1013.30000 0004 1936 834XBrain and Mind Centre, University of Sydney, Camperdown, NSW Australia
| | - Elena Pozzi
- grid.488501.00000 0004 8032 6923Orygen, The National Centre of Excellence in Youth Mental Health, Parkville, VIC Australia ,grid.1008.90000 0001 2179 088XMelbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne, Parkville, VIC Australia
| | - Paul M. Thompson
- grid.42505.360000 0001 2156 6853Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA USA
| | - Neda Jahanshad
- grid.42505.360000 0001 2156 6853Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA USA
| | - Lianne Schmaal
- grid.488501.00000 0004 8032 6923Orygen, The National Centre of Excellence in Youth Mental Health, Parkville, VIC Australia ,grid.1008.90000 0001 2179 088XCentre for Youth Mental Health, The University of Melbourne, Parkville, VIC Australia
| | - Bernhard T. Baune
- grid.5949.10000 0001 2172 9288Department of Psychiatry, University of Münster, Münster, Germany ,grid.1008.90000 0001 2179 088XDepartment of Psychiatry, Melbourne Medical School, The University of Melbourne, Melbourne, VIC Australia ,grid.1008.90000 0001 2179 088XThe Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, VIC Australia
| | - Udo Dannlowski
- grid.5949.10000 0001 2172 9288Department of Psychiatry, University of Münster, Münster, Germany
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16
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Sämann PG, Iglesias JE, Gutman B, Grotegerd D, Leenings R, Flint C, Dannlowski U, Clarke‐Rubright EK, Morey RA, Erp TG, Whelan CD, Han LKM, Velzen LS, Cao B, Augustinack JC, Thompson PM, Jahanshad N, Schmaal L. FreeSurfer
‐based segmentation of hippocampal subfields: A review of methods and applications, with a novel quality control procedure for
ENIGMA
studies and other collaborative efforts. Hum Brain Mapp 2020; 43:207-233. [PMID: 33368865 PMCID: PMC8805696 DOI: 10.1002/hbm.25326] [Citation(s) in RCA: 47] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2020] [Revised: 11/26/2020] [Accepted: 12/13/2020] [Indexed: 12/11/2022] Open
Abstract
Structural hippocampal abnormalities are common in many neurological and psychiatric disorders, and variation in hippocampal measures is related to cognitive performance and other complex phenotypes such as stress sensitivity. Hippocampal subregions are increasingly studied, as automated algorithms have become available for mapping and volume quantification. In the context of the Enhancing Neuro Imaging Genetics through Meta Analysis Consortium, several Disease Working Groups are using the FreeSurfer software to analyze hippocampal subregion (subfield) volumes in patients with neurological and psychiatric conditions along with data from matched controls. In this overview, we explain the algorithm's principles, summarize measurement reliability studies, and demonstrate two additional aspects (subfield autocorrelation and volume/reliability correlation) with illustrative data. We then explain the rationale for a standardized hippocampal subfield segmentation quality control (QC) procedure for improved pipeline harmonization. To guide researchers to make optimal use of the algorithm, we discuss how global size and age effects can be modeled, how QC steps can be incorporated and how subfields may be aggregated into composite volumes. This discussion is based on a synopsis of 162 published neuroimaging studies (01/2013–12/2019) that applied the FreeSurfer hippocampal subfield segmentation in a broad range of domains including cognition and healthy aging, brain development and neurodegeneration, affective disorders, psychosis, stress regulation, neurotoxicity, epilepsy, inflammatory disease, childhood adversity and posttraumatic stress disorder, and candidate and whole genome (epi‐)genetics. Finally, we highlight points where FreeSurfer‐based hippocampal subfield studies may be optimized.
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Affiliation(s)
| | - Juan Eugenio Iglesias
- Centre for Medical Image Computing University College London London UK
- The Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology Massachusetts General Hospital/Harvard Medical School Boston Massachusetts US
- Computer Science and AI Laboratory (CSAIL), Massachusetts Institute of Technology (MIT) Cambridge Massachusetts US
| | - Boris Gutman
- Department of Biomedical Engineering Illinois Institute of Technology Chicago USA
| | | | - Ramona Leenings
- Department of Psychiatry University of Münster Münster Germany
| | - Claas Flint
- Department of Psychiatry University of Münster Münster Germany
- Department of Mathematics and Computer Science University of Münster Germany
| | - Udo Dannlowski
- Department of Psychiatry University of Münster Münster Germany
| | - Emily K. Clarke‐Rubright
- Brain Imaging and Analysis Center, Duke University Durham North Carolina USA
- VISN 6 MIRECC, Durham VA Durham North Carolina USA
| | - Rajendra A. Morey
- Brain Imaging and Analysis Center, Duke University Durham North Carolina USA
- VISN 6 MIRECC, Durham VA Durham North Carolina USA
| | - Theo G.M. Erp
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior University of California Irvine California USA
- Center for the Neurobiology of Learning and Memory University of California Irvine Irvine California USA
| | - Christopher D. Whelan
- Imaging Genetics Center Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California Los Angeles California USA
| | - Laura K. M. Han
- Department of Psychiatry Amsterdam University Medical Centers, Vrije Universiteit and GGZ inGeest, Amsterdam Neuroscience Amsterdam The Netherlands
| | - Laura S. Velzen
- Orygen Parkville Australia
- Centre for Youth Mental Health The University of Melbourne Melbourne Australia
| | - Bo Cao
- Department of Psychiatry, Faculty of Medicine & Dentistry University of Alberta Edmonton Canada
| | - Jean C. Augustinack
- The Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology Massachusetts General Hospital/Harvard Medical School Boston Massachusetts US
| | - Paul M. Thompson
- Imaging Genetics Center Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California Los Angeles California USA
| | - Neda Jahanshad
- Imaging Genetics Center Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California Los Angeles California USA
| | - Lianne Schmaal
- Orygen Parkville Australia
- Centre for Youth Mental Health The University of Melbourne Melbourne Australia
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17
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Hilger K, Winter NR, Leenings R, Sassenhagen J, Hahn T, Basten U, Fiebach CJ. Predicting intelligence from brain gray matter volume. Brain Struct Funct 2020; 225:2111-2129. [PMID: 32696074 PMCID: PMC7473979 DOI: 10.1007/s00429-020-02113-7] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2019] [Accepted: 07/04/2020] [Indexed: 12/21/2022]
Abstract
A positive association between brain size and intelligence is firmly established, but whether region-specific anatomical differences contribute to general intelligence remains an open question. Results from voxel-based morphometry (VBM) - one of the most widely used morphometric methods - have remained inconclusive so far. Here, we applied cross-validated machine learning-based predictive modeling to test whether out-of-sample prediction of individual intelligence scores is possible on the basis of voxel-wise gray matter volume. Features were derived from structural magnetic resonance imaging data (N = 308) using (a) a purely data-driven method (principal component analysis) and (b) a domain knowledge-based approach (atlas parcellation). When using relative gray matter (corrected for total brain size), only the atlas-based approach provided significant prediction, while absolute gray matter (uncorrected) allowed for above-chance prediction with both approaches. Importantly, in all significant predictions, the absolute error was relatively high, i.e., greater than ten IQ points, and in the atlas-based models, the predicted IQ scores varied closely around the sample mean. This renders the practical value even of statistically significant prediction results questionable. Analyses based on the gray matter of functional brain networks yielded significant predictions for the fronto-parietal network and the cerebellum. However, the mean absolute errors were not reduced in contrast to the global models, suggesting that general intelligence may be related more to global than region-specific differences in gray matter volume. More generally, our study highlights the importance of predictive statistical analysis approaches for clarifying the neurobiological bases of intelligence and provides important suggestions for future research using predictive modeling.
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Affiliation(s)
- Kirsten Hilger
- Department of Psychology, Goethe University Frankfurt, Frankfurt am Main, Germany.
- Department of Psychology, Julius Maximilian University Würzburg, Würzburg, Germany.
- IDeA Center for Individual Development and Adaptive Education, Frankfurt am Main, Germany.
- Department of Psychology I, University Wuerzburg, Marcusstr. 9-11, 97070, Würzburg, Germany.
| | - Nils R Winter
- Institute of Translational Psychiatry, University Hospital Münster, Münster, Germany
| | - Ramona Leenings
- Institute of Translational Psychiatry, University Hospital Münster, Münster, Germany
| | - Jona Sassenhagen
- Department of Psychology, Goethe University Frankfurt, Frankfurt am Main, Germany
| | - Tim Hahn
- Institute of Translational Psychiatry, University Hospital Münster, Münster, Germany
| | - Ulrike Basten
- Department of Psychology, Goethe University Frankfurt, Frankfurt am Main, Germany
| | - Christian J Fiebach
- Department of Psychology, Goethe University Frankfurt, Frankfurt am Main, Germany
- IDeA Center for Individual Development and Adaptive Education, Frankfurt am Main, Germany
- Brain Imaging Center, Goethe University Frankfurt, Frankfurt am Main, Germany
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18
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Goltermann J, Opel N, Redlich R, Repple J, Kaehler C, Grotegerd D, Dohm K, Leehr EJ, Böhnlein J, Förster K, Meinert S, Enneking V, Emden D, Leenings R, Winter NR, Hahn T, Mikhail S, Jansen A, Krug A, Nenadić I, Rietschel M, Witt SH, Heilmann-Heimbach S, Hoffmann P, Forstner AJ, Nöthen MM, Baune BT, Kircher T, Dannlowski U. Replication of a hippocampus specific effect of the tescalcin regulating variant rs7294919 on gray matter structure. Eur Neuropsychopharmacol 2020; 36:10-17. [PMID: 32451266 DOI: 10.1016/j.euroneuro.2020.03.021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/06/2019] [Revised: 03/09/2020] [Accepted: 03/27/2020] [Indexed: 10/24/2022]
Abstract
While the hippocampus remains a region of high interest for neuropsychiatric research, the precise contributors to hippocampal morphometry are still not well understood. We and others previously reported a hippocampus specific effect of a tescalcin gene (TESC) regulating single nucleotide polymorphism (rs7294919) on gray matter volume. Here we aimed to replicate and extend these findings. Two complementary morphometric approaches (voxel based morphometry (VBM) and automated volumetric segmentation) were applied in a well-powered cohort from the Marburg-Münster Affective Disorder Cohort Study (MACS) including N=1137 participants (n=636 healthy controls, n=501 depressed patients). rs7294919 homozygous T-allele genotype was significantly associated with lower hippocampal gray matter density as well as with reduced hippocampal volume. Exploratory whole brain VBM analyses revealed no further associations with gray matter volume outside the hippocampus. No interaction effects of rs7294919 with depression nor with childhood trauma on hippocampal morphometry could be detected. Hippocampal subfield analyses revealed similar effects of rs7294919 in all hippocampal subfields. In sum, our results replicate a hippocampus specific effect of rs7294919 on brain structure. Due to the robust evidence for a pronounced association between the reported polymorphism and hippocampal morphometry, future research should consider investigating the potential clinical and functional relevance of the reported association.
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Affiliation(s)
- Janik Goltermann
- Department of Psychiatry, University of Münster, Albert-Schweitzer-Campus 1, Building A9, 48149 Münster, Germany
| | - Nils Opel
- Department of Psychiatry, University of Münster, Albert-Schweitzer-Campus 1, Building A9, 48149 Münster, Germany; Interdisciplinary Centre for Clinical Research (IZKF), University of Mü̈nster, Münster, Germany
| | - Ronny Redlich
- Department of Psychiatry, University of Münster, Albert-Schweitzer-Campus 1, Building A9, 48149 Münster, Germany
| | - Jonathan Repple
- Department of Psychiatry, University of Münster, Albert-Schweitzer-Campus 1, Building A9, 48149 Münster, Germany
| | - Claas Kaehler
- Department of Psychiatry, University of Münster, Albert-Schweitzer-Campus 1, Building A9, 48149 Münster, Germany; Department of Mathematics and Computer Science, University of Münster, Germany
| | - Dominik Grotegerd
- Department of Psychiatry, University of Münster, Albert-Schweitzer-Campus 1, Building A9, 48149 Münster, Germany
| | - Katharina Dohm
- Department of Psychiatry, University of Münster, Albert-Schweitzer-Campus 1, Building A9, 48149 Münster, Germany
| | - Elisabeth J Leehr
- Department of Psychiatry, University of Münster, Albert-Schweitzer-Campus 1, Building A9, 48149 Münster, Germany
| | - Joscha Böhnlein
- Department of Psychiatry, University of Münster, Albert-Schweitzer-Campus 1, Building A9, 48149 Münster, Germany
| | - Katharina Förster
- Department of Psychiatry, University of Münster, Albert-Schweitzer-Campus 1, Building A9, 48149 Münster, Germany
| | - Susanne Meinert
- Department of Psychiatry, University of Münster, Albert-Schweitzer-Campus 1, Building A9, 48149 Münster, Germany
| | - Verena Enneking
- Department of Psychiatry, University of Münster, Albert-Schweitzer-Campus 1, Building A9, 48149 Münster, Germany
| | - Daniel Emden
- Department of Psychiatry, University of Münster, Albert-Schweitzer-Campus 1, Building A9, 48149 Münster, Germany
| | - Ramona Leenings
- Department of Psychiatry, University of Münster, Albert-Schweitzer-Campus 1, Building A9, 48149 Münster, Germany
| | - Nils R Winter
- Department of Psychiatry, University of Münster, Albert-Schweitzer-Campus 1, Building A9, 48149 Münster, Germany
| | - Tim Hahn
- Department of Psychiatry, University of Münster, Albert-Schweitzer-Campus 1, Building A9, 48149 Münster, Germany
| | - Sami Mikhail
- Department of Psychiatry, University of Münster, Albert-Schweitzer-Campus 1, Building A9, 48149 Münster, Germany
| | - Andreas Jansen
- Department of Psychiatry, University of Marburg, Germany
| | - Axel Krug
- Department of Psychiatry, University of Marburg, Germany
| | - Igor Nenadić
- Department of Psychiatry, University of Marburg, Germany
| | - Marcella Rietschel
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Stephanie H Witt
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Stefanie Heilmann-Heimbach
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
| | - Per Hoffmann
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany; Department of Biomedicine, University of Basel, Basel, Switzerland
| | - Andreas J Forstner
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany; Department of Biomedicine, University of Basel, Basel, Switzerland; Centre for Human Genetics, University of Marburg, Marburg, Germany; Department of Psychiatry (UPK), University of Basel, Basel, Switzerland
| | - Markus M Nöthen
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
| | - Bernhard T Baune
- Department of Psychiatry, University of Münster, Albert-Schweitzer-Campus 1, Building A9, 48149 Münster, Germany; Department of Psychiatry, Melbourne Medical School, The University of Melbourne, Melbourne, VIC, Australia; The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, VIC, Australia
| | - Tilo Kircher
- Department of Psychiatry, University of Marburg, Germany
| | - Udo Dannlowski
- Department of Psychiatry, University of Münster, Albert-Schweitzer-Campus 1, Building A9, 48149 Münster, Germany.
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19
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Repple J, Meinert S, Bollettini I, Grotegerd D, Redlich R, Zaremba D, Bürger C, Förster K, Dohm K, Stahl F, Opel N, Hahn T, Enneking V, Leehr EJ, Böhnlein J, Leenings R, Kaehler C, Emden D, Winter NR, Heindel W, Kugel H, Bauer J, Arolt V, Benedetti F, Dannlowski U. Influence of electroconvulsive therapy on white matter structure in a diffusion tensor imaging study. Psychol Med 2020; 50:849-856. [PMID: 31010441 DOI: 10.1017/s0033291719000758] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
BACKGROUND Electroconvulsive therapy (ECT) is a fast-acting intervention for major depressive disorder. Previous studies indicated neurotrophic effects following ECT that might contribute to changes in white matter brain structure. We investigated the influence of ECT in a non-randomized prospective study focusing on white matter changes over time. METHODS Twenty-nine severely depressed patients receiving ECT in addition to inpatient treatment, 69 severely depressed patients with inpatient treatment (NON-ECT) and 52 healthy controls (HC) took part in a non-randomized prospective study. Participants were scanned twice, approximately 6 weeks apart, using diffusion tensor imaging, applying tract-based spatial statistics. Additional correlational analyses were conducted in the ECT subsample to investigate the effects of seizure duration and therapeutic response. RESULTS Mean diffusivity (MD) increased after ECT in the right hemisphere, which was an ECT-group-specific effect. Seizure duration was associated with decreased fractional anisotropy (FA) following ECT. Longitudinal changes in ECT were not associated with therapy response. However, within the ECT group only, baseline FA was positively and MD negatively associated with post-ECT symptomatology. CONCLUSION Our data suggest that ECT changes white matter integrity, possibly reflecting increased permeability of the blood-brain barrier, resulting in disturbed communication of fibers. Further, baseline diffusion metrics were associated with therapy response. Coherent fiber structure could be a prerequisite for a generalized seizure and inhibitory brain signaling necessary to successfully inhibit increased seizure activity.
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Affiliation(s)
| | | | - Irene Bollettini
- Division of Neuroscience, Scientific Institute Ospedale San Raffaele, Milano, Italy
| | | | - Ronny Redlich
- Department of Psychiatry, University of Muenster, Germany
| | - Dario Zaremba
- Department of Psychiatry, University of Muenster, Germany
| | | | | | - Katharina Dohm
- Department of Psychiatry, University of Muenster, Germany
| | - Felix Stahl
- Department of Psychiatry, University of Muenster, Germany
| | - Nils Opel
- Department of Psychiatry, University of Muenster, Germany
| | - Tim Hahn
- Department of Psychiatry, University of Muenster, Germany
| | | | | | | | | | - Claas Kaehler
- Department of Psychiatry, University of Muenster, Germany
- Institute of Pattern Recognition and Image Analysis, University of Muenster, Germany
| | - Daniel Emden
- Department of Psychiatry, University of Muenster, Germany
| | - Nils R Winter
- Department of Psychiatry, University of Muenster, Germany
| | - Walter Heindel
- Department of Clinical Radiology, University of Muenster, Germany
| | - Harald Kugel
- Department of Clinical Radiology, University of Muenster, Germany
| | - Jochen Bauer
- Department of Clinical Radiology, University of Muenster, Germany
| | - Volker Arolt
- Department of Psychiatry, University of Muenster, Germany
| | - Francesco Benedetti
- Division of Neuroscience, Scientific Institute Ospedale San Raffaele, Milano, Italy
- University Vita-Salute San Raffaele, Italy
| | - Udo Dannlowski
- Department of Psychiatry, University of Muenster, Germany
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20
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Opel N, Redlich R, Repple J, Kaehler C, Grotegerd D, Dohm K, Zaremba D, Goltermann J, Steinmann LAM, Krughöfer R, Leehr EJ, Böhnlein J, Förster K, Bürger C, Meinert S, Enneking V, Emden D, Leenings R, Winter N, Heindel W, Kugel H, Thalamuthu A, Hahn T, Arolt V, Baune BT, Dannlowski U. Childhood maltreatment moderates the influence of genetic load for obesity on reward related brain structure and function in major depression. Psychoneuroendocrinology 2019; 100:18-26. [PMID: 30268003 DOI: 10.1016/j.psyneuen.2018.09.027] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/20/2018] [Revised: 08/16/2018] [Accepted: 09/16/2018] [Indexed: 10/28/2022]
Abstract
Obesity is a clinically relevant and highly prevalent somatic comorbidity of major depression (MDD). Genetic predisposition and history of childhood trauma have both independently been demonstrated to act as risk factors for obesity and to be associated with alterations in reward related brain structure and function. We therefore aimed to investigate the influence of childhood maltreatment and genetic risk for obesity on structural and functional imaging correlates associated with reward processing in MDD. 161 MDD patients underwent structural and functional MRI during a frequently used card guessing paradigm. Main and interaction effects of a polygenic risk score for obesity (PRS) and childhood maltreatment experiences as assessed using the Childhood Trauma Questionnaire (CTQ) were investigated. We found that maltreatment experiences and polygenic risk for obesity significantly interacted on a) body mass index b) gray matter volume of the orbitofrontal cortex as well as on c) BOLD response in the right insula during reward processing. While polygenic risk for obesity was associated with elevated BMI as well as with decreased OFC gray matter and increased insular BOLD response in non-maltreated patients, these associations were absent in patients with a history of childhood trauma. No significant main effect of PRS or maltreatment on gray matter or BOLD response could be detected at the applied thresholds. The present study suggests that childhood maltreatment moderates the influence of genetic load for obesity on BMI as well as on altered brain structure and function in reward related brain circuits in MDD.
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Affiliation(s)
- Nils Opel
- Department of Psychiatry, University of Münster, Germany.
| | - Ronny Redlich
- Department of Psychiatry, University of Münster, Germany
| | | | - Claas Kaehler
- Department of Psychiatry, University of Münster, Germany; Department of Mathematics and Computer Science, University of Münster, Germany
| | | | - Katharina Dohm
- Department of Psychiatry, University of Münster, Germany
| | - Dario Zaremba
- Department of Psychiatry, University of Münster, Germany
| | | | | | | | | | | | | | | | | | | | - Daniel Emden
- Department of Psychiatry, University of Münster, Germany
| | | | - Nils Winter
- Department of Psychiatry, University of Münster, Germany
| | - Walter Heindel
- Institute of Clinical Radiology, University of Münster, Germany
| | - Harald Kugel
- Institute of Clinical Radiology, University of Münster, Germany
| | - Anbupalam Thalamuthu
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales, Australia
| | - Tim Hahn
- Department of Psychiatry, University of Münster, Germany
| | - Volker Arolt
- Department of Psychiatry, University of Münster, Germany
| | - Bernhard T Baune
- Department of Psychiatry, Melbourne Medical School, The University of Melbourne, Melbourne, Australia
| | - Udo Dannlowski
- Department of Psychiatry, University of Münster, Germany
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21
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Leenings R, Glatz C, Heidbreder A, Boentert M, Pipa G, Young P. P 120 A machine learning approach to detecting sleep and sleep disorders in acceleration sensor data. Clin Neurophysiol 2017. [DOI: 10.1016/j.clinph.2017.06.193] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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